Global tuberculosis report 2013

Global tuberculosis report 2013

WHO Library Cataloguing-in-Publication Data Global tuberculosis report 2013. 1.Tuberculosis – epidemiology. 2.Tuberculosis, Pulmonary – prevention and control. 3.Tuberculosis – economics. 4.Tuberculosis, Multidrug-Resistant. 5.Annual reports. I.World Health Organization. ISBN 978 92 4 156465 6 (NLM classification: WF 300)

© World Health Organization 2013 All rights reserved. Publications of the World Health Organization are available on the WHO web site (www.who.int) or can be purchased from WHO Press, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland (tel.: +41 22 791 3264; fax: +41 22 791 4857; e-mail: bookorders@who.int). Requests for permission to reproduce or translate WHO publications – whether for sale or for non-commercial distribution – should be addressed to WHO Press through the WHO web site (www.who.int/about/licensing/copyright_form/en/index.html). The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement. The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters. All reasonable precautions have been taken by the World Health Organization to verify the information contained in this publication. However, the published material is being distributed without warranty of any kind, either expressed or implied. The responsibility for the interpretation and use of the material lies with the reader. In no event shall the World Health Organization be liable for damages arising from its use. Cover design by Tom Hiatt, Western Pacific Regional Office and Irwin Law, WHO headquarters. The front cover illustrates the latest status of global progress for five indicators that are part of the Millennium Development Goals framework. These are the incidence rate of tuberculosis disease per 100 000 population per year, the prevalence of tuberculosis disease per 100 000 population, the tuberculosis mortality rate per 100 000 population per year, the case detection rate (the number of cases detected and reported to national tuberculosis programmes divided by the estimated incidence) and the treatment success rate for new TB patients started on treatment. Each pair of shapes represents both the most recent level of the indicator and a baseline year against which progress is measured. For incidence (green and dark orange), prevalence (grey and pink) and mortality (light orange and light blue), the top of the combined height of each pair of shapes shows the level in 1990. The lower of the two shapes in each pair shows the level in 2012. For the case detection rate, the combined height of each pair of shapes (dark blue and brown) shows the level in 2012 and the lower of the two shapes (dark blue) illustrates the level in 1995. For the treatment success rate (red and yellow), the combined height of each pair shows the level in 2011 and the lower of the two shapes (red) shows the level in 1995. More information about these indicators and progress towards global targets are provided in Chapter 2 and Chapter 3 of the Global Tuberculosis Report 2013. Designed by minimum graphics Printed in France WHO/HTM/TB/2013.11

Contents

Abbreviations iv Acknowledgements v Executive summary Chapter 1. Introduction Chapter 2. The burden of disease caused by TB Chapter 3. TB case notifications and treatment outcomes Chapter 4. Drug-resistant TB Chapter 5. Diagnostics and laboratory strengthening Chapter 6. Addressing the co-epidemics of TB and HIV Chapter 7. Financing Chapter 8. Research and development Annexes 1. Methods used to estimate the global burden of disease caused by TB 2. Country profiles 3. Regional profiles 4. Key indicators for the world, WHO regions and individual countries 99 113 137 145 ix 1 6 28 45 59 68 75 86

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Abbreviations

Advocacy, Communication and Social Mobilization ACTG AIDS Clinical Trials Group ADR adverse drug reactions acid-fast bacilli AFB AIDS acquired immunodeficiency syndrome ARI annual risk of infection ART antiretroviral therapy BCG Bacille-Calmette-Guérin BRICS Brazil, Russian Federation, India, China, South Africa CDR case detection rate CEM cohort event monitoring CFR case fatality rate CFU colony-forming units CPT co-trimoxazole preventive therapy CBC community-based care DOTS the basic package that underpins the Stop TB Strategy DR-TB drug-resistant tuberculosis DRS drug resistance surveillance DST drug susceptibility testing DS-TB drug-susceptible tuberculosis DTLC District TB and Leprosy Coordinator EBA early bactericidal activity ECDC European Centre for Disease Prevention and Control ERR electronic recording and reporting EU European Union FDA Food and Drug Administration FIND Foundation for Innovative New Diagnostics GDP gross domestic product GLC Green Light Committee GLI Global Laboratory Initiative GNI gross national income HBC high-burden country HIV human immunodeficiency virus HR Hazard ratio ICD-10 International Classification of Diseases (10th revision) Infectious Disease Research Institute IDRI IGRA interferon-gamma release assay IPAQT Initiative for Promoting Affordable, Quality TB Tests IPT isoniazid preventive therapy IRR incidence rate ratio LED light-emitting diode LPA line-probe assay

ACSM

latent TB infection Millennium Development Goal multidrug-resistant tuberculosis maternal, newborn and child health nucleic acid amplification test national AIDS programme new funding model national tuberculosis [control] programme Organisation for Economic Co-operation and Development OR Operational research PAL Practical Approach to Lung health PCR polymerase chain reaction PDA personal digital assistant PEPFAR US President’s Emergency Plan for AIDS Relief POC point of care PPM public–private mix QMS quality management system rGLC Regional Green Light Committee RNTCP Revised National TB Control Programme [India] rRNA ribosomal ribonucleic acid RR relative risk RR-TB rifampicin-resistant tuberculosis SD standard deviation SITT Integrated Tuberculosis Information System SRL supranational reference laboratory STAG-TB Strategy and Technical Advisory Group for TB TAG Treatment Action Group TB tuberculosis TB-MAC TB Modelling and Analysis Consortium TB-TEAM Tuberculosis Technical Assistance Mechanism TBVI Tuberculosis Vaccine Initiative TFM transitional funding mechanism TST tuberculin skin test UHC universal health coverage UN United Nations UNAIDS Joint United Nations Programme on HIV/AIDS UNITAID international facility for the purchase of diagnostics and drugs for diagnosis and treatment of HIV/AIDS, malaria and TB United States Agency for International USAID Development UNPD United Nations Population Division vital registration VR WHO World Health Organization XDR-TB extensively drug-resistant tuberculosis ZN Ziehl Neelsen

LTBI MDG MDR-TB MNCH NAAT NAP NFM NTP OECD

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Acknowledgements

This global tuberculosis (TB) report was produced by a core team of 15 people: Annabel Baddeley, Anna Dean, Hannah Monica Dias, Dennis Falzon, Katherine Floyd, Inés Garcia, Philippe Glaziou, Tom Hiatt, Irwin Law, Christian Lienhardt, Linh Nguyen, Charalambos Sismanidis, Hazim Timimi, Wayne van Gemert and Matteo Zignol. The team was led by Katherine Floyd. Overall guidance was provided by the Director of the Global TB Programme, Mario Raviglione. The data collection forms (long and short versions) were developed by Philippe Glaziou and Hazim Timimi, with input from staff throughout the WHO Global TB Programme. Hazim Timimi led and organized all aspects of data management. Inés Garcia and Andrea Pantoja conducted all review and follow-up of financial data. The review and follow-up of all other data was done by a team of reviewers. This included Annabel Baddeley, Annemieke Brands, Andrea Braza, Katsura Danno, Anna Dean, Hannah Monica Dias, Dennis Falzon, Wayne van Gemert, Soleil Labelle, Knut Lönnroth, Linh Nguyen, Salah Ottmani, Hazim Timimi, Fraser Wares and Matteo Zignol at WHO headquarters; Amal Bassili from the Eastern Mediterranean Regional Office; and Suman Jain, Sai Pothapregada, Nino Mdivani, Eliud Wandwalo and Mohammed Yassin from the Global Fund. Data for the European Region were collected and validated jointly by the WHO Regional Office for Europe and the European Centre for Disease Prevention and Control (ECDC); we thank in particular Encarna Gimenez, Vahur Hollo and Csaba Ködmön from ECDC for providing validated data files and Andrei Dadu from the WHO Regional Office for Europe for his substantial contribution to follow-up and validation of data for all European countries. Review of TB/HIV data was undertaken in collaboration with Michel Beusenberg, Chika Hayashi, Lisa Nelson and Michelle Williams from the WHO HIV department. Victoria Bendaud, Josephine Dy, and Taavi Erkkola from UNAIDS managed the process of data collection from national AIDS programmes, provided a TB/HIV dataset and worked closely with WHO staff to review and validate TB/HIV data. Philippe Glaziou and Charalambos Sismanidis prepared estimates of TB disease burden and associated figures and tables (Chapter 2), with support from Tom Hiatt. Particular thanks are due to Carel Pretorius (Futures Institute), who worked closely with Philippe Glaziou on analyses and related estimates of TB mortality among HIV-positive people, as well as to Dennis Falzon for coordinating a systematic review that was used to produce estimates of mortality

related to multidrug-resistant TB (MDR-TB) and to Harish Nair and Luciana Brondi from the University of Edinburgh for conducting this review. Tom Hiatt prepared all figures and tables on TB notification and treatment outcome data (Chapter 3). Anna Dean, Dennis Falzon and Matteo Zignol analysed data and prepared the figures and tables related to drug-resistant TB (Chapter 4), with input from Charalambos Sismanidis. Tom Hiatt and Wayne van Gemert prepared figures and tables on laboratory strengthening and the rollout of new diagnostics (Chapter 5). Annabel Baddeley, Katsura Danno, Tom Hiatt and Linh Nguyen analysed TB/HIV programmatic data and prepared the associated figures and tables (Chapter 6). Inés Garcia and Andrew Siroka analysed financial data, and prepared the associated figures and tables (Chapter 7). Christian Lienhardt, Christopher Gilpin and Karin Weyer prepared the figures on the pipelines for new TB drugs, diagnostics and vaccines (Chapter 8), with input from the respective Working Groups of the Stop TB Partnership. Tom Hiatt coordinated the finalization of all figures and tables and was the focal point for communications with the graphic designer. The writing of the main part of the report was led by Katherine Floyd, with contributions from Dennis Falzon, Philippe Glaziou, Irwin Law, Ikushi Onozaki, and Charalambos Sismanidis (Chapter 2); Hannah Monica Dias, Wayne van Gemert, Haileyesus Getahun, Thomas Joseph, Mukund Uplekar and Lana Tomaskovic (Chapter 3); and Inés Garcia and Christian Gunneberg (Chapter 7). Chapter 4, on drug-resistant TB, was prepared by Anna Dean, Dennis Falzon and Matteo Zignol, with input from Katherine Floyd, Philippe Glaziou and Charalambos Sismanidis. Chapter 5, on diagnostics and laboratory strengthening, was prepared by Wayne van Gemert, with input from Christopher Gilpin, Fuad Mirzayev and Karin Weyer. Chapter 6 was prepared by Annabel Baddeley, Haileyesus Getahun, Linh Nguyen and Katherine Floyd. Chapter 8, on research and development, was led by Christian Lienhardt, with inputs from Christopher Gilpin, Karin Weyer and Katherine Floyd. Chapter 8 was carefully reviewed by the chairs and secretariats of the Working Groups of the Stop TB Partnership. Particular thanks are due to Michael Brennan, Uli Fruth and Jennifer Woolley (new vaccines); Daniela Cirillo (new diagnostics); and Barbara Laughon and Mel Spigelman (new TB drugs). The report team is also grateful to Emily Bloss (US Centers for Disease Control and Prevention) and Hillary Kipruto (WHO Country Office, Kenya) for their contributions to content related to strengthening of TB surveillance in Chapter 2, including a case study of the introduction of

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electronic recording and reporting in Kenya; to Rajendra Yadav and Masami Fujita (WHO Country Office, Cambodia) for their contribution to an analysis of the integration of TB, HIV and mother and child health services in Cambodia (Chapter 6); and to various internal and external reviewers for useful comments and suggestions on advanced drafts of chapter text. The special supplement on the “Countdown to 2015” that accompanies the global report was prepared by Anna Dean, Hannah Monica Dias, Katherine Floyd, Irwin Law, Mario Raviglione, Diana Weil and Karin Weyer, with valuable inputs from many people at global, regional and country levels. We thank in particular Sai Pothapregada and Eliud Wandwalo from the Global Fund, who facilitated discussions with and inputs from many Fund Portfolio Managers. Annex 1, which explains methods used to produce estimates of the burden of disease caused by TB, was written by Philippe Glaziou and Charalambos Sismanidis with very helpful input from Carel Pretorius. We thank Colin Mathers of the WHO Mortality and Burden of Disease team for his careful review. The country profiles that appear in Annex 2 and the regional profiles that appear in Annex 3 were prepared by Hazim Timimi. Annex 4, which contains a wealth of global, regional and country-specific data from the global TB database, was prepared by Tom Hiatt and Hazim Timimi. We thank Pamela Baillie in the Global TB Programme’s monitoring and evaluation team for impeccable administrative support, Doris Ma Fat from the WHO Mortality and Burden of Disease team for providing TB mortality data extracted from the WHO Mortality Database, and Peter Ghys, Mary Mahy and Karen Stanecki (UNAIDS) for providing epidemiological data that were used to estimate HIV-associated TB mortality. The entire report was edited by Tim France (Inis Communication). We thank him for his excellent work. We also thank, as usual, Sue Hobbs for her excellent work on the design and layout of this report. Her contribution, as in previous years, was greatly appreciated. The principal source of financial support for WHO work on global TB monitoring and evaluation is the United States Agency for International Development (USAID), without which it would be impossible to produce the Global Tuberculosis Report. Production of the report was also supported by the governments of Japan and the Republic of Korea. We acknowledge with gratitude their support. In addition to the core report team and those mentioned above, the report benefited from the input of many staff working in WHO regional and country offices and hundreds of people working for national TB programmes or within national surveillance systems who contributed to the reporting of data and to the review of report material prior to publication. These people are listed below, organized by WHO region. We thank them all for their invaluable contribution and collaboration, without which this report could not have been produced. Among the WHO staff not already mentioned above, we

thank in particular Khurshid Alam Hyder, Daniel Kibuga, Rafael López Olarte, André Ndongosieme, Wilfred Nkhoma and Henriette Wembanyama for their major contribution to facilitation of data collection, validation and review.

WHO staff in regional and country offices WHO African Region Harura Adamu, Boubacar Ould Abdel Aziz, Esther Aceng, Inacio Alvarenga, Balde Amadou, Ayodele Awe, Sanni Babatunde, Bazie Babou, Nayé Bah, Marie Barouan, Abera Bekele, Norbert Bidounga, Gaël Claquin, Augusto da Cruz Claudina, Peter Clement, Noel Djemadji, Ismael Hassen Endris, Amos Omoniyi Fadare, Louisa Ganda, Boingotlo Gasennelwe, Patrick Hazangwe, Joseph Imoko, Michael Jose, Joel Kangangi, Katherine Lao, Nzuzi Katondi, Bah Keita, Daniel Kibuga, Hillary Kipruto, Désiré Aristide Komangoya Nzonzo, Sharmila Lareef-Jah, Frank Lule, Mwendaweli Maboshe, Mbemba Leonard, Richard Mbumba, Julie Mugabekazi, André Ndongosieme, Denise Nkezimana, Wilfred Nkhoma, Nicolas Nkiere, Ghislaine Nkone Asseko, Ishmael Nyasulu, Laurence Nyiramasarabwe, Samuel Ogiri, Daniel Olusoti, Amos Omoniyi, Chijioke Osakwe, Felicia Owusu-Antwi, Philips Patrobas, Kalpeshsinh Rahevar, Bacary Sambou, Kefas Samson, Neema Simkoko, Desta Tiruneh, Alexis Tougordi, Henriette Wembanyama.

WHO Region of the Americas Monica Alonso Gonzalez, Angel Manuel Alvarez, Luis Gerardo Castellanos, Gerardo de Cossio, Rachel Eersel, Marcos Espinal, Ingrid García, Mirtha Del Granado, Rosalinda Hernández, Vidalia Lesmo, Rafael López Olarte, Wilmer Marquiño, Thais dos Santos, Alfonso Tenorio, Jorge Victoria, Anna Volz.

WHO Eastern Mediterranean Region Mohamed Abdel Aziz, Ali Akbar, Samiha Baghdadi, Amal Bassili, Najwa El Emam, Hamida Khattabi, Aayid Munim, Ghulam Nabi Kazi, Ali Reza Aloudel, Gabriele Riedner, Karam Shah, Sindani Ireneaus Sebit, Bashir Suleiman, Rahim Taghizadeh.

WHO European Region Martin van den Boom, Brenda van den Bergh, Andreea Cassandra Butu, Silvu Ciobanu, Pierpaolo de Colombani, Andrei Dadu, Irina Danilova, Masoud Dara, Jamshid Gadoev, Gayane Ghukasyan, Sayohat Hasanova, Arax Hovhannesyan, Saliya Karymbaeva, Mehmet Kontas, Kristin Kremer, Dmitriy Pashkevich, Valiantsin Rusovich, Bogdana Shcherbak-Verlan, Javahir Suleymanova, Szabolcs Szigeti, Melita Vujnovic.

WHO South-East Asia Region Mohammad Akhtar, Vikarunnesa Begum, Erwin Cooreman, Deki, Khurshid Alam Hyder, Navaratnasingam Janakan, Kim Tong Hyok, La Win Maung, Jorge Luna, Partha Mandal, Amaya Maw-Naing, Giampaolo Mezzabotta,

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Bo Myint, Ye Myint, Eva Nathanson, Rajesh Pandav, Razia Pendse, Sri Prihatini, K Rezwan, Rim Kwang Il, Hwang Kum Ryong, Mukta Sharma, Aminath Shenalin, Achuthan Nair Sreenivas, Chawalit Tantinimitkul, Wangchuk Lungten.

WHO Region of the Americas Christian Acosta, Shalauddin Ahmed, Valentina Antonieta Alarcon Guizado, Xochil Alemán de Cruz, Kiran kumar Alla, Valeria Almanza Torrez, Mirian Alvarez, Raúl Álvarez, Aisha Andrewin, A. Alister Antoine, Chris Archibald, Carlos Alberto Marcos Ayala Luna, Wiedjaiprekash Balesar, Draurio Barreira, Patricia Bartholomay, Soledad Beltrame, María del Carmen Bermúdez, Lynrod Brooks, Marta Calona de Abrego, Martín Castellanos Joya, Jorge Castillo Carbajal, Kenneth Castro, Judith Cazares, Gemma Chery, Carlos Cuadra, Ofelia Cuevas, D’Auvergne Cleophas, Jose Davy, Cecilia de Arango, Eva de Weever-Lista, Camille Deleveaux, Dy-Juan De Roza, Roger Duncan, España Cedeño Mercedes, Manuel Salvador España Rueda, Fernandez Hugo, Cecilia Figueroa Benites, Victor Gallant, Julio Garay Ramos, Sarita Aguirre García, Izzy Gerstenbluth, Margarita Godoy, Roscio Gómez, Ilse Maria Góngora Rivas, Silvino González, Yaskara Halabi, Kevin Harvey, Dorothea Hazel, Maria Henry, Tania Herrera, Carla Jeffries, Dihadenys Lemus Molina, Athelene Linton, Maria Josefa Llanes Cordero, Marvin Andres Maldonado Rivera, Maldonado Saavedra Andrea, Marcelino Belkys, Eva Martìnez, María de Lourdes Martínez Olivares, Zeidy Mata Azofeifa, Joan McLeod-Simon, Timothy McLaughlin-Munroe, Roque Miramontes, Leilawatie Mohammed, Jeetendra Mohanlall, Ernesto Moreno, Francis Morey, Willy Morose, Michael Owen, Cheryl Peek-Ball, Janelle Pickering, Tomasa Portillo, Irad Potter, Manohar Singh Rajamanickam, Dottin Ramoutar, Anna Esther Reyes Godoy, Paul Ricketts, Jorge Rodriguez De Marco, Myrian Román, Nilda de Romero, Carolyn Russell, Wilmer Salazar, Deborah Stijnberg, Sutton Jackurlyn, Torres Clarita, Maribelle Tromp, William Turner, Melissa Valdez, Daniel Vázquez, Nestor Vera, Michael Williams, David Yost, Oritta Zachariah.

WHO Western Pacific Region Shalala Ahmadova, Niño Dayanghirang, Asaua Faasino, Salu Failauga, Ogtay Gozalov, Cornelia Hennig, Tom Hiatt, Tauhid Islam, Narantuya Jadambaa, Ridha Jebeniani, Sung Hye Kim, Miwako Kobayashi, Woo-Jin Lew, Katsunori Osuga, Khanh Pham, Fabio Scano, Jacques Sebert, Catharina van Weezenbeek, Rajendra Yadav, Dongbao Yu.

National respondents who contributed to reporting and verification of data WHO African Region Abdou-Salam Abderemane, Ouédraogo Adama, Abdelrahim Barka Abderramane, Jean Louis Abena Foe, Sofiane Alihalassa, Arlindo Amaral, Kouamé Amenan, Séverin Anagonou, Younoussa Assoumani, Georges Bakaswa, Adama Marie Bangoura, Jorge Noel Barreto, Ballé Boubakar, Victor Bonkoungou, Frank Adae Bonsu, Miguel Camara, Evangelista Chisakaitwa, Ernest Cholopray, Nkemdilim Chukwueme, Catherine Cooper, Swasilanne da Silva, B. de Sousa Bandeira, Isaias Dambe, Davi Kokou Mawulé, Serge Diagbouga, Aicha Diakité, Awa Helene Diop, Sicelo Dlamini, Themba Dlamini, Thaddée Ndikumana, Oumou Fofana, Susan Gacheri, Evariste Gasana, Michel Gasana, Sandile Ginindza, Martin Gninafon, Nii Nortey Hanson-Nortey, Adama Jallow, Saffa Kamara, Madou Kane, Henry Kanyerere, Nathan Kapata, Biruck Kebede, Kerram Aziza, Deogratias Kibambazi, Patrick Konwuloh, Jacquemin Kouakou, Popaul Kulonga, Rossin Lebeke, Lillian Ishengoma, Llang Bridget Maama-Maime, Marcel Lougue, Maxime Lunga, Ghislaine Mabeluanga Tshitenge, Jocelyn Mahoumbou, Angelo Makpenon, David Mametja, Ivan Manhiça, Tseliso Marata, Farai Mavhunga, Mba Bekolo Frenk José Mathieu, Salem Salem Mohameden, Louine Morel, Youwaoga Isidore Moyenga, James Mpunga, Frank Mugabe, Kenneth Mugisha, Clifford Munyandi, Lindiwe Mvusi, Aboubacar Mzembaba, Ronald Ncube, Fulgence Ndayikengurukiye, Yvon Martial Ngana, Antoine Ngoulou, Lourenço Nhocuana, Blasdus Franz Njako, Emmanuel Nkiligi, M Nkou, Joshua Obasanya, Davidson Ogunade, Hermann Ongouo, Abdelhadi Oumar, Issoufou Ousmane, Maria Conceição Palma, Victor Pereira, Thato Raleting, Sahondra Jeanine Randriambeloson, Rujeedawa Mohammed Fezul, Samey Agbenyegan, Charles Sandy, Kebba D Sanneh, Marie Sarr Diouf, Mineab Sebhatu, Mamie Shoma, Angele Shoma Matota, René Simalo, Joseph Sitienei, Nicholas Siziba, Philippe Takongo, Celstino Francisco Teixeira, Mohamed Abdallahi Traoré, Nassiama Traoré, Kassim Traoré, Alie Wurie, Eucher Dieudonné Yazipo, Ranivomahefa Myrienne Bakoliarisoa Zanajohary, Abbas Zezai, Eric Ismaël Zoungrana.

WHO Eastern Mediterranean Region Fadhil Abbas, Mohammad S Abouzeid, Khaled Abu Ruhman, Nadia Abu Sabra, Ahmadi Shahnaz, Mohamed Redha Al Lawati, Al Saidi Fatmah, Samia Ali Alagab, Abdelbary Abdullah Ahmed Al-Hammadi, Abdullatif Al-Khal, Saeed Al Saffar, Kifah Alshaqeldi, Bahnasy Samir, Bennani Kenza, Kinaz Cheikh, Walid Daoud, Mohamed Furjani, Amal Galal, Dhikrayet Gamara, Assia Haissama Mohamed, Hiba Kamal Hamad Elneel, Kaalthoom Hassan, Hawa Hassan Guessod, Lou Joseph, Onwar Otien Jwodh Chol, Basharat Khan, Joseph Lasu, Sayed Daoud Mahmoodi, Khadiga Adam Mohammed, Mokhtar Alaa, Mulham Mustafa, Nasehi Mahshid, Ejaz Qadeer, Mohammad Khalid Seddiq, Sghiar Mohammed, Mohemmed Tabena, Tamara Tayeb, Najib Abdul aziz Abdullah Thabit, Seddik Walha, Yaacoub Hiam.

WHO European Region Abildaev Tleukhan Shildebaevich, Mokhonim Abdulloeva, Ibrahim Abubakar, Rafig Abuzarov, Nurhan Albayrak, Natavan Alikhanova, Avtandil Alisherov, Ewa Augustynowicz-

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Kopeć, Ekkehardt Altpeter, Laura Anderson, Delphine Antoine, Trude Margrete Arnesen, Rusudan Aspindzelashvili, Andrei Astrovko, Elizabeta Bachiyska, Anna Ivanovna Barbova, Yana Besstraschnova, Venera Lazarevna Bismilda, Oktam Ikramovich Bobokhojaev, Olivera Bojovic, Eric C. Böttger, Bonita Brodhun, Noa Cedar, Daniel Chemtob, Domnica Ioana Chiotan, Ana Ciobanu, Nico Cioran, Andra Cirule, Thierry Comolet, Radmila Curcic, Manfred Danilovitš, Edita Davidaviciene, Hayk Davtyan, Pava Dimitrijevic, António Diniz, Francis Drobniewski, Raquel Duarte, Mladen Duronjic, Connie Erkens, Jennifer Fernandez Garcia, Lyalya Gabbasova, Viktor Gasimov, Lárus Jón Guðmundsson, Gennady Gurevich, Walter Haas, Hasan Hafizi, Evgeny Hanyukov, Armen Hayrapetyan, Peter Helbling, Sven Hoffner, Daniela Homorodean, Jahongir Jurakhonovich Ismoilov, Mamuka Japaridze, Vincent Jarlier, Soledad Jiménez Pajares, Jerker Jonsson, Abdullat Kadyrov, Gulmira Kalmambetova, Dmitry Klymuk, Maria KorzeniewskaKosela, Ainura Koshoeva, Košnik Mitja, Gabor Kovacs, Tiina Kummik, Nino Lomtadze, Stevan Lučić, Jasminka Maglajllic, Turid Mannsåker, Mathys Vanessa, Rafail Mehdiyev, Rukije Mehmeti, Donika Mema, Vladimir Milanov, Alvard Mirzoyan, Gjyle Mulliqi, Gulnora Murmusaeva, Seher Musaonbasioglu, Ucha Nanava, Zdenka Novakova, Joan O’Donnell, Analita Pace Asciak, Clara Palma Jordana, Elena Pavlenko, Olga Pavlova, Monique Perrin, Edita Pimkina, Monika Polanova, Georgeta Gilda Popescu, Gordana Radosavljevic Asic, Bozidarka Rakocevic, Thomas Rendal, Vija Riekstina, Jerome Robert, Elena Rodríguez Valín, Tom Rogers, Elena Romancenco, Kazimierz Roszkowski-Sliz, Sabine Rüsch-Gerdes, Branislava Savic, Gérard Scheiden, Hasia Kaidar Shwartz, Anabela Silva, Girts Skenders, Cathrine Slorbak, Erika Slump, Hanna Soini, Ivan Solovic, Dick van Soolingen, Flemming Stenz, Sergey Sterlikov, Jana Svecova, Svetina Šorli Petra, Silva Tafaj, Talevski Stefan, Odorina Tello Anchuela, Mirzagaleb Tillyashaykhov, Aida

Ustamujic, Gulnoz Uzakova, Tonka Varleva, Piret Viiklepp, Cveta Vragoterova, Gerard de Vries, Jiri Wallenfels, Wanlin Maryse, Pierre Weicherding, Aysegul Yildirim, Zakoska Maja, Oksana Zalutskaya, Ilona Zemanová, Manca Žolnir Dovč, Hasan Zutic.

WHO South-East Asia Region Shina Ahmed, Aminath Aroosha, Choe Kum Song, Emdadul Hoque, RS Gupta, Sirinapha Jittimanee, Suksont Jittimanee, Niraj Kulshrestha, Constantino Lopes, Thandar Lwin, Dyah Erti Mustikawati, Tin Zar Naing, Chawetsan Namwat, Md Nuruzzaman Haque, Nirupa Pallewatta, Rajendra Prasad Pant, Kiran Rade, Dyah Armi Riana, Chewang Rinzin, Sudath Samaraweera, Gamini Senevirathne, Janaka Thilakarathne, Sabino Viegas, Bimal Kumar Yadav.

WHO Western Pacific Region Paul Aia, Cecilia Teresa T. Arciaga, Nemia Bainivalu, Christina Bareja, Risa J. Bukbuk, Cheng Shiming, Phonenaly Chittamany, Chou Kuok Hei, Nese Ituaso Conway, Du Xin, Mayleen J. Ekiek, Fanai Saen, Rangiau Fariu, Ludovic Floury, Louise Fonua, Jiloris Frederick Dony, Anna Marie Celina Garfin, Go Un-Yeong, Shakti Gounder, Anie Haryani Hj Abdul Rahman, Noel Itogo, Tom Jack, Seiya Kato, Khin Mar Kyi Win, Lamar Daniel, Leo Lim, Liza Lopez, Sakiusa Mainawalala, Henri-Pierre Mallet, Tan Eang Mao, Markleen Tagaro, Serafi Moa, Suzana Mohd Hashim, Nguyen Binh Hoa, Nguyen Viet Nhung, Nou Chanly, Ochirbat Batbayar, Connie Bieb Olikong, Park Yoon-Sung, Nukutau Pokura, Waimanu Pulu, Purev Nasanjargal, Rabauliman Marcelina, Bereka Reiher, Bernard Rouchon, Temilo Seono, Tokuaki Shobayashi, Vita A. Skilling, Grant Storey, Phannasinh Sylavanh, Kenneth Reuee Tabutoa, Tam Cheuk Ming, Kyaw Thu, Tieng Sivanna, Tong Ka Io, Rosalind Vianzon, Wang Yee Tang, Wang Lixia.

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Executive summary

Tuberculosis (TB) remains a major global health problem. In 2012, an estimated 8.6 million people developed TB and 1.3 million died from the disease (including 320 000 deaths among HIV-positive people).1 The number of TB deaths is unacceptably large given that most are preventable. Nearly 20 years after the WHO declaration of TB as a global public health emergency, major progress has been made towards 2015 global targets set within the context of the Millennium Development Goals (MDGs). Two years ahead of the deadline, the Global Tuberculosis Report 2013 and accompanying supplement Countdown to 2015 assess progress towards the 2015 targets and the top priority actions needed to achieve and/or move beyond them.

 Many countries have made considerable progress to address the TB/HIV co-epidemic. However, globallevel targets for HIV testing among TB patients and provision of antiretroviral therapy (ART) to those who are HIV-positive have not been reached.

Five priority actions required to accelerate progress towards 2015 targets: 1. Reach the missed cases. About 3 million people who developed TB in 2012 were missed by national notification systems. Key actions needed to detect people with the illness and ensure that that they get the right treatment and care include: expanded services (including rapid tests) throughout health systems bolstered by the support of nongovernmental organizations, community workers and volunteers to diagnosis and report cases; intensified collaboration with public hospitals and private health facilities who are treating patients but not reporting; instituting mandatory notification of cases in more countries; and better data compilation. 2. Address MDR-TB as a public health crisis. In high MDR-TB burden countries, increased capacity to diagnose MDR-TB must be matched with supplies of quality drugs and scaled-up country capacity to deliver effective treatment and care. This will require high-level political will and leadership and more collaboration among partners, including drug regulatory authorities, donor and technical agencies, civil society and the pharmaceutical industry. 3. Accelerate the response to TB/HIV. The top priority is to increase coverage of ART for HIV-positive TB patients towards the 100% target. Expanded coverage of TB preventive treatment among people living with HIV is the second priority. 4. Increase financing to close all resource gaps. An estimated US$ 7–8 billion per year is required for a full response to the TB epidemic in low- and middle-income countries in 2014 and 2015 (excluding research and development for new TB diagnostics, drugs and vaccines). Funding in 2013 is about US$ 6 billion. Increases in both domestic and donor financing are needed to close the gap of up to US$ 2 billion per year, including via the full replenishment of the Global Fund in 2013. Progress remains fragile and could be reversed without adequate funding. 5. Ensure rapid uptake of innovations. The fast uptake of new tools and strategies for better diagnosis, treatment and prevention of all forms of TB can be accelerated by country-specific operational research and translation of findings into policy and practice. GLOBAL TUBERCULOSIS REPORT 2013 ix

COUNTDOWN TO 2015: key findings On track:  The rate of new TB cases has been falling worldwide for about a decade, achieving the MDG global target. TB incidence rates are also falling in all six WHO regions. The rate of decline (2% per year) remains slow.  Globally by 2012, the TB mortality rate had been reduced by 45% since 1990. The target to reduce deaths by 50% by 2015 is within reach.  Two WHO regions have already achieved the 2015 targets for reduced incidence, prevalence and mortality: the Region of the Americas and the Western Pacific Region.  Of the 22 high TB burden countries (HBCs) that account for about 80% of the world’s TB cases,2 seven have met all 2015 targets for reductions in TB incidence, prevalence and mortality. Four more HBCs are on track to do so by 2015.

Off track:  By 2012, the level of active TB disease in the community (prevalence) had fallen by 37% globally since 1990. The target of a 50% reduction by 2015 is not expected to be achieved.  The African and European regions are currently not on track to achieve the mortality and prevalence targets.  Among the 22 HBCs, 11 are not on track to reduce incidence, prevalence and mortality in line with targets. Reasons include resource constraints, conflict and instability, and generalized HIV epidemics.  Progress towards targets for diagnosis and treatment of multidrug-resistant TB (MDR-TB) is far off-track. Worldwide and in most countries with a high burden of MDR-TB, less than 25% of the people estimated to have MDR-TB were detected in 2012.

ADDITIONAL FINDINGS The report is based primarily on data provided by WHO’s Member States. In 2013, data were reported by 178 Member States and a total of 197 countries and territories that collectively have more than 99% of the world’s TB cases.

Burden of disease The current global picture of TB shows continued progress, but not fast enough.  An estimated 1.1 million (13%) of the 8.6 million people who developed TB in 2012 were HIV-positive. About 75% of these cases were in the African Region.  Globally in 2012, an estimated 450  000 people developed MDR-TB and there were an estimated 170  000 deaths from MDR-TB .  Most TB cases and deaths occur among men, but TB remains among the top three killers of women worldwide. There were an estimated 410 000 TB deaths among women in 2012, including 160 000 among HIV-positive women. Half of the HIV-positive people who died from TB in 2012 were women. Of the estimated 8.6 million new TB cases worldwide in 2012, 2.9 million were women.  There were an estimated 530  000 TB cases among children (under 15 years of age) and 74 000 TB deaths (among HIV-negative children) in 2012 (6% and 8% of the global totals, respectively).  The majority of cases worldwide in 2012 were in the South-East Asia (29%), African (27%) and Western Pacific (19%) regions. India and China alone accounted for 26% and 12% of total cases, respectively.  The TB incidence rate at country level ranges substantially, with around 1000 or more cases per 100 000 people in South Africa and Swaziland, and fewer than 10 per 100 000 population in parts of the Americas, several countries in western Europe, Japan, Australia and New Zealand.

 About 75% of the estimated 2.9 million missed cases – people who were either not diagnosed or diagnosed but not reported to NTPs – were in 12 countries. In order of total numbers, these were India (31% of the global total), South Africa, Bangladesh, Pakistan, Indonesia, China, Democratic Republic of the Congo, Mozambique, Nigeria, Ethiopia, the Philippines and Myanmar.  Xpert® MTB/RIF, a rapid molecular diagnostic test, is being rapidly adopted by countries to detect TB and rifampicin-resistant TB. By end June 2013, 1402 testing machines and 3.2 million test cartridges had been procured by 88 of the 145 countries eligible for concessional prices.  Treatment success rates for TB remain lowest in the European Region, where in 2011 only 72% of new cases were successfully treated.

MDR-TB and XDR-TB detection and treatment outcomes Undetected cases and treatment coverage gaps constitute a public health crisis.  Globally in 2012, data from drug resistance surveys and continuous surveillance among notified TB cases suggest that 3.6% of newly diagnosed TB cases and 20% of those previously treated for TB had MDR-TB. The highest levels of MDR-TB are found in eastern Europe and central Asia, where in some countries more than 20% of new TB cases and more than 50% of those previously treated for TB have MDR-TB.  A total of 94 000 TB patients eligible for MDR-TB treatment were detected in 2012: 84  000 people with confirmed MDR-TB (i.e. resistance to both rifampicin, the most powerful TB drug, and isoniazid), plus 10  000 with rifampicin resistance detected using Xpert MTB/ RIF. This was a 42% increase in detected cases eligible for treatment compared with 2011. The largest increases between 2011 and 2012 were in India, South Africa and Ukraine.  Just over 77 000 people with MDR-TB were started on second-line treatment in 2012, equivalent to 82% of the 94  000 newly detected cases that were eligible for treatment globally. Treatment coverage gaps for detected cases were much larger in some countries, especially in the African Region (51% enrolled in treatment), and widened in China, Pakistan and South Africa.  At least one case of extensively drug-resistant TB (XDRTB) had been reported by 92 countries by the end of 2012. On average, an estimated 9.6% of MDR-TB cases have XDR-TB.  Globally, only 48% of MDR-TB patients in the 2010 cohort of detected cases were successfully treated, reflecting high mortality rates and loss to follow-up. A treatment success rate of 75% or more for patients with MDR-TB was achieved in 34 of 107 countries.

TB detection and treatment outcomes Millions of people access effective TB care each year but “missed cases” hold back gains.  Between 1995 and 2012, 56 million people were successfully treated for TB in countries that had adopted WHO’s global TB strategy, saving 22 million lives.  In 2012, 6.1 million cases of TB were notified to national TB programmes (NTPs). Of these, 5.7 million were people newly diagnosed in 2012 and 0.4 million were previously diagnosed TB patients whose treatment regimen was changed.  In 2011, the treatment success rate continued to be high at 87% among all new TB cases.  Notifications of TB cases have stabilized globally. In 2012, about 66% (5.7 million) of the estimated 8.6 million people who developed TB were notified as newly diagnosed cases.

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Addressing TB-HIV TB-HIV collaborative services are expanding, but global targets are not yet in sight.  The main interventions to reduce the burden of HIV in TB patients are HIV testing and provision of ART and cotrimoxazole preventive therapy (CPT) to those found to be HIV-positive. The main interventions to reduce TB among people living with HIV are regular screening for TB among people in HIV care and provision of isoniazid preventive therapy (IPT) to those without active TB who meet eligibility criteria (estimated at 50% of those newly enrolled in HIV care).  Progress in the implementation of TB/HIV interventions was further consolidated in 2012. Globally, 46% of TB patients knew their HIV status (up from 40% in 2011). In the African Region that has the highest TB/ HIV burden, 74% of TB patients knew their HIV status (up from 69% in 2011). Among the 41 countries with the highest TB/HIV burden, more than 85% of TB patients knew their HIV status in 15 countries, and in 7 of these countries over 90% of patients knew their HIV status.  The coverage of ART among TB patients who were known to be HIV-positive reached 57% in 2012, up from 49% in 2011. As in the past few years, about 80% of HIVpositive TB patients were treated with CPT.  In 2012, 4.1 million people enrolled in HIV care were reported to have been screened for TB, up from 3.5 million in 2011. Of the reported 1.6 million people newly enrolled in HIV care in 2012, 0.5 million (31%) were provided with IPT.

 Growth in domestic and international donor funding has been clearly documented since 2002. There is capacity to further increase domestic funding, especially in BRICS (Brazil, the Russian Federation, India, China and South Africa) that have almost 50% of global TB cases.  International donor funding reported by NTPs amounted to US$  0.8 billion in 2013, about three-quarters of which was from the Global Fund. To close resource gaps, at least US$ 1.6 billion is needed in both 2014 and 2015.  International donor funding is crucial in many countries, accounting for more than 50% of total funding in the group of 17 HBCs excluding BRICS, and in all lowincome countries. The proportion is even higher in some individual countries.

Research and development New TB diagnostics, medicines and vaccines are crucial to end the global TB epidemic.  More than 50 companies are involved in development of new diagnostic tests.  10 new or repurposed TB drugs are in late phases of clinical development. In late 2012, bedaquiline became the first novel TB drug approved in 40 years. In June 2013, WHO issued interim guidance for its use in treatment of MDR-TB.  There are 10 vaccines for TB prevention and two immunotherapeutic vaccines in the pipeline. In early 2013, results from a Phase IIb proof-of-concept study of one of the preventive vaccine candidates were published. While efficacy was not superior to the Bacille-Calmette-Guérin (BCG) vaccine alone, the study demonstrated that a trial of a novel TB vaccine is feasible in a high TB burden setting.  Short, effective and well-tolerated treatments for latent TB infection, a point-of-care diagnostic test, and an effective post-exposure vaccine are needed to help end the global TB epidemic.

TB financing International donor funding and more domestic investments are essential.  Of the US$  7‒8 billion per year required in low and middle-income countries in 2014 and 2015, about two thirds is needed for the detection and treatment of drugsusceptible TB, 20% for treatment of MDR-TB, 10% for rapid diagnostic tests and associated laboratory strengthening, and 5% for collaborative TB/HIV activities.

1

The estimated number of TB deaths among HIV-positive people in 2011 was 336 000. Estimates of TB deaths among HIV-positive people for the entire period 1990‒2012 were updated in 2013 using the Spectrum software, which has been used for more than a decade to produce estimates of the burden of disease caused by HIV. In 2013, a TB module in Spectrum was available for the first time for use in the country consultations on HIV burden estimates that are organized by UNAIDS every two years. Estimation of the number of TB cases living with HIV, and of the number of TB deaths among HIV-positive people, was integrated into this process. 2 The 22 HBCs are Afghanistan, Bangladesh, Brazil, Cambodia, China, the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Kenya, Mozambique, Myanmar, Nigeria, Pakistan, the Philippines, the Russian Federation, South Africa, Thailand, Uganda, the United Republic of Tanzania, Viet Nam and Zimbabwe.

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chapter 1

Introduction Box 1.1

Basic facts about TB TB is an infectious disease caused by the bacillus Mycobacterium tuberculosis. It typically affects the lungs (pulmonary TB) but can affect other sites as well (extrapulmonary TB). The disease is spread in the air when people who are sick with pulmonary TB expel bacteria, for example by coughing. In general, a relatively small proportion of people infected with M. tuberculosis will develop TB disease; however, the probability of developing TB is much higher among people infected with HIV. TB is also more common among men than women, and affects mostly adults in the economically productive age groups. The most common method for diagnosing TB worldwide is sputum smear microscopy (developed more than 100 years ago), in which bacteria are observed in sputum samples examined under a microscope. Following recent breakthroughs in TB diagnostics, the use of rapid molecular tests for the diagnosis of TB and drug-resistant TB is increasing, as highlighted in Chapter 5 and Chapter 8 of this report. In countries with more developed laboratory capacity, cases of TB are also diagnosed via culture methods (the current reference standard). Without treatment, TB mortality rates are high. In studies of the natural history of the disease among sputum smearpositive/HIV-negative cases of pulmonary TB, around 70% died within 10 years; among culture-positive (but smearnegative) cases, 20% died within 10 years.a Effective drug treatments were first developed in the 1940s. The most effective first-line anti-TB drug, rifampicin, became available in the 1960s. The currently recommended treatment for new cases of drug-susceptible TB is a sixmonth regimen of four first-line drugs: isoniazid, rifampicin, ethambutol and pyrazinamide. Treatment success rates of 85% or more for new cases are regularly reported to WHO by Member States (Chapter 3). Treatment for multidrugresistant TB (MDR-TB), defined as resistance to isoniazid and rifampicin (the two most powerful anti-TB drugs) is longer, and requires more expensive and more toxic drugs. For most patients with MDR-TB, the current regimens recommended by WHO last 20 months, and treatment success rates are much lower (Chapter 4). For the first time in four decades, new TB drugs are starting to emerge from the pipeline and combination regimens that include new compounds are being tested in clinical trials, as discussed in Chapter 8. There are several TB vaccines in Phase I or Phase II trials (Chapter 8). For the time being, however, a vaccine that is effective in preventing TB in adults remains elusive. a

Tuberculosis (TB) remains a major global health problem. It causes ill-health among millions of people each year and ranks as the second leading cause of death from an infectious disease worldwide, after the human immunodeficiency virus (HIV). The latest estimates included in this report are that there were 8.6 million new TB cases in 2012 and 1.3 million TB deaths (just under 1.0 million among HIV-negative people and 0.3  million HIV-associated TB deaths). Most of these TB cases and deaths occur among men, but the burden of disease among women is also high. In 2012, there were an estimated 2.9  million cases and 410 000 TB deaths among women, as well as an estimated 530 000 cases and 74 000 deaths among children.1 The number of TB deaths is unacceptably large given that most are preventable if people can access health care for a diagnosis and the right treatment is provided. Short-course regimens of first-line drugs that can cure around 90% of cases have been available for decades. These large numbers of cases and deaths notwithstanding, 20 years on from the 1993 World Health Organization (WHO) declaration of TB as a global public health emergency, major progress has been made. Globally, the TB mortality rate (deaths per 100 000 population per year) has fallen by 45% since 1990 and TB incidence rates (new cases per 100 000 population per year) are falling in most parts of the world. In the 18 years since the launch of a new international strategy for TB care and control by WHO in the mid-1990s (the DOTS strategy) and the subsequent global rollout of DOTS and its successor (the Stop TB Strategy,2 Box 1.2), a cumulative total of 56 million people were successfully treated for TB between 1995 and 2012, saving approximately 22 million lives. The overarching goal of the Stop TB Strategy is to achieve 2015 global targets (shown in Box 1.2) for reductions in the burden of disease caused by TB. The target set within the United Nations (UN) Millennium Development Goals (MDGs) is that TB incidence should be falling by 2015 (MDG Target 6.c). Besides incidence, four other TB indicators are included in the MDG monitoring framework: the prevalence rate, the mortality rate, the case detection rate (the number of notified cases divided by the estimated number of incident cases in the same year, expressed as a percentage), and the treatment success rate (the percentage 1 The

Tiemersma EW et al. Natural history of tuberculosis: duration and fatality of untreated pulmonary tuberculosis in HIV-negative patients: A systematic review. PLoS ONE, 2011, 6(4): e17601.

estimated number of deaths among children excludes TB deaths in HIV-positive children, for which estimates are not yet available. Further details are provided in Chapter 2. 2 Raviglione M, Uplekar M. WHO’s new Stop TB strategy. The Lancet, 2006, 367: 952–5.

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Box 1.2

The Stop TB Strategy at a glance THE STOP TB STRATEGY VISION GOAL OBJECTIVES A TB-free world To dramatically reduce the global burden of TB by 2015 in line with the Millennium Development Goals (MDGs) and the Stop TB Partnership targets n Achieve universal access to high-quality care for all people with TB n Reduce the human suffering and socioeconomic burden associated with TB n Protect vulnerable populations from TB, TB/HIV and drug-resistant TB n Support development of new tools and enable their timely and effective use n Protect and promote human rights in TB prevention, care and control TARGETS n MDG 6, Target 6.c: Halt and begin to reverse the incidence of TB by 2015 n Targets linked to the MDGs and endorsed by the Stop TB Partnership: – 2015: reduce prevalence of and deaths due to TB by 50% compared with a baseline of 1990 – 2050: eliminate TB as a public health problem (defined as <1 case per 1 million population per year)

COMPONENTS 1. Pursue high-quality DOTS expansion and enhancement a. Secure political commitment, with adequate and sustained financing b. Ensure early case detection, and diagnosis through quality-assured bacteriology c. Provide standardized treatment with supervision, and patient support d. Ensure effective drug supply and management e. Monitor and evaluate performance and impact 2. Address TB/HIV, MDR-TB, and the needs of poor and vulnerable populations a. Scale up collaborative TB/HIV activities b. Scale up prevention and management of MDR-TB c. Address the needs of TB contacts, and of poor and vulnerable populations 3. Contribute to health system strengthening based on primary health care a. Help improve health policies, human resource development, financing, supplies, service delivery and information b. Strengthen infection control in health services, other congregate settings and households c. Upgrade laboratory networks, and implement the Practical Approach to Lung Health d. Adapt successful approaches from other fields and sectors, and foster action on the social determinants of health 4. Engage all care providers a. Involve all public, voluntary, corporate and private providers through public–private mix approaches b. Promote use of the International Standards for Tuberculosis Care 5. Empower people with TB, and communities through partnership a. Pursue advocacy, communication and social mobilization b. Foster community participation in TB care, prevention and health promotion c. Promote use of the Patients’ Charter for Tuberculosis Care 6. Enable and promote research a. Conduct programme-based operational research b. Advocate for and participate in research to develop new diagnostics, drugs and vaccines

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figure 1.1

Seventeen annual WHO global TB reports, 1997–2012 1997: First report: epidemiology and surveillance 2002: Added financing and strategy for 22 high-burden countries (HBCs)

2003: Financing and strategy (all countries)

July 2009: Online data collection introduced December 2009: Short update to 2009 report in transition to earlier reporting of data and report publication

of TB patients who are successfully treated). The Stop TB Partnership adopted the MDG target and in addition set global targets to halve TB prevalence and death rates by 2015 compared with their levels in 1990. The scale at which interventions included in the Stop TB Strategy need to be implemented to achieve the 2015 targets for reductions in disease burden, and the associated funding requirements, have been described in Global Plans developed by the Stop TB Partnership. The latest plan covers the period 2011– 2015 and has a price tag of US$ 47 billion.1 As the MDG target year of 2015 approaches, work on a post-2015 development framework is assuming increasing prominence. In June 2013, a high-level panel established by the UN Secretary General to provide recommendations about the content of a post-2015 development framework, including possible goals and targets, submitted its report.2 One of the twelve proposed goals for 2030 is to “Ensure healthy lives”, under which a suggested target is to “Reduce the burden of disease from HIV/AIDS, TB, malaria, neglected tropical diseases and priority noncommunicable diseases”. Important themes within the report are building on the MDGs and equity, and for health specifically the importance of steady progress towards universal health coverage (UHC) is highlighted. In line with the development of a post-2015 development framework and in response to a request from Member States, WHO began the process of developing a post-2015 global TB strategy in 2012. Following a series of consultations between June 2012 and July 2013, the draft strategy includes the goal of ending the global TB epidemic by 2035, with corresponding global targets for major reductions in TB cases and deaths by 2035 and milestones for 2020, 2025 and 2030. Achieving the proposed targets is based on three strategic pillars: integrated, patient-centred TB care

1

The Global Plan to Stop TB, 2011–2015. Geneva, World Health Organization, 2010 (WHO/HTM/STB/2010.2). Available at http://w w w.stoptb.org /assets/documents/global/plan/ TB _ GlobalPlanToStopTB2011-2015.pdf 2 http://www.un.org/sg/management/beyond2015.shtml

and prevention; bold policies and supportive systems; and intensified research and innovation. It is anticipated that the strategy will be reviewed by the WHO Executive Board in January 2014 and discussed at the World Health Assembly in May 2014. In the context of global TB strategies and targets, WHO has published a global TB report every year since 1997 (Figure 1.1). The main aim of the report is to provide a comprehensive and up-to-date assessment of the TB epidemic and progress in prevention, diagnosis and treatment of the disease at global, regional and country levels, based primarily on data that are reported by countries and territories to WHO in annual rounds of global TB data collection (Box 1.3). This 2013 global TB report is the eighteenth in the series of annual reports, and uses data reported by a total of 197 countries and territories including 178 Member States that account for over 99% of the world’s estimated cases of TB reported data ( Table 1.1). With just over two years remaining before the end of 2015, a special feature of this 2013 global report is that it is accompanied by a supplement focused on the ‘Countdown to 2015’ (Box 1.4). The main part of the report contains seven major chapters. Each chapter is intended to stand alone, but links to other chapters are highlighted where appropriate. Chapter 2 contains the latest estimates of the burden of disease caused by TB and assessment of progress towards the 2015 targets at global, regional and country levels. Estimates for women and children specifically are given particular attention. Following new analytical and modelling work in 2013, the chapter also contains new estimates of the number of cases of and deaths from MDR-TB and of HIV-related TB mortality. The latest status of efforts to improve measurement of TB cases and deaths at country level, with guidance and support from the WHO Global Task Force on TB Impact Measurement, is described. Chapter 3 presents data on the numbers of cases notified to NTPs and reported to WHO and their treatment outcomes, including breakdowns of TB cases by type, sex and age. Recent progress in increasing the reporting of cases by private sector providers through engagement of

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Box 1.3

Data collected in the 2013 round of global TB data collection Data were requested on the following topics: TB case notifications and treatment outcomes, including breakdowns by TB case type, age, sex and HIV status; an overview of services for the diagnosis and treatment of TB; laboratory diagnostic services; drug management; monitoring and evaluation; surveillance and surveys of drug-resistant TB; management of drug-resistant TB; collaborative TB/HIV activities; TB infection control; engagement of all care providers in TB control; the budgets of national TB control programmes (NTPs) in 2013 and 2014; utilization of general health services (hospitalization and outpatient visits) during treatment; and NTP expenditures in 2012. A shortened version of the online questionnaire was used for high-income countries (that is, countries with a gross national income per capita of ≥US$ 12 616 in 2012, as defined by the World Bank)a and/or low-incidence countries (defined as countries with an incidence rate of <20 cases per 100 000 population or <10 cases in total). Countries reported data using an online web-based system (www.stoptb.org/tme). The system was opened for reporting on 14 March, with a deadline of 15 May for all WHO regions except the Region of the Americas (29 May) and the European Region (30 May). Countries in the European Union submit notification data to a system managed by the European Centre for Disease Prevention and Control (ECDC). Data from the ECDC system were uploaded into the WHO online system. Data were reviewed, and followed up with countries where appropriate, by a team of reviewers from WHO (headquarters and regional offices) and the Global Fund to Fight AIDS, Tuberculosis and Malaria (the Global Fund). Validation of data by respondents was also encouraged via a series of in-built, real-time checks of submitted data as well as a summary report of apparent inconsistencies or inaccuracies (this report can be generated at any time within the online system). Following corrections and updates by countries, the data used for the main part of this report were the data available in July 2013. Annex 4 was produced on 1 October, by which time additional data had been reported by a few European countries.b Besides the data reported through the standard TB questionnaire, data about screening for TB among people living with HIV and provision of isoniazid preventive therapy (IPT) to those without active TB were collected by the HIV department in WHO and the Joint United Nations Programme on HIV/AIDS (UNAIDS). The data were jointly validated and imported into the global TB database. a. b.

http://data.worldbank.org/about/country-classifications For this reason, there may be slight discrepancies between the main part of the report and Annex 4.

Table 1.1

Reporting of data in the 2013 round of global TB data collection Countries and territories WHO region or set of countries Number Number that reported data Number Member States Number that reported data

African Region Eastern Mediterranean Region European Regiona Region of the Americas South-East Asia Region Western Pacific Region High-burden countries (HBCs)b World a

46 23 54 46 11 36 22 216

45 23 42 46 11 30 22 197

46 22 53 35 11 27 22 194

45 22 41 35 11 24 22 178

Countries that did not report by the deadlines were mostly low-incidence countries in Western Europe. b The HBCs are Afghanistan, Bangladesh, Brazil, Cambodia, China, the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Kenya, Mozambique, Myanmar, Nigeria, Pakistan, the Philippines, the Russian Federation, South Africa, Thailand, Uganda, the United Republic of Tanzania, Viet Nam and Zimbabwe.

large hospitals in five countries, the contribution of community health workers and volunteers to the referral of TB cases and treatment support in 13 countries, and strikingly high notification rates in prisons in parts of the European Region, are highlighted. Chapter 4 focuses on drug-resistant TB. The first part of the chapter covers progress in drug resistance surveillance and associated estimates of the absolute number and proportion of TB patients that have MDR-TB and extensively drug-resistant TB (XDR-TB). The second part of the chapter presents and discusses the latest data on the pro-

grammatic response to MDR-TB, including the coverage of testing for drug resistance among new and previously treated TB patients, the number of cases detected with MDRTB and enrolled on treatment, and treatment outcomes. Chapter 5, on TB diagnostics and laboratory strengthening, covers three topics. These are policy developments between mid-2012 and mid-2013, the status of laboratory capacity and incorporation of WHO guidance into national policy in 2012, and recent progress in strengthening laboratories and associated diagnostic capacity. The latest data on the roll out of the rapid molecular test Xpert MTB/RIF

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since it was recommended in 2010 and two multinational projects (EXPAND-TB and TBXpert) are included. Chapter 6 contains the most recent data on progress in implementing collaborative TB/HIV activities to jointly address the epidemics of TB and HIV. These include HIV testing for TB patients, provision of antiretroviral therapy (ART) to HIV-positive TB patients, intensified screening for TB among people living with HIV and treatment for those without active TB with IPT. Chapter 7 assesses financing for TB care and control. Funding requirements for a full response to the global TB epidemic up to 2015, which were updated in early 2013 as part of preparatory work undertaken to inform the replenishment of the Global Fund, are presented first. Key findings from a study of long-term trends (2002–2011) using data compiled in the WHO annual rounds of data collection and recently published in The Lancet Global Health are then summarized, followed by a detailed analysis of new data reported in 2013. Chapter 8 discusses research and development for new TB diagnostics, drugs and vaccines. After years of stagnation, considerable progress has occurred in the past decade and the development pipelines as of mid-2013 are described and discussed. The report also has four annexes. Annex 1 explains the methods used to produce estimates of the burden of disease caused by TB. Annex 2 contains country profiles for the 22 HBCs that collectively account for about 80% of the world’s TB cases (profiles for all countries are available online1). Annex 3 contains regional profiles. Annex 4 consists of summary tables that provide data on key indicators for the world, the six WHO regions and individual countries.

Box 1.4

Special supplement on the Countdown to 2015 The MDGs were established by the UN at the turn of the 21st century, with targets set for 2015 (www.un.org/ millenniumgoals). Designed to drive progress worldwide and endorsed by all countries, the targets have been the focus of international and national development efforts for more than a decade. TB was included as part of MDG 6. In addition to TB targets and indicators that are part of the MDG framework, targets for the response needed to address the specific challenges of MDR-TB and the TB/HIV co-epidemic have been set for 2015 in the Global Plan to Stop TB 2011–2015. With just over two years remaining before the target deadline of the end of 2015, this 2013 global TB report is accompanied by a special supplement called Countdown to 2015. The supplement provides an overview of progress towards the 2015 targets set within the MDG framework and for the response to TB/HIV and MDR-TB specifically, and the top priority actions needed to either move beyond or accelerate towards these targets. Snapshots are provided globally, regionally and for the 22 HBCs that have about 80% of the world’s TB cases and that have received greatest attention at the global level since 2000. The snapshots are based on the data presented in the main chapters of the report and the annexes, complemented by recommendations from recent programme reviews, published literature, and discussions with experts at global, regional and national levels.

1

www.who.int/tb/data

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Chapter 2

The burden of disease caused by TB Key facts and messages ■■ The global burden of TB remains enormous. In 2012, there were an estimated 8.6 million incident cases of TB and 1.3 million people died from the disease (940 000 deaths among people who were HIV-negative and 320 000 among people who were HIV-positive). Among these deaths there were an estimated 170 000 from MDR-TB, a relatively high total compared with 450 000 incident cases of MDR-TB. ■■ Although the number of TB cases and deaths remains unnecessarily large for a mostly curable disease, there has been major progress towards global targets for reductions in the burden of disease. The 2015 MDG target of halting and reversing TB incidence has been achieved, with TB incidence falling globally for several years (2% per year in 2012). Globally, the TB mortality rate has fallen by 45% since 1990 and the Stop TB Partnership target of a 50% reduction by 2015 is within reach. Mortality and incidence rates are falling in all six WHO regions and in most of the 22 HBCs that account for over 80% of the world’s TB cases. ■■ This is the first year in which estimates of TB deaths among HIVpositive people were produced using the UNAIDS Spectrum model, leading to revisions to previously published estimates for the period 1990–2011. The estimated percentage of TB cases living with HIV remains unchanged, at 13% globally in 2012. ■■ Although most TB cases and deaths occur among men, the burden of disease is high among women. In 2012, an estimated 410 000 women died from TB (250 000 among HIV-negative women and 160 000 among HIV-positive women). There were also an estimated 74 000 TB deaths among HIV-negative children (estimates of HIV-associated mortality are not yet available). ■■ The South-East Asia and Western Pacific Regions collectively accounted for 58% of the world’s TB cases in 2012. The African Region had approximately one quarter of the world’s cases, and the highest rates of cases and deaths relative to population (255 incident cases per 100 000 on average, more than double the global average of 122). India and China had the largest number of cases (26% and 12% of the global total, respectively). South Africa and Swaziland had the highest incidence rate per capita (about 1 new case for every 100 people each year). ■■ The quality and coverage of data available to estimate TB disease burden continues to improve. In 2012, data from vital registration systems were used to estimate TB mortality in 121 countries (up from 3 countries in 2008); there has been unprecedented progress in the implementation of national TB prevalence surveys since 2008; and efforts to improve the monitoring of TB incidence by strengthening routine health information systems and implementing inventory studies to measure under-reporting of diagnosed cases are expanding. ■■ Five national TB prevalence surveys were implemented in 2012 (in the Gambia, Nigeria, Rwanda, the United Republic of Tanzania and Thailand) and a further five will start or be completed in 2013 (in Ghana, Indonesia, Malawi, Sudan and Zambia). These surveys provide a direct measure of disease burden, often for the first time, and will be used to update estimates of disease burden once results are finalized. They also provide rich data to inform programme policy and strategy.

The burden of disease caused by TB can be measured in terms of incidence (defined as the number of new and relapse cases of TB arising in a given time period, usually one year), prevalence (defined as the number of cases of TB at a given point in time) and mortality (defined as the number of deaths caused by TB in a given time period, usually one year). This chapter presents estimates of TB incidence, prevalence and mortality (absolute numbers and rates) between 1990 and 2012 and (for prevalence and mortality) forecasts up to 2015 (in sections 2.1–2.3). These data are used to assess progress towards achieving the global targets for reductions in TB disease burden set for 2015: that incidence should be falling (MDG Target 6.c) and that prevalence and death rates should be halved by 2015 compared with 1990 (Box 1.2 in Chapter 1). Key aspects of the methods used to produce the estimates are provided at the beginning of each section.1 Estimates of the number of incident TB cases among people living with HIV, the number of incident cases of MDR-TB, mortality due to MDR-TB and TB deaths disaggregated by HIV status are included in the relevant sections. Estimates are presented globally, for the six WHO Regions, and at country level with particular focus on the 22 HBCs. In response to increasing demand and global attention, special consideration is given to estimates of TB disease burden among women and children. Updates to data sources and methods used to produce estimates of TB disease burden compared with those published in 2012 are highlighted in Box 2.1. There is uncertainty in all estimates of the burden of disease caused by TB. Section 2.4 profiles efforts to improve measurement of this burden under the umbrella of the WHO Global Task Force on TB Impact Measurement. The recent and unprecedented progress in implementing national TB prevalence surveys is summarized and expanding efforts to strengthen surveillance of cases and deaths via notification and vital registration (VR) systems are described. 1

A detailed description is provided in Annex 1.

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GLOBAL TUBERCULOSIS REPORT 2013

Box 2.1

Updates to estimates of TB disease burden in this report and updates that are anticipated in the near future Each year, new data become available for the estimation of TB disease burden. Periodically, new approaches to the use of available data are developed. This box provides a summary of updates that were made in 2013. Updates for specific countries that are expected in the near future, pending the finalization of analyses of data from recently completed prevalence surveys, are also highlighted.

Updates in this report 1. TB/HIV burden estimates In 2013, and for the first time, estimates of TB incidence among people living with HIV and TB mortality among HIVpositive people were generated using the Spectrum software programme.a Spectrum has been used for more than a decade to produce estimates of the burden of disease caused by HIV, to build projections about the future course of the HIV epidemic and to assess the potential impact of interventions. A TB module was developed in 2012 and 2013 through a collaboration between the Futures Institute, the TB Modelling and Analysis Consortium (TB-MAC), UNAIDS and WHO. It was initially tested in two regional workshops held in Johannesburg, South Africa (in March 2013) and subsequently in a workshop for countries in western Africa. The mathematical methods implemented in Spectrum as well as the input data are described in Annex 1. It is anticipated that the TB module will be extended to include projections of the future course of the TB epidemic and the potential impact of selected interventions, building on existing estimates of TB disease burden generated by WHO. The updated estimates of TB incidence among people living with HIV published in this report are generally very consistent with previously published estimates, especially for countries with a generalized HIV epidemic and strong TB/ HIV surveillance systems. The updated time series of mortality estimates at global level and for the African Region indicate a lower level of TB mortality among HIVpositive people compared with estimates published in 2012. As a result of the use of Spectrum, country-specific estimates of TB mortality among HIV-positive people that are fully consistent with overall estimates of HIV mortality are available for the first time. These are shown in Annex 2 and in online country profiles. 2. MDR-TB mortality and incidence Estimates of MDR-TB mortality and incidence were last produced in 2008 and published in a 2010 WHO report on the MDR-TB epidemic. A systematic literature review of evidence about mortality a

associated with MDR-TB was commissioned by WHO in 2013. The results have been used to produce global estimates of MDR-TB incidence and mortality in 2012. The estimate of mortality due to MDR-TB is slightly higher than before, but the uncertainty interval greatly overlaps the previous one. The estimate of MDRTB incidence is similar to the previous estimate. 3. Newly reported data There are relatively small changes to estimates of TB incidence, mortality and prevalence for many countries that reflect vital registration data reported to WHO between mid-2012 and mid2013, updated WHO estimates of the overall number of deaths (that provide overall mortality envelopes), updates to estimates of the burden of HIV-associated TB and new TB notification data including corrections made to historical data. In most instances, changes are well within the uncertainty intervals of previously published estimates of TB burden and time trends are generally consistent. Newlyreported data are the reason for small changes to estimates of the number of TB deaths among women and children. 4. In-depth epidemiological reviews In January 2013, estimates of TB burden for Viet Nam were updated in close consultation with the NTP and other stakeholders. These resulted in changes to estimates of the level of and trends in TB incidence, prevalence and mortality compared with those published in the 2012 global TB report. Updates drew on new analyses from prevalence survey data, evidence about the influence on trends in case notifications of increased reporting to the NTP of cases diagnosed in the private sector and prisons and new analyses of broader influences on TB disease burden such as economic growth, health system performance and the coverage of health insurance. 5. Inclusion of newly reported cases without documented treatment history in incidence estimates In previous years, notified TB patients without any reported treatment history were not considered as incident cases (incident cases were the sum of new and

relapse cases). In this report, notified cases for which the treatment history is unknown are considered to be incident cases. This change is justified for two reasons: first, in countries facing problems with incomplete documentation of treatment history, the vast majority of such cases are first episodes or relapse episodes; second, WHO received several requests from NTPs (or equivalent) to include all patients with no documented treatment history in the count of new and relapse episodes to avoid understating the true burden of TB. This change affects relatively few countries, most of which are in western Europe.

Updates anticipated in the near future Updates to estimates of disease burden are expected in several countries that have recently completed or will soon complete national TB prevalence surveys. These include five HBCs: Indonesia, Nigeria, Pakistan, Thailand and the United Republic of Tanzania. Additional countries include the Gambia and Rwanda, both of which completed surveys in 2012, and Ghana where a survey began in March 2013. In addition to a prevalence survey, an inventory study to estimate TB underreporting was completed in Pakistan in 2012 (see also section 2.4) and an in-depth epidemiological review was conducted in Thailand in August 2013. A workshop for the six countries that had completed surveys by July 2013 (i.e. the Gambia, Nigeria, Pakistan, Rwanda, Thailand and United Republic of Tanzania) as well as their technical partners will be held at WHO headquarters in November 2013, to conduct and complete analyses of survey data. Following this workshop, updates to estimates of TB disease burden will be possible. These updates will be made available in online country profiles and associated data sets. In 2014, a thorough review of the current epidemiological and modelling methods used to estimate TB disease burden will be conducted by the WHO Global Task Force on TB Impact Measurement. The recommendations may result in some further updates in the 2014 global TB report.

http://www.futuresinstitute.org/spectrum.aspx

GLOBAL TUBERCULOSIS REPORT 2013

7

2.1 TB incidence TB incidence has never been measured at national level because this would require long-term studies among large cohorts of people (hundreds of thousands) at high cost and with challenging logistics. Notifications of TB cases provide a good proxy indication of TB incidence in countries that have both high-performance surveillance systems (for example, there is little underreporting of diagnosed cases) and where the quality of and access to health care means that few cases (or a negligible number) are not diagnosed. In the large number of countries where these criteria are not yet met, TB incidence can be estimated using an inventory study (in which the level of underreporting is assessed) combined with capture–recapture analysis to estimate under-diagnosis, provided that certain assumptions are satisfied.1 To date, such studies have been undertaken in only a few countries: examples include Egypt, Iraq and Yemen (see section 2.4). The ultimate goal is to directly measure TB incidence from TB notifications in all countries. This requires a combination of strengthened surveillance, better quantification of underreporting (i.e. the number of cases that are missed by surveillance systems) and universal access to health care. A TB surveillance checklist developed by the WHO Global Task Force on TB Impact Measurement defines the standards that need to be met

for notification data to provide a direct measure of TB incidence (further details in section 2.4). For most countries, incidence estimates are currently based on notification data combined with country consultations in which in-depth analyses of the available surveillance, survey and programmatic data are undertaken, and expert opinion about the fraction of cases diagnosed but not reported, or not diagnosed at all, is elicited and documented. The 96 countries (with 89% of estimated TB cases) covered by such consultations since 2008 are shown in Figure 2.1. For remaining countries not covered in workshops and in which notifications do not provide a good proxy indication of TB incidence, estimates are based on extending previously published time series, mortality data from VR systems combined with evidence about the case fatality rate, or ecological modelling (see Annex 1 for details). In 2012, there were an estimated 8.6 million incident cases of TB (range, 8.3 million–9.0 million) globally, equivalent to 122 cases per 100 000 population ( Table 2.1, Table 2.2). The absolute number of incident cases is falling, albeit slowly (Figure 2.2). Most of the estimated number of cases in 2012 occurred in Asia (58%) and the African Region (27%);2 smaller proportions of cases occurred in the Eastern Mediterranean Region (8%), the European Region (4%) and the Region of

figure 2.1

Coverage of country consultations on estimates of TB disease burden, 2008–2013

1

An inventory study can be used to measure the number of cases that are diagnosed but not reported, but using results to estimate the total number of incident cases using capture–recapture methods requires that certain conditions are met. These are explained in a guide on inventory studies recently published by WHO, which is available at: www.who.int/tb/publications/inventory_studies/en/index.html 2 Asia refers to the WHO Regions of South-East Asia and the Western Pacific.

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GLOBAL TUBERCULOSIS REPORT 2013

Table 2.1

Estimated epidemiological burden of TB, 2012. Numbers in thousands.a MORTALITY b POPULATION BESTc LOW HIGH BEST HIV-POSITIVE TB MORTALITY LOW HIGH BEST PREVALENCE LOW HIGH BEST INCIDENCE LOW HIGH BEST HIV-positive INCIDENT TB CASES LOW HIGH

Afghanistan Bangladeshd Brazil Cambodia China DR Congo Ethiopia Indiae Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global a b

29 825 154 695 198 656 14 865 1 377 065 65 705 91 729 1 236 687 246 864 43 178 25 203 52 797 168 834 179 160 96 707 143 170 52 386 66 785 36 346 47 783 90 796 13 724 4 432 959 892 529 961 103 616 591 904 540 1 833 359 1 845 562 7 053 684

11 70 4.9 9.3 44 36 16 270 67 9.5 13 25 27 62 23 19 31 9.2 4.7 6.1 18 4.6 780 230 19 100 36 450 110 940

4.6 29 4.6 4.3 43 16 12 170 30 5.4 1 12 1.6 27 22 18 3.7 3.8 0.8 3.2 12 0.2 630 160 16 63 35 330 96 790

20 < 0.1 < 0.1 130 < 0.1 < 0.1 5.2 16 46 64 21 390 120 15 41 44 86 110 25 20 86 17 12 9.9 25 16 940 310 21 150 36 590 120 1 100 2.5 0.6 1.2 6.3 5.6 42 2.1 7.7 45 4.6 19 1.2 2.2 0.4 0.9 5.5 4.6 37 1.8 6.6 35 3.8 11 0.8

0.3 0.1 3 0.7 1.5 8.1 7.3 48 3 8.9 53 5.3 25 1.3 0.1 2.2 100 2.8 12 8 2.7 20 280 270 7.2 4.7 4.4 56 5.4

110 670 120 110 1 400 380 210 2 800 730 130 140 260 270 670 450 170 450 110 64 84 200 59 9 600 2 700 390 1 100 510 4 800 2 400

54 340 51 96 1 200 200 170 1 900 350 71 28 200 43 320 390 73 160 47 24 45 78 13

180 1 100 210 130 1 600 620 250 3 900 1 200 210 340 320 710 1 100 500 320 880 190 120 140 370 140

56 350 92 61 1 000 210 230 2 200 460 120 140 200 180 410 260 130 530 80 65 79 130 77 7 000 2 300 280 670 360 3 400 1 600 8 600

47 290 76 52 880 190 170 2 000 380 110 96 170 85 340 210 110 430 66 53 74 99 60 6 700 2 100 260 590 340 3 200 1 500 8 300

67 410 110 70 1 100 250 290 2 400 540 120 190 230 310 490 310 150 630 95 79 84 170 97 7 400 2 500 300 750 390 3 700 1 800 9 000

0.3 0.2 16 2.7 7.3 16 23 130 7.5 45 83 19 46 3.8 0.5 9.3 330 12 35 32 9.3 55 880 830 31 11 19 170 24 1 100

0.2 0.2 13 2.3 6.4 14 17 120 5.6 44 58 16 21 3.1 0.4 7.9 270 10 28 30 6.9 42 810 760 28 10 17 160 21 1 000

0.5 0.3 19 3.1 8.2 19 30 140 9.7 47 110 21 80 4.6 0.6 11 390 14 42 34 12 69 960 910 34 12 21 180 27 1 200

0.1 < 0.1 1.8 88 2.2 9.2 7 2.1 18 270 250 6.4 4.2 3.9 51 4.8 320 1.5 75 1.9 8 5.8 1.8 15 250 230 5.6 3.8 3.4 46 4.2 300

8 200 11 000 2 100 300 730 380 3 700 2 100 3 300 490 1 600 650 6 100 2 600

340 12 000 11 000 13 000

Numbers for mortality, prevalence and incidence shown to two significant figures. Totals (HBCs, regional and global) are computed prior to rounding. Mortality excludes deaths among HIV-positive TB cases. Deaths among HIV-positive TB cases are classified as HIV deaths according to ICD-10 and are shown separately in this table. c Best, low and high indicate the point estimate and lower and upper bounds of the 95% uncertainty interval. d Estimates of TB disease burden have not been approved by the NTP in Bangladesh and a joint reassessment (by the NTP and WHO) will be undertaken following completion of the national TB prevalence survey scheduled for 2014. e Estimates for India have not yet been officially approved by the Ministry of Health & Family Welfare, Government of India, and should therefore be considered provisional.

GLOBAL TUBERCULOSIS REPORT 2013

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Table 2.2

Estimated epidemiological burden of TB, 2012. Rates per 100 000 population except where indicateda MORTALITY b POPULATION (THOUSANDS) BEST LOW HIGH HIV-POSITIVE TB MORTALITY BEST LOW HIGH BEST PREVALENCE LOW HIGH BEST INCIDENCE LOW HIGH HIV PREVALENCE IN INCIDENT TB CASES (%) BEST LOW HIGH

Afghanistan Bangladeshc Brazil Cambodia China DR Congo Ethiopia Indiad Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global a b

29 825 154 695 198 656 14 865 1 377 065 65 705 91 729 1 236 687 246 864 43 178 25 203 52 797 168 834 179 160 96 707 143 170 52 386 66 785 36 346 47 783 90 796 13 724 4 432 959 892 529 961 103 616 591 904 540 1 833 359 1 845 562 7 053 684

37 45 2.5 63 3.2 54 18 22 27 22 53 48 16 34 24 13 59 14 13 13 20 33 18 26 1.9 16 3.9 25 5.8 13

15 19 2.3 29 3.1 24 13 14 12 13 3.9 23 0.9 15 22 13 7 5.8 2.3 6.8 13 1.2 14 18 1.7 10 3.9 18 5.2 11

68 84 2.6 110 3.3 97 23 32 48 34 163 84 51 61 26 14 164 25 33 21 27 117 21 35 2.2 24 4 32 6.4 16

0.3 < 0.1 1.3 3.8 < 0.1 9.7 6.1 3.4 0.9 18 177 8.8 11 0.7 0.1 1.2 168 3.3 25 15 2.4 132 6 28 0.7 0.7 0.4 2.8 0.3 4.6

< 0.1 < 0.1 1.1 2.7 < 0.1 8.3 5 3 0.7 15 138 7.3 6.7 0.5 < 0.1 1 144 2.9 22 12 2 111 5.6 26 0.6 0.6 0.4 2.5 0.2 4.3

1.1 < 0.1 1.5 4.7 0.1 12 8 3.9 1.2 21 209 10 15 0.8 0.1 1.5 192 4.2 32 17 2.9 147 6.4 30 0.7 0.8 0.5 3.1 0.3 4.8

358 434 59 764 99 576 224 230 297 299 553 489 161 376 461 121 857 159 175 176 218 433 216 303 40 180 56 264 128 169

181 218 25 645 86 301 180 155 144 164 111 377 25 181 405 51 305 71 67 95 86 92 186 239 31 118 42 203 115 149

595 721 107 892 113 938 272 319 506 475 1 340 616 420 641 520 221 1 680 282 334 283 410 1 030 248 373 51 256 72 333 142 190

189 225 46 411 73 327 247 176 185 272 552 377 108 231 265 91 1 000 119 179 165 147 562 159 255 29 109 40 187 87 122

156 185 38 353 64 282 183 159 153 261 383 322 50 190 219 77 827 98 145 154 109 434 151 235 27 96 38 174 80 117

226 268 55 474 82 375 321 193 220 283 753 435 186 276 316 106 1 190 142 216 175 192 706 166 275 31 122 43 200 95 127

0.55 < 0.1 17.3 4.34 0.73 7.66 10.2 5.95 1.65 38.7 59.7 9.33 25.2 0.92 0.18 7.14 63.0 15.2 53.2 41.2 6.97 70.9 7.37 36.6 11.4 1.88 5.26 4.94 1.49 12.8

0.41 < 0.1 17.1 4.21 0.73 7.65 10.1 5.93 1.65 38.7 59.6 9.32 24.8 0.84 0.18 7.03 62.9 15.2 52.9 41.2 6.94 70.7 7.35 34.7 8.67 1.34 3.80 4.31 0.92 11.6

0.68 < 0.1 17.4 4.44 0.73 7.66 10.2 5.97 2.33 38.7 59.8 9.33 25.7 0.96 0.18 7.25 63.0 15.3 53.3 41.3 6.99 71.4 7.40 38.4 14.4 2.52 6.93 5.62 2.18 14.0

Best, low and high indicate the point estimate and lower and upper bounds of the 95% uncertainty interval. Mortality excludes deaths among HIV-positive TB cases. Deaths among HIV-positive TB cases are classified as HIV deaths according to ICD-10 and are shown separately in this table. c Estimates of TB disease burden have not been approved by the NTP in Bangladesh and a joint reassessment (by the NTP and WHO) will be undertaken following completion of the national TB prevalence survey scheduled for 2014. d Estimates for India have not yet been officially approved by the Ministry of Health & Family Welfare, Government of India, and should therefore be considered provisional.

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GLOBAL TUBERCULOSIS REPORT 2013

figure 2.2

figure 2.3

Estimated absolute numbers of TB cases and deaths (in millions), 1990–2012 TB incidence 10.0

Estimated TB incidence: top-ten countries, 2012 a. Incidence: absolute numbers India China G G

All TB cases 7.5

South Africa Indonesia Pakistan G G

G

Millions

5.0

Bangladesh Philippines Ethiopia G

G

G

2.5 HIV positive TB cases

DR Congo Myanmar

G

G

0.5 0 1990 1995 2000 2005 2012

1.0

1.5 Millions

2.0

2.5

b. Incidence: rate per 100 000 population TB deaths 2.0 TB deaths among HIV negative people 1.5 Swaziland South Africa Sierra Leone Namibia Lesotho Millions 1.0 Djibouti Zimbabwe TB deaths among HIV positive peoplea 0.5 Mozambique Timor Leste Gabon 0 1990 a G G G G G G G

G

G

G

400 1995 2000 2005 2012

800

1200

1600

Rate per 100 000 population per year

HIV-associated TB deaths are classified as HIV deaths according to ICD-10.

the Americas (3%). The 22 HBCs that have been given highest priority at the global level since 2000 (listed in Table 2.1 and Table 2.2) accounted for 81% of all estimated incident cases worldwide. The five countries with the largest number of incident cases in 2012 were India (2.0 million– 2.4 million), China (0.9 million–1.1 million), South Africa (0.4 million–0.6 million), Indonesia (0.4 million–0.5 million) and Pakistan (0.3 million–0.5 million); these and the other five countries that make up the top ten in terms of numbers of cases are highlighted in Figure 2.3. India and China alone accounted for 26% and 12% of global cases, respectively. Of the 8.6 million incident cases, an estimated 0.5 million were children and 2.9 million (range, 2.7– 3.1 million) occurred among women (Box 2.2). The 8.6 million incident TB cases in 2012 included 1.0 million–1.2 million (12–14%) among people living with HIV, with a best estimate of 1.1 million (13%) ( Table 2.1, Table 2.2). The proportion of TB cases co-infected with HIV was highest in countries in the African Region (Figure 2.4).

Overall, 37% of TB cases were estimated to be co-infected with HIV in this region, which accounted for 75% of TB cases among people living with HIV worldwide. In parts of southern Africa, more than 50% of TB cases were co-infected with HIV (Figure 2.4). Following a systematic review of evidence about mortality caused by MDR-TB (Box 2.3), global estimates of the burden of MDR-TB were updated in 2013 (Box 2.1). The best estimate is that there were 450  000 (range, 300  000‒600  000) new cases of MDR-TB worldwide in 2012. This total includes cases of primary and acquired MDR-TB. The number of incident TB cases relative to population (the incidence rate) varies widely among countries (Figure 2.5). The lowest rates are found predominantly in high-income countries including most countries in western Europe, Canada, the United States of America, Japan, Australia and New Zealand. In these countries, the incidence rate per 100 000 population is less than 10 cases per

GLOBAL TUBERCULOSIS REPORT 2013

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Box 2.2

The burden of TB disease among women and children The burden of TB morbidity and mortality among women (defined as females aged ≥ 15 years) and children (defined as people aged <15 years) is larger than often realised. This is the second consecutive year in which the WHO global TB report highlights the burden of disease among children and for the first time includes estimates of the burden among women disaggregated by region and HIV status. There were an estimated 2.9 million new cases of TB and 410 000 deaths from the disease among women in 2012. Among children, there were an estimated 530 000 new cases in 2012 and 74 000 deaths among children who were HIV-negative. Methods used to produce these estimates and further details about results are provided below. The estimates of TB morbidity and mortality among children are slightly higher than those published in the 2012 global TB report, reflecting new surveillance data that show more TB cases being notified among children globally, and new VR data. The burden of TB in women: estimates of TB incidence and mortality, 2012 Incidence Regional estimates of the women:men ratio for new (all case types) TB case notifications in 2012 were generated and assumed to be the same as the ratio among incident TB cases in 2012 (see Annex 1 for further details). The resulting global and regional estimates of incidence are shown in Table B2.2.1. Women account for 34% of the total of 8.6 million incident cases in 2012. The African and South-East Asia regions account for 68% of the cases among women. Table B2.2.1

TB deaths were calculated for women and men, after adjustment for incomplete coverage and ill-defined causes (see Annex 1 for further details). For countries without VR data, an ecological statistical model was used to predict the ratio of male to female TB mortality. The model included a set of risk factors known to be associated with TB mortality (GDP per capita, the percentage of new cases with MDR-TB, HIV prevalence in the general population and the treatment success rate). Globally, there were 2.55 (range, 1.92–3.18) male deaths among HIV-negative adults for every female death (Figure B2.2.1). Regional differences are evident ( Table B2.2.2), with the African and South-East Asia regions accounting for 69% of total deaths. The main limitation in the methods used is that the 120 countries reporting usable VR data were all middle- or high-income countries. Predictions for lowincome countries had to be extrapolated from these countries. TB deaths among HIV-positive people were disaggregated by sex using the assumption that the male to female sex ratio is similar to the sex ratio of AIDS deaths estimated by UNAIDS. Globally, the numbers of HIV-associated TB deaths were similar among men and women (Figure B2.2.2). However, there were striking regional variations ( Table B2.2.2). In the African Region, more deaths occurred among women than men, while in other regions more deaths were estimated to have occurred among men. Table B2.2.2

Estimated number of TB deaths among women in 2012, disaggregated by WHO region HIV-negative Best estimate Uncertainty interval Best estimate HIV-positive Uncertainty interval

Total number of new TB notifications (all case types) and estimated incident cases among women in 2012, disaggregated by WHO region WHO region Number of TB case notifications Estimated TB incidence Best estimate Uncertainty interval

AFR AMR EMR EUR SEAR WPR Global

80 000 5 900 32 000 10 000 93 000 26 000 250 000

53 000–110 000 5 000–6 700 18 000–46 000 9 700–10 000 65 000–120 000 24 000–29 000 210 000–290 000

140 000 2 000 1 400 1 200 18 000 1 200 160 000

130 000–150 000 1 900–2 200 1 300–1 600 1 000–1 300 16 000–20 000 1 000–1 300 150 000–170 000

AFR AMR EMR EUR SEAR WPR Global

361 645 63 626 101 910 79 279 431 470 392 030 1 429 960

860 000 100 000 280 000 120 000 1 100 000 510 000 2 900 000

780 000–940 000 91 000–110 000 240 000–330 000 110 000–130 000 990 000–1 200 000 460 000–550 000 2 700 000–3 100 000

The burden of TB in children: estimates of TB notifications, incidence and mortality (among those HIVnegative), 2012 TB notifications and incidence The global number of new TB case notifications among children (aged <15 years) is estimated at 349 000 in 2012 ( Table B2.2.3). This includes cases reported among children and an estimate of the number of cases among children in countries that did not report notifications disaggregated by age. For countries that did not report age-disaggregated data (Figure B2.2.3), it was assumed that the ratio of child to adult notified cases was the same (for each case type) as in those countries that did report notifications disaggregated by age (an alternative method using the assumption that the ratio of childhood to adult notification rates was the same gave similar results). WHO does not request age-disaggregated data for relapse cases or those reported as of unknown case type, and the number of children in these categories was assumed to be zero. To estimate TB incidence among children, it was assumed that the case detection rate for all ages at the global level in 2012 (best

Mortality In total, there were an estimated 410 000 TB deaths among women in 2012. This includes 250 000 (range, 210 000–290 000) TB deaths among HIV-negative women (29% of all TB deaths among HIV-negative adults) and 160 000 (range, 150 000– 170 000) HIV-associated TB deaths (50% of all HIV-associated TB deaths). Newly reported data and a decrease in the overall TB mortality envelope explain the decrease in the estimated number of TB deaths among women compared with figures reported in previous years (see also Box 2.1). Mortality data disaggregated by age and sex from VR systems were used to produce estimates of TB deaths among HIV-negative adults for 120 countries (VR data were available for 121 countries but for China, age and sex-disaggregated data were not available).

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estimate 66%, range 64%–69%) was the same for adults and children. On this basis, TB incidence among children is estimated at 530 000 (range, 510 000–550 000) in 2012, equivalent to about 6% of the total number of 8.6 million incident cases. Limitations of the methods used include:

Figure B2.2.1

Figure B2.2.2

The male:female ratio for HIV-negative TB deaths among adults (aged ≥15 years), globally and for WHO regions AFR AMR EMR EUR

The male:female ratio for HIVassociated TB deaths among adults (aged ≥15 years), globally and for WHO regions AFR AMR EMR EUR

"" The assumption that the case SEAR SEAR detection rate is the same for adults and children, in the WPR WPR absence of any data on levels Global Global of underreporting of diagnosed cases for children and adults 1 2 3 4 1 2 3 Sex Ratio (M:F) Sex Ratio (M:F) separately. "" The assumption that reported cases were true cases of TB. Misdiagnosis is possible, especially Table B2.2.3 given the difficulties of diagnosing TB in children. New TB case notifications in 2012, by case type and "" The proportion of cases among children may be different in age disaggregation countries for which age-disaggregated data were not available. However, reporting of cases disaggregated by age has been SmearSmearExtrapositive negative pulmonary improving and the number of countries not reporting agedisaggregated data was relatively low in 2012. Total notifications 2 568 789 1 935 971 817 462 a

Mortality among HIV-negative children Mortality data reported to WHO from VR systems that were disaggregated by age were available for 120 countries. These data were used to calculate TB death rates per 100 000 population for children and adults, after adjustment for incomplete coverage and ill-defined causes (see Annex 1 for further details). For countries without VR data, an ecological statistical model was used to predict the ratio of childhood to adult TB mortality rates. The total number of deaths from TB among HIV-negative children was estimated to be 74 000 (range, 59 000–90 000), equivalent to about 8% of the total number of 940 000 TB deaths among HIV negative people in 2012. An estimate of TB mortality among HIV-positive children is not included in this report, due to the difficulties arising from the miscoding of HIV deaths as TB deaths. However, age disaggregation of HIV-associated TB mortality will be one of the future outcomes of the TB component of Spectrum (see Box 2.1). Steps to improve estimation of TB cases among children include: "" a global consultation to further develop analytical methods and to define and prioritize actions needed to obtain new data in September 2013; "" promotion of case-based electronic recording and reporting systems that facilitate compilation and analysis of agedisaggregated data; "" nationwide inventory surveys to measure underreporting of childhood TB; "" more contact-tracing studies and the integration of TB activities in maternal, newborn and child health services to find childhood cases that might otherwise not be diagnosed. Figure B2.2.3

Countries disaggregating by age Countries not disaggregating by age (% total notifications disaggregated) Number of countries that reported notifications disaggregated by age (number of HBCs)b Total childhood notifications from countries disaggregating by age Total estimated childhood notifications among all countries a b

2 551 136 17 653 (99%) 204 (22) 46 488

1 597 530 338 441 (83%) 184 (14) 163 477 349 000

678 953 138 509 (83%) 184 (14) 91 308

This includes reported cases for whom smear results were unknown or not done. An additional nine countries reported zero TB cases for 2012 and three countries had not reported data to WHO by July 2013.

Reporting of notification data disaggregated by age, 2012

Age disaggregation All case types disaggregated Only smear-positive cases disaggregated No age disaggregation No data reported

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13

figure 2.4

Estimated HIV prevalence in new TB cases, 2012

HIV prevalence in new TB cases, all ages (%) 0 4 5 19 20 49 ≥50 No data Not applicable

figure 2.5

Estimated TB incidence rates, 2012

Estimated new TB cases (all forms) per 100 000 population per year 0 9.9 10 19 20 49 50 124 125 299 300 499 ≥500 No data Not applicable

14

GLOBAL TUBERCULOSIS REPORT 2013

figure 2.6

Global trends in estimated rates of TB incidence, prevalence and mortality. Left: Global trends in estimated incidence rate including HIV-positive TB (green) and estimated incidence rate of HIV-positive TB (red). Centre and right: Trends in estimated TB prevalence and mortality rates 1990–2012 and forecast TB prevalence and mortality rates 2013–2015. The horizontal dashed lines represent the Stop TB Partnership targets of a 50% reduction in prevalence and mortality rates by 2015 compared with 1990. Shaded areas represent uncertainty bands. Mortality excludes TB deaths among HIV-positive people. Incidence 150 Rate per 100 000 population per year 300 Rate per 100 000 population per year 1990 1995 2000 2005 2010 2015 Prevalence 30 Mortality

Rate per 100 000 population

100

200

20

50

100

10

0 1990 1995 2000 2005 2010

0

0 1990 1995 2000 2005 2010 2015

100  000 population. Most countries in the Region of the Americas have rates below 50 per 100 000 population and this is the region with the lowest burden of TB on average. Most of the HBCs have rates of around 150‒300 cases per 100 000 population ( Table 2.2); HBCs with markedly lower rates are Brazil and China, while rates are above 500 per 100 000 population in Mozambique, South Africa and Zimbabwe. Other countries in the top ten worldwide in terms of incidence rates are mostly in Africa (Figure 2.3). In South figure 2.7

Africa and Swaziland, the best estimate is that at least 1 in every 100 people (1000 or more per 100  000 population) develops TB each year. Globally, the incidence rate was relatively stable from 1990 up to around 2001, and then started to fall (Figure 2.6), achieving the MDG target ahead of the 2015 deadline. Between 2011 and 2012, the rate of decline was 2%. This downward trend needs to be sustained to ensure that the MDG target is met in 2015. Incidence rates are also declin-

Estimated TB incidence rates by WHO region, 1990–2012. Regional trends in estimated TB incidence rates (green) and estimated incidence rates of HIV-positive TB (red). Shaded areas represent uncertainty bands. 400 300 200 Rate per 100 000 population per year 100 0 Europe Africa 80 60 40 20 0 South East Asia The Americas 200 150 100 50 0 Western Pacific Eastern Mediterranean

100 75

300

200 150

200 50 100 25 0 1990 1995 2000 2005 2012 0 1990 1995 2000 2005 2012 50 0 1990 1995 2000 2005 2012 100

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figure 2.8

Estimated TB incidence rates, 22 high-burden countries, 1990–2012. Trends in estimated TB incidence rates (green) and estimated incidence rates of HIV-positive TB (red). Shaded areas represent uncertainty bands. 300 200 200 100 100 0 50

Afghanistan

400 300

Bangladesha

150 100

Brazil

1000 750 500 250 0

Cambodia

200 150 100 50 0

China

0

0

500 400 300 200 100

DR Congo

800 600 400 200 0

Ethiopia

300 200 100

India

300 200 100

Indonesia

400 300 200 100 0

Kenya

Rate per 100 000 population per year

0

0

0

1250 1000 750 500 250 0

Mozambique

600 400 200

Myanmar

600 400 200

Nigeria

400 300 200 100 0

Pakistan

600 400 200

Philippines

0

0

0

200 150 100 50 0

Russian Federation

1250 1000 750 500 250 0

South Africa

250 200 150 100 50 0

Thailand

1250 1000 750 500 250 0

Uganda

300 200 100

UR Tanzania

0 1990 1995 2000 2005 2012 1990 1995 2000 2005 2012

1990 400 300 200 100 0 1990 1995 2000 2005 2012

1995

2000

2005

2012

Viet Nam

1250 1000 750 500 250 0

Zimbabwe

1990

1995

2000

2005

2012

a

Estimates of TB disease burden have not been approved by the national TB programme in Bangladesh and a joint reassessment will be undertaken following the completion of the prevalence survey planned for 2014.

ing in all of six WHO regions (Figure 2.7), fastest in the European Region (6.5% per year) and slowest in the Eastern Mediterranean and South-East Asia Regions (less than 1% per year and 2% per year, respectively). Incidence rates have been falling since the mid-1990s in the Eastern Mediterranean Region and since around 2000 in the South-East Asia Region; they peaked around 1997 in the European Region and around 2002 in the African region, and have been falling since 1990 in the Region of the Americas and the Western Pacific Region. The latest assessment for the 22 HBCs suggests that incidence rates are falling in most countries (Figure 2.8).

2.2 TB prevalence In countries with a relatively high burden of TB (around 100 cases per 100 000 population or more), the prevalence of bacteriologically-confirmed pulmonary TB can be directly measured in nationwide population-based surveys using sample sizes of around 50 000 people. Survey results can be 16 GLOBAL TUBERCULOSIS REPORT 2013

used to produce a national estimate of TB prevalence that includes all forms of TB. The cost of a survey usually ranges from US$ 1 to 4 million, and comprehensive theoretical and practical guidance on survey design, implementation, analysis and reporting of results is available.1 Repeat surveys conducted about every 10 years allow trends in disease burden to be assessed. HBCs that have completed repeat surveys in the last 10 years include Cambodia, China, the Philippines and Thailand, and repeat surveys are planned in Myanmar and Viet  Nam. Countries in which surveys have been implemented or are planned in the near future are shown in Figure 2.9. Between 2008 and 2017, an unprecedented number of national TB prevalence surveys have been or will be conducted (see also section 2.4). In low- and medium-burden countries, sample sizes and 1

TB prevalence surveys: a handbook. Geneva, World Health Organization, 2011 (WHO/HTM/TB/2010.17). Available at www.who.int/ tb/advisory_bodies/impact_measurement_taskforce/resources_ documents/thelimebook/

figure 2.9

Countries in which national population-based surveys of the prevalence of TB disease have been implemented using currently recommended screening and diagnostic methodsa since 1990 or are planned in the near future: status in July 2013

No national survey planned National survey plannedb National survey ongoing One national survey completed Repeat national survey planned ≥1 repeat national survey completed Not applicable a b

Screening methods include field chest X-ray; culture is used to confirm diagnosis. “National survey planned” means that a country has submitted at least a draft survey protocol and a budget to the WHO Global Task Force on TB Impact Measurement.

costs become prohibitively large. If survey data are not available, prevalence can be indirectly estimated as the product of incidence and the average duration of disease, but with considerable uncertainty (Annex 1). TB prevalence can be estimated only indirectly for most countries. There were an estimated 12 million prevalent cases (range, 11  million–13  million) of TB in 2012 ( Table 2.1), equivalent to 169 cases per 100 000 population ( Table 2.2). By 2012, the prevalence rate had fallen 37% globally since 1990. Current forecasts suggest that the Stop TB Partnership target of halving TB prevalence by 2015 compared with a baseline of 1990 will not be met worldwide (Figure 2.6). Regionally, prevalence rates are declining in all six WHO regions (Figure 2.10). The Region of the Americas halved the 1990 level of TB prevalence by around 2004, well in advance of the target year of 2015, and the best estimate suggests that the Western Pacific Region achieved the 50% reduction target in 2012. Reaching the 50% reduction target by 2015 appears feasible in the South-East Asia Region and also in the European Region with a relatively small acceleration in the current rate of progress. The target appears out of reach in the African and Eastern Mediterranean Regions.

2.3 TB mortality TB mortality among HIV-negative people can be directly measured using data from national VR systems, provided that these systems have high coverage and causes of death are accurately coded according to the latest revision of the International classification of diseases (ICD-10). Sample VR systems covering representative areas of the country (e.g. as in China) provide an interim solution. Mortality surveys can also be used to estimate deaths caused by TB. In 2012, most countries with a high burden of TB lacked national or sample VR systems and few had conducted mortality surveys. In the absence of VR systems or mortality surveys, TB mortality can be estimated as the product of TB incidence and the case fatality rate, or from ecological modelling based on mortality data from countries with VR systems. TB mortality among HIV-positive people is hard to measure even when VR systems are in place because deaths among HIV-positive people are coded as HIV deaths and contributory causes (such as TB) are often not reliably recorded. For this 2013 report, country-specific estimates of TB deaths among HIV-positive people were produced for the first time using the Spectrum software that has been used for HIV burden estimates for over a decade (Box 2.1). Until 2008, WHO estimates of TB mortality used VR data for only three countries. This was substantially improved to 89 countries in 2009; however most of the data were from countries in the European Region and the GLOBAL TUBERCULOSIS REPORT 2013 17

figure 2.10

Trends in estimated TB prevalence rates 1990–2012 and forecast TB prevalence rates 2013–2015, by WHO region. Shaded areas represent uncertainty bands. The horizontal dashed lines represent the Stop TB Partnership target of a 50% reduction in the prevalence rate by 2015 compared with 1990. The other dashed lines show projections up to 2015. Africa The Americas 400 100 300 200 200 Rate per 100 000 population 50 100 0 Europe 150 400 100 200 0 South East Asia 0 Western Pacific Eastern Mediterranean

400

50

200

100

0 1990 1995 2000 2005 2010 2015

0 1990 1995 2000 2005 2010 2015

0 1990 1995 2000 2005 2010 2015

Box 2.3

MDR-TB mortality – methods used to produce updated estimates As part of a 2010 global report on the MDR-TB epidemic and the global response, it was estimated that there were 150 000 deaths (range: 53 000–270 000) from MDR-TB in 2008.a This was the first time WHO published a global estimate of MDR-TB mortality and, given limitations in the available evidence, annual updates have not been attempted. In theory, the number of deaths from MDR-TB can be estimated as the product of total deaths from TB, the overall proportion of TB cases that have MDR-TB (5.7%), and the relative risk (RR) of dying among people with MDR-TB compared with those without MDR-TB. However, while estimates of total TB mortality and the prevalence of MDR-TB have been available for several years from VR data (i.e. for total TB deaths) and representative surveillance or survey data (for the proportion of cases with MDR-TB), an estimate of the RR was not. In 2013, WHO commissioned a systematic review of the RR of dying from MDR-TB compared with TB. Twenty-five studies that included data about mortality among patients enrolled on treatment for MDR-TB and TB (without MDR-TB), during and after treatment, were identified. These allowed calculation of a global estimate of the RR of dying from MDR-TB (2.36, range 1.67–3.05). The 25 studies had a broad geographical coverage and included countries with both high and low burdens of MDR-TB and HIV, but were insufficient to estimate region-specific RRs. Based on the results of the meta-analysis, it is estimated that globally in 2012, there were 170 000 deaths (range: 100 000– 240 000) from MDR-TB. a

Multidrug- and extensively drug-resistant TB (M/XDR-TB): 2010 global report on surveillance and response (WHO/HTM/TB/2010.3). Geneva, World Health Organization, 2010. Available at http://www.who.int/tb/publications/2010/978924599191/en/

18

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figure 2.11

Countries (in orange) for which TB mortality is estimated using measurements from vital registration (n=121) systems and/or mortality surveys (n=2, India and Viet Nam)

Region of the Americas, which accounted for less than 10% of the world’s TB cases. In 2011, the first uses of sample VR data from China and survey data from India enabled a further major improvement to estimates of TB mortality. For the current report, VR data of sufficient coverage and quality were available for 121 countries. Combined with survey data from India and Viet Nam, this means that estimates of TB mortality are based on direct measurements of TB mortality in 123 countries (shown in Figure 2.11). Collectively, these 123 countries account for 45% of the estimated number of TB deaths globally. The parts of the world where there are major gaps in the availability of VR data are the African Region and parts of the South-East Asia Region; in the latter, Indonesia is currently building a sample VR system. There were an estimated 1.3 million TB deaths in 2012 ( Table 2.1, Figure 2.2): 940 000 among HIV-negative people and 320  000 among HIV-positive people (TB deaths among HIV-positive people are classified as HIV deaths in ICD-10).1 These deaths included 410 000 among women and 74 000 among children (Box 2.2). There were approximately 170 000 deaths from MDR-TB (range, 102 000‒242 000): methods used to produce this new global estimate of MDRTB mortality are explained in Box 2.3. Approximately 75% of total TB deaths occurred in the African and South-East Asia Regions in 2012 (both including and excluding TB deaths among HIV-positive people). India and South Africa accounted for about one-third of global TB deaths. The number of TB deaths per 100 000 population averaged 13 globally in 2012 ( Table 2.2) and 17.6 when TB

deaths among HIV-positive people are included. There is considerable variation among countries (Figure 2.12), ranging from under 1 TB death per 100  000 population (examples include most countries in western Europe, Canada, the United States of America, Australia and New Zealand) to more than 40 deaths per 100  000 population in much of the African Region as well as three HBCs in Asia (Bangladesh, Cambodia and Myanmar). Globally, mortality rates (excluding deaths among HIV-positive people)2 have fallen by 45% since 1990; the current forecast suggests that the Stop TB Partnership target of a 50% reduction in TB mortality by 2015 compared with a baseline of 1990 will be achieved (Figure 2.6). Mortality rates are declining in all six WHO regions (Figure 2.13). The 2015 target has already been surpassed in the Region of the Americas (since 2004) and the Western Pacific Region (since 2002), and may have been reached in the Eastern Mediterranean Region. Among the other three regions, the South-East Asia Region appears best placed to achieve the target. Mortality rates appear to be falling in most of the 22 HBCs (Figure 2.14), although there is considerable uncertainty about the level of and trends in mortality in some countries, notably Mozambique, Nigeria, South Africa and Zimbabwe.

1

International statistical classification of diseases and related health problems, 10th revision (ICD-10), 2nd ed. Geneva, World Health Organization, 2007. 2 Trends in TB mortality rates are restricted to TB deaths among HIV-negative people, given that TB deaths among HIV-positive people are classified as HIV deaths in ICD-10.

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figure 2.12

Estimated TB mortality rates excluding TB deaths among HIV-positive people, 2012

Estimated TB deaths per 100 000 population 0 0.9 1 3.9 4 9.9 10 19 20 39 ≥40 No data Not applicable

figure 2.13

Trends in estimated TB mortality rates 1990–2012 and forecast TB mortality rates 2013–2015, by WHO region. Estimated TB mortality excludes TB deaths among HIV-positive people. Shaded areas represent uncertainty bands.a The horizontal dashed lines represent the Stop TB Partnership target of a 50% reduction in the mortality rate by 2015 compared with 1990. The other dashed lines show projections up to 2015. Africa 60 The Americas Eastern Mediterranean

6 40

40 Rate per 100 000 population per year

4 20 2

20

0 Europe 7.5

0 South East Asia

0 Western Pacific 20

60

40 5.0 20

15 10

2.5

5 0 1990 1995 2000 2005 2010 2015 1990 1995 2000 2005 2010 2015 0 1990 1995 2000 2005 2010 2015

0

a

The width of an uncertainty band narrows as the proportion of regional mortality estimated using vital registration data increases or the quality and completeness of the vital registration data improves.

20

GLOBAL TUBERCULOSIS REPORT 2013

figure 2.14

Trends in estimated TB mortality rates 1990–2012 and forecast TB mortality rates 2013–2015, 22 highburden countries. Estimated TB mortality excludes TB deaths among HIV-positive people. The horizontal dashed lines represent the Stop TB Partnership target of a 50% reduction in the mortality rate by 2015 compared with 1990. The other dashed lines show projections up to 2015.a Uncertainty is due to adjustments made to the mortality data from vital registration systems that were reported by countries (mortality data from vital registration systems are represented by the “x” symbol). Further explanation of methods is provided in Annex 1. Afghanistan 90 60 30 0 50 0 100

Bangladeshb 7.5 5.0 2.5 0

Brazil 300 200 100 0

Cambodia 20 15 10 5 0

China

DR Congo 100 50 0 60 40 20 0

Ethiopia 40 20 0

India 100 75 50 25 0

Indonesia 40 20 0

Kenya

Rate per 100 000 population per year

Mozambique 300 200 100 0 200 150 100 50 0

Myanmar 150

Nigeria

Pakistan 60 100 40 20 0

Philippines

100 50 0 50 0

Russian Federation 20 15 10 5 0 50 0 150 100

South Africa 40 20 0

Thailand 200 100 0 1990 1995 2000 2005 2010 2015

Uganda 60 40 20 0 1990 1995 2000 2005 2010 2015

UR Tanzania

Viet Nam 60 40 20 0 1990 1995 2000 2005 2010 2015

Zimbabwe 100

1990 1995 2000 2005 2010 2015

a

50 0 1990 1995 2000 2005 2010 2015

The width of an uncertainty band narrows as the quality and completeness of vital registration data improves. b Estimates of TB disease burden have not been approved by the national TB programme in Bangladesh and a joint reassessment will be undertaken following the completion of the prevalence survey planned for 2014.

2.4 Strengthening measurement of the burden of disease caused by TB: the WHO Global Task Force on TB Impact Measurement The estimates of TB incidence, prevalence and mortality and their trend presented in sections 2.1–2.3 are based on the best available data and analytical methods. Nonetheless, there remains considerable scope to improve measurement of the level of and trends in TB disease burden. This final section of the chapter describes the latest status of efforts to improve measurement of the burden of disease caused by TB, under the umbrella of the WHO Global Task Force on TB Impact Measurement. This task force was established in 2006 and includes representatives from leading technical and financial partners and countries with a high burden of TB.1 At its second meeting in December 2007, the Global Task

Force on TB Impact Measurement defined three strategic areas of work:2  strengthening surveillance towards the ultimate goal of direct measurement of incidence and mortality from notification and VR systems, respectively; 1

Many countries with a high burden of TB are engaged in the work of the Task Force. Partners that are actively participating in the work of the Task Force include the Centers for Disease Control and Prevention in the USA, the European Centre for Disease Prevention and Control, the Global Fund, Public Health England, the KNCV Tuberculosis Foundation, the London School of Hygiene and Tropical Medicine in the UK, the Research Institute for Tuberculosis in Japan, the Union and the United States Agency for International Development (USAID). 2 TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper no. 2; WHO/HTM/TB/2009.416). Available at www.who.int/tb/ publications/2009/impactmeasurementpolicy/

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21

 conducting surveys of the prevalence of TB disease in a set of global focus countries that meet epidemiological and other relevant criteria; and  periodic review and updating of the methods used to translate surveillance and survey data into estimates of TB incidence, prevalence and mortality. In 2008 and 2009, methods were thoroughly reviewed and updated by an expert group convened by the task force. Updates were discussed and endorsed by the full task force in March 2010. Current methods are described in detail in Annex 1, and an updated review is planned in 2014 (Box 2.1). The following sections focus on the other two strategic areas of work: strengthened surveillance and national TB prevalence surveys. Further details are available on the task force’s web site.1

Inventory studies to measure or estimate TB underreporting One of the standards in the TB surveillance checklist is that all diagnosed cases of TB are reported to the national surveillance system. The two benchmarks that must be satisfied are that TB reporting is a legal requirement, and that ≥90% of TB cases are reported to national health authorities, as determined by a national-level investigation such as an inventory study. To date, few countries have implemented an inventory study but as the number doing so increases, estimates of the level of and trend in TB incidence will improve. Even when underreporting is considerable and notification data are not a good proxy for TB incidence, results from inventory studies can be used to quantify the gap and obtain more precise estimates of disease burden and provide valuable information about where efforts to collaborate with public and private sector providers are needed (see also Chapter 3, section 3.2.1). In 2012, the Global Task Force on TB Impact Measurement completed a guide on how to design and implement an inventory study, and how to analyse and report results.2 In the past 10 years, inventory studies combined with capture–recapture analysis have been implemented in the Netherlands, the UK, French Guiana, Egypt, Iraq, Pakistan and Yemen. Results from the study in Iraq are summarized in Box 2.6.

2.4.1 Strengthening surveillance Reasons for uncertainty in current estimates of TB incidence include use of expert opinion about both the number of cases that are diagnosed but not reported to national surveillance systems and the number of cases that are not diagnosed at all (section 2.1). Major challenges in estimating TB mortality include the lack of VR systems of sufficient coverage and quality in many countries, notably in Africa and parts of Asia (Figure 2.11). The long-term goal of directly measuring the level of and trends in TB disease burden from routine surveillance data, using notification data to measure TB incidence and VR data to measure TB mortality, requires strengthened surveillance in many countries. Countries for which more robust estimates of mortality were available in 2012 are shown in Figure 2.11.

Electronic recording and reporting of data Several of the standards in the TB surveillance checklist are about data quality. In all of the regional and country workshops held between 2008 and 2013, it was evident that it is much easier to assess the quality of TB surveillance data in countries with case-based electronic recording and reporting systems. Besides facilitating assessment of data quality, electronic recording and reporting systems have other major advantages compared to systems based solely on paper-based recording and reporting. These include:  Better programme and resource management, by encouraging staff to use and act upon live data. This may help to prevent defaulting from treatment and assist with management of drug supplies (including avoidance of stock-outs).  Improved surveillance by making it easier for facilities not traditionally linked to the NTP, such as hospitals, prisons and the private sector, to report TB cases, and by reducing the burden of compiling and submitting data through paper-based quarterly reports.  Analysis and use of data is facilitated, since data can be readily imported into statistical packages. Results are then available to decision-makers more quickly and it is possible to detect outbreaks promptly. 1

TB surveillance checklist of standards and benchmarks Strengthening surveillance to move towards the goal of direct measurement of TB incidence and mortality requires a clear understanding of what a ‘model’ surveillance system should look like and a method for assessing the current performance of TB surveillance. Following considerable work in 2011 and 2012, a TB surveillance checklist that defines the standards and associated benchmarks that need to be met for a country’s notification and VR data to be used as a direct measure of TB incidence and mortality has been developed (Box 2.4). Use of the checklist began in January 2013 and it is being applied in a growing number of countries (Figure 2.15) as the basis for identifying what standards are already met and the investments required to close remaining gaps. This work is being undertaken in close collaboration with the Global Fund so that use of the checklist is integrated into the fund’s grant processes and findings can inform investments by the fund as well as national governments and other partners (Box 2.5). With more than 100 lowand middle-income countries receiving TB grants from the Global Fund, this approach has great potential to make a real difference to TB surveillance worldwide. An initial list of 25 priority countries has been defined.

www.who.int/tb/advisory_bodies/impact_measurement_ taskforce 2 Assessing tuberculosis underreporting through inventory studies. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2012.12). Available at: www.who.int/tb/publications/inventory_studies/en/ index.html

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Box 2.4

The TB surveillance checklist of standards and benchmarks A major goal of TB surveillance is to provide an accurate measure of the number of new TB cases and TB deaths that occur each year, and to be able to assess trends over time. In some countries, TB surveillance already meets the standards necessary to do this, but in others there are important gaps. For example, TB cases that are diagnosed in the private sector are not reported in many settings, and in many low- and middle-income countries some people with TB may not easily access health care and therefore not be diagnosed at all. Furthermore, a large number of countries lack vital registration systems with the geographical coverage and quality required to accurately measure deaths caused by TB (section 2.3). The Checklist of standards and benchmarks for TB surveillance and vital registration systems was developed with the following objectives: "" To assess a national surveillance system’s ability to accurately measure TB cases and deaths. "" To identify TB surveillance gaps in national surveillance systems that need to be addressed. The outcomes of the checklist can be used to identify countries with surveillance systems that already provide an accurate measure of the number of TB cases and deaths that occur each year, and to define the actions necessary to strengthen surveillance in countries in which gaps are identified.a Countries in the former category can be certified as having surveillance data that provide a direct measure of TB incidence and/or mortality. The checklist was developed by a team of experts in disease surveillance in conjunction with expert advice from meetings organized by WHO in September 2011 and May 2012. The checklist underwent two rounds of field-testing in eleven countries: Brazil, China, Egypt, Estonia, Japan, Kenya, the Netherlands, Thailand, Uganda, the United Kingdom and the United States of America. The checklist is ten pages long and has two parts. Part A consists of eighteen questions that are used to characterise the national TB surveillance system; these provide the background for part B, which consists of thirteen standards and their associated benchmarks. The standards are general statements about the characteristics that define a high-performance TB surveillance system; nine standards are related to the measurement of TB cases and one is related to the measurement of TB deaths. There are three supplementary standards that can be used to assess whether a country’s surveillance system provides a direct measure of the number of drug-resistant TB cases, HIV-positive TB cases, and TB cases among children. For each of the thirteen standards, benchmarks define (in quantitative terms wherever possible) the level of performance considered sufficient to meet the respective standard. An accompanying user guide explains the rationale for each standard and associated benchmark(s), and the methods that should be used to assess whether the benchmarks and hence the standard are met. Illustrative examples are also provided in the user guide. Based on a completed assessment using the checklist, countries can identify key actions needed to address identified gaps in notification and vital registration systems. It is anticipated that an assessment of TB surveillance using the checklist would take place every three to five years, but could also be done more frequently. Following the 2012 recommendations of the Global Fund’s Technical Evaluation Reference Group and a collaborative agreement between the fund and WHO, assessments of TB surveillance using the checklist are increasingly being integrated within the fund’s grant mechanisms. As such, assessments with the checklist should be timed to coincide with programme reviews, Global Fund grant renewals and the development of the concept notes required to access funding in the fund’s new funding model (NFM) launched in 2013. Results can then be used to develop or update monitoring and evaluation investment plans that can be supported through grants from the Global Fund as well as by national budgets and by other partners. This collaborative effort with the Global Fund has great potential to help strengthen TB surveillance in more than a hundred countries receiving grants worldwide. Assessments in 15 highburden and high-impact countries are being prioritized in 2013 and 2014; by August 2013, a total of eleven countries including eight of the fund’s high-burden or high-impact countries had completed the assessment (Figure 2.15). The checklist and user guide are available on the website of the WHO Global Task Force on TB Impact Measurement: http://www.who.int/tb/advisory_bodies/ impact_measurement_taskforce/en/ a

The checklist is not intended to assess a system’s ability to fulfil other programmatic requirements, e.g. patient care, delivery of laboratory results, or drug management.

 Higher quality data, since automated data quality checks can be used and duplicate or misclassified notifications can be identified and removed (which is very difficult or impossible to do nationally with paper-based systems). It is also easier to introduce new data items.  Identification of clusters of cases in space and time, including clusters of drug-resistant cases, thus allowing early investigation and containment of epidemics. Countries that have national electronic case-based databases of TB patients are shown in Figure 2.16. A recent

example of the implementation of a case-based electronic recording and reporting system, in Kenya, is described in Box 2.7. Recent guidance on electronic recording and reporting for TB care and control, developed by WHO and partners in 2011, is available on the task force’s website.1

1

Electronic recording and reporting for TB care and control. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2011.22). Available at www.who.int/tb/publications/electronic_recording_ reporting

GLOBAL TUBERCULOSIS REPORT 2013

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Box 2.5

The TB surveillance checklist in Indonesia: from implementation to resource mobilization A national assessment of the TB surveillance system in Indonesia using the Checklist of standards and benchmarks for TB surveillance and vital registration systems (see Box 2.4) was undertaken in February 2013, linked to a national programme review. A thorough analysis of all available national, provincial and district level time series of TB notification and other available surveillance data was completed. A desk review of NTP manuals, guidelines, policy and training documents, annual reports, reporting forms and registers was conducted. Other information was collected through interviews with NTP staff, partners and other stakeholders. The TB surveillance system is based on quarterly reporting of notified cases from health facilities, to districts, to provinces and finally to the national level. It is currently transitioning to a web- and case-based electronic recording and reporting system. TB case definitions were consistent with international guidelines. There were 483 out of 497 districts in the country that submitted all quarterly reports to the national level in 2011. The system produced externally but not internally consistent data. Since TB reporting is not a legal requirement, not all TB cases were reported to the NTP, but the level of underreporting of cases from the private to the public sector has not been measured nationally. There have been steady improvements in access to health care, but it is still not at a level sufficient to ensure that all TB cases have access to diagnosis and care. A nationally representative VR system with standard coding of causes of death is being developed. Only provincial level drug resistance surveys have been conducted so far, and while HIV testing of TB cases was improving the coverage remains low. Finally, childhood TB was diagnosed in limited settings. Activities to address the gaps that were identified from the implementation of the checklist were defined (see Table B2.7.1). One of the top priorities is maintenance of the sample VR system, which costs US$ $0.5–1 per capita in the sampled areas (equivalent to about US$ 2.5–5 million per year for the population of 5 million to be covered). For the other activities in Table B2.7.1, the total budget requirement was estimated to be US$ 1 million, among which one top priority (identified in the key recommendations arising from the 2013 programme review) is implementation of a mandatory notification policy. Through continuous consultations between the NTP, WHO and the Global Fund, the financing required for the investment plan was identified and secured. This example shows how the checklist can be used to conduct a standardized assessment of TB surveillance, highlight progress achieved as well as remaining gaps to be addressed, and to secure funding for an investment plan to close the gaps with support from the Global Fund. Table B2.7.1

Investment plan for strengthening surveillance in Indonesia based on gaps identified through the implementation of the Checklist of standards and benchmarks for TB surveillance and vital registration systems (total budget US$ 1 million excluding VR system funded separately) Activity n Vital registration (VR): maintaining and scaling up the nationallyrepresentative sample VR system n Inventory study to measure the level of underreporting n Capacity building for data management and statistical analysis – through attending courses and extra staffing at the central level n Implementation of the Service Availability and Readiness Assessment Tool and health facility data quality assessment n Assessment of the Integrated Tuberculosis Information System (SITT) Phase 2 in 2014 n Implementing mandatory notification policy n Analysis of available mortality data n Drug resistance survey or sentinel surveillance n Nationally representative survey of HIV prevalence among TB patients n Corrective actions required to compile all the reports from Papua

2.4.2 National surveys of the prevalence of TB disease Before 2007, few countries had implemented nationwide prevalence surveys. In the 1990s, national surveys were confined to China, Myanmar, the Philippines and the Republic of Korea. Before 2009 and with the exception of Eritrea in 2005, the last national surveys in the African Region were undertaken between 1957 and 1961. From 2002 to 2008, there was typically one survey per year. In 2007, WHO’s Global Task Force on TB Impact Measurement identified 53 countries that met epidemiological and other criteria for implementing a survey. A set of 22 global focus countries were selected to receive particular support in the years leading up to 2015. The African countries were: Ethiopia, Ghana, Kenya, Malawi, Mali, Mozambique, Nigeria, Rwanda, Sierra Leone, South Africa, Uganda,

the United Republic of Tanzania and Zambia. Countries in Asia were: Bangladesh, Cambodia, China, Indonesia, Myanmar, Pakistan, the Philippines, Thailand and Viet Nam. Since early 2008, substantial efforts to support countries to design, implement, analyse and report on surveys have been made. Examples include development of updated guidance,1 coordination of technical assistance, expert reviews of protocols, organization of study tours and mid-term survey reviews, and global and regional workshops to support survey design and implementation and to share results and lessons learned among countries. As part of these efforts, 1

TB prevalence surveys: a handbook. Geneva, World Health Organization, 2011 (WHO/HTM/TB/2010.17). Available at www.who.int/ tb/advisory_bodies/impact_measurement_taskforce/resources_ documents/thelimebook/

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GLOBAL TUBERCULOSIS REPORT 2013

figure 2.15

Countries (in orange) where the TB surveillance checklist of standards and benchmarks has been used: status in August 2013

Box 2.6

Inventory studies to estimate TB underreporting: an example from Iraq Inventory studies compare the number of TB cases meeting standard case definitions in all or in a sample of public and private health facilities with the records of TB cases notified to local and national authorities. This enables the level of underreporting of diagnosed cases to be quantified. In certain circumstances, the results from inventory studies can be combined with a type of modelling called capture–recapture analysis to estimate TB incidence. A WHO guide on the design and implementation of inventory studies, and analysis and reporting of results, was published in 2013. The results from the survey in Iraq,a which was completed in 2011, are illustrated below. The number of TB cases that were detected by three types of health service providers was studied during a three-month period in eight randomly selected governorates (out of a total of 18). The total number of detected cases was 1980. Cases that were detected but not reported to the NTP accounted for 16% of total detected cases i.e. the level of underreporting was 16%. Capture–recapture modelling was used to estimate that an additional 473 cases (95% confidence interval: 394–565) had not been detected by any of the three types of health providers. These results were used to estimate that there were approximately 14 500 incident cases of TB in Iraq in 2011 (a downward revision compared with previous estimates) and that about 60% of cases were being detected (an upward revision from the previous best estimate of 48%). The value of study results went beyond updates to estimates of TB incidence. Examples include: Figure B2.6.1

Results from the 2011 inventory study in Iraq NTP (n=1673) 988 416 25 244 (N=1980) 99 9 Public (n=377) 199 Private (n=649)

"" Updated estimates were crucial for the development of a sound national strategic plan and to assess progress towards the 2015 MDG target. "" The national strategic plan includes interventions designed to address the causes of underreporting that were identified during the study. "" The mapping of all health facilities delivering care to chest-symptomatic patients in study areas (that covered 50% of the country) provided a foundation for sustained engagement of all care providers through PPM initiatives. a

Huseynova S et al. Estimating tuberculosis burden and reporting in resource-limited countries: a capture-recapture study in Iraq. International Journal of Tuberculosis and Lung Disease. 2013;17(4):462–7.

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figure 2.16

Availability of national electronic case-based databases of TB patients, 2012

All TB patients MDR TB patients only None No data Not applicable

figure 2.17

Global progress in implementing national surveys of the prevalence of TB disease, actual (2002–2013) and expected (2014–2017) 9 8 7 Asia – GFC    Africa – GFC    Non – GFC Kenya Mozambique South Africa

Number of surveys

6 5 4 3 2 1 0 Cambodia Malaysia Indonesia Eritrea

Global focus countries (GFC) selected by WHO Global Task Force on TB Impact Measurement Ethiopia Cambodia Philippines Thailand Viet Nam Bangladesh Myanmar China Pakistan Lao PDR

Uganda Nigeria Rwanda UR Tanzania Thailand Gambia Ghana Malawi Zambia Indonesia Sudan Bangladesh DPR Korea Mongolia Nepal Zimbabwe Myanmar Philippines Viet Nam

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014– 2015

2016– 2017

the concept of Asia–Asia, Asia–Africa and Africa–Africa (‘AA’) collaboration has been strongly promoted. Following six years of substantial effort at country, regional and global levels, unprecedented progress has been achieved (Figure 2.17). If surveys are implemented according to schedule, more than 20 surveys will be implemented between 2011 and 2015. Five national TB prevalence surveys were implemented in 2012 (Gambia, Nigeria, Rwanda, the United Republic of Tanzania and Thailand) and a further five will start or be completed in 2013 (Ghana, Indonesia, Malawi, Sudan and Zambia). These surveys provide an unbiased estimation of disease burden, often for the first time, and will be used to update estimates

of disease burden once results are finalized (Box 2.1). Surveys are also providing a rich source of data to inform programme policy and strategy. Although results remain provisional pending finalization of analyses in late 2013 (Box 2.1), an excellent recent example is provided by the 2012 survey in Nigeria (Box 2.8). For other recent surveys, some country-specific reports are already publicly available (for example, from China, Cambodia, Ethiopia and Myanmar) and others are in the pipeline. Papers for peer-reviewed journals are also in preparation, from these and other recent surveys. WHO, together with countries and technical partners, started preparing or planning global and regional synthe-

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Box 2.7

Implementation of an innovative electronic surveillance and management system in Kenya The NTP in Kenya has rolled out an innovative electronic system to support surveillance and management, called TIBU (which means cure in Swahili). In addition to running electronic versions of its standard district TB registers, the TIBU system makes use of the country’s extensive mobile communications network and widespread use of mobile phones to make payments to MDR-TB patients that help to support their treatment through the popular M-Pesa mobile payment system. The system will also be used to manage drug supplies and laboratory data and consumables. At TIBU’s core is a national case-based database that stores details about each individual patient episode of TB (including cases of MDR-TB). Users access the system either through a web browser or by using an Android ‘app’. The NTP has given each District TB and Leprosy Coordinator (DTLC) a tablet computer that runs the Android operating system and is fitted with a SIM card to connect to the internet through mobile telephone networks. DTLCs can access the system during their regular visits to all facilities providing TB diagnostic and treatment services within their district and enter TB patient details into the TIBU app during their visits to these facilities. Data are transmitted directly to the national database via the mobile network. Data remain stored on the tablet if no connection is available at a facility and are subsequently transmitted to the national database as soon as a connection is available. TIBU automatically generates various reports, including standard quarterly reports, charts and maps for all levels of the administrative chain. The NTP and developers work closely with other parts of the Ministry of Health to ensure that TIBU complies with national standards, such that it can communicate with the ministry’s other health information systems.a TIBU uses Kenya’s national facility coding scheme (http://www.ehealth.or.ke/facilities/ facilitytypes.aspx) and therefore the developers were able to build a seamless link to the Kenya Health Information Systemb that provides district, provincial and national health officials with indicators for multiple health areas, including TB. This allows standard TB indicators to be automatically updated every quarter in the ministry’s system. TIBU has been developed in phases. Development was initiated in 2007 and the original intention was to run the system on personal digital assistants (PDAs). However, problems with initial attempts to implement the system combined with the rapid rise, availability and falling costs of Android-based mobile devices, as well as the widespread adoption of mobile phones, led to a decision to switch to the development of an Android app for use on smartphones and tablet computers. Plans for future phases include extending coverage beyond TB and leprosy to patients with asthma and other lung diseases, integration with the laboratory management system and eventually, if resources allow, roll out of tablets to over 4000 health care facilities where TB diagnostic and treatment services are offered. a

In May 2013 the World Health Assembly adopted resolution WHA66.24 on promoting such standardization and interoperability of health information systems (http://apps.who.int/gb/ebwha/pdf_files/WHA66/A66_R24-en.pdf).  b Based on the open source DHIS2 platform http://www.dhis2.org/

Box 2.8

The 2012 national TB prevalence survey in Nigeria: programmatic implications Implementation of the first-ever national TB prevalence survey in Nigeria began in February 2012 and field activities (covering 70 geographic clusters) were completed in October 2012. Nigeria became the second African country to successfully complete a national survey according to current WHO guidelines, following Ethiopia in 2011. A total of 43 439 people (aged ≥15) participated in the study. Survey results included that 75% of previously undetected cases found during the survey had sputum smear-positive TB and classic TB symptoms that met national screening criteria (this proportion was higher than in any other survey implemented since 2002). Comparison of the number of prevalent cases of sputum-smear positive TB with notification data for the same age group showed a prevalence:notification ratio of 5 (also higher than in any other survey implemented since 2002). The survey also illustrated that the burden of TB was geographically uneven, ranging from very low to extremely high levels among survey clusters. An important conclusion already drawn from the survey results is that a top priority is to expand access to and improve the quality of basic TB diagnostic and treatment services. If high-quality DOTS services were readily available, it would be expected that both the percentage of prevalent cases with typical TB symptoms and the prevalence:notification ratio would be much lower. A second conclusion is that specific focus is needed on geographic ‘hotspots’ where the disease burden is highest.

ses of the main results and lessons learned from national TB prevalence surveys in 2012. A paper that summarizes the results and lessons learned from surveys conducted 1990–2012 in Asia is nearing completion and a similar paper about recent surveys in Africa is planned. An overall

synthesis of the main implications of results from recent prevalence surveys implemented in Asia and Africa for post-2015 global TB policy and strategy is also in the pipeline. These global and regional summaries will be widely disseminated once available, starting in 2014.

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Chapter 3

TB case notifications and treatment outcomes Key facts and messages ■■ In 2012, 6.1 million cases of TB were notified by NTPs and reported to WHO: 5.7 million were individuals newly diagnosed in 2012 and 0.4 million were previously diagnosed TB patients whose treatment regimen was changed. India and China accounted for 39% of notified cases of TB worldwide in 2012, African countries for 23% and the 22 HBCs for 82%. ■■ In 2011, the treatment success rate was 87% among all new TB cases and 87% among new cases of sputum smear-positive pulmonary TB (the most infectious cases). Improvement in treatment outcomes is needed in the European Region, where the treatment success rate in 2011 was 72% and 65% for new cases and new smear-positive cases respectively. ■■ The provision of diagnosis and treatment according to the DOTS/Stop TB Strategy has resulted in major achievements in TB care and control. Between 1995 and 2012, 56 million people were successfully treated for TB in countries that had adopted the DOTS/Stop TB Strategy, saving 22 million lives. ■■ Notifications of TB cases have stabilized in recent years, and in 2012 represented 66% (range, 64–69%) of estimated incident cases. The gap between notifications and incident cases can be explained by a mixture of underreporting of diagnosed TB cases (for example, failure to notify cases diagnosed in the private sector) and underdiagnosis due to poor access to health care and/or failure to detect cases when people visit health care facilities. Major efforts are needed to ensure that all cases are detected, notified to national surveillance systems and treated according to international standards. ■■ In 2012, most notified TB patients were 15–44 years of age. Children (aged <15 years) accounted for 6% of notified cases. The male:female ratio was 1.7 globally, ranging from 1.0 to 2.1 among the six WHO regions.

Routine recording and reporting of the numbers of TB cases diagnosed and treated by NTPs and monitoring of treatment outcomes was one of the five components of the global TB strategy (DOTS) launched by WHO in the mid-1990s and it remains a core element of its successor, the Stop TB Strategy (Chapter 1). With the standard definitions of cases and treatment outcomes recommended by WHO and associated recording and reporting framework as a foundation, global monitoring of trends in case notifications and treatment outcomes has been possible since 1995. The number of people diagnosed and treated for TB and associated treatment outcomes is routinely monitored by NTPs in almost all countries, which in turn report these data to WHO in annual rounds of global TB data collection (Chapter 1). This chapter has four parts. Section 3.1 summarizes the total number of people diagnosed with TB and notified by NTPs in 2012, including disaggregation by case type, age and sex. The share of notifications accounted for by the prison sector in the European Region and the high case notification rates among the prison population are also highlighted. Section 3.2 presents and discusses the contribution to total case notifications of public–public and public–private mix (PPM) initiatives in 29 countries and of community-based care in 13 countries. Section 3.3 presents trends in notifications between 1990 and 2012 and compares these with trends in estimated TB incidence. Estimates of the ratio of notified:incident cases (an indicator known as the case detection rate or CDR) are provided for selected years. Section 3.4 describes the latest data on treatment outcomes (for cases registered for treatment in 2011) as well as treatment outcomes achieved in each year since 1995.

3.1 Case notifications in 2012 by type of disease, age and sex The definitions of TB cases recommended by WHO until the end of 2012, and that were used in the 2013 round of global TB data collection, are shown in Box 3.1. Although not used in the global TB report this year, it should be highlighted that after a two-year consultation process, WHO issued updated guidance on definitions of cases and treatment outcomes and an associated reporting framework in March 2013.1 These updates were necessary to accommodate 1

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/HTM/TB/2013.2). Geneva, World Health Organization, 2013. (Available at www.who.int/iris/bitstream/10665/79199/1/ 9789241505345_eng.pdf).

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Table 3.1

Case notifications, 2012 NEW CASES PULMONARY CASES LABORATORY CONFIRMED PERCENTAGE OF PULMONARY CASES LABORATORY CONFIRMED RETREATMENT CASES

TOTAL NOTIFIED

SMEAR-POSITIVE

SMEAR-NEGATIVE

SMEAR NOT DONE

EXTRAPULMONARY

CASE TYPE UNKNOWN

RELAPSE

RETREATMENT EXCL. RELAPSE

NEW AND RELAPSE a

Afghanistan Bangladesh Brazil Cambodia China DR Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global

29 578 173 619 82 755 40 258 900 678 112 499 147 592 1 467 585 331 424 99 149 50 827 148 149 97 853 273 097 235 608 149 921 349 582 61 208 47 211 63 892 103 906 38 720 5 005 111 1 412 639 232 695 430 789 337 167 2 331 455 1 345 466 6 090 211

13 319 106 790 40 152 14 838 316 332 71 124 47 236 629 589 202 319 36 937 20 951 42 909 52 901 110 545 93 586 27 467 119 898 30 998 24 916 25 138 51 033 12 163 2 091 141 600 355 122 606 173 963 78 336 1 065 852 500 171 2 541 283

4 740 24 451 12 178 8 509 533 977 13 214 47 340 317 616 104 866 28 574 19 797 73 042 32 972 109 425 115 263 59 019 63 210 17 537 11 487 21 393 21 706 14 354 1 654 670 345 947 35 606 135 346 118 614 586 455 691 714 1 913 682

2 665 0 8 592 0 2 073 2 073

6 906 30 549 10 297 15 290 6 479 20 669 46 854 234 029 15 697

702 0 11 0 0 0 2 139 0 0 0 0 0 0 0 0 0 3 210 0 6 062 977 1 669 702 30 3 004 3 287 9 669

13 319 106 790 42 489 14 838 316 332 71 124 47 236 637 273 202 319 36 937 20 951 42 909 52 901 110 545 93 586 41 123 180 857 30 998b 24 916 25 138 51 033 12 163 2 144 779 656 272 132 070 175 025 112 577 1 027 902 502 652 2 606 498

62 81 70 64 37 84 49 67 66 50 51 37 62 50 45 47 71 64 65 54 67 41 56 63 76 55 55 62 42 57

1 049 3 065 3 867 446 31 784 3 977 1 820 106 463 5 942 3 419 1 451 4 558 2 513 6 095 4 080 8 211 26 668 1 887 1 334 1 052 7 259 1 369 228 309 60 497 9 949 11 208 25 185 131 245 45 277 283 361

197 4 936 7 633 73 10 033 3 515 2 269 177 749 2 600 6 162 3 086 6 979 5 035 5 622 19 409 44 168 25 918 904 2 548 1 714 1 794 2 960 335 304 67 770 13 862 10 020 67 662 201 335 34 740 395 389

29 381 168 683 75 122 40 185 890 645 108 984 145 323 1 289 836 328 824 92 987 47 741 141 170 92 818 267 475 216 199 105 753 323 664 60 304 44 663 62 178 102 112 35 760 4 669 807 1 344 869 218 833 420 769 269 505 2 130 120 1 310 726 5 694 822

8 123 0 0 0 1 039 71 421 1 783 0 2 962 100 731 100 537 14 564 8 523 6 257 0 9 751 139 632

15 934 5 542 20 661 4 432 41 410 3 270 10 017 42 467 8 852 5 143 14 595 18 904 4 912 582 909 234 539 34 400 90 943 39 029 338 303 59 294 796 508

Blank cells indicate data not reported. a NEW AND RELAPSE includes cases for which the treatment history is unknown. b LABORATORY CONFIRMED data for Thailand refer to smear-positive cases only. Data on cases that were laboratory confirmed using other methods were not reported.

diagnosis using Xpert MTB/RIF and other WHO-endorsed molecular tests (Chapter 5), as well as offering an opportunity to improve aspects of the existing (2006) framework, such as inclusion of more comprehensive reporting of TB cases among children. The updated definitions, which will be used in WHO’s 2014 round of global TB data collection, are summarized in Box 3.2. In 2012, 6.1 million people with TB were notified to NTPs and reported to WHO. Of these, 5.7 million had a new episode of TB (shown as the total of new and relapse cases in Table 3.1). Of these 5.7 million cases, 5.4 million had TB for the first time and 0.3 million were people who had a recurrent episode of TB after being previously cured of the disease. Besides a small number of cases whose history of

treatment was not recorded, the remaining 0.4 million had already been diagnosed with TB but their treatment was changed to a retreatment regimen. Among people who were diagnosed with TB for the first time (new cases), 2.5 million had sputum smear-positive pulmonary TB, 1.9 million had sputum smear-negative pulmonary TB, and 0.8 million had extrapulmonary TB; the remaining cases did not have a sputum smear done or their case type was unknown ( Table 3.1). India and China accounted for 39% of the 5.7 million new and relapse cases of TB that were notified in 2012 (23% and 16%, respectively); the South-East Asia and Western Pacific Regions in which these countries are respectively located together accounted for 60% of such cases globally. African countries GLOBAL TUBERCULOSIS REPORT 2013 29

Box 3.1

WHO definitions of TB cases used until the end of 2012 (and in this global TB report)a Definite case of TB  A patient with Mycobacterium tuberculosis complex identified from a clinical specimen, either by culture or by a newer method such as molecular line probe assay (LPA). In countries lacking laboratory capacity to routinely identify M. tuberculosis, a pulmonary case with one or more initial sputum specimens positive for acid-fast bacilli (AFB) is also considered to be a ‘definite’ case, provided that there is functional external quality assurance with blind rechecking. Case of TB  A definite case of TB (defined above) or one in which a health worker (clinician or other medical practitioner) has diagnosed TB and decided to treat the patient with a full course of anti-TB treatment. Case of pulmonary TB  A patient with TB disease involving the lung parenchyma. Smear-positive pulmonary case of TB  A patient with one or more initial sputum smear examinations (direct smear microscopy) AFB-positive; or one sputum examination AFBpositive plus radiographic abnormalities consistent with active pulmonary TB as determined by a clinician. Smear-positive cases are the most infectious and thus of the highest priority from a public health perspective. Smear-negative pulmonary case of TB  A patient with pulmonary TB who does not meet the above criteria for smearpositive disease. Diagnostic criteria should include: at least two AFB-negative sputum smear examinations; radiographic abnormalities consistent with active pulmonary TB; no response to a course of broad-spectrum antibiotics (except in a patient for whom there is laboratory confirmation or strong clinical evidence of HIV infection); and a decision by a clinician to treat with a full course of anti-TB chemotherapy. A patient with positive culture but negative AFB sputum examinations is also a smear-negative case of pulmonary TB. Extrapulmonary case of TB  A patient with TB of organs other than the lungs (e.g. pleura, lymph nodes, abdomen, genitourinary tract, skin, joints and bones, meninges). Diagnosis should be based on one culture-positive specimen, or histological or strong clinical evidence consistent with active extrapulmonary disease, followed by a decision by a clinician to treat with a full course of anti-TB chemotherapy. A patient in whom both pulmonary and extrapulmonary TB has been diagnosed should be classified as a pulmonary case. New case of TB  A patient who has never had treatment for TB or who has taken anti-TB drugs for less than one month. Retreatment case of TB  There are three types of retreatment case: (i) a patient previously treated for TB who is started on a retreatment regimen after previous treatment has failed (treatment after failure); (ii) a patient previously treated for TB who returns to treatment having previously defaulted; and (iii) a patient who was previously declared cured or treatment completed and is diagnosed with bacteriologically-positive (sputum smear or culture) TB (relapse). Case of multidrug-resistant TB (MDR-TB)  TB that is resistant to two first-line drugs: isoniazid and rifampicin. For most patients diagnosed with MDR-TB, WHO recommends treatment for 20 months with a regimen that includes secondline anti-TB drugs. a See

Treatment of tuberculosis guidelines, 4th ed. Geneva, World Health Organization, 2010 (WHO/HTM/STB/2009.420). Available at http://whqlibdoc. who.int/publications/2010/9789241547833_eng.pdf

accounted for 24% of new and relapse TB cases globally (one quarter of these cases were from one country – South Africa). The WHO Eastern Mediterranean and European Regions and the Region of the Americas accounted for 16% of new and relapse TB cases notified in 2012 (7%, 5% and 4%, respectively); combined, the 22 HBCs accounted for 82% of such cases. Among the 22 HBCs, the percentage of new pulmonary cases that were bacteriologically confirmed was highest in Bangladesh (81%) and the Democratic Republic of the Congo (84%), and relatively low in China (37%), the Philippines (45%), the Russian Federation (47%) and Zimbabwe (41%). Almost all (96%) of the notifications of new cases of smear-positive pulmonary TB were disaggregated by age and sex ( Table 3.2); 88% were aged 15–64 years, 59% were aged 15–45 years and 2% were children (aged <15 years). The global male:female sex ratio was 1.9, but among HBCs this varied from 0.5 in Afghanistan to 3.0 in Viet Nam. Variation among countries may reflect real differences in epidemiology as well as differential access to or use of health care services linked to the NTP.

Reporting of cases disaggregated by age and sex was much less complete for new smear-negative pulmonary and extrapulmonary cases. For example, data disaggregated by age and sex according to the categories shown in Table 3.2 were not available for 11 HBCs. When the available data for all new cases were combined, most cases (82%) were aged 15–64 years, 55% were aged 15–45 years and 6% were among children (<15 years); the male:female ratio was 1.7, ranging from 1.0 to 2.1 among the six WHO regions. Further efforts are needed to improve reporting of all cases disaggregated by age and sex. In the European Region, WHO and the European Centre for Disease Control and Prevention (ECDC) also request countries to report notifications in the civilian and prison sectors separately. These data show that notifications in the prison sector can be a considerable share of all cases, and that case notification rates in the prison population can be strikingly high. A summary of the latest data in the European Region and selected countries, and an example of success in reducing notification rates in the Russian Federation, are provided in Box 3.3.

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Box 3.2

WHO definitions of TB cases recommended for use starting in 2013 and that will be used in the 2014 global TB reporta Bacteriologically confirmed case of TB  A patient from whom a biological specimen is positive by smear microscopy, culture or WHO-approved rapid diagnostic test (such as Xpert MTB/RIF). All such cases should be notified, regardless of whether TB treatment is started. Clinically diagnosed case of TB  A patient who does not fulfil the criteria for bacteriologically confirmed TB but has been diagnosed with active TB by a clinician or other medical practitioner who has decided to give the patient a full course of TB treatment. This definition includes cases diagnosed on the basis of X-ray abnormalities or suggestive histology and extrapulmonary cases without laboratory confirmation. Clinically diagnosed cases subsequently found to be bacteriologically positive (before or after starting treatment) should be reclassified as bacteriologically confirmed. Case of pulmonary TB  Any bacteriologically confirmed or clinically diagnosed case of TB involving the lung parenchyma or the tracheobronchial tree. Miliary TB is classified as pulmonary TB because there are lesions in the lungs. Tuberculous intra-thoracic lymphadenopathy (mediastinal and/ or hilar) or tuberculous pleural effusion, without radiographic abnormalities in the lungs, constitute a case of extrapulmonary TB. A patient with both pulmonary and extrapulmonary TB should be classified as a case of pulmonary TB. Case of extrapulmonary TB  Any bacteriologically confirmed or clinically diagnosed case of TB involving organs other than the lungs, e.g. pleura, lymph nodes, abdomen, genitourinary tract, skin, joints and bones, meninges. New case of TB  A patient who has never been treated for TB or has taken anti-TB drugs for less than 1 month. Retreatment case of TB  A patient who has been treated for 1 month or more with anti-TB drugs in the past. Retreatment cases are further classified by the outcome of their most recent course of treatment into four categories. 1. Relapse patients have previously been treated for TB, were declared cured or treatment completed at the end of their most recent course of treatment, and are now diagnosed with a recurrent episode of TB (either a true relapse or a new episode of TB caused by reinfection). 2. Treatment after failure patients have previously been treated for TB and their most recent course of treatment failed. 3. Treatment after loss to follow-up patients have previously been treated for TB and were declared ‘lost to follow-up’ at the end of their most recent course of treatment (this category corresponds to the ‘defaulted’ category defined in Box 3.1). 4. Other previously treated patients are those who have previously been treated for TB but whose outcome after their most recent course of treatment is unknown or undocumented. Case of multidrug-resistant TB (MDR-TB)  As defined in Box 3.1 Case of rifampicin-resistant TB (RR-TB)  A patient with TB that is resistant to rifampicin detected using phenotypic or genotypic methods, with or without resistance to other anti-TB drugs. It includes any resistance to rifampicin, whether mono-resistance, multidrug resistance, polydrug resistance or extensive drug resistance. a

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/ HTM/TB/2013.2). Geneva, World Health Organization, 2013. Available at www.who.int/iris/bitstream/10665/79199/1/9789241505345_eng.pdf

3.2

Contribution of public–public and public–private mix initiatives and community-based TB activities to TB case notifications in 2012

3.2.1 Public–public and public–private mix (PPM) Ensuring proper diagnosis, standardized treatment and prompt notification of all TB cases to NTPs requires collaboration with the full range of health care providers. Engaging all care providers in TB care and control is component 4 of the Stop TB Strategy (Chapter 1). Its two subcomponents are:  involving all public, voluntary, corporate and private providers through PPM approaches; and  promoting the International Standards for Tuberculosis Care.1 Many countries have scaled up PPM initiatives. Demonstrating progress in terms of the contribution of non-NTP providers to total case notifications requires systematic recording of the source of referral and place of TB treat-

ment locally, and reporting and analysis of aggregated data nationally.2 In 2013, 73 countries reported summary data to WHO, and data for 29 of these countries (including 14 HBCs) are shown in Table 3.3. In most of these countries, PPM initiatives contributed about 10% to 40% of total notifications. Considering that the private medical sector in Africa is much smaller compared with that in Asia, the contribution of private-for-profit and not-for-profit providers in Ethiopia, Kenya, Nigeria and the United Republic of Tanzania is noteworthy. Progress in parts of Asia is also noticeable – almost every fourth case in Indonesia and the Philippines was notified by non-NTP care providers in 2012. Large public sector hospitals have contributed sizeable proportions of cases in China and Indonesia as well as in the Philippines, and engagement of large hospitals is one of the major strategies required to improve detection and notification of TB 1 2

http://www.istcweb.org/ISTC_Documents.html WHO recommends that the source of referral and the place of treatment should be routinely recorded and reported.

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Table 3.2

TB case notifications by age and sex, 2012 NEW SMEAR-POSITIVE CASES % AGED < 15 YEARS MALE: FEMALE RATIO ALL NEW CASES a % AGED < 15 YEARS MALE: FEMALE RATIO

0–14 YEARS

15–44 YEARS

45–64 YEARS

≥65 YEARS

0–14 YEARS

15–44 YEARS

45–64 YEARS

≥65 YEARS

Afghanistan Bangladesh Brazil Cambodia China DR Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global

588 966 580 53 1 091 3 138 12 957 1 703 996 338 1 187 3 947 1 032 48 2 650 117 636 490 142 293 32 952 14 340 2 012 5 641 325 17 116 2 693 42 127

8 469 56 209 25 209 6 000 138 667 47 722 378 071 116 326 29 779 24 076 38 590 66 901 49 736 17 039 86 899 13 525 18 535 17 855 23 310 9 568 1 172 486 387 286 61 956 107 871 46 286 617 926 230 572 1 451 897

3 106 34 674 11 129 6 064 110 614 17 066 186 737 70 491 5 114 14 405 10 571 29 149 29 617 8 793 24 964 11 435 4 777 5 257 18 363 1 870 604 196 106 782 27 462 43 608 24 440 336 069 172 377 710 738

1 156 14 941 3 190 2 724 65 960 3 198 – 51 824 13 799 1 048 – 4 090 2 553 10 548 6 943 1 587 4 151 5 921 914 1 536 9 218 432 205 733 22 983 11 282 16 843 7 355 94 741 88 191 241 395

4 <1 1 <1 <1 4 2 <1 3 <1 2 4 1 <1 2 <1 3 2 <1 2 2 3 2 3 <1 2 <1 2

0.5 1.9 2.3 1.2 2.5 1.3 – 2.2 1.5 1.6 – 1.9 1.6 1.1 2.3 2.7 1.3 2.4 1.8 1.8 3.0 1.3 1.9 1.5 1.7 1.2 2.4 2.0 2.4 1.9 2 911 23 541 5 954 894 852 167 236 45 899 53 351 60 455 397 219 351 268 1 985 343 231 38 997 19 974 21 545 20 575 112 503 195 965 409 559 3 688 38 578 62 298 187 239 26 302 58 762 5 254 11 183 27 343 5 368 172 706 58 234 100 254 13 853 22 579 3 994 5 625 397 615 284 934 170 687 4 842 2 388 88 156 42 306 48 190 20 056 20 602 6 322

15 3 3 – <1 – 16 7 8 7 13 – – 10 – 4 13 – – 9 – 8 6 9 5 10 5 6 1 6

0.6 1.6 2.0 – 2.2 – 1.2 – 1.4 1.4 – – – 1.0 1.9 2.2 1.2 – – 1.5 – 1.2 1.7 1.3 1.6 1.0 1.9 1.8 2.1 1.7

231 674 1 724 885 97 629 9 646 41 847 10 042 119 186 13 945 571 919 98 753 133 536 129 898 739 149 498 524

292 295 2 171 779 1 075 428

Blank cells indicate data that could not be reported for the age categories shown. – indicates values that cannot be calculated. a Numbers in each age category are only shown if data were reported for all four age categories for each category of TB case. For this reason, there are small discrepancies between numbers presented in this table and in the tables that appear in Box 2.2 of Chapter 2.

cases. Experience from a project that was recently completed in five countries is profiled in Box 3.4. Approaches to engage non-NTP care providers vary according to the local context, but there are some important cross-cutting elements. One is provision of standardized care by non-NTP providers according to national guidelines, in return for provision of free anti-TB drugs, supervision and quality assurance, and financial or nonfinancial incentives by NTPs. A second is the use of the Inter-

national Standards for Tuberculosis Care, which facilitates the use of best practices in TB diagnosis and treatment among all care providers, especially those in the private sector. In the European Region and the Region of the Americas, contributions to case notifications from public sector providers outside the purview of the Ministry of Health, such as social security organizations and prison health services, are relatively large.

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GLOBAL TUBERCULOSIS REPORT 2013

Box 3.3

TB and prisons As an airborne disease, TB thrives in the crowded, poorlyventilated environments found in prisons in many parts of the world. Conditions of prison life including malnutrition and stress can also contribute to a higher risk of developing TB disease, and inadequate or inaccessible medical care can lead to poor treatment outcomes and acquisition of resistance. Prisoners disproportionately come from marginalized socioeconomic backgrounds – including substance users, homeless people, people with mental illness, ethnic minorities, asylum seekers and immigrants – and therefore often enter the prison system with an existing high prevalence of TB infection or even with active disease. Prisons also contribute to overall TB burden in that they are not entirely closed systems: TB can be spread to prison staff and visitors, and at some point most prisoners are released into the general population. The WHO European Region is currently the only region that systematically collects and analyses data from Member States on the burden of TB in prisons.a As is likely the situation in most countries around the world, the burden of TB in prisons in European countries is disproportionately high and often makes a considerable contribution to overall country case notifications. Notification rates of new TB cases in prisons in all reporting countries were multiple times higher than the rates found in the general population (relative risks ranging from 4 to 180), and were over 1000 per 100 000 detainees in Azerbaijan, Georgia and Kyrgyzstan (2500, 3300 and 3000 per 100 000 detainees, respectively) in 2011. Among reporting countries, case notifications from prisons accounted for over 10% of national notifications of new TB cases in Georgia (19%) and the Russian Federation (11%) in 2011. Given that some countries in the region have not been able to report data on TB notifications in prisons and that limited data are available on trends, the contribution of TB notifications in prisons to overall TB notifications in the region is uncertain. To reduce the burden of TB in prisons, a comprehensive package of measures is required.b,c These include early diagnosis using systematic screeningd and rapid diagnostics, proper infection control, improved living conditions and nutrition, supervised and complete TB treatment with appropriate drugs, treatment of comorbidities including HIV, diabetes, hepatitis and substance use disorders, and continuity of care in the public sector when a prisoner under treatment is released. The Russian Federation was successful in introducing several measures that significantly reduced the burden of TB in its penitentiary system (Figure B3.3.1).e By reinforcing systematic screening, improving infection control measures, strengthening treatment, and building cooperation between the Ministry of Justice, Ministry of Health institutions, and international partners, TB notification rates decreased sharply from 4347 cases per 100 000 detainees in 1999 (i.e., TB was detected in 1 of 25 detainees in 1999) to 1387 cases per 100 000 detainees in 2006. The decrease since 2006 has been gradual, reflecting the continuing challenges facing TB control in the penitentiary sector, including rising rates of TB/HIV coinfection and drug-resistant TB, as well as the continued concentration of socioeconomically marginalized people entering the prison system. Of note is the higher notification rate found in the pre-trial detention centres compared with correctional facilities in 2011 (1588 compared with 1179 per 100 000 detainees, respectively), reflecting in part the underlying high prevalence of TB infection and disease among socioeconomically marginalized people who enter the pre-trial detention centres from the general population. In Eastern Europe, drug-resistant TB has been associated with detention and in many countries prisons have had to deal with substantial caseloads of MDR-TB patients.f–h The provision of effective MDR-TB care for prison inmates is therefore important. The possibility of close monitoring of imprisoned patients may also be conducive to achievement of good treatment outcomes. For example, data from the penitentiary sector in Azerbaijan show treatment success rates in the range 65%–81% in the 2007–2009 patient cohorts treated in accordance with WHO-recommended standards.i a

Figure B3.3.1

TB notification rate in the prison facilities of the Russian Federation (1999–2011), overall and disaggregated by pre-trial detention centres and correctional facilities 5000 TB notification rate per 100 000 detainees per year 4000 3000 2000 1000 0 1999

b See c

d e

f

g

2001

2003

2005

2007

2009

2011

h

Combined prison facilities Correctional facilities Pre trial detention centres

i

Tuberculosis surveillance and monitoring in Europe 2012. Stockholm, European Centre for Disease Prevention and Control/WHO Regional Office for Europe, 2012. Guidelines for the control of tuberculosis in prisons. Geneva, World Health Organization, 1998 (WHO/TB/98.250). Dara M, Chadha SS, Melchers NV, van den Hombergh J, Gurbanova E, Al-Darraji H, van der Meer JBW. Time to act to prevent and control tuberculosis among inmates. International Journal of Tuberculosis and Lung Disease, 2013 Jan; 17(1):4–5. Systematic screening for active tuberculosis: principles and recommendations. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2013.04). Tuberculosis in the Russian Federation 2011: an analytical review of statistical indicators used in the Russian Federation and in the world (in Russian). Moscow, Ministry of Health of the Russian Federation et al., 2013. Skrahina A, Hurevich H, Zalutskaya A, et al. Multidrug-resistant tuberculosis in Belarus: the size of the problem and associated risk factors. Bulletin of the World Health Organization, 2013;91:36–45. Aerts A, Habouzit M, Mschiladze L, et al. Pulmonary tuberculosis in prisons of the ex-USSR state of Georgia: results of a nation-wide prevalence survey among sentenced inmates. International Journal of Tuberculosis and Lung Disease, 2000 Dec; 4(12):1104–10. Shin SS, Pasechnikov AD, Gelmanova IY, Peremitin GG, Strelis AK, Mishustin S, et al. Treatment outcomes in an integrated civilian and prison MDR-TB treatment program in Russia. International Journal of Tuberculosis and Lung Disease, 2006 Apr; 10(4):402–8. Review of tuberculosis prevention, control and care in Azerbaijan. Copenhagen, World Health Organization, 2013.

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Table 3.3

Contribution of public-private and public-public mix (PPM) to notifications of TB cases in 29 countries, 2012 Country Types of care providers engaged Number of TB cases notified by public non-NTP care providers a Number of TB cases notified by private care providersb Contribution to total notifications of TB cases in 2012 (%)

AFRICAN REGION  Ethiopia Ghana Kenya Lesotho Nigeria Swaziland United Republic of Tanzania REGION OF THE AMERICAS  El Salvador Peru Diverse non-NTP public and private providers Social security organizations and other non-NTP public providers Private clinics, hospitals, laboratories and pharmacies Health insurance organizations, NGOs and other public non-NTP providers Health insurance organizations, prisons, military and private care providers Diverse non-NTP public and private providers Private clinics and hospitals Diverse private and non-NTP public providers Diverse private and non-NTP public providers Public hospitals including university, military and police hospitals, prisons and private hospitals Diverse non-NTP public and private providers, and prisons Diverse non-NTP public providers and prisons Diverse private, non-NTP public and NGO providers Diverse private, non-NTP public and NGO providers Public and private hospitals Diverse private, non-NTP public and NGO providers Diverse private providers Diverse non-NTP public and private providers Diverse non-NTP public and private providers General public hospitals Private clinics and hospitals Diverse non-NTP public and private providers 761 6 576 50 – 40 22 Diverse private providers Diverse non-NTP public and private providers Private clinics and hospitals, and prisons Diverse private providers Public non-NTP and NGO hospitals and private clinics Diverse non-NTP public and private providers Private facilities and faith based organizations – 1 107 817 – 14 096 1 489 – 17 133 832 10 364 1 044 8 121 841 13 734 12 13 12 10 24 33 22

EASTERN MEDITERRANEAN REGION  Afghanistan Egypt Iran (Islamic Republic of) Iraq Pakistan Sudan Syrian Arab Republic Yemen EUROPEAN REGION  Georgia Tajikistan SOUTH-EAST ASIA REGION Bangladesh Indiac Indonesia Myanmar Nepal Sri Lanka Thailand WESTERN PACIFIC REGION China Philippines Viet Nam a

1 362 1 993 1 205 2 693 925 450 175 3486

2 128 213 3 189 2 938 56 363 1 475 2 400 –

12 26 40 65 21 10 86 35

673 1 549 2 429 13 572 77 376 8 999 – 5 004 1 532 388 487 11 804 3 404

1628 – 14 934 3 533 5 432 26 879 5 366 445 1 267 – 36 744 4 724

58 24 10 – 25 23 15 60 4.6 44 24 8.0

Includes all contributions from non-NTP providers, including public hospitals, public medical colleges, prisons/detention centres, military facilities, railways and public health insurance organizations. sector providers include private individual and institutional providers, corporate/business sector providers, mission hospitals, non-governmental organizations and faith-based organizations. c Data for India are for smear-positive cases of pulmonary TB in 14 cities where PPM surveillance is in place. b Private

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GLOBAL TUBERCULOSIS REPORT 2013

Box 3.4

Engaging hospitals to improve TB care and prevention In 2009, WHO initiated a project to help intensify TB case detection in five countries in Africa and Asia. Intensified hospital engagement, mainly targeting large hospitals in urban areas, was the main intervention in all five countries. Through a consultative process involving NTPs, departments responsible for hospitals within the ministries of health, directors of participating hospitals, and WHO, a total of 86 hospitals covering a total population of 10 million were involved. This included 20 hospitals in Kinshasa in the Democratic Republic of the Congo; 10 in Accra, Ghana; 17 in Manila, The Philippines; 36 in Swaziland; and the 3 largest national general hospitals in three cities in Viet Nam (Hanoi, Ho Chi Minh City and Hue). The initiative was funded by the Department of Foreign Affairs, Trade and Development of Canada. Prior to the project, hospitals provided TB diagnosis and treatment for many patients without following national guidelines or having formal referral and notification routines. The specific objectives of the project were to improve TB diagnosis and management of patients presenting to hospitals through setting up mechanisms for internal coordination, and to improve external networking to help intensify TB case detection and notification. The main activities were improving identification of people with suspected TB; standardization of diagnostic routines and introduction of external quality assurance in hospital laboratories; establishing a ‘hospital DOTS unit’; a systematic approach to internal referrals so that cases diagnosed in hospitals would be referred to the hospital DOTS unit; formalization of routines for external referral of cases to health centres and feedback about referrals from health centres; ensuring proper treatment and follow up of patients started on treatment in hospitals; and introduction of standardized recording and reporting. After successful implementation of project activities, total hospital notifications increased from about 2000 per year across the five sites before the project to about 12 000 per year in 2012. The documented number of people tested for TB with a bacteriological test increased in all sites, and the average increase was roughly fourfold (Figure B3.4.1). Documentation of referrals for treatment and feedback to confirm treatment initiation demonstrated that the losses after referral were very large at baseline in the two Asian countries (the Philippines and Viet Nam). These losses were substantially reduced by the end of the third project year through improved communication between hospitals and the primary health care facilities to which they were making referrals. Treatment success rates among those started on treatment in hospitals were similar to those reported by the NTP. This project helped to describe a baseline situation in which hospitals were not engaged. It then demonstrated that it is possible to proactively engage hospitals and align their services to national guidelines and in turn to improve detection of TB cases and notification to NTPs. All countries have either developed new national policies for hospital engagement or are in the process of doing so, based on the project results. Similar efforts are anticipated and needed in other countries. Figure B3.4.1

Trends in bacteriological testing for TB and TB case notifications in project sites, 2010–2012 100 000 80 000 60 000 40 000 20 000 0 2010

Number

2011 Number of bacteriological tests done Total number of TB cases diagnosed and notified Number of bacteriologically positive cases diagnosed

2012

3.2.2 Community contributions to TB notifications and treatment support Community-based TB activities can be defined as activities that are conducted outside the premises of formal health facilities, within community-based structures (for example, schools and places of worship) and homesteads. Such activities can be implemented by community health workers1 and community volunteers,2 regardless of whether they are employed and supervised by a government department or by a nongovernmental organization, and make an important contribution to health services including prevention, diagnosis, improved treatment adherence, care and support. In the specific context of TB, community activities can help to increase case notifications and improve treatment outcomes, especially in settings where people with TB have poor access to formal health services.

As shown in section 3.3, approximately one third of people with TB are diagnosed but not reported to national surveillance systems, or not diagnosed at all. Accurate documentation of the contributions of communities to TB notifications and treatment support has been challenging. One reason has been the lack of standardization of indicators that can be used for routine recording and 1

Community health workers can be defined as people with some formal education who have been given training to contribute to community-based health services, including TB prevention and patient care and support. Their profile, roles and responsibilities vary greatly among countries, and their time is often compensated by incentives in kind or in cash. 2 Community volunteers can be defined as community members who have been systematically sensitized about TB prevention and care, either through a short, specific training scheme or through repeated, regular contact sessions with professional health workers.

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Box 3.5

The ENGAGE-TB approach The ENGAGE-TB approacha describes the need for nongovernmental organizations and other civil society organizations to integrate community-based TB activities into their existing work. Pilot projects in five African countries (the Democratic Republic of the Congo, Ethiopia, Kenya, South Africa and the United Republic of Tanzania) are showing promising results. Selected nongovernmental organizations in these countries have started integrating TB services into community-based programmes for HIV, maternal, newborn and child health (MNCH), and cancer screening, with financial support from the Bristol Myers Squibb Foundation. NGO Country Project focus

Femmeplus

Democratic Republic of the Congo Ethiopia

Integration of TB services into community-based HIV activities in two major cities (Kinshasa and Kikwit) Integration of TB/HIV services into community-based MNCH activities in a pastoralist region Integrated community-based TB, HIV and cancer screening project Integration of community-based TB/HIV services into MNCH programmes in pastoralist communities Strengthening integration of TB into community-based HIV activities Integration of TB services into community-based HIV services

AMREF

CUAMM Save the Children

Ethiopia Ethiopia

Centre for Positive Care Pathfinder

South Africa

UR Tanzania

NGO: nongovernmental organization

The challenge is to scale up these experiences and significantly increase the number of community-based workers and volunteers who are providing screening for TB, referring those who might have TB for diagnosis and then providing follow-up care and support to those diagnosed with the disease. WHO is finalizing an implementation manual that will help to inform nongovernmental organizations and NTPs about how they can work together to implement integrated community-based TB activities, with a particular focus on nongovernmental organizations working on MNCH, HIV, primary health care, agriculture, livelihood development and education services. a

ENGAGE-TB – Integrating community-based tuberculosis activities into the work of nongovernmental organizations. Geneva, World Health Organization, 2012.

reporting. To address this challenge, WHO recently developed a minimum set of standardized indicators as part of its ENGAGE-TB approach (Box 3.5). In 2013, these indicators were used to collect standardized, comparable data from a set of 13 countries in which data were known to be routinely recorded and reported in at least some geographical areas.1 Data collection was undertaken separately from the main round of global TB data collection, since most countries are not routinely recording and reporting such data and they are not relevant in all settings. Among the 13 countries ( Table 3.4), notified TB patients referred from the community as a share of total notifications in the areas covered by reporting ranged from 2% in Myanmar (in 92/330 districts) to 33% in Ethiopia (in 98 out of 821 districts). It is possible that these figures are an underestimate, pending optimization of recording and reporting systems. Nonetheless, the finding that the contribution of communities in referring people with TB was under 10% in several countries suggests that there may be opportunities to use untapped community resources in TB prevention, diagnosis and treatment. In settings where access to formal health services is limited, more emphasis in policy and practice on the role of community referrals of people with presumptive TB as early as possible is warranted. The share of patients receiving treatment support in the community was generally high: for example, 50% countrywide in India and 88% countrywide in Kenya. Kenya also provides an interesting example of the untapped potential of communities. While 88% of all TB patients were reported as having received support for treatment adherence, demonstrating the spread and reach of community workers and volunteers in the country, only 5% of TB case notifications had been referred by community members. This suggests that more could be done to increase community engagement in and contribution to TB screening and referral. It is evident that data on community contributions to referrals and treatment adherence are not collected uniformly or systematically, even in the 13 countries shown in Table 3.4. Only three of the 13 countries reported data for both indicators that covered all districts in the country (Burkina Faso, Kenya and Rwanda). The remaining countries reported data that covered only parts of the country (sometimes very limited areas) or data were not available for both indicators. Better understanding of the contribution of communities to TB services will require more routine collection of data; this is of greatest relevance in settings where community contributions are considered a necessary and integral part of TB services.

1

There was no attempt to compile data about the contribution of communities to programme design and implementation (including advocacy activities at local levels). Such data are not routinely available.

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GLOBAL TUBERCULOSIS REPORT 2013

Table 3.4

Community contributions to TB case notifications and treatment adherence support, 2011–2012 Notified patients from community referrals, 2012 Country Share of total notifications in areas for which data were reported (%) Geographic coverage of data Patients who received treatment support in the community (2011 cohort unless specified) Share of cohort in areas for which data were reported (%) Geographic coverage of data

Burkina Faso Côte d’Ivoire DR Congo Ethiopia India Kenya Malawi Myanmar Nigeria Rwanda Senegal Uganda UR Tanzania a

9% 16% 10% 33% 3% 5% 20% 2% Not available 28% 6% Not available 14%

All districts 59/82 districts 45/515 districts 98/821 districts 374/662 districts All districts 2/28 districts 92/330 districts All districts All districts

33% Not available 3% 40%a 50% 88% 91% 2% 5% 46% Not available 35%

All districts 8/515 districts 98/821 districts All districts All districts 2/28 districts 92/330 districts 36/774 districts All districts All districts All districts

63/162 districts

86%

Data are for the 2012 cohort.

3.3 Trends in case notifications since 1990 and estimates of the case detection rate Globally, the number of TB cases diagnosed and notified per 100 000 population was relatively stable between 1990 and 2000, rose sharply between 2000 and 2008 and has subsequently started to fall slowly (Figure 3.1). Globally and in all WHO regions, a clear gap exists between the numbers of notified cases and the estimated numbers of incident cases, although this has narrowed in the past decade globally and in all six WHO regions (Figure 3.2). Trends in the 22 HBCs are shown in Figure 3.3, and for other countries are illustrated in country profiles that are available online.1 The case detection rate (CDR)2 for TB is an indicator that is included within the MDGs (Chapter 1). For a given country and year, the CDR is calculated as the number of new and relapse TB cases (see Box 3.1 for definitions) that were notified by NTPs ( Table 3.1), divided by the estimated number of incident cases of TB that year. The CDR is expressed as a percentage; it gives an approximate3 indication of the proportion of all incident TB cases that are actually diagnosed, reported to NTPs and started on treatment. The best estimate of the CDR for all forms of TB globally in 2012 was 66% (range, 64–69%), up from 53–59% in 2005 and 38–43% in 1995 – the year in which the DOTS strategy began to be introduced and expanded ( Table 3.5). The highest CDRs in 2012 were estimated to be in the Region of the Americas (best estimate 79%; range, 74–85%), the Western 1 2

figure 3.1

Global trends in case notification (black) and estimated TB incidence (green) rates, 1990–2012. Case notifications include new and relapse cases (all forms). 200

Rate per 100 000 population per year

150

100

50

0 1990 1995 2000 2005 2012

www.who.int/tb/data The CDR is actually a ratio rather than a rate, but the term ‘rate’ has become standard terminology in the context of this indicator. 3 It is approximate because of uncertainty in the underlying incidence of TB and because notified cases are not necessarily a subset of incident cases that occurred in the same year; see Chapter 2 for further discussion.

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figure 3.2

Case notification and estimated TB incidence rates by WHO region, 1990–2012. Regional trends in case notification rates (new and relapse cases, all forms) (black) and estimated TB incidence rates (green). Shaded areas represent uncertainty bands. 400 300 200 Rate per 100 000 population per year 100 0 Europe Africa 80 60 40 20 0 South East Asia The Americas 160 120 80 40 0 Western Pacific Eastern Mediterranean

100 75

300

200 150

200 50 100 25 0 1990 1995 2000 2005 2012 0 1990 1995 2000 2005 2012 50 0 1990 1995 2000 2005 2012 100

Pacific Region (best estimate 81%; range, 75–89%) and the European Region (best estimate 74%; range, 70–79%). The other regions had estimated CDRs in the range of 55–71%, with best estimates of around 60%. All regions have improved their estimated CDRs since the mid-1990s, with improvements particularly evident since 2000. Among the 22 HBCs, the highest rates of case detection in 2012 were estimated to be in Brazil, China, Kenya, the Philippines and the Russian Federation. The lowest rates, with best estimates of around 50%, were in Afghanistan, Bangladesh, the Democratic Republic of the Congo, Mozambique, Nigeria and Zimbabwe. The gap between notifications to national surveillance systems and the true number of incident cases can be explained by two factors. The first is underreporting of diagnosed TB cases, for example because private sector providers fail to notify cases. The second is under-diagnosis of people with TB for reasons such as poor access to health care and failure to recognize TB signs and symptoms and test for TB when people do present to health care facilities. Achieving the goal of universal health coverage, implementing PPM initiatives such as those described in section 3.2, and ensuring that there is an effective regulatory framework that includes mandatory notification of cases are essential to reduce underreporting and under-diagnosis. A point-of-care diagnostics test would also help.

definitions that will be used from 2014 are explained in Box 3.7.

3.4.1 New cases of smear-positive pulmonary TB Data on treatment outcomes for new sputum smearpositive cases of pulmonary TB are shown in Table 3.6 and Figure 3.4. Globally, the rate of treatment success for the 2.6 million new cases of sputum smear-positive pulmonary TB who were treated in the 2011 cohort was 87%. This was the fifth successive year that the target of 85% (first set by the World Health Assembly in 1991) was met or exceeded globally. It is also impressive that as the size of the global treatment cohort grew from 1.0 million in 1995 to 2.7 million in 2009 and 2010 and 2.6 million in 2011, the treatment success rate progressively improved. Among the six WHO regions, three met or exceeded the 85% target: the Eastern Mediterranean Region, the SouthEast Asia Region and the Western Pacific Region. The treatment success rate was 82% in the African Region (where there has been steady improvement since 1999), 78% in the Region of the Americas (similar to the previous seven years) and 65% in the European Region (where major efforts to increase treatment success rates are needed). Of the 22 HBCs, 16 reached or exceeded the 85% target in 2011, including Ethiopia and Nigeria for the first time. Five HBCs reported lower rates of treatment success: Brazil (76%), the Russian Federation (52%), South Africa (79%), Uganda (77%) and Zimbabwe (81%). Nonetheless, among these five countries all except the Russian Federation sustained their level or made progress compared with 2010.

3.4 Treatment outcomes Definitions of the categories used to report treatment outcomes in this report are provided in Box 3.6. The updated

38

GLOBAL TUBERCULOSIS REPORT 2013

figure 3.3

Case notification and estimated TB incidence rates, 22 high-burden countries, 1990–2012. Trends in case notification rates (new and relapse cases, all forms) (black) and estimated TB incidence rates (green). Shaded areas represent uncertainty bands. 300 200 200 100 100 0 50

Afghanistan

400 300

Bangladesh

150 100

Brazil

1000 750 500 250 0

Cambodia

200 150 100 50 0

China

0

0

500 400 300 200 100

DR Congo

800 600 400 200 0

Ethiopia

300 200 100

India

300 200 100

Indonesia

400 300 200 100 0

Kenya

Rate per 100 000 population per year

0

0

0

1250 1000 750 500 250 0

Mozambique

600 500 400 300 200 100 0

Myanmar

600 400 200

Nigeria

400 300 200 100 0

Pakistan

600 400 200

Philippines

0

0

200 150 100 50 0

Russian Federation

1250 1000 750 500 250 0

South Africa

250 200 150 100 50 0

Thailand

1250 1000 750 500 250 0

Uganda

300 200 100

UR Tanzania

0 1990 1995 2000 2005 2012 1990 1995 2000 2005 2012

1990 400 300 200 100 0 1990 1995 2000 2005 2012

1995

2000

2005

2012

Viet Nam

1250 1000 750 500 250 0

Zimbabwe

1990

1995

2000

2005

2012

figure 3.4

Treatment outcomes by WHO region, 2011 cohorts a. New smear positive cases AFR AMR EMR EUR SEAR WPR Global 0% 20% 40% 60% 80% 100% AFR AMR EMR EUR SEAR WPR Global 0% 20% Died

b. All new cases

40%

60%

80% Defaulted

100% Not evaluated

Successfully treated

Treatment failed

GLOBAL TUBERCULOSIS REPORT 2013

39

Table 3.5

Estimates of the case detection rate for new and relapse cases (%), 1995–2012a 1995 BEST b LOW HIGH BEST 2000 LOW HIGH BEST 2005 LOW HIGH BEST 2010 LOW HIGH BEST 2012 LOW HIGH

Afghanistan Bangladesh Brazil Cambodia China DR Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global

– 21 79 23 32 31 11 59 8.9 61 23 10 8.9 4.5 48 60 56 59 23 59 33 55 38 32 67 23 51 44 37 40

– 17 66 19 27 26 7.2 52 7.1 56 11 8.0 2.7 3.7 40 51 47 50 14 51 25 40 36 27 63 21 49 40 32 38

– 26 97 30 39 38 18 67 12 66 73 13 170 5.5 58 70 69 72 41 69 47 79 42 39 72 26 54 49 42 43

18 25 74 27 33 40 33 49 20 72 23 15 12 3.3 47 75 59 32 29 68 56 56 39 39 70 25 59 41 39 41

15 21 62 22 28 34 22 45 16 67 13 13 3.9 2.8 39 65 49 27 20 60 43 45 37 33 65 22 55 38 35 39

22 31 91 34 38 48 55 55 25 77 51 19 170 4.1 57 89 72 39 48 77 78 71 42 48 75 28 62 44 44 44

46 38 85 52 74 55 48 49 57 80 30 53 26 39 53 66 61 57 47 74 63 50 55 52 75 48 65 50 70 56

39 32 72 44 65 47 32 44 47 76 20 45 32 44 56 50 48 36 69 49 40 51 44 71 43 61 46 63 53

57 47 100 63 85 64 80 55 71 85 53 63 48 65 78 74 69 65 80 86 63 58 61 81 54 70 53 77 59

52 45 82 64 86 56 66 60 66 81 33 66 40 66 65 83 70 79 60 77 70 53 66 60 76 64 77 61 80 66

44 38 69 56 76 49 49 54 56 78 25 57 23 55 54 71 59 66 50 72 54 43 63 56 71 57 72 56 73 63

63 55 99 75 98 65 93 66 80 85 48 77 82 80 79 98 85 95 75 82 95 69 69 65 82 72 82 65 87 68

52 49 82 66 89 51 64 59 72 79 34 71 51 65 84 81 62 76 69 79 76 46 66 59 79 63 74 62 81 66

44 41 69 57 79 44 49 54 61 76 25 62 29 54 71 70 52 64 57 74 59 37 63 55 74 56 70 58 75 64

63 59 99 77 100 59 87 66 87 83 50 83 110 78 100 96 75 92 85 84 100 60 70 64 85 71 79 66 89 69

9.6 200

– indicates values that cannot be calculated. a Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously. b Best, low and high indicate best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations.

Data for Mozambique were not reported to WHO, but the level in 2010 was 85%. In the Russian Federation, improvement of treatment outcomes has been identified as a high priority by the Ministry of Health and actions to improve it have been defined. These include ensuring earlier detection of MDR-TB and enrolment of patients on second-line treatment, and strengthening patient support to improve adherence to treatment (especially among the most socially and economically disadvantaged patients). It is expected that the introduction of a patient-based monitoring system for those with MDR/XDR-TB and patients coinfected with HIV in the near future will also help to improve the quality of care and treatment outcomes.

3.4.2 All new cases Data on treatment outcomes for all new cases of TB are shown in Table 3.7 and Figure 3.4. Globally, the rate of treatment success was 87% in 2011. Among the six WHO regions, the highest rates were in the Eastern Mediterranean Region (88%), the South-East Asia Region (89%) and Western Pacific Region (93%). The treatment success rate was 79% in the African Region, a big improvement from 73% in 2010. In the Region of the Americas and the European Region it was 75% and 72%, respectively. Of the 22 HBCs, 15 reached or exceeded a treatment success rate of 85% among all new cases in 2011, including Ethiopia (following a major improvement from 77% in

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GLOBAL TUBERCULOSIS REPORT 2013

Box 3.6

Box 3.7

Definitions of treatment outcomes for drugsusceptible TB until the end of 2012 and in this global TB reporta Cured  A patient who was initially sputum smear-positive and who was sputum smear-negative in the last month of treatment and on at least one previous occasion. Completed treatment  A patient who completed treatment but did not meet the criteria for cure or failure. This definition applies to sputum smear-positive and sputum smearnegative patients with pulmonary TB and to patients with extrapulmonary disease. Died  A patient who died from any cause during treatment. Failed  A patient who was initially sputum smear-positive and who remained sputum smear-positive at month 5 or later during treatment. Also included in this definition are patients found to have a multidrug-resistant strain at any point in time during treatment, whether they are smear-negative or smear– positive. Defaulted  A patient whose treatment was interrupted for two consecutive months or more. Not evaluated  A patient whose treatment outcome is not known. Successfully treated  A patient who was cured or who completed treatment. Cohort  A group of patients in whom TB has been diagnosed, and who were registered for treatment during a specified time period (e.g. the cohort of new sputum smear-positive cases registered in the calendar year 2010). This group forms the denominator for calculating treatment outcomes. The sum of the above treatment outcomes, plus any cases for whom no outcome is recorded (including those ‘still on treatment’ in the European Region) and ‘transferred out’ cases should equal the number of cases registered. Some countries monitor outcomes among cohorts defined by sputum smear and/or culture, and define cure and failure according to the best laboratory evidence available for each patient. a See

WHO definitions of treatment outcomes for drug-susceptible TB recommended for use starting in 2013 and that will be used in the 2014 global TB reporta Cured  A pulmonary TB patient with bacteriologicallyconfirmed TB at the beginning of treatment who was smear- or culture-negative in the last month of treatment and on at least one previous occasion. Completed treatment  A TB patient who completed treatment without evidence of failure but with no record to show that sputum smear or culture results in the last month of treatment and on at least one previous occasion were negative, either because tests were not done or because results are unavailable. Died  A patient who died from any cause during treatment. Failed  A TB patient whose sputum smear or culture is positive at month 5 or later during treatment. Lost to follow-up  A TB patient who did not start treatment or whose treatment was interrupted for two consecutive months or more. Not evaluated  A TB patient for whom no treatment outcome is assigned. This includes cases ‘transferred out’ to another treatment unit as well as cases for whom the treatment outcome is unknown to the reporting unit. Successfully treated  A patient who was cured or who completed treatment. Cohort  As defined in Box 3.6. In addition, it should be highlighted that any patient found to have drugresistant TB and placed on second-line treatment is removed from the drug-susceptible TB outcome cohort. This means that management of the standard TB register and of the second-line TB treatment register needs to be coordinated to ensure proper accounting of the outcomes of treatment. (See also Box 4.4) a

Treatment of tuberculosis guidelines, 4th ed. Geneva, World Health Organization, 2010 (WHO/HTM/STB/2009.420). Available at http://whqlibdoc.who.int/publications/2010/9789241547833_eng.pdf

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/HTM/TB/2013.2). Geneva, World Health Organization, 2013. Available at www.who.int/iris/bitstream/10665/79199/ 1/9789241505345_eng.pdf

Box 3.8

Achievements in global TB care and control, 1995–2012 WHO began systematic monitoring of TB control progress in 1995. Data compiled on an annual basis since then allow achievements in TB care and control to be assessed. Between 1995 and 2012, 56 million people were successfully treated for TB in countries that had adopted the DOTS/Stop TB Strategy. This saved approximately 22 million lives.a The number of lives saved is based on the estimate that in the absence of treatment, approximately one third of people with TB would die of the disease. This estimate allows for differences in the mortality rates for smear-positive compared with other types of TB disease (see Chapter 1), and for differences in mortality rates between HIV-negative and HIV-positive people. a

For estimates of the incremental number of lives saved by improvements in TB care associated with implementation of the DOTS and Stop TB Strategy compared with pre-1995 standards of care, see Glaziou P et al. Lives saved by tuberculosis control and prospects for achieving the 2015 global target for reducing tuberculosis mortality. Bulletin of the World Health Organization, 2011, 89:573–582.

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Table 3.6

Treatment success for new smear-positive cases (%) and cohort size (thousands), 1995–2011 a. Treatment success (%) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Afghanistan Bangladesh Brazil Cambodia China DR Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global

– 71 17 91 93 74 61 25 91 75 39 67 49 70 60 65 58 64 44 73 89 53 53 60 50 79 67 33 80 57

– 63 20 94 94 48 71 21 81 77 55 79 32 – 35 57 61 78 33 76 89 32 50 56 51 66 58 31 72 54

45 73 27 91 95 64 72 18 54 65 65 82 73 67 78 67 68 58 40 77 85 69 56 64 58 73 72 29 91 60

33 77 40 95 95 70 74 27 58 77 – 82 73 23 71 68 72 68 62 76 92 70 62 70 67 57 63 40 92 64

86 79 78 93 95 69 74 21 50 79 71 81 75 70 87 65 57 77 61 78 92 73 60 68 79 79 75 34 91 64

85 81 71 91 93 78 80 34 87 80 75 82 79 74 88 68 63 69 63 78 92 69 67 71 76 81 75 50 90 69

84 83 55 92 95 77 76 54 86 80 78 81 79 77 88 67 61 75 56 81 93 71 72 70 69 82 74 63 91 73

87 84 80 92 92 78 76 60 86 79 78 81 79 78 88 67 68 74 60 80 92 67 75 73 81 84 74 68 90 76

86 85 77 93 93 83 70 76 87 80 76 81 78 79 88 61 67 73 68 81 92 66 81 73 80 82 75 79 91 80

89 90 76 91 94 85 79 82 90 80 77 84 73 82 87 60 69 74 70 81 93 54 84 74 79 83 71 84 91 83

90 91 76 93 94 85 78 86 91 82 79 84 75 83 89 58 71 75 73 82 92 68 86 76 79 83 72 87 92 85

84 92 73 93 94 86 84 86 91 85 83 84 76 88 88 58 74 77 70 85 93 60 87 75 76 86 70 87 92 84

87 92 72 94 94 87 84 87 91 85 79 85 82 91 89 58 74 83 75 88 92 78 87 80 79 88 71 88 92 86

88 91 71 95 94 87 84 87 91 85 84 85 78 90 88 57 76 82 70 88 92 74 87 80 77 88 70 88 92 86

86 92 72 95 95 88 84 88 91 86 85 85 83 91 89 55 73 86 67 88 92 78 88 80 76 88 69 89 93 86

90 92 74 94 96 90 83 88 90 87 85 86 84 91 91 53 79 85 71 90 92 81 88 81 75 88 67 88 93 87

91 92 76 93 95 87 90 88 90 88 – 86 85 92 90 54 79 85 77 88 93 81 88 82 78 88 65 89 94 87

b. Cohort size (thousands) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Afghanistan Bangladesh Brazil Cambodia China DR Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global

11 30 46 45 4.4 9.1 131 175 16 25 5.1 11 265 291 3.0 12 6.5 13 11 13 7.9 9.7 9.5 24 0.8 90 126 0.05 43 28 45 20 0.1 15 15 20 21 38 48 9.7 12 739 967 178 233 129 134 46 51 34 94 318 360 296 372 1 001 1 245

2.0 2.9 2.0 3.1 6.3 7.8 6.8 10 10 12 13 13 12 13 14 34 38 38 38 41 47 54 63 85 102 104 106 109 106 99 43 30 27 34 41 29 38 43 42 48 38 41 41 42 43 12 13 16 15 14 17 19 19 21 19 19 20 18 17 16 189 210 208 214 190 194 267 385 473 470 466 464 449 430 377 26 33 35 36 41 45 54 62 65 63 66 66 72 73 71 12 15 21 30 32 37 40 41 39 37 38 41 45 47 41 293 284 345 349 384 396 420 489 507 553 592 616 625 630 642 21 40 46 52 54 76 93 129 159 175 161 166 169 183 198 19 22 27 28 31 31 34 41 40 39 38 37 37 36 37 11 12 13 14 15 16 17 18 18 18 19 20 20 9.2 10 12 17 21 24 27 31 37 40 43 41 42 42 42 11 13 15 16 17 21 28 34 35 40 44 46 45 45 47 2.8 29 3.0 4.1 6.3 15 20 32 48 66 89 100 102 104 106 27 21 37 50 55 59 68 78 81 86 87 85 89 89 94 0.7 0.7 1.5 3.6 4.1 5.2 6.3 26 26 31 32 32 32 30 37 55 37 81 86 101 99 114 127 135 140 143 144 139 134 133 3.7 8.0 14 23 20 27 28 28 30 29 30 33 28 30 31 18 13 14 14 17 19 20 21 21 20 21 23 23 23 26 22 24 24 24 24 24 25 26 25 25 25 24 25 24 24 54 55 53 53 54 57 56 58 55 56 54 53 51 52 51 15 13 16 11 10 10 12 13 12 13 13 14 17 16 14 879 912 1 044 1 119 1 186 1 260 1 450 1 776 1 965 2 087 2 132 2 181 2 184 2 185 2 140 268 235 323 365 409 452 491 552 564 566 577 591 606 599 579 125 111 110 111 102 105 110 121 119 132 116 109 123 126 127 60 89 66 64 52 76 81 98 114 132 156 167 167 170 171 24 48 22 41 50 54 60 80 81 98 108 114 105 99 97 376 399 473 512 550 604 661 780 856 938 974 1 011 1 022 1 045 1 065 294 313 353 360 346 357 439 575 663 663 661 657 641 622 560 1 147 1 195 1 347 1 453 1 510 1 649 1 842 2 206 2 396 2 529 2 591 2 649 2 665 2 662 2 599

Blank cells indicate data not reported. – indicates values that cannot be calculated.

42

GLOBAL TUBERCULOSIS REPORT 2013

Table 3.7

Treatment success for all new cases (%) and cohort size (thousands), 1995–2011 a. Treatment success (%) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Afghanistan Bangladesh Brazil Cambodia China DR Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global

– 71 17 91 93 74 61 25 91 75 39 67 49 70 60 65 58 64 44 73 89 53 53 60 50 79 67 33 80 57

– 63 20 94 94 48 71 21 81 77 55 79 32 – 35 57 61 78 33 76 89 32 50 56 51 66 58 31 72 54

45 73 27 91 95 64 72 18 54 65 65 82 73 67 78 67 68 58 40 77 85 69 56 64 58 73 72 29 91 60

33 77 40 95 95 70 74 27 58 77 – 82 73 23 71 68 72 68 62 76 92 70 62 70 67 57 63 40 92 64

86 79 78 93 95 69 74 21 50 79 71 81 75 70 87 65 57 77 61 78 92 73 60 68 79 79 75 34 91 64

85 81 71 91 93 78 80 34 87 80 75 82 79 74 88 68 63 69 63 78 92 69 67 71 76 81 75 50 90 69

84 83 55 92 95 77 76 54 86 80 78 81 79 77 88 67 61 75 56 81 93 71 72 70 69 82 74 63 91 73

87 84 80 92 92 78 76 60 86 79 78 81 79 78 88 67 68 74 60 80 92 67 75 73 81 84 74 68 90 76

86 85 77 93 93 83 70 76 87 80 76 81 78 79 88 61 67 73 68 81 92 66 81 73 80 82 75 79 91 80

89 90 72 91 92 85 79 81 87 77 77 82 73 80 78 65 65 71 70 82 92 48 82 70 76 82 76 83 88 81

90 90 72 91 92 85 78 87 89 81 79 83 75 82 89 67 69 71 73 83 92 66 85 74 75 82 77 87 90 84

84 91 69 92 92 60 84 87 90 83 83 83 76 86 88 69 70 75 68 85 92 67 85 72 73 86 75 87 90 84

87 90 72 93 93 86 84 88 90 83 79 84 82 90 88 69 71 81 72 88 91 78 87 77 78 87 76 88 91 85

88 91 69 94 93 86 80 88 90 84 84 84 78 89 84 69 73 80 67 88 92 70 87 77 73 87 76 88 91 85

86 91 70 94 94 88 81 89 89 84 85 84 84 91 85 68 68 84 64 88 92 75 86 76 73 87 75 89 91 85

86 91 72 89 95 89 77 89 89 86 85 88 81 90 90 66 53 83 68 89 92 76 86 73 73 88 74 89 92 84

88 91 73 94 95 87 89 89 88 87 – 88 85 92 87 65 77 82 73 88 93 80 88 79 75 88 72 89 93 87

b. Cohort size (thousands) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Afghanistan Bangladesh Brazil Cambodia China DR Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federation South Africa Thailand Uganda UR Tanzania Viet Nam Zimbabwe High-burden countries AFR AMR EMR EUR SEAR WPR Global

11 30 46 45 4.4 9.1 131 175 16 25 5.1 11 265 291 3.0 12 6.5 13 11 13 7.9 9.7 9.5 24 0.8 90 126 0.05 43 28 45 20 0.1 15 15 20 21 38 48 9.7 12 739 967 178 233 129 134 46 51 34 94 318 360 296 372 1 001 1 245

2.0 2.9 2.0 3.1 6.3 7.8 6.8 10 10 12 13 13 12 26 26 34 38 38 38 41 47 54 63 119 141 144 106 156 150 148 43 30 27 34 41 29 38 81 78 81 47 73 75 78 71 12 13 16 15 14 17 19 30 34 34 35 38 39 40 37 189 210 208 214 190 194 267 644 788 847 889 932 923 877 856 26 33 35 36 41 45 54 62 65 92 89 93 106 109 92 12 15 21 30 32 37 40 41 39 37 38 139 139 152 91 293 284 345 349 384 396 420 1 066 1 071 1 137 1 199 1 226 1 244 1 229 1 209 21 40 46 52 54 76 93 206 244 266 263 293 289 296 314 19 22 27 28 31 31 34 97 98 101 99 99 99 90 82 11 12 13 14 15 16 17 18 18 18 19 20 20 9.2 10 12 17 21 24 27 66 73 84 85 90 91 127 135 11 13 15 16 17 21 28 34 35 40 44 46 86 78 84 2.8 29 3.0 4.1 6.3 15 20 84 117 149 191 206 212 256 255 27 21 37 50 55 59 68 126 81 123 136 140 141 162 190 0.7 0.7 1.5 3.6 4.1 5.2 6.3 39 74 97 99 103 101 94 89 55 37 81 86 101 99 114 243 259 271 247 236 367 338 292 3.7 8.0 14 23 20 27 28 47 49 47 47 54 43 48 49 18 13 14 14 17 19 20 21 21 31 37 39 38 40 43 22 24 24 24 24 24 25 61 59 58 25 59 60 59 59 54 55 53 53 54 57 56 92 55 91 91 91 88 88 89 54 43 43 39 40 45 46 40 12 13 13 14 17 16 14 879 912 1 044 1 119 1 186 1 260 1 450 3 183 3 430 3 799 3 872 4 134 4 374 4 403 4 252 268 235 323 365 409 452 491 846 886 940 930 1 087 1 297 1 215 1 094 125 111 110 111 102 105 110 191 187 197 157 168 191 200 188 60 89 66 64 52 76 81 178 226 259 307 320 331 391 398 24 48 22 42 50 55 60 184 221 274 276 279 248 250 217 376 399 473 512 550 604 661 1 530 1 639 1 758 1 835 1 880 1 940 1 980 1 986 294 313 353 360 346 357 439 963 1 030 1 163 1 216 1 261 1 259 1 240 1 213 1 147 1 195 1 347 1 453 1 511 1 649 1 843 3 892 4 188 4 592 4 720 4 995 5 267 5 275 5 096

Blank cells indicate data not reported. – indicates values that cannot be calculated.

GLOBAL TUBERCULOSIS REPORT 2013

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Box 3.9

Outcomes of TB treatment by HIV status In 2013, 96 countries with 331 000 HIV-positive TB patients reported treatment outcomes for 2011 that were disaggregated by HIV status. These countries accounted for 58% of all HIV-positive TB patients registered in that year. This was a considerable increase from 2010, when countries that reported outcomes disaggregated by HIV status accounted for 25% of TB patients with a documented HIVpositive test result. Much of the improvement is due to the reporting of data disaggregated by HIV status for the first time by high TB/HIV burden countries such as South Africa and Uganda. Of the 41 TB/HIV priority countries (listed in Table 6.1 of Chapter 6), 19 reported treatment outcomes disaggregated by HIV status: Burundi, Burkina Faso, Brazil, Botswana, China, Ghana, Haiti, India, Kenya, Lesotho, Mali, Myanmar, Namibia, Nigeria, South Africa, Swaziland, Thailand, the United Republic of Tanzania and Viet Nam. Data for 2011 show that treatment outcomes for HIVpositive TB patients continue to be worse than those of HIV-negative TB patients. The treatment success rate for all new HIV-positive TB patients was 73% compared with 87% among HIV-negative TB patients (Figure B3.9.1). If it is assumed that HIV-positive TB patients who defaulted from treatment would have died from TB, the death rate was 19% among HIV-positive TB patients compared with 3% among HIV-negative TB patients. Such findings are consistent with two autopsy studies in South Africa, which showed that undiagnosed TB remains the main cause of death among HIV-positive people.a,b a

Figure B3.9.1

Treatment success (a) and death rates (b) among HIVpositive and HIV-negative TB patients, 2011 100 80 60 40 20 0 HIV+ HIV HIV+ HIV (117 094) (959 174) (163 300) (845 907) New smear positive patients (data from 88 countries) New smear negative and extrapulmonary patients (data from 72 countries) HIV+ (79 817) HIV (385 748) a. Treatment success, 2011

Percentage of cohort (%)

Retreatment patients (data from 59 countries)

30

b. Death rate among evaluated cases, 2011

Mutevedzi P et al. Early mortality following initiation of ART in rural South Africa: the contribution of existing co-morbidities. 20th Conference on Retroviruses and Opportunistic Infections. Atlanta, Georgia, USA, 3–6 March 2013 (Paper 832; www.retroconference. org/2013b/Abstracts/46910.htm, accessed 3 June 2013). b Martinson N et al. Undiagnosed infectious TB in adult home deaths: South Africa 2013. 20th Conference on Retroviruses and Opportunistic Infections. Atlanta, Georgia, USA, 3–6 March 2013 (Paper 837; www. retroconference.org/2013b/Abstracts/45780.htm, accessed 3 June 2013).

Percentage (%)

20

10

0 HIV+ HIV HIV+ HIV (109 137) (925 024) (148 798) (811 586) New smear positive patients (data from 88 countries) New smear negative and extrapulmonary patients (data from 72 countries) HIV+ HIV (73 354) (370 385) Retreatment patients (data from 59 countries)

2010 to 89% in 2011) and Nigeria for the first time. The six countries that reported lower rates of treatment success were Brazil (73%), the Russian Federation (65%), South Africa (77%), Thailand (82%), Uganda (73%) and

Zimbabwe (80%). Data were not reported for Mozambique. Treatment outcomes are worse among HIV-positive TB patients compared with HIV-negative TB patients (Box 3.9). Further efforts are needed to narrow the gap.

44

GLOBAL TUBERCULOSIS REPORT 2013

Chapter 4

Drug-resistant TB Key facts and messages ■■ By the end of 2012, data on anti-TB drug resistance were available for 136 countries (70% of 194 WHO Member States), either from continuous surveillance (mostly high-income countries and other countries of the WHO European Region) or special surveys. ■■ Surveys underway in 2013 in the group of 36 high TB and/or MDR-TB burden countries and from which results are expected in 2014 include the first nationwide surveys in Azerbaijan, India, Pakistan, Turkmenistan and Ukraine, and repeat surveys in China, Ethiopia, Kenya, the Philippines, South Africa, Thailand and Viet Nam. ■■ Globally, an estimated 3.6% (95% CI: 2.1–5.1%) of new cases and 20.2% (95% CI: 13.3–27.2%) of previously treated cases have MDR-TB. The highest levels are in eastern Europe and central Asia where in several countries, more than 20% of new cases and more than 50% of previously treated cases have MDR-TB. ■■ There were an estimated 450 000 (range: 300 000–600 000) new cases of MDR-TB worldwide in 2012. Among patients with pulmonary TB notified in 2012 i.e. the group of patients known to NTPs and that can be tested for drug resistance using WHOrecommended diagnostic tests, there were an estimated 300 000 (range: 220 000–380 000) MDR-TB cases in 2012. More than half of these cases were in India, China and the Russian Federation. ■■ Extensively drug-resistant TB (XDR-TB) has been reported by 92 countries. On average, an estimated 9.6% (95% CI: 8.1%–11%) of MDR-TB cases have XDR-TB. ■■ A total of 94 000 TB cases eligible for MDR-TB treatment (84 000 with MDR-TB and 10 000 with rifampicin resistance detected using Xpert MTB/RIF) were notified globally in 2012, mostly by European countries, India and South Africa. This represented progress compared with 2011, when 62 000 cases were detected; the largest increases between 2011 and 2012 were in India, South Africa and Ukraine. However, worldwide and in most countries with a high burden of MDR-TB, less than one-third of the TB patients estimated to have MDR-TB were actually detected in 2012. ■■ Countries detecting close to 100% of the notified TB patients estimated to have MDR-TB in 2012 included Estonia, Kazakhstan, Latvia, Lithuania, South Africa and Ukraine. The lowest figures were in the South-East Asia Region (21%) and the Western Pacific Region (6%), which combined have 55% of the world’s cases of MDR-TB. ■■ Just over 77 000 people with MDR-TB were started on second-line treatment in 2012, equivalent to 82% of the 94 000 newly detected cases that were eligible for such treatment globally. Diagnostic:treatment gaps were much larger in some countries, especially in the African Region (51% of detected cases enrolled on treatment), and widened between 2011 and 2012 in China, Pakistan and South Africa. ■■ The 2015 treatment success target of ≥75% set in the Global Plan to Stop TB 2011–2015 for MDR-TB was reached by 34 of 107 countries that reported outcome data for the 2010 patient cohort. However, overall only 48% of patients were successfully treated. ■■ Intensified global and national efforts to detect cases of MDR-TB, to enrol them on treatment, and to improve treatment outcomes are urgently required.

Drug-resistant TB (DR-TB) threatens global TB control and is a major public health concern in several countries. This chapter summarizes the progress made in global surveillance of anti-TB drug resistance, using the most recent data on MDR-TB and XDR-TB gathered from special surveys and continuous surveillance systems, and summarizes global estimates of disease burden associated with MDR-TB based on these data (section 4.1). It also includes an assessment of national progress in diagnosing and treating MDR-TB, using data on diagnostic testing for DR-TB, enrolment on treatment with second-line drugs for those found to have MDR-TB, and treatment outcomes (section 4.2).

4.1 Surveillance of drug-resistant TB 4.1.1 Progress in the coverage of drug resistance surveillance Since the launch of the Global Project on Anti-tuberculosis Drug Resistance Surveillance in 1994, data on drug resistance have been systematically collected and analysed from 136 countries worldwide (70% of WHO Member States). This includes 70 countries that have continuous surveillance systems based on routine diagnostic drug susceptibility testing (DST) of all TB patients and 66 countries that rely on special epidemiological surveys of representative samples of patients. The progress towards achieving global coverage of drug resistance data is shown in Figure 4.1. GLOBAL TUBERCULOSIS REPORT 2013 45

figure 4.1

Progress in global coverage of data on drug resistance, 1994–2013

Year of most recent data 1995 1999 2000 2004 2005 2009 2010 2012 Ongoing in 2013 No data Subnational data only Not applicable

Continuous surveillance for MDR-TB, based on routine DST of TB patients and systematic collection, collation and analysis of data, is the most effective approach to monitor trends in drug resistance over time. Additionally, such systems can detect outbreaks that might otherwise be undetected, even during the course of a survey if the outbreak site was not among those sites selected for patient enrolment. The number of countries that can rely on data generated by continuous surveillance systems is increasing, due to efforts invested in scaling up the availability of culture and DST services. Several high MDR-TB burden countries in the European Region, including Belarus, Georgia, Kazakhstan, Republic of Moldova, Ukraine and the Baltic States, have put in place high quality surveillance systems to monitor drug resistance both in new and previously treated TB cases. A group of countries – Bolivia, Chile, Colombia, Costa Rica, Ecuador, Egypt, El Salvador, Kyrgyzstan, Lebanon, Mongolia, Nicaragua, Rwanda, Sri Lanka, Syrian Arab Republic and Tajikistan – that previously relied on special surveys to monitor drug resistance, have now established routine surveillance systems for all previously treated cases. This is the first step towards achieving routine DST for all TB patients. Special surveys still represent the most common approach to investigating the burden of drug resistance in resource-limited settings where routine DST is not accessible to all TB patients due to lack of laboratory capacity or resources. Between 2010 and 2012, drug resistance surveys were completed for the first time in 16 countries: Afghanistan (Central region), Albania, Bangladesh, Belar46 GLOBAL TUBERCULOSIS REPORT 2013

us, Benin, Bulgaria, Kyrgyzstan, Malawi, Nigeria, Saudi Arabia, Somalia, Tajikistan, Tunisia, Uganda, Uzbekistan and Yemen. In addition, Egypt, Brazil, Nepal and Zambia completed a repeat survey. In mid-2013, drug resistance surveys were ongoing in 12 high TB and MDR-TB burden countries. These include the first nationwide surveys in Azerbaijan, India, Pakistan, Turkmenistan, Ukraine, and repeat surveys in China, Ethiopia, Kenya, the Philippines, South Africa, Thailand and Viet Nam. Molecular technologies are increasingly being used in drug resistance surveys to simplify logistics and reduce laboratory workload. GenoType® MTBDRplus (Hain Lifescience, Germany) was used in the national survey completed in 2012 in Nigeria and Xpert® MTB/RIF (Cepheid, USA) is being used in the surveys underway in Pakistan and Papua New Guinea. Several more countries are planning to use Xpert MTB/RIF as a screening tool in drug resistance surveys. Though not a complete surrogate for MDR-TB, particularly in settings where levels of drug resistance are low, rifampicin resistance is the most important indicator of MDR-TB, with serious clinical implications for affected patients. In countries where there is not yet the capacity for culture and DST using conventional methods or where laboratories cannot cope with the large workload generated by a drug resistance survey, Xpert MTB/RIF can play an important role. It can be used to screen specimens for rifampicin resistance and identify those requiring further testing to be performed at national or supranational TB reference laboratories, also reducing the cost of initial screening by conventional commercial DST systems.

Five high TB and MDR-TB burden countries (Afghanistan, Brazil, Democratic Republic of the Congo, Indonesia and the Russian Federation) still rely on drug resistance surveillance data gathered from sub-national areas only. These countries should consider conducting nationwide drug resistance surveys in the short term to better understand the burden of MDR-TB and to guide the planning of diagnostic and treatment services. A further six countries (Dominican Republic, Guinea, Iran, Lesotho, Sierra Leone and Zimbabwe) rely on drug resistance data gathered from studies conducted in the late 1990s and should consider implementing repeat surveys. Central and Francophone Africa remain the parts of the world where drug resistance surveillance data are most lacking, largely as a result of the current weak laboratory infrastructure. Efforts should be made to increase diagnostic and surveillance capacity in these settings so that a drug resistance survey can be conducted. Of the 136 countries with surveillance data on drug resistance, 35% (48 countries) have only one data point and should consider repeating surveys to assess time trends. Data on time trends in drug resistance were available from 88 countries and 10 territories worldwide for a total of 870 country-year data points. Among the 36 high TB and high MDR-TB burden countries, 11 countries (Cambodia, Estonia, Georgia, Latvia, Lithuania, Mozambique, Myanmar, Republic of Moldova, the Russian Federation (7 Federal Subjects), Thailand and Viet Nam) have completed at least two surveys at least five years apart, allowing trends over time to be evaluated. However, for five of these counfigure 4.2

tries (Cambodia, Mozambique, Myanmar, Thailand and Viet Nam) the most recent data are more than five years old. Among the six countries with recent data, in Estonia and Latvia, surveillance data show that the rates of both TB and MDR-TB have been declining. These data suggest that MDR-TB can indeed be controlled once effective policy decisions are put into practice, and the necessary prevention and control measures are implemented. In Lithuania, Georgia, Republic of Moldova and most Federal Subjects of the Russian Federation, MDR-TB rates appear to be stable whereas in Ivanovo Oblast and Mary-El Republic MDR-TB rates are increasing. Extending trend analyses to other countries requires more data from repeat surveys or continuous surveillance systems. NTPs should plan to repeat drug resistance surveys regularly, approximately every five years, until capacity for continuous surveillance is established.

4.1.2 Percentage of new and previously treated TB cases that have MDR-TB Globally, 3.6% (95% CI: 2.1–5.1%) of new TB cases and 20.2% (95%CI: 13.3–27.2%) of previously treated cases are estimated to have MDR-TB ( Table 4.1). These estimates are essentially unchanged from 2011. The proportions of new and previously treated TB cases with MDR-TB at the country level are shown in Figure 4.2 and Figure 4.3, and for the 27 high MDR-TB burden countries in Table 4.1. Eastern European and especially central Asian countries continue to have the highest levels of MDRTB. Among new cases, examples include Azerbaijan (22.3% in 2007), Belarus (34.8% in 2012), Estonia (19.7% in 2012),

Percentage of new TB cases with MDR-TBa

Percentage of cases 0 2.9 3 5.9 6 11.9 12 17.9 ≥18 No data Subnational data only Not applicable a

Figures are based on the most recent year for which data have been reported, which varies among countries.

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Table 4.1

Estimated proportion of TB cases that have MDR-TB, globally and for 27 high MDR-TB burden countries and WHO regions Estimated % of new TB cases with MDR-TB a Estimated % of retreatment TB cases with MDR-TB a

Confidence interval

Confidence interval

Armenia Azerbaijan Bangladesh Belarus Bulgaria China DR Congo Estonia Ethiopia Georgia India Indonesia Kazakhstan Kyrgyzstan Latvia Lithuania Myanmar Nigeria Pakistan Philippines Republic of Moldova Russian Federation South Africa Tajikistan Ukraine Uzbekistan Viet Nam High MDR-TB burden countries AFR AMR EMR EUR SEAR WPR Global a

9.4 22 1.4 35 2.3 5.7 2.5 20 1.6 9.2 2.2 1.9 23 26 11 11 4.2 2.9 3.5 4.0 24 23 1.8 13 14 23 2.7 4.2 2.3 2.2 3.5 16 2.2 4.7 3.6

7.0–12 19–27 0.7–2.5 33–37 1.3–3.8 4.5–7.0 0.1–5.0 14–26 0.9–2.8 7.9–11 1.9–2.6 1.4–2.5 22–24 23–31 8.8–14 9.5–14 3.1–5.6 2.1–4.0 0.1–12 2.9–5.5 21–26 21–25 1.4–2.3 9.8–16 14–15 18–30 2.0–3.7 2.1–6.2 0.2–4.4 1.4–3.0 0.1–11 10–22 1.6–2.8 3.3–6.1 2.1–5.1

43 56 29 69 23 26 10 50 12 31 15 12 55 68 32 44 10 14 32 21 62 49 6.7 56 32 62 19 21 11 14 33 45 16 22 20

38–49 50–62 24–34 66–71 17–31 22–30 3.5–17 35–65 5.6–21 27–35 11–19 8.1–17 54–56 65–72 23–42 39–49 6.9–14 10–19 7.5–56 14–29 59–65 45–53 5.4–8.2 52–61 31–33 53–71 14–25 12–30 4.4–17 4.7–22 12–54 39–52 11–21 18–27 13–27

Kazakhstan (22.9% in 2012), Kyrgyzstan (26.4% in 2011), the Republic of Moldova (23.7% in 2012), the Russian Federation (average: 23.1%, with Yamalo-Nenets Autonomous Area being the highest: 41.9% in 2011) and Uzbekistan (23.2% in 2011). Among previously treated cases, examples include Azerbaijan (Baku City: 55.8% in 2007), Belarus (68.6% in 2012), Estonia (50.0% in 2012), Kazakhstan (55.0% in 2012), Kyrgyzstan (68.4% in 2012), the Republic of Moldova (62.3% in 2012), Tajikistan (56.0% in 2012) and Uzbekistan (62.0% in 2011). In the Russian Federation, even though the average proportion of cases with MDRTB does not exceed 50%, the proportion is well above 50% in several Federal Subjects (with Ulyanovsk Oblast at the highest level: 74.0% in 2011).1

Box 4.1

MDR-TB in children TB in children poses a diagnostic challenge, as paucibacillary disease is more likely. Specimens suitable for culture and DST are more difficult to obtain, particularly from the youngest children who cannot expectorate sputum. Consequently, little is known about the burden of MDR-TB in children. The relationship between MDR-TB and age group (children aged less than 15 years versus adults aged 15 years or older) was recently assessed using representative drug resistance surveillance data reported to WHO between 1994 and 2012. Data were analysed for 376 293 TB cases for whom age and DST data were available. Odds ratios were derived by logistic regression with robust standard errors, as described in detail elsewhere.a Of the 85 countries reporting data from nationwide surveys or surveillance systems, 34 reported at least one paediatric MDR-TB case. A child with TB was shown to be as likely as an adult with TB to have MDR-TB. It is therefore essential that the identification of MDR-TB in children be strengthened. Efforts should be made to systematically conduct household contact investigation of all patients with MDR-TB, including children. Additionally, children must be routinely included in all drug resistance surveillance activities, including drug resistance surveys. a

Zignol et al. Multidrug-resistant tuberculosis in children: evidence from global surveillance. European Respiratory Journal 2013; 42:701–7.

Best estimates are for the latest available year. Estimates in italics are based on regional data.

More positively, levels of drug resistance among new cases remain low (<3%) in many parts of the world, including almost all countries in the Region of the Americas, most African countries where drug resistance surveys have been conducted, most of the South-East Asia Region, most of western Europe, and several countries in the Western Pacific Region (examples include Australia, Cambodia, Japan, New Zealand and Viet Nam). 1

Tuberculosis in the Russian Federation 2011: an analytical review of statistical indicators used in the Russian Federation and in the world (in Russian). Moscow: Ministry of Health of the Russian Federation et al., 2013.

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GLOBAL TUBERCULOSIS REPORT 2013

figure 4.3

Percentage of previously treated TB cases with MDR-TBa

Percentage of cases 0 5.9 6 11.9 12 29.9 30 49.9 ≥50 No data Subnational data only Not applicable a

Figures are based on the most recent year for which data have been reported, which varies among countries. The high percentages of previously treated TB cases with MDR-TB in Bahrain, Bonaire – Saint Eustatius and Saba, Cook Islands, Iceland, Sao Tome and Principe, and Lebanon refer to only a small number of notified cases (< 10).

4.1.3 Estimated global incidence of MDR-TB and estimated number of MDR-TB cases among notified TB patients in 2012 The data compiled from surveillance of drug resistance among TB patients allow estimation of the total number of incident cases of MDR-TB worldwide in 2012. The number of incident cases includes not only cases among notified TB patients, but also cases among people diagnosed with TB that were not notified to NTPs (and in whom MDR-TB may not have been detected) and cases among people not yet diagnosed with TB. Globally in 2012, there were an estimated 450 000 (range: 300 000‒600 000) new cases of MDR-TB. Methods used to produce this estimate are explained in Annex 1. Data compiled from surveillance of drug resistance among TB patients also allow production of global as well as country-specific estimates of the number of MDR-TB cases among notified TB patients with pulmonary TB. These are the MDR-TB cases that could be found by NTPs if all notified patients were tested for drug resistance to rifampicin and isoniazid using WHO-recommended diagnostic tests, and is a useful indicator for assessing country performance in detecting cases of MDR-TB and enrolling them on treatment. Globally in 2012, there were an estimated 300 000 (range: 220  000–380  000) MDR-TB cases among notified TB patients. Country-specific estimates are discussed in section 4.2.

4.1.4 Resistance to second-line drugs Extensively drug-resistant TB (XDR-TB) had been reported by 92 countries globally by the end of 2012 (Figure 4.4). A total of 75 countries and 4 territories reported representative data from continuous surveillance or special surveys regarding the proportion of MDR-TB cases that had XDR-TB. Combining their data, the average proportion of MDR-TB cases with XDR-TB was 9.6% (95% CI: 8.1%–11%), similar to the estimate from 2011 (9.0%). Thirteen of these countries reported more than 10 XDR-TB cases in the most recent year for which data were available. Among those countries, the proportion of MDR-TB cases with XDRTB was highest in Azerbaijan (Baku city: 12.8%), Belarus (11.9%), Latvia (16.0%), Lithuania (24.8%) and Tajikistan (Dushanbe city and Rudaki district: 21.0%). The proportion of MDR-TB cases with resistance to fluoroquinolones and second-line injectable agents was 16.5% (95% CI: 12.3–20.7) and 22.7% (15.4%–30.0%), respectively. A total of 32.0% (21.9%–42.1%) of patients with MDRTB have resistance to a fluoroquinolone, a second-line injectable agent, or both. These patients would likely be eligible to receive bedaquiline, the new bactericidal drug recently approved for use in patients with MDR-TB when options to treat using existing drugs have been exhausted (see Box 8.2 in Chapter 8).

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figure 4.4

Countries that had notified at least one case of XDR-TB by the end of 2012

At least one case reported No cases reported Not applicable

4.2 Management of drug-resistant TB 4.2.1 Coverage of drug susceptibility testing (DST) The diagnosis of DR-TB requires TB patients to be tested for susceptibility to drugs. Notification data combined with data from drug resistance surveillance suggest that if all notified TB patients with pulmonary TB had been tested in 2012, around 300 000 cases of MDR-TB would have been found (section 4.1.3). Targets included in the Global Plan to Stop TB 2011–2015 are that by 2015 all new cases of TB considered at high risk of MDR-TB (estimated to be about 20% of all new bacteriologically-positive TB cases globally), as well as all previously treated cases, should undergo DST for at least the first-line drugs rifampicin and isoniazid. Similarly, all patients with MDR-TB should be tested for XDR-TB. First-line DST results were reported by just over 50% of countries in 2012 and overall for a small proportion of cases ( Table 4.2). Globally, only 5% of new bacteriologically-confirmed TB cases and 9% of those previously treated for TB were tested for MDR-TB in 2012. The proportion of new cases with DST results has increased slightly in recent years but remains below the target envisaged for 2012 by the Global Plan (Figure 4.5). Coverage was highest in the European Region, where 72% of new cases and 41% of previously treated cases were tested for MDR-TB in 2012, reflecting the relatively better access to TB laboratory services than elsewhere. Levels of testing were particularly low in the African and South-East Asia Regions (0.3% and 0.1% of new bacteriologically cases and 3.1% and 0.7% of previously treated cases, respectively).

Among the 27 high MDR-TB burden countries – which account for >85% of estimated MDR-TB cases in the world – the proportion of TB patients who were tested ranged from 56 to 100% among new cases in 13 of the 14 European countries reporting data (17% in Tajikistan; no data reported by Azerbaijan), and exceeded 60% among previously treated cases in nine of these countries. Among non-European high MDR-TB burden countries, testing for MDR-TB among new cases was highest in China (3.6%). In previously treated cases, the coverage of testing was higher and reached 10% in Indonesia and 12% in China and the Philippines. In South Africa, 16% of TB cases overall were tested for MDR-TB although DST data were not available separately for new and previously treated cases. Five other countries did not report data, including India, the country estimated to have the highest number of MDR-TB cases among notified TB patients ( Table 4.2). Among TB patients who were notified and confirmed to have MDR-TB in 2012, 23% were reported to have DST performed for both fluoroquinolones and second-line injectable drugs. Second-line DST coverage exceeded 90% in Armenia, Bulgaria, the Democratic Republic of the Congo, Georgia and Latvia. South Africa accounted for most of the global cases for which second-line DST data were reported, as well as the highest proportion observed in the African Region (the regional figure drops from 62% to 1% when South Africa is excluded). Second-line DST reports were available for 53% of MDR-TB cases in the Western Pacific Region, 47% in the Region of the Americas and 3–8% in the other regions. Improving the coverage of diagnostic DST is urgently needed to improve the detection of MDR-TB and XDR-TB.

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Table 4.2

DST coverage among TB and MDR-TB cases, globally and for 27 high MDR-TB burden countries and WHO regions, 2012 New bacteriologically-positive cases Number with DSTa results % of cases with DST results Retreatment cases Number with DSTa results % of cases with DST results Confirmed MDR-TB cases Number with DST b results % of cases with DST results

Armenia Azerbaijan Bangladesh Belarus Bulgaria China DR Congo Estonia Ethiopia Georgia India Indonesia Kazakhstanc Kyrgyzstan Latvia Lithuania Myanmar Nigeria Pakistan Philippines Republic of Moldova Russian Federation South Africa Tajikistan Ukraine Uzbekistan Viet Nam High MDR-TB burden countries AFR AMR EMR EUR SEAR WPR Global

286 41 2 164 687 11 472 12 193 469 1 931 2 8 154 958 666 1 017 11 461 35 1 264 32 647 919 11 185 2 703 77 277 2 216 28 625 1 990 85 962 1 352 16 485 136 630

64 – <0.1 90 71 3.6 <0.1 100 1.0 84 – <0.1 >100 57 97 100 – <0.1 0.4 <0.1 67 79 – 17 77 56 – 3.9 0.3 22 1.1 72 0.1 3.3 5.1

108 557 1 183 142 4 861 95 46 180 541 821 10 443 662 100 350 94 154 2 038 933 12 324 496 5 925 798 42 851 3 969 5 481 1 617 37 774 2 292 8 134 59 267

27 – 7.0 84 45 12 1.3 82 4.4 45 – 10 93 61 88 100 – 1.2 1.3 8.7 63 24 – 66 72 30 – 7.7 3.1 23 7.6 41 0.7 10 8.7

92 142 49 2 042 65 55 341 597 184 511 106 210 84

100 – 28 – 100 68 100 89 – 99 3.6 43 – 53 96 77 11 – – – – –

11 046 345 356 16 225 11 303 1 384 51 2 523 1 619 2 365 19 245

72 50 – 21 – 21 62 47 3.2 6.7 8.4 53 23

Blank cells indicate data not reported. – indicates values that cannot be calculated. a DST is for isoniazid and rifampicin. b DST is for a fluoroquinolone and a second-line injectable drug. c A possible explanation for why the percentage for new cases in Kazakhstan exceeds 100% is inadequate linkages between clinical and laboratory registers.

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figure 4.5

DST coverage among new cases and enrolment on MDR-TB treatment, compared with the targets in the Global Plan to Stop TB, 2011–2015. Lines indicate the planned targets, blue squares show the situation in 2009–2012 and orange circles the projected enrolments 2013–2015. Data on projected enrolments in 2015 were incomplete. 25 20 Percentage of cases Number of patients 15 10 5 0 2009 a. DST coverage among new bacteriologically positive cases 300 000 250 000 200 000 150 000 100 000 50 000 0 2009 b. Enrolment on MDR TB treatment

2010

2011

2012

2013

2014

2015

2010

2011

2012

2013

2014

2015

Box 4.2

XDR-TB in Africa In 2006, a cluster of XDR-TB patients in rural South Africa made international headlines.a All of the patients from this cluster who were tested for HIV were found to be infected. Most of these patients died very quickly. South Africa remains the country that reports the most XDR-TB cases in the world and annual notifications have increased from 467 in 2009 to 1 596 in 2012. About 10% of MDR-TB cases reported in this country have XDR-TB. Figure B4.2.1

This requires the strengthening of laboratory capacity, the introduction of new rapid diagnostics and improved reporting from diagnostic centres (see Chapter 5). The identification of XDR-TB cases in countries worldwide (Box 4.2, Figure 4.4) reflects the risk of acquisition of additional second-line drug resistance and the transmission of resistant strains when TB care and prevention (including infection control) are inadequate.

4.2.2 Notification of MDR-TB cases and enrolment on treatment The low coverage of DST in many countries is one of the main constraints limiting the detection of MDR-TB among people diagnosed with TB. Globally, 83 715 cases of MDRTB were notified to WHO in 2012, with India, the Russian Federation and South Africa reporting more than a half of these cases ( Table 4.3). In addition, just over 10 000 rifampicin-resistant TB (RR-TB) cases were reported to have been detected using rapid molecular techniques.1 India, Kyrgyzstan, the Philippines and Uzbekistan each reported >500 of such cases. The 83 715 reported cases of MDR-TB cases represented 28% of the 300 000 (range, 220 000–380 000) pulmonary TB patients estimated to have MDR-TB in 2012 ( Table 4.3), up from 20% in 2011, and 19% of the 450 000 (range: 000‒600  000) estimated incident MDR-TB cases in 300  the world in 2012. Much of the increase between 2011 and 2012 was accounted for by India (4237 to 16 588), South Africa (10  085 to 15  419)2 and Ukraine (4305 to 6934), although increases were reported by a total of 17 high MDR-TB burden countries and all WHO regions with the exception of the Region of the Americas. In the Democratic 1

Treatment outcomes for 623 TB patients with XDRTB in South Africa, 2010 Completed 6% Died 49% Cured 12%

Not evaluated 17% Treatment failed 8%

Lost to follow up 9%

By the end of 2012, 15 countries in the African region had identified and reported at least one case of XDR-TB (Figure 4.4). In 2012, two high MDR-TB burden countries in the African Region – the Democratic Republic of the Congo and Nigeria – each reported their first XDR-TB case. Seven African countries reported starting XDR-TB patients on treatment in 2011 or 2012, most of them in South Africa. Treatment outcomes reported by South Africa reveal the very low likelihood of a favourable outcome in such patients and the high proportion of patients lost to or not evaluated by the health services (see Figure B4.2.1). a

Gandhi NR, Moll A, Sturm AW, Pawinski R, Govender T, Lalloo U, et al. Extensively drug-resistant tuberculosis as a cause of death in patients co-infected with tuberculosis and HIV in a rural area of South Africa. The Lancet. 2006; 368(9547):1575–80.

These are in addition to other rifampicin-resistant cases detected by Xpert MTB/RIF, which were included under MDR-TB notifications following subsequent testing for isoniazid resistance. 2 In South Africa, the number of cases detected was above the estimated number of cases among pulmonary TB patients; this could reflect either that the estimates of the number of MDR-TB cases among TB patients are too conservative and/or the absence of linkages between the clinical and laboratory registers.

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Table 4.3

Estimated MDR-TB cases in 2012, notified cases of MDR-TB and enrolments on MDR-TB treatment 2009–2012, and treatment outcome reporting for 2010 cohort, globally and for 27 high MDR-TB burden countries and WHO regions Estimated MDR-TB among notified pulmonary TB cases, 2012 notified cases Cases enrolled on MDR-TB treatment MDR-TB cases reported with treatment outcome data, 2010 cohort

Best

Low

High

2009

2010

2011

2012

2012 notified / estimated (%)a

2009

2010

2011

2012

N

%b

Armenia Azerbaijan Bangladesh Belarus Bulgaria China DR Congo Estonia Ethiopia Georgia India Indonesia Kazakhstan Kyrgyzstan Latvia Lithuania Myanmar Nigeria Pakistan Philippines Republic of Moldova Russian Federation South Africa Tajikistan Ukraine Uzbekistan Viet Nam High MDR-TB burden countries AFR AMR EMR EUR SEAR WPR Global

250 2 800 4 200 2 200 100 59 000 2 900 70 2 100 630 64 000 6 900 8 800 1 800 120 300 6 000 3 600 11 000 13 000 1 700 46 000 8 100 910 6 800 4 000 3 800 270 000 38 000 7 100 18 000 74 000 90 000 74 000 300 000

220 2 600 3 100 2 100 78 52 000 670 56 1 200 570 49 000 5 200 8 700 1 600 100 270 4 600 2 700 0 10 000 1 600 43 000 6 900 800 6 500 3 700 3 000 180 000 14 000 4 500 0 60 000 71 000 57 000 220 000

280 3 000 5 200 2 200 130 66 000 5 100 85 3 000 690 79 000 8 500 9 000 1 900 140 330 7 500 4 500 29 000 16 000 1 800 49 000 9 400 1 000 7 000 4 300 4 600 350 000 62 000 9 600 42 000 88 000 110 000 91 000 380 000

156

177 552 339

79 811 509 1 594 55 1 601 121 78 212 475 4 237 383 7 408 806 105 296 690 95 344 1 148 1 001 13 785 10 085 604 4 305 1 385 601

92 596 513 1 604 49 3 007 65 62 284 346 16 588 428 7 608 958 110 271 778 107 1 602 679 894 13 612 15 419 694 6 934 1 728 273

37 21 12 73 49 5.1 2.2 89 14 55 26 6.2 86 53 92 90 13 3.0 15 5.2 53 30 >100 76 >100 43 7.2 28 48 42 12 50 21 6.0 28

134

154 286

88 592 390 1 446 42 1 155 128 75 199 737 3 384 260 5 261 492 103 296 163 38 344 2 397 765 18 902 5 643 380 4 950 855 578 49 663 7 467 3 087 756 36 313 4 597 4 946 57 166

101 406 513 2 478 36 1 906 179 54 289 665 14 143 426 7 213 790 110 271 442 125 1 045 1 918 853 18 452 6 494 535 7 672 1 491 713 69 320 9 303 3 102 1 602 42 399 15 845 5 070 77 321

132 263 329 1 442 56 1 222 105 64 114 504 2 182 140 5 777 441 88 310 188 23 195 783

75 48 97 91 100 44 121 102 81 140 74 77 78 78 101 100 98 110 44 150 –

352

339 200

1 342 43 474 91 86 233 369 1 660

1 576 56 2 792 87 63 140 359 2 967 182

43 458 176 86 88 266 1 136 20 3 209 545 124 322 64 0 368 501 334 8 143 4 143 52 3 186 464 307 24 521 5 994 3 153 707 17 169 2 040 1 429 30 492

56 1 222 191 63 120 618 2 967 142 5 705 566 87 310 192 23 424 548 791 13 692 5 402 245 3 870 628 101 38 942 7 209 3 249 967 28 336 3 901 2 210 45 872

3 644 785 131 322 815 28 49 1 073 1 069 14 686 9 070 319 3 482 654 217 40 798 10 741 2 884 496 28 157 2 560 2 059 46 897

7 387 566 87 310 192 21 444 522 1 082 13 692 7 386 333 5 336 1 023 101 47 772 9 340 2 661 873 33 776 3 942 4 295 54 887

4 681 4 882 245 3 902 628 97 28 793 6 166 2 374 676 19 496 3 113 2 456 34 281

34 66 74 73 61 96 60 66 89 77 58 79 57 62

52 813 75 301 12 384 3 474 841 34 199 6 615 4 394 18 129 2 967 2 236 36 708 19 202 4 473

61 907 83 715

Blank cells indicate data not reported. – indicates values that cannot be calculated. Notified cases of MDR-TB in 2012 as a percentage of the best estimate of MDR-TB cases among all cases of pulmonary TB in the same year. The percentage may exceed 100% if estimates of the number of MDR-TB are too conservative and if linkage between the clinical and laboratory registers is inadequate. b The percentage of MDR-TB cases originally notified in 2010 with outcomes reported. The percentage may exceed 100% as a result of updated information about MDR-TB cases in 2010, inadequate linkages between notification systems for TB and MDR-TB, and the inclusion in the treatment cohort of cases of MDR-TB cases from a year prior to 2010. a

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figure 4.6

Number of MDR-TB cases estimated to occur among notified pulmonary TB cases, 2012

MDR TB cases 0 199 200 1999 2000 19 999 20 000 49 999 ≥ 50 000 No data Not applicable

Republic of the Congo, the Philippines and Viet Nam, which detected less than 30% of their estimated burden in 2012, MDR-TB notifications decreased between 2011 and 2012. Of the MDR-TB cases reported globally in 2012, most (82%) were detected in either the European Region (36 708), India (16 588) or South Africa (15 419). Countries detecting close to 100% of the TB patients estimated to have MDR-TB in 2012 included Estonia, Kazakhstan, Latvia, Lithuania, South Africa and Ukraine ( Table 4.3). In the African and European Regions and the Region of the Americas, about 50% of the TB patients estimated to have MDR-TB were detected in 2012. The lowest figures were in the two regions with the largest number of cases: the South-East Asia region (21%) and the Western Pacific Region (6%). India and China, the two countries estimated to have the largest numbers of TB patients with MDRTB (both over 50  000, Figure 4.6), strongly influence the overall figures for the South-East Asia and Western Pacific Regions. China and India, together with the Russian Federation – which ranks third globally in total cases of MDR-TB – detected and reported less than one third of the TB patients estimated to have MDR-TB (5%, 26% and 30% respectively). The absolute numbers of TB cases started on second-line treatment for MDR-TB increased from 30  492 in 2009 to 77 321 in 2012 (+154%). There was a 40% increase in enrolments between 2011 and 2012 in the 27 high MDR-TB burden countries, which reflected progress in 20 of these countries and especially in India, Kazakhstan and Ukraine ( Table 4.3). The ratio of the numbers of patients starting treatment with second-line drug regimens for MDR-TB, to those notified with MDR-TB in 2012, was 92% globally 54 GLOBAL TUBERCULOSIS REPORT 2013

(82% when RR-TB cases are included), but was lower in the African (51%) and South-East Asia (83%) Regions ( Table 4.3). Waiting lists of people requiring treatment for MDRTB are persisting or growing in several countries, particularly when additional RR-TB cases diagnosed using Xpert MTB/RIF are taken into account. Diagnosis:treatment gaps of 5% or more were evident in 14 of the high MDRTB burden countries in 2012 (Figure 4.7), and the ratio of MDR-TB cases diagnosed to enrolments on MDR-TB treatment increased by more than 10% between 2011 and 2012 in China, Pakistan and South Africa. The number of XDRTB cases reported worldwide increased from 1464 to 2230 between 2011 and 2012. All the WHO regions reported more XDR-TB cases enrolled on treatment in 2012 than in 2011, reaching 1557 globally in 2012. Common constraints to treatment scale up include a critical shortage of trained staff, insufficient availability of second-line medications, inadequate numbers of facilities for treatment and monitoring, incomplete diagnosis of patients and other weaknesses in the coordination of activities required for effective programmatic management of DR-TB. There is a global shortfall in capacity to place people diagnosed with MDR-TB on treatment, and increased resources for the programmatic management of MDR-TB are urgently required. In a few countries, such as Georgia, the Russian Federation and Ukraine, enrolments have outstripped notifications of MDR-TB in recent years. Possible explanations for this include frequent empirical treatment of TB patients considered at risk of having MDR-TB but for whom a laboratory-confirmed diagnosis is missing, incomplete report-

figure 4.7

MDR-TB cases (orange) and additional rifampicin-resistant TB cases (blue) detected compared with TB cases enrolled on MDR-TB treatment (green) 2009–2012, globally and in 27 high MDR-TB burden countries, 2009–2012 200 150 100 50 0

Armenia 800

Azerbaijan

600

Bangladesh

2500 2000

Belarus

600 400

400

1500 1000 500

200 200 0 0

0

60

Bulgaria

3000

China

200 150 100

DR Congo

100 80 60 40

Estonia

40

2000

20

1000

50 0

20 0

0

0

300

Ethiopia

800

Georgia 15000

India

500 400 300 200

Indonesia

200

600 10000

100

400

5000 100

0

200

0

0

8000

Kazakhstan

1000 750 500

Kyrgyzstan

150

Latvia

350 330

Lithuania

Number of cases

6000 4000 2000 0

100

310 290

250 0

50 270 0 250

Myanmar 800 600 200 400 200 0 100 300

Nigeria

2000 1500 1000 500 0

Pakistan

2500 2000 1500 1000 500

Philippines

0

1100 900 700

Republic of Moldova

20000

Russian Federation 15000

South Africa

800 600 400 200 0

Tajikistan

15000 10000 10000 5000

500 300 5000

0

8000

Ukraine

2000 1500 1000

Uzbekistan

800 600 400

Viet Nam

100 000 80 000 60 000 40 000

Global

6000

4000 500 2000 2009 2010 2011 2012 0 2009 2010 2011 2012 200 0 2009 2010 2011 2012

20 000 0 2009

2010

2011

2012

GLOBAL TUBERCULOSIS REPORT 2013

55

Box 4.3

Pharmacovigilance for TB care A PRACTICAL HANDBOOK ON THE PHARMACOVIGILANCE OF MEDICINES USED IN THE TREATMENT OF TUBERCULOSIS ENHANCING THE SAFETY OF THE TB PATIENT

Pharmacovigilance is defined by WHO as: “The science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drugrelated problem.”

Adverse drug reactions (ADRs) can lead to a TB patient interrupting treatment before completion, thus contributing to avoidable morbidity, drug resistance, treatment failure, reduced quality of life, or death. It is important to routinely monitor the occurrence of ADRs in TB patients on treatment in NTPs. This is particularly relevant in the care of patients with DR-TB and patients who are HIV-positive. Three approaches to pharmacovigilance are in use: "" Spontaneous reporting. This involves the reporting of ADRs – e.g. ototoxicity associated with aminoglycosides – to the national pharmacovigilance centre. "" Targeted spontaneous reporting. This is an extension of spontaneous reporting that can be focused on the surveillance of serious adverse events in specific patient groups, such as patients with MDR-TB. "" Cohort event monitoring (CEM). This is an active form of surveillance, similar in design and management to an epidemiological cohort study. CEM is particularly well suited to the post-marketing surveillance of new drugs. In 2012, WHO produced a handbook on pharmacovigilance for TB.a WHO offers technical assistance to countries for the introduction and strengthening of pharmacovigilance in their programmes. The handbook explains how pharmacovigilance can be effectively implemented in a TB programme through key stakeholders, including regulators and manufacturers, and provides a step-by-step approach to identifying signals, assessing the relationship between an event and a drug, determination of causality, acting on observations and communication of findings. a

(2013) (Figure 4.5b). To reach the targets set out in the Global Plan and advance towards universal access to treatment, a bold and concerted drive is still needed on many fronts of TB care, particularly in the countries where the burden is highest. The capacity to address this challenge has increased in recent years as a result of the intensified technical assistance provided by international organizations. With the reform of the Green Light Committee (GLC) structure in 2011, and the creation of regional level committees (rGLCs) in all six WHO regions, international support to national efforts to strengthen programmatic management of DR-TB is now focused on devolving available resources and technical assistance closer to countries.

4.2.3 Treatment outcomes for MDR-TB and XDR-TB Standardized monitoring methods and indicators have allowed countries to report MDR-TB treatment outcomes in a comparable manner for several years. In 2013, the definitions for treatment outcomes were simplified and the reporting requirements changed to allow for the inclusion of RR-TB cases in the MDR-TB cohort (Box 4.4). The number of cases reported in annual MDR-TB treatment outcome cohorts has tripled between 2007 and 2010, reflecting increases in all regions (Figure 4.8). All high MDR-TB burden countries have now reported treatment outcomes for at least one annual cohort since 2007. A total of 107 countries reported outcomes for more than 34 000 MDR-TB cases started on treatment in 2010 ( Table 4.3). This is equivalent to 62% of the number of MDR-TB cases notified by countries in the same year. The low proportion reflects weaknesses in reporting systems to reconcile outcome data with notifications. The Global Plan envisages that by 2015, all countries will report outcomes for all notified MDR-TB cases. In 2010, only 71 countries – including 13 high MDR-TB burden countries – reported outcomes for a cohort whose size exceeded 80% of the original number of MDR-TB notifications in 2010. Overall, the proportion of MDR-TB patients in the 2010 cohort who successfully completed treatment was 48%, while 28% of cases were reported as lost to follow-up or had no outcome information. Treatment success was highest in the Eastern Mediterranean Region (56%), as well as in the Region of the Americas (54%) where this proportion has increased steadily since 2007 alongside a reduction in the proportion of patients whose treatment outcome was not evaluated. In the 2010 cohort, deaths were highest in the African Region (17%) and the proportion of patients whose treatment failed was highest in the European Region (11%). The Global Plan’s target of achieving at least 75% treatment success in MDR-TB patients by 2015 was only reached by 34/107 countries reporting outcomes for the 2010 cohort, but included three high MDR-TB burden countries: Bangladesh, Ethiopia and Viet Nam. Among a subset of 795 XDR-TB patients in 26 countries, treatment success was 20% overall and 44% of patients died; excluding South Africa, the figures were 27% and 28% respectively (Box 4.2).

A practical handbook on the pharmacovigilance of medicines used in the treatment of tuberculosis: enhancing the safety of the TB patient. Geneva, World Health Organization, 2012 (www.who.int/medicines/ publications/pharmacovigilance_tb/ ).

ing of laboratory data, or enrolment of ‘backlogs’ or waiting lists of MDR-TB patients who were detected before 2012. Among 119 countries reporting sex-disaggregated data for enrolments, the median male:female ratio was 2. Most countries that reported data on MDR-TB patient enrolments did not report the inclusion of any children. In the 44 countries that did, the proportion of children ranged from <1% to 33% of total enrolments. Many countries envisage increases in the number of patients enrolled on treatment for MDR-TB between 2013 and 2015. However, global projections remain well below Global Plan targets, partly as a result of slow rates of increase as well as incomplete information regarding forecasts, notably for China (2015) and the Russian Federation

56

GLOBAL TUBERCULOSIS REPORT 2013

Figure 4.8

Treatment outcomes for patients diagnosed with MDR-TB by WHO region, 2007–2010 cohorts. The total numbers of cases with outcome data are shown beside each bar. Africa 2007 2008 2009 2010 4 570 5 496 6 143 6 166 2007 2008 2009 2010 The Americas 1 458 1 732 2 298 2 374

Eastern Mediterranean 2007 2008 2009 2010 128 262 511 676 2007 2008 2009 2010

Europe 4 097 6 904 12 131 19 496

South East Asia 2007 2008 2009 2010 253 413 1 140 3 113 2007 2008 2009 2010

Western Pacific 453 758 1 027 2 456 20% 40% 60% 80% 100%

0% Global 2007 2008 2009 2010 0% 20% 40% 60% 80% 10 959 15 565 23 250 34 281 100%

Cured Treatment failed

Completed Lost to follow up

Died Not evaluated

Progressing towards the target for treatment success requires the scale up of treatment programmes globally, enhancing the effectiveness of drug regimens, support to patients to avoid treatment interruption and improved data collection. In particular, countries need to analyse the poor treatment outcomes observed in MDR-TB cases and intensify measures to improve adherence and monitoring. TB programmes need to apply a package of services for MDR-TB patients that include free TB and ancillary medications, free laboratory testing, enablers and social support, and the use of short treatment regimens following current WHO policy in selected patients. The treatment of XDR-TB patients in particular remains very unsatisfactory and more effective regimens for this condition are urgently required.

4.2.4 Other aspects of MDR-TB programme management During their illness, patients with MDR-TB may be cared for as either outpatients or within hospitals, usually secondary or tertiary facilities. WHO recommends that, where possible, patients with MDR-TB should be treated using ambulatory or community-based care rather than models of care based principally on hospitalization. National policies and practices differ in the predominant model of care that is employed. Among the high MDR-TB burden countries, the lowest level of hospitalization was reported by the Philippines (5% of MDR-TB patients), while levels in Eastern European countries ranged between 75 and 100% but were lower in Central Asia (30–50% in Kazakhstan, Tajikistan and Uzbekistan). In the African Region, there is wide variation in the extent to which GLOBAL TUBERCULOSIS REPORT 2013 57

patients with MDR-TB are hospitalized, ranging from 10% of patients (Democratic Republic of the Congo) to 100% (Ethiopia and Nigeria). Globally, the average duration of hospital stay ranged from 7 to 240 days (median: 84 days). The number of visits to a health facility after diagnosis of

Box 4.4

WHO definitions of treatment outcomes for RR-TB, MDR-TB and XDR-TB Cured  Treatment completed as recommended by the national policy without evidence of failure AND three or more consecutive cultures taken at least 30 days apart are negative after the intensive phase. Treatment completed  Treatment completed as recommended by the national policy without evidence of failure BUT no record that three or more consecutive cultures taken at least 30 days apart are negative after the intensive phase. Treatment failed  Treatment terminated or need for permanent regimen change of at least two anti-TB drugs because of: "" lack of conversion by the end of the intensive phase; or "" bacteriological reversion in the continuation phase after conversion to negative; or "" evidence of additional acquired resistance to fluoroquinolones or second-line injectable drugs; or "" adverse drug reactions. Died  A patient who died for any reason during the course of treatment. Lost to follow-up  A patient whose treatment was interrupted for two consecutive months or more. Not evaluated  A patient for whom no treatment outcome is assigned (this includes cases ‘transferred out’ to another treatment unit and whose treatment outcome is unknown). Successfully treated  The sum of cured and treatment completed. Cohort  A group of patients where RR-TB has been diagnosed (including MDR-TB and XDR-TB), and who were started on a full course of a second-line MDR-TB drug regimen during a specified time period (e.g. the cohort of MDR-TB cases registered in the calendar year 2010). This group forms the denominator for calculating treatment outcomes. With the revised definitions, any patient found to have drug-resistant TB and placed on second-line treatment is removed from the drug-susceptible TB outcome cohort. This means that management of the basic management unit TB register and of the second-line TB treatment register needs to be coordinated to ensure proper accounting of the outcomes of treatment. More details on the definition of conversion, reversion and the end of the intensive phase are provided in the WHO guidance.a a

MDR-TB also varies markedly among countries, from 30 or less (Bangladesh, the Democratic Republic of the Congo, Estonia, Pakistan, and Viet Nam) to over 600 (Bulgaria, Indonesia, Latvia, Tajikistan and Uzbekistan). Palliative and end-of-life care delivered through homebased or institutional services is fundamental to alleviate the suffering associated with MDR-TB, particularly in patients with advanced disease that is not responding to treatment. Only eleven high MDR-TB burden countries –10 in the European region plus South Africa – reported that they provided such care within the scope of their NTPs. When considered in the context of the poor outcomes reported in patients with MDR-TB and especially XDR-TB, this finding attests to the persistent, huge unmet need for palliative care services in countries with the largest burdens of drug-resistant TB. Among 18 high MDR-TB burden countries providing information on the quality of second-line drugs in the public sector in 2012, two countries reported that all of the drugs that they used conformed only to national regulatory norms. In the other 16 countries, most reported conformity to international standards for all supplies of kanamycin (11), capreomycin (9, with 2 other countries not using it), levofloxacin (10, with 1 other not using it), ethionamide/ prothionamide (12), cycloserine/terizidone (11) and p -aminosalicylic acid (10, with 2 others not using it). More information is required to adequately monitor TB patients on MDR-TB treatment than is needed for drugsusceptible TB. The definitions for monitoring of RR-TB and MDR-TB and their outcomes were revised in 2013 (see Box 3.2 in Chapter 3 and Box 4.4). The employment of electronic systems to manage patient data is therefore strongly encouraged. One of the Global Plan’s targets is that all 27 high MDR-TB countries manage their data on treatment of MDR-TB patients electronically by 2015. By 2012, 19 reported that national databases were in place for MDR-TB patients (see Figure 2.15 in Chapter 2). These systems differ markedly from one country to another, varying from individual patient medical records accessible online to the periodic collation of records from registers across the country. Before introducing electronic systems to handle patient data, WHO recommends that NTPs undertake a detailed assessment of their needs and expectations and then try to match these with the best suited informatics solution. A fragmentary approach with parallel systems dealing with different programme components (for example, management of data for patients with drugsusceptible and drug-resistant TB in separate systems) should be avoided. Guidance on the design and implementation of electronic systems for recording and reporting data was produced by WHO and technical partners in 2012.1

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/HTM/TB/2013.2). Geneva, World Health Organization, 2013 (www. who.int/iris/bitstream/10665/79199/1/9789241505345_eng.pdf ).

4

Electronic recording and reporting for TB care and control. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2011.22).

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Chapter 5

Diagnostics and laboratory strengthening Key facts and messages ■■ The conventional laboratory tests for the diagnosis of TB, which have been used for decades, are sputum smear microscopy and bacterial culture. Diagnosis based on cultured specimens is the reference standard but results take weeks to obtain. Drug susceptibility testing (DST) on cultures is used to detect resistance to first- and second-line TB drugs. ■■ There have been important breakthroughs in TB diagnostics in recent years. In 2010, WHO endorsed the first rapid molecular test that can be used to simultaneously test for pulmonary TB and rifampicin resistance, Xpert® MTB/ RIF. The sensitivity of the test is much better than smear microscopy and is comparable to solid culture. In 2013, a review of the 2010 policy was initiated, to examine the substantial body of new evidence on the use and positioning of Xpert MTB/RIF for the diagnosis of pulmonary, extrapulmonary and paediatric TB. Updated guidance is expected in 2014. ■■ Xpert MTB/RIF is being rapidly adopted by countries. By the end of June 2013, 1402 GeneXpert machines and 3.2 million Xpert MTB/RIF cartridges had been procured by 88 of the 145 countries eligible for concessional prices. Almost half (49%) of reporting low- and middle-income countries and territories indicated that WHO policy guidance on Xpert MTB/RIF had been incorporated into their national guidelines. South Africa is the first country to adopt Xpert MTB/RIF as the primary diagnostic test for TB, replacing smear microscopy. ■■ Laboratory capacity to conduct high-quality sputum smear microscopy requires significant strengthening. Only 14 of the 22 HBCs met the target of having 1 microscopy centre per 100 000 population in 2012, and only eight reported a programme for external quality assessment that covered at least 95% of all centres in the country. ■■ Globally, laboratory capacity to perform DST continues to be low and is not growing quickly enough to ensure that TB patients with MDR-TB are promptly diagnosed. From 2009 to 2012, the percentage of new and previously treated TB patients receiving DST increased from 4% to 5% and from 6% to 9%, respectively. The EXPAND-TB project, which started in 2009 and has entered a phase of routine testing in 25 countries, shows how it is possible to introduce routine testing for drug resistance and achieve considerable increases in the number of MDR-TB cases detected. ■■ The national reference laboratory of Uganda has become the newest member of the WHO/Global Laboratory Initiative (GLI) Supranational Reference Laboratory (SRL) Network, filling a critical geographical gap in East Africa.

The early, rapid and accurate detection of TB and drug resistance relies on a well-managed and equipped laboratory network. Laboratory confirmation of TB and drug resistance is critical to ensure that people with TB signs and symptoms are correctly diagnosed and have access to the correct treatment as soon as possible. The conventional laboratory tests for the diagnosis of TB, which have been used for decades, are sputum smear microscopy and culture. Diagnosis based on culture is the reference standard but results take weeks to obtain. Drug susceptibility testing (DST) on cultured specimens is the conventional method used to detect resistance to first- and second-line TB drugs. Following increased investments in TB research and development in the past decade (Chapter 8), there have been important breakthroughs in TB diagnostics. In 2008, rapid molecular tests (line probe assays, or LPAs) for detection of RR-TB and MDR-TB using positive sputum specimens or cultures were recommended by WHO. In 2010, the first rapid molecular test that can be used to simultaneously test for TB and rifampicin resistance, Xpert® MTB/RIF (Cepheid, Sunnyvale, CA, USA), was recommended for diagnosis of pulmonary TB and rifampicin resistance in adults. The sensitivity of the test is much better than smear microscopy and similar to solid culture.1 Although laboratories play a fundamental role in TB care and control, only 57% of the 4.6 million new pulmonary TB patients notified globally in 2012 were bacteriologically confirmed using a WHO-recommended diagnostic method. Low coverage of laboratory confirmation may result in people without TB needlessly being enrolled on TB treatment, while true TB cases are being missed. Furthermore, the 5.7 million incident (new and relapse) TB patients diagnosed and notified to NTPs in 2012 represent only 66% of the estimated 8.6 million incident TB cases globally. The gap reflects both underreporting of diagnosed TB cases and failure to diagnose cases at all; the latter can be attributed in part to weak laboratory capacity in many countries. Detection of TB without investigating for drug resistance can lead to poor treatment outcomes, additional and unnecessary suffering and costs for patients and further spread of drug-resistant strains. While there was a small increase between 2011 and 2012, only 5.1% of new cases and 8.7% of previously treated cases received DST in 2012. 1

Steingart KR et al. Xpert® MTB/RIF assay for pulmonary tuberculosis and rifampicin resistance in adults (Review). Cochrane Database of Systematic Reviews 2013, Issue 1. Art. No.: CD009593. 2013.

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Of the 300 000 cases of MDR-TB estimated to exist among notified TB patients with pulmonary TB in 2012 (i.e. the group of patients known to NTPs and that could be tested for drug resistance using WHO-recommended diagnostic tests), only 83 715 received a laboratory-confirmed diagnosis of MDR-TB and were notified in 2012. In addition, just over 10 000 RR-TB cases were detected using rapid molecular methods, though without results for isoniazid DST at the time of reporting. Given the large burden of undiagnosed DR-TB, strengthening DST capacity is a high priority for NTPs (see also Chapter 4). This chapter has three parts. Section 5.1 summarizes the key developments in WHO guidance on TB diagnostics and laboratory strengthening during 2012–2013. Section 5.2 provides the status of laboratory capacity globally, regionally and nationally based on data reported to WHO by countries in 2013. The focus is on the 36 countries in the combined list of 22 HBCs and 27 high MDR-TB burden countries. Innovative public–private mix (PPM) laboratory initiatives are highlighted as well. Section 5.3 describes recent achievements in strengthening TB laboratories, covering incorporation of WHO guidance into policy and practice at country level and the latest status of progress of two multinational projects (EXPAND-TB and TBXpert) that are helping to introduce new diagnostics.

5.1 Developments in WHO policy guidance on TB diagnostics and laboratory strengthening, 2012–2013 WHO follows a systematic process for policy development on TB diagnostics, involving synthesis of the available evidence through systematic reviews and meta-analyses where possible, assessment of the evidence by an external Expert Group using the GRADE approach,1 and development of policy guidance2 for dissemination to Member States and other stakeholders.3 Policy documents are reviewed every 3–5 years, and revised as necessary when new evidence becomes available. The first WHO policy guidance on the use of Xpert® MTB/RIF was issued in December 2010. The recommendations were that Xpert MTB/RIF should be used as the initial diagnostic test in individuals at risk of having MDRTB or HIV-associated TB (strong recommendation), and that Xpert MTB/RIF could be used as a follow-on test to microscopy in settings where MDR and/or HIV is of lesser concern, especially in smear-negative specimens (this was a conditional recommendation, recognizing major resource implications). The 2010 recommendations applied to the use of Xpert MTB/RIF in sputum specimens only, as data on its performance (sensitivity and specificity) for testing of extrapulmonary specimens at that time were limited. The recommendations applied to children, but only based on generalization of data from adults. Following rapid uptake of Xpert MTB/RIF (see section 5.2), a substantial body of new evidence had been generated by 2013.4 This included much more data about the test’s performance characteristics (sensitivity and specificity) in

a wide range of laboratory and epidemiological settings, additional data on test accuracy in detection of extrapulmonary and paediatric TB, and more evidence about affordability and cost-effectiveness from early implementers in a limited number of settings. WHO therefore embarked on a review of policy guidance in 2013. Three systematic reviews were commissioned on the sensitivity and specificity of Xpert MTB/RIF for the diagnosis of pulmonary and extrapulmonary TB and RR-TB, in adults and children. A review of published studies on the affordability and cost-effectiveness of Xpert MTB/RIF was also conducted. An Expert Group convened by WHO met in May 2013 to review the expanded body of evidence, according to GRADE procedures. Based on the outcomes of the review and the recommendations of the Expert Group, which were also supported by WHO’s Strategy and Technical Advisory Group for TB (STAG-TB) in June 2013, updated WHO policy guidance was under development at the time that the current report went to press. Upon finalization, the recommendations are expected to have a major impact on further country adoption of Xpert MTB/RIF into diagnostic and clinical algorithms. Several other new TB diagnostic tests are on the horizon, in various stages of research and development (see Chapter 8). Once data on their performance are available in varying epidemiological settings, WHO will be in a position to evaluate their performance and develop corresponding policy guidance. A comprehensive list of existing WHO policy documents, including those on the use of microscopy, culture, DST and non-commercial and molecular methods, can be found at: http://www.who.int/tb/laboratory/policy_ statements In addition to diagnostics, WHO also develops guidance in other areas of laboratory strengthening. In 2013, the WHO Tuberculosis laboratory biosafety manual was issued, featuring a risk-based approach that guides the essential biosafety measures required for performing different technical procedures. The manual describes the combination of good laboratory practices together with administrative controls, containment principles, safety equipment and laboratory facilities that are required to minimize the generation of infectious aerosols and thus prevent laboratory-acquired infections. The risk-based approach to laboratory biosafety is framed around a threetiered system of ‘low’, ‘moderate’ and ‘high’ TB risk precautions: 1 2

www.gradeworkinggroup.org WHO handbook for guideline development. Geneva, World Health Organization, 2012. 3 WHO policies on TB diagnostics are available at: www.who.int/tb/ laboratory/policy_statements 4 Weyer K et al. Rapid molecular TB diagnosis: evidence, policy-making and global implementation of Xpert® MTB/RIF. European Respiratory Journal. November 22, 2012, doi: 10.1183/09031936.00157212

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 Low TB risk precautions. These apply to direct acid-fast bacilli (AFB) microscopy and to Xpert MTB/RIF.  Moderate TB risk precautions. These apply to the processing of sputum specimens for primary culture inoculation, direct testing (i.e. on sputum smear-positive samples) using direct non-commercial drug susceptibility assays and LPAs.  High TB risk precautions in TB containment laboratories. These apply to procedures used to manipulate cultures (solid and liquid) for identification and DST, and for indirect testing (i.e. on culture isolates) using LPA and non-commercial DST.

5.2 Status of laboratory capacity globally, regionally and nationally Diagnosis of TB in most low- and middle-income countries still relies on low-cost sputum smear microscopy, despite its relatively low sensitivity and inability to detect drug resistance. The Global Plan to Stop TB 2011–2015 includes the target that countries maintain at least one smear microscopy centre per 100 000 population. Globally the target has been met (1.1 centres per 100 000 population in 2012), but considerable disparities remain at regional and country levels ( Table 5.1). Eight of the 22 HBCs did not meet the target in 2012: Bangladesh, China, Myanmar, Nigeria, Pakistan, the Russian Federation, South Africa and Viet Nam. Overall, the Western Pacific and Eastern Mediterranean Regions had less than one centre per 100 000 population. Given the continued critical role of microscopy in TB detection and monitoring of treatment, ensuring high-quality performance of smear microscopy is essential. Of the 153 countries and territories that reported data on the number of smear microscopy centres in 2012, only 39% indicated the existence of an external quality assessment programme that covered all centres in the country. Among the 22 HBCs, only three reported such a programme that encompassed all centres in 2012 (Bangladesh, India and Viet Nam), five reported a programme that included at least 95% of centres (Cambodia, China, Myanmar, the Russian Federation and South Africa), and 14 reported a programme that included at least 80% of centres. In 2009, WHO recommended the use of the more sensitive fluorescent light-emitting diode (LED) microscopy as a replacement for traditional Ziehl–Neelsen (ZN) microscopy. Globally the switch to LED microscopes has been gradual, and they were reported to be present in only 2% of microscopy centres in 2012. Overall in 2012, the African Region was the most advanced in rolling out LED microscopes (6% of microscopy centres), led by South Africa where 97% of microscopy centres were reported to have them. Other HBCs in the African Region have shown significant increases in uptake from 2011 to 2012, including the United Republic of Tanzania (3% to 17% of microscopy centres) and Mozambique (<1% to 9%). The current target in the Global Plan to Stop TB 2011– 2015 for both culture and DST (to at least rifampicin and isoniazid) capacity is one laboratory per 5 million popu-

lation. In 2012, 14 of the 27 high MDR-TB burden countries did not reach the target ( Table 5.1; there were two additional countries that did not report data). Of these 27 countries, 9 reported more than one laboratory per 5 million population using LPAs – a high-throughput molecular tool that can be used at central and regional levels to rapidly detect resistance to rifampicin and, in some cases, isoniazid. The nine countries comprise eight European countries and South Africa. Of the 147 countries and territories that reported numbers of laboratories with capacity to perform DST, 22 indicated that such capacity did not exist in 2012. While countries and territories with small TB patient populations may find it more practical to send specimens to neighbouring countries for DST than to establish national capacity, countries with larger patient populations should aim as a priority to build sustainable DST capacity in-country to allow timely diagnosis of drug-resistant strains. Eight countries reported more than 1000 notified TB cases in 2012 yet reported having no capacity to perform DST: Afghanistan, Chad, Eritrea, Guinea-Bissau, Liberia, Papua New Guinea, Sierra Leone and Somalia. Quality-assured DST is critical to ensure accurate detection of drug resistance for subsequent treatment decisions and to avoid false diagnoses. Of the high TB and MDR-TB burden countries that reported on external quality assessment coverage of DST laboratories (34 of 36), 27 (79%) reported having a scheme that encompassed all DST laboratories. Of the 117 countries globally that reported on external quality assessment coverage of DST laboratories, 70% (82 countries) reported such a scheme. Given its high sensitivity to detect TB and rifampicin resistance together with its ability to be placed at relatively low levels of laboratory networks, Xpert MTB/RIF has been rapidly adopted by countries. By the end of June 2013, 3.2 million test cartridges and 1402 GeneXpert machines (comprising 7553 machine modules) had been procured in 88 of the 145 countries eligible to purchase machines and cartridges at concessional prices (Figure 5.1).1 The current price per cartridge is US$ 9.98, following a novel financing agreement reached in August 2012 between the manufacturer and the United States Agency for International Development (USAID), the United States President’s Emergency Plan for AIDS Relief (PEPFAR), UNITAID and the Bill & Melinda Gates Foundation. South Africa alone accounts for 43% of the modules and 60% of the cartridges procured globally, and is aiming to position Xpert MTB/RIF as a replacement for microscopy for the diagnosis of TB. After South Africa, leading procurers include India, Pakistan, Zimbabwe and Nigeria. The complete or partial replacement of microscopy by Xpert MTB/RIF as the initial diagnostic test and the increasing number of rifampicin-resistant cases being detected by Xpert MTB/RIF will require adjustment of countries’ smear, culture and DST capacities going forward. 1

http://www.who.int/tb/laboratory/mtbrifrollout/

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Table 5.1

Laboratory capacity, 2012a SMEAR MICROSCOPY PERCENTAGE OF LABORATORIES USING LED MICROSCOPES CULTURE LABORATORIES PER 5 MILLION POPULATION DRUG SUSCEPTIBILITY TESTING NUMBER OF LABORATORIES LABORATORIES PER 5 MILLION POPULATION LINE PROBE ASSAY XPERT MTB/RIF

Yes   Armenia

No  

HIGH TB BURDEN

HIGH MDR-TB BURDEN

NUMBER OF LABORATORIES

LABORATORIES PER 100 000 POPULATION

NUMBER OF LABORATO RIES

NUMBER OF LABORATORIES

LABORATORIES PER 5 MILLION POPULATION

NUMBER OF SITES

Afghanistan Azerbaijan Bangladesh Belarus Brazil Bulgaria Cambodia China DR Congo Estonia Ethiopia Georgia India Indonesia Kazakhstan Kenya Kyrgyzstan Latvia Lithuania Mozambique Myanmar Nigeria Pakistan Philippines Republic of Moldova Russian Federation South Africa Tajikistan Thailand Uganda Ukraine UR Tanzania Uzbekistan Viet Nam Zimbabwe High-burden countries

                                   

                                   

603 30 72 1 070 196 4 000 34 214 3 328 1 522 5 2 531 11 13 098 5 566 466 1 818 122 16 300 458 1 314 1 388 2 565 1 031 187 89 1 081 1 152 821 945 291 800 185 – – – – – – – – –

2.0 1.0 0.8 0.7 2.1 2.0 0.5 1.4 0.2 2.3 0.4 2.8 0.3 1.1 2.3 2.9 4.2 2.2 0.8 – 1.2 0.9 0.8 0.8 2.7 – 0.7 0.4 1.1 1.6 3.2 1.8 2.0 1.0 0.9 1.3 1.0 0.9 1.5 2.2 0.8 0.7 1.2 0.5 1.1

2 0 4 2 2 – 0 10 2 <1 100 0 9 2 0 0 8 0 0 – 9 14 2 <1 <1 – – 97 4 6 8 5 17 1 <1 1 2 2 6 <1 <1 2 2 2 2 – – – – – – – – –

2 1 7 3 29 220 31 3 1 014 4 2 5 2 70 46 22 2 11 4 3 2 5 7 13 117 15 3 65 4 86 4 7 25 2

0.3 1.7 3.8 < 0.1 15 5.5 21 1.0 3.7 0.3 7.7 0.3 2.3 0.3 0.9 6.8 0.2 10 9.7 – 0.6 0.2 0.1 0.2 0.7 – 4.1 1.4 1.9 4.9 0.6 9.4 0.4 1.2 1.4 0.7 1.8 1.9 0.6 16 1.4 9.8 0.5 3.4 3.8

0 1 3 3 8 35 14 1 190 2 2 1 1 38 5 22 2 3 1 2 2 3 4 3 110 15 1 18 4 41 1 3 2 2 – – – – – – – – –

0 1.7 1.6 < 0.1 4.3 0.9 9.6 0.3 0.7 0.2 7.7 < 0.1 1.1 0.2 0.1 6.8 0.2 2.7 2.4 – 0.4 0.2 < 0.1 0.1 0.2 – 3.8 1.4 0.6 1.3 0.6 4.5 0.1 0.5 0.1 0.7 0.5 0.6 0.4 0.8 0.4 4.6 0.2 0.6 0.9

0 1 1 1 8 8 4 0 21 1 2 5 2 33 2 11 2 2 1 0 2 4 2 1

0 1.7 0.5 < 0.1 4.3 0.2 2.7 0 < 0.1 < 0.1 7.7 0.3 2.3 0.1 < 0.1 3.4 0.2 1.8 2.4 – 0 0.2 0.1 < 0.1 < 0.1 – –

1 0 7 12 8 13 0 6 16 26 2 7 1 32 9 4 15 7 2 12 3 32 15 17

15 1 12 4 0 3 3 2 0 – – – – – – – – –

1.4 0.6 0.9 0.6 0 0.3 0.5 0.1 0 0.1 0.2 0.3 0.2 0.1 1.8 0.1 0.1 0.3

100 3 14 25 15 13 7 22 17 – – – – – – – – –

High MDR-TB burden countries AFR AMR EMR EUR SEAR WPR Global

Blank cells indicate data not reported. – indicates values that cannot be calculated. a The regional and global figures are aggregates of data reported by low- and middle-income countries and territories. Data for the variables shown in the table are not requested from high-income countries in the WHO data collection form.

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figure 5.1

Progress in the roll-out of Xpert MTB/RIF, by July 2013

Xpert MTB/RIF cartridges ordered 0 1 1999 2000 9999 10 000 39 999 40 000 99 999 ≥ 100 000 Not eligible for preferential pricing Not applicable

The introduction of Xpert MTB/RIF reduces the need for culture as a diagnostic test, yet the growing number of RR-TB cases will require culture for monitoring of treatment and DST of other anti-TB drugs to guide the design of treatment regimens. The increasing capacity of countries to diagnose RR-TB must also be matched by increased capacity to provide appropriate treatment to the diagnosed cases (see also Chapter 4). One of the main reasons for low case detection rates in many parts of the world (Chapter 3) is the existence of a significant private sector, in which care providers frequently diagnose people with TB but fail to notify these cases to national authorities. The quality of diagnostic services in the private sector is highly variable, and some private practitioners continue to use tests that are not recommended by WHO, including antibody-based serodiagnostics and interferon-gamma release assays (IGRAs) for detection of active TB. Furthermore in some settings, laboratories in the public sector that are not under the auspices of the NTP also diagnose TB without necessarily following recommended guidelines and quality assurance procedures. Collaboration between NTPs and all laboratories offering TB diagnosis is therefore critical to ensure that national guidelines are followed, that appropriate diagnostic tests are used, and that patients diagnosed with TB are notified to the NTP and receive proper care. In 2012, 20 of 36 high TB and MDRTB burden countries reported some level of collaboration with laboratories in the private sector, and 25 reported collaboration with non-NTP laboratories in the public sector. Additionally, the availability of WHO-recommended diagnostic tests at concessional prices from manufacturers

under specified conditions has been used as leverage by new initiatives to form innovative PPM partnerships, increasing access to WHO-recommended diagnostics for people seeking care in the private sector. Examples are provided in Box 5.1.

5.3 Strengthening TB laboratories globally, regionally and nationally Advances in TB diagnostics in recent years provide an opportunity to improve laboratory capacity to rapidly and accurately detect TB and drug resistance. One of the main prerequisites for effective uptake of new diagnostics is dynamic policy reform, properly incorporating new tests and testing methods into diagnostic algorithms. Table 5.2 presents the uptake of selected WHO policy guidance on TB diagnostics into NTP guidelines at global, regional and country levels, focusing on the 36 countries in the combined list of 22 HBCs and 27 high MDR-TB burden countries. Overall, high burden countries have been faster in adopting WHO TB diagnostic guidelines than the global average. All reporting high MDR-TB burden countries, 95% of HBCs and 84% of reporting countries globally had reported incorporation of the WHO policy guidance on conventional phenotypic DST into their national guidelines by 2012. Three quarters (74%) of all countries globally had incorporated guidance on liquid culture and rapid speciation. Countries in the European Region have been particularly fast in adopting these policies, with 97% of countries reporting having taken up these technologies. Uptake of WHO policy on use of LPAs for detection of resistance to rifampicin remains relatively modest, with GLOBAL TUBERCULOSIS REPORT 2013 63

Box 5.1

Innovative PPM initiatives to increase access to WHO-recommended diagnostics Some manufacturers of rapid diagnostics, including Becton, Dickenson and Company (producer of the BD MGIT™ 960 automated liquid culture system), Hain LifeScience (Genotype® MTBDRplus line probe assay) and Cepheid (Xpert® MTB/RIF) offer their products to NTPs and their not-for-profit partners in low- and middle-income countries at concessional prices. Private for-profit sector laboratories have traditionally not been included in such arrangements, resulting in prices that are prohibitively high for poor people seeking care in the private sector and encouraging use of other diagnostics that are not recommended by WHO. Recently, two public–private mix (PPM) initiatives that aim to increase access to rapid and accurate diagnostics for vulnerable populations in Asian settings with vast private sector markets have been established. In June 2012, the government of India took the unprecedented step of banning the import, manufacture, distribution and sale of antibody-based TB serodiagnostic tests, in line with the WHO recommendation that such tests should not be used to diagnose TB. Unfortunately, this ban created a gap in the private market that allowed other suboptimal tests to gain market share, especially since TB diagnostics recommended by WHO were considered too expensive and well beyond the reach of the typical TB patient. To overcome this market shortcoming, the Initiative for Promoting Affordable, Quality TB Tests (IPAQT)a in India was launched in March 2013. IPAQT is a consortium of 42 private diagnostic laboratories supported by not-for-profit stakeholders (examples include the Clinton Health Access Initiative and the McGill International TB Centre). It has established agreements with Cepheid Inc, Hain LifeScience, and Becton, Dickenson and Company that allow access to concessional prices for Xpert MTB/RIF, first-line line probe assays, and liquid culture in the private sector, which is normally excluded from negotiated pricing agreements. Participating laboratories must abide by several conditions: they need to be accredited to assure quality; they must report confirmed cases to the Revised National TB Control Programme (RNTCP); they must adhere to a ceiling price when charging patients; and they must refrain from using any tests that are not recommended by WHO or the RNTCP. Together, the laboratories participating in IPAQT have approximately 3000 franchisee laboratories and over 10 000 specimen collection centres across India, thus increasing access to rapid, accurate and affordable diagnostics for patients seeking care in the country’s extensive private sector. As part of the recently launched UNITAID-funded TBXpert project (Box 5.2) and with support from the Stop TB Partnership TB REACH initiative funded by the Department of Foreign Affairs, Trade and Development of Canada, innovative social business models have been formed in Bangladesh, Indonesia and Pakistan by Interactive Research and Development in cooperation with local partners and NTPs. Based in the megacities of Dhaka, Jakarta and Karachi and equipped with up to 25 GeneXpert instruments each, these social business models will provide Xpert MTB/RIF tests received from the TBXpert project free of charge to people at high risk of TB who seek care at private screening centres and other partnering locations. Free treatment will be provided to everyone diagnosed with TB, in cooperation with NTPs. Revenue will be generated from adjunct tests and services provided to patients, allowing for sustainability of the businesses beyond the duration of the three-year TBXpert project. a

www.ipaqt.org/

only 58% of countries globally adopting the policy to date. Uptake is, however, growing. In the Region of the Americas, for example, 61% of countries reported incorporation of the policy in their national guidelines in 2012 compared to only 17% in 2011. Approximately half of low- and middle-income countries and territories globally (49%) indicated that they had incorporated WHO guidance on Xpert MTB/RIF into their diagnostic algorithms for people at risk of HIV-associated and DR-TB by the end of 2012, highlighting fast uptake of recommendations first issued in December 2010. High MDR-TB burden countries have been particularly quick to adopt WHO guidance, with 84% of countries reporting incorporation of the test into their diagnostic algorithms for people at risk of drug-resistant TB. Funding from sources including the Global Fund, PEPFAR, USAID, TB REACH and Médecins Sans Frontières has supported ministries of health to rapidly establish capacity to use Xpert MTB/RIF. These initiatives, together with the TBXpert and EXPANDTB projects, will enable further roll out and scale up of the test in targeted low- and middle-income countries, with

expected increased detection of DR-TB and HIV-associated TB (Box 5.2). The WHO/Global Laboratory Initiative (GLI) TB Supranational Reference Laboratory (SRL) Network is a driving force in strengthening national and central level laboratories globally, providing long-term technical assistance to countries under the framework of collaborative agreements. The network comprises 29 laboratories covering all six WHO regions. The newest addition to the network is the national TB reference laboratory of Uganda; this fills a critical geographical gap that had existed in the network in East Africa. The laboratory has already established collaborative agreements with Somalia, South Sudan and Zambia for provision of technical assistance. Additionally, four candidate SRLs are under mentorship, including the national TB reference laboratories of Benin, Denmark and South Africa, and the Aga Khan University of Pakistan. Pending completion of successful mentorship and the establishment of country partners, the new laboratories will help to widen the geographical reach of the network, in particular in the African and Eastern Mediterranean Regions.

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Table 5.2

Incorporation of WHO guidance for diagnosis of TB into national policy, 2012a CONVENTIONAL DRUG SUSCEPTIBILITY TESTING (DST) LIQUID CULTURE AND RAPID SPECIATION TEST LINE-PROBE ASSAY FOR DETECTING RESISTANCE TO RIFAMPICIN ALGORITHM FOR THE DIAGNOSIS OF TB IN PEOPLE LIVING WITH HIV XPERT MTB/RIF FOR DIAGNOSIS OF TB IN PERSONS AT RISK OF HIV-ASSOCIATED TB XPERT MTB/RIF FOR DIAGNOSIS OF DRUG-RESISTANT TB IN PERSONS AT RISK

Yes   Armenia

No  

HIGH TB BURDEN

HIGH MDR-TB BURDEN

Afghanistan Azerbaijan Bangladesh Belarus Brazil Bulgaria Cambodia China DR Congo Estonia Ethiopia Georgia India Indonesia Kazakhstan Kenya Kyrgyzstan Latvia Lithuania Mozambique Myanmar Nigeria Pakistan Philippines Republic of Moldova Russian Federation South Africa Tajikistan Thailand Uganda Ukraine UR Tanzania Uzbekistan Viet Nam Zimbabwe High-burden countries High MDR-TB burden countries AFR AMR EMR EUR SEAR WPR Global

                                   

                                   

                                  95% 100% 81% 91% 77% 100% 82% 61% 84%

                                  77% 88% 67% 68% 68% 97% 73% 56% 74%

                                 77% 92% 54% 61% 38% 82% 64% 39% 58%

                                  95% 96% 74% 82% 75% 81% 82% 78% 78%

                                  73% 84% 60% 35% 32% 60% 64% 33% 49%

                                  77% 84% 62% 35% 36% 56% 64% 33% 49%

Blank cells indicate data not reported. a The regional and global figures are aggregates of data reported by low- and middle-income countries and territories. Data for the variables shown in the table are not requested from high-income countries in the WHO data collection form.

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Box 5.2

The EXPAND-TB and TBXpert projects: progress to date Launched in 2009 and continuing until the end of 2014, the EXPAND-TB project aims to accelerate and expand access to diagnostics for patients at risk of MDR-TB in 27 countries. EXPAND-TB has full ownership by the ministries of health of the recipient countries and works on a model of best practices, learning-by-doing, and optimizing resources for laboratory strengthening at country level. The project is a collaboration between WHO, the Global Laboratory Initiative (GLI), the Foundation for Innovative New Diagnostics (FIND) and the Stop TB Partnership Global Drug Facility (GDF), and is funded by UNITAID and other partners. EXPAND-TB builds on US$ 87 million of UNITAID support to maximize resources and technical assistance from multiple partners for laboratory strengthening, including the Global Fund, the World Bank, PEPFAR, USAID, the American Society for Microbiology, the US Centers for Disease Control and Prevention, Johns Hopkins University, the KfW Development Bank, the KNCV Tuberculosis Foundation, Partners in Health, Project Hope, PATH, the International Figure B5.2.1 Committee of the Red Cross and The Union. Overcoming the challenges to establish the necessary infrastructure Increase in cases of MDR-TB reported by selected for central level laboratories capable of using liquid culture and LPAs, the countries participating in the EXPAND-TB project, 2009–2012, compared with 2008 baseline EXPAND-TB project is showing major progress in routine detection and reporting of drug-resistant TB. For example, 24 870 MDR-TB cases were India diagnosed in supported laboratories in 24 reporting countries in 2012. 20 000 The cumulative number of diagnosed cases of MDR-TB reached 36 965 by 16 588 the end of 2012, equivalent to 32% of the overall project target. Several 15 000 of the countries participating in the project have reported striking increases in the numbers of laboratory-confirmed cases of drug-resistant 10 000 TB, especially in 2012 (Figure B5.2.1). The project has recently been amended to add Xpert MTB/RIF to the list of procured diagnostics, along 4237 5000 with liquid culture and LPAs. In October 2012, project partners began 2967 1660 to pilot a strategy for a transition from project-funded to country308 based financing. The experience from the pilot will be used as a model 0 2008 2009 2010 2011 2012 for implementation across all EXPAND-TB recipient countries for the remainder of the project, ensuring a smooth transition and sustainability Belarus of achievements when EXPAND-TB ends. 3000 2665 Procurement and installation of GeneXpert instruments started in mid-2013 for the new TBXpert project, which will provide approximately 1.4 million Xpert MTB/RIF test cartridges and 230 GeneXpert machines 2000 to 21 recipient low- and middle-income countries over three years. The 1594 1576 1342 US$ 25.9 million project is funded by UNITAID and managed by the WHO Global TB Programme and the Stop TB Partnership. To ensure country 923 1000 absorptive capacity and effective use of the technology, the TBXpert project links a broad network of partners and existing initiatives for TB laboratory strengthening and innovative approaches to expand access to 0 vulnerable populations in both the public and private sector (Box 5.1), 2008 2009 2010 2011 2012 resulting in increased and rapid case detection of TB, HIV-associated TB and RR-TB. TBXpert project partners include the GLI, TB REACH, the GDF, Côte d’Ivoire 300 the EXPAND-TB project, Interactive Research and Development and the African Society for Laboratory Medicine. 221 200

MDR-TB cases detected

MDR-TB cases detected

MDR-TB cases detected

Figure B5.2.2

Countries (in brown) participating in the TBXpert project 100 24 0 2008 Tajikistan 2500 2135 2009 2010 2011 2012 43 50 30

MDR-TB cases detected

2000 1500 1000 604 500 0 2008 2009 2010 2011 2012 319 333

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The SRL Network is expanding its membership to include Centres of Excellence (SRL-CE), a new category that recognizes laboratories that are performing well in large low- and middle-income countries and that work primarily to build in-country laboratory capacity. Countries with laboratories currently eligible to apply for designation as an SRL-CE include Brazil, China, India, the Russian Federation and South Africa. To be eligible for this designation, laboratories need to be nominated by their NTP to the WHO country office, establish a collaborative agreement with an existing SRL, undergo a laboratory assessment by WHO, and actively implement a quality management system towards accreditation.

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Chapter 6

Addressing the co-epidemics of TB and HIV Key facts and messages ■■ In 2012, 1.1 million (13%) of 8.6 million people who developed TB worldwide were HIV-positive. The African Region accounted for 75% of the estimated number of HIVpositive incident TB cases. ■■ The number of people dying from HIV-associated TB has been falling since 2003. However, there were still 320 000 deaths from HIV-associated TB in 2012 and further efforts are needed to reduce this burden. ■■ The prevalence of HIV co-infection among TB patients is highest in the African Region. Of TB patients with an HIV test result, 43% tested positive in 2012, ranging from 9.6% in Angola and Ethiopia to 77% in Swaziland. ■■ Globally, the percentage of notified TB patients with a documented HIV test result was 46% in 2012, up from 40% in 2011 and 15 times higher than the 2004 level. In the African Region, 74% of notified TB patients had an HIV test result in 2012, a further improvement compared with 69% in 2011. Among the 41 countries with the highest TB/HIV burden, 15 achieved HIV testing levels of ≥85%, including seven (Kenya, Malawi, Mozambique, Rwanda, Swaziland, Togo and Zambia) above 90%. ■■ There was an encouraging increase in ART coverage among HIV-positive TB patients between 2011 and 2012, from 49% worldwide in 2011 to 57% in 2012. Nonetheless, given the WHO recommendation that all HIV-positive TB patients are eligible for ART, the coverage of ART for HIVpositive TB patients still needs to be greatly improved. ■■ In 2012, 80% of HIV-positive TB patients were provided with co-trimoxazole preventive therapy (CPT), a level similar to recent years. ■■ In 2012, 4.1 million people enrolled in HIV care were reported to have been screened for TB, up from 3.5 million in 2011. Of the reported 1.6 million people newly enrolled in HIV care in 2012, almost 520 000 were provided with isoniazid preventive therapy (IPT). Coverage needs to be increased, since about 50% of those newly enrolled in HIV care and screened for TB are likely to be eligible for IPT.

People living with HIV who are also infected with TB are much more likely to develop TB disease than those who are HIV-negative.1 Starting in the 1980s, the HIV epidemic led to a major upsurge in TB cases and TB mortality in many countries, especially in southern and eastern Africa (Chapter 2, Chapter 3). In 2012, 1.1 million (13%) of the 8.6 million people who developed TB worldwide were HIV-positive (Chapter 2, Table 2.1); 75% of these HIV-positive TB cases were in the African Region. Although the number of people dying from HIV-associated TB has continued to fall globally and in most regions including the African Region, there were still 320 000 deaths from HIV-associated TB in 2012, with approximately equal numbers among men and women (see Chapter 2). UNAIDS and the Stop TB Partnership have set a target of halving TB mortality rates among people who are HIV-positive by 2015 compared with 2004.2 WHO recommendations on the interventions needed to prevent, diagnose and treat TB in people living with HIV have been available since 2004,3,4 and are collectively known as collaborative TB/HIV activities. They include establishing and strengthening coordination mechanisms for delivering integrated TB and HIV services, testing TB patients for HIV, providing ART and CPT to TB patients living with HIV, providing HIV prevention services for TB patients, intensifying TB case-finding among people living with HIV, offering IPT to people living with HIV who do not have active TB, and controlling the spread of TB infection in health care and congregate settings (the latter three activities are referred to as the Three ‘Is’ for HIV/TB). Since December 2010, the rapid molecular test Xpert MTB/RIF has been recommended as the primary diagnostic test for TB among people living with HIV who have TB signs and symptoms. WHO began monitoring the implementation and expansion of collaborative TB/HIV activities in 2004. This chap1

The probability of developing TB among people living with HIV divided by the probability of developing TB among HIV-negative people is the incidence rate ratio (IRR). The estimated global IRR (all ages) in 2012 was 29.6 (uncertainty interval 27.1–32.1). Further details are provided in Annex 1. 2 G etting to zero: 2011–2015 strategy. Geneva, Joint United Nations Programme on HIV/AIDS, 2010. 3 Interim policy on collaborative TB/HIV activities. Geneva, World Health Organization, 2004 (WHO/HTM/TB/2004.330; WHO/ HTM/HIV/2004.1). Available at http://whqlibdoc.who.int/hq/ 2004/who_htm_tb_2004.330_eng.pdf 4 WHO policy on collaborative TB/HIV activities: guidelines for national programmes and other stakeholders. Geneva, World Health Organi­ zation, 2012 (WHO/ HTM/TB/2012.1). Available at http://whqlibdoc. who.int/publications/2012/9789241503006_eng_Annexes.pdf

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ter presents the latest status of progress, using data for 2004 up to 2012.

figure 6.1

Number of TB patients with known HIV status, 2004−2012 3000 HIV status Negative Positive

6.1 HIV testing for TB patients In 2012, the number of notified TB patients who had a documented HIV test result reached 2.8 million (Figure 6.1), equivalent to 46% of notified TB cases ( Table 6.1, Figure 6.2). This was an increase from 2.5 million and 40% respectively in 2011, and 15 times the level of 3.1% reported in 2004 (Figure 6.2). The coverage of HIV testing for TB patients was particularly high in the African Region, where 74% of TB patients had a documented HIV test result in 2012, up from 69% in 2011 (Figure 6.2). Impressively, in 29 of 46 African countries, ≥75% of TB patients had a documented HIV test result in 2012 (Figure 6.3). Overall, among the 41 countries identified as priorities for the global TB/HIV response, (listed in Table 6.1), 53% of TB patients notified had a documented HIV test. Of these countries, 15 achieved testing levels of ≥85% including seven (Kenya, Malawi, Mozambique, Rwanda, Swaziland, Togo and Zambia) that achieved levels above 90%. In addition, although national data for China show that 34% of TB patients were tested for HIV in 2012, coverage was 88% in the 294 high TB/HIV burden counties in which testing of all notified TB patients is recommended. Globally, there were 87 countries in which ≥75% of TB patients had a documented HIV test result. TB patients (thousands)

2000

1000

0

2004

2005 2006

2007

2008

2009

2010

2011

2012

figure 6.2

Percentage of TB patients with known HIV status, 2004−2012 80 African region Percentage of TB patients 60 Global 40

20 Regions outside Africa 0 2004 2005 2006 2007 2008 2009 2010 2011 2012

figure 6.3

Percentage of patients with known HIV status by country, 2012a

Percentage of notified TB patients 0 14 15 49 50 74 ≥75 No data Not applicable a

In the 294 counties in China identified for HIV testing among notified TB patients, 100 017 of 113 978 notified cases were tested for HIV (88%). Data for the Russian Federation are for new TB patients only excluding cases in prisons.

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Table 6.1

HIV testing, treatment for HIV-positive TB patients and prevention of TB among people living with HIV, globally and for 41 high TB/HIV burden countries and WHO regions, 2012. Numbers in thousands except where indicated. ESTIMATED HIV-POSITIVE INCIDENT TB CASES NUMBER OF TB PATIENTS WITH KNOWN HIV STATUS % OF NOTIFIED TB PATIENTS TESTED FOR HIV % OF TESTED TB PATIENTS HIV-POSITIVE % OF IDENTIFIED HIV-POSITIVE TB PATIENTS STARTED ON CPT % OF IDENTIFIED HIV-POSITIVE TB PATIENTS STARTED ON ART NUMBER OF HIVPOSITIVE PEOPLE SCREENED FOR TB NUMBER OF HIV-POSITIVE PEOPLE PROVIDED WITH IPT

BEST

LOW

HIGH

Angola Botswana Brazil Burkina Faso Burundi Cambodia Cameroon Central African Republic Chad China Congo Côte d’Ivoire Djibouti DR Congo Ethiopia Ghana Haiti India Indonesia Kenya Lesotho Malawi Mali Mozambique Myanmar Namibia Nigeria Russian Federation Rwanda Sierra Leone South Africa Sudan Swaziland Thailand Togo Uganda Ukraine UR Tanzania Viet Nam Zambia Zimbabwe High TB/HIV burden countries AFR AMR EMR EUR SEAR WPR Global

5.5 5.1 16 1.6 2.5 2.7 19 5.3 4.1 7.3 3.6 8.0 0.54 16 23 2.8 4.3 130 7.5 45 9.9 16 1.2 83 19 7.3 46 9.3 2.9 3.9 330 4.3 13 12 1.2 35 4.8 32 9.3 35 55 1 000 830 31 11 19 170 24 1 100

4.7 4.5 13 1.3 2.2 2.3 16 4.4 3.4 6.4 2.9 6.9

6.5 5.6 19 1.8 2.8 3.1 23 6.4 4.8 8.2 4.3 9.2

12 6.0 46 4.6 5.7 32 21 3.8 4.8 309 2.0 21 1.3 35 96 12 14 822 2.7 93 10 19 1.5 48 19 9.9 83 76b 6.1 12 294 3.1 7.4 44 2.7 41 34 52 68 45 34 2 454 1 040 129 58 204 904 451 2 787

23 89 55 84 82 80 82 46 44 34a 17 85 36 31 65 78 81 56 0.8 94 88 93 28 94 13 88 84 99 87 84 15 95 72 91 86 85 82 66 100 88 53 74 56 14 60 39 34 46

9.6 63 20 15 19 4.4 37 39 20 1.9 33 27 10 16 10 24 20 5.4 28 39 75 59 28 58 27 47 23 26 12 65 7.5 77 13 24 50 14 39 7.0 54 70 21 43 16 3.5 6.3 6.2 3.1 20

100 91 0 96 94 98 83 28

20 75 61 37 72 59 92 18 98 97 88 42 98 99 80 99 26 74 0 98 77 87 94 96 73 93 26 80 79 61 69 67 89 79 80

100 66 100 75 55 88 55 20 65 59 23 44 64 40 82 37 46 59 29 74 53 81 100 55 83 72 56

12

1.1

7.4 0.2 1.1 12 1.0 295

0.45 0.64 14 19 17 30 2.4 3.1 3.5 5.1 120 140 5.6 9.7 44 47 8.7 11 15 17 1.2 1.3 58 110 16 21 5.8 8.9 21 80 7.9 11 2.6 3.2 3.2 4.8 270 390 3.5 5.1 11 15 10 14 0.98 1.4 28 42 3.9 5.7 30 34 6.9 12 32 39 42 69 960 1 100 760 910 28 34 10 12 17 21 160 180 27 21 1 000 1 200

0 272 2.1 1 324 23 21 393 30 15

16 21 17

12 140 122 8.9 950 1.3 69

12 2.3

69 54 17 66 62 76 49 94 54 47 60 18 57 55 76 48 74 61 56 57

1.1 370 1.9

14 357 5.7

4 024 2 392 4.5 15 24 1 352 308 4 095

509 473 19 0.2 18 < 0.01 8.6 519

Blank cells indicate data not reported. a In the 294 counties in China identified for HIV testing among notified TB patients, 100 017 of 113 978 notified cases were tested for HIV (88%). Among these, 1605 were HIV-positive (1.6%). b Data for the Russian Federation exclude retreatment cases and cases from prisons.

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Outside the African Region, in 2012 the percentage of TB patients who had a documented HIV test result reached ever, 60% in the European Region. It should be noted, how­ that the coverage of testing in the Russian Federation is underestimated since the national data on HIV testing reported to WHO are for new TB cases in the civilian sector only (i.e. excluding prisons) while the denominator used in calculations of coverage is all notified TB cases. The percentage of TB patients with a documented HIV test result in the Region of the Americas was 56% in 2012. Brazil (where 55% of new TB cases had a documented HIV test result, very similar to the regional average) accounted for more than a third of all cases tested in the region, followed by Mexico (12%) and Haiti (10%). In other regions, where testing rates have remained consistently low, the percentage ranged from 14% in the Eastern Mediterranean Region to 39% in the South-East Asia Region. The highest rates of HIV co-infection were reported for TB patients in the African Region ( Table 6.1), where 43% of those with an HIV test result were positive (compared with 46% in 2011). The percentage of TB patients found to be HIV-positive in the 28 African countries in the list of 41 priority countries ranged from 10% in Ethiopia and Angola to 77% in Swaziland. In the Region of the Americas, the percentage of TB patients with a documented HIV test result who were HIV-positive was 16%. In the Eastern Mediterranean, European, South-East Asia and Western Pacific Regions, less than 10% of TB patients with a documented HIV test result were HIV-positive. The global average across all regions was 20%, and 21% among the 41 high TB/HIV burden countries.

figure 6.4

Number of HIV-positive TB patients enrolled on co-trimoxazole preventive therapy (CPT) and antiretroviral therapy (ART), 2004–2012 600 500 TB patients (thousands) 400 300 200 100 0 2004 CPT HIV positive

ART

2005

2006

2007

2008

2009

2010

2011

2012

6.2 Antiretroviral therapy and co-trimoxazole preventive therapy for TB patients living with HIV ART is a critical intervention for reducing the risk of TB morbidity and mortality among people living with HIV. It reduces the individual risk of TB disease by 65%, irrespective of CD4 cell count,1 and when combined with IPT it can have a significant impact on TB prevention.2 In the latest WHO guidelines released in July 2013,3 the threshold CD4 count at which starting ART is recommended has been raised from a CD4 count of ≤350 to ≤500 CD4/mm3. Implementation of these guidelines on a large scale should substantially reduce morbidity and mortality resulting from HIV-associated TB. As in previous guidelines, ART is recommended for all TB patients living with HIV, irrespective of their CD4 cell count. CPT also helps to reduce mortality among HIV-positive TB patients.4 The number of HIV-positive TB patients on ART has grown from a very low level in 2004 (Figure 6.4) to reach 0.3 million in 2012. Among TB patients notified in 20125 and who had a documented HIV-positive test result, 57% were on ART globally ( Table 6.1, Figure 6.5); this is a considerable improvement from 49% in 2011. In the African Region, 55% of TB patients notified in 2012 who had a documented HIV-positive test result were on ART (up

from 48% in 2011). Among the 41 high TB/HIV burden countries, 28 reported enrolling more than 50% of notified TB patients known to be living with HIV on ART in 2012 ( Table 6.1, Figure 6.6). This important progress notwithstanding, the WHO recommendation that all HIV-positive TB patients are eligible for ART irrespective of their CD4 cell count also means that the coverage of ART for HIV-positive TB patients still needs to be greatly improved with the goal of reaching the 2015 target of 100% set in the Global Plan to Stop TB 2011–2015. Early initiation of ART, as soon as possible within eight weeks after initiation of TB treatment or within two weeks for profoundly immunosuppressed patients (CD4 count <50), is recommended. WHO also strongly recommends the integration of ART and TB treatment services for TB patients living with HIV either through TB or HIV treatment facilities in settings with a high burden of TB and HIV. In many settings, facilities providing TB services are more decentralized than ART services and offer an opportunity to scale up the delivery of integrated TB and HIV services through task shifting and task sharing.6 A recent example of the integration of TB services with those for HIV and 1

Suthar AB et al. Antiretroviral therapy for prevention of tuberculosis in adults with HIV: a systematic review and meta-analysis. PLoS Medicine, 2012, 9(7): e1001270. (doi:10.1371/journal.pmed.1001270). 2 Samandari T et al. 6-month versus 36-month isoniazid preventive treatment for tuberculosis in adults with HIV infection in Botswana: a randomised, double-blind, placebo-controlled trial. The Lancet. 2011 May 7;377(9777):1588-98. doi: 10.1016/S01406736(11)60204-3. 3 Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. Geneva, World Health Organization, 2013. Available at http://apps.who.int/iris/bitstream/ 10665/85321/1/9789241505727_eng.pdf 4 Nunn AJ et al. Role of co-trimoxazole prophylaxis in reducing mortality in HIV infected adults being treated for tuberculosis: randomized clinical trial. British Medical Journal. 2008, 337:a257. 5 In the annual WHO TB data collection form, countries are asked to report the number of TB patients notified in the most recent calendar year who were living with HIV and who “started or continued on ART”. 6 Global Tuberculosis Report 2012. Geneva, World Health Organization, 2012.

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figure 6.5

Percentage of TB patients with known HIV status who were HIV positive, and percentage of HIV-positive TB patients enrolled on co-trimoxazole preventive therapy (CPT) and antiretroviral therapy (ART), 2007–2012a % of TB patients with known HIV status who were HIV positive 100 Percentage of TB patients 80 60 40 20 0 2007 a

% of HIV positive patients on CPT 100 80 60 40 20 0 2007 100 80 60 40 20

% of HIV positive patients on ART

2008

2009

2010

2011

2012

2008

2009

2010

2011

2012

0 2007

2008

2009

2010

2011

2012

The solid lines show values for countries that reported data. The shaded areas show upper and lower limits when countries that did not report data are considered.

figure 6.6

Percentage of HIV-positive TB patients enrolled on antiretroviral therapy (ART), 2012

Percentage of HIV positive TB patients 0 24 25 49 50 74 75 100 No data Not applicable

maternal, new-born and child health (MNCH) services is provided in Box 6.1. Globally, 0.4 million TB patients living with HIV were enrolled on CPT in 2012, up from a negligible number in 2004. The absolute number fell between 2011 and 2012, which is at least partly explained by the decrease in the number of HIV-positive TB cases reported between 2011 and 2012 (Figure 6.4). The coverage of CPT among TB patients with a documented HIV-positive test result was 80% in 2012, similar to the level of 2010 and 2011 ( Table 6.1, Figure 6.5). The African, South-East Asia and Western Pacific Regions achieved particularly high levels of enrolment on CPT: 79%, 89% and 79%, respectively ( Table 6.1). Of the 41 high TB/HIV burden countries, the percentage of

HIV-positive TB patients enrolled on CPT in 2012 exceeded 90% in Angola, Botswana, Burkina Faso, Burundi, Cambodia, India, Kenya, Lesotho, Mozambique, Namibia, Rwanda, Swaziland, Uganda, the United Republic of Tanzania and Zambia.

6.3 Intensifying TB screening and isoniazid preventive therapy among people living with HIV Recording and reporting of TB screening among people living with HIV and provision of IPT to those without active TB is a particular challenge in many countries, and further efforts are needed to facilitate and improve the tracking of progress nationally and globally (Box 6.2).

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Box 6.1

Linkages between TB, HIV and maternal, newborn and child health (MNCH) services in Cambodia Cambodia has achieved great progress in responding to its HIV epidemic and in reducing TB prevalence and mortality. It has also made progress in improving services for maternal, newborn and child health (MNCH). Attendance at antenatal services and the percentage of deliveries at health facilities have increased and maternal and under-five mortality have both been reduced. Major efforts to establish and strengthen service linkages between the TB, HIV and MNCH programmes have also been made. Linkages between TB and HIV services In 2012, 80% of notified TB patients knew their HIV status and 88% of HIV-positive TB patients were on ART. The number of people living with HIV given IPT increased by a factor of 22 between 2006 and 2012, following the introduction of the WHO screening algorithm to rule out active TB (and associated removal of the previous requirement for a positive tuberculin skin test before initiation of IPT). Linkages between MNCH and HIV services The percentage of pregnant women tested for HIV increased from 16% in 2007 to 82% in 2012. The coverage of ART among HIV-infected pregnant women increased from 11% in 2007 to 65% in 2012. The percentage of infants born to HIV-positive women who were provided with ART to prevent motherto-child transmission rose from 50% in 2010 to 73% in 2012. Linkages between MNCH and TB services A new MNCH-TB collaborative framework offering cross-programme referrals between TB services and clinics providing antenatal, growth monitoring and immunization services promises to further reduce the burden of TB among women and children. Scaling up collaboration among the three programmes Collaboration among the three programmes aims to strengthen linkages and synergies to achieve better outcomes. The government, with support from WHO, has piloted efforts to set up a collaborative project involving the three programmes in two districts. Lessons learned from these and other pilot sites are helping the country to maximize potential for cross-programme collaboration and to optimize the use of resources. The three-programme collaborative activities being piloted include: 1. Harmonizing transportation of blood samples required for testing HIV that are collected at sites providing services for pregnant women, TB patients and populations at high risk of HIV. 2. Harmonizing information, education and communication related to MNCH, HIV and TB at the sites providing MNCH, HIV and TB services. 3. Expanding cross-programme laboratory services. 4. Strengthening the system for referrals between the three programmes including standardization of communication and referral procedures. 5. Harmonization of community system strengthening by sharing the costs and time spent during monthly meetings of village health support groups at health centres.

Box 6.2

Improving the quality of TB/HIV data: challenges and solutions Major efforts have been made in recent years to improve the quality of TB/HIV data. Indicators used by TB and HIV programmes have been standardized and collaboration between TB and HIV programmes has been improved, with clear definition of responsibilities for data collection related to TB/HIV interventions. WHO and UNAIDS have worked intensively with countries to try to ensure complete and consistent reporting and to reconcile any apparent discrepancies between data reported by TB and HIV programmes. These efforts notwithstanding, challenges remain: "" Missing or inaccurate denominators required to calculate the coverage of TB screening and IPT among people living with HIV. There has been an increase in the number of countries capturing and reporting data on the number of people living with HIV who are screened for TB and the number without active TB who are provided with IPT. However, many of these countries are not reporting the corresponding denominators needed to calculate coverage (i.e. people registered in HIV care and people newly registered in HIV care, for screening and IPT respectively). There are also examples of the same figures being reported for both denominators. "" Discrepant reporting by NTPs and National AIDS Programmes (NAPs). In some countries, the NTP and NAP report different figures for the number of HIV-positive TB patients who are on ART. In 32 countries, the numbers reported by the NTP and NAP were different in both 2011 and 2012. Although subsequent data verification and harmonization efforts led to consensus on one number in most countries, the different numbers could not be reconciled for either year in Angola, Myanmar and the United Republic of Tanzania. Solutions to address this problem include improving systems for recording and reporting data and further strengthening of collaboration and communication between the NAP and NTP as well as their partners.

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figure 6.7

figure 6.8

Intensified TB case-finding among people living with HIV, 2005–2012 5 Number of people screened (millions) 4 3 2 1 0 2005

Provision of isoniazid preventive therapy (IPT) to people living with HIV without active TB, 2005–2012 600 Number of H V-positive people without active TB (thousands) 500 400 300 200 100 0 2005 2006 2007 2008 2009 2010 2011 2012

2006

2007

2008

2009

2010

2011

2012

In 2012, a total of 4.1 million people who were enrolled in HIV care were screened for TB in 61 countries, an increase from 3.5 million in 58 countries in 2011 (Figure 6.7). In the 49 countries that reported both the number screened for TB and the number in HIV care, the coverage of screening was 66% (3.9/5.9 million). Among 42 countries that reported data, IPT was initiated among almost 520  000 people newly registered in HIV care in 2012. This was an increase from less than 450 000 people in 2011 (Figure 6.8). One country – South Africa – accounted for 71% of the global total with 370 000 people reported to have been provided with IPT in 2012, followed by Ethiopia (30 000), Malawi (21  000), Mozam-

bique (17 000), Lesotho (16 000), Haiti (15 000), Ukraine (14 000), and Namibia (12 000). Thirty countries reported both the total number of people newly enrolled in HIV care (1.6 million) and the number of people living with HIV who were started on IPT (0.47 million) in 2012 i.e. 30% of those newly enrolled in HIV care were initiated on IPT. If the WHO-recommended four-symptom screening algorithm is used to rule out active TB in people living with HIV, approximately 50% of people living with HIV would be expected to be eligible for IPT.1 Further efforts are needed to reach the Global Plan’s 2015 target of providing IPT to all those eligible.

1

Getahun H, et al. Development of a standardized screening rule for tuberculosis in people living with HIV in resource-constrained settings: Individual participant data meta-analysis of observational studies. PLoS Medicine, 2011, 8(1): e1000391. doi:10.1371/journal. pmed.1000391.

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Chapter 7

Financing Key facts and messages ■■ Funding required for a full response to the global TB epidemic in low- and middle-income countries is estimated at US$ 8 billion per year by 2015 (excluding research and development for new TB diagnostics, drugs and vaccines). Of this total, about two thirds is needed for the detection and treatment of drug-susceptible TB, 20% for treatment of MDR-TB, 10% for rapid diagnostic tests and associated laboratory strengthening, and 5% for collaborative TB/HIV activities. ■■ A recent long-term study using data reported to WHO shows that TB funding in low- and middle-income countries grew substantially between 2002 and 2011, especially in Brazil, the Russian Federation, India, China and South Africa (BRICS). The increasing self-sufficiency of these and some other countries is a success story for these countries and the global TB community. ■■ Despite growth in funding for TB, funding gaps persist and additional funding needs to be mobilized from both domestic and international donor sources. There is capacity to increase funding from domestic sources beyond the US$ 5.3 billion available in 2013, especially in BRICS. Funding required from international donor sources is estimated at US$ 1.6–2.3 billion per year. ■■ Funding from international donor sources is expected to reach US$ 0.8 billion in 2013; most of this funding is from the Global Fund and USAID. Donor funding accounts for a large share (≥50%) of total funding in some country groups, notably the 17 HBCs excluding BRICS and all lowincome countries, and an even higher proportion in some individual countries. International donors have a crucial role in sustaining and ensuring further progress in TB prevention, diagnosis and treatment worldwide. ■■ The cost per person successfully treated for TB with firstline drugs is in the range US$ 100 to US$ 500 in almost all countries with a high burden of TB.

Progress in TB prevention, diagnosis and treatment requires adequate funding sustained over many years. WHO began annual monitoring of funding for TB in 2002, and findings have subsequently been published in global TB reports. Particular attention has always been given to the 22 HBCs that account for about 80% of estimated cases (Chapter 2). Recent reports have included aggregated analyses of trends since 2006 for approximately 100 countries. In 2012, WHO conducted a comprehensive analysis of long-term trends in TB funding in low- and middle-income countries for the decade 2002–2011, using data reported by countries between 2002 and 2012. The analysis was able to include 104 out of a total of 154 countries classified by the World Bank as low- or middle-income in 2011 (gross national income (GNI) per capita < US$ 12,476). These 104 countries had 94% of the world’s estimated cases of TB and 88% of the world’s estimated cases of MDR-TB in 2011. Levels of funding in 2011 were then analysed in combination with the most recent estimates of resource requirements for TB prevention, diagnosis and treatment to assess the funding that could be mobilized from domestic sources and the balance required from international donors up to 2015. Results from these analyses were published in an article in the August 2013 issue of The Lancet Global Health.1 Given this very recent publication, the scope of this financing chapter has been adjusted compared with previous years to avoid unnecessary duplication. Section 7.1 presents the most up-to-date estimates of financial resources required until the end of 2015 in all of the 154 countries that were classified as low- or middle-income countries in 2011, alongside projections of the funding that could be mobilized domestically. Section 7.2 provides a summary of the main findings from the analysis of trends in funding between 2002 and 2011 in 104 low- and middle-income countries. With this background and context, the rest of the chapter (section 7.3) contains detailed analyses of TB funding in 2013, using data compiled in the 2013 round of global TB data collection. Funding levels in 2013 are presented by WHO region and for other country groupings based on income level, burden and geography, with breakdowns by source of funding (section 7.3.1) and category of expenditure (section 7.3.2). Funding gaps reported by countries are also illustrated and discussed (section 7.3.3). 1

Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middle-income countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15.

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Further country-specific data can be found in finance profiles that are available online.1

7.1 Estimates of funding required up to 2015 for a full response to the global TB epidemic The Global Plan to Stop TB 2011–20152 sets out the actions and funding needed for a full response to the TB epidemic, based on the Stop TB Strategy.3 The overall goal of the plan is to achieve the 2015 global targets for reductions in cases of and deaths from TB (i.e. that incidence should be falling and that prevalence and mortality rates should be halved compared with their levels in 1990) (Chapter 1). Key components of the plan include increasing the number of patients detected and treated according to WHO’s recommended strategy from 5.8 million in 2011 to 6.9 million by 2015 (which would be equivalent to more than 80% of projected incident cases in that year); ensuring that all previously treated patients and all new patients with known risk factors for MDR-TB are tested for drug resistance by 2015 (including with recently endorsed rapid tests such as Xpert MTB/RIF that are discussed in Chapter 5); enrolment of all TB patients with confirmed MDR-TB (projected to be around 300 000 in 2015) on second-line treatment; HIV testing of all patients with TB; and prompt initiation of ART in all HIV-positive TB patients. In 2013, the Global Plan datasets were used in combination with new country-specific planning and budgeting work with nine high TB or high MDR-TB burden countries to produce updated estimates of funding needs for TB prevention, diagnosis and treatment in low- and middleincome countries.4 The nine countries were Ethiopia, India, Indonesia, Kazakhstan, Kenya, Nigeria, Pakistan, South Africa and Ukraine. Analyses were conducted in the context of estimates of funding needs and funding gaps required for the Global Fund’s replenishment efforts in 2013.5 WHO subsequently extended these analyses to cover all low- and middle-income countries and not only the countries eligible to apply to the fund.6 Notable countries (in terms of TB burden and funding requirements) that are not eligible to apply to the Global Fund are Brazil, China and the Russian Federation. During the course of the work done for the first prereplenishment meeting held in April 2013, it should be highlighted that the Global Fund, WHO, UNAIDS, and other partners agreed that funding needs for ART for HIVpositive TB patients should be included in estimates of HIV resource needs to avoid double-counting. For this reason, the estimates of resource requirements for TB/HIV interventions included in the updated estimates of resource needs for TB are lower than those published in the Global Plan. Funding needs were compared with the domestic funding that could be mobilized in two alternative scenarios. The first scenario was that TB funding could increase (from a 2011 baseline) in line with International Monetary Fund forecasts for growth in total government expenditures.7

The second scenario had the same assumptions as the first, but also assumed that countries that currently under­ perform in domestic financing relative to their income level (i.e. their ability to pay) and disease burden reach the level of the median performer by 2020. These scenarios were chosen to be fully consistent with the methods previously used to assess the potential to mobilize domestic funding for prevention, treatment and care of HIV.8 The main results from these analyses are summarized in Figure 7.1. The total funding required in all low- and middle-income countries reaches about US$  8 billion in 2015, compared with US$ 6 billion in 2012 (Figure 7.2).9 Of the total funding required, about two thirds is needed for the detection and treatment of drug-susceptible TB, 20% for treatment of MDR-TB, 10% for rapid diagnostic tests and associated laboratory strengthening, and 5% for collaborative TB/HIV activities (excluding ART). Funding needed for each of these four categories increases over time. The largest relative increases are for treatment of MDR-TB and diagnostics/laboratory strengthening. There is potential to mobilize a large share of these funding needs from domestic resources in some country groups, notably BRICS and upper middle-income countries (Figure 7.1). Elsewhere, there are relatively large gaps between the estimated amounts of domestic funding that could be mobilized and the total funding needed, especially in three country groups: the 17 HBCs excluding BRICS; low-income countries; and the African Region excluding South Africa. In the first scenario in which domestic funding grows from 2011 levels in line with projected growth in total government expenditures, the total gap amounts to US$ 2.3 billion per year by 2015. In the second and more optimistic scenario, the gap would be US$ 1.6 billion per year by 2015. 1 2

www.who.int/tb/data The Global Plan to Stop TB, 2011–2015. Geneva, World Health Organization, 2010 (WHO/HTM/STB/2010.2). 3 Raviglione M, Uplekar M. WHO’s new Stop TB strategy. Lancet 2006; 367: 952–5. 4 Funding required for research and development for new TB diagnostics, drugs and vaccines was not considered. In the Global Plan, it is estimated that about US$ 2 billion per year is needed for research and development. 5 The Global Fund to Fight AIDS, Tuberculosis and Malaria fourth replenishment (2014–2016): needs assessment. Geneva, Global Fund to Fight AIDS, Tuberculosis and Malaria, 2013. 6 Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middle-income countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15. 7 World economic outlook database. Washington, International Monetary Fund, 2012 (www.imf.org/external/pubs/ft/weo/2012/02/ weodata/index.aspx). 8 Schwartlander B, Stover J, Hallett T, et al. Towards an improved investment approach for an effective response to HIV/AIDS. The Lancet 2011; 377: 2031–41. 9 In Figure 7.1 , country groups are not all mutually exclusive. The global total can be calculated by adding together the totals in the panels for BRICS, low-income countries, lower middle-income countries (excluding China and India) and upper middle-income countries (excluding Brazil, the Russian Federation and South Africa).

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Figure 7.1

Forecast of funding that could be mobilized from domestic sources compared with total funding needed for a full response to the global TB epidemic in nine country groups, 2012–2015. The black line shows the total funding required. The blue band represents scenario 1, which shows domestic funding that could be mobilized if domestic funding increases from a 2011 baseline at the same rate of growth as International Monetary Fund forecasts of growth in total government expenditures. The green band shows additional resources that could be mobilized, compared with scenario 1, if current underperformers (relative to income level and TB disease burden) improve at a consistent rate to reach the level of the median performer by 2020. BRICS=Brazil, the Russian Federation, India, China, South Africa. 5.0 4.0 3.0 2.0 0.5 1.0 0 2012 0 2012 0 2012 0.10 1.0 0.20 BRICS 1.5 17 HBCs excluding BRICS 0.30 Low income countries excluding HBCs

US$ billions

2013

2014

2015

2013

2014

2015

2013

2014

2015

Low income countries 0.8

1.8 1.6

Lower middle income countries excluding I and C

1.2 1.0 0.8 0.6 0.4 0.2 0

Upper middle income countries excluding B, R, S

0.6 US$ billions

1.4 1.2

0.4

1.0 0.8 0.6

0.2

0.4 0.2

0 2012

2013

2014

2015

0 2012

2013

2014

2015

2012

2013

2014

2015

0.9 0.8 0.7 0.6 US$ billions 0.5 0.4 0.3 0.2 0.1

Africa excluding S

Asia excluding I and C 1.2 1.0 0.8 0.6 0.4 0.2 0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 2012 2013 2014 2015

Rest of world excluding B and R

0 2012

2013

2014

2015

0 2012

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2014

2015

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Figure 7.2

Total funding required for a full response to the global TB epidemic, by intervention area, 2013–2015 8 TB/HIV Laboratory strengthening/ diagnostics MDR TB Drug susceptible TB

6 US$ billions

4

2

0 2012 2013 2014 2015

It should be highlighted that in the second and more optimistic scenario, it is assumed that countries that currently underperform in terms of their levels of domestic financing relative to their TB burden and income level will steadily progress to reach the level of the current median peformer (in terms of domestic funding relative to burden and income level) by 2020. Two countries in particular – India and Indonesia – would need to substantially increase their levels of domestic funding for this scenario to materialize in practice, since they account for about two-thirds of the additional funding in Scenario 2 compared with Scenario 1. Current trends are not in line with Scenario 2. In India, domestic funding reported for 2013 is lower than the amount available in 2012, while in Indonesia an increase in domestic funding between 2012 and 2013 was reported but by a relatively small amount (see Annex 2 for further details).

7.2 Trends in TB funding, 2002–2011: a summary Data reported to WHO between 2002 and 2012 allowed analysis of trends 2002–2011 in 104 countries. These 104 countries are shown in Table 7.1 (an additional 21 countries that could be included in analyses of funding in 2013, described in section 7.3, are shown in bold). Among the 104 countries, there were ≥6 observations for 83 countries. For most countries, there were between 7 and 10 observations, including 14/22 HBCs that had 10 observations each and 5/22 HBCs for which there were 9/10 observations. Values for country-year combinations for which data were missing in the 104 countries were imputed using country-specific linear regression models. Details on the criteria used to include or exclude countries and the imputation methods are available in an online technical appendix.1

1

Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middle-income countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15.

In the 104 low- and middle-income countries with 94% of the world’s TB cases and 88% of the world’s MDR-TB cases, total funding for TB (domestic plus international donor sources) grew in real terms (2011 US$ prices) from US$ 1.7 billion in 2002 to US$ 4.4 billion in 2011. The increases varied among country groups, from 100% in low-income countries to 177% in upper middle-income countries. Increases in funding were accompanied by large increases in the number of people successfully treated for TB, from 2.8 million in 2002 to 5.0 million in 2011. A cumulative total of 43 million people were treated between 2002 and 2011. The cost per patient treated was in the range US$ 100–500 in most of the countries with the highest burdens of TB. The size of the patient caseload and gross domestic product (GDP) per capita explained more than 70% of the variation among countries in the cost per patient treated. Domestic funding (national and local budgets, and loans) in the 104 countries included in trend analyses rose from US$ 1.5 billion in 2002 to US$ 3.9 billion in 2011. Loans accounted for a small proportion (≤5%) of total domestic funding each year. Most of the increase in total domestic funding (US$ 1.7 out of US$ 2.4 billion [71%]) was accounted for by BRICS (which account for almost half of the world’s TB cases) and other middle-income countries in Asia, Latin America and Europe. The magnitude of domestic funding in these country groups (69–98% of total funding per year) and BRICS in particular (>95% of total funding per year) meant that domestic funding dominated total funding for TB globally (88–92% per year). International donor funding in the 104 countries included in trend analyses grew from US$ 0.2 billion in 2002 to US$ 0.5 billion in 2011. There was striking variation among country groups in terms of the share of total funding provided from international donor sources. By 2011, donor funding represented 39% of total funding in the 17 HBCs excluding BRICS, which account for about one third of the world’s TB cases; 42% of funding in African countries excluding South Africa; and 67% of total funding in lowincome countries (25 of which are in Africa). The Global Fund accounted for 64% of all donor funding reported by countries during the decade 2002–2011. Most funding was used for the diagnosis and treatment of drug-susceptible TB (over 85% each year). Small amounts were used for diagnosis and treatment of MDRTB, although funding started to increase in BRICS, upper middle-income countries, and countries in Europe and Latin America around 2006. Despite growth in funding from domestic and international donor sources, NTPs were not able to mobilize all the funding that they estimated to be needed. Funding gaps (i.e. the difference between assessments by NTPs of funding needs for TB prevention, diagnosis and treatment and the actual amount of funds mobilized) persisted, and increased from US$ 257 million in 2002 to US$ 563 million in 2011. It should be noted that the funding gaps reported by NTPs are sometimes based on relatively conservative assessments of funding needs. When national strategic plans with more

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Table 7.1

125 countries included in analyses of TB financing in 2013a,b LOW-INCOME (21% of notified cases globally) LOWER-MIDDLE-INCOME (46% of of notified cases globally) UPPER-MIDDLE-INCOME (27% of notified cases globally) BRICS (47% of notified cases globally) 17 HIGH-BURDEN COUNTRIES EXCLUDING BRICS (33% of notified cases globally) 14 HIGH MDR-TB BURDEN COUNTRIES (NOT IN THE LIST OF 22 HIGH-BURDEN COUNTRIES) (2% of notified cases globally)

African

Benin, Burkina Faso, Burundi, Central African Republic, Chad, Comoros, DR Congo, Eritrea, Ethiopia, Gambia, Guinea, GuineaBissau, Kenya, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Sierra Leone, Togo, Uganda, UR Tanzania, Zimbabwe Haiti

Cameroon, Cape Verde, Congo, Côte d’Ivoire, Ghana, Lesotho, Mauritania, Nigeria, Sao Tome and Principe, Senegal, Swaziland, Zambia

Algeria, Botswana, Gabon, Namibia, South Africa

South Africa

DR Congo, Ethiopia, Kenya, Mozambique, Nigeria, Uganda, United Republic of Tanzania, Zimbabwe

Americas

Bolivia, El Salvador, Guatemala, Guyana, Honduras, Nicaragua, Paraguay

Argentina, Belize, Brazil, Colombia, Dominican Republic, Ecuador, Jamaica, Mexico, Panama, Suriname, Venezuela Iran, Iraq, Jordan, Lebanon, Libya, Tunisia

Brazil

Eastern Mediterranean

Afghanistan, South Sudan

Djibouti, Egypt, Morocco, Pakistan, Sudan, Syrian Arab Republic, West Bank and Gaza Strip, Yemen Armenia, Georgia, Moldova, Ukraine, Uzbekistan

Afghanistan , Pakistan

European

Kyrgyzstan, Tajikistan

Bosnia and Herzegovina, Bulgaria, Kazakhstan, Montenegro, Romania, Serbia, The Former Yugoslav Republic of Macedonia, Turkey Maldives, Thailand

Russian Federation

Armenia, Bulgaria, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Republic of Moldova, Tajikistan, Ukraine, Uzbekistan

South-East Asia

Bangladesh, Democratic People’s Republic of Korea, Myanmar, Nepal Cambodia

Bhutan, India, Indonesia, Sri Lanka, Timor-Leste

India

Bangladesh, Indonesia, Myanmar, Thailand

Western Pacific

Federal States of Micronesia, Kiribati, Lao People’s Democratic Republic, Mongolia, Papua New Guinea, Phillipines, Samoa, Solomon Islands, Vanuatu, Viet Nam

American Samoa, China, Fiji, Malaysia, Marshall Islands, Palau, Tonga, Tuvalu

China

Cambodia, Phillipines, Viet Nam

Excluded due to insufficient data

Albania, Angola, Azerbaijan, Costa Rica, Cuba, Dominica, Grenada, Palau, Peru, Saint Lucia, Saint Vincent and the Grenadines, Turkmenistan

Azerbaijan, Belarus, Lithuania

a b

Analyses focus primarily on low and middle-income countries. Three high-income countries (Estonia, Latvia and the Russian Federation) were included because they are in the list of 22 high-burden countries or the list of 27 high-MDR-TB burden countries. Additional countries included in analyses of TB financing in 2013 compared with those included in analyses of trends 2002–2011 are shown in bold.

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Figure 7.3

Available funding for TB care and control in 125 countries reporting 96% of global cases by source of funding and WHO region, 2013 3.0 US$ billions (current 2013 US$) 2.5 2.0 1.5 1.0 0.5 0 EUR AFR WPR SEAR AMR EMR Global Fund Grants (excluding Global Fund) Government, general health care services (inpatient and outpatient care) Government, NTP budget (including loans)

ambitious targets are developed, as was done for the nine countries described in section 7.1, funding needs and gaps invariably increase. The gap between the US$ 8 billion estimated to be needed for a full response to the TB epidemic in 2015 (section 7.1) and the US$ 6.1 billion available in 2013 (see section 7.3 below) is US$ 1.9 billion. Overall, these findings show that TB funding increased substantially between 2002 and 2011, resulting in impressive and cost-effective gains. The increasing self-sufficiency of many countries, including BRICS, which account for almost half of the world’s TB cases, is a success story for these countries and the global TB community. At the same time, it is clear that international donor funding remains crucial in many countries and needs to be continued to sustain and consolidate recent gains.

Figure 7.4

7.3 TB funding in 2013 Data reported by countries to WHO in the 2013 round of global TB data collection allowed inclusion of 122 lowand middle-income countries (GNI per capita less than US$ 12 616 in 2012) in analyses of TB funding by source of funding and category of expenditure in 2013 ( Table 7.1; the additional countries compared with those included in analyses of trends 2002–2011 are shown in bold). An additional three high-income countries (Estonia, Latvia and the Russian Federation) were also included in analyses because they are in the list of 22 HBCs or 27 high MDRTB HBCs. Collectively, the 125 countries account for 96% of the world’s TB cases. Methods used to compile, validate and analyse these data are summarized in Box 7.1. The total funding available in the 125 countries in 2013 amounts to US$ 6.1 billion, and US$ 3.1 billion excluding the European Region (Figure 7.3). Approximately US$ 1.3 billion is available in the African Region, much of which is accounted for by South Africa. In the other four WHO regions, funding is in the range US$ 0.2 to US$ 0.7 billion.

Available funding for TB care and control in 125 countries reporting 96% of global cases by source of funding and income group, 2013 3.0 US$ billions (current 2013 US$) 2.5 2.0 1.5 1.0 0.5 0 Upper High middle income income Lower Low middle income income Global Fund Grants (excluding Global Fund) Government, general health care services (inpatient and outpatient care) Government, NTP budget (including loans)

Figure 7.5

Available funding for TB care and control in BRICS, 17 other HBCs and Africa excluding South Africa, by source of funding, 2013 3.5 US$ billions (current 2013 US$) 3.0 2.5 2.0 1.5 1.0 0.5 0 BRICS Africa without South Africa Other HBCs Global Fund Grants (excluding Global Fund) Government, general health care services (inpatient and outpatient care) Government, NTP budget (including loans)

7.3.1 Funding in 2013 by source of funding Of the total of US$  6.1 billion reported for 2013, 87% (US$ 5.3 billion) is from domestic sources and 13% (US$ 0.8 billion) is from international donor sources (Figure 7.3, Figure 7.4). Both fall short of amounts needed for a full response to the TB epidemic up to 2015 (section 7.1). The US$  5.3 billion from domestic sources represents at most 67% of the total needed by 2015. The US$ 0.8 billion from international donor sources is at most 50% of the US$ 1.6– 2.3 billion per year estimated to be required by 2015, and remains much less than international donor funding for malaria (US$  1.8 billion in 2011)1 and HIV (US$  8.2 billion in 2011).2 Of the international donor funding for TB in 2013, approximately three-quarters was from the 1

World malaria report 2012. Geneva, World Health Organization, 2012. 2 World AIDS day report 2012. Geneva, Joint United Nations Programme on HIV/AIDS, 2012 (www.unaids.org/en/resources/ presscentre/pressreleaseandstatementarchive/2012/november/ 20121120prresults).

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Box 7.1

Methods used to compile, validate and analyse financial data reported by countries to WHO WHO began monitoring government and international donor financing for TB in 2002. All data are stored in the WHO global TB database. The standard methods used to compile, review, validate and analyse these financial data have been described in detail elsewhere.a,b This box provides a summary. Each year, WHO requests data from low- and middle-income countries about funding for NTPs by category of expenditure and source of funding, and funding gaps by category of expenditure, in US dollars. Categories of expenditure for TB comprise: firstline drugs; NTP staff; programme management and supervision activities; laboratory supplies and equipment; advocacy, communication, and social mobilization activities; community-based care; public–private mix approaches; collaborative TB/ HIV activities; the Practical Approach to Lung Health; operational research including surveys; outpatient visits; and hospital admissions. Categories of expenditure for MDR-TB are: secondline drugs; other items specifically for programmatic management of patients with MDR-TB; hospital admissions; and outpatient visits. Funding sources are defined as national or local government, loans (both classified as domestic funding), grants from the Global Fund, and grants from other donors (both classified as international donor funding). Countries that are classified as high-income are asked to report data on total funding and total expenditures (without breakdowns by source of funding and category of expenditure). WHO uses methods to review and validate data that have remained consistent since 2002. These methods include routine checks for plausibility and consistency, including validation checks that are built into the online reporting system. Examples of validation checks are checks for implausibly large year-to-year changes (for example in total reported funding by source and by category of expenditure), or implausibly high or low values relative to the number of TB patients (for example, first-line or second-line drug budgets or expenditures per patient that greatly exceed prices quoted by the Global TB Drug Facility). Methods to review and validate data also include discussions with country respondents to resolve queries, and triangulation with other data sources such as the detailed budgets prepared using the WHO TB planning and budgeting tool,c economic evaluations that include detailed cost data, the Global Fund and the Organization for Economic Co-operation and Development (OECD) Creditor Reporting System. Particular attention has always been given to the 22 HBCs. In a few countries (China and the Russian Federation are prominent examples), funding for TB reported by NTPs includes funding for all staff, infrastructure, and other inputs necessary for hospital admissions and outpatient visits during TB treatment, because care is provided in TB-specific hospitals and clinics that have dedicated budgets. In most countries, however, the funding used for inpatient and outpatient care for TB patients is not captured in funding reported by NTPs. Since detailed costing studies of TB diagnosis and treatment in a wide range of countries show that hospitalization and outpatient care are the most important costs not captured by financial data reported by NTPs, both for drug-susceptible TB and MDR-TB, the estimation of financial resources used for inpatient and outpatient care of TB patients has always been given considerable attention in WHO’s work on global monitoring of TB financing. For all countries with the exception of those such as China and the Russian Federation, the funding used for inpatient and outpatient care of TB patients is estimated by multiplying the number of outpatient visits and days of inpatient care per patient (reported by NTPs to WHO each year) by country-specific estimates of their unit cost available from the WHO-CHOICE database,d and then by the reported number of TB patients. This is done separately for: a) patients with drugsusceptible TB; and b) patients with MDR-TB, based on the utilization data that are reported separately for these two groups of patients on the annual WHO TB data collection form. a

Floyd K, Pantoja A, Dye C. Financing tuberculosis control: the role of a global financial monitoring system. Bulletin of the World Health Organization; 2007; 85: 334–40. b Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middle-income countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15. c Planning and budgeting for TB control activities. Geneva, World Health Organization, 2013. (www.whoint/tb/dots/planning_budgeting_tool ). d Choosing interventions that are cost effective (WHO-CHOICE). Geneva, World Health Organization, 2008 (www.who.int/choice/ country/country_specific/ ).

Global Fund; the remainder was largely from USAID. Technical assistance to support countries to effectively mobilize funding from the Global Fund and to implement grants once approved is provided by the TB Technical Assistance Mechanism (Box 7.2). Breakdowns of total funding by source for different country groups are shown in Figure 7.4 and Figure 7.5. Findings strongly reinforce those previously reported for the decade 2002–2011 (Section 7.2). BRICS are relatively selfsufficient overall (95% of funding from domestic sources), although India is an exception where only 64% of funding in 2013 is from domestic sources (and as shown in Annex 1,

for the NTP budget specifically, 37% is funded from domestic sources in 2013). High-income countries are fully selfsufficient and the group of upper middle-income countries rely on international donor funding for only a small share (4%) of their total funding (and most is accounted for by China). Low- and lower middle-income countries account for most of the international donor funding (US$  0.7 billion, 88%). In the group of low-income countries, it accounts for about half of total funding. International donor funding also has a crucial role in the 17 HBCs excluding BRICS, and in African countries excluding South Africa (Figure 7.5), where it accounts for 35% and 54% respectively of

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Box 7.2

Technical Assistance for national TB programmes; the role of TB-TEAM The TB Technical Assistance Mechanism (TB-TEAM) was established to coordinate and monitor the provision of technical assistance to NTPs. The secretariat and a dedicated websitea are hosted by WHO’s Global TB Programme and funded by USAID. In mid-2013, there were 34 technical partners actively engaged in TB-TEAM. Each partner shares information about country missions, including reports that are uploaded to the countryspecific pages of the TB-TEAM website. In 2012, TB-TEAM partners reported 706 missions. By topic area, laboratory strengthening and the programmatic management and scale up of MDR and XDR-TB accounted for one quarter of all missions. A further 30% of missions were related to monitoring and evaluation/impact measurement, national TB programme reviews and management of drugs and commodities. Most missions were conducted by WHO (40%) and KNCV Tuberculosis Foundation (20%). A further 24% were conducted by the US Centers for Disease Control and Prevention (CDC); the Union, and the Global TB Drug Facility (GDF). The main focus of TB-TEAM to date has been provision of technical assistance to support the implementation of grants from the Global Fund. Within the context of the fund’s new funding model (NFM) established in 2013, this is now being extended to support the development of robust national strategic plans and associated concept notes that are required for the mobilization of new financial resources (as opposed to implementation of grants that have already been secured) from the Global Fund. The focus on support to countries that are current or potential Global Fund recipients reflects the fact that the fund is the main source of international donor funding in many countries, especially in low-income countries and several high-burden, lower-middle income countries (section 7.2). TB-TEAM partners are taking a proactive approach to providing technical support to countries, giving particular attention to grants that are not performing well. The TB-TEAM secretariat monitors progress in mobilization of funding and implementation of grants using indicators such as proposal success rates, funding for TB as a share of total grant approvals, disbursement rates and grant performance ratings. Statistics for these indicators in 2012 can be summarized as follows: "" Proposal success rates. TB-TEAM helped 21 countries to mobilize resources via the Global Fund’s transitional funding mechanism (TFM). This was put in place during the transition to the NFM to prevent countries from experiencing critical funding shortages that would affect essential services. Among the three diseases supported by the fund, TB proposals had the best recommendation rate (the Technical Review Panel of the Global Fund recommended that 87% of TB proposals should be approved compared with 79% for malaria and 62% for HIV). "" TB as a share of total funding. In the TFM, US$ 130 million was awarded to TB grants, equivalent to 25% of all approved funding. "" Disbursement rates. In total and across all grants in 101 countries, US$ 509 million was disbursed for TB in 2012, equivalent to 15% of total disbursements (US$ 3.4 billion) by the Global Fund. Of the remaining funding, US$ 1.8 billion (54%) was disbursed to HIV grants, US$ 1.0 billion (30%) to malaria grants and US$ 32 million (1%) to crosscutting investments. "" Grant performance ratings. At the end of 2012, TB grants were performing relatively well (Figure B7.1.1), with 86% in the top three categories of A1 (excellent), A2 (meets expectations) and B1 (adequate), compared with 53% for malaria grants and 79% for HIV grants. The other categories are B2 (adequate but potential demonstrated) and C (inadequate). Figure B.7.1.1

Latest Global Fund performance rating by disease for all 423 active grants (Global Fund Database, accessed January 2013) 100 80 Percentage (%) 60 40 20 0 Malaria (110 grants) HIV/AIDS (183 grants) TB (130 grants) Grand Total (423 grants) C B2 B1 A2 A1

In 2013 and 2014, Global Fund projections suggest that an estimated US$ 1.9 billion will be disbursed to TB grants. This equates to an amount per year that is approximately double the level of 2012. TB-TEAM aims to support countries as effectively as possible to help to ensure that these funds are disbursed and used well. a

www.stoptb.org/countries/tbteam/

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Table 7.2

Reported NTP budget, available funding for NTP budget by intervention area and estimated cost of inpatient and outpatient care for drug-susceptible (DS-TB) and MDR-TB, 36 high TB or high MDR-TB burden countries, 2013 (current US$ millions) Available funding Reported NTP budget DS-TB MDR-TB TB/HIV PPM/PAL/ACSM/ CBC/OR/surveys Other Inpatient and outpatient care: DS-TBb Inpatient and outpatient care: MDR-TBb

22 High-burden countries Afghanistan Bangladesh Brazil Cambodia China Democratic Republic of the Congo Ethiopia India Indonesia Kenya Mozambique Myanmar Nigeria Pakistan Philippines Russian Federationc South Africa Thailanda Uganda United Republic of Tanzania Viet Nam Zimbabwe 22 high-burden countries total Armenia Azerbaijan Belarusa Bulgaria Estonia Georgia Kazakhstan Kyrgyzstan Latvia Lithuania Republic of Moldovaa Tajikistan Ukraine Uzbekistan 27 high MDR-TB burden countries 36 high TB or high MDR-TB burden countries 35 46 85 76 4 011 4 371 2.6 5.0 21 15 2 312 2 471 2.8 1.1 15 14 448 464 0 0.6 0.6 0 164 172 0.6 1.1 0 1.5 108 130 15 8.6 7.9 46 325 340 16 0.8 10 242 35 4.8 14 0.1 2.6 149 11 3.7 0.3 0.5 2.8 70 5.6 1.1 0 0 0 1.0 0.3 0 0.6 0 0 1.7 13 0 0.3 0.2 4.8 21 4.0 0.1 13 43 87 24 359 61 145 182 119 55 11 36 154 73 149 1 592 475 44 31 58 66 38 3 814 5.4 6.0 4.6 60 5.3 267 8.7 47 84 39 19 5.6 9.1 17 26 27 1 332 217 31 6.0 14 4.4 11 2 241 4.5 0.8 1.6 6.3 0.6 25 1.7 6.0 67 8.3 0.5 1.1 3.5 4.6 34 8.9 129 41 3.9 2.2 0.5 4.6 0.1 350 0.6 0 0 2.3 0.2 0.2 0.3 3.1 0 1.3 0.5 0 1.6 1.6 0.1 0.4 27 124 0.1 0.2 2.1 1.2 3.4 170 0 0.7 1.9 5.8 2.2 12 1.0 12 18 8.4 0.5 0.8 0.4 3.6 1.5 6.9 0.4 19 6.8 3.9 0.9 3.4 0.5 111 0.1 1.3 0.2 0 0.7 0.5 4.5 3.6 2.1 0.6 0.8 0 0 22 5.0 2.7 104 67 0 9.3 1.3 4.8 1.4 232 0.2 – – 22 0.1 3.6 192 13 20 – 11 6.6 66 84 854 919 – 3.2 1.1 40 5.7 400 402 2.9 5.0 20 6.7 0 0.2 11 84 39 9 5.7 5.6 6.2 11 109 0 109 3.3 0.6 1.5 49 15 494 7.5 – – 1.5 0.1 3.2 57 3.1 7.3 0 1.4 1.4 0.2 0 0 0.6 32 2.0 0.3 0.1 1.6 1.3 0.8 3.4 0 232 0 0 0.1 0.6 0.1 279 1.2

Remaining high MDR-TB burden countries

Blank cells indicate data not reported. – indicates values that cannot be calculated. a Based on data reported for 2013 in the 2012 round of data collection. In 2013, Thailand was not able to report funding for the sub-national level. b No amount is shown for China and the Russian Federation because NTP budget includes all costs for inpatient and outpatient care. c The staff and infrastructure required for TB care and control could not be disaggreated for MDR-TB and DS-TB separately and are shown under DS-TB. The full amount for staff and other recurrent costs for TB hospitals is included in the column for DS-TB.

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Figure 7.6

Figure 7.7

Available funding for TB care and control in 125 countries reporting 96% of global cases by intervention area and WHO region, 2013 3.0 US$ billions (current 2013 US$) 2.5 2.0 1.5 1.0 0.5 0 EURa a

Available funding for TB care and control in BRICS, 17 other HBCs and Africa excluding South Africa, by intervention area, 2013 3.5 US$ billions (current 2013 US$) 3.0 2.5 2.0 1.5 1.0 0.5 0 BRICS a

Other TB/HIV Inpatient and outpatient care: MDR TB MDR TB Inpatient and outpatient care: DS TB DS TBb

Other TB/HIV Inpatient and outpatient care: MDR TB MDR TB Inpatient and outpatient care: DS TB DS TBa

AFR

WPR

SEAR

AMR

EMR

For EUR, DS-TB includes all of the staff and infrastructure required for TB care and control in the Russian Federation that could not be disaggregated for MDR-TB and DS-TB separately. The amount of funding shown for MDR-TB in the European Region is thus an underestimate. b Drug-susceptible TB (DS-TB) includes funding available for first-line drugs, NTP staff, programme management and supervision, and laboratory equipment and supplies.

Africa without South Africa

Other HBCs

For BRICS, drug susceptible TB (DS-TB) includes all of the staff and infrastructure required for TB care and control in the Russian Federation that could not be disaggregated for MDR-TB and DS-TB separately. The amount of funding shown for MDR-TB in BRICS is thus an underestimate.

total funding in 2013. The share is even higher in specific countries and above 80% in four HBCs: Afghanistan, the Democratic Republic of the Congo, Pakistan and Uganda (Annex 2).

7.3.2 Funding in 2013 by budget category Funding in 2013 by budget category is shown by WHO region in Figure 7.6, for other country groups in Figure 7.7 and for HBCs and high-MDR-TB burden countries in Table 7.2. It should be highlighted that the amount of funding shown for MDR-TB in the European Region is an underestimate due to the fact that the budget category ‘Drug-susceptible-TB’ (DS-TB) includes all of the staff and infrastructure required for TB prevention, diagnosis and treatment in the Russian Federation that could not be disaggregated for MDR-TB and DS-TB separately. Among the 122 low- and middle-income countries for which a breakdown could be calculated, most of the funding available in 2013 is for diagnosis and treatment of DS-TB. The WHO regions in which the shares of funding for MDR-TB are highest are the African Region (mostly explained by South Africa), the European Region and the South-East Asia Region. This is consistent with the distribution of the burden of MDR-TB cases, which are mostly in BRICS and the European Region, and with the latest data on numbers of MDR-TB patients detected and enrolled on treatment (Chapter 4). These data show that European countries and South Africa are enrolling the highest proportion of estimated cases of MDR-TB on treatment and that progress in scaling up treatment in India (in the SouthEast Asia Region) is accelerating. The low share of funding

for MDR-TB in the Western Pacific Region, within which most of the estimated cases of MDR-TB are in China, is consistent with the small number of cases reported to have been detected and started on treatment in China in 2012 (just over 3000, equivalent to 5% of the estimated number of TB patients with MDR-TB). Among the 22 HBCs, 85% of the available funding for MDR-TB treatment is accounted for by BRICS ( Table 7.2). Most of the reported funding for collaborative TB/HIV activities is accounted for by the African Region (77%), followed by Europe (16%). This is consistent with the distribution of the burden of TB/HIV: the latest estimates are that 75% of HIV-positive TB patients are in the African Region (Chapter 6).

7.3.3 Reported funding gaps in 2013 In 2013, funding gaps reported by NTPs (i.e. the difference between assessments by NTPs of funding needs for TB prevention, diagnosis and treatment and the actual amount of funds mobilized) amount to US$ 1 billion. This is a considerable increase from gaps in the range US$ 0.3–0.6 billion that were reported during the decade 2002–2011 (section 7.2). A possible explanation may be that NTPs are developing more ambitious plans for implementation and scale up of interventions with resulting increases in funding gaps. African countries account for almost half of the total (Figure 7.8a), followed by Asian countries (37% of the total). Funding gaps were reported by countries in all income groups with the exception of high-income countries (Figure 7.8b), and for multiple elements of TB prevention, diagnosis and treatment (Figure 7.8c).

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Figure 7.8

Funding gaps reported by national TB programmes in 125 countries with 96% of global cases, 2013 a. By region and income group Rest of World 15%

Africa 48%

Asia: Other 30%

Asia: Low income, high burden 7%

b. By income group Upper middle income 20% Low income 36%

Lower middle income 44%

c. By intervention area DS TB, first line drugs 3% Other 17% DS TB, excluding first line drugs 33%

TB/HIV 9%

MDR TB 13%

ACSM/CBC/PPM/PAL/OR surveys 25%

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Chapter 8

Research and development Key facts and messages ■■ Efforts to develop new TB diagnostics, drugs and vaccines have intensified during the past decade and considerable progress has been made. ■■ More than 50 companies are involved in the development of TB diagnostics. Although many new diagnostic technologies are available on the market, accelerated field evaluation of diagnostic accuracy and robustness of these assays is needed. ■■ Increased and sustained investment in new TB diagnostics remains essential for the development of an accurate, easy-to-use, affordable point-of-care assay for the rapid and early diagnosis of TB. ■■ There are 10 new or repurposed anti-TB drugs currently in late phases of clinical development. In December 2012, one of the new compounds, bedaquiline, was approved for use in treatment of patients with MDR-TB by the US Food and Drug Administration (FDA). Interim guidance about the use of bedaquiline in the treatment of MDR-TB was issued by WHO in June 2013. Bedaquiline is the first new drug approved for TB treatment in many years. ■■ Results from two Phase III trials of four-month regimens for the treatment of drug-susceptible TB are expected in late 2013. New combination regimens are also being tested in a series of early bactericidal activity (EBA) or two-month sputum-culture conversion Phase II studies. ■■ There are 10 vaccine candidates for TB prevention in Phase I, Phase II or Phase IIb trials and two immunotherapeutic vaccines in Phase II or Phase III trials. ■■ Results from a Phase IIb proof-of-concept study of the vaccine candidate MVA 85A were published in February 2013. Among infants who received the vaccine as a boost to the Bacille-Calmette-Guérin (BCG) vaccine, no additional protection was conferred compared with BCG alone. This study demonstrated, however, that the vaccine had an acceptable safety profile in this population, and that a high quality trial of a novel TB vaccine can be conducted and produce robust results in a high TB burden setting. ■■ Research and development is one of the three pillars of the WHO post-2015 global TB strategy, in recognition of its crucial role in accelerating reductions in TB incidence and mortality to reach post-2015 global TB targets.

The proposed goal of the post-2015 global TB strategy is to end the global TB epidemic (Chapter 1). Despite major progress in TB care and control since the mid-1990s (Chapters 2–7), reaching this goal will require major technological breakthroughs from the research and development pipeline. Short, effective and well-tolerated treatments for latent TB infection, a point-of-care diagnostic test able to distinguish latent TB infection from active TB disease, and an effective post-exposure vaccine are of key importance to end the global TB epidemic. This is the third successive year in which a chapter on research and development has been included in the Global tuberculosis report. The status of progress in the development of new TB diagnostics, drugs and vaccines as of July 2013 is summarized, drawing on information provided by the secretariats of the relevant Working Groups of the Stop TB Partnership and recent publications. Particular attention is given to developments between August 2012 and July 2013. The final section of the chapter highlights key elements of the research and development agenda post2015.

8.1 New diagnostics for TB Sputum smear microscopy remains the most widely used diagnostic test for TB, despite its relatively low sensitivity (especially for those with paucibacillary TB such as people living with HIV and children). The current reference standard for the bacteriological confirmation of TB is culture in liquid media. However, culture-based diagnosis is not widely available in most high TB burden settings because it requires sophisticated laboratory and biosafety infrastructure, and test results take up to several weeks to obtain. Recent breakthroughs include the development of rapid molecular tests that can be used to diagnose TB and rifampicin-resistant TB at decentralized levels of health systems. These tests are now being rolled out worldwide (see also Chapter 5). However, TB remains unique among the major infectious diseases in lacking accurate and rapid point-ofcare tests, largely due to insufficient progress in biomarker discovery despite active ongoing research. Indeed, the most pressing priority in TB diagnostics research today is the development of a simple, low-cost, instrument-free rapid test using one or more reliable biomarkers that can be implemented at the first point of patient contact with peripheral health services, or used as a triage test at community level to rapidly identify people who should be referred for confirmatory testing. The status of development and evaluation of new TB

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diagnostics in July 2013 is summarized in Figure 8.1, based on recent documentation produced by UNITAID1 and the Treatment Action Group (TAG).2 In Figure 8.1, diagnostic tests and methods on the market are grouped according to whether they have been evaluated by WHO and, if so, whether they have been endorsed. Given the rapidly evolving TB diagnostic landscape, WHO has established a systematic process for the timely evaluation of evidence and formulation of policy on new TB diagnostics. This is described in Box 8.1 and further details are available elsewhere. It should also be highlighted that the list of technologies in ‘early development’ is not necessarily complete or exhaustive.3 Those listed are the ones documented in the UNITAID and TAG reports. Development of molecular technologies such as nucleic acid amplification tests (NAATs) is most advanced i.e. either already commercially available or in late-stage development. The majority of tests are, however, intended for use at reference laboratory level only, requiring dedicated infrastructure and experienced staff. Most NAATs require manual preparation of samples, which is technically challenging and prevents their use at more decentralized laboratory levels. Testing in reference laboratories offers higher throughput of tests and/or improved screening of samples for drug resistance markers, but is typically relatively expensive. The next-generation molecular tests that have emerged since Xpert® MTB/RIF have not yet undergone rigorous field trials in the settings where their use is intended, and substantial challenges with sample processing and DNA extraction in peripheral laboratories has been reported for all of them. Technologies in the early stages of development (first part of Figure 8.1) include tests to detect TB, drug resistance, or TB and drug resistance combined. These include microarray-based multiplexing diagnostic platforms for the simultaneous detection of a large number of resistanceconferring mutations; assays that use novel approaches to combine nucleic acid testing with phage-based technology to identify drug resistance in clinical isolates; a rapid colorimetric culture-based method for detection of resistance to rifampicin, isoniazid and fluoroquinolones for use at the intermediate laboratory level; second-generation Xpert assays for the detection of resistance to drugs other than rifampicin; and a cartridge-based point-of-care isothermal amplification platform. In addition to technologies aimed 1

Figure 8.1

An overview of progress in the development and evaluation of TB diagnostics, July 2013 Technologies in early developmenta Volatile organic compounds " BreathLink, Menssana Research, USA " Prototype breath analyzer device, Next Dimensions Technology, USA Molecular technologies " Alere Q, Alere, USA " B-SMART, LabCorp, USA " Gendrive MTB/RIF ID, Epistem, UK " LATE-PCR, Brandeis University, USA " GeneXpert XDR cartridge, Cepheid, USA " TruArray MDR-TB, Akkoni, USA " INFINITIMTB Assay, AutoGenomics, USA Culture-based technologies " BNP Middlebrook, NanoLogix, USA " MDR-XDR TB Color Test, FIND, Switzerland/Imperial College, UK " TREK Sensititre MYCOTB MIC plate, Trek Diagnostic Systems/Thermo Fisher Scientific, USA Other technologies " TB Rapid Screen, Global BioDiagnostics, USA " TBDx, Signature Mapping Medical Sciences, USA

Evaluated by WHO but not yet endorsed due to insufficient evidence Molecular technologies " TB LAMP, Eiken, Japan " Genotype MTBDRsl, Hain Lifescience, Germany

On the market but evidence for use not yet submitted to WHO for evaluation Molecular technologies " iCubate System, iCubate, USA " TB drug resistance array, Capital Bio, China " EasyNAT TB Diagnostic kit, Ustar Biotechnologies, China " Truelab/Truenat MTB, Molbio/bigtec Diagnostics, India Non-molecular technologies " Alere Determine TB-LAM, Alere, USA

Evaluated by WHO and not recommended " Commercial serodiagnostics (all manufacturers) " Interferon-gamma release assays for the detection of active TB (all settings)

Technologies endorsed by WHO Molecular technologies " Xpert MTB/RIFb " Line probe assays (acid-fast bacilli smear-positive sputum specimens or culture-positive specimens) Microscopy " Ziehl-Neelsen and fluorescence microscopy methods Culture-based technologies " Commercial liquid culture systems and rapid speciation " Non-commercial culture and drug susceptibility testing methods a

Tuberculosis: Diagnostics Technology and Market Landscape 2013. Geneva, UNITAID/World Health Organization, 2013. Available at: http://www.unitaid.eu/images/marketdynamics/publications/ TB-Dx-Landscape_1-Jul-2013.pdf 2 Clayden P. et al (on behalf of The HIV i-Base/Treatment Action Group) 2013 Pipeline Report: HIV, Hepatitis C Virus (HCV), and Tuberculosis (TB) Drugs, Diagnostics, Vaccines, Preventive Technologies, Research Toward a Cure, and Immune-Based and Gene Therapies in Development. New York, Treatment Action Group, 2013. Available at: http://www.treatmentactiongroup.org/pipeline-report 3 Weyer K et al. Rapid molecular TB diagnosis: evidence, policy-making and global implementation of Xpert® MTB/RIF European Respiratory Journal erj01572-2012; published ahead of print 2012, doi:10.1183/09031936.00157212.

This is not an exhaustive list of technologies in early development. Those listed are the ones documented in recent (2013) publications by UNITAID and TAG. b Updated policy guidance on Xpert MTB/RIF is under development. See Chapter 5 for further details.

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Box 8.1

Evidence required for WHO review of new diagnostics Phase 1: Research and Development "" Upstream research and development to define and validate a prototype; "" Laboratory validation under international standards that culminates in a design-locked product; "" WHO interacts with developers if requested to discuss end-user requirements such as biosafety, assay robustness and intended settings of use. Phase 2: Evaluation and Demonstration "" The performance of the new diagnostic product should be evaluated in controlled trials at 3–5 trial sites in high-burden TB and HIV countries; "" Product registration with global and/or national regulatory authorities; "" Product specifications and performance should subsequently be validated in uncontrolled trials under field conditions in 5–10 trial sites in high-burden TB and HIV countries, and include cost-effectiveness studies. Phase 3: Evidence Assessment NEW TECHNOLOGIES "" Submission of a dossier with Phase I and Phase II data to WHO. FAST-FOLLOWER "" Manufactured under ISO 13:485 standards; "" Equivalent performance demonstrated – Supranational Reference Laboratory comparison; "" Structured evidence assessment using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach; "" WHO does not recommend technologies for individual country use. Phase 4: Phased uptake and collection of evidence for scale-up "" New diagnostic successfully implemented in routine diagnostic services by early implementers in high-burden countries; "" Systematic assessment of proposed algorithms, laboratory workload, operational constraints and costeffectiveness; "" Lessons learnt by early implementers used for country adaptation. Phase 5: Scale-up and Policy refinement "" Scale-up of the new diagnostic, with subsequent data used to inform and refine WHO policy guidance in a dynamic and on-going process.

at diagnosis of TB and drug-resistant TB, assays for use in monitoring patients’ response to treatment are needed as alternatives to culture. Ribosomal RNA (rRNA)-based amplification assays have potential to be used in this way, given that rRNA levels per TB bacilli are much higher than genomic DNA targets and that they are present only in viable organisms. Several new diagnostic technologies are on the market, but evidence to support their use has not been provided to WHO and thus their performance characteristics have not been assessed and WHO cannot recommend their use. As an alternative to real-time polymerase chain reaction (PCR) assays (e.g. Xpert MTB/RIF) or line-probe assays for the detection of TB and drug resistance, these technologies include PCR assays combined with DNA microarrays (arrays), which allow the detection of a greater number of resistance conferring alleles and may potentially offer superior performance for the rapid detection of drug resistance. The technologies include:  iCubate system (iCubate, USA). This is a multiplexed PCR assay that detects TB, non-tuberculous mycobacteria and drug resistance-conferring mutations in a single reaction. The assay allows multiple targets to be amplified with array detection technology that simultaneously analyses multiple targets. The assay is currently available for research purposes only.  Capital Bio Corporation (China) has developed a TB drug resistance detection array kit that can detect 14 of the most frequently found mutations in three genes associated with resistance to rifampicin and isoniazid. The assay is currently only appropriate for testing at reference laboratory level given the complexity of performing the assay.  EasyNAT TB Diagnostic kit, Ustar Biotechnologies, (China) has developed three isothermal based NAATs for the detection of TB as well as rifampicin and isoniazid resistance-conferring mutations. A clinical trial conducted in four provinces across central and northern China showed promising preliminary results for a rapid and easy-to-use screening tool for the diagnosis of pulmonary TB.  A micro-PCR system developed by Truelab™ (Molbio, India) was launched in 2013 in India. The system uses microchips with TB-specific genetic sequences for the quantitative detection of TB DNA in sputum samples in a one hour reaction from sample preparation to final reporting of results. Battery powered equipment is used for the steps of DNA extraction, amplification and detection. Although promising, only limited evaluation data are currently available.  Alere Determine LAM, (Alere, USA). This is an assay for the detection of M. tuberculosis lipoarabinomannan in urine. The assay seems to be most useful for the diagnosis of TB in people living with HIV who have a low CD4 count.

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Two tests are commercially available but have not been endorsed by WHO after evaluation. The first is a manual molecular assay to detect TB DNA in sputum specimens (TB-LAMP®, Eiken Chemical Co. Ltd., Japan). The evidence-based process followed by WHO concluded that the data available for the TB-LAMP assay were insufficient to proceed with the development of policy guidance. Additional independent evaluation studies to investigate TB-LAMP as a replacement test for culture are now underway in 16 countries (17 sites). The second assay evaluated by WHO but not endorsed is a line probe assay for detecting resistance to second-line anti-TB agents (GenoType® MTBDR sl, Hain Lifescience, Germany). This cannot be recommended as a replacement test for conventional phenotypic testing for drug susceptibility because of suboptimal sensitivity in detecting resistance to fluoroquinolones and second-line injectable agents. The latter group of drugs also share mutations, which means that even if they are detected by the line probe assay it is not possible to identify exactly which drug(s) is linked to the detected mutation(s), and therefore the test cannot be used to guide the choice of individual injectable drugs to be used in treatment regimens for MDRTB. Conventional phenotypic testing for drug susceptibility to second-line drugs therefore remains necessary for all detected strains of MDR-TB and to confirm or exclude XDR-TB. Two rapid molecular tests have been evaluated and endorsed by WHO in recent years (bottom of Figure 8.1). Line-probe assays that allow the rapid diagnosis of TB and drug resistance within a day were endorsed in 2008.1 Their use is currently limited to acid-fast bacilli sputum smear-positive samples or positive cultures. Xpert MTB/ RIF (Cepheid, Sunnyvale, CA, USA) was endorsed by WHO in 2010 for the rapid diagnosis (i.e. within 2 hours) of pulmonary TB and rifampicin-resistance in adults.2 In July 2013, the Xpert MTB/RIF assay remained the only fully automated real-time DNA-based cartridge test that can detect both TB and resistance to rifampicin, and the only mature technology representing a new generation of automated molecular diagnostic platforms. Since 2010, almost 100 articles on Xpert MTB/RIF have been published and others are underway.3 In 2013, given the amount of additional data, WHO commissioned three systematic reviews of the evidence on sensitivity and specificity of Xpert MTB/RIF as a test for pulmonary and extrapulmonary TB, in both adults and children. Findings were reviewed by an expert group and updated recommendations are anticipated in 2014 (see Chapter 5). The UNITAID 2013 Report: Tuberculosis: Diagnostic technology and market landscape4 describes the following four innovations to the Xpert MTB/RIF technology, which were made or under development in 2012 and 2013.  Assay improvements. A new prototype assay for MDRTB is in development. This uses new dyes and quenchers that increase the spectral range for detection of targets using 10 fluorophores rather than the six currently used.

 Remote calibration. This was made available in late 2012 and is already being used in more than 40 countries. It allows users to recalibrate the optical system, verify the functioning of the thermal system and conduct a series of system-level tests to ensure full system functionality within specifications. It is anticipated that over 90% of modules can be successfully calibrated over the internet.  Enhancements to data management. Real-time aggregation of geo-positioned test data (from which personal identifiers have been removed) is being evaluated in South Africa. This offers the potential to substantially improve monitoring of the TB epidemic and the associated programmatic response.  HIV cartridges for use with the GeneXpert platform. These are planned for release in 2014. A separate cartridge for the qualitative and quantitative detection of HIV viral load is in development. With over 50 companies working on TB diagnostics, there is now considerable industry interest in TB diagnostics. Nonetheless, a recent survey of more than 25 test developers identified several critical frequently-asked questions for which answers are required by industry to invest in TB diagnostic test development (www.tbfaqs.org). Test developers are particularly interested in identifying the most important attributes on which to focus test development efforts (examples include cost, sensitivity, specificity, infrastructure requirements, time to result, throughput, sputum versus other samples, manual versus automated, point-of-care versus centralized laboratory testing, integrated or reflex drug resistance test and which drugs are critical for DST). In addition, updated market analyses are urgently needed, given that the TB diagnostics market landscape has changed significantly since the last global assessment of the TB diagnostics market in 2006. 5 Updated market analyses and development of target product

1

2

3

4

5

Molecular Line Probe Assay for rapid screening of patients at risk of MDR-TB. Policy Statement. Geneva, World Health Organization, 2008. Available at http://www.who.int/tb/features_archive/policy_ statement.pdf Policy Statement: Automated real-time Nucleic Acid Amplification Technology for Rapid and Simultaneous Detection of Tuberculosis and Rifampicin Resistance: Xpert MTB/RIF System. Geneva: World Health Organization, 2011 (WHO/HTM/TB/2011.4). Available at http:// whqlibdoc.who.int/publications/2011/9789241501545_eng.pdf Weyer K et al. Rapid molecular TB diagnosis: evidence, policy-making and global implementation of Xpert® MTB/RIF European Respiratory Journal erj01572-2012; published ahead of print 2012, doi:10.1183/09031936.00157212. Tuberculosis: Diagnostics Technology and Market Landscape 2013. Geneva, UNITAID/World Health Organization, 2013. Available at: http://www.unitaid.eu/images/marketdynamics/publications/ TB-Dx-Landscape_1-Jul-2013.pdf Diagnostics for tuberculosis. Global Demand and market potential. Geneva, Special Programme for Research and Training in Tropical Diseases (TDR) and Foundation for Innovative New Diagnostics (FIND), 2006. Available at: http://www.who.int/tdr/publications/ documents/tbdi.pdf

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figure 8.2

The development pipeline for new TB drugs, July 2013a Discovery Preclinical development Clinical development

Lead optimization Cyclopeptides Diarylquinoline DprE Inhibitors InhA Inhibitor LeuRS Inhibitor Macrolides Mycobacterial Gyrase Inhibitors Pyrazinamide Analogs Riminophenazines Ruthenium (II) complexes Spectinamides Translocase-1 Inhibitors

Preclinical development CPZEN-45 DC-159a Q203 SQ609 SQ641 TBI-166

Good Laboratory Practice toxicity PBTZ-169 TBA-354

Phase I

Phase II AZD5847 Bedaquiline (TMC-207) Linezolid Novel Regimensb PA-824 Rifapentine SQ-109 Sutezolid (PNU100480)

Phase III Delamanid (OPC-67683) Gatifloxacin Moxifloxacin Rifapentine

Chemical classes: fluoroquinolone, rifamycin, oxazolidinone, nitroimidazole, diarylquinoline, benzothiazinone a b

Details for projects listed can be found at www.newtbdrugs.org/pipeline and ongoing projects for which a lead compound has not been identified can be viewed at www.newtbdrugs.org/pipeline-discovery. Combination regimens: NC-001-(J-M-Pa-Z), Phase IIa; NC-002-(M-Pa-Z), Phase IIb; NC-003-(C-J-Pa-Z), Phase IIa; PanACEA-MAMS-TB-01-(H-R-Z-E-Q-M), Phase IIb.

profiles could facilitate greater engagement of test developers in TB diagnostics. Despite good progress with the pipeline for new diagnostics, much more effort and investment are needed by both donors and manufacturers to expedite evaluations of new technologies in different epidemiological settings in order to determine their diagnostic accuracy and robustness in the settings of intended use. Substantial additional funding and innovation for new TB diagnostic development remain essential to ensure the availability of tests that are reliable, easy to use, affordable, and accessible to all those with TB. More than ever, the TB diagnostic pipeline needs increased and sustained investment.

The status of the pipeline for new anti-TB drugs in July 2013 is shown in Figure 8.2. There are seven drugs in Phase II (early bactericidal activity, EBA, and eight-week culture conversion) trials and four drugs in Phase III (efficacy) trials. In total, there are 10 new or repurposed drugs in Phase II or Phase III trials; one drug (rifapentine, a rifamycin that has a longer half-life than rifampicin) is in both Phase II and Phase III trials, for different indications.

8.2.1 Phase III trials Results from a Phase III trial (the ‘Rifaquin trial’) that evaluated the safety and efficacy of two regimens for patients with drug-susceptible TB, in which moxifloxacin was substituted for isoniazid in the intensive phase of treatment and rifapentine was used in the continuation phase of treatment, were presented in March 2013.1 A total of 827 patients with drug-susceptible TB were enrolled in Botswana, South Africa, Zambia and Zimbabwe. Both new regimens were well tolerated. The six-month regimen with a weekly dose of rifapentine (1200 mg) and moxifloxacin in the continuation phase was not inferior to the currently recommended regimen. However, the four-month regimen with twice-weekly doses of rifapentine (900 mg) and moxifloxacin in the continuation phase was clearly inferior to the currently recommended regimen. Two Phase III trials are evaluating four-month combination regimens in which a fluoroquinolone (gatifloxacin in the case of the OFLOTUB trial and moxifloxacin in the case of the ReMOX trial) is substituted for either ethambutol (in the 1

8.2 New drugs to treat and prevent TB The anti-TB drugs currently used in first-line treatments are around 50 years old. The regimen that is currently recommended by WHO for new cases of drug-susceptible TB is highly efficacious, with cure rates of around 90% in HIV-negative patients. Nonetheless, it requires six months of treatment with first-line drugs (a combination of rifampicin, isoniazid, ethambutol and pyrazinamide for two months, followed by a four-month continuation phase of rifampicin and isoniazid). Regimens for treatment of MDR-TB currently recommended by WHO entail at least 20 months of treatment with second-line drugs for most patients, and are associated with multiple (and sometimes serious) sideeffects and lower cure rates (see Chapter 4). There are also interactions between anti-TB treatments and antiretro­ viral therapy (ART) for people living with HIV. New drugs are required to shorten and simplify treatment, to improve the efficacy and tolerability of treatment for MDR-TB and to improve the treatment of TB among people living with HIV. 90 GLOBAL TUBERCULOSIS REPORT 2013

Jindani A et al. 2013. A Multicentre Randomized Clinical Trial to Evaluate High-dose Rifapentine with a Quinolone for Treatment of Pulmonary TB: The RIFAQUIN Trial. Oral abstract and paper 147LB. 20th Conference on Retroviruses and Opportunistic Infections (CROI), March 3–6 2013, Atlanta.

Box 8.2

WHO interim guidance on the use of bedaquiline to treat MDR-TB WHO estimates that about 450 000 new cases of MDR-TB occur worldwide each year (Chapter 2). Current drug regimens recommended by WHO for treatment of MDR-TB present many challenges: treatment lasts 20 months or more, and requires daily dosages of drugs that are more toxic, less effective, and far more expensive than those used to treat drug-susceptible TB.a Globally, only about 50% of patients who start MDR-TB therapy are treated successfully (Chapter 4). For the first time in over 40 years, a new TB drug with a novel mechanism of action – bedaquiline – has become available for use. It was approved by the US FDA in December 2012, following an accelerated approval process. There is considerable interest in the potential of this drug to treat MDR-TB. However, information remains limited, since it has only been evaluated in two Phase IIb trials for safety and efficacy. For these reasons, WHO has issued “interim policy guidance”.b This interim guidance provides advice on the inclusion of bedaquiline in combination therapy for MDR-TB in accordance with the existing WHO guidelines for the programmatic management of drug-resistant TB.a The interim guidance lists five conditions that must be fulfilled for bedaquiline to be used to treat adults with MDR-TB: 1. Effective treatment and monitoring. Treatment must be closely monitored for effectiveness and safety, using sound treatment and management protocols approved by relevant national authorities. 2. Proper patient inclusion. Special caution is required when bedaquiline is used in people aged 65 and over, and in adults living with HIV. Its use among pregnant women and children is not advised. 3. Informed consent. Patients must be fully aware of the potential benefits and risks of the new drug, and give documented informed consent before embarking on treatment. 4. Adherence to WHO recommendations. All principles on which WHO-recommended MDR-TB treatment regimens are based must be followed. In particular, four effective secondline drugs must be part of the regimen. In line with the general principles of TB treatment, bedaquiline should not be introduced into a regimen in which the companion drugs are failing to show effectiveness. 5. Active pharmacovigilance and management of adverse events. Active pharmacovigilance measures must be in place to ensure early detection and proper management of adverse drug reactions and potential interactions with other drugs. WHO strongly recommends the acceleration of Phase III trials to generate more comprehensive evidence that can inform future policy guidance on bedaquiline. The organization will review, revise or update the interim guidance as additional information on efficacy and safety becomes available. WHO is also developing a document that will provide operational guidance on the implementation of bedaquiline and is working with partners to help ensure rational introduction of the drug. a

Guidelines for the programmatic management of drug-resistant tuberculosis – 2011 update. Geneva, World Health Organization, 2011 (WHO/HTM/TB 2011.6). b The use of bedaquiline in the treatment of multidrug-resistant tuberculosis: interim policy guidance. World Health Organization. Geneva, Switzerland. 2013 (WHO/HTM/TB/2013.6).

OFLOTUB trial) or ethambutol or isoniazid (in the ReMOX trial). The results from both trials are expected in late 2013. A new compound, delamanid (OPC-67683), is currently being tested in a Phase III trial as an adjunct to existing optimized regimens for treatment of MDR-TB.

8.2.2 Phase II trials – individual compounds The safety, tolerability and antimicrobial activity of an increased daily dose of rifapentine (at 10, 15 and 20 mg/ kg) in combination with isoniazid, pyrazinamide and ethambutol during the first two months of treatment are being investigated in a Phase IIb trial (TBTC trial 29X). Early results were reported in May 2013.1 These showed that rifapentine-based regimens were well-tolerated, with no toxicity events specifically related to increasing doses of the drug. Compared with the currently recommended six-month regimen, a higher proportion of patients who received the regimens including rifapentine had converted to culture-negative status (both in solid and liquid 1

Moro et al. Tolerability and safety of escalating Rifapentine (RPT) doses during the first two months of tuberculosis (TB) treatment. Abstract A6051. American Thoracic Society International Conference, Philadelphia, May 17–22, 2013

medium) after eight weeks. Among patients receiving the regimen with the highest dose of rifapentine, 100% were culture-negative after eight weeks of treatment (compared with 16 weeks for those receiving the current standard of care). The trial investigators concluded that the robust antimicrobial activity alongside the good tolerability and safety of the compound at increasing doses justified the assessment of daily high-dose rifapentine in regimens of shorter than six months duration in a Phase III trial. Among other drugs tested in Phase II trials, the highest-profile in the past year is bedaquiline (TMC-207). The US Food and Drug Administration (FDA) approved the use of bedaquiline as an adjunct to existing regimens for the treatment of MDR-TB in December 2012, under an accelerated procedure. Bedaquiline became the first new TB drug to be approved for use in 40 years. A Phase III trial, which will investigate the safety and efficacy of bedaquiline when used in combination with a short MDR-TB regimen, is scheduled to start before the end of 2013. Following the release of trial results and the FDA decision, WHO issued interim guidance about the use of bedaquiline in the treatment of MDR-TB in June 2013 (Box 8.2). Five other individual compounds are in the Phase II

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development phase. These are linezolid, sutezolid, PA-824, SQ-109 and AZD-5847. Linezolid (a member of the oxazolidinone antibiotic class of drugs) was approved in 2000 for the treatment of drug-resistant, gram-positive bacterial infections. It has good anti-mycobacterial activity in vitro and is increasingly used ‘off-label’ for patients who have highly drug-resistant TB. However, serious adverse events (such as peripheral and optic neuropathies, anaemia and thrombocytopenia) have been reported. Results from a prospective, randomized trial in which linezolid was used to treat patients with XDR-TB who had not responded to other available chemotherapeutic options were published in late 2012.1 A total of 41 patients were randomly assigned to linezolid therapy (600 mg per day), which was either started immediately or after two months without any change to the background regimen. After confirmed sputum-smear conversion or after four months of treatment (whichever came first), patients underwent a second randomization to continue linezolid therapy at a dose of either 600 mg or 300 mg per day for at least an additional 18 months, with close monitoring of toxicity. The results showed that at four months, 15 of the 19 patients (79%) in the immediate-start group and 7 of the 20 (35%) in the delayed-start group had converted to culture-negative status (p = 0.001). Most patients (34 of 39 [87%]) had a negative sputum culture within six months after linezolid had been added to their drug regimen. Of the 38 patients treated with linezolid, 31 (82%) had clinically significant adverse events that were possibly or probably related to linezolid, including three patients who discontinued therapy. Patients who received 300 mg per day after the second randomization had fewer adverse events than those who continued taking 600 mg per day. Thirteen patients completed therapy and had not relapsed at the end of follow up. Four cases of acquired resistance to linezolid were observed. Trial investigators concluded that linezolid was effective at achieving culture conversion among patients with chronic XDR pulmonary TB, but warned that patients must be monitored carefully for adverse events. Study limitations include the small number of patients evaluated, and that 10% of patients acquired resistance to linezolid. Further data are needed to balance the long-term risks and benefits of linezolid when used as part of a combination regimen with other effective anti-TB drugs. Sutezolid (PNU-100480) is an oxazolidinone and an analogue of linezolid. It has been tested in an EBA study at doses of either 600 mg twice a day or 1200 mg once a day. Results were presented in 2012 and showed that sutezolid led to a significant reduction in log colony forming units (CFU) counts compared with the baseline level following 14 days of treatment, using both dosage options.2 The results suggested a superior response with the 600 mg twice-daily dose. PA-824 is a nitroimidazole compound that is being tested as part of several potential combination regimens (see below).

SQ-109, originally synthesized as a derivative of ethambutol, is also being tested as part of a combination regimen (see below). AZD-5847 is being tested in a Phase II trial.

8.2.3 Phase II trials – new regimens Besides individual compounds, new combinations of drugs are or will soon be tested in various Phase II trials. In the Global tuberculosis report 2012, the results of the EBA study of a new combination regimen (NC-001) that included moxifloxacin, pyrazinamide and the novel drug PA-824 were summarized.3 Three trials of various combination regimens are currently underway. The first of these is NC-002 , which is building on the NC-001 study to test the same regimen in a two-month trial. The trial is being implemented in South Africa and the United Republic of Tanzania. The regimen is being tested in patients with drug-susceptible TB and in patients who have drug-resistant TB but not resistance to the drugs included in the new regimen. The NC-002 trial is a landmark trial, since it is the first to simultaneously investigate treatment of both drug-sensitive and drugresistant TB with the same regimen. Results are expected at the end of 2013.4 The second trial, NC-003, is testing the EBA of various combinations of clofazimine, bedaquiline, PA-824 and pyrazinamide in patients with drug-susceptible TB.5 The MAMS-TB-01 trial, conducted by the PanACEA consortium, is evaluating new three-month combination regimens using a new adaptive study design.6 The drugs included in the combination regimens are isoniazid, rifampicin, pyrazinamide, ethambutol, moxifloxacin and SQ-109. The end-point of the trial is time to culture conversion in liquid media. The trial started in May 2013.7

8.2.4 New developments in the treatment of latent TB infection New drugs are being tested for the treatment of latent TB infection (LTBI) in people without active TB disease. Rifapentine has been investigated as part of a combined regimen (TBTC 26, also called PREVENT-TB), and the first results were published in December 2011.8 Enrolment and 1 Lee

M et al. Linezolid for Treatment of Chronic Extensively Drug-Resistant Tuberculosis. New England Journal of Medicine 2012;367:1508-18. DOI: 10.1056/NEJMoa1201964 2 Wallis R et al. Safety, tolerability and early bactericidal activity in sputum of PNU-100480 (sutezolid) in patients with pulmonary tuberculosis (Abstract THLBB02). 19th International AIDS Conference 2012, July 22–27, Washington DC. 3 Diacon AH et al. 14-day bactericidal activity of PA-824, bedaquiline, pyrazinamide and moxifloxacin combinations: a randomised trial. The Lancet, 2012 4 See: http://clinicaltrials.gov/show/NCT01498419 5 See: http://clinicaltrials.gov/show/NCT01691534 6 Phillips P et al. Innovative trial designs are practical solutions for improving the treatment of tuberculosis. Journal of Infectious Diseases. 2012;205 Suppl 2:S250–7. 7 See: http://clinicaltrials.gov/show/NCT01785186 8 Sterling T et al. Three Months of Rifapentine and Isoniazid for Latent Tuberculosis Infection. New England Journal of Medicine 2011; 365;23: 2155–66.

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Box 8.3

Raising the profile of treatment for latent TB infection One third of the world’s population is estimated to be latently infected with M. tuberculosis. People with latent TB infection (LTBI) do not have symptoms of TB and are not infectious, but they are at risk of developing active disease and becoming infectious. Studies show that 5–20% of those infected will develop active TB at some point in their lifetime, with the majority developing TB disease within 2–5 years of the initial infection. Several factors increase the risk of progressing from infection to active TB disease: immunosuppression (for example, related to HIV infection or immunosuppressive treatment), malnutrition, diabetes and alcohol abuse. Preventing active TB by addressing these risk factors as well as proper diagnosis and treatment of LTBI in selected risk groups is thus important for the individual and public health. Modelling has shown that diagnosis and treatment of LTBI could play a key role in TB elimination. WHO has recently published guidelines on TB contact investigation and on systematic screening of active TB,a,b both of which offer an entry point to identification of risk groups for LTBI diagnosis and treatment. Isoniazid preventive therapy (IPT) is the mainstay of current WHO recommendations on treatment of LTBI. Treatment is recommended for two specific population groups: people living with HIV, and children less than five years old who are household or close contacts of TB patients. A recent Cochrane review showed that rifampicinand rifapentine-containing regimens among HIV negative people have higher completion rate and fewer adverse events compared with those based on IPT only.c Before initiating LTBI treatment, it is essential that active TB is effectively ruled out and the diagnosis of LBTI reliably established. The tuberculin skin test (TST) and interferon-gamma release assays (IGRA) are designed to detect a cellular immune response to M. tuberculosis, but do not differentiate between latent infection and active disease and, if negative, do not allow TB infection to be ruled out. Most importantly, they cannot accurately predict the risk of infected individuals developing active TB disease, and their use in routine practice poses operational and resource challenges. There are several unanswered questions related to the detection and management of LTBI that require urgent scientific attention and increased research investments. There is still limited understanding of the fundamental biology of latency and there are no truly adequate animal models to study it. There is also no diagnosis and treatment for people who are latently infected with drugresistant strains of M. tuberculosis. Expediting the discovery of robust tools to effectively diagnose and treat LTBI is crucially important for global TB control. Particular emphasis needs to be given to development of a better understanding of the basic pathogenesis of M. tuberculosis and the identification of biomarkers that will enable reliable diagnosis and shorter and less toxic treatment for LTBI. Following recent developments in the treatment of LTBI, WHO plans to update its guidelines on the management of LTBI. This will entail a review of the existing evidence with a particular focus on risk groups that have the highest likelihood of progression to active TB disease following infection, and due consideration to risk-benefit analysis and concomitant risk factors. a

Recommendations for investigating contacts of persons with infectious tuberculosis in low- and middle-income countries. Available at http://apps.who.int/iris/ bitstream/10665/77741/1/9789241504492_ eng.pdf b Systematic screening for active tuberculosis – Principles and recommendations. Available at http://apps.who.int/iris/bitstream/ 10665/84971/1/9789241548601_eng.pdf c Sharma SK et al. Rifamycins (rifampicin, rifabutin and rifapentine) compared to isoniazid for preventing tuberculosis in HIV-negative people at risk of active TB. Cochrane Database of Systematic Reviews 2013, Issue 7. Art. No.: CD007545. DOI: 10.1002/14651858.CD007545. pub2.

follow-up for two groups of particular interest (young children 2–11 years of age, and people living with HIV) were extended and are scheduled to end in September 2013. Preliminary results showed that the once-weekly, three month regimen of rifapentine and isoniazid (3HP) was generally well-tolerated and offered ‘substantial advantages’ compared with the current standard of nine months of isoniazid for treatment of LTBI in children.1 Study 33, also called iAdhere, is a follow-up Phase IV study of TBTC 26, investigating the effectiveness of the 3HP combination (tested in PREVENT-TB), either given by: (1) DOT, (2) self-administered, or (3) self-administered with text message reminders by cell phone. This study is expected to be completed in March 2014. A second study is an AIDS Clinical Trials Group (ACTG) trial of daily rifapentine and isoniazid for one month to treat LTBI in people living with HIV. A third study to evaluate the effect of single and repeated administration of rifapentine (given as a daily or weekly regimen) on steadystate pharmacokinetic parameters of efavirenz, emtricitabine and tenofovir given as a fixed dose combination

(ATRIPLA™) started patient enrolment in September 2012 and recruitment was completed in August 2013. A fourth study to compare the safety and effectiveness of a four-week daily regimen of rifapentine and isoniazid with a standard nine-month regimen of daily isoniazid among people living with HIV started patient enrolment in May 2012 and is expected to complete enrolment in March 2018. A fifth study to determine the safety and tolerability of a fourmonth, once daily rifampicin regimen in children is being conducted by the Canadian Institutes of Health Research and McGill University and results are expected in 2016.2 1 Villarino

et al. Tolerability among children of three months of once-weekly rifapentine + INH (3HP) vs. 9 months of daily INH (9H) for treatment of latent tuberculosis infection: The PREVENT TB Study (TBTC Study 26/ACTG 5259). IDSA Conference 2012. 2 Clayden P et al, on behalf of the HIV i-Base/Treatment Action Group. 2013 Pipeline Report: HIV, Hepatitis C Virus (HCV), and Tuberculosis (TB) Drugs, Diagnostics, Vaccines, Preventive Technologies, Research Toward a Cure, and Immune-Based and Gene Therapies in Development. Available at: http://www.treatmentactiongroup.org/ pipeline-report

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8.3 New vaccines to prevent TB The slow decline in TB incidence globally and the growing problem of MDR-TB highlight the critical need for new effective TB vaccines. The BCG vaccine for the prevention of TB is almost 100 years old, and while the vaccine protects against severe forms of TB in children (TB meningitis and miliary TB), its efficacy in preventing pulmonary TB in adults is highly variable. BCG is also not recommended for use in infants known to be infected with HIV, due to the risk of disseminated BCG disease. The development of techniques for genetic manipulation of mycobacteria, completion of the genome sequence of M. tuberculosis in the 1990s, and recent advances in immunology provide historic opportunities for developing a new generation of TB vaccines that can achieve dramatically higher levels of impact. For the past decade, two major strategies have been used to develop new vaccines for prevention of TB.1 One strategy has been to develop vaccines that would have a higher efficacy than BCG and replace it – such as an improved version of BCG or a new attenuated live M. tuberculosis vaccine. The second strategy has been a ‘prime-boost’ strategy in which BCG continues to be given to neonates (as is done currently, since it prevents TB in infants and children), and a new vaccine is given as a ‘booster’ dose to increase the efficacy and extend the duration of protection. Modelling of the potential public health impact of new TB vaccines in the WHO South-East Asia Region suggested that a TB vaccine for infants with 60% efficacy would contribute to a significant decline in TB incidence by 2050.2 Furthermore, this modelling also indicated that if a preventive TB vaccine of similar efficacy among adolescents and adults was delivered as part of a mass vaccination strategy, the impact on the TB epidemic would be much larger. More recent modelling of the public health impact of a new vaccine at global level3 has reinforced this finding, indicating that an adolescent and adult vaccine with 60% efficacy could potentially avert 30‒50 million new TB cases over a 25 year period. The much greater potential impact of an adult/adolescent vaccine has shifted the focus of TB vaccine development towards a new paradigm that emphasizes the development of a diverse pipeline of new TB vaccine candidates that target the prevention of TB in this older population. Scientific advances have also enabled the pursuit of more sophisticated approaches to vaccine design, and the global pipeline of TB vaccine candidates in clinical trials is more robust than at any previous period in history, now including recombinant BCGs, attenuated M. tuberculosis strains, recombinant viral-vectored platforms, protein/adjuvants combinations, and mycobacterial extracts. The status of the pipeline for new vaccines in July 2013 is shown in Figure 8.3. There are 12 vaccine candidates in clinical trials. Most are designed for prevention of TB, either to prevent infection (pre-exposure) or to prevent primary progression to disease or reactivation of latent TB (postexposure). Two are BCG replacement vaccines and two are proposed as immunotherapeutic agents, to improve responsiveness to chemotherapy or prevent relapse or re-infection.

Two vaccines are in Phase IIb studies. MVA85A is an attenuated vaccinia-vectored vaccine candidate expressing Ag85A of M. tuberculosis. It was designed as a booster vaccine for BCG vaccinated infants and the first Phase IIb trial of this vaccine was conducted in South Africa from 2009 to 2012 with results published in early 2013 (Box 8.4).4 An additional Phase IIb trial of MVA85A is currently being conducted in adults living with HIV in Senegal and South Africa; the trial has been recently re-designed as a safety trial in which up to 650 participants will be enrolled. M72+AS01E is a protein subunit vaccine, formulated in a novel adjuvant to enhance immunogenicity. It contains a fusion protein of the M. tuberculosis antigens 32A and 39A in the adjuvant AS01E. Safety and immunogenicity are being tested in three different populations: infants in The Gambia, people living with HIV in India and adults with TB disease in China (Province of Taiwan) and Estonia. The Phase IIb study will be the largest trial of a novel TB vaccine in adults, aiming to enrol 4500 HIV-negative adults in TB-endemic countries in Africa. The primary endpoint will be the protective efficacy of two doses of M72+ AS01E against pulmonary TB disease. Secondary endpoints include safety and immunogenicity. There are six additional vaccines in Phase II trials. AERAS-402/Crucell Ad35 is an adenovirus-vectored vaccine candidate expressing three M. tuberculosis antigens: Ag85A, Ag85B and TB10.4. It is designed as a booster vaccine for infants, adolescents and adults. Although started as a Phase IIb proof-of-concept trial, based on preliminary data the trial is now being revised to be a smaller Phase II trial with safety and immunogenicity as primary endpoints. Of note, AERAS-402/Crucell Ad35 and MVA85A are also being tested in combination, to try to drive a balanced CD4+/CD8+ immune response. One or two doses of AERAS-402/Crucell Ad35 followed by a dose of MVA85A are being evaluated in a combined Phase I/Phase II trial in adults in the United Kingdom for safety and immuno­ genicity. Three vaccines are protein subunit adjuvanted vaccines, initially developed by the Statens Serum Institute in Copenhagen, Denmark. Hybrid 1 + IC31 contains Ag85B and ESAT-6 in an adjuvant, IC31. Hybrid 56 + IC31 contains antigens 85B and ESAT6 as well as AgRv2660, which is expressed during latency. Hybrid 4 + IC31, now being developed with Sanofi Pasteur, is a fusion protein candi1

Evans TG, Brennan MJ, Barker L and Thole J. Preventive vaccines for tuberculosis. Vaccine. 31S (2013) B223– B226. 2 Abu-Raddad LJ, et al. Epidemiological benefits of more-effective tuberculosis vaccines, drugs, and diagnostics. Proceedings of the National Academy of Science. 2009. 106:33; 13980–13985. 3 A model of the global public health impact of new TB vaccines was commissioned by Aeras and developed by Applied Strategies. Formal publication of the model and associated results is pending. 4 Tameris MD, et al. Safety and efficacy of MVA85A, a new tuberculosis vaccine, in infants previously vaccinated with BCG: a randomised, placebo-controlled phase 2b trial. The Lancet. 2013. 381:9871; 1021–1028.

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figure 8.3

The development pipeline for new TB vaccines, July 2013 Phase I AdAg85A McMaster, CanSino Phase II VPM 1002 Max Planck, VPM, TBVI, Serum Institute Phase IIb MVA85A/AERAS-485 Oxford, Aeras, EDCTP Phase III M. Vaccae Anhui Longcom

P  B  P I MTBVAC TBVI, Zaragoza, Biofabri

P  B H1+IC31 SSI, TBVI, EDCTP, Intercell

B  P I  i t M72+AS01 GSK, Aeras

i t

P ID93+GLA-SE Infectious Disease Research Institute (IDRI), Aeras

B  P I

P  B  P I RUTI Archivel Farma, S.L.

B Crucell Ad35/MVA85A Crucell, Oxford, Aeras

B  P I  i t H56/AERAS-456+IC31 SSI, Aeras, Intercell

P  B

P  B  P I H4/AERAS-404+IC31 SSI, Sanofi Pasteur, Aeras, Intercell

P

Prime 

B Boost  P I Post-infection  i t Immunotherapy

B Crucell Ad35/AERAS-402 Crucell, Aeras

B

TB Vaccine Types Viral-vectored: MVA85A, AERAS-402, AdAg85A Protein/adjuvant: M72, Hybrid-1, Hyvac 4, H56, ID93 rBCG: VPM 1002 Killed WC or Extract: Mw, RUTI Source: Tuberculosis Vaccine Candidates, Working Group on New Vaccines

date that expresses Ag85B and TB10.4; the latter antigen is from the same gene family as ESAT-6. All three vaccines are being studied in Phase IIa clinical trials in Africa. VPM 1002 is a live recombinant vaccine, derived from the Prague strain of BCG into which the listerolysin gene from Listeria monocytogenes has been cloned and the urease gene deleted to improve immunogenicity. A Phase IIa trial of this vaccine has recently been completed in South Africa. A second Phase II trial will assess the safety and immunogenicity of the vaccine in HIV exposed/unexposed newborns. RUTI is a non-live vaccine based on fragmented M. tuberculosis bacteria. It is in a Phase IIa trial in Spain and is being developed as an immunotherapeutic vaccine. In addition to the vaccine candidates described above, AnHui Longcom, a Chinese pharmaceutical company, is studying Mycobacterium vaccae, a non-living preparation from the non-pathogenic bacterium, as an adjunct to standard antimicrobial therapy. Phase III efficacy studies are reportedly underway. There are three vaccine candidates in Phase I clinical trials. These include the first live attenuated M. tuberculosis vaccine, MTBVAC, as well as a new fusion protein vaccine, ID93, formulated with a novel adjuvant GLA-SE. MTBVAC is being developed by the University of Zaragosa, Institut Pasteur, BIOFABRI and the Tuberculosis Vaccine Initiative (TBVI). It is a live M. tuberculosis strain attenuated via deletions of the phoP and fad D26 genes. It is the first live attenuated M. tuberculosis vaccine to enter a Phase I clinical trial. ID93+GLA-SE is a recombinant fusion protein formulated in the novel adjuvant, GLA-SE. It is being developed

by the Infectious Disease Research Institute (IDRI) in collaboration with Aeras. It expresses three M. tuberculosis virulence antigens (Rv2608, Rv3619 and Rv3620) and one M. tuberculosis latency antigen (Rv1813). It is beginning a Phase 1b trial in adults in South Africa to assess safety and immunogenicity in this population. Ad5 Ag85A is an adenovirus serotype 5 vector expressing Ag85A. It has been developed by McMaster University with support from CanSino, a Chinese biotechnology company based in Tianjin. The vaccine was recently evaluated in a Phase I trial that demonstrated no vaccine-related serious adverse events and showed greater immunogenicity in the study group primed with BCG. Research on new TB vaccines is now at a crucial juncture. Despite the diversity that already exists in the global portfolio of TB vaccine candidates in clinical trials, there is growing recognition among scientists and researchers in the field that there is still too much similarity in the immunological strategies being pursued.1 In the absence of known immune correlates for either protective immunity against TB or control of infection, the portfolio must be further diversified so that candidates explore a different and novel immunological ‘space’. There is already a robust pipeline of candidates being evaluated pre-clinically – including nucleic acid-based (DNA and RNA) vaccines – and these pursuits may help to broaden the diversity of the clinical portfolio and fill the scientific gaps that currently exist. To rationalize and streamline the advancement of TB vaccine candidates, consensus has been 1

Evans TG et al. Preventive vaccines for tuberculosis. Vaccine 31S (2013) B223– B226.

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Box 8.4

The MVA85A trial in South Africa MVA85A is a poxvirus (“Modified Vaccinia Ankara”, MVA)-vectored vaccine that expresses the immune-dominant M. tuberculosis antigen 85A. It was originally developed at the University of Oxford. An infant Phase IIb proofof-concept trial was recently completed in South Africa.a The study population consisted of 2794 BCG-vaccinated, HIV-negative infants aged 4–6 months, with both study arms almost equally sized: 1399 infants received one dose of MVA85A, while 1395 infants in the control arm received a placebo (Candin, a C. albicans-derived skin test antigen). Follow up lasted 37 months. The primary objective of the study was to assess the safety of MVA85A in these infants. The secondary objectives were to evaluate the efficacy of the vaccine against: (a) the disease and (b) M. tuberculosis infection, as measured by Quantiferon conversion (this distinction is important as infection only leads to active TB disease in a small minority of immunecompetent individuals). Additional objectives included the evaluation of immunogenicity. Conclusions drawn from the results of the Phase IIb trial This was the first clinical trial to evaluate the efficacy of a new TB vaccine candidate for prevention of clinical TB or M. tuberculosis infection, and results were therefore of considerable interest to the vaccine research and public health communities. In this trial, MVA85A appeared to be safe and well tolerated, confirming similar findings from previous Phase I and Phase IIa clinical trials using this vaccine. None of the observed serious adverse events (or deaths) observed in the study arm were assessed by the investigators to be related to the vaccine, and only one serious adverse event involving a brief hospitalization occurred in the placebo group. The primary efficacy analysis was based on the number of TB cases among the vaccinated versus control subjects. In the vaccine arm, there were 32 cases, while in the placebo arm there were 39 cases. Based on this, the calculated vaccine efficacy was 17.3% (95% CI: -31.9% to 48.2%) for the primary TB case definition, which was not statistically significant. Moreover, there was no evidence of protection against M. tuberculosis infection: using the Quantiferon-TB Gold assay as the readout. A total of 349 out of 2792 infants became infected (178 in the vaccine arm and 171 in the placebo arm), giving a calculated vaccine efficacy of –3.8% (95% CI: -28.1% to 15.9%), which was also not statistically significant. Implications for future studies of this and other TB vaccine candidates Phase IIb proof–of-concept trials are designed to allow ‘triage’ of vaccine candidates and target populations, to decrease risks before embarking on hugely complex and resource consuming Phase III trials. Current regulations require a Phase IIb proof–of-concept trial to be corroborated in larger Phase III trials before a vaccine can be licensed. This study demonstrated that the vaccine had an acceptable safety profile in infants, and that a high quality trial of a novel TB vaccine can be conducted and produce robust results in a high TB burden setting. The vaccine was given months after all the infants had received BCG vaccine, and it is possible that BCG may have provided a plateau level of protection, with very little, if any additional protection added by MVA85A. Rates of TB in South Africa (and the Western Cape province in particular) are exceptionally high in all age groups, including young children, and this high force of infection may be difficult to address with any vaccine. It cannot be assumed that similar results would have been obtained in other populations. It is also possible that adults, adolescents and older children could be a better target population for this vaccine: there is some evidence that it induces a stronger immune response in older age groups than in infants. Adults and adolescents are the primary source of transmission as they more likely to develop the most infectious forms of the disease and account for the largest share of the burden of TB disease worldwide. The vaccine is currently being evaluated in HIV-infected adults in Senegal and South Africa, using a two-dose regimen. For all these reasons, the results of the trial should not be considered as providing any definitive answer to the question of whether a new TB vaccine can provide better protection than BCG alone. Further studies of this and other vaccines are urgently needed. Several of the other TB vaccine candidates in the clinical pipeline differ from MVA85A both in their antigenic composition and in the way these antigens are delivered. a

Tameris MD, et al. Safety and efficacy of MVA85A, a new tuberculosis vaccine, in infants previously vaccinated with BCG: a randomized, placebo-controlled phase 2b trial. The Lancet. 2013. 381:9871; 1021–1028.

developed among key stakeholders on ‘stage-gating’ criteria for new TB vaccines, and increased emphasis is being placed on global coordination among key stakeholders to advance a common research agenda. To supplement these existing efforts, a re-prioritized focus on early stage research is also underway. In accordance with this shift in emphasis, more energy and resources will be directed towards the pursuit of novel designs, to studies focused on immunological mechanisms and biomarkers, and to a diversification of scientific approaches and strategies to ensure that a more diverse pipeline of new TB vaccine candidates moves forward into clinical trials.1

8.4 The post-2015 global TB strategy: the critical role of research and development Fundamental science is necessary to drive innovations in new tools for improved TB care and control. Fundamental research is required to better characterize M. tuberculosis and to improve understanding of the interaction between the bacillus and the human host, as a basis for maintaining the flow of new technologies into the product pipeline. Researchers are making great strides in redefining the 1

Brennan MJ and Thole J (editors). Tuberculosis vaccines: A strategic blueprint for the next decade. Tuberculosis. 2012. 92: Supplement 1; S6–S13.

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spectrum of TB disease and the transition from latent to active TB, and developing a better understanding of the behaviour of M. tuberculosis within the host. This progress is expected to deliver better knowledge about pathogenesis and identification of biomarkers and bio-signatures relevant to new TB diagnostics. It is also expected to point to new targets for anti-TB drugs as well as early indicators of protective immunity, vaccine efficacy and early response to treatment. Such developments will facilitate the selection and testing of new interventions. To highlight the crucial role of research in ending the global TB epidemic, the WHO post-2015 global TB strategy that is currently under development includes “Intensified Research and Innovation” as one of three strategic pillars (Chapter 1). The strategy is being developed as a successor to the Stop TB Strategy, which covers the period 2006–2015. In wide consultations held during 2012 and 2013, there has been strong support for this pillar and its two main subcomponents, which are:

1. Discovery, development and rapid uptake of new tools, interventions and strategies; 2. Research to optimize implementation and impact. The research pillar will be essential to the success of the two other pillars of the post-2015 global TB strategy and the achievement of post-2015 global TB targets. Biomedical research will need to be integrated as a critical component of the new post-2015 research strategy. Creating connections among scientific disciplines that have historically been inadequate or lacking (for example, biomedical research, epidemiology and operational research) will depend upon close collaboration, consultation and input from many research and public health stakeholders. The need for more and expanded operational research to optimize implementation and adopt innovations will require extensive work at the country level, for example to generate essential data on the epidemiology of TB (‘Know your epidemic’) and universal health coverage, and to allow adaptation of global recommendations and policies at the national level.

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Annex 1

Methods used to estimate the global burden of disease caused by TB

This annex explains the methods that were used to produce estimates of the global burden of disease caused by TB (measured in terms of incidence, prevalence and mortality). It has nine major sections:  General approach. This section provides some background information about the methods used to produce estimates of disease burden.  Definitions. This section defines TB incidence, prevalence and mortality, the case fatality rate (CFR) and the case notification rate. It also explains the regions for which estimates of disease burden are produced and sources of information on population estimates.  Estimates of TB mortality, 1990–2012 . This section explains the three methods used to estimate TB mortality, and the countries for which they were applied. Methods for estimating the number of HIV-associated TB deaths and for disaggregation of TB mortality by age and sex are also described.  Estimates of TB incidence, 1990–2012. This section explains the main methods used to estimate TB incidence, and the countries for which they were applied. Methods to estimate the prevalence of HIV among incident TB cases are described.  Estimates of TB prevalence, 1990–2012 . This section explains the two methods used to estimate TB prevalence, and the countries for which they were applied.  Estimates of multidrug-resistant TB (MDR-TB) incidence and mortality. This section explains the main methods used to estimate MDR-TB mortality and incidence based on drug resistance surveillance data and parameters obtained from a recent literature review.  Projections of TB incidence, prevalence and mortality. This section explains how projections from 2013 to 2015 were produced.  Uncertainty framework. This section explains the general approach to including uncertainty in all estimates.

burden, simplification of models,3 updates to parameter values based on the results of systematic reviews, much greater use of mortality data from vital registration (VR) systems and systematic documentation of uncertainty (hence the uncertainty intervals shown on all of the estimates of disease burden in this report).

2. 2.1

Definitions Incidence, prevalence, mortality, case fatality rate, case notification rate

Incidence is defined as the number of new and recurrent (relapse) episodes of TB (all forms) occurring in a given year. Recurrent episodes are defined as a new episode of TB in people who have had TB in the past and for whom there was bacteriological confirmation of cure and/or documentation that treatment was completed (Box 3.1, Chapter 3). In the remainder of this Annex, relapse cases are referred to as recurrent cases because the term is more useful when explaining the estimation of TB incidence. Recurrent cases may be true relapses or a new episode of TB caused by reinfection. In current case definitions, both relapse cases and patients who require a change in treatment are called ‘retreatment cases’. However, people with a continuing episode of TB that requires a treatment change are prevalent cases, not incident cases. Prevalence is defined as the number of TB cases (all forms) at a given point in time. Mortality from TB is defined as the number of deaths caused by TB in HIV-negative people, according to the latest revision of the International classification of diseases (ICD-10). TB deaths among HIV-positive people are classified as HIV deaths in ICD-10. For this reason, estimates of deaths from TB in HIV-positive people are presented separately from those in HIV-negative people. The case fatality rate is the risk of death from TB among people with active TB disease.4 The case notification rate refers to new and recurrent episodes of TB notified to WHO for a given year, expressed per 100 000 population. The case notification rate for new and recurrent TB is important in the estimation of TB incidence. In some countries, however, information on treatment history may be missing for some cases. When data on treatment history are not available, recurrent cases cannot be distinguished from cases whose treatment was 1

1.

General approach

Estimates of the burden of disease caused by TB (measured in terms of incidence, prevalence and mortality) are produced annually by WHO using information gathered through surveillance systems (case notifications and death registrations), special studies (including surveys of the prevalence of disease, mortality surveys and in-depth analyses of surveillance data), expert opinion and consultations with countries. Two recent publications provide up-to-date guidance about how TB incidence, prevalence and mortality should be measured,1 based on the work of the WHO Global Task Force on TB Impact Measurement.2 The methods used to estimate the burden of disease were updated in 2009 following 18 months of work by an expert group convened by the Task Force. These updates were endorsed at a meeting of the full Task Force in March 2010. Improvements to methods included systematic documentation of expert opinion and how this has been used to produce estimates of disease

TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper, no. 2; WHO/HTM/TB/2009.416). The policy paper is available on the Task Force web site: www.who.int/tb/advisory_bodies/impact_ measurement_taskforce 2 For further details, see the Task Force web site at: www.who.int/tb/ advisory_bodies/impact_measurement_taskforce 3 For example, some parameter values are now estimated only at global level or for regions, rather than for each country individually. 4 Straetemans M et al. Assessing tuberculosis case fatality ratio: a meta-analysis. PLoS One. 2011, 6(6):e20755.

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changed, since both are registered and reported in the category ‘retreatment’. Patients reported in the ‘unknown history’ category are considered incident TB episodes (new or relapse). This is a change from previous years in view of past difficulties to estimate with NTPs the proportion of true new or relapse TB episodes in this category of patients (previously, patients with unknown treatment history were not considered new or relapse cases). This change affects relatively few countries, mostly in Western Europe.

3.1

Estimating TB mortality among HIV-negative people from vital registration data and mortality surveys

2.2 Regions Regional analyses are generally undertaken for the six WHO regions (that is, the African Region, the Region of the Americas, the Eastern Mediterranean Region, the European Region, the South-East Asia Region and the Western Pacific Region). For analyses related to MDR-TB and for an ecological model used to estimate TB mortality in some countries, nine epidemiological regions were defined. These were African countries with high HIV prevalence, African countries with low HIV prevalence, Central Europe, Eastern Europe, high-income countries,1 Latin America, the Eastern Mediterranean Region (excluding high-income countries), the South-East Asia Region (excluding highincome countries) and the Western Pacific Region (excluding high-income countries). The countries in these nine regions are listed in Appendix 1.

2.3

Population estimates

The source of population estimates needed to calculate various TB indicators was the 2012 revision of the World Population Prospects, which is produced by the United Nations Population Division (UNPD).2 The UNPD estimates sometimes differ from those made by countries.

3.

Estimates of TB mortality, 1990–2012

The best sources of data about deaths from TB (excluding TB deaths among HIV-positive people) are VR systems in which causes of death are coded according to ICD-10 (although the older ICD-9 and ICD-8 classification are still in use in several countries). Deaths from TB in HIV-positive people are coded under HIV-associated codes. Three methods were used to estimate TB mortality among HIV-negative people:  direct measurements of mortality from VR systems or mortality surveys;  indirect estimates based on an ecological model that uses data from VR systems;  indirect estimates derived from multiplying estimates of TB incidence by estimates of the CFR. Each method is described in more detail below. Details on the method used for each country are available online at www.who.int/tb/publications/global_report/gtbr13_ mortality_source.csv.

Data from VR systems are reported to WHO by Member States and territories every year. In countries with functioning VR systems in which causes of death are coded according to the two latest revisions of the International classification of diseases (underlying cause of death: ICD-10 A15-A19, equivalent to ICD-9: 010-018), VR data are the best source of information about deaths from TB among people not infected with HIV. When people with AIDS die from TB, HIV is registered as the underlying cause of death and TB is recorded as a contributory cause. Since one third of countries with VR systems report to WHO only the underlying causes of death and not contributory causes, VR data usually cannot be used to estimate the number of TB deaths in HIV-positive people. TB mortality data obtained from VR systems are essential to understanding trends in TB disease burden where case notifications have incomplete coverage or their coverage is not documented through an inventory study. An updated description of the global coverage and quality of VR data is available in World Health Statistics 2013.3 As of May 2013, 125 countries had reported mortality data to WHO (including data from sample VR systems and mortality surveys), among 217 countries and territories from which TB data were requested. These 125 countries included 9 of the 22 high TB burden countries (HBCs): Brazil, China, India, the Philippines, the Russian Federation, South Africa, Thailand, Viet Nam and Zimbabwe. However, the VR data on TB deaths from South Africa and Zimbabwe were not used for this report because large numbers of HIV deaths were miscoded as TB deaths. Improved empirical adjustment procedures have recently been published,4 and options for specific post-hoc adjustments for misclassification errors in the measurement of TB mortality will be reviewed extensively by the WHO Global Task Force on TB Impact Measurement in 2014. Among the countries for which VR data could be used (see Figure 2.11 in Chapter 2), there were 2087 country-year data points 1990–2012. Of these data points, 24 outliers and points obtained from systems with very low coverage were excluded for analytical purposes. Outliers were detected visually by plotting country-specific time series of reported TB mortality rates. As of June 2013, 62 data points were available for 2010, 35 for 2011 and none for 2012. On average, 16 data points were retained for analysis per country (standard deviation (SD) of 6.7) from a total of 2063 usable data points. 1

High-income countries are defined by the World Bank as countries with a per capita gross national income (GNI) of ≥US$  12 616 in 2012. 2 http://esa.un.org/unpd/wpp/ (accessed June 2013). 3 www.who.int/gho/publications/world_health_statistics/2013/en/ (accessed July 2013) (see particularly pages 15–16). 4 Birnbaum JK, Murray CJL, Lozano R. Exposing misclassified HIV/ AIDS deaths in South Africa. Bulletin of the World Health Organization, 2011, 89:278–285.

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Reports of TB mortality were adjusted upwards to account for incomplete coverage (estimated deaths with no cause documented) and ill-defined causes of death (ICD-9 code B46, ICD-10 codes R00–R99).1 It was assumed that the proportion of TB deaths among deaths not recorded by the VR system was the same as the proportion of TB deaths in VR-recorded deaths. For VRrecorded deaths with ill-defined causes, it was assumed that the proportion of deaths attributable to TB was the same as the observed proportion in recorded deaths. The adjusted number of TB deaths da was obtained from the VR report d as follows: d da = c(1 – g) where c denotes coverage (i.e. the number of deaths with a documented cause divided by the total number of estimated deaths) and g denotes the proportion of ill-defined causes. The uncertainty related to the adjustment was estimated with standard deviation SD = d /4[1/c (1 – g ) – 1]. The uncertainty calculation does not account for miscoding, such as HIV deaths miscoded as deaths due to TB. Missing data between existing adjusted data points were interpolated. Trailing missing values were predicted using exponential smoothing models for time series.2 A penalized likelihood method based on the in-sample fit was used for country-specific model selection. Leading missing values were similarly predicted backwards to 1990. A total of 799 country-year data points were thus imputed. Results from mortality surveys were used to estimate TB mortality in India and Viet Nam. In 2012, 45% of global TB mortality (excluding HIV) was directly measured from VR or survey data (or imputed from survey or VR data from previous years). The remaining 55% was estimated using the indirect methods described in section 3.2 and section 3.3.

cess rate; the total number of newly notified TB cases per year; whether or not a country had a high or low burden of MDR-TB; whether a country was among the 22 HBCs or not; and a categorical variable classifying countries in nine groups with similar TB epidemiology (see Appendix 1). At the univariate level, all risk factors were associated with the outcome of TB mortality. The final multivariate model included the infant mortality rate per 1000 live births, HIV prevalence among the general population, gross domestic product per capita, the percentage of the total population aged <15 and ≥65 years, whether a country was in the list of 22 HBCs or not; and the categorical variable that defined country groups with similar TB epidemiology. Out of a total 4686 country-year observations in the time series for 1990–2011, 802 could not be predicted due to data not being available for any of the ten variables included in the model. Estimates of TB mortality predicted by the model were used for 26 countries3 in which VR or mortality survey data of sufficient quality and coverage were not available and for which estimates of TB incidence were judged too uncertain.

3.3

Estimating TB mortality among HIV-negative people from estimates of case-fatality rates and TB incidence

In 68 countries lacking VR data of the necessary coverage and quality (in total, 94 countries lacked VR data of sufficient coverage and quality but among 26 of them, the ecological model described above was used), TB mortality was estimated as the product of TB incidence (see section 4) and the CFR using a model developed in 2012. CFRs were estimated separately for TB cases notified to NTPs and non-notified cases and, within these two groups, separate estimates were made for HIV-negative TB cases in high-income and other countries ( Table A1.1). Table A1.1

3.2

Estimating TB mortality among HIV-negative people from an ecological model

Estimates of TB case-fatality rates (HIV-negative) by case type and country Case type and country group Mean (Standard deviation)

An out-of-sample, goodness-of-fit, stepwise selection approach was used in 2012 using the series 1990–2011 to select an ecological model that could predict TB mortality in countries without VR data. The model was based on the time series of VR data reported to WHO as described above, expressed as counts of TB deaths and corrected for illdefined causes of deaths and VR coverage. A population-averaged negative binomial model, with total population as the offset converting model outputs to rates, was used to account for the longitudinal structure of the data as well as the observed over-dispersion of counts of TB deaths. Ten variables were investigated for inclusion in the model. These were: the infant mortality rate per 1000 live births; gross domestic product per capita; HIV prevalence among the general population; the percentage of the total population aged <15 and ≥65 years; the TB treatment suc-

Non-notified: high-income countries Non-notified: other countries Notified: high-income countries Notified: other countries

0.12 (0.042) 0.32 (0.13) 0.039 (0.042) 0.074 (0.03)

For consistency with VR- or survey-based mortality estimates, CFRs were estimated such that they gave the best fit to the directly measured TB death rates (within their uncertainty ranges) in the 123 countries with VR or mortality 1

Mathers CD et al. Counting the dead and what they died from: an assessment of the global status of cause of death data. Bulletin of the World Health Organization, 2005, 83:171–177. 2 Hyndman R et al. Forecasting with exponential smoothing: the state space approach. Springer Series in Statistics, 2008. 3 For the list of the 26 countries, see www.who.int/tb/publications/ global_report/gtbr13_ mortality_source.csv.

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survey data that were retained for analysis, in conjunction with WHO estimates of distributions of TB incidence in those countries. This statistical fitting used Bayesian linear models and was done separately for two groups of countries (high-income and all other countries), to account for differences in the ratio of reported TB mortality to TB notification rates among these two groups (data not shown). The models used normal errors and Gibbs sampling: y = ( I – N ) β1 + N β2 + e , e ~ N (0, σ2) where y is TB mortality from VR, I denotes TB incidence excluding people living with HIV, N denotes TB notifications excluding people living with HIV, and parameters β1 and β2 denote the CFR in non-notified and notified cases respectively. Semi-conjugate priors were set with an uninformative inverse Gamma prior on the conditional error variance: b ~ N ( b i , B i -2), σ2 ~ IG (5.10 -4 ,5.10 -4) For low- and middle-income countries, priors b and their precision B were defined based on literature reviews1 and the country-year CFR parameters used by WHO for the years 1999–2008. For high-income countries, non-informative priors were used. Convergence of Markov Chains was assessed graphically and using convergence diagnostic tests. Within each case category 1990–2011, mortality estimates were computed by taking the product of posterior distributions of the CFR, assumed to be time-independent ( Table A1.1), and country-year specific distributions of estimated incidence.

Table A1.2

Estimates of the case fatality ratio among HIV-positive TB cases Non-notified Notified

HIVMode of triangular distribution HIV+ not receiving ART Mode of triangular distribution Receiving ART for less than one year Mode of triangular distribution Receiving ART for more than one year Mode of triangular distribution

0.43 0.78 0.62 0.49

0.03 0.09 0.06 0.04

are urgently needed. This is especially the case for countries such as South Africa and Zimbabwe, where national VR systems are already in place. In other countries, more efforts are needed to initiate the implementation of sample VR systems as an interim measure.

3.5

TB mortality disaggregated by age and sex

3.4

Estimating TB mortality among HIV-positive people

No nationally representative measurements of HIV-associated TB mortality were available from VR systems for use in this report. In the absence of direct measurements, TB mortality among HIV-positive people was estimated indirectly according to the following methods (also see section 4.5) implemented in the Spectrum software.2 TB mortality is calculated as the product of HIV-positive TB incidence (see section 4.5) and case fatality ratios: M = (I-N)Fu + NFn where I represents incident TB cases among people living with HIV, N represents HIV-positive cases that are notified, (I-N) represents HIV-positive TB cases that are not notified and M represents TB mortality among HIV-positive people. Fn and Fu are the case fatality ratios for notified and non-notified incident cases, respectively. The case fatality ratios were obtained in collaboration with the TB Modeling and Analysis Consortium (TB-MAC),3,4,5 and are shown in Table A1.2. The disaggregation of incident TB into notified and not notified cases is based on the ratio of the point estimates for incident and notified cases. A single CFR was used for all bootstrapped mortality estimates. Direct measurements of HIV-associated TB mortality

For countries with VR data, it was possible to estimate TB deaths (excluding TB deaths among HIV-positive people) among children (aged <15 years) and adults (aged ≥ 15 years) separately. It was also possible to disaggregate TB deaths by sex. For these countries, male:female and child:adult ratios of TB deaths (expressed as rates per 100 000 population) were calculated (after correction for ill-defined causes of deaths and VR coverage). The ecological model described in section 3.2 was used to predict ratios for countries with no VR data. Directly measured (i.e. based on VR data for the latest available year) or predicted country-level ratios were then used to estimate ratios for WHO regions. These were then used to estimate the global ratio which was in turn applied to the global number of estimated TB deaths among HIV-negative TB cases to produce age and sex-disaggregated estimates. TB deaths among HIV-positive people were disaggregated by sex using the assumption that the male:female sex ratio is the same as the sex ratio of AIDS deaths estimated by UNAIDS. Further details are provided in Box 2.2, Chapter 2. Disaggregation of TB deaths by age and sex will be one of the future developments of the TB component of the Spectrum software (also see section 3.4).

1

Straetemans M et al. Assessing tuberculosis case fatality ratio: a meta-analysis. PLoS One. 2011, 6(6):e20755. 2 http://www.futuresinstitute.org/spectrum.aspx 3 Tiemersma EW, van der Werf MJ, Borgdorff MW, Williams BG, Nagelkerke NJ (2011) Natural history of tuberculosis: duration and fatality of untreated pulmonary tuberculosis in HIV negative patients: a systematic review. PLoS One 6: e17601. 4 Corbett EL, Watt CJ, Walker N, Maher D, Williams BG, et al. (2003) The growing burden of tuberculosis: global trends and interactions with the HIV epidemic. Archives of Internal Medicine; 163: 1009– 1021. 5 Mukadi YD, Maher D, Harries A (2001) Tuberculosis case fatality rates in high HIV prevalence populations in sub-Saharan Africa. AIDS; 15: 143–152.

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4.

Estimates of TB incidence, 1990–2012

No country has ever undertaken a nationwide survey of TB incidence because of the large sample sizes required and associated major logistic and financial challenges. As a result, there are no direct measurements of the incidence of TB. Theoretically, data from TB surveillance systems that are linked to health systems of high coverage and performance may capture all (or almost all) incident cases of TB. The WHO Global Task Force on TB Impact Measurement has developed a set of TB surveillance standards and benchmarks that, if met, would allow direct measurement of TB cases and deaths from surveillance data (Chapter 2). In the absence of direct measurements, estimates of TB incidence for almost all countries rely on methods described in sections 4.1–4.3. It should be emphasized that incidence estimates are no longer derived from surveys of the prevalence of TB infection as measured in tuberculin surveys. The WHO Global Task Force on TB Impact Measurement has agreed that methods for deriving incidence from the prevalence of infection are unreliable. The Task Force has also stated that, with a few exceptions, repeat tuberculin surveys do not provide a reliable estimate of the trend in TB incidence.1

modelling were used to estimate the gap between notified cases and TB incidence in three countries that participated in regional workshops: Egypt, Iraq and Yemen. A full description of the methods used in these workshops is available in a report of the workshop held for countries in the African Region (in Harare, Zimbabwe, December 2010).4 Table A1.3

Sources of information and data on TB incidence used in regional workshops and country missions Possible categories of incident cases Sources of data

Do not have physical or financial access to health care Seek care, but TB not diagnosed TB diagnosed, but not reported Reported cases a

Demographic and health surveys, KABPa surveys Survey ‘Inventory’ survey TB surveillance

Capture– recapture modelling

KABP = knowledge, attitudes, behaviour and practices.

4.1

Estimating TB incidence from estimates of the proportion of cases detected

Distributions of the proportion of cases that were not reported in the three reference years were assumed to follow a Beta distribution ( Table A1.4). Reasons for using Beta distributions include the following:  They are continuous and defined on the interval (0, 1). Since the variance of the proportions of cases that were not reported tend to be large as a result of high uncertainty, random draws of numbers from a normal distribution would yield numbers outside the interval (0, 1). The use of truncated normal distributions may result in excess density towards one of the bounds.  They are not necessarily symmetrical.  They are defined with two parameters that can be estimated from available data using the method of moments.5 The shape and scale parameters necessary to define the Beta distribution were computed using the method of moments, as follows: First, the variance for the distribution was taken as: V = ((u – l )/4)2 where l and u are the lower and upper bounds of the plausible range for the proportion of incident cases that were 1

Notification data for new and recurrent cases have been analysed in combination with evidence about the coverage of the TB surveillance system and expert opinion in six regional workshops and country missions held during the period 2009–2013, according to methods developed by the WHO Global Task Force on TB Impact Measurement. By May 2013, these workshops and country missions had covered 96 countries (Figure 2.1, Chapter 2), with several countries re-assessed multiple times. For the 96 countries covered by these regional workshops and country missions, incidence was estimated according to the following equation: case notifications incidence = 1 – underreporting Expert opinion about the proportion of TB cases2 that were not reported was elicited for three reference years (1997, 2003 and, depending on when the workshop was held, 2008–2012). This was done following in-depth analysis of notification data (including data from sub-national administrative levels), programmatic data reflecting efforts in TB care and control (for example, data on infrastructure, staffing, the performance of services and funding) and (where available) data from inventory studies. 3 In addition, data on access to health care from Demographic and Health Surveys and the overall performance of health systems (using indicators such as the infant mortality rate) were used to substantiate opinion on the proportion of cases with no or very limited access to health care ( Table A1.3). Results from inventory studies combined with capture–recapture

TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper, no. 2; WHO/HTM/TB/2009.416). 2 Defined as cases of all forms of TB, including sputum smear-positive pulmonary cases, sputum smear-negative pulmonary cases and extrapulmonary cases. 3 Measurements from ‘inventory’ studies can be used to quantify the number of cases that are diagnosed but not reported to national surveillance systems. 4 See  www.who.int/tb/advisory_bodies/impact_measurement_ taskforce 5 Rényi A. Probability theory. New York, Dover Publications Inc., 2007.

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reported (also referred to as the case detection rate in Chapter 3). Shape 1 (noted α) and 2 (noted β) follow from: s = E(l – E ) – l V α = sE β = s(l – E ) where E is the expected value of the distribution. Time series for the period 1990–2012 were built according to the characteristics of the levels of underreporting and under-diagnosis that were estimated for the three reference years. A cubic spline extrapolation of V and E, with knots set at the reference years, was used for countries with low-level or concentrated HIV epidemics. In countries with a generalized HIV epidemic, the trajectory of incidence from 1990 to the first reference year (usually 1997) was based on the annual rate of change in HIV prevalence. Incidence trajectories were derived from the series of notified TB cases using Monte Carlo simulations from which expected values, 2.5th and 97.5th centiles were extracted. All computations were conducted in the R statistical environment.1 In two countries, incidence rates were estimated to be similar to those in a neighbouring country because information from surveillance systems was insufficient: estimates for West Bank and Gaza Strip were extrapolated from estimates for Jordan and estimates for South Sudan were extrapolated from estimates for Sudan. The estimates for West Bank and Gaza Strip and South Sudan should therefore be considered as preliminary. Trends in incidence were derived from repeat tuberculin survey results in Bhutan, India and Yemen and for 40 countries (including countries in Eastern Europe) from trends in mortality. If there were insufficient data to determine the factors leading to time-changes in case notifications, incidence was assumed to follow a horizontal trend going through the most recent estimate of incidence.

el does allow for stochastic fluctuations. The exceptions were the United Kingdom and the Netherlands, where the underreporting of TB cases has been measured using inventory studies and capture–recapture modelling.2,3 For these two countries, the results from these studies were used to measure TB incidence directly.

4.3 Estimating TB incidence from empirical measurements of disease prevalence Incidence can be estimated using measurements from national surveys of the prevalence of TB disease combined with estimates of the duration of disease. Incidence is estimated as the prevalence of TB divided by the average duration of disease. In practice, the duration of disease cannot be directly measured. For example, measurements of the duration of symptoms in prevalent TB cases that are detected during a prevalence survey are systematically biased towards lower values, since active case-finding truncates the natural history of undiagnosed disease. Measurements of the duration of disease in notified cases ignore the duration of disease among non-notified and untreated cases. Literature reviews commissioned by the WHO Global Task Force on TB Impact Measurement have provided estimates of the duration of disease in untreated TB cases from the pre-chemotherapy era (before the 1950s). The best estimate of the mean duration of disease (for smear-positive cases and smear-negative cases combined) in HIV-negative individuals is about three years. However, the proportion of incident cases that remain untreated is unknown. There are few data on the duration of disease in HIV-positive individuals. When measurements from two prevalence surveys were available, trends in TB prevalence were derived by fitting a log-linear model to available measurements. When three or more prevalence measurements were available, the prevalence trajectory was built using cubic spline interpolation. If only one prevalence survey measurement was available, time-trends were assessed using in-depth analysis of surveillance data, as described above. In this report, the prevalence to incidence method was used for two countries: Ethiopia and the Lao People’s Democratic Republic.

4.2 Estimating TB incidence from data on case notifications and expert opinion for high-income countries For high-income countries, the level of TB incidence was assumed to be distributed between the notification rate for new and recurrent cases combined, including reported cases with undocumented treatment history as explained in section 2.1 (lower uncertainty bound, noted l ) and 1.3 times the notification rate (upper uncertainty bound, noted u), as informed by expert opinion. The distribution of incidence was assumed to follow a Beta distribution with shape and scale parameters computed using the method of moments, as described above. In the absence of country-specific data on the quality and coverage of TB surveillance systems, it was assumed that TB surveillance systems from countries in the high-income group performed similarly well, although the mod106 GLOBAL TUBERCULOSIS REPORT 2013

4.4 Disaggregation of TB incidence In this report, TB incidence is disaggregated by HIV-infection status (see section 4.5) at country level. The estimation of smear-positive TB incidence was discontinued in 1

R Development Core Team. R: a language and environment for statistical computing. Vienna, R Foundation for Statistical Computing, 2009 (www.R-project.org). 2 Tuberculosis in the UK: annual report on tuberculosis surveillance in the UK 2010. London, Health Protection Agency Centre for Infections, 2010 (also available at: www.hpa.org.uk/web/HPAweb&HPAwebStandard/ HPAweb_C/1287143581697; accessed July 2011). 3 van Hest NA et al. Completeness of notification of tuberculosis in The Netherlands: how reliable is record-linkage and capture–recapture analysis? Epidemiology and Infection, 2007, 135(6):1021–1029.

TABLE A1.4

Parameter estimates used to produce estimates of TB incidence, prevalence and mortality Model parameter Distribution Distribution parametersb

Ī (1– Ī ) –1 V Ī (1– Ī ) –1 β = (1– Ī ) . V α=Ī. where Ī was set at 1.3 times the notification rate, noted N, and V is defined by: V= HIV prevalence among incident TB Betaa 0.3 4 N 2

Incidence, high-income countries

Betaa

α=– x.

– (1– x –) x V

–1

– – – ) . x (1– x ) – 1 β = (1– x V – is the expected value and V is given by: Where x V= Duration of disease, non-notified HIV-negative cases of TB Duration of disease, non-notified HIV-positive cases of TB Duration of disease, notified HIV-negative cases of TB Duration of disease, notified HIV-positive cases of TB a b

u–l 2 4

Uniform Uniform Uniform Uniform

l = 1, u = 4 (years) l = 0.01, u = 0.2 (years) l = 0.2, u = 2 (years) l = 0.01, u = 1 (years) x a –1 (1– x) β –1 1 a –1 t 0

The probability density function of the Beta distribution is: u and l denote upper and lower bounds.

ƒ ( x; a, β) =

(1– t) β –1 dt

2010, for reasons explained in detail in the global report published in 2010. Global and WHO regional estimates of sex-disaggregated incidence were also calculated, based on country-level female:male ratios of total new (all case types) TB case notifications, under the assumption that they are a proxy of female:male ratios of incidence. Model-based estimated WHO regional ratios were applied to global incidence for the final sex disaggregation (Chapter 2). TB incidence was also disaggregated by age, to produce global estimates among children (aged <15 years) and adults (aged ≥ 15 years). Details of methods are provided in Chapter 2, Box 2.2.

regression method was used to estimate the relative risk (RR) for TB incidence according to the CD4 categories used by Spectrum for national HIV projections. Spectrum data were based on the national projections prepared for the UNAIDS Report on the global AIDS epidemic 2012. The model can also be used to estimate TB mortality among HIV-positive people, the resource requirements associated with recently updated guidance on ART3 and the impact of ART expansion. A flexible and relatively simple way of modelling TB incidence (or any time-dependent function) is to represent it as k time-dependent m’th order cubic-spline functions: I(x) = Σi=1 to k βi Bmi(x) where βi is the i’th spline coefficient and Bmi(x) represents the evaluation of the i-th basis function at time(year) x. The 1

4.5 Estimates of HIV prevalence among incident TB cases, 1990–2012 TB incidence was disaggregated by HIV and CD4 status using the Spectrum software.1 WHO estimates of TB incidence were used as inputs to the Spectrum HIV model. The model was fitted to WHO estimates of TB incidence, and then used to produce estimates of TB incidence among people living with HIV disaggregated by CD4 category.2 A

http://www.futuresinstitute.org/spectrum.aspx Stover J, McKinnon R, Winfrey B. Spectrum: a model platform for linking maternal and child survival interventions with AIDS, family planning and demographic projections. International Journal of Epidemiology 2010; 39 Suppl 1:i7–10. 3 http://www.who.int/hiv/pub/guidelines/arv2013/en/index.html 2

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order of each basis function is m and cubic splines are used, i.e. m=3. The equation simply states that any time-dependent function, such as incidence, can be represented as a linear combination of cubic-spline basis functions. The values of the cubic-spline coefficients β were determined by an optimization routine that minimizes the least squares error between incidence data (Iobs) and the estimated incidence curve I(x): Σx=1990:2012 |I(x) - Iobs(x)|2 + λ β T S β Here |I - Iobs|2 is the sum of squared errors in estimated incidence and S is a difference penalty matrix applied directly to the parameters β to control the level of variation between adjacent coefficients of the cubic-spline, and thus control (through a choice of λ) the smoothness of the time-dependent case incidence curve. Another important purpose of the use of the smoothness penalty matrix S is to regularize (by creating smoothness dependencies between adjacent parameters) the ill-conditioned inverse problem (more unknown parameters than the data can resolve) that would tend to over fit the data when left ill-conditioned.

50–99 CD4 cells/μL, and CD4 count less than 50 cells μL), the risk of infection is represented as: F(c<500) = F(c>500)∙p(1)∙p(2)dc, where p(1) is a parameter that is used to recognize that people living with HIV who have high CD4 counts could be at higher risk of TB infection relative to those who are HIV-negative, and p(2) controls the exponential increase in RR that occurs with CD4 decline. dc is the number of 100μL CD4 decline associated with the midpoint of each CD4 category relative to 500: dc= (3.0, 4.4, 8.6, 12.9, 19.2, 28.6, 37.3) for the six CD4 categories. A reduction in RR is applied for those who have been on ART for more than one year.

Parameter assumptions To match total TB incidence and estimates of the number of HIV-positive TB cases from HIV testing data where available, it was assumed that p(1)=2.5 and p(2) was fitted accordingly. In the RR-approach, the ‘biological meaning’ that should be attached to the parameters and a more straightforward interpretation of these parameters as regression coefficients need to be balanced. Both parameters can be fitted or both can be fixed. Varying at least p(2) captures the variation among countries that is expected due to variation in the baseline (HIV-negative) CD4 count, and it strikes a balance between the biological and regression mechanisms. The RR model approach to estimation of TB incidence was used for people on ART. Although an estimate of TB incidence among people on ART could be obtained from surveillance data reported to WHO (such that it is arguably not necessary to use the RR model), limitations of the ART data (in particular that some countries appear to report cumulative totals of people on ART) meant that the RR approach needed to be used. Hazard ratios (HR) of 0.35 were assumed for all CD4 at ART initiation categories. Suthar et al have reported HRs of 0.16, 0.35 and 0.43 for those on ART with CD4 count < 200, 200–350 and > 350,3 and these values could in principle be used. However, Spectrum tracks only CD4 at initiation, thus limiting the use of CD4-specific HRs for people on ART. It was further assumed that the HR of 0.35 applies only to patients on ART for more than six months. Spectrum’s ART-mortality estimates, derived mostly from ART cohorts in Sub-Saharan Africa, suggest that mortality remains very 1

Cubic-Splines and confidence intervals The cubic-spline method was then used to fit indicators (incidence, case notifications, etc.) to a set of bootstrapped data, obtained by sampling from the normal error distribution resulting from fitting the ‘point estimate’. This bootstrap method produces a sample of projected cubic-spline curves that are practically equivalent to a set that would be obtained from fitting the model to the same number of repeated measurements (or assessments) of the given indicator. Confidence intervals based on the bootstrapped data are typically narrow in the years where the model has data to utilize, and ‘spread out’ after that, according to a Gaussian process with an increasing variance.

Projecting TB incidence among people living with HIV by CD4 category The disaggregation of TB incidence by CD4 category among people living with HIV was based on the idea that an increase in the relative risk for TB incidence is a function of CD4 decline. Williams et al captured this idea in a model for the relationship between the RR for TB and CD4 decline.1 They suggested a 42% (+/- 17%) increase in RR for TB for each unit of 100µL CD4 decline. The Spectrum-TB model’s disaggregation method is based on the Williams et al. model. The model first estimates incidence among people living with HIV, and then calculates the ‘risk of TB’ F=I- / P-, where I- is TB incidence among people living with HIV and P- is the number of people living with HIV who are susceptible to TB. An assumption is made that the risk of TB infection among people living with HIV with CD4 count > 500 μL is proportional to F (it was assumed that it was higher by a factor of 2.52). For each 100 µL CD4 decline in the remaining categories (350–499, 250–349, 200–249, 100–199,

Williams B. The impact of ART for HIV on TB. http://www.who.int/ hiv/topics/artforprevention/williams.pdf (accessed July 2013). 2 Sonnenberg P, et al. How Soon after Infection with HIV Does the Risk of Tuberculosis Start to Increase? A Retrospective Cohort Study in South African Gold Miners. Journal of Infectious Diseases. 2005 Jan 15;191(2):150–8. 3 Suthar AB, Lawn SD, del Amo J, Getahun H, Dye C, et al. (2012) Antiretroviral Therapy for Prevention of Tuberculosis in Adults with HIV: A Systematic Review and Meta-Analysis. PLoS Med 9(7): e1001270. doi:10.1371/journal.pmed.1001270

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high in the first six months of ART. Since TB is a leading contributor to mortality among HIV-positive people, it was judged that the HR for patients on ART for 0‒6 months is likely to remain high; therefore, a reduction factor due to ART was not applied for this subset of patients.

Table A1.5

Sources of data on HIV prevalence among incident TB cases Direct measurement of the prevalence of HIV in TB patients Number of country-years

National surveysa HIV sentinel surveillance Provider-initiated testing and counselling with at least 50% coverage of testing Total, at least one data source available a

124 24 1297 1322

Likelihood function A simple least squares approach was used to fit the model to total TB incidence, and to all available estimates of TB incidence among people living with HIV. These estimates of TB incidence among people living with HIV were obtained by three sampling methods: population surveys of the prevalence of HIV among TB cases (least biased, but scarce due to logistical constraints), sentinel HIV data (biases include more testing of people with advanced HIV-related disease) and routine HIV testing of reported TB patients (variable coverage). To increase the influence of survey data, replicas of the survey data were included in the likelihood function. In other words, for years for which data from HIV testing were available, identical copies of the HIV-test data were added to the likelihood function. The estimate of total TB incidence was based on much more data, evenly spread out in the estimation period 1990–2015. Model testing showed that using two replicates of the HIV survey data (i.e. duplicating the survey data) and two replicates of the routine testing data with coverage greater than 90% was the best approach to disaggregating TB incidence: the fit passed close to the survey or highcoverage routine testing data points that were available. For each of a) HIV sentinel and b) routine testing with coverage between 50–90%, data were not used. A prototype Bayesian importance sampling (IMIS) algorithm was developed to handle complex data weighing possibilities, but it was based on subjective priors and likelihood functions and is more time-consuming to run than simple least squares. For the purposes of producing estimates for all countries automatically, the least squares method was used. In future, least squares and IMIS fitting could be made available to the end user. For countries with no data, a range for p(2) was estimated from countries with survey or testing data, which suggest that p(2) = 1.96 [1.8–2.1]. The RR-model was then fitted to total TB incidence only. There is no satisfactory way to verify results for TB incidence among people living with HIV when no HIV-testing data are available. However, comparison of the global estimate for TB incidence among people living with HIV produced by Spectrum and estimates previously published by WHO (based on a different method using HIV prevalence instead of CD4 distributions and using HIV-test data in a different way) suggests that the RR-model works reasonably well. Provider-initiated testing and counselling with at least 50% HIV testing coverage is the most widely available source of information on the prevalence of HIV in TB patients. However, this source of data is affected by biases, particularly when coverage is closer to 50% than to 100%. In all countries with repeat data from testing, the relation-

the reported survey number is over-stated as a number of country reports confused survey and routine testing with near 100% coverage

ship between the prevalence of HIV in TB patients and the coverage of HIV testing was examined graphically. In some countries, the prevalence of HIV in TB patients was found to decrease with increasing HIV testing coverage while in others it increased with increasing HIV testing coverage; in most countries, the prevalence of HIV followed highly inconsistent patterns (with repeat changes in direction) as HIV testing coverage increased. Therefore, it was not possible to adjust for the effect of incomplete coverage of HIV testing on estimates of the prevalence of HIV among TB patients. The assumption was thus made that TB patients with an HIV test result were statistically representative of all TB cases. As coverage of HIV testing continues to increase globally, biases will decrease. For the 1003 country-year data points corresponding to countries for which no surveillance data were available, the prevalence of HIV was estimated indirectly according to the following equation: t= hρ l + h(ρ – l)

In this equation, t is HIV prevalence among incident TB cases, h is HIV prevalence among the general population (from the latest time-series provided by UNAIDS) and ρ is the incidence rate ratio (IRR) (defined as the incidence rate of TB in HIV-positive people divided by the incidence rate of TB in HIV-negative people). We then let logit(t) be log(t/ (1-t)) and logit(h) be log(h/(1-h)). Using data from countries where HIV prevalence has been estimated by UNAIDS as an independent variable, a linear model of logit-transformed t was fitted using logit-transformed h according to the following equation, written in matrix notation: ˆ = Xβ T ˆ is a vector of predicted logit(t), X is an n x 2 matrix where T in which the first column holds 1s, and the second column holds logit(h). The vector β holds estimated model parameters. Models were tested with lags set for logit(h) ranging from no lag to a lag of eight years. The best fit was obtained with a lag of one year. Models were run using Monte Carlo simulations in which h was drawn randomly from a Beta distribution with shape parameters computed as described in Section 4.1, (low and high uncertainty bounds are provided by UNAIDS – also see Table A1.5). The model was run 50  000 times

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using country-specific distributions for H and T (noted in capital letters to denote vectors or matrices) based on their uncertainty intervals. The uncertainty bounds for β were chosen as the 2.5th and 97.5th centiles.

5.

Estimates of TB prevalence, 1990–2012

considered to be similar in terms of TB epidemiology (for country groups see Appendix 1). The observed and imputed estimates of the proportion of new and retreatment cases of TB that have MDR-TB were then pooled to give a global estimate, with countries weighted according to their share of global notifications of new and retreatment cases.

The best way to measure the prevalence of TB is through national population-based surveys of TB disease.1,2 Data from such surveys are available for an increasing number of countries (Chapter 2). It should be noted, however, that measurements of prevalence are typically confined to the adult population. Furthermore, prevalence surveys exclude extrapulmonary cases and do not allow the diagnosis of cases of culture-negative pulmonary TB. When there is no direct measurement from a national survey of the prevalence of TB disease, prevalence is the most uncertain of the three TB indicators used to measure disease burden. This is because prevalence is the product of two uncertain quantities: (i) incidence and (ii) disease duration. The duration of disease is very difficult to quantify because it cannot be measured during surveys of the prevalence of TB disease (surveys truncate the natural history of disease). Duration can be assessed in self-presenting patients, but there is no practical way to measure the duration of disease in patients who are not notified to NTPs. Indirect estimates of prevalence were calculated according to the following equation: P = ∑ I i,j d i,j , i ∈ {1,2}, j ∈ {1,2} where the index variable i denotes HIV+ and HIV–, the index variable j denotes notified and non-notified cases, d denotes the duration of disease in notified cases and I is total incidence. In the absence of measurements, we did not allow duration in notified cases to vary among countries. Given their underlying uncertainty, prevalence estimates should be used with great caution in the absence of direct measurements from a prevalence survey. Unless measurements were available from national programmes (for example, Turkey), assumptions of the duration of disease were used as shown in the last four rows of Table A1.3.

6.2

MDR-TB mortality, 2012

The VR mortality data reported to WHO by Member States does not differentiate between MDR-TB and non-MDR-TB as a cause of death (there is no specific ICD-9 or ICD-10 codes for MDR-TB, although countries such as South Africa have allocated two specific codes U51 and U52 to classify deaths from MDR-TB and XDR-TB respectively). 3 Therefore, a systematic review and meta-analysis of the published literature was undertaken to estimate the relative risk of dying from MDR-TB compared with non MDR-TB. The global estimate of MDR-TB deaths (Box 2.3) was then based on the following formula: m = M.p.r Where: m = global MDR-TB mortality, M = global TB mortality, p = overall proportion of MDR-TB among prevalent TB cases, approximated by the weighted average of the proportion of new and retreated cases that have MDRTB, r = the relative risk of dying from MDR-TB versus nonMDR-TB.

6.3 Numbers of incident cases of MDR-TB, 2012 The global estimate of MDR-TB incidence was calculated as the addition of three groups of MDR-TB incident cases: 1. incident MDR-TB among new pulmonary and extra-pulmonary incident TB cases, using the proportion of MDR-TB among new cases from drug resistance surveillance (DRS); 2. incident MDR-TB among relapses, using the proportion of MDR-TB among new cases from DRS and the estimated relative risk of MDR among relapse versus new cases; and 3. incident MDR-TB among retreated cases that are not relapses, which was assumed to follow a uniform distribution with min=0, max=upper limit of the global proportion of MDR-TB among retreated cases estimated from DRS. A second method to estimate global MDR-TB incidence was also explored, in which the global estimate of mortality due 1

6. 6.1

Estimates of the number of cases of and deaths from MDR-TB Proportion of notified cases of TB that have MDR-TB, 2012

Global and regional estimates of the proportion of new and retreatment cases of TB that had MDR-TB in 2012 were calculated using country-level information. If countries had reported data on the proportion of new and retreatment cases of TB that have MDR-TB from routine surveillance or a survey of drug resistance the latest available information was used. For countries that have not reported such data, estimates of the proportion of new and retreatment cases of TB that have MDR-TB were produced using modelling (including multiple imputation) that was based on data from countries for which data do exist. Estimates for countries without data were based on countries that were 110 GLOBAL TUBERCULOSIS REPORT 2013

Glaziou P et al. Tuberculosis prevalence surveys: rationale and cost. International Journal of Tuberculosis and Lung Disease, 2008, 12(9):1003–1008. 2 TB prevalence surveys: a handbook. Geneva, World Health Organization, 2011 (WHO/HTM/TB/2010.17). 3 Mortality and causes of death in South Africa, 2010: Findings from death notification .  http://w w w.statssa.gov.za /publications/ p03093/p030932010.pdf

to MDR-TB was divided by the estimated case fatality ratio (CFR) among cases of MDR-TB. The CFR was calculated as a weighted average of the case fatality ratio among patients that are treated and those that are not, according to the following formula: ƒ = pt * ƒt + (1-pt)*ƒun Where: pt = proportion treated, approximated by the proportion of enrolled MDR-TB patients on treatment out of those estimated to exist among notified TB patients with pulmonary TB; ƒt = case fatality rate among patients treated for MDR-TB, using treatment outcome data for MDR-TB patient cohorts; ƒun = case fatality rate among people with MDR-TB who are not treated, which was assumed to follow a uniform distribution with min=0.4, max=0.6. Outputs from both methods gave similar best estimates of MDR-TB incidence with largely overlapping confidence intervals.

6.4

Resistance to second-line drugs among patients with MDR-TB

Data from 75 countries were used to produce global estimates of the following proportions: (i) patients with MDRTB who had XDR-TB; (ii) patients with MDR-TB who had fluoroquinolone resistance; (iii) patients with MDR-TB who had resistance to second-line injectable drugs and fluoroquinolones but not XDR-TB. The latest available national and subnational data from each country were analysed using logistic regression models with robust standard errors to account for the clustering effect at the level of the country or territory. The analysis was limited to countries in which more than 66% of MDR-TB cases received second-line DST.

7.

Projections of incidence, prevalence and mortality up to 2015

Projections of  TB incidence, prevalence and mortality rates up to 2015 enable assessment of whether global targets set for 2015 are likely to be achieved at global, regional and country levels. Projections for the years 2013–2015 were  made using exponential smoothing  models fitted to data from 2006–2012.

8.

Estimation of uncertainty

There are many potential sources of uncertainty associated with estimates of TB incidence, prevalence and mortality, as well as estimates of the burden of HIV-associated TB and MDR-TB. These include uncertainties in input data, in parameter values, in extrapolations used to impute missing data, and in the models used. We used fixed population values from the UNPD. We did not account for any uncertainty in these values. Notification data are of uneven quality. Cases may be

underreported (for example, missing quarterly reports from remote administrative areas are not uncommon), misclassified (in particular, misclassification of recurrent cases in the category of new cases is common), or overreported as a result of duplicated entries in TB information systems. The latter two issues can only be addressed efficiently in countries with case-based nationwide TB databases that include patient identifiers. Sudden changes in notifications over time are often the result of errors or inconsistencies in reporting, but may sometimes reflect abrupt changes in TB epidemiology (for example, resulting from a rapid influx of migrants from countries with a high burden of TB, or from rapid improvement in case-finding efforts). Missing national aggregates of new and recurrent cases were imputed by interpolation. Notification trajectories were smoothed using a penalized cubic splines function with parameters based on the data. Attempts to obtain corrections for historical data are made every year, but only rarely do countries provide appropriate data corrections. Mortality estimates incorporated the following sources of uncertainty: sampling uncertainty in the underlying measurements of TB mortality rates from data sources, uncertainty in estimates of incidence rates and rates of HIV prevalence among both incident and notified TB cases, and parameter uncertainty in the Bayesian model. Time series of TB mortality were generated for each country through Monte Carlo simulations. Unless otherwise specified, uncertainty bounds and ranges were defined as the 2.5th and 97.5th centiles of outcome distributions. Throughout this report, ranges with upper and lower bounds defined by these centiles are provided for all estimates established with the use of simulations. When uncertainty was established with the use of observed or other empirical data, 95% confidence intervals are reported. The model used the following sequence: (1) Overall TB incidence estimation after review and cleaning of case notification data; (2) cleaning and adjustment of raw mortality data from VR systems and mortality surveys, followed by imputation of missing values in countries with VR or survey data – in some countries, step 1 was updated to account for mortality data; (3) cleaning of measurements of HIV prevalence among TB patients followed by estimating HIV-positive TB incidence using the Spectrum programme and HIV-positive TB mortality; (4) estimation of HIV prevalence among incident cases of TB through modelling in countries with no measurements; (5) estimation of HIV-negative TB mortality in countries with no VR data followed with an update of step 1 in some countries; (6) review of prevalence measurements, adjustments for childhood TB and bacteriologically unconfirmed TB, and estimation of prevalence followed with an update of step 1 in some countries; (7) estimation of incidence and mortality disaggregated by age and sex and disaggregated by drug resistance status. The general approach to uncertainty analyses was to draw values from specified distributions for every param-

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eter (except for notifications and population values) in Monte Carlo simulations, with the number of simulation runs set so that they were sufficient to ensure stability in the outcome distributions. For each country, the same random generator seed was used for every year, and errors were assumed to be time-dependent within countries (thus generating autocorrelation in time series). Regional parameters were used in some instances (for example, for CFRs). Summaries of quantities of interest were obtained by extracting the mean, 2.5th and 97.5th centiles of posterior distributions. Wherever possible, uncertainty was propagated analytically by approximating the moments of functions of random variables using Taylor expansions – such as when taking the product or the ratio of two random variables – rather than through Monte Carlo simulations, in order to shorten computing time.

High-income countries: Andorra, Aruba, Australia, Austria, the Bahamas, Bahrain, Barbados, Belgium, Bermuda, Brunei Darussalam, Canada, the Cayman Islands, China, Hong Kong SAR, China Macao SAR, Croatia, Cyprus, the Czech Republic, Denmark, Equatorial Guinea, Estonia, Finland, France, French Polynesia, Germany, Greece, Greenland, Guam, Hungary, Iceland, Ireland, Israel, Italy, Japan, Kuwait, Luxembourg, Malta, Monaco, the Netherlands, the Netherlands Antilles, New Caledonia, New Zealand, Northern Mariana Islands, Norway, Oman, Poland, Portugal, Puerto Rico, Qatar, the Republic of Korea, Saint Kitts and Nevis, San Marino, Saudi Arabia, Singapore, Slovakia, Slovenia, Spain, Sweden, Switzerland, Trinidad and Tobago, the Turks and Caicos Islands, US Virgin Islands, United Arab Emirates, the United Kingdom, the United States. Eastern Mediterranean: Afghanistan, Egypt, Iran (Islamic Republic of), Iraq, Jordan, Lebanon, Libya, Morocco, Pakistan, Syrian Arab Republic, Tunisia, West Bank and the Gaza Strip, Yemen. Latin America: Anguilla, Antigua and Barbuda, Argentina, Belize, Bolivia (Plurinational State of), Bonaire, Saint Eustatius and Saba, Brazil, British Virgin Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, the Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Sint Maarten (Dutch part), Suriname, Uruguay, Venezuela (Bolivarian Republic of). South East Asia: Bangladesh, Bhutan, Democratic People’s Republic of Korea, India, Indonesia, Maldives, Myanmar, Nepal, Sri Lanka, Thailand, Timor-Leste. West Pacific: American Samoa, Cambodia, China, Cook Islands, Fiji, Kiribati, Lao People’s Democratic Republic, Malaysia, Marshall Islands, Micronesia (Federated State of), Mongolia, Nauru, Niue, Palau, Papua New Guinea, the Philippines, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, Vanuatu, Viet Nam, Wallis and Futuna Islands.

Appendix 1. Epidemiological regions used for analyses Africa – countries with high HIV prevalence: Botswana, Burundi, Cameroon, the Central African Republic, the Congo, Côte d’Ivoire, the Democratic Republic of the Congo, Ethiopia, Gabon, Kenya, Lesotho, Malawi, Mozambique, Namibia, Nigeria, Rwanda, South Africa, South Sudan, Swaziland, Uganda, the United Republic of Tanzania, Zambia, Zimbabwe. Africa – countries with low HIV prevalence: Algeria, Angola, Benin, Burkina Faso, Cape Verde, Chad, the Comoros, Djibouti, Eritrea, the Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Madagascar, Mali, Mauritania, Mauritius, the Niger, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, Sudan, Togo. Central Europe: Albania, Bosnia and Herzegovina, Montenegro, Serbia, the former Yugoslav Republic of Macedonia, Turkey. Eastern Europe: Armenia, Azerbaijan, Belarus, Bulgaria, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, the Republic of Moldova, Romania, the Russian Federation, Tajikistan, Turkmenistan, Ukraine, Uzbekistan.

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Annex 2

Country profiles

 High TB burden Estimates of TB burdena 2012 Number (thousands)

Afghanistan Population 2012 30 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 120 100 80 60 40 20 0 1990 1995 2000 2005 2010

Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

11 (4.6–20) 0.087 (<0.01–0.33) 110 (54–180) 56 (47–67) 0.31 (0.19–0.46) 52 (44–63)

37 (15–68) 0.29 (0.01–1.1) 358 (181–595) 189 (156–226) 1 (0.63–1.5)

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

1 049 (84) 160 (13) 37 (3) 1 246 29 578

1000 750 500 250 0 1990

13 319 (47) Relapse 4 740 (17) Treatment after failure 2 665 702 28 332 29 381 (9) Treatment after default (2) Total retreatment Total cases notified 6 906 (24) Other

1995

2000

2005

2010

300

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

200

M:F ratio Age < 15

0.5 588

0.7 2 455 2012

100

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

2.0 0.3 0 Yes, outside country

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

91 84 77 No Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

7 275 5 5 5 80 25

(25) (<1) (100) (100)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

6 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 3.5 (0.1–12) 750 (21–2 600) New

Retreatment

4

32 (7.5–56) 400 (93–700) Retreatment Total

2

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

38 (3%) 31

38 31 38 16 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

13 3% 65% 32%

12 8 4 0

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

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Bangladesh Population 2012 155 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 150

High TB burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

100

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

70 (29–130) 0.092 (0.082–0.1) 670 (340–1 100) 350 (290–410) 0.24 (0.2–0.29) 49 (41–59)

45 (19–84) 0.06 (0.05–0.07) 434 (218–721) 225 (185–268) 0.16 (0.13–0.19)

50

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

3 065 (38) 807 (10) 257 (3) 3 872 (48) 8 001 173 619

1000 750 500 250 0 1990

106 790 (66) Relapse 24 451 (15) Treatment after failure 0 0 161 790 3 828 164 855 (0) Treatment after default (0) Total retreatment Total cases notified 30 549 (19) Other

1995

2000

2005

2010

400 ncidence (rate per 100 000 population per year) 300 200 100 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

1.9 966

1.9 1 109

0.9 2 767 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.7 <0.1 <0.1 Yes, outside country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

92 89 82 Yes Number (%)

80

Is rifampicin used throughout treatment for new patients?

60

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

2 086 63 63 63 429 0 Retreatment

(1) (3) (100) (100)

40 1995

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

80 Number of patients 60 40 20 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.4 (0.7–2.5) 1 900 (920–3 300) New

29 (24–34) 2 300 (1 900–2 700) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

41 (<1%) 10

557 (7%) 503

622 513 513 50 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB controlb National TB programme budget (US$ millions)

43

40 30 20 10 0 2009 2010 2011 2012 Unfunded

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. Estimates of TB disease burden have not been approved by the national TB programme in Bangladesh and a joint reassessment will be undertaken following the completion of the prevalence survey planned for 2014. b Comprehensive data on domestic and international funding in 2013 could not be reported. Funding from USAID for October 2012–September 2013 was US$10 million.

Funded domestically

Funded internationally

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GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

 High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands)

Brazil Population 2012 199 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 10 8 6 4 2 0 1990

Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

4.9 (4.6–5.2) 2.5 (2.2–3) 120 (51–210) 92 (76–110) 16 (13–19) 82 (69–99)

2.5 (2.3–2.6) 1.3 (1.1–1.5) 59 (25–107) 46 (38–55) 8 (6.6–9.5)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

40 152 (56) Relapse 12 178 (17) Treatment after failure 8 592 (12) Treatment after default 10 297 (14) Other 11 (<1) 71 230 25 75 097 Total retreatment Total cases notified

3 867 (34) 296 (3) 3 204 (28) 4 133 (36) 11 500 82 755

Prevalence (rate per 100 000 population)

TB case notifications 2012

300

200

100

0 1990

1995

2000

2005

2010

150

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

100

M:F ratio Age < 15

2.3 580

1.8 1 266

1.5 542 2012

50

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

2.0 5.5 0.9 Yes, in country

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

76 70 49 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

45 733 9 049 0 9 049

(55) (20) (0) (100)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

10 000 Number of patients 8000 6000 4000 2000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.4 (1–1.8) 850 (620–1 100) New

Retreatment

7.5 (5.7–9.9) 860 (660–1 100) Retreatment Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

700 (2%) 562

198 (2%) 122

900 684 713 100 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

87 84% 2% 14%

80 60 40 20 0 2009 2010 2011 2012 2013 Unfunded

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

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117

 High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands)

Cambodia Population 2012 15 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 400 300 200 100 0 1990

Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

9.3 (4.3–16) 0.56 (0.41–0.7) 110 (96–130) 61 (52–70) 2.7 (2.3–3.1) 66 (57–77)

63 (29–110) 3.8 (2.7–4.7) 764 (645–892) 411 (353–474) 18 (15–21)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

446 (86) 51 (10) 22 (4) 519 40 258

2500 2000 1500 1000 500 0 1990

14 838 (38) Relapse 8 509 (22) Treatment after failure 0 0 38 637 1 102 39 083 (0) Treatment after default (0) Total retreatment Total cases notified 15 290 (40) Other

1995

2000

2005

2010

1000

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

750 500 250 0 1990

M:F ratio Age < 15

1.2 53

2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

1.4 1.0 0.3 No

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

93 94 74 Yes Number (%)

90

Is rifampicin used throughout treatment for new patients?

80

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

32 359 1 433 1 410 1 268 1 145

(80) (4) (98) (88)

70 1995

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

6000 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.4 (0.71–2.5) 330 (160–590) New

Retreatment

4000

11 (4–22) 56 (21–110) Retreatment Total

2000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

16 (<1%) 10

86 (17%) 65

102 75 110 45 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

24 5% 34% 62%

30

15

0 Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

118

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



China Population 2012 1 377 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 25 20 15 10 5 0 1990

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

44 (43–46) 1.2 (0.93–1.5) 1 400 (1 200–1 600) 1 000 (880–1 100) 7.3 (6.4–8.2) 89 (79–100)

3.2 (3.1–3.3) 0.08 (0.07–0.11) 99 (86–113) 73 (64–82) 0.53 (0.47–0.6)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

316 332 (37) Relapse 533 977 (62) Treatment after failure 2 073 (<1) Treatment after default 6 479 (<1) Other 0 858 861 0 890 645 (0) Total retreatment Total cases notified

31 784 (76) 2 281 (5) 738 (2) 7 014 (17) 41 817 900 678

Prevalence (rate per 100 000 population)

TB case notifications 2012

300

200

100

0 1990

1995

2000

2005

2010

200 ncidence (rate per 100 000 population per year) 150 100 50 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

2.5 1 091

2.1 4 288

0.8 246 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.2 3.7 0.7 Yes, in country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

95 95 90 Yes Number (%)

95 90 85 80 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT statusb

309 385 5 866 3 454 294 795

(34) (2) (59)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

6000 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 5.7 (4.5–7) 49 000 (38 000–60 000) New

Retreatment

4000

26 (22–30) 11 000 (9 000–12 000) Total

2000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

11 472 (4%) 826

4 861 (12%) 1 678

16 333 3 007 1 906 400 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

359 74% 11% 15%

300 200 100 0

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

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Democratic republic of the congo Population 2012 66 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 150

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

100

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

36 (16–64) 6.3 (5.5–8.1) 380 (200–620) 210 (190–250) 16 (14–19) 51 (44–59)

54 (24–97) 9.7 (8.3–12) 576 (301–938) 327 (282–375) 25 (22–29)

50

0 1990

1995

2000

2005

2010

TB case notifications 2012 New cases

(%)

3 977 (53) 597 (8) 597 (8) 2 321 (31) 7 492 112 499 Prevalence (rate per 100 000 population)

1500

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

71 124 (68) Relapse 13 214 (13) Treatment after failure 105 007 108 984 Treatment after default Total retreatment Total cases notified 20 669 (20) Other

1000

500

0 1990

1995

2000

2005

2010

400

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

300 200 100 0 1990

M:F ratio Age < 15

1.3 3 138

2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

2.3 0.3 0.2 Yes, in and outside country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

87 89 74 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

35 097 5 748 3 485 2 296 Retreatment

(31) (16) (61) (40)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

8000 Number of patients 6000 4000 2000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.5 (0.01–5) 2 100 (8.4–4 200) New

10 (3.5–17) 760 (260–1 300) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

12 (<1%) 5

95 (1%) 59

109 65 179 2013 Total budget (US$ millions) 60 40 20 0

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

61 1% 25% 74%

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

120

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



Ethiopia Population 2012 92 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 80 60 40 20 0 1990

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

16 (12–21) 5.6 (4.6–7.3) 210 (170–250) 230 (170–290) 23 (17–30) 64 (49–87)

18 (13–23) 6.1 (5–8) 224 (180–272) 247 (183–321) 25 (19–33)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

1 820 (45) 281 (7) 482 (12) 1 506 (37) 4 089 147 592

800 600 400 200 0 1990

47 236 (33) Relapse 47 340 (33) Treatment after failure 2 073 0 143 503 0 145 323 (1) Treatment after default (0) Total retreatment Total cases notified 46 854 (33) Other

1995

2000

2005

2010

750

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

500

M:F ratio Age < 15

1.2 7 682

1.1 7 852 2012

250

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

2.8 0.3 <0.1 No

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

90 87 78 Yes Number (%)

80

Is rifampicin used throughout treatment for new patients?

60

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

96 245 9 819 3 619 8 022 272 178 30 395

(65) (10) (37) (82)

40 1995

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

12 000 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.6 (0.86–2.8) 1 600 (830–2 700) New

Retreatment

8000

12 (5.6–21) 480 (230–870) Total

4000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

469 (<1%) 30

180 (4%) 102

856 284 289 180 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

145 17% 32% 51%

120

60

0 Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

121



India Population 2012 1 237 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 60

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

40

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

270 (170–390) 42 (37–48) 2 800 (1 900–3 900) 2 200 (2 000–2 400) 130 (120–140) 59 (54–66)

22 (14–32) 3.4 (3–3.9) 230 (155–319) 176 (159–193) 10 (9.4–12)

20

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

629 589 (53) Relapse 317 616 (27) Treatment after failure 2 139 (<1) 1 183 373 1 289 836 Treatment after default Total retreatment Total cases notified 234 029 (20) Other

106 463 (37) 16 400 (6) 64 782 (23) 96 567 (34) 284 212 1 467 585

Prevalence (rate per 100 000 population)

TB case notifications 2012

600

400

200

0 1990

1995

2000

2005

2010

300

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

200

M:F ratio Age < 15

2.2 12 957 34 467

33 501 2012

100

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

1.1 0.3 0.2 Yes, in country

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

88 90 75 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

821 807 44 063 40 537 25 790 1 324 386

(56) (5) (92) (59)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

50 000 Number of patients 40 000 30 000 20 000 10 000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.2 (1.9–2.6) 21 000 (18 000–25 000) New

Retreatment

15 (11–19) 43 000 (32 000–54 000) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

55 611 16 588 14 143 250 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

182 37% 57% 6%

200 150 100 50 0 2009 2010 2011 2012 2013 Unfunded

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. Estimates for India have not yet been officially approved by the Ministry of Health & Family Welfare, Government of India and should therefore be considered provisional.

Funded domestically

Funded internationally

122

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



indonesia Population 2012 247 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 150

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

100

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

67 (30–120) 2.1 (1.8–3) 730 (350–1 200) 460 (380–540) 7.5 (5.6–9.7) 72 (61–87)

27 (12–48) 0.86 (0.74–1.2) 297 (144–506) 185 (153–220) 3.1 (2.3–3.9)

50

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

5 942 (70) 467 (5) 954 (11) 1 179 (14) 8 542 331 424

1000 750 500 250 0 1990

202 319 (63) Relapse 104 866 (32) Treatment after failure 15 697 322 882 328 824 Treatment after default (5) Other Total retreatment Total cases notified

1995

2000

2005

2010

300

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

200

M:F ratio Age < 15

1.5 1 703

1.3 22 956

0.9 2 684 2012

100

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

2.3 0.9 0.1 Yes, in country

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

90 85 71 Yes Number (%)

80

Is rifampicin used throughout treatment for new patients?

60

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

2 676 754 133 221 22 677

(<1) (28) (18) (29)

40 1995

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

3000 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.9 (1.4–2.5) 5 800 (4 300–7 700) New

Retreatment

2000

12 (8.1–17) 1 000 (690–1 500) Total

1000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

2 (<1%) 2

821 (10%) 425

824 428 426 125 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

119 14% 35% 51%

100 75 50 25 0 2009 2010 2011 2012 2013 Unfunded

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

123

 High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands)

kenya Population 2012 43 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 60

Rate (per 100 000 population)

40

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

9.5 (5.4–15) 7.7 (6.6–8.9) 130 (71–210) 120 (110–120) 45 (44–47) 79 (76–83)

22 (13–34) 18 (15–21) 299 (163–475) 272 (261–283) 105 (101–109)

20

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

36 937 (41) Relapse 28 574 (32) Treatment after failure 8 123 0 89 568 0 92 987 (9) Treatment after default (0) Total retreatment Total cases notified 15 934 (18) Other

3 419 (36) 326 (3) 1 408 (15) 4 428 (46) 9 581 99 149

Prevalence (rate per 100 000 population)

TB case notifications 2012

600

400

200

0 1990

1995

2000

2005

2010

400

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

300 200 100 0 1990

M:F ratio Age < 15

1.6 996

1.2 1 907

1.2 2 465 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

4.2 0.2 0.2 Yes, in and outside country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100

New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment Is rifampicin used throughout treatment for new patients?

88 85 82 Yes Number (%)

Treatment success rate (%)

Treatment success rate 2011 (%)

80

60

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

92 890 35 837 35 025 26 487

(94) (39) (98) (74)

40 1995

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

60 000 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.5 (0.01–5) 1 800 (7.4–3 700) New

Retreatment

40 000

10 (3.5–17) 980 (340–1 600) Total

20 000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

78 (<1%) 9

1 183 (12%) 205

1 344 225 202 60 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

55 24% 15% 61%

40

20

0 Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

124

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



mozambique Population 2012 25 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 400 300 200 100 0 1990

High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

13 (0.98–41) 45 (35–53) 140 (28–340) 140 (96–190) 83 (58–110) 34 (25–50)

53 (3.9–163) 177 (138–209) 553 (111–1 342) 552 (383–753) 330 (228–450)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

20 951 (45) Relapse 19 797 (43) Treatment after failure 0 46 290 0 47 741 (0) Treatment after default Total retreatment Total cases notified 5 542 (12) Other

1 451 (32) 243 (5) 248 (5) 2 595 (57) 4 537 50 827

Prevalence (rate per 100 000 population)

TB case notifications 2012

3000

2000

1000

0 1990

1995

2000

2005

2010

1250

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

1000 750 500 250 0 1990

M:F ratio Age < 15

2 506

841 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

1.2 0.6 0.4 Yes, outside country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

Yes Number (%)

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

47 960 27 979 27 319 15 391 17 317

(94) (58) (98) (55)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

30 000 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 3.5 (2.2–4.8) 1 400 (900–2 000) New

Retreatment

20 000

12 (0–25) 540 (0–1 100) Total

10 000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

205 (<1%) 44

243 (5%) 136

448 266 213 40 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

11 19% 51% 30%

30 20 10 0

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

125



Myanmar Population 2012 53 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 300

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

200

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

25 (12–44) 4.6 (3.8–5.3) 260 (200–320) 200 (170–230) 19 (16–21) 71 (62–83)

48 (23–84) 8.8 (7.3–10) 489 (377–616) 377 (322–435) 35 (30–41)

100

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

4 558 (40) 1 671 (14) 521 (5) 4 787 (41) 11 537 148 149

2000 1500 1000 500 0 1990

42 909 (31) Relapse 73 042 (53) Treatment after failure 0 0 136 612 0 141 170 (0) Treatment after default (0) Total retreatment Total cases notified 20 661 (15) Other

1995

2000

2005

2010

600 ncidence (rate per 100 000 population per year)

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

400

M:F ratio Age < 15

1.9 338

2012

200

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.9 0.2 0.2 Yes, in and outside country

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

86 90 72 Yes Number (%)

Treatment success rate (%)

80

60

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

40 1995

1997

1999

2001

2003

2005

2007

2009

2011

19 219 5 161 4 270 Retreatment

(13) (27) (83) 6000 Number of patients

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

4000

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 4.2 (3.1–5.6) 4 900 (3 600–6 500) New

10 (6.9–14) 1 200 (790–1 600) Total

2000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

778 442 2013 Total budget (US$ millions) 40 30 20 10 0

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

36 2% 39% 60%

2009

2010

2011

2012

2013 Unfunded

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

Funded domestically

Funded internationally

126

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



nigeria Population 2012 169 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 200 150 100 50 0 1990

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

27 (1.6–86) 19 (11–25) 270 (43–710) 180 (85–310) 46 (21–80) 51 (29–110)

16 (0.92–51) 11 (6.7–15) 161 (25–420) 108 (50–186) 27 (13–47)

1995

2000

2005

2010

TB case notifications 2012 New cases

(%)

2 513 (33) 612 (8) 1 174 (16) 3 249 (43) 7 548 97 853 Prevalence (rate per 100 000 population)

1500

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

52 901 (59) Relapse 32 972 (37) Treatment after failure 4 432 90 305 92 818 Treatment after default (5) Other Total retreatment Total cases notified

1000

500

0 1990

1995

2000

2005

2010

600

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

500 400 300 200 100 0 1990 1995 Incidence

M:F ratio Age < 15

1.6 1 187

2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.8 0.1 <0.1 Yes, outside country

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

85 85 82 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

82 641 19 342 15 565 10 866 140 460 2 257 Retreatment

(84) (23) (80) (56)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

20 000 Number of patients 15 000 10 000 5000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.9 (2.1–4) 2 500 (1 800–3 400) New

14 (10–19) 1 100 (770–1 500) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

11 (<1%) 11

94 (1%) 94

107 107 125 180 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

154 8% 24% 68%

120

60

0 Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

127

 High TB burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands)

Pakistan Population 2012 179 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 200 150 100 50 0 1990

Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

62 (27–110) 1.2 (0.83–1.3) 670 (320–1 100) 410 (340–490) 3.8 (3.1–4.6) 65 (54–78)

34 (15–61) 0.66 (0.46–0.75) 376 (181–641) 231 (190–276) 2.1 (1.7–2.6)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

110 545 (42) Relapse 109 425 (42) Treatment after failure 0 0 261 380 0 267 475 (0) Treatment after default (0) Total retreatment Total cases notified 41 410 (16) Other

6 095 (52) 847 (7) 1 241 (11) 3 534 (30) 11 717 273 097

Prevalence (rate per 100 000 population)

TB case notifications 2012

1500

1000

500

0 1990

1995

2000

2005

2010

400

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

300 200 100 0 1990

M:F ratio Age < 15

1.1 3 947

1.0 13 884

0.8 8 328 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.8 0.2 0.1 Yes, in country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

92 93 80 Yes Number (%)

Treatment success rate (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

1997

1999

2001

2003

2005

2007

2009

2011

10 419 30 30 22 Retreatment

(4) (<1) (100) (73) 40 Number of patients 30 20 10

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 3.5 (0.1–12) 7 700 (220–27 000) New

32 (7.5–56) 3 700 (880–6 600) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

461 (<1%) 19

154 (1%) 55

4 198 1 602 1 045 80 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

73 5% 85% 9%

60 40 20 0

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

128

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

 High TB burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands)

philippines Population 2012 97 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 80 60 40 20 0 1990

Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

23 (22–25) 0.11 (0.09–0.13) 450 (390–500) 260 (210–310) 0.46 (0.38–0.55) 84 (71–100)

24 (22–26) 0.11 (0.09–0.14) 461 (405–520) 265 (219–316) 0.48 (0.39–0.57)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

93 586 (44) Relapse 115 263 (54) Treatment after failure 0 3 270 0 212 119 0 216 199 (0) Treatment after default (2) Other (0) Total retreatment Total cases notified

4 080 (17) 591 (3) 1 243 (5) 17 575 (75) 23 489 235 608

Prevalence (rate per 100 000 population)

TB case notifications 2012

1500

1000

500

0 1990

1995

2000

2005

2010

600

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

400

M:F ratio Age < 15

2.3 1 032

1.6

1.2

200

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

2012

2.7 0.7 0.2 Yes, in country

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

90 85 65 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

2 040 4

(<1) (<1)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

10 Number of patients 8 6 4 2 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 4 (2.9–5.5) 8 400 (6 000–11 000) New

Retreatment

21 (14–29) 4 900 (3 400–6 800) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

35 (<1%) 11

2 038 (9%) 653

2 107 679 1 918 160 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

149 16% 15% 69%

120 80 40 0

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

129



Russian federation Population 2012 143 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 25 20 15 10 5 0 1990

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

19 (18–20) 1.8 (1.5–2.2) 170 (73–320) 130 (110–150) 9.3 (7.9–11) 81 (70–96)

13 (13–14) 1.2 (1–1.5) 121 (51–221) 91 (77–106) 6.5 (5.5–7.5)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

8 211 (16) 9 109 (17) 2 593 (5) 32 466 (62) 52 379 149 921

400 300 200 100 0 1990

27 467 (28) Relapse 59 019 (61) Treatment after failure 1 039 0 97 542 0 105 753 (1) Treatment after default (0) Total retreatment Total cases notified 10 017 (10) Other

1995

2000

2005

2010

200

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

150 100 50 0 1990

M:F ratio Age < 15

2.7 48

2.2 730

1.3 2 910 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.7 4.1 3.8 Yes, in country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

54 73 42 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT statusb

75 995 4 880 Retreatment Number of patients

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

8000 6000 4000 2000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 23 (21–25) 20 000 (18 000–22 000) New

49 (44–53) 25 000 (23 000–28 000) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

32 647 (79%) 6 537

12 324 (24%) 7 075

44 971 13 612 18 452 1800 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

1 592 100% <1% 0%

1200

600

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b The reported number of TB patients with known HIV status is for new TB patients in the civilian sector only. It was not possible to calculate the percentage of all TB patients with known HIV status.

0

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

130

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



south africa Population 2012 52 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 200 150 100 50 0 1990

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

31 (3.7–86) 88 (75–100) 450 (160–880) 530 (430–630) 330 (270–390) 62 (52–75)

59 (7–164) 168 (144–192) 857 (305–1 685) 1 003 (827–1 194) 631 (521–752)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

26 668 (51) 3 123 (6) 7 788 (15) 15 007 (29) 52 586 349 582

2000 1500 1000 500 0 1990

119 898 (40) Relapse 63 210 (21) Treatment after failure 71 421 (24) Treatment after default 42 467 (14) Other 0 296 996 0 323 664 (0) Total retreatment Total cases notified

1995

2000

2005

2010

1250 ncidence (rate per 100 000 population per year) 1000 750 500 250 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

1.3 2 650

1.1 33 601

1.0 2 327 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.4 1.4 1.4 Yes, in country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

79 76 66 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

294 196 190 093 140 868 101 937 949 800 369 747

(84) (65) (74) (54)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

250 000 Number of patients 200 000 150 000 100 000 50 000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.8 (1.4–2.3) 4 600 (3 700–5 800) New

Retreatment

6.7 (5.4–8.2) 3 500 (2 800–4 300) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

37 310 15 419 6 494 500 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

475 97% 3% 0%

400 300 200 100 0 2009 2010 2011 2012 2013 Unfunded

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

131

 High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands)

Thailand Population 2012 67 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 60

Rate (per 100 000 population)

40

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

9.2 (3.8–17) 2.2 (1.9–2.8) 110 (47–190) 80 (66–95) 12 (10–14) 76 (64–92)

14 (5.8–25) 3.3 (2.9–4.2) 159 (71–282) 119 (98–142) 18 (15–22)

20

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

1 887 (68) 327 (12) 577 (21) 2 791 61 208

500 400 300 200 100 0 1990

30 998 (54) Relapse 17 537 (31) Treatment after failure 57 387 1 030 59 274 Treatment after default Total retreatment Total cases notified 8 852 (15) Other

1995

2000

2005

2010

250 ncidence (rate per 100 000 population per year) 200 150 100 50 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

2.4 117

2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

1.6 4.9 1.3 Yes, in country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

85 78 69 Yes Number (%)

80

Is rifampicin used throughout treatment for new patients?

60

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

44 035 5 807 4 460 3 591

(72) (13) (77) (62)

40 1995

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

10 000 Number of patients 8000 6000 4000 2000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.7 (1–2.6) 800 (480–1 200) New

Retreatment

35 (28–42) 960 (780–1 200) Retreatment Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

7 379 492 50 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

44b 92% 2% 6%

40 30 20 10 0 2009 2010 2011 2012 2013 Unfunded

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b Based on data reported for 2013 in the 2012 round of data collection. In 2013, Thailand was not able to report funding for the sub-national level.

Funded domestically

Funded internationally

132

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

 High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands)

uganda Population 2012 36 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 300

Rate (per 100 000 population)

200

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

4.7 (0.82–12) 9.2 (8–12) 64 (24–120) 65 (53–79) 35 (28–42) 69 (57–85)

13 (2.3–33) 25 (22–32) 175 (67–334) 179 (145–216) 95 (77–115)

100

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

1 334 (34) 270 (7) 1 164 (30) 1 114 (29) 3 882 47 211

2500 2000 1500 1000 500 0 1990

24 916 (58) Relapse 11 487 (27) Treatment after failure 1 783 0 43 329 0 44 663 (4) Treatment after default (0) Total retreatment Total cases notified 5 143 (12) Other

1995

2000

2005

2010

1250

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

1000 750 500 250 0 1990

M:F ratio Age < 15

1.8 636

2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

3.2 0.6 0.6 Yes, in country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

77 66 71 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

40 581 20 376 19 163 9 962

(86) (50) (94) (49)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

25 000 Number of patients 20 000 15 000 10 000 5000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.4 (0.6–2.2) 540 (230–860) New

Retreatment

12 (6.8–19) 470 (260–750) Retreatment Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

196 (<1%) 9

748 (19%) 71

1 406 89 41 40 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

31 7% 62% 31%

30 20 10 0

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

133



United republic of tanzania Population 2012 48 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 80 60 40 20 0 1990

High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

6.1 (3.2–9.9) 7 (5.8–8) 84 (45–140) 79 (74–84) 32 (30–34) 79 (74–84)

13 (6.8–21) 15 (12–17) 176 (95–283) 165 (154–175) 68 (64–72)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

1 052 (38) 154 (6) 201 (7) 1 359 (49) 2 766 63 892

800 600 400 200 0 1990

25 138 (41) Relapse 21 393 (35) Treatment after failure 0 0 61 126 0 62 178 (0) Treatment after default (0) Total retreatment Total cases notified 14 595 (24) Other

1995

2000

2005

2010

300

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

200

M:F ratio Age < 15

1.8 490

1.3 2 508

1.2 2 282 2012

100

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

2.0 0.4 0.1 Yes, in country

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

88 88 82 Yes Number (%)

90 80 70 60 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

52 499 20 269 19 501 10 993 357 400 Retreatment

(82) (39) (96) (54)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

25 000 Number of patients 20 000 15 000 10 000 5000 0

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.1 (0.3–2.8) 500 (140–1 300) New

0 (0–5.9) 0 (0–160) Retreatment Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

639 (3%) 12

108 (4%) 12

1 006 42 44 60 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

58 14% 19% 67%

40

20

0 Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

134

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



Viet nam Population 2012 91 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 80 60 40 20 0 1990

High TB burden | High HIV burden | High MDR-TB burden Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

18 (12–25) 2.1 (1.8–2.7) 200 (79–370) 130 (99–170) 9.3 (6.9–12) 76 (59–100)

20 (13–27) 2.4 (2–2.9) 218 (86–410) 147 (109–192) 10 (7.6–13)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Prevalence (rate per 100 000 population)

TB case notifications 2012 Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

7 259 (80) 567 (6) 494 (5) 733 (8) 9 053 103 906

1000 750 500 250 0 1990

51 033 (54) Relapse 21 706 (23) Treatment after failure 3 210 94 853 102 112 (3) Treatment after default Total retreatment Total cases notified 18 904 (20) Other

1995

2000

2005

2010

400

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

300 200 100 0 1990

M:F ratio Age < 15

3.0 142

2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

0.9 1.4 0.1 Yes, in country

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

93 93 82 No Number (%)

90 80 70 60 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

68 259 4 775 3 486 2 232 5 663

(66) (7) (73) (47)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

6000 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.7 (2–3.7) 2 100 (1 500–2 800) New

Retreatment

4000

19 (14–25) 1 700 (1 300–2 300) Total

2000

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2003 2004

2005 2006

2007 2008

2009

2010 2011 on ART

2012

273 713 80 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

66 8% 20% 72%

60 40 20 0

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

135

 High TB burden | High HIV burden Estimates of TB burdena 2012 Number (thousands)

zimbabwe Population 2012 14 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 150

Rate (per 100 000 population)

100

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

4.6 (0.16–16) 18 (15–20) 59 (13–140) 77 (60–97) 55 (42–69) 46 (37–60)

33 (1.2–117) 132 (111–147) 433 (92–1 034) 562 (434–706) 399 (308–501)

50

0 1990

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

12 163 (35) Relapse 14 354 (42) Treatment after failure 2 962 0 34 391 0 35 760 (9) Treatment after default (0) Total retreatment Total cases notified 4 912 (14) Other

1 369 (32) 200 (5) 176 (4) 2 584 (60) 4 329 38 720

Prevalence (rate per 100 000 population)

TB case notifications 2012

1500

1000

500

0 1990

1995

2000

2005

2010

1000

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

ncidence (rate per 100 000 population per year)

750 500 250 0 1990

M:F ratio Age < 15

1.3 293

1.2 2 177

1.1 441 2012

Laboratories Smear (per 100 000 population) Culture (per 5 million population) Drug susceptibility testing (per 5 million population) Is second-line drug susceptibility testing available?

1.3 0.7 0.7 No

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment

81 80 78 Yes Number (%)

80 60 40 20 0 1995

Is rifampicin used throughout treatment for new patients?

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

34 212 23 957 6 301 4 419 Retreatment

(88) (70) (26) (18)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

40 000 Number of patients 30 000 20 000 10 000 0 2003 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 1.9 (1–3.3) 570 (300–960) New

8.3 (1.8–22) 360 (76–970) Retreatment Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

2005 2006

2007 2008

2009

2010 2011 on ART

2012

360 (3%) 43

258 (6%) 35

689 149 105 45 2013 Total budget (US$ millions)

HIV-positive TB patients

on CPT

Financing TB control National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

38 4% 39% 56%

30

15

0 Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

136

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

Annex 3

Regional profiles

 WHO Member States  46 Estimates of TB burdena 2012

WHO african region Population 2012 893 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 80 60 40 20 0 1990

Number (thousands)

Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

230 (160–310) 250 (230–270) 2 700 (2 100–3 300) 2 300 (2 100–2 500) 830 (760–910) 59 (55–64)

26 (18–35) 28 (26–30) 303 (239–373) 255 (235–275) 93 (85–102)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

600 355 (47) Relapse 345 947 (27) Treatment after failure 100 537 (7.8) Treatment after default 234 539 (18) Other 977 (<1) 1 282 355 2 017 1 342 852 Total retreatment Total cases notified

60 497 (47) 9 174 (7.2) 17 468 (14) 41 128 (32) 128 267 1 412 639

Prevalence (rate per 100 000 population)

TB case notifications 2012

750

500

250

0 1990

1995

2000

2005

2010

400 ncidence (rate per 100 000 population per year)

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

300 200 100 0 1990

M:F ratio Age < 15

1.5 14 340

1.2 54 760

1.1 18 667 Number of Member Statesb

Laboratories 2012 Smear (per 100 000 population) ≥ 1 Culture (per 5 million population) ≥ 1 Drug susceptibility testing (per 5 million population) ≥ 1

28 out of 43 15 out of 43 9 out of 43

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

Treatment success rate 2011 (%) Treatment success rate (%)

100

New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment MDR-TB (2010 cohort)

82 76 68 46 Number (%)c

80 60 40 20 0 1995

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

1 040 292 443 558 346 739 243 037 2 391 601 473 214

(74) (43) (79) (55)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

500 Number of patients 400 300 200 100 0 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.3 (0.2–4.4) 24 000 (2 100–46 000) New

Retreatment

11 (4.4–17) 14 000 (5 600–22 000) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2 216 (<1%) 211

3 969 (3.1%) 1 453

45 689 18 129 9 303 2013 Total budget (US$ millions)

2005

2006

2007

2008

2009 on CPT

2010

2011 on ART

2012

HIV-positive TB patients

Financing TB control (low- and middle-income countries)d National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

1500

1 360 44 21 36

1000

500

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b Data are not collected from all Member States. c Calculations exclude countries with missing numerators or denominators. d Financing indicators exclude funding for general healthcare services provided outside NTPs.

0

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

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WHO region of the americas Population 2012 961 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 8 6 4 2 0 1990

WHO Member States  35 Other countries and territories  11 Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

19 (16–21) 6 (6–7) 390 (300–490) 280 (260–300) 31 (28–34) 79 (74–85)

1.9 (1.7–2.2) 0.66 (0.58–0.75) 40 (31–51) 29 (27–31) 3.3 (3–3.6)

1995

2000

2005

2010

150

TB case notifications 2012 New cases

(%)

9 949 (42) 1 195 (5.0) 5 858 (25) 6 809 (29) 23 811 232 695

Retreatment cases (%)

Prevalence (rate per 100 000 population)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

122 606 (59) Relapse 35 606 (17) Treatment after failure 14 564 (7.0) Treatment after default 34 400 (16) Other 1 669 (<1) 208 845 39 218 794 Total retreatment Total cases notified

100

50

0 1990

1995

2000

2005

2010

80 ncidence (rate per 100 000 population per year) 60 40 20 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

1.7 2 012

1.5 5 381

1.3 2 143 Number of Member Statesb

Laboratories 2012 Smear (per 100 000 population) ≥ 1 Culture (per 5 million population) ≥ 1 Drug susceptibility testing (per 5 million population) ≥ 1

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

18 out of 23 20 out of 23 9 out of 23 100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment MDR-TB (2010 cohort) 78 71 51 54 Number (%)c

80 60 40 20 0 1995

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

129 174 20 355 3 513 13 699 4 485 18 710 Retreatment

(56) (16) (61) (76)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

25 Number of patients 20 15 10 5 0 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.2 (1.4–3) 3 800 (2 400–5 200) New

14 (4.7–22) 3 200 (1 100–5 300) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005

2006

2007

2008

2009 on CPT

2010

2011 on ART

2012

28 625 (22%) 1 347

5 481 (23%) 1 482

34 785 2 967 3 102 Total budget (US$ millions) 2013 200 150 100 50 0

HIV-positive TB patients

Financing TB control (low- and middle-income countries)d National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

185 69 12 19

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b Data are not collected from all Member States. c Calculations exclude countries with missing numerators or denominators. d Financing indicators exclude funding for general healthcare services provided outside NTPs.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

140

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



WHO eastern mediterranean region Population 2012 617 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 60

WHO Member States  22 Other countries and territories  1 Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

40

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

100 (63–150) 4 (4–5) 1 100 (730–1 600) 670 (590–750) 11 (10–12) 63 (56–71)

16 (10–24) 0.68 (0.61–0.76) 180 (118–256) 109 (96–122) 1.8 (1.6–2)

20

0 1990

1995

2000

2005

2010

TB case notifications 2012 New cases

(%)

11 208 (53) 2 007 (9.5) 2 813 (13) 5 200 (24) 21 228 430 789

Prevalence (rate per 100 000 population)

500 400 300 200 100 0 1990

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

173 963 (42) Relapse 135 346 (33) Treatment after failure 8 523 (2.1) Treatment after default 90 943 (22) Other 702 (<1) 409 477 84 420 685 Total retreatment Total cases notified

1995

2000

2005

2010

200 ncidence (rate per 100 000 population per year) 150 100 50 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

1.2 5 641

1.0 20 716

0.8 13 451 Number of Member Statesb

Laboratories 2012 Smear (per 100 000 population) ≥ 1 Culture (per 5 million population) ≥ 1 Drug susceptibility testing (per 5 million population) ≥ 1

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

7 out of 22 13 out of 22 9 out of 22 100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment MDR-TB (2010 cohort) 88 89 74 56 Number (%)c

80 60 40 20 0 1995

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

58 498 2 020 1 010 881 15 012 243 Retreatment

(14) (3.5) (69) (48)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

2.0 Number of patients 1.5 1.0 0.5 0 2004

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 3.5 (0.1–11) 11 000 (320–36 000) New

32 (12–54) 6 900 (2 400–11 000) Total

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

2005

2006

2007

2008

2009 on CPT

2010

2011 on ART

2012

1 990 (1.1%) 104

1 617 (7.6%) 468

7 256 2 236 1 602 Total budget (US$ millions) 2013 200 150 100 50 0

HIV-positive TB patients

Financing TB control (low- and middle-income countries)d National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

188 32 53 16

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b Data are not collected from all Member States. c Calculations exclude countries with missing numerators or denominators. d Financing indicators exclude funding for general healthcare services provided outside NTPs.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

141



WHO european region Population 2012 905 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 10 8 6 4 2 0 1990

WHO Member States  53 Other countries and territories  1 Estimates of TB

burdena

2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

36 (35–36) 4 (3–4) 510 (380–650) 360 (340–390) 19 (17–21) 74 (70–79)

3.9 (3.9–4) 0.43 (0.38–0.49) 56 (42–72) 40 (38–43) 2.1 (1.9–2.3)

1995

2000

2005

2010

200

TB case notifications 2012 New cases

(%)

25 185 (27) 11 542 (12) 4 883 (5.3) 51 237 (55) 92 847 337 167

Prevalence (rate per 100 000 population)

Retreatment cases (%)

150 100 50 0 1990

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

78 336 (32) Relapse 118 614 (49) Treatment after failure 6 257 (2.6) Treatment after default 39 029 (16) Other 30 (<1) 242 266 2 054 267 451 Total retreatment Total cases notified

1995

2000

2005

2010

100 ncidence (rate per 100 000 population per year) 80 60 40 20 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

2.4 325

1.9 2 681

1.2 7 036 Number of Member Statesb

Laboratories 2012 Smear (per 100 000 population) ≥ 1 Culture (per 5 million population) ≥ 1 Drug susceptibility testing (per 5 million population) ≥ 1

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

8 out of 53 37 out of 53 32 out of 53 100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment MDR-TB (2010 cohort) 65 79 47 49 Number (%)c

80 60 40 20 0 1995

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

203 705 12 900 1 249 5 414 23 567 17 938

(60) (6.3) (67) (74)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

15 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 16 (9.5–22) 32 000 (19 000–45 000) New

Retreatment

10

45 (39–51) 42 000 (36 000–48 000) Total

5

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2004

2005

2006

2007

2008

2009 on CPT

2010

2011 on ART

2012

85 962 (73%) 13 393

37 774 (41%) 18 372

125 655 37 769 42 399 Total budget (US$ millions) 2013 2500 2000 1500 1000 500 0 2009

HIV-positive TB patients

Financing TB control (low- and middle-income countries)d National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

2 217 92 3.7 4.3

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b Data are not collected from all Member States. c Calculations exclude countries with missing numerators or denominators. d Financing indicators exclude funding for general healthcare services provided outside NTPs.

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

142

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data



WHO south-east asia region Population 2012 1 833 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 80 60 40 20 0 1990

WHO Member States  11 Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

450 (330–590) 51 (46–56) 4 800 (3 700–6 100) 3 400 (3 200–3 700) 170 (160–180) 62 (58–67)

25 (18–32) 2.8 (2.5–3.1) 264 (203–333) 187 (174–200) 9.2 (8.5–10)

1995

2000

2005

2010

New cases

(%)

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

1 065 852 (53) Relapse 586 455 (29) Treatment after failure 0 (0) Treatment after default Total retreatment Total cases notified 338 303 (17) Other 3 004 (<1) 1 993 614 5 261 2 124 859

131 245 (39) 22 348 (6.7) 69 100 (21) 109 887 (33) 332 580 2 331 455

Prevalence (rate per 100 000 population)

TB case notifications 2012

600

400

200

0 1990

1995

2000

2005

2010

300 ncidence (rate per 100 000 population per year)

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

200

M:F ratio Age < 15

2.0 17 116

1.4 26 320

1.0 7 782 Number of Member Statesb

100

Laboratories 2012 Smear (per 100 000 population) ≥ 1 Culture (per 5 million population) ≥ 1 Drug susceptibility testing (per 5 million population) ≥ 1

9 out of 11 3 out of 11 2 out of 11

0 1990

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment MDR-TB (2010 cohort) 89 89 75 46 Number (%)c Treatment success rate (%)

100 80 60 40 20 0 1995

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

904 223 56 093 45 415 34 167 1 351 768 8

(39) (6.2) (89) (61)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

60 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 2.2 (1.6–2.8) 36 000 (26 000–46 000) New

Retreatment

16 (11–21) 54 000 (37 000–70 000) Total

40

20

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

1 352 (<1%) 43

2 292 (<1%) 1 273

66 757 19 202 15 845 2013 Total budget (US$ millions)

0 2004

2005

2006

2007

2008

2009 on CPT

2010

2011 on ART

2012

HIV-positive TB patients

Financing TB control (low- and middle-income countries)d National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

600

469 30 41 29

400

200

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b Data are not collected from all Member States. c Calculations exclude countries with missing numerators or denominators. d Financing indicators exclude funding for general healthcare services provided outside NTPs.

0

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

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WHO western pacific region Population 2012 1 846 million Mortality (excludes H V+TB) (rate per 100 000 population per year) 30

WHO Member States  27 Other countries and territories  9 Estimates of TB burdena 2012 Number (thousands) Rate (per 100 000 population)

20

Mortality (excludes HIV+TB) Mortality (HIV+TB only) Prevalence (includes HIV+TB) Incidence (includes HIV+TB) Incidence (HIV+TB only) Case detection, all forms (%)

110 (96–120) 5 (4–5) 2 400 (2 100–2 600) 1 600 (1 500–1 800) 24 (21–27) 81 (75–89)

5.8 (5.2–6.4) 0.26 (0.23–0.29) 128 (115–142) 87 (80–95) 1.3 (1.1–1.5)

10

0 1990

1995

2000

2005

2010

TB case notifications 2012 New cases

(%)

45 277 (57) 3 714 (4.6) 3 137 (3.9) 27 889 (35) 80 017 1 345 466

Prevalence (rate per 100 000 population)

400 300 200 100 0 1990

Retreatment cases (%)

Smear-positive Smear-negative Smear-unknown / not done Extrapulmonary Other Total new Other (history unknown) Total new and relapse

500 171 (40) Relapse 691 714 (55) Treatment after failure 9 751 (<1) Treatment after default 59 294 (4.7) Other 3 287 (<1) 1 264 217 1 232 1 309 494 Total retreatment Total cases notified

1995

2000

2005

2010

200 ncidence (rate per 100 000 population per year) 150 100 50 0 1990

New cases Smear-negative/ unknown/ Smear-positive not done Extrapulmonary

M:F ratio Age < 15

2.4 2 693

2.0 4 945

1.0 767 Number of Member Statesb

Laboratories 2012 Smear (per 100 000 population) ≥ 1 Culture (per 5 million population) ≥ 1 Drug susceptibility testing (per 5 million population) ≥ 1

1995 Incidence

2000 Incidence (HIV+TB)

2005

2010 Notifications

12 out of 17 11 out of 17 4 out of 17 100 Treatment success rate (%)

Treatment success rate 2011 (%) New smear-positive and/or culture-positive New smear-negative/extrapulmonary Retreatment MDR-TB (2010 cohort) 94 93 86 46 Number (%)c

80 60 40 20 0 1995

TB/HIV 2012 TB patients with known HIV status HIV-positive TB patients HIV-positive TB patients on co-trimoxazole preventive therapy (CPT) HIV-positive TB patients on antiretroviral therapy (ART) HIV-positive people screened for TB HIV-positive people provided with IPT

451 302 14 119 5 088 7 722 308 193 8 557

(34) (3.1) (79) (56)

1997

1999

2001

2003

2005

2007

2009

2011

New smear-positive (and/or culture-positive) New smear-negative/extrapulmonary

Retreatment

15 Number of patients

Estimates of MDR-TB burden 2012a New % of TB cases with MDR-TB MDR-TB cases among notified pulmonary TB cases 4.7 (3.3–6.1) 57 000 (40 000–74 000) New

Retreatment

10

22 (18–26) 18 000 (14 000–21 000) Total

5

Reported cases of MDR-TB 2012 Cases tested for MDR-TB Laboratory-confirmed MDR-TB cases Patients started on MDR-TB treatment

Retreatment

0 2004

2005

2006

2007

2008

2009 on CPT

2010

2011 on ART

2012

16 485 (3.3%) 943

8 134 (10%) 2 602

33 909 4 473 5 070 Total budget (US$ millions) 2013 800 600 400 200 0

HIV-positive TB patients

Financing TB control (low- and middle-income countries)d National TB programme budget (US$ millions) % Funded domestically % Funded internationally % Unfunded

662 50 15 36

Data are as reported to WHO. Estimates of TB and MDR-TB burden are produced by WHO in consultation with countries. a Ranges represent uncertainty intervals. b Data are not collected from all Member States. c Calculations exclude countries with missing numerators or denominators. d Financing indicators exclude funding for general healthcare services provided outside NTPs.

2009

2010

2011

2012

2013 Unfunded

Funded domestically

Funded internationally

144

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

Annex 4

Key indicators for the world, WHO regions and individual countries Summary by WHO region African Region Region of the Americas Eastern Mediterranean Region European Region South-East Asia Region Western Pacific Region 147 155 181 207 225 255 267

summary by who region Table A4.1 Estimates of the burden of disease caused by TB, 1990–2012 Table A4.2 Incidence, notification and case detection rates, all forms, 1990–2012 Table A4.3 Case notifications, 1990–2012 Table A4.4 Treatment outcomes, new smear-positive cases, 1995–2011 Table A4.5 Treatment outcomes, retreatment cases, 1995–2011 Table A4.6 HIV testing and provision of CPT, ART and IPT, 2005–2012 Table A4.7 Testing for MDR-TB and number of confirmed cases of MDR-TB, 2005–2012 Table A4.8 New smear-positive case notification by age and sex, 1995–2012 149 150 151 152 152 153 153 154

Estimates of mortality, prevalence and incidence Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See ANNEX 1 for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. The main updates implemented in this report are explained in Box 2.1 of Chapter 2. Estimates published in previous global TB control reports should no longer be used.

Data source Data shown in this annex are taken from the WHO global TB database on 1 October 2013. Data shown in the main part of the report were taken from the database in July 2013. As a result, data in this annex may differ slightly from those in the main part of the report. Data for all years can be downloaded from www.who.int/tb/data.

148

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Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

149

summary by who region

1990 1995 2000 2005 2010 2011 2012 Africa 1990 1995 2000 2005 2010 2011 2012 The Americas 1990 1995 2000 2005 2010 2011 2012 Eastern 1990 Mediterranean 1995 2000 2005 2010 2011 2012 Europe 1990 1995 2000 2005 2010 2011 2012 South-East 1990 Asia 1995 2000 2005 2010 2011 2012 Western 1990 Pacific 1995 2000 2005 2010 2011 2012 Global

5 298 5 718 6 102 6 489 6 890 6 972 7 054 503 577 655 744 847 870 893 727 783 841 892 942 951 961 378 429 480 533 593 605 617 849 863 870 882 899 902 905 1 310 1 435 1 560 1 682 1 790 1 812 1 833 1 532 1 630 1 697 1 756 1 820 1 833 1 846

1 300 1 400 1 400 1 200 1 000 980 940 210 230 250 240 230 230 230 43 37 29 24 21 19 19 120 130 140 120 100 100 100 39 60 71 66 44 40 36 570 640 680 620 500 480 450 320 260 200 150 120 110 110

(1 100–1 500) (1 100–1 600) (1 100–1 600) (1 000–1 400) (850–1 200) (820–1 100) (790–1 100) (120–340) (140–350) (130–400) (130–390) (160–310) (160–310) (160–310) (35–52) (32–42) (25–33) (21–27) (18–24) (17–22) (16–21) (57–200) (67–210) (70–230) (65–190) (61–150) (62–150) (63–150) (36–43) (58–62) (69–73) (64–67) (43–46) (39–41) (35–36) (410–750) (460–840) (500–890) (480–780) (370–660) (350–620) (330–590) (280–350) (230–300) (160–230) (140–170) (110–130) (100–120) (96–120)

25 24 22 19 15 14 13 43 41 38 32 27 26 26 5.9 4.7 3.5 2.7 2.2 2 1.9 32 30 29 23 17 17 16 4.6 6.9 8.1 7.4 4.9 4.5 3.9 43 44 43 37 28 26 25 21 16 12 8.6 6.4 6.1 5.8

(21–29) (20–28) (18–27) (16–22) (12–17) (12–16) (11–16) (24–67) (24–61) (20–61) (17–53) (19–36) (18–35) (18–35) (4.8–7.1) (4.1–5.4) (3.0–4.0) (2.3–3.1) (1.9–2.5) (1.8–2.3) (1.7–2.2) (15–54) (16–50) (15–48) (12–36) (10–25) (10–25) (10–24) (4.2–5.1) (6.7–7.2) (7.9–8.4) (7.3–7.6) (4.8–5.1) (4.4–4.6) (3.9–4.0) (31–57) (32–58) (32–57) (29–47) (21–37) (19–34) (18–32) (18–23) (14–18) (9.6–14) (7.9–9.5) (5.9–7.1) (5.5–6.7) (5.2–6.4)

15 000 16 000 16 000 15 000 13 000 12 000 12 000 2 000 2 300 2 600 2 700 2 700 2 700 2 700 750 600 510 440 390 400 390 1 100 1 200 1 200 1 200 1 100 1 100 1 100 610 1 000 1 100 910 620 580 510 6 100 6 700 7 000 6 300 5 200 5 000 4 800 4 000 3 900 3 600 3 100 2 500 2 500 2 400

(13 000–16 000) (14 000–17 000) (14 000–18 000) (13 000–16 000) (11 000–14 000) (11 000–14 000) (11 000–13 000) (1 300–3 000) (1 600–3 200) (1 700–3 700) (1 800–3 800) (2 100–3 300) (2 100–3 300) (2 100–3 300) (540–990) (470–750) (390–640) (340–550) (300–490) (300–500) (300–490) (600–1 600) (720–1 700) (740–1 800) (740–1 700) (710–1 500) (720–1 600) (730–1 600) (500–720) (840–1 200) (890–1 400) (700–1 100) (470–790) (440–740) (380–650) (5 200–7 000) (5 800–7 700) (6 000–8 100) (5 300–7 400) (4 000–6 600) (3 900–6 400) (3 700–6 100) (3 600–4 400) (3 500–4 300) (3 200–4 000) (2 700–3 400) (2 300–2 800) (2 200–2 700) (2 100–2 600)

274 275 263 225 182 176 169 404 405 397 364 318 310 303 103 76 60 49 41 42 40 279 272 256 216 184 182 180 71 120 129 103 68 64 56 465 469 449 375 293 278 264 261 238 210 174 139 134 128

(249–302) (251–301) (237–290) (200–250) (160–205) (155–198) (149–190) (254–590) (276–558) (257–567) (239–515) (249–395) (244–383) (239–373) (74–136) (59–95) (47–76) (38–61) (32–52) (32–53) (31–51) (159–433) (168–401) (155–383) (138–312) (120–260) (119–258) (118–256) (59–85) (97–144) (103–159) (79–130) (52–87) (49–82) (42–72) (400–535) (404–538) (387–516) (314–442) (224–371) (213–352) (203–333) (238–286) (216–262) (187–234) (156–193) (124–153) (120–148) (115–142)

7 800 8 400 9 000 9 200 8 800 8 700 8 600 1 200 1 600 2 000 2 300 2 300 2 300 2 300 430 380 340 310 280 280 280 460 530 560 600 650 660 670 370 560 640 570 420 400 360 2 900 3 100 3 400 3 600 3 500 3 500 3 400 2 500 2 300 2 000 1 800 1 700 1 600 1 600

(7 200–8 500) (7 900–9 000) (8 500–9 500) (8 700–9 700) (8 400–9 100) (8 400–9 100) (8 300–9 000) (950–1 600) (1 300–1 900) (1 700–2 400) (2 000–2 700) (2 100–2 500) (2 100–2 500) (2 100–2 500) (370–490) (360–410) (320–370) (290–330) (260–300) (260–300) (260–300) (360–580) (470–590) (500–630) (530–670) (570–720) (580–740) (590–750) (350–380) (530–590) (600–680) (530–600) (400–450) (380–430) (340–390) (2 500–3 200) (2 800–3 400) (3 200–3 700) (3 300–3 900) (3 200–3 700) (3 200–3 700) (3 200–3 700) (2 100–2 900) (2 000–2 600) (1 800–2 300) (1 700–2 000) (1 500–1 800) (1 500–1 800) (1 500–1 800)

147 148 148 142 128 125 122 245 275 310 310 271 262 255 59 49 41 34 30 30 29 122 123 118 112 109 109 109 43 65 73 64 47 44 40 218 218 220 213 194 191 187 161 138 119 105 92 90 87

(136–160) (139–157) (139–156) (134–150) (123–133) (120–130) (117–127) (189–309) (226–329) (255–370) (263–361) (249–293) (242–284) (235–275) (51–68) (46–52) (38–43) (32–36) (28–32) (28–32) (27–31) (94–153) (109–137) (104–132) (99–126) (96–122) (97–122) (96–122) (41–45) (62–69) (69–78) (60–68) (44–50) (42–47) (38–43) (192–246) (198–239) (203–237) (197–229) (181–208) (177–204) (174–200) (135–189) (120–158) (106–133) (95–115) (84–100) (82–98) (80–95)

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSEb NUMBER RATEa

CASE DETECTION PERCENT

Global

Africa

The Americas

Eastern Mediterranean

Europe

South-East Asia

Western Pacific

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

5 298 5 718 6 102 6 489 6 890 6 972 7 054 503 577 655 744 847 870 893 727 783 841 892 942 951 961 378 429 480 533 593 605 617 849 863 870 882 899 902 905 1 310 1 435 1 560 1 682 1 790 1 812 1 833 1 532 1 630 1 697 1 756 1 820 1 833 1 846

7 800 8 400 9 000 9 200 8 800 8 700 8 600 1 200 1 600 2 000 2 300 2 300 2 300 2 300 430 380 340 310 280 280 280 460 530 560 600 650 660 670 370 560 640 570 420 400 360 2 900 3 100 3 400 3 600 3 500 3 500 3 400 2 500 2 300 2 000 1 800 1 700 1 600 1 600

(7 200–8 500) (7 900–9 000) (8 500–9 500) (8 700–9 700) (8 400–9 100) (8 400–9 100) (8 300–9 000) (950–1 600) (1 300–1 900) (1 700–2 400) (2 000–2 700) (2 100–2 500) (2 100–2 500) (2 100–2 500) (370–490) (360–410) (320–370) (290–330) (260–300) (260–300) (260–300) (360–580) (470–590) (500–630) (530–670) (570–720) (580–740) (590–750) (350–380) (530–590) (600–680) (530–600) (400–450) (380–430) (340–390) (2 500–3 200) (2 800–3 400) (3 200–3 700) (3 300–3 900) (3 200–3 700) (3 200–3 700) (3 200–3 700) (2 100–2 900) (2 000–2 600) (1 800–2 300) (1 700–2 000) (1 500–1 800) (1 500–1 800) (1 500–1 800)

147 148 148 142 128 125 122 245 275 310 310 271 262 255 59 49 41 34 30 30 29 122 123 118 112 109 109 109 43 65 73 64 47 44 40 218 218 220 213 194 191 187 161 138 119 105 92 90 87

(136–160) (139–157) (139–156) (134–150) (123–133) (120–130) (117–127) (189–309) (226–329) (255–370) (263–361) (249–293) (242–284) (235–275) (51–68) (46–52) (38–43) (32–36) (28–32) (28–32) (27–31) (94–153) (109–137) (104–132) (99–126) (96–122) (97–122) (96–122) (41–45) (62–69) (69–78) (60–68) (44–50) (42–47) (38–43) (192–246) (198–239) (203–237) (197–229) (181–208) (177–204) (174–200) (135–189) (120–158) (106–133) (95–115) (84–100) (82–98) (80–95)

280 620 1 100 1 300 1 100 1 100 1 100 230 460 780 960 880 850 830 17 31 32 34 33 33 31 0.91 2.8 5.9 8.6 11 11 11 1.8 3.4 6.7 17 20 19 19 22 110 210 220 180 170 170 1.8 8.6 17 24 24 24 24

(230–320) 5.2 (4.4–6.1) (560–680) 11 (9.8–12) (960–1 200) 17 (16–19) (1 200–1 400) 20 (18–21) (1 100–1 200) 17 (15–18) (1 000–1 200) 16 (15–17) (1 000–1 200) 15 (14–16) (190–280) 46 (38–56) (410–520) 80 (71–91) (690–880) 119 (105–134) (850–1 100) 130 (115–145) (800–950) 103 (94–113) (780–930) 98 (89–107) (760–910) 93 (85–102) (14–20) 2.3 (2.0–2.7) (28–33) 3.9 (3.6–4.3) (30–35) 3.8 (3.5–4.2) (31–37) 3.8 (3.5–4.1) (30–36) 3.5 (3.1–3.8) (30–36) 3.5 (3.1–3.8) (28–34) 3.3 (3.0–3.6) (0.77–1.1) 0.2 (0.20–0.28) (2.5–3.2) 0.7 (0.59–0.74) (5.3–6.6) 1.2 (1.1–1.4) (7.6–9.6) 1.6 (1.4–1.8) (9.9–12) 1.9 (1.7–2.1) (9.7–12) 1.8 (1.6–1.9) (10–12) 1.8 (1.6–2.0) (1.8–1.9) 0.2 (0.21–0.23) (3.3–3.6) 0.4 (0.38–0.42) (6.2–7.1) 0.8 (0.71–0.82) (15–18) 1.9 (1.7–2.0) (18–21) 2.2 (2.0–2.4) (18–21) 2.1 (2.0–2.3) (17–21) 2.1 (1.9–2.3) (19–26) 1.7 (1.5–2.0) (96–120) 7.5 (6.7–8.4) (190–230) 13 (12–15) (200–240) 13 (12–14) (160–190) 9.9 (9.1–11) (160–180) 9.4 (8.7–10) (160–180) 9.2 (8.5–10) (1.5–2.1) 0.1 (0.10–0.14) (7.4–9.9) 0.5 (0.45–0.61) (15–19) 1 (0.90–1.1) (21–27) 1.4 (1.2–1.5) (22–27) 1.3 (1.2–1.5) (22–27) 1.3 (1.2–1.5) (21–27) 1.3 (1.1–1.5)

3 740 222 3 400 278 3 748 455 5 148 342 5 792 075 5 833 253 5 776 838 418 520 504 377 794 464 1 188 876 1 380 530 1 386 327 1 344 122 231 215 258 232 238 636 230 124 214 930 221 625 219 349 234 620 121 745 141 748 287 178 412 913 415 719 420 769 242 429 289 874 373 094 368 624 328 254 312 588 286 765 1 719 365 1 401 096 1 414 228 1 789 388 2 124 237 2 142 573 2 130 120 894 073 824 954 786 285 1 284 152 1 331 211 1 354 421 1 375 713

71 59 61 79 84 84 82 83 87 121 160 163 159 151 32 33 28 26 23 23 23 62 28 30 54 70 69 68 29 34 43 42 37 35 32 131 98 91 106 119 118 116 58 51 46 73 73 74 75

48 40 42 56 66 67 67 34 32 39 52 60 61 59 54 67 70 75 76 78 79 51 23 25 48 64 63 63 66 51 59 65 77 78 79 60 45 41 50 61 62 62 36 37 39 70 80 83 85

(44–52) (38–43) (39–44) (53–59) (63–69) (64–70) (64–70) (27–44) (27–39) (33–48) (44–61) (56–65) (56–66) (55–64) (47–63) (63–72) (65–75) (71–81) (71–82) (73–84) (74–85) (40–66) (21–26) (22–28) (43–54) (57–72) (56–71) (56–71) (63–69) (49–54) (55–62) (61–70) (73–83) (73–83) (74–84) (53–68) (41–49) (38–45) (46–54) (57–66) (58–67) (58–67) (31–43) (32–42) (35–44) (63–77) (73–87) (76–90) (78–93)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

150

NOTIFIED NEW AND RELAPSE nc ude

fo whi h 2013 he tre tm GLOBAL TUBERCULOSIS ases REPORT

tory s unk wn. years can be downloaded from www.who.int/tb/data Data for all

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE RELAPSE RETREAT UNKNOWN NEW PULM POSITIVE UNKNOWN PULMONARY 30 046 1 175 290 1 541 607 2 413 708 2 655 557 2 630 564 2 563 744 24 064 212 910 368 750 550 004 601 149 606 085 600 355 1 542 138 932 131 294 124 840 116 994 122 010 122 730 1 587 46 851 60 959 113 765 168 627 170 748 173 963 0 104 444 94 442 96 121 91 324 85 551 80 453 2 769 357 882 510 053 857 371 1 047 013 1 067 367 1 065 852 84 314 271 376 109 671 607 630 450 578 803 520 391 22 393 1 811 850 1 615 263 1 722 281 2 002 463 2 037 926 2 084 246 6 137 191 477 222 230 364 785 477 516 467 022 446 213 516 72 312 60 392 56 056 52 265 51 165 50 338 12 394 51 823 34 289 102 274 137 301 135 388 143 869 0 146 592 208 147 157 237 145 140 136 456 129 293 3 241 939 945 741 471 594 185 615 463 598 800 586 455 105 409 701 348 734 447 744 574 778 649 095 728 078 4 237 262 728 399 677 686 525 806 373 817 668 813 960 2 067 72 689 141 255 208 979 247 020 240 839 234 707 723 32 991 32 037 33 285 32 240 34 048 34 496 754 33 382 40 754 64 612 92 070 93 605 90 943 0 29 866 35 081 49 747 40 951 46 012 43 134 656 76 865 120 708 242 332 328 421 333 993 338 303 37 16 935 29 842 87 570 65 671 69 171 72 377 0 5 37 8 111 12 870 12 164 9 689 0 0 0 2 941 561 1 073 977 0 5 37 3 685 2 133 1 502 1 636 0 0 0 12 633 623 702 0 0 0 0 8 008 3 381 83 0 0 0 1 439 1 508 2 878 3 004 0 0 0 34 27 2 707 3 287 734 59 240 115 334 259 937 285 966 284 815 288 119 554 15 133 19 173 60 092 53 967 52 357 60 085 180 1 723 10 834 10 152 10 413 10 087 10 100 0 2 407 5 568 6 495 11 203 11 223 11 208 0 7 927 21 607 22 248 24 304 24 628 25 133 0 5 546 27 095 93 859 130 714 135 650 131 245 0 26 504 31 057 67 091 55 365 50 870 50 348 49 0 236 107 406 355 418 071 413 363 393 437 49 0 68 118 66 449 94 506 74 545 67 960 0 0 14 344 12 481 12 133 11 856 13 879 0 0 0 5 334 8 713 10 102 10 020 0 0 19 127 64 831 60 736 67 986 65 121 0 0 80 444 158 215 208 542 215 554 201 335 0 0 54 074 99 045 33 441 33 320 35 122 783 59 240 351 441 666 292 704 037 698 178 681 556 603 15 133 87 291 126 541 148 473 126 902 128 045 180 1 723 25 178 22 633 22 546 21 943 23 979 0 2 407 5 568 11 829 19 916 21 325 21 228 0 7 927 40 734 87 079 85 040 92 614 90 254 0 5 546 107 539 252 074 339 256 351 204 332 580 0 26 504 85 131 166 136 88 806 84 190 85 470 29 44 229 18 172 28 846 50 116 17 080 0 0 0 2 075 317 18 951 1 785 29 44 56 2 106 885 2 813 49 0 0 0 20 3 079 4 132 84 0 0 173 3 663 18 527 16 560 8 669 0 0 0 202 1 118 3 885 5 261 0 0 0 10 106 4 920 3 775 1 232 57 39 49 58 57 56 55 80 53 62 60 56 56 57 75 66 68 69 69 70 71 11 47 64 53 55 56 55 42 31 38 39 39 38 46 28 41 59 63 64 65 44 43 52 60 52 47 42

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Global YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSE 3 740 222 3 400 278 3 748 455 5 148 342 5 792 075 5 833 253 5 776 838 418 520 504 377 794 464 1 188 876 1 380 530 1 386 327 1 344 122 231 215 258 232 238 636 230 124 214 930 221 625 219 349 234 620 121 745 141 748 287 178 412 913 415 719 420 769 242 429 289 874 373 094 368 624 328 254 312 588 286 765 1 719 365 1 401 096 1 414 228 1 789 388 2 124 237 2 142 573 2 130 120 894 073 824 954 786 285 1 284 152 1 331 211 1 354 421 1 375 713 b

• 71 Africa

82 •

• 83 The Americas

151 •

• 32 Eastern Mediterranean

23 •

• 62 Europe

68 •

• 29 South-East Asia

32 •

• 131 Western Pacific

116 •

• 58

75 •

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

es r whic the years reatme t ist ry is downloaded u known. Data for all can be from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

151

summary by who region

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Global

• 57 Africa

87 •

• 60 The Americas

82 •

• 50 Eastern Mediterranean

78 •

• 79 Europe

88 •

• 67 South-East Asia

66 •

• 33 Western Pacific

89 •

• 80

94 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

1 175 290 1 541 607 2 413 708 2 662 588 2 655 557 2 630 564 212 910 368 750 550 004 607 254 601 149 606 085 138 932 131 294 124 840 110 614 116 994 122 010 46 851 60 959 113 765 168 013 168 627 170 748 104 444 94 442 96 121 100 493 91 324 85 551 357 882 510 053 857 371 1 028 656 1 047 013 1 067 367 314 271 376 109 671 607 647 558 630 450 578 803

1 000 581 1 452 991 2 396 387 2 664 704 2 661 653 2 610 821 177 567 364 804 563 750 605 932 598 985 578 920 128 531 110 642 118 840 122 534 126 450 126 859 46 318 63 749 113 742 167 317 169 872 170 903 33 823 41 480 81 410 105 441 98 689 106 626 318 410 512 286 855 962 1 022 380 1 045 179 1 064 879 295 932 360 030 662 683 641 100 622 478 562 634

85 94 99 100 100 99 83 99 102 100 100 96 93 84 95 111 108 104 99 105 100 100 101 100 32 44 85 105 108 125 89 100 100 99 100 100 94 96 99 99 99 97

40 60 77 80 80 80 46 59 62 70 72 72 37 60 55 53 53 54 60 69 72 74 74 74 58 47 59 56 54 51 9 44 83 85 85 85 67 85 89 90 90 91

17 9 7 7 7 7 14 12 13 10 9 10 14 17 24 23 22 23 19 12 11 14 14 14 10 28 13 13 13 15 23 6 4 3 4 4 13 5 3 3 3 3

3 4 4 4 4 4 6 7 7 5 5 5 3 5 5 5 5 5 2 4 3 3 2 2 6 5 8 8 8 8 1 2 4 4 4 4 2 2 2 2 2 2

1 1 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 2 3 2 1 1 1 1 6 6 7 12 12 8 0 1 2 2 2 2 1 1 1 1 1 1

5 7 5 4 4 4 12 11 9 6 6 6 6 8 7 8 8 7 13 8 8 5 5 5 4 6 7 6 6 6 2 7 6 5 5 5 4 2 1 1 1 1

34 19 4 4 3 4 20 10 7 7 6 6 39 11 9 11 11 9 4 6 5 3 3 4 16 7 5 5 7 12 64 40 1 1 1 1 13 4 3 3 3 2

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Global

• 86 Africa

72 •

• 69 The Americas

68 •

• 72 Eastern Mediterranean

51 •

• 75 Europe

74 •

• 40 South-East Asia

47 •

• 68 Western Pacific

75 •

• 90

86 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

59 240 351 441 666 292 673 854 704 037 698 178 15 133 87 291 126 541 144 320 148 473 126 902 1 723 25 178 22 633 21 492 22 546 21 943 2 407 5 568 11 829 17 964 19 916 21 325 7 927 40 734 87 079 67 190 85 040 92 614 5 546 107 539 252 074 331 424 339 256 351 204 26 504 85 131 166 136 91 464 88 806 84 190

71 395 188 509 546 182 594 019 613 895 601 904 5 756 44 147 114 838 94 342 113 405 85 278 1 104 15 302 18 603 19 158 17 499 20 228 1 860 4 217 12 860 16 332 18 326 22 191 480 10 739 39 497 58 966 58 698 58 831 3 271 59 337 254 378 332 286 338 748 350 251 58 924 54 767 106 006 72 935 67 219 65 125

121 54 82 88 87 86 38 51 91 65 76 67 64 61 82 89 78 92 77 76 109 91 92 104 6 26 45 88 69 64 59 55 101 100 100 100 222 64 64 80 76 77

82 60 51 49 47 48 57 47 35 50 41 53 61 47 38 29 26 27 61 51 60 56 54 52 20 39 32 27 25 24 62 57 49 48 47 45 88 83 81 79 79 80

4 10 19 23 22 24 12 11 27 20 13 15 11 8 16 22 23 24 14 11 15 21 21 22 20 19 18 22 25 23 6 14 22 27 28 30 2 3 6 7 7 6

3 6 7 7 7 7 9 9 11 9 6 7 6 5 6 8 7 8 3 6 5 4 4 4 11 9 11 11 11 10 4 6 7 7 7 7 3 2 3 3 3 3

3 4 4 6 5 5 3 3 3 3 3 3 4 3 2 3 2 3 4 7 4 3 3 3 8 14 13 22 16 15 5 5 5 4 4 4 3 2 3 2 2 3

3 11 12 10 10 10 12 16 13 9 7 9 11 12 15 19 20 20 12 15 10 10 10 10 32 11 14 11 10 10 15 15 15 12 12 11 1 1 2 2 2 2

4 10 6 5 10 7 6 14 12 10 31 12 8 25 21 21 21 18 5 11 6 6 8 8 8 8 10 7 13 18 8 3 2 2 2 3 3 9 6 7 7 6

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

152

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 8.3 34 40 46 11 60 69 74 35 53 56 57 0.88 11 11 14 40 55 57 60 1.6 23 33 39 2.4 20 25 32 463 027 2 080 846 2 526 072 2 808 221 140 713 888 765 1 013 342 1 040 262 84 032 121 421 129 613 132 943 2 582 44 596 48 271 58 498 171 248 212 727 215 256 212 880 31 847 546 350 767 813 909 026 32 605 266 987 351 777 454 612 PATIENTS NOTIFIED (NEW AND RETREAT) 5 554 697 6 210 146 6 246 616 6 170 275 1 255 325 1 475 036 1 460 872 1 412 082 242 605 227 063 233 481 233 228 292 512 421 626 425 821 430 789 433 455 388 990 380 574 351 886 1 947 603 2 332 779 2 358 127 2 331 455 1 383 197 1 364 652 1 387 741 1 410 835 % OF HIVNUMBER OF % OF HIVPOSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT 76 81 82 79 78 81 82 79 10 50 41 63 18 50 60 69 25 58 63 71 50 86 88 89 31 55 71 79 35 46 49 57 29 44 47 55 81 63 69 77 16 44 31 49 16 61 58 62 31 56 58 61 33 41 48 56 25 938 204 802 446 598 518 670 22 211 182 524 438 121 473 214 3 727 12 906 1 705 18 710 0 253 52 243 0 6 575 4 565 17 938 0 581 368 8 0 1 963 1 787 8 557

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Global 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS 103 683 493 186 569 074 549 769 73 332 394 332 465 647 443 558 14 232 19 615 20 497 20 798 330 1 360 1 738 2 036 6 543 12 858 11 790 13 103 7 025 52 519 55 608 56 093 2 221 12 502 13 794 14 181

% OF TESTED TB PATIENTS HIV-POSITIVE 22 24 23 20 52 44 46 43 17 16 16 16 13 3 3.6 3.5 2.8 5.9 5.3 6.2 22 9.6 7.2 6.2 6.8 4.6 3.9 3.1

•8 Africa

46 •

• 11 The Americas

74 •

• 35 Eastern Mediterranean •1 Europe

57 •

14 •

• 40 South-East Asia •2 Western Pacific •2

60 •

32 •

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 72870 118835 133064 153626 1826 2732 1311 2565 14568 11309 13334 29869 1442 2397 2264 1990 34527 89005 89438 92580 661 1073 1204 1352 19846 12319 25513 25270 b

YEAR Global 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

TOTAL CONFIRMED CASES OF MDR-TB 11988 54887 61907 85085 2445 9340 12384 18146 4427 2661 3474 2967 350 873 841 2249 4347 33776 34199 36772 68 3942 6615 19202 351 4295 4394 5749 a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB 2.9 4 4.6 5.7 0.32 0.36 0.19 0.39 11 8.6 10 23 1.3 1.4 1.2 1.1 27 68 67 76 <0.1 0.1 0.1 0.13 2.9 1.7 4.2 4.6 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

310 000 (230 000–380 000) 170 000 (98 000–240 000)

140 000 (91 000–190 000)

Africa

38 000 (14 000–62 000)

24 000 (2 100–46 000)

14 000 (5 600–22 000)

The Americas

7 100 (4 600–9 600)

3 800 (2 400–5 200)

3 200 (1 100–5 300)

Eastern Mediterranean

18 000 (0–42 000)

11 000 (320–36 000)

6 900 (2 400–11 000)

Europe

74 000 (60 000–88 000)

33 000 (20 000–46 000)

41 000 (35 000–46 000)

South-East Asia

90 000 (71 000–110 000)

36 000 (26 000–46 000)

54 000 (37 000–70 000)

Western Pacific

78 000 (60 000–95 000)

59 000 (41 000–76 000)

19 000 (15 000–23 000)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB 24002 3.6 47315 6.7 48124 6.9 60589 8.9 3922 3.1 4294 2.9 3707 2.9 4118 3.2 11003 49 4234 19 4234 19 5565 23 94 0.79 1257 6.3 1466 6.9 1617 7.6 7024 8.1 34212 40 31646 34 38268 42 420 0.17 1264 0.37 1935 0.55 2292 0.69 1539 0.93 2054 2.3 5136 6.1 8729 10

a

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). b BACT+VE = bacteriologically positive cases.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

153

summary by who region

39 •

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

Global

Africa

The Americas

Eastern Mediterranean

Europe

South-East Asia

Western Pacific

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

7 491 12 387 18 415 20 239 19 701 17 046 2 910 3 625 7 635 8 393 8 551 6 032 437 3 464 1 520 1 050 1 103 935 2 010 1 339 1 546 2 316 1 924 1 999 553 201 299 156 164 138 165 2 453 5 064 6 737 6 490 6 581 1 416 1 305 2 351 1 587 1 469 1 361

48 816 115 250 242 356 268 884 265 503 246 030 16 754 29 522 54 066 57 146 59 072 51 158 2 888 18 564 16 410 11 461 12 436 12 125 6 796 8 135 13 558 19 526 19 630 20 119 3 588 4 636 6 170 7 319 6 536 5 997 3 179 30 093 94 638 114 806 114 254 111 501 15 611 24 300 57 514 58 626 53 575 45 130

76 799 172 896 329 720 345 937 349 803 330 650 28 172 47 654 94 388 98 636 105 549 96 915 3 443 21 869 16 671 14 267 15 023 14 784 8 673 9 002 14 609 19 993 20 303 20 411 7 046 8 322 9 151 13 259 13 704 13 038 6 467 45 720 120 560 136 683 136 142 133 040 22 998 40 329 74 341 63 099 59 082 52 462

65 678 156 274 312 526 336 981 333 792 321 408 20 240 34 435 71 072 78 660 81 247 79 312 3 157 19 787 14 369 11 332 11 704 11 278 5 475 6 525 10 798 14 908 14 984 15 178 10 157 9 862 9 150 12 447 13 498 13 394 6 508 47 107 122 256 142 080 141 636 140 542 20 141 38 558 84 881 77 554 70 723 61 704

49 514 121 277 261 233 298 715 300 666 290 214 12 017 17 923 40 974 48 543 49 967 46 870 2 448 15 138 12 340 10 627 11 234 10 716 3 731 4 409 8 729 13 086 13 857 14 006 7 625 8 065 8 704 12 270 12 966 12 301 5 241 38 058 107 228 132 411 135 592 136 569 18 452 37 684 83 258 81 778 77 050 69 752

41 756 82 844 184 836 227 530 229 756 225 684 7 008 8 970 18 931 24 094 24 393 23 665 1 866 9 899 7 801 7 433 7 709 7 596 3 732 2 990 6 581 10 596 11 049 11 333 5 716 4 313 4 443 6 916 7 569 7 624 4 682 25 080 74 084 101 728 106 420 108 866 18 752 31 592 72 996 76 763 72 616 66 600

34 776 75 156 166 858 186 815 183 782 177 736 4 104 5 751 12 143 14 478 14 732 14 186 2 251 9 717 7 951 7 084 7 198 6 989 2 604 3 036 5 595 9 521 9 871 10 059 4 842 3 321 4 089 4 125 4 329 4 113 3 523 16 208 45 533 67 131 72 264 72 554 17 452 37 123 91 547 84 476 75 388 69 835

0 0 42 7 502 579 268 0 0 0 17 516 31 0 0 0 59 56 67 0 0 0 0 0 160 0 0 42 7 423 7 5 0 0 0 0 0 0 0 0 0 3 0 5

7 730 14 749 26 178 28 825 28 133 24 834 3 167 4 315 10 023 10 287 10 632 8 003 431 3 535 1 718 1 137 1 241 1 044 1 881 1 711 2 766 4 377 3 839 3 642 548 290 422 301 257 224 250 3 222 8 591 10 923 10 654 10 535 1 453 1 676 2 658 1 800 1 510 1 386

41 378 94 641 199 700 210 729 209 821 197 407 15 873 29 530 57 115 55 537 57 027 48 828 2 293 15 305 12 405 8 405 8 517 8 615 5 035 6 710 13 529 21 108 21 322 22 258 2 906 3 506 4 667 4 958 4 734 4 258 2 187 21 518 71 923 84 006 85 376 85 726 13 084 18 072 40 061 36 715 32 845 27 722

50 102 110 306 220 530 225 986 224 552 210 454 19 005 35 386 75 056 76 051 76 968 67 255 2 434 14 961 11 563 8 496 8 766 8 561 5 797 5 780 12 098 17 151 17 214 17 341 3 636 4 405 5 101 6 559 6 767 6 336 2 834 25 653 76 779 84 704 84 383 82 947 16 396 24 121 39 933 33 025 30 454 28 014

32 741 74 705 153 503 163 260 162 884 153 967 11 339 20 037 43 213 47 070 47 873 43 481 1 654 10 323 7 891 5 818 5 875 5 710 3 679 3 922 8 386 12 183 12 380 12 564 2 594 2 945 3 161 4 218 4 507 4 387 2 404 19 241 54 000 63 272 64 868 64 170 11 071 18 237 36 852 30 699 27 381 23 655

22 688 49 823 106 029 118 565 119 644 115 659 6 643 9 402 22 855 26 299 26 401 23 378 1 109 7 294 5 933 4 880 4 973 5 023 3 047 2 851 6 245 9 776 10 060 10 187 1 549 1 798 2 242 3 051 3 195 2 986 2 003 13 019 37 709 48 470 50 920 52 118 8 337 15 459 31 045 26 089 24 095 21 967

17 816 33 696 72 022 86 264 87 668 86 968 3 655 4 581 11 047 13 522 13 543 12 683 912 5 038 3 788 3 467 3 690 3 760 2 742 2 039 4 383 7 532 7 770 8 082 1 560 1 243 1 336 2 033 2 292 2 125 1 866 8 142 24 289 34 052 36 755 38 516 7 081 12 653 27 179 25 658 23 618 21 802

16 686 33 829 65 717 75 368 74 004 74 189 1 734 2 578 7 163 8 685 8 843 8 642 1 311 5 894 4 751 4 068 4 243 4 157 1 902 1 893 3 399 7 032 6 432 6 784 3 289 2 490 3 176 3 398 3 693 3 528 1 480 5 468 12 975 20 004 21 593 22 187 6 970 15 506 34 253 32 181 29 200 28 891

0 0 15 2 601 313 172 0 0 0 9 301 37 0 0 0 22 9 30 0 0 0 0 0 20 0 0 15 2 567 3 3 0 0 0 0 0 0 0 0 0 3 0 82

MALE:FEMALE RATIO 1.7 1.8 1.8 1.9 1.9 1.9 1.5 1.4 1.3 1.4 1.4 1.5 1.6 1.6 1.6 1.7 1.8 1.7 1.4 1.4 1.2 1.1 1.2 1.2 2.5 2.3 2.1 2.4 2.3 2.4 2.3 2.1 2.0 2.0 2.0 2.0 1.8 2.0 2.2 2.4 2.4 2.4

154

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

African region Table A4.1 Estimates of the burden of disease caused by TB, 1990–2012 Table A4.2 Incidence, notification and case detection rates, all forms, 1990–2012 Table A4.3 Case notifications, 1990–2012 Table A4.4 Treatment outcomes, new smear-positive cases, 1995–2011 Table A4.5 Treatment outcomes, retreatment cases, 1995–2011 Table A4.6 HIV testing and provision of CPT, ART and IPT, 2005–2012 Table A4.7 Testing for MDR-TB and number of confirmed cases of MDR-TB, 2005–2012 Table A4.8 New smear-positive case notification by age and sex, 1995–2012 Table A4.9 Laboratories, NTP services, drug management and infection control, 2012 Table A4.10 Measured percentage of TB cases with MDR-TB, most recent year available 157 160 163 166 169 172 174 176 179 180

Estimates of mortality, prevalence and incidence Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See ANNEX 1 for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. The main updates implemented in this report are explained in Box 2.1 of Chapter 2. Estimates published in previous global TB control reports should no longer be used.

Data source Data shown in this annex are taken from the WHO global TB database on 1 October 2013. Data shown in the main part of the report were taken from the database in July 2013. As a result, data in this annex may differ slightly from those in the main part of the report. Data for all years can be downloaded from www.who.int/tb/data.

156

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Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATE a

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Algeria

Angola

Benin

Botswana

Burkina Faso

Burundi

Cameroon

Cape Verde

Central African Republic

Chad

Comoros

Congo

Côte d'Ivoire

Democratic Republic of the Congo

Equatorial Guinea

Eritrea

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

26 29 32 34 37 38 38 10 12 14 17 20 20 21 5 6 7 8 10 10 10 1 2 2 2 2 2 2 9 10 12 13 16 16 16 6 6 7 8 9 10 10 12 14 16 18 21 21 22 <1 <1 <1 <1 <1 <1 <1 3 3 4 4 4 4 5 6 7 8 10 12 12 12 <1 <1 <1 <1 <1 <1 <1 2 3 3 4 4 4 4 12 14 16 17 19 19 20 35 42 47 54 62 64 66 <1 <1 <1 <1 <1 <1 <1 3 3 4 5 6 6 6

2.8 2.9 4.4 5 5.3 5.4 5.6 4 6.1 5.8 4.4 6.6 7.6 8.7 0.97 0.95 0.95 0.87 0.88 0.91 0.94 1.3 1.3 0.88 0.66 0.48 0.45 0.42 1.2 1.4 1.5 1.5 1.4 1.4 1.4 1.3 3 2.6 2.2 1.8 1.8 1.8 2.3 5.8 8.1 7.3 6.6 6.3 6.4 0.13 0.14 0.15 0.15 0.13 0.12 0.11 3.6 5.1 5.2 3.9 2.6 2.4 2.2 0.86 1.5 2 2.3 2.3 2.2 2.3 0.043 0.038 0.037 0.045 0.045 0.046 0.045 0.7 0.83 1.1 1.7 1.8 1.8 1.8 4.8 8.2 9 6.6 4.7 4.7 4.4 26 28 29 29 33 35 36 0 0 0 0 0 0 0 0.39 0.33 0.3 0.29 0.28 0.28 0.28

(0.970–5.5) (0.980–5.9) (1.5–8.8) (1.7–9.9) (1.8–11) (1.9–11) (1.9–11) (1.0–8.9) (2.3–12) (2.4–11) (1.7–8.1) (3.0–12) (3.5–13) (3.9–15) (0.390–1.8) (0.390–1.7) (0.400–1.7) (0.380–1.6) (0.390–1.6) (0.400–1.6) (0.420–1.7) (0.095–4.2) (0.076–4.4) (0.046–2.9) (0.190–1.4) (0.120–1.1) (0.120–1.0) (0.110–0.920) (0.470–2.3) (0.540–2.6) (0.580–2.8) (0.610–2.7) (0.630–2.5) (0.620–2.5) (0.600–2.5) (0.570–2.3) (1.2–5.6) (1.1–4.9) (0.960–4.0) (0.840–3.2) (0.840–3.2) (0.790–3.2) (0.980–4.1) (2.2–11) (3.1–16) (3.0–14) (2.8–12) (2.7–11) (2.7–12) (0.034–0.290) (0.055–0.270) (0.057–0.290) (0.057–0.280) (0.051–0.240) (0.049–0.220) (0.047–0.210) (1.3–6.9) (1.9–9.9) (1.9–10) (1.5–7.5) (1.0–4.8) (0.980–4.4) (0.840–4.3) (0.370–1.5) (0.610–2.9) (0.800–3.7) (0.940–4.2) (1.0–4.1) (0.960–3.9) (0.980–4.1) (0.018–0.077) (0.017–0.069) (0.016–0.065) (0.019–0.083) (0.019–0.082) (0.019–0.083) (0.019–0.084) (0.220–1.4) (0.340–1.5) (0.500–2.0) (0.730–3.0) (0.790–3.3) (0.800–3.3) (0.780–3.4) (1.9–9.0) (3.2–16) (3.6–17) (2.8–12) (2.1–8.2) (2.2–8.3) (1.8–8.0) (9.9–49) (11–53) (12–53) (13–52) (15–59) (15–62) (16–64) (0–0.063) (0–0.087) (0–0.086) (0–0.058) (0–0.058) (0–0.053) (0–0.054) (0.260–0.540) (0.220–0.460) (0.200–0.420) (0.190–0.400) (0.190–0.390) (0.190–0.390) (0.190–0.400)

11 9.9 14 15 14 14 15 39 50 42 26 34 38 42 19 16 14 11 9.3 9.3 9.4 97 85 50 35 24 23 21 14 14 13 11 9.2 8.8 8.5 23 48 40 28 20 19 18 19 42 51 40 32 30 29 37 36 34 31 26 25 23 122 156 143 99 59 54 50 14 22 24 23 20 18 18 10 8.3 6.9 7.6 6.6 6.5 6.3 29 31 36 47 44 44 42 40 58 56 38 25 24 22 74 67 61 54 54 54 54 0 0 0 0 0 0 0 12 9.7 7.7 5.9 4.9 4.7 4.6

(3.7–21) (3.4–20) (4.9–28) (5.1–29) (5.0–28) (5.0–29) (5.1–29) (9.9–87) (19–96) (17–77) (11–49) (16–60) (17–66) (19–73) (7.9–36) (6.6–29) (5.8–25) (4.7–19) (4.1–16) (4.1–17) (4.2–17) (6.9–302) (4.8–276) (2.6–165) (10–76) (6.0–56) (5.9–51) (5.5–46) (5.3–26) (5.3–26) (5.0–24) (4.5–20) (4.0–16) (3.9–16) (3.7–15) (10–40) (19–90) (16–73) (12–51) (9.1–35) (8.8–33) (8.0–32) (8.1–34) (16–80) (19–98) (16–75) (14–58) (13–54) (12–54) (9.8–81) (14–68) (13–65) (12–59) (11–49) (10–46) (9.5–42) (45–236) (57–303) (53–277) (37–190) (24–110) (22–99) (19–95) (6.2–26) (8.8–41) (9.7–45) (9.4–42) (8.5–35) (8.0–33) (7.9–33) (4.4–19) (3.6–15) (3.0–12) (3.2–14) (2.8–12) (2.8–12) (2.6–12) (9.4–61) (13–56) (16–63) (21–85) (19–80) (19–78) (18–77) (16–74) (23–109) (22–105) (16–69) (11–43) (11–43) (9.1–41) (28–140) (27–126) (25–112) (24–97) (24–96) (24–97) (24–97) (0–17) (0–20) (0–17) (0–9.7) (0–8.3) (0–7.4) (0–7.4) (7.9–17) (6.4–14) (5.1–11) (3.9–8.3) (3.2–6.9) (3.1–6.6) (3.0–6.5)

29 32 47 53 56 57 59 39 55 59 57 80 90 99 9.7 8.9 9.3 9.2 10 11 11 13 15 13 11 8.1 7.5 6.9 12 12 13 13 14 14 14 15 32 27 22 20 20 20 24 56 80 78 76 68 69 1.2 1.3 1.4 1.4 1.3 1.2 1.2 40 55 54 40 28 26 24 9.4 16 21 24 28 28 28 0.38 0.35 0.34 0.4 0.42 0.45 0.44 7.7 9.6 14 21 23 23 23 48 78 83 64 49 51 45 240 270 290 300 350 360 380 0.38 0.42 0.67 0.81 1.2 1.2 1.2 16 12 7.6 9.1 9.6 9.5 9.3

(13–53) (13–59) (20–85) (23–95) (24–100) (25–100) (25–110) (14–76) (27–93) (29–99) (22–110) (35–140) (42–160) (48–170) (4.7–17) (4.3–15) (4.6–16) (4.6–15) (5.0–17) (5.3–18) (5.6–18) (1.9–33) (2.6–37) (3.4–28) (5.2–19) (3.6–14) (3.4–13) (3.1–12) (5.4–20) (5.7–21) (6.0–22) (6.6–22) (7.1–23) (7.2–23) (6.9–22) (7.8–24) (16–53) (14–45) (12–37) (11–33) (11–33) (10–32) (12–39) (26–98) (36–140) (36–140) (36–130) (32–120) (33–120) (0.440–2.3) (0.640–2.2) (0.670–2.3) (0.680–2.3) (0.630–2.1) (0.610–2.0) (0.590–2.0) (17–72) (23–100) (23–99) (17–71) (13–47) (12–44) (11–40) (4.7–16) (7.7–27) (10–36) (12–41) (14–47) (14–46) (14–46) (0.180–0.660) (0.170–0.600) (0.160–0.580) (0.200–0.680) (0.210–0.710) (0.230–0.740) (0.220–0.740) (2.6–16) (4.6–16) (6.9–24) (9.8–35) (11–39) (11–40) (11–40) (23–80) (38–130) (40–140) (33–100) (25–80) (26–83) (23–75) (110–420) (130–470) (140–480) (150–500) (180–560) (190–590) (200–620) (0.150–0.720) (0.160–0.820) (0.300–1.2) (0.350–1.5) (0.520–2.0) (0.560–2.2) (0.510–2.2) (6.5–29) (4.1–25) (1.9–17) (3.2–18) (3.6–18) (3.6–18) (3.5–18)

112 110 148 156 151 152 152 378 458 421 347 411 447 474 195 149 134 113 107 109 110 915 925 720 579 411 380 343 132 121 108 97 89 88 82 263 510 408 289 219 214 199 195 404 504 432 366 320 319 340 326 311 288 257 248 237 1 360 1 680 1 500 1 000 637 579 520 157 228 252 243 237 229 221 93 75 64 67 62 64 62 323 352 455 580 557 548 530 394 551 513 366 258 262 228 695 654 611 558 555 568 576 101 96 130 135 166 174 164 484 362 194 187 167 160 152

(49–202) (46–203) (64–267) (67–281) (65–273) (65–274) (66–274) (137–738) (225–772) (207–709) (132–663) (181–731) (209–772) (230–804) (93–333) (72–253) (66–225) (56–189) (53–179) (54–182) (55–184) (135–2 410) (166–2 310) (194–1 580) (276–991) (185–727) (172–668) (157–600) (61–230) (57–209) (52–186) (49–161) (46–147) (45–145) (42–136) (140–425) (251–858) (207–675) (151–471) (116–354) (114–345) (106–322) (98–325) (186–704) (227–889) (201–750) (174–629) (152–549) (153–544) (125–660) (161–549) (152–526) (142–485) (129–427) (124–414) (119–395) (583–2 460) (704–3 070) (631–2 720) (438–1 790) (304–1 090) (279–987) (251–884) (78–264) (111–388) (122–429) (119–412) (118–397) (114–383) (109–372) (45–159) (36–129) (30–111) (33–114) (31–103) (32–105) (31–103) (108–654) (168–601) (222–770) (276–994) (265–955) (262–938) (250–913) (193–664) (265–940) (249–870) (187–604) (133–424) (135–430) (115–380) (327–1 200) (318–1 110) (308–1 020) (285–920) (288–908) (297–923) (301–938) (39–193) (35–187) (58–231) (58–243) (75–294) (79–305) (69–299) (198–894) (121–731) (49–436) (67–368) (63–319) (60–307) (56–294)

17 20 28 31 33 34 34 21 27 35 46 59 62 66 6.4 6 6 6 6.5 6.8 7 7.4 14 16 14 9.9 9 8.2 7.6 8.3 8.2 8.4 9 9.1 9 9.1 20 19 15 13 13 13 14 29 49 57 56 51 52 0.62 0.67 0.71 0.73 0.71 0.71 0.71 25 39 39 27 19 18 17 5.6 9 13 15 18 18 19 0.22 0.21 0.21 0.22 0.23 0.24 0.25 4 6.7 11 15 16 16 17 29 54 60 46 36 37 34 110 140 150 180 200 210 210 0.3 0.35 0.52 0.66 0.94 1 1 8 6.7 6.2 5.9 5.8 5.7 5.7

(13–22) (15–26) (20–36) (23–41) (24–44) (25–44) (25–45) (13–31) (22–33) (28–42) (37–54) (50–69) (53–73) (55–77) (5.3–7.6) (4.9–7.1) (4.9–7.1) (5.0–7.2) (5.4–7.8) (5.6–8.1) (5.8–8.3) (2.9–14) (8.8–19) (13–20) (13–15) (8.8–11) (8.1–10) (7.3–9.1) (6.5–8.9) (7.0–9.6) (7.0–9.6) (7.1–9.8) (7.6–10) (7.7–11) (7.6–10) (8.0–10) (18–23) (17–22) (14–17) (12–15) (12–15) (11–14) (11–16) (24–34) (41–59) (47–68) (47–67) (42–61) (43–61) (0.380–0.910) (0.550–0.800) (0.580–0.850) (0.600–0.880) (0.590–0.850) (0.590–0.850) (0.590–0.850) (21–30) (32–47) (32–46) (23–33) (16–22) (15–21) (14–20) (4.7–6.7) (7.4–11) (10–15) (12–18) (15–21) (15–22) (16–22) (0.180–0.270) (0.180–0.250) (0.170–0.250) (0.180–0.260) (0.190–0.270) (0.200–0.290) (0.200–0.290) (2.5–5.9) (5.4–8.0) (9.3–13) (12–18) (13–19) (13–20) (14–20) (25–33) (47–62) (52–68) (40–53) (31–41) (32–42) (30–39) (92–140) (110–160) (130–180) (150–200) (180–230) (180–240) (190–250) (0.260–0.340) (0.310–0.400) (0.460–0.590) (0.580–0.750) (0.830–1.1) (0.890–1.1) (0.900–1.2) (5.3–11) (4.5–9.5) (4.1–8.7) (3.9–8.2) (3.8–8.1) (3.8–8.1) (3.8–8.0)

66 68 87 93 90 90 89 205 226 250 276 304 310 316 128 100 86 74 69 70 70 533 855 918 733 503 455 408 87 82 71 62 58 57 54 162 321 288 198 144 139 130 112 206 310 312 274 243 238 175 168 160 153 147 145 144 861 1 200 1 070 690 433 400 367 95 128 151 150 151 151 151 54 46 39 36 33 34 34 169 245 353 425 391 387 381 238 379 369 267 190 191 172 327 327 327 327 327 327 327 80 80 101 110 135 142 139 243 198 157 121 100 97 93

(48–86) (50–89) (64–114) (68–121) (66–118) (66–117) (65–117) (127–303) (185–272) (204–300) (227–329) (256–355) (261–362) (266–369) (106–152) (82–118) (71–102) (61–88) (57–82) (58–83) (58–83) (212–997) (553–1 220) (736–1 120) (667–802) (449–560) (406–507) (364–454) (73–101) (70–95) (60–83) (53–73) (49–67) (48–66) (46–63) (143–183) (283–362) (254–325) (174–223) (127–163) (122–157) (114–147) (92–133) (170–246) (255–369) (258–372) (226–327) (200–290) (197–283) (108–259) (137–201) (131–193) (125–184) (121–175) (120–173) (119–172) (710–1 030) (988–1 430) (884–1 280) (569–822) (357–515) (330–477) (302–438) (78–112) (106–153) (125–180) (124–178) (125–179) (125–179) (125–180) (44–64) (38–55) (32–46) (30–43) (28–40) (28–41) (28–41) (104–250) (200–294) (298–412) (347–510) (320–470) (317–465) (311–458) (206–272) (329–433) (320–422) (232–306) (165–217) (165–218) (149–198) (262–398) (268–392) (273–385) (279–379) (282–375) (282–375) (282–375) (70–91) (70–90) (88–114) (96–124) (119–153) (124–161) (122–158) (162–341) (132–278) (104–220) (80–169) (67–140) (64–136) (62–131)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

157

African region

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Ethiopia

Gabon

Gambia

Ghana

Guinea

Guinea-Bissau

Kenya

Lesotho

Liberia

Madagascar

Malawi

Mali

Mauritania

Mauritius

Mozambique

Namibia

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

48 57 66 76 87 89 92 <1 1 1 1 2 2 2 <1 1 1 1 2 2 2 15 17 19 21 24 25 25 6 8 9 10 11 11 11 1 1 1 1 2 2 2 23 27 31 36 41 42 43 2 2 2 2 2 2 2 2 2 3 3 4 4 4 12 13 16 18 21 22 22 9 10 11 13 15 15 16 8 9 10 12 14 14 15 2 2 3 3 4 4 4 1 1 1 1 1 1 1 14 16 18 21 24 25 25 1 2 2 2 2 2 2

23 27 27 22 17 16 16 0.39 0.62 0.99 1.1 0.8 0.73 0.72 0.33 0.4 0.44 0.57 0.78 0.84 0.91 5.3 5.4 5.1 4 2.5 2.1 1.7 3.7 4.2 3.9 3.3 2.8 2.6 2.6 0.21 0.26 0.36 0.32 0.43 0.46 0.49 7.1 4.5 5.9 8.1 8.2 8.9 9.5 0.35 0.34 0.29 0.2 0.27 0.34 0.34 0.62 1.1 1.6 1.6 1.9 1.9 1.9 13 11 11 10 10 10 10 3.8 3.7 3.2 2.3 1.8 1.5 1.4 1.2 1.2 1.2 1.3 1.3 1.3 1.3 0.38 0.92 1.5 2.3 3.2 3.4 3.5 0.027 0.013 <0.01 0.013 0.012 0.019 0.012 13 16 14 12 12 13 13 0.074 0.15 0.46 0.46 0.34 0.32 0.32

(14–35) (16–41) (16–41) (13–33) (12–23) (12–21) (12–21) (0.160–0.710) (0.250–1.2) (0.390–1.9) (0.430–2.0) (0.340–1.4) (0.320–1.3) (0.300–1.3) (0.087–0.730) (0.160–0.740) (0.180–0.810) (0.230–1.1) (0.300–1.5) (0.330–1.6) (0.360–1.7) (0.880–14) (1.1–13) (1.2–12) (1.3–8.3) (1.2–4.4) (1.0–3.6) (0.880–2.9) (1.4–7.2) (1.6–8.1) (1.5–7.3) (1.4–6.1) (1.2–5.0) (1.2–4.7) (1.1–4.8) (0.051–0.480) (0.100–0.470) (0.130–0.690) (0.110–0.660) (0.150–0.860) (0.150–0.920) (0.160–0.990) (2.8–13) (2.0–7.9) (2.8–10) (4.3–13) (5.1–12) (5.3–14) (5.4–15) (0.100–0.730) (0.110–0.680) (<0.01–1.1) (0–1.6) (<0.01–1.3) (<0.01–1.4) (<0.01–1.4) (0.130–1.5) (0.400–2.0) (0.580–3.0) (0.630–3.1) (0.790–3.5) (0.810–3.5) (0.830–3.5) (4.9–25) (4.4–21) (4.4–20) (4.3–19) (4.3–18) (4.4–18) (4.3–19) (0.700–9.5) (0.760–8.9) (0.360–9.0) (0.130–7.4) (0.680–3.5) (0.560–3.0) (0.570–2.7) (0.510–2.1) (0.540–2.2) (0.560–2.2) (0.600–2.2) (0.620–2.2) (0.630–2.2) (0.630–2.3) (0.015–1.3) (0.390–1.7) (0.610–2.9) (0.880–4.4) (1.2–6.1) (1.2–6.5) (1.3–6.9) (0.026–0.028) (0.012–0.013) (<0.01–<0.01) (0.013–0.014) (0.011–0.012) (0.019–0.019) (0.012–0.012) (0.360–48) (1.0–52) (0.430–49) (0.360–44) (0.890–38) (0.890–40) (0.980–41) (0.058–0.091) (0.110–0.180) (0.360–0.580) (0.350–0.580) (0.270–0.410) (0.250–0.390) (0.260–0.400)

49 48 41 29 20 18 18 41 57 81 78 51 46 44 36 38 36 39 46 49 51 36 32 27 19 10 8.6 6.9 62 54 44 34 25 24 23 21 22 28 23 27 28 29 30 16 19 23 20 21 22 22 19 16 10 14 17 17 29 51 54 50 48 47 46 114 82 69 56 48 47 46 40 37 28 18 12 9.9 9 15 13 12 11 9.3 9.1 9 19 39 57 73 88 91 93 2.5 1.1 0.68 1.1 0.94 1.5 0.97 98 101 75 58 51 51 53 5.2 8.8 24 23 15 14 14

(29–73) (28–72) (25–63) (17–44) (14–26) (14–24) (13–23) (17–74) (23–107) (32–152) (32–145) (22–93) (20–83) (18–81) (9.4–80) (15–70) (15–66) (16–74) (18–87) (19–92) (20–96) (6.0–93) (6.3–79) (6.3–62) (5.9–39) (5.0–18) (4.2–15) (3.5–11) (23–119) (21–103) (17–83) (14–63) (11–46) (10–42) (9.8–42) (5.0–47) (9.2–41) (11–54) (7.5–46) (9.4–54) (9.5–57) (9.8–59) (12–57) (7.4–29) (9.0–32) (12–36) (12–30) (13–32) (13–34) (6.5–46) (6.5–39) (0.38–58) (0–82) (<0.1–66) (0.20–67) (0.18–68) (6.0–71) (19–97) (20–104) (19–94) (20–88) (20–86) (20–84) (43–220) (33–154) (28–127) (24–103) (21–88) (20–85) (19–84) (7.4–101) (7.6–90) (3.2–80) (1.0–57) (4.5–23) (3.6–19) (3.6–17) (6.4–26) (6.0–24) (5.5–21) (5.0–19) (4.4–16) (4.4–16) (4.3–15) (0.76–65) (17–71) (23–106) (28–140) (33–170) (34–175) (34–181) (2.4–2.6) (1.1–1.2) (0.67–0.70) (1.1–1.1) (0.93–0.95) (1.5–1.6) (0.96–0.98) (2.6–357) (6.4–323) (2.3–270) (1.7–208) (3.7–160) (3.6–161) (3.9–163) (4.1–6.4) (6.9–11) (19–31) (17–28) (12–19) (11–18) (11–18)

200 270 280 250 220 210 210 4 6.4 11 13 10 9.8 9.2 3.2 4 4.6 5.8 7.7 8.2 8.8 47 50 48 40 29 26 23 33 40 38 33 33 32 31 2.4 2.9 3.7 3.8 4.8 5 5.2 64 54 85 120 130 130 130 4.3 5.7 7.2 7.9 8.5 8.9 8.7 6.7 9.4 14 16 20 20 21 110 98 96 95 97 98 99 39 43 41 34 27 24 22 11 12 12 12 13 13 14 5.7 9.7 15 20 27 29 30 0.58 0.57 0.54 0.52 0.5 0.49 0.48 120 140 130 120 130 130 140 11 13 27 23 18 15 16

(140–290) (200–370) (210–370) (190–320) (170–270) (170–260) (170–250) (2.0–6.6) (3.1–11) (5.2–19) (6.0–21) (5.0–17) (4.7–17) (4.3–16) (1.2–6.2) (2.0–6.6) (2.3–7.7) (2.9–9.7) (3.8–13) (4.1–14) (4.4–15) (12–110) (15–110) (17–96) (17–72) (15–48) (13–44) (11–41) (15–58) (19–68) (18–64) (16–57) (16–54) (16–54) (16–53) (0.860–4.8) (1.4–5.0) (1.8–6.2) (1.7–6.6) (2.3–8.1) (2.4–8.5) (2.5–8.9) (32–110) (29–85) (46–140) (65–200) (65–200) (68–210) (71–210) (1.6–8.2) (2.4–10) (2.4–15) (1.3–20) (2.5–18) (2.8–18) (2.7–18) (2.2–14) (4.6–16) (6.7–24) (7.7–26) (9.8–33) (10–34) (10–35) (50–190) (48–170) (47–160) (48–160) (49–160) (50–160) (50–160) (12–80) (16–81) (13–85) (10–72) (14–45) (12–40) (11–36) (6.0–18) (6.5–18) (6.7–19) (7.0–20) (7.3–21) (7.4–21) (7.6–22) (1.1–14) (4.7–17) (7.3–24) (9.9–35) (13–47) (13–50) (14–52) (0.220–1.1) (0.290–0.950) (0.270–0.910) (0.260–0.870) (0.250–0.830) (0.250–0.820) (0.240–0.810) (7.5–370) (17–400) (10–390) (12–350) (25–320) (26–330) (28–340) (5.1–18) (5.7–23) (9.8–53) (6.5–51) (6.3–36) (5.3–31) (6.1–29)

426 480 429 331 250 237 224 419 592 898 908 663 612 563 350 372 373 404 455 472 490 320 301 257 188 121 106 92 556 505 429 350 299 287 274 237 256 290 264 300 306 312 272 196 273 345 306 305 299 267 323 387 409 425 439 424 321 453 482 475 493 494 495 946 729 609 522 461 452 442 412 427 365 262 182 156 140 138 131 117 105 94 94 92 283 417 536 651 756 775 794 55 51 46 43 41 40 39 863 897 701 576 541 544 553 751 770 1 430 1 160 834 699 688

(285–594) (342–642) (318–556) (250–422) (199–307) (191–288) (180–272) (210–699) (289–1 000) (426–1 540) (434–1 550) (323–1 120) (295–1 040) (265–971) (129–679) (186–622) (184–628) (200–677) (227–762) (236–788) (245–819) (81–722) (91–634) (89–510) (81–338) (62–199) (52–179) (41–162) (257–968) (237–873) (205–734) (171–590) (149–500) (143–481) (136–459) (84–469) (120–442) (142–490) (121–462) (144–513) (145–525) (148–537) (138–452) (108–311) (147–437) (183–559) (159–500) (163–491) (164–475) (99–515) (134–593) (129–784) (65–1 060) (126–903) (139–905) (130–888) (102–661) (220–769) (231–822) (234–798) (247–822) (245–827) (244–832) (434–1 650) (356–1 230) (300–1 020) (261–870) (233–767) (228–749) (222–735) (131–849) (165–810) (118–749) (77–556) (95–298) (80–256) (72–229) (75–221) (73–206) (65–184) (58–164) (52–149) (52–148) (51–146) (53–703) (202–707) (268–895) (315–1 110) (357–1 300) (364–1 340) (373–1 370) (21–105) (25–85) (23–76) (22–72) (20–68) (20–66) (20–65) (56–2 730) (104–2 520) (56–2 130) (59–1 660) (105–1 320) (106–1 330) (111–1 340) (358–1 280) (344–1 360) (517–2 790) (321–2 510) (291–1 660) (241–1 390) (271–1 300)

180 240 280 260 230 230 230 2.1 3.4 6.5 8.1 7.4 7.2 7 1.7 2.2 2.8 3.6 4.6 4.8 5.1 23 28 29 25 21 20 18 15 20 20 20 20 20 20 1.6 2 2.4 3 3.7 3.9 4 33 46 89 130 120 120 120 2.9 5.7 10 12 13 13 13 4.2 4.6 7 8.7 12 12 13 45 45 46 48 51 52 52 31 46 53 46 33 30 26 6 7.2 7.9 8.3 8.8 8.9 9 4.6 5.9 7.5 9.6 12 13 13 0.29 0.29 0.29 0.28 0.27 0.26 0.26 54 76 94 110 130 130 140 5.4 9.5 27 28 19 16 15

(100–270) (140–360) (170–420) (150–390) (170–310) (170–300) (170–290) (1.7–2.5) (2.8–4.1) (5.3–7.7) (6.7–9.6) (6.1–8.8) (5.9–8.6) (5.8–8.3) (1.0–2.5) (1.8–2.6) (2.3–3.3) (2.9–4.3) (3.8–5.5) (4.0–5.7) (4.2–6.0) (10–40) (16–44) (18–41) (19–33) (18–24) (17–22) (16–21) (12–18) (16–23) (17–24) (17–24) (17–24) (17–24) (17–24) (1.1–2.2) (1.6–2.4) (2.0–2.9) (2.5–3.6) (3.0–4.4) (3.2–4.6) (3.3–4.8) (28–37) (43–50) (84–95) (120–140) (120–130) (120–130) (110–120) (2.2–3.8) (5.0–6.4) (9.0–12) (10–14) (11–14) (11–15) (11–15) (2.6–6.2) (3.7–5.5) (5.7–8.4) (7.1–10) (9.6–14) (10–15) (11–15) (37–54) (37–54) (38–55) (39–57) (42–61) (43–62) (43–62) (22–41) (38–55) (44–63) (38–54) (31–35) (27–32) (24–28) (5.8–6.3) (6.9–7.6) (7.6–8.3) (7.9–8.7) (8.4–9.2) (8.5–9.3) (8.5–9.4) (2.8–6.8) (4.8–7.0) (6.1–9.0) (7.9–12) (10–15) (10–15) (11–16) (0.180–0.430) (0.240–0.350) (0.240–0.350) (0.230–0.330) (0.220–0.320) (0.220–0.310) (0.210–0.310) (8.5–140) (24–160) (41–170) (63–170) (90–180) (93–180) (96–190) (4.3–6.6) (7.5–12) (21–33) (22–35) (15–23) (13–20) (12–18)

367 419 421 342 269 258 247 221 315 527 586 475 450 428 185 204 225 248 273 279 284 155 167 152 119 86 79 72 248 249 234 211 188 183 178 158 174 192 211 233 238 242 139 169 286 359 298 288 272 184 323 553 639 633 632 630 199 219 242 266 293 299 304 391 335 293 262 242 238 234 326 462 467 354 219 191 163 76 80 77 69 63 62 60 228 251 277 305 337 344 350 28 26 24 23 22 21 21 401 478 513 524 544 548 552 379 575 1 410 1 390 867 723 655

(218–553) (249–633) (251–636) (203–516) (191–359) (191–335) (183–321) (182–263) (260–375) (435–627) (484–698) (392–566) (372–536) (354–510) (114–273) (167–245) (184–271) (203–298) (226–325) (230–331) (234–337) (69–275) (93–263) (97–220) (88–154) (75–97) (69–89) (63–82) (204–295) (205–297) (193–279) (173–251) (155–224) (151–219) (146–213) (108–217) (142–209) (157–230) (173–254) (192–278) (196–283) (200–289) (121–159) (155–184) (267–305) (339–380) (286–311) (276–300) (261–283) (135–240) (283–367) (484–626) (535–752) (553–719) (551–717) (550–716) (123–293) (179–263) (197–290) (218–320) (242–349) (247–356) (251–362) (322–466) (276–400) (241–349) (216–313) (199–288) (196–284) (193–280) (230–438) (383–548) (387–554) (292–421) (203–236) (177–206) (151–176) (72–80) (76–84) (74–81) (66–73) (60–66) (59–65) (57–63) (140–336) (205–302) (226–333) (250–367) (277–402) (283–410) (288–418) (17–41) (21–31) (20–29) (19–28) (18–26) (18–25) (17–25) (62–1 050) (153–985) (227–914) (298–811) (377–741) (380–747) (383–753) (300–468) (456–709) (1 110–1 730) (1 100–1 720) (686–1 070) (573–891) (524–800)

a

Rates are per 100 000 population.

158

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Niger

Nigeria

Rwanda

Sao Tome and Principe

Senegal

Seychelles

Sierra Leone

South Africa

Swaziland

Togo

Uganda

United Republic of Tanzania

Zambia

Zimbabwe

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

8 9 11 13 16 17 17 96 108 123 140 160 164 169 7 6 8 9 11 11 11 <1 <1 <1 <1 <1 <1 <1 8 9 10 11 13 13 14 <1 <1 <1 <1 <1 <1 <1 4 4 4 5 6 6 6 37 41 45 48 51 52 52 <1 <1 1 1 1 1 1 4 4 5 6 6 6 7 18 21 24 29 34 35 36 25 30 34 39 45 46 48 8 9 10 11 13 14 14 10 12 13 13 13 13 14

7.7 6.8 5 3.7 2.9 2.8 2.8 34 40 47 46 34 30 27 2.7 4.4 4.1 2 1.3 1.2 1.2 0.031 0.034 0.018 0.012 0.024 0.027 0.03 1.8 2.2 2.6 2.5 2.5 2.6 2.7 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 2.4 2 2.4 5.9 8.2 8.3 8.5 16 15 20 25 26 28 31 0.31 0.27 0.37 0.32 0.46 0.67 0.78 0.23 0.37 0.59 0.58 0.54 0.56 0.58 8.7 8.3 8.5 7.6 5.5 5.1 4.7 9.9 6.4 5.8 5.7 6.2 6.1 6.1 4.9 3.9 3.1 2.2 3.2 3.4 3.9 3.5 1.9 2.1 3.6 4 4.6 4.6

(2.9–15) (2.5–13) (2.0–9.5) (1.5–6.8) (1.3–5.2) (1.2–5.0) (1.2–5.1) (0.019–180) (0.250–170) (0.077–230) (0.084–220) (3.1–100) (2.0–93) (1.6–86) (1.1–5.1) (1.7–8.4) (1.6–7.7) (0.880–3.7) (0.610–2.3) (0.580–2.1) (0.530–2.1) (<0.01–0.070) (0.013–0.064) (<0.01–0.032) (<0.01–0.023) (0.010–0.045) (0.011–0.050) (0.012–0.055) (0.800–3.3) (0.980–4.0) (1.1–4.7) (1.1–4.4) (1.1–4.5) (1.2–4.7) (1.2–4.8) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.730–5.2) (0.730–3.9) (0.860–4.8) (2.2–11) (3.1–16) (3.1–16) (3.2–16) (4.2–34) (5.6–28) (4.0–48) (2.0–75) (2.2–80) (2.9–83) (3.7–86) (0.051–0.800) (0.065–0.620) (<0.01–1.4) (<0.01–2.0) (<0.01–2.3) (0.015–2.5) (0.031–2.7) (0.100–0.410) (0.160–0.670) (0.250–1.1) (0.250–1.0) (0.230–0.970) (0.240–1.0) (0.250–1.0) (<0.01–48) (<0.01–46) (0.055–37) (0.660–23) (1.0–14) (0.960–13) (0.820–12) (3.8–19) (2.2–13) (1.9–12) (2.7–9.8) (3.3–10) (3.3–9.8) (3.2–9.9) (1.5–10) (1.1–8.3) (0.940–6.5) (0.450–5.4) (0.970–6.8) (1.1–7.0) (1.4–7.7) (0.068–13) (0–15) (0–16) (<0.01–18) (0.037–17) (0.140–17) (0.160–16)

99 74 46 28 18 17 16 35 37 38 33 22 18 16 37 78 49 22 12 11 10 27 26 13 7.6 14 15 16 24 26 26 22 20 20 20 2 2 2 2.5 1.8 1.8 1.8 61 51 59 116 142 142 143 42 35 44 51 51 55 59 36 28 34 29 39 56 63 6.1 8.7 12 10 8.5 8.6 8.7 50 40 35 26 16 15 13 39 21 17 15 14 13 13 63 44 31 19 24 25 28 33 16 17 28 31 35 33

(37–191) (28–143) (18–86) (12–51) (8.0–33) (7.4–30) (6.8–30) (<0.1–183) (0.23–161) (<0.1–185) (<0.1–159) (2.0–64) (1.2–57) (0.92–51) (15–70) (30–149) (19–91) (9.3–39) (5.7–21) (5.2–19) (4.6–18) (7.1–59) (10–49) (5.3–23) (2.8–15) (5.7–25) (6.1–27) (6.4–29) (11–44) (11–46) (12–48) (9.6–39) (8.7–35) (8.7–35) (8.8–35) (1.9–2.0) (1.9–2.0) (1.9–2.0) (2.4–2.7) (1.8–1.9) (1.8–1.9) (1.8–1.9) (18–128) (18–99) (21–116) (43–223) (54–273) (53–274) (53–275) (11–93) (14–68) (8.9–107) (4.1–156) (4.3–155) (5.6–159) (7.0–164) (5.9–93) (6.8–64) (0.74–129) (0–177) (<0.1–196) (1.3–208) (2.5–219) (2.7–11) (3.8–16) (5.0–22) (4.5–19) (3.7–15) (3.8–15) (3.8–15) (<0.1–273) (<0.1–223) (0.23–151) (2.3–79) (3.0–40) (2.7–36) (2.3–33) (15–74) (7.3–43) (5.6–35) (6.9–25) (7.4–22) (7.1–21) (6.8–21) (19–132) (13–93) (9.4–64) (3.9–47) (7.4–51) (8.0–52) (9.8–55) (0.65–128) (0–125) (0–129) (<0.1–146) (0.28–129) (1.1–125) (1.2–117)

65 57 44 34 30 29 28 290 340 400 420 330 300 270 26 37 35 21 15 14 13 0.3 0.32 0.22 0.2 0.26 0.28 0.3 19 23 27 26 28 29 30 0.035 0.059 0.045 0.053 0.048 0.039 0.036 21 18 22 53 74 76 78 170 180 250 360 410 430 450 3.4 3.4 6.1 7.4 9 11 11 2.7 4 5.6 5.9 6.2 6.6 6.9 86 89 92 88 70 68 64 94 76 80 82 86 85 84 52 53 53 47 51 52 55 34 34 49 60 57 61 59

(30–110) (26–99) (21–75) (17–57) (15–50) (14–49) (14–48) (0.550–1 400) (4.9–1 300) (2.6–1 700) (4.2–1 700) (62–830) (49–760) (43–710) (13–44) (17–64) (17–59) (11–35) (7.9–24) (7.2–22) (7.0–21) (0.110–0.590) (0.160–0.530) (0.093–0.410) (0.070–0.390) (0.130–0.450) (0.140–0.470) (0.150–0.500) (9.4–31) (12–39) (14–45) (13–44) (14–47) (14–49) (15–50) (<0.01–0.091) (0.028–0.100) (0.021–0.080) (0.026–0.091) (0.023–0.082) (0.016–0.071) (0.013–0.072) (7.8–39) (8.3–31) (10–39) (25–90) (36–130) (37–130) (37–130) (64–340) (81–310) (100–480) (110–750) (140–840) (150–860) (160–880) (1.0–7.3) (1.4–6.3) (1.5–14) (1.1–19) (1.5–23) (2.6–24) (2.9–25) (1.3–4.6) (2.0–6.6) (2.7–9.4) (2.9–10) (3.0–11) (3.2–11) (3.4–12) (0.490–370) (0.760–370) (6.1–290) (22–200) (27–130) (26–130) (24–120) (47–160) (37–130) (38–140) (43–130) (46–140) (45–140) (45–140) (24–91) (26–90) (26–89) (20–83) (25–87) (25–87) (28–90) (2.4–110) (0.860–130) (3.9–150) (7.0–170) (9.1–150) (12–150) (13–140)

839 620 396 261 187 176 166 302 311 326 298 210 181 161 356 655 417 228 136 121 114 258 244 159 128 149 154 159 249 269 273 234 217 217 219 50 79 57 61 52 42 39 507 454 537 1 030 1 290 1 290 1 300 475 427 568 748 803 831 857 397 357 573 666 751 870 907 71 92 114 107 99 102 104 492 429 380 305 207 192 175 368 254 234 211 190 183 176 665 605 524 406 387 379 388 323 295 389 473 438 458 433

(388–1 460) (283–1 080) (189–678) (130–436) (94–312) (88–294) (83–277) (0.58–1 440) (4.5–1 230) (2.1–1 400) (3.0–1 220) (39–521) (30–464) (25–420) (173–603) (305–1 130) (205–701) (120–370) (73–219) (65–196) (61–183) (96–499) (122–408) (67–291) (46–253) (72–252) (76–258) (80–264) (125–414) (135–448) (137–453) (116–393) (106–366) (106–366) (108–368) (7.7–131) (37–135) (26–100) (29–104) (25–90) (17–78) (14–78) (194–968) (211–788) (245–940) (491–1 750) (624–2 180) (625–2 200) (626–2 220) (173–925) (195–747) (225–1 070) (234–1 560) (266–1 630) (289–1 650) (305–1 680) (116–847) (149–653) (145–1 290) (104–1 730) (130–1 900) (213–1 970) (232–2 030) (34–122) (46–155) (56–193) (52–181) (47–169) (49–174) (51–176) (2.8–2 140) (3.6–1 800) (25–1 200) (76–689) (80–392) (74–366) (67–334) (185–611) (123–430) (113–399) (111–341) (102–306) (97–295) (95–283) (308–1 160) (299–1 020) (256–885) (177–727) (186–659) (185–640) (197–642) (23–1 000) (7.4–1 090) (31–1 180) (55–1 320) (70–1 140) (93–1 110) (92–1 030)

28 25 21 19 18 18 18 120 150 210 240 210 190 180 21 29 27 17 11 11 9.8 0.16 0.16 0.16 0.16 0.17 0.17 0.17 10 13 15 16 18 18 19 0.03 0.03 0.029 0.029 0.028 0.028 0.027 8.4 8.3 11 26 38 39 40 110 130 260 450 500 520 530 2.3 3.2 8.5 13 15 16 17 1.8 2.5 3.5 4.2 4.6 4.7 4.9 110 110 100 87 71 68 65 58 68 80 83 80 78 79 56 70 72 65 61 61 60 31 56 91 100 83 81 77

(23–33) (20–29) (17–25) (15–22) (15–21) (15–21) (15–21) (1.3–500) (8.0–490) (15–660) (33–660) (100–360) (91–340) (85–310) (19–23) (26–32) (24–30) (15–19) (10–13) (9.4–12) (8.8–11) (0.098–0.230) (0.130–0.190) (0.130–0.190) (0.140–0.190) (0.140–0.200) (0.140–0.210) (0.140–0.210) (8.5–12) (11–16) (13–18) (13–19) (15–21) (15–22) (16–22) (0.019–0.044) (0.025–0.036) (0.024–0.035) (0.024–0.035) (0.023–0.033) (0.023–0.033) (0.023–0.033) (5.2–12) (6.4–11) (8.1–14) (21–31) (31–45) (32–47) (32–49) (76–150) (110–160) (210–310) (360–540) (420–600) (430–610) (430–630) (1.4–3.4) (2.7–3.9) (7.0–10) (10–15) (13–18) (13–19) (14–20) (1.5–2.1) (2.0–3.0) (2.9–4.2) (3.5–5.1) (3.8–5.5) (3.9–5.6) (4.0–5.8) (57–180) (62–180) (63–150) (63–120) (57–86) (55–82) (53–79) (49–67) (58–78) (70–91) (76–89) (75–85) (74–83) (74–84) (49–63) (64–76) (67–77) (59–71) (55–67) (55–67) (54–66) (17–50) (39–77) (72–110) (81–130) (64–100) (62–100) (60–97)

358 270 191 142 113 108 104 128 139 172 175 133 118 108 290 513 325 181 106 94 86 135 124 114 105 96 94 93 138 153 155 142 137 136 137 43 40 37 33 31 30 30 207 212 264 503 660 668 674 301 317 576 925 981 993 1 000 267 337 803 1 150 1 290 1 320 1 350 47 58 72 77 73 73 73 624 542 427 304 209 193 179 226 226 236 213 177 169 165 710 788 713 566 462 444 427 296 483 726 799 633 603 562

(295–426) (223–321) (157–227) (118–170) (94–135) (90–129) (86–124) (1.3–526) (7.4–456) (12–536) (23–476) (64–225) (55–204) (50–186) (259–323) (458–571) (290–362) (162–202) (94–118) (84–105) (77–96) (83–199) (102–149) (93–137) (88–123) (79–115) (78–113) (76–111) (114–164) (126–183) (128–184) (117–169) (113–163) (112–162) (113–163) (27–64) (33–48) (30–44) (27–40) (25–37) (25–36) (24–35) (128–305) (162–269) (196–341) (410–605) (540–791) (542–807) (540–821) (206–413) (259–381) (471–691) (756–1 110) (809–1 170) (819–1 180) (827–1 190) (165–394) (275–405) (657–964) (938–1 380) (1 060–1 530) (1 090–1 570) (1 110–1 610) (39–56) (48–69) (59–86) (63–91) (60–87) (60–87) (60–87) (328–1 010) (297–860) (259–636) (220–402) (169–253) (156–234) (145–216) (193–261) (193–261) (207–268) (197–229) (166–189) (159–180) (154–175) (624–801) (719–861) (661–767) (519–615) (418–509) (401–489) (385–470) (159–476) (335–658) (573–897) (634–984) (489–795) (466–757) (434–706)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

159

African region

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSE NUMBER RATEa

b

CASE DETECTION PERCENT

Algeria

Angola

Benin

Botswana

Burkina Faso

Burundi

Cameroon

Cape Verde

Central African Republic

Chad

Comoros

Congo

Côte d'Ivoire

Democratic Republic of the Congo

Equatorial Guinea

Eritrea

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

26 29 32 34 37 38 38 10 12 14 17 20 20 21 5 6 7 8 10 10 10 1 2 2 2 2 2 2 9 10 12 13 16 16 16 6 6 7 8 9 10 10 12 14 16 18 21 21 22 <1 <1 <1 <1 <1 <1 <1 3 3 4 4 4 4 5 6 7 8 10 12 12 12 <1 <1 <1 <1 <1 <1 <1 2 3 3 4 4 4 4 12 14 16 17 19 19 20 35 42 47 54 62 64 66 <1 <1 <1 <1 <1 <1 <1 3 3 4 5 6 6 6

17 20 28 31 33 34 34 21 27 35 46 59 62 66 6.4 6 6 6 6.5 6.8 7 7.4 14 16 14 9.9 9 8.2 7.6 8.3 8.2 8.4 9 9.1 9 9.1 20 19 15 13 13 13 14 29 49 57 56 51 52 0.62 0.67 0.71 0.73 0.71 0.71 0.71 25 39 39 27 19 18 17 5.6 9 13 15 18 18 19 0.22 0.21 0.21 0.22 0.23 0.24 0.25 4 6.7 11 15 16 16 17 29 54 60 46 36 37 34 110 140 150 180 200 210 210 0.3 0.35 0.52 0.66 0.94 1 1 8 6.7 6.2 5.9 5.8 5.7 5.7

(13–22) (15–26) (20–36) (23–41) (24–44) (25–44) (25–45) (13–31) (22–33) (28–42) (37–54) (50–69) (53–73) (55–77) (5.3–7.6) (4.9–7.1) (4.9–7.1) (5.0–7.2) (5.4–7.8) (5.6–8.1) (5.8–8.3) (2.9–14) (8.8–19) (13–20) (13–15) (8.8–11) (8.1–10) (7.3–9.1) (6.5–8.9) (7.0–9.6) (7.0–9.6) (7.1–9.8) (7.6–10) (7.7–11) (7.6–10) (8.0–10) (18–23) (17–22) (14–17) (12–15) (12–15) (11–14) (11–16) (24–34) (41–59) (47–68) (47–67) (42–61) (43–61) (0.380–0.910) (0.550–0.800) (0.580–0.850) (0.600–0.880) (0.590–0.850) (0.590–0.850) (0.590–0.850) (21–30) (32–47) (32–46) (23–33) (16–22) (15–21) (14–20) (4.7–6.7) (7.4–11) (10–15) (12–18) (15–21) (15–22) (16–22) (0.180–0.270) (0.180–0.250) (0.170–0.250) (0.180–0.260) (0.190–0.270) (0.200–0.290) (0.200–0.290) (2.5–5.9) (5.4–8.0) (9.3–13) (12–18) (13–19) (13–20) (14–20) (25–33) (47–62) (52–68) (40–53) (31–41) (32–42) (30–39) (92–140) (110–160) (130–180) (150–200) (180–230) (180–240) (190–250) (0.260–0.340) (0.310–0.400) (0.460–0.590) (0.580–0.750) (0.830–1.1) (0.890–1.1) (0.900–1.2) (5.3–11) (4.5–9.5) (4.1–8.7) (3.9–8.2) (3.8–8.1) (3.8–8.1) (3.8–8.0)

66 68 87 93 90 90 89 205 226 250 276 304 310 316 128 100 86 74 69 70 70 533 855 918 733 503 455 408 87 82 71 62 58 57 54 162 321 288 198 144 139 130 112 206 310 312 274 243 238 175 168 160 153 147 145 144 861 1 200 1 070 690 433 400 367 95 128 151 150 151 151 151 54 46 39 36 33 34 34 169 245 353 425 391 387 381 238 379 369 267 190 191 172 327 327 327 327 327 327 327 80 80 101 110 135 142 139 243 198 157 121 100 97 93

(48–86) (50–89) (64–114) (68–121) (66–118) (66–117) (65–117) (127–303) (185–272) (204–300) (227–329) (256–355) (261–362) (266–369) (106–152) (82–118) (71–102) (61–88) (57–82) (58–83) (58–83) (212–997) (553–1 220) (736–1 120) (667–802) (449–560) (406–507) (364–454) (73–101) (70–95) (60–83) (53–73) (49–67) (48–66) (46–63) (143–183) (283–362) (254–325) (174–223) (127–163) (122–157) (114–147) (92–133) (170–246) (255–369) (258–372) (226–327) (200–290) (197–283) (108–259) (137–201) (131–193) (125–184) (121–175) (120–173) (119–172) (710–1 030) (988–1 430) (884–1 280) (569–822) (357–515) (330–477) (302–438) (78–112) (106–153) (125–180) (124–178) (125–179) (125–179) (125–180) (44–64) (38–55) (32–46) (30–43) (28–40) (28–41) (28–41) (104–250) (200–294) (298–412) (347–510) (320–470) (317–465) (311–458) (206–272) (329–433) (320–422) (232–306) (165–217) (165–218) (149–198) (262–398) (268–392) (273–385) (279–379) (282–375) (282–375) (282–375) (70–91) (70–90) (88–114) (96–124) (119–153) (124–161) (122–158) (162–341) (132–278) (104–220) (80–169) (67–140) (64–136) (62–131)

<0.01 <0.01 0.025 0.057 0.08 0.085 0.086 0.51 1.3 2.5 4 5.3 5.3 5.5 2.1 1.9 1.5 1.2 0.99 1 1 1.5 7.2 11 9.3 6.3 5.7 5.1 2.9 3.3 2.8 2.3 1.8 1.7 1.6 1.6 6.7 7.4 4.8 3 2.8 2.5 0.71 5.5 17 22 21 19 19 0.039 0.057 0.071 0.074 0.067 0.068 0.071 9.8 18 18 11 6.3 5.8 5.3 0.69 1.8 3.1 3.7 3.6 3.8 4.1

(<0.01–<0.01) (<0.01–<0.01) (0.018–0.032) (0.042–0.074) (0.059–0.10) (0.062–0.11) (0.063–0.11) (0.31–0.75) (1.1–1.5) (2.0–3.0) (3.3–4.8) (4.5–6.2) (4.5–6.2) (4.7–6.5) (1.7–2.4) (1.5–2.2) (1.3–1.8) (1.0–1.5) (0.82–1.2) (0.84–1.2) (0.84–1.2) (0.58–2.7) (4.7–10) (9.0–14) (8.4–10) (5.6–7.0) (5.1–6.3) (4.5–5.6) (2.5–3.4) (2.8–3.8) (2.4–3.3) (2.0–2.7) (1.5–2.1) (1.4–1.9) (1.3–1.8) (1.4–1.8) (5.9–7.5) (6.5–8.3) (4.3–5.5) (2.7–3.4) (2.4–3.1) (2.2–2.8) (0.58–0.84) (4.6–6.6) (14–20) (18–26) (18–25) (16–23) (16–23) (0.024–0.058) (0.046–0.069) (0.057–0.085) (0.060–0.089) (0.055–0.081) (0.055–0.081) (0.058–0.086) (8.1–12) (15–21) (15–21) (9.4–14) (5.2–7.5) (4.8–6.9) (4.4–6.4) (0.57–0.83) (1.5–2.2) (2.5–3.6) (3.1–4.4) (2.9–4.2) (3.2–4.6) (3.4–4.8)

<0.1 <0.1 <0.1 0.2 0.2 0.2 0.2 4.9 11 18 24 27 26 27 41 31 22 15 10 10 10 105 456 638 494 321 285 253 33 32 25 17 11 10 9.5 28 107 110 62 33 29 25 5.8 40 105 121 103 91 88 11 14 16 15 14 14 14 336 549 492 287 145 131 118 12 26 37 37 30 32 33

(0–<0.1) (<0.1–<0.1) (<0.1–0.10) (0.12–0.22) (0.16–0.28) (0.16–0.29) (0.16–0.29) (3.0–7.2) (8.7–13) (14–21) (20–29) (23–32) (22–31) (22–31) (34–49) (26–37) (18–26) (12–18) (8.6–12) (8.6–12) (8.3–12) (42–196) (295–651) (511–777) (449–541) (286–357) (254–317) (226–281) (28–38) (27–37) (21–29) (15–20) (9.7–13) (8.9–12) (8.0–11) (25–31) (94–121) (97–124) (55–70) (29–37) (26–33) (22–28) (4.8–7.0) (33–47) (87–126) (100–145) (85–123) (75–109) (73–104) (6.8–16) (12–17) (13–19) (12–19) (11–17) (11–17) (12–17) (277–400) (453–654) (406–587) (237–342) (119–172) (108–156) (97–141) (9.7–14) (22–31) (31–44) (31–44) (25–36) (26–38) (27–39)

11 607 13 507 18 572 21 336 22 336 21 429 21 880 10 271 5 143 16 062 37 175 44 655 47 240 51 819 2 074 2 400 2 697 3 270 3 756 4 212 3 966 2 938 5 665 9 292 10 058 7 013 6 603 6 161 1 497 2 572 2 331 3 478 4 800 5 286 5 210 4 575 3 326 6 421 6 585 7 611 6 742 6 921 5 892 3 292 5 251 21 499 24 073 24 533 24 802 221 303 292 356 380 420 2 124 3 339 3 210 6 643 5 611 8 084 2 591 3 186 6 311 9 452 10 505 10 585 140 123 120 111 117 120 591 3 615 9 239 9 853 10 150 10 975 11 303 7 841 11 988 15 094 19 681 22 708 22 476 23 762 21 131 42 819 61 024 97 075 114 170 110 132 108 984 260 306

44 46 59 63 60 57 57 99 42 115 225 228 234 249 41 40 39 40 39 43 39 212 358 529 536 356 332 307 17 25 20 26 31 33 32 82 54 96 85 82 71 70 49 24 33 119 117 116 114 63 76 61 73 77 85 73 102 81 153 126 179 44 46 63 81 87 85 34 26 23 18 17 17 25 133 296 278 247 260 261 65 84 94 113 120 116 120 61 102 130 180 184 172 166 70 69

67 68 67 68 67 63 64 48 19 46 82 75 76 79 32 40 45 54 57 62 57 40 42 58 73 71 73 75 20 31 28 41 54 58 58 50 17 33 43 57 51 54 44 11 11 38 43 48 48 36 45 40 50 53 59 8.5 8.5 12 35 32 49 46 36 42 53 58 56 63 58 58 51 49 49 15 54 84 66 63 67 68 27 22 25 42 63 61 69 19 31 40 55 56 53 51 87 87

(52–92) (52–92) (52–92) (52–92) (51–91) (48–87) (49–87) (33–78) (16–23) (38–56) (68–99) (64–89) (65–90) (67–94) (27–39) (34–49) (38–55) (46–66) (48–69) (52–75) (48–68) (21–100) (29–65) (47–72) (67–80) (64–79) (66–82) (68–84) (17–23) (27–37) (24–33) (36–49) (46–63) (50–68) (50–69) (45–57) (15–19) (30–38) (38–49) (51–65) (45–58) (48–62) (37–53) (9.6–14) (8.9–13) (32–46) (36–52) (40–58) (40–58) (24–58) (38–55) (33–49) (42–60) (45–65) (49–72) (7.1–10) (7.1–10) (9.9–14) (30–43) (27–38) (41–59) (39–56) (30–43) (35–51) (45–65) (48–70) (47–68) (53–76) (48–70) (49–71) (43–62) (41–59) (41–59) (9.9–24) (45–66) (72–99) (55–80) (53–77) (56–82) (57–84) (24–31) (19–26) (22–29) (37–49) (55–73) (53–70) (61–81) (15–23) (26–38) (34–48) (47–64) (49–65) (46–61) (44–59) (77–99) (77–99)

<0.01 <0.01 0.01 0.94 2.1 3.2 3.8 3.4 3.5 3.6 8.3 21 25 17 9.4 9.5 8.8 8.1 12 14 16 16 17 16 0.014 0.028 0.062 0.11 0.18 0.2 0.2 0.15 0.4 0.97 1.1 0.8 0.79 0.73

(<0.01–<0.01) (<0.01–<0.01) (<0.01–0.012) (0.58–1.4) (1.7–2.5) (2.7–3.7) (3.1–4.6) (2.8–4.1) (2.8–4.2) (2.9–4.3) (7.2–9.5) (19–24) (22–28) (15–19) (8.2–11) (8.3–11) (7.6–10) (6.5–9.9) (9.7–14) (12–17) (14–19) (14–19) (14–19) (14–19) (0.012–0.016) (0.024–0.032) (0.054–0.071) (0.095–0.12) (0.16–0.21) (0.18–0.23) (0.17–0.23) (0.098–0.21) (0.27–0.56) (0.64–1.4) (0.72–1.5) (0.53–1.1) (0.53–1.1) (0.49–1.0)

0.1 0.5 1.4 40 76 102 108 83 82 83 68 151 154 98 50 49 44 23 28 30 30 26 26 25 3.7 6.3 12 18 26 29 27 4.5 12 25 22 14 13 12

(<0.1–0.13) (0.45–0.65) (1.2–1.7) (24–58) (62–91) (86–119) (88–130) (68–100) (67–98) (68–100) (59–78) (131–172) (134–177) (85–112) (43–57) (43–56) (38–51) (19–28) (23–34) (25–35) (25–34) (23–30) (22–30) (22–29) (3.2–4.2) (5.5–7.1) (11–14) (16–20) (23–30) (25–32) (24–31) (3.0–6.3) (7.8–16) (16–34) (15–31) (9.3–20) (8.9–19) (7.9–17)

820 883 3 699 21 453 6 652 3 585 2 870 3 049 3 143

118 123 113 630 169 74 50 51 51

87 (77–99) 87 (77–99) 46 320 110 61 50 53 55 (33–70) (230–480) (77–160) (44–92) (36–75) (38–80) (39–83)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

160

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSE NUMBER RATE a

b

CASE DETECTION PERCENT

Ethiopia

Gabon

Gambia

Ghana

Guinea

Guinea-Bissau

Kenya

Lesotho

L beria

Madagascar

Malawi

Mali

Mauritania

Mauritius

Mozambique

Namibia

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

48 57 66 76 87 89 92 <1 1 1 1 2 2 2 <1 1 1 1 2 2 2 15 17 19 21 24 25 25 6 8 9 10 11 11 11 1 1 1 1 2 2 2 23 27 31 36 41 42 43 2 2 2 2 2 2 2 2 2 3 3 4 4 4 12 13 16 18 21 22 22 9 10 11 13 15 15 16 8 9 10 12 14 14 15 2 2 3 3 4 4 4 1 1 1 1 1 1 1 14 16 18 21 24 25 25 1 2 2 2 2 2 2

180 240 280 260 230 230 230 2.1 3.4 6.5 8.1 7.4 7.2 7 1.7 2.2 2.8 3.6 4.6 4.8 5.1 23 28 29 25 21 20 18 15 20 20 20 20 20 20 1.6 2 2.4 3 3.7 3.9 4 33 46 89 130 120 120 120 2.9 5.7 10 12 13 13 13 4.2 4.6 7 8.7 12 12 13 45 45 46 48 51 52 52 31 46 53 46 33 30 26 6 7.2 7.9 8.3 8.8 8.9 9 4.6 5.9 7.5 9.6 12 13 13 0.29 0.29 0.29 0.28 0.27 0.26 0.26 54 76 94 110 130 130 140 5.4 9.5 27 28 19 16 15

(100–270) (140–360) (170–420) (150–390) (170–310) (170–300) (170–290) (1.7–2.5) (2.8–4.1) (5.3–7.7) (6.7–9.6) (6.1–8.8) (5.9–8.6) (5.8–8.3) (1.0–2.5) (1.8–2.6) (2.3–3.3) (2.9–4.3) (3.8–5.5) (4.0–5.7) (4.2–6.0) (10–40) (16–44) (18–41) (19–33) (18–24) (17–22) (16–21) (12–18) (16–23) (17–24) (17–24) (17–24) (17–24) (17–24) (1.1–2.2) (1.6–2.4) (2.0–2.9) (2.5–3.6) (3.0–4.4) (3.2–4.6) (3.3–4.8) (28–37) (43–50) (84–95) (120–140) (120–130) (120–130) (110–120) (2.2–3.8) (5.0–6.4) (9.0–12) (10–14) (11–14) (11–15) (11–15) (2.6–6.2) (3.7–5.5) (5.7–8.4) (7.1–10) (9.6–14) (10–15) (11–15) (37–54) (37–54) (38–55) (39–57) (42–61) (43–62) (43–62) (22–41) (38–55) (44–63) (38–54) (31–35) (27–32) (24–28) (5.8–6.3) (6.9–7.6) (7.6–8.3) (7.9–8.7) (8.4–9.2) (8.5–9.3) (8.5–9.4) (2.8–6.8) (4.8–7.0) (6.1–9.0) (7.9–12) (10–15) (10–15) (11–16) (0.180–0.430) (0.240–0.350) (0.240–0.350) (0.230–0.330) (0.220–0.320) (0.220–0.310) (0.210–0.310) (8.5–140) (24–160) (41–170) (63–170) (90–180) (93–180) (96–190) (4.3–6.6) (7.5–12) (21–33) (22–35) (15–23) (13–20) (12–18)

367 419 421 342 269 258 247 221 315 527 586 475 450 428 185 204 225 248 273 279 284 155 167 152 119 86 79 72 248 249 234 211 188 183 178 158 174 192 211 233 238 242 139 169 286 359 298 288 272 184 323 553 639 633 632 630 199 219 242 266 293 299 304 391 335 293 262 242 238 234 326 462 467 354 219 191 163 76 80 77 69 63 62 60 228 251 277 305 337 344 350 28 26 24 23 22 21 21 401 478 513 524 544 548 552 379 575 1 410 1 390 867 723 655

(218–553) (249–633) (251–636) (203–516) (191–359) (191–335) (183–321) (182–263) (260–375) (435–627) (484–698) (392–566) (372–536) (354–510) (114–273) (167–245) (184–271) (203–298) (226–325) (230–331) (234–337) (69–275) (93–263) (97–220) (88–154) (75–97) (69–89) (63–82) (204–295) (205–297) (193–279) (173–251) (155–224) (151–219) (146–213) (108–217) (142–209) (157–230) (173–254) (192–278) (196–283) (200–289) (121–159) (155–184) (267–305) (339–380) (286–311) (276–300) (261–283) (135–240) (283–367) (484–626) (535–752) (553–719) (551–717) (550–716) (123–293) (179–263) (197–290) (218–320) (242–349) (247–356) (251–362) (322–466) (276–400) (241–349) (216–313) (199–288) (196–284) (193–280) (230–438) (383–548) (387–554) (292–421) (203–236) (177–206) (151–176) (72–80) (76–84) (74–81) (66–73) (60–66) (59–65) (57–63) (140–336) (205–302) (226–333) (250–367) (277–402) (283–410) (288–418) (17–41) (21–31) (20–29) (19–28) (18–26) (18–25) (17–25) (62–1 050) (153–985) (227–914) (298–811) (377–741) (380–747) (383–753) (300–468) (456–709) (1 110–1 730) (1 100–1 720) (686–1 070) (573–891) (524–800)

11 36 61 54 30 27 23 0.12 0.47 1.6 2.5 2.1 2 1.9 0.023 0.071 0.2 0.47 0.78 0.77 0.76 1.7 4.2 5.9 5.4 3.7 3.3 2.8 1.1 2.8 4.1 4.5 3.8 3.7 3.7 0.08 0.23 0.55 1 1.3 1.4 1.6 3.6 19 47 64 51 49 45 0.083 2.2 7.6 10 9.7 9.5 9.9 0.095 0.31 0.8 1 0.91 0.83 0.76 0.34 0.55 0.73 0.77 0.7 0.67 0.64 13 29 37 33 21 19 16 0.59 1.2 1.6 1.6 1.3 1.3 1.2 0.05 0.1 0.17 0.27 0.44 0.5 0.57 <0.01 <0.01 0.011 0.017 0.016 0.015 0.014 0.84 15 41 61 78 81 83 0.48 2.8 15 19 11 8.7 7.3

(6.3–16) (22–55) (36–92) (32–81) (21–40) (20–35) (17–30) (0.096–0.14) (0.39–0.56) (1.3–1.9) (2.0–2.9) (1.7–2.5) (1.6–2.4) (1.5–2.2) (0.014–0.033) (0.058–0.085) (0.16–0.24) (0.38–0.56) (0.65–0.93) (0.64–0.91) (0.63–0.90) (0.74–2.9) (2.3–6.6) (3.8–8.6) (4.0–7.0) (3.2–4.2) (2.9–3.7) (2.4–3.1) (0.90–1.3) (2.3–3.3) (3.3–4.8) (3.7–5.4) (3.2–4.6) (3.1–4.5) (3.0–4.4) (0.054–0.11) (0.19–0.27) (0.45–0.66) (0.84–1.2) (1.1–1.5) (1.2–1.7) (1.3–1.9) (3.1–4.1) (18–21) (44–50) (60–67) (49–53) (47–51) (44–47) (0.061–0.11) (1.9–2.5) (6.6–8.6) (8.3–12) (8.5–11) (8.3–11) (8.7–11) (0.058–0.14) (0.25–0.38) (0.65–0.98) (0.83–1.3) (0.73–1.1) (0.67–1.0) (0.61–0.93) (0.28–0.40) (0.46–0.66) (0.60–0.87) (0.64–0.92) (0.57–0.83) (0.55–0.80) (0.53–0.77) (9.5–18) (24–34) (31–44) (27–39) (20–23) (18–21) (15–17) (0.56–0.62) (1.2–1.3) (1.6–1.7) (1.5–1.7) (1.3–1.4) (1.2–1.4) (1.2–1.3) (0.031–0.074) (0.083–0.12) (0.14–0.20) (0.22–0.32) (0.36–0.53) (0.41–0.60) (0.47–0.68) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.013) (0.014–0.021) (0.013–0.020) (0.013–0.018) (0.011–0.017) (0.13–2.2) (4.8–31) (18–74) (35–94) (54–110) (56–110) (58–110) (0.38–0.59) (2.2–3.4) (12–19) (15–23) (8.3–13) (6.9–11) (5.8–8.9)

22 64 93 71 35 30 25 12 44 132 178 136 125 115 2.5 6.7 16 33 47 44 42 11 25 31 25 15 13 11 18 35 46 47 35 33 32 7.8 20 43 73 81 88 94 15 70 151 177 124 116 105 5.2 125 408 517 483 467 485 4.5 15 28 32 23 20 18 2.9 4.1 4.6 4.2 3.3 3.1 2.9 143 291 329 256 142 125 100 7.4 14 16 13 9.4 8.9 8.2 2.5 4.4 6.3 8.4 12 14 15 <0.1 0.3 0.9 1.4 1.3 1.2 1.1 6.2 94 227 290 327 331 330 34 168 798 932 483 391 323

(13–33) (38–97) (55–140) (42–107) (25–46) (22–39) (19–33) (10–15) (36–52) (108–157) (146–212) (112–162) (103–149) (95–137) (1.5–3.6) (5.5–8.0) (13–19) (27–39) (39–56) (37–53) (35–50) (5.0–20) (14–39) (20–46) (19–33) (13–17) (12–15) (9.6–12) (15–22) (29–42) (38–55) (39–56) (29–42) (28–40) (27–39) (5.3–11) (16–24) (35–52) (59–87) (67–97) (73–105) (77–112) (13–17) (64–76) (141–161) (168–188) (119–129) (111–121) (101–109) (3.8–6.8) (109–142) (357–462) (433–608) (422–549) (408–531) (423–550) (2.8–6.7) (12–18) (22–34) (25–38) (18–28) (16–25) (15–22) (2.4–3.5) (3.4–4.9) (3.8–5.5) (3.5–5.0) (2.7–3.9) (2.6–3.7) (2.4–3.4) (101–192) (241–345) (273–391) (211–305) (132–153) (116–135) (93–108) (7.0–7.8) (13–14) (15–17) (13–14) (9.0–9.9) (8.5–9.4) (7.8–8.6) (1.5–3.7) (3.6–5.2) (5.1–7.5) (6.9–10) (10–15) (11–16) (12–18) (<0.1–<0.1) (0.24–0.35) (0.74–1.1) (1.2–1.7) (1.1–1.6) (1.0–1.5) (0.92–1.3) (0.97–16) (30–194) (100–404) (165–449) (227–446) (229–451) (228–450) (27–41) (133–207) (631–983) (738–1 150) (383–596) (310–482) (258–394)

88 634 26 034 91 101 124 262 154 694 156 539 145 323 917 1 115 2 512 3 790 4 404 4 929 1 023 1 553 2 031 1 989 2 302 2 333 6 407 8 636 10 933 12 124 14 607 15 389 14 753 1 988 3 523 5 440 6 863 11 038 11 359 11 407 1 163 1 613 1 273 1 774 2 183 2 063 1 939 11 788 28 142 64 159 102 680 99 272 97 320 92 987 2 525 5 181 9 746 10 802 11 674 11 561 10 776 1 393 1 500 3 432 6 597 7 906 8 093 6 261 21 616 18 993 24 432 26 019 25 782 12 395 19 155 23 604 25 491 21 092 19 361 20 335 2 933 3 087 4 216 4 704 5 291 5 428 5 446 5 284 3 849 3 067 2 162 2 461 1 804 2 616 119 131 160 125 122 114 128 15 899 17 882 21 158 33 231 43 558 44 627 47 741 2 671 1 540 10 799 14 920 11 281 10 806 10 003

184 46 138 163 178 175 158 97 103 182 244 276 302 96 126 141 118 133 130 44 52 58 57 60 62 58 33 45 62 72 101 102 100 114 142 100 125 138 127 117 50 103 205 287 243 232 215 158 295 525 561 581 570 525 67 52 105 167 194 193 54 161 104 116 120 116 131 192 208 197 140 125 128 37 34 41 39 38 38 37 261 165 113 69 68 49 69 11 12 14 10 9.9 9.2 10 117 112 116 158 182 182 189 189 93 569 736 518 487 443

50 11 33 48 66 68 64 44 33 31 51 61 71 47 56 57 43 48 46 28 31 38 48 70 79 81 13 18 27 34 54 55 56 73 81 52 59 59 53 48 36 61 72 80 81 80 79 86 91 95 88 92 90 83 31 21 39 57 65 64 14 48 40 48 50 49 40 42 45 56 64 66 78 49 43 53 57 60 61 61 110 66 41 22 20 14 20 41 45 55 45 46 43 49 29 23 23 30 33 33 34 50 16 40 53 60 67 68

(33–85) (7.2–18) (22–55) (32–80) (49–93) (52–91) (49–87) (37–53) (28–40) (26–38) (43–62) (52–74) (59–85) (39–57) (47–69) (47–70) (36–52) (40–58) (39–56) (16–63) (20–55) (26–60) (37–64) (62–80) (70–90) (71–92) (11–16) (15–22) (22–32) (29–41) (45–66) (47–67) (47–68) (53–110) (68–100) (43–64) (49–72) (50–72) (45–65) (40–58) (32–41) (56–66) (67–77) (76–85) (78–85) (77–84) (76–83) (66–120) (81–100) (84–110) (75–100) (81–110) (79–100) (73–95) (25–37) (18–26) (33–48) (48–69) (54–79) (53–77) (12–17) (40–58) (33–48) (40–58) (42–61) (41–60) (30–57) (35–50) (38–54) (47–68) (59–69) (61–71) (73–85) (46–51) (41–45) (51–56) (54–60) (57–63) (58–64) (58–64) (78–190) (55–80) (34–50) (19–28) (17–25) (12–17) (16–24) (28–66) (37–55) (46–68) (37–55) (39–56) (36–53) (41–60) (11–190) (11–73) (13–51) (20–53) (25–48) (24–48) (25–50) (40–63) (13–20) (33–51) (43–67) (48–75) (55–85) (55–84)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

161

African region

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSE NUMBER RATE a

b

CASE DETECTION PERCENT

Niger

Nigeria

Rwanda

Sao Tome and Principe

Senegal

Seychelles

Sierra Leone

South Africa

Swaz land

Togo

Uganda

United Republic of Tanzania

Zambia

Zimbabwe

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

8 9 11 13 16 17 17 96 108 123 140 160 164 169 7 6 8 9 11 11 11 <1 <1 <1 <1 <1 <1 <1 8 9 10 11 13 13 14 <1 <1 <1 <1 <1 <1 <1 4 4 4 5 6 6 6 37 41 45 48 51 52 52 <1 <1 1 1 1 1 1 4 4 5 6 6 6 7 18 21 24 29 34 35 36 25 30 34 39 45 46 48 8 9 10 11 13 14 14 10 12 13 13 13 13 14

28 25 21 19 18 18 18 120 150 210 240 210 190 180 21 29 27 17 11 11 9.8 0.16 0.16 0.16 0.16 0.17 0.17 0.17 10 13 15 16 18 18 19 0.03 0.03 0.029 0.029 0.028 0.028 0.027 8.4 8.3 11 26 38 39 40 110 130 260 450 500 520 530 2.3 3.2 8.5 13 15 16 17 1.8 2.5 3.5 4.2 4.6 4.7 4.9 110 110 100 87 71 68 65 58 68 80 83 80 78 79 56 70 72 65 61 61 60 31 56 91 100 83 81 77

(23–33) (20–29) (17–25) (15–22) (15–21) (15–21) (15–21) (1.3–500) (8.0–490) (15–660) (33–660) (100–360) (91–340) (85–310) (19–23) (26–32) (24–30) (15–19) (10–13) (9.4–12) (8.8–11) (0.098–0.230) (0.130–0.190) (0.130–0.190) (0.140–0.190) (0.140–0.200) (0.140–0.210) (0.140–0.210) (8.5–12) (11–16) (13–18) (13–19) (15–21) (15–22) (16–22) (0.019–0.044) (0.025–0.036) (0.024–0.035) (0.024–0.035) (0.023–0.033) (0.023–0.033) (0.023–0.033) (5.2–12) (6.4–11) (8.1–14) (21–31) (31–45) (32–47) (32–49) (76–150) (110–160) (210–310) (360–540) (420–600) (430–610) (430–630) (1.4–3.4) (2.7–3.9) (7.0–10) (10–15) (13–18) (13–19) (14–20) (1.5–2.1) (2.0–3.0) (2.9–4.2) (3.5–5.1) (3.8–5.5) (3.9–5.6) (4.0–5.8) (57–180) (62–180) (63–150) (63–120) (57–86) (55–82) (53–79) (49–67) (58–78) (70–91) (76–89) (75–85) (74–83) (74–84) (49–63) (64–76) (67–77) (59–71) (55–67) (55–67) (54–66) (17–50) (39–77) (72–110) (81–130) (64–100) (62–100) (60–97)

358 270 191 142 113 108 104 128 139 172 175 133 118 108 290 513 325 181 106 94 86 135 124 114 105 96 94 93 138 153 155 142 137 136 137 43 40 37 33 31 30 30 207 212 264 503 660 668 674 301 317 576 925 981 993 1 000 267 337 803 1 150 1 290 1 320 1 350 47 58 72 77 73 73 73 624 542 427 304 209 193 179 226 226 236 213 177 169 165 710 788 713 566 462 444 427 296 483 726 799 633 603 562

(295–426) (223–321) (157–227) (118–170) (94–135) (90–129) (86–124) (1.3–526) (7.4–456) (12–536) (23–476) (64–225) (55–204) (50–186) (259–323) (458–571) (290–362) (162–202) (94–118) (84–105) (77–96) (83–199) (102–149) (93–137) (88–123) (79–115) (78–113) (76–111) (114–164) (126–183) (128–184) (117–169) (113–163) (112–162) (113–163) (27–64) (33–48) (30–44) (27–40) (25–37) (25–36) (24–35) (128–305) (162–269) (196–341) (410–605) (540–791) (542–807) (540–821) (206–413) (259–381) (471–691) (756–1 110) (809–1 170) (819–1 180) (827–1 190) (165–394) (275–405) (657–964) (938–1 380) (1 060–1 530) (1 090–1 570) (1 110–1 610) (39–56) (48–69) (59–86) (63–91) (60–87) (60–87) (60–87) (328–1 010) (297–860) (259–636) (220–402) (169–253) (156–234) (145–216) (193–261) (193–261) (207–268) (197–229) (166–189) (159–180) (154–175) (624–801) (719–861) (661–767) (519–615) (418–509) (401–489) (385–470) (159–476) (335–658) (573–897) (634–984) (489–795) (466–757) (434–706)

1.1 1.7 2.1 2.2 1.9 1.9 1.9 2.2 16 46 64 53 49 46 11 15 13 7.5 3.7 3.3 2.9 <0.01 <0.01 <0.01 0.015 0.018 0.018 0.017 0.17 0.4 0.8 1.2 1.5 1.6 1.7

(0.91–1.3) 14 (12–17) (1.4–2.1) 19 (16–22) (1.7–2.5) 19 (16–23) (1.8–2.6) 16 (14–20) (1.6–2.3) 12 (9.8–14) (1.6–2.3) 11 (9.5–14) (1.5–2.2) 11 (8.9–13) (0.023–9.1) 2.3 (<0.1–9.5) (0.84–52) 15 (0.78–48) (3.3–140) 38 (2.7–118) (8.6–170) 46 (6.2–125) (26–91) 33 (16–57) (23–85) 30 (14–52) (21–80) 27 (13–47) (9.5–12) 148 (132–165) (13–16) 260 (232–290) (12–15) 157 (140–175) (6.7–8.3) 79 (71–88) (3.3–4.1) 34 (31–38) (3.0–3.7) 30 (26–33) (2.6–3.2) 25 (22–28) (<0.01–<0.01) 2 (1.2–2.9) (<0.01–<0.01) 3.8 (3.1–4.6) (<0.01–0.010) 6.2 (5.0–7.4) (0.012–0.017) 9.6 (8.0–11) (0.015–0.021) 9.9 (8.1–12) (0.014–0.021) 9.6 (7.9–11) (0.014–0.021) 9.2 (7.5–11) (0.14–0.20) 2.2 (1.8–2.6) (0.33–0.48) 4.6 (3.8–5.5) (0.66–0.96) 8.1 (6.7–9.7) (1.0–1.4) 11 (8.9–13) (1.3–1.8) 12 (9.7–14) (1.3–1.9) 12 (9.6–14) (1.4–2.0) 12 (9.9–14)

5 200 1 980 4 701 7 873 10 130 10 510 10 989 20 122 13 423 25 821 63 990 84 121 86 778 92 818 6 387 3 054 6 093 7 220 6 703 6 623 6 091 17 97 136 121 136 115 4 977 7 561 8 508 9 765 11 061 11 022 12 265 41 8 20 14 17 21 20 632 1 955 3 760 6 737 12 859 12 734 13 074 80 400 73 917 151 239 270 178 354 786 362 453 323 664 2 050 5 877 8 705 10 101 8 337 7 165 1 324 1 520 1 409 2 541 2 791 2 888 2 843 14 740 25 316 30 372 41 040 42 885 46 306 44 663 22 249 39 847 54 442 61 022 61 098 59 357 62 178 16 863 35 958 49 806 49 576 44 154 43 583 40 726 9 132 30 831 50 855 50 454 44 209 38 404 35 760

67 22 43 60 64 64 64 21 12 21 46 53 53 55 89 54 73 77 62 59 53 14 70 88 68 74 61 66 87 86 87 85 83 89 59 11 25 16 19 23 22 16 50 91 132 224 217 219 219 178 337 560 690 698 618 213 552 788 847 688 582 35 35 29 46 44 45 43 84 122 125 143 126 132 123 87 133 160 157 136 128 130 215 407 493 432 334 320 289 87 265 407 397 338 287 261

19 8 22 42 56 59 62 16 8.9 12 26 40 45 51 30 11 22 42 59 63 62 11 61 84 71 79 66 48 57 56 61 63 61 65 140 27 69 48 61 76 73 7.5 23 34 26 34 32 32 73 56 59 61 70 70 62 63 69 69 66 52 43 74 61 40 60 61 61 59 13 23 29 47 60 68 69 39 59 68 74 77 76 79 30 52 69 76 72 72 68 29 55 56 50 53 48 46

(16–23) (6.7–9.7) (19–27) (35–51) (47–68) (49–71) (52–75) (4.0–1 600) (2.7–170) (3.9–170) (9.6–200) (23–82) (26–95) (29–110) (27–34) (9.4–12) (20–25) (38–47) (53–66) (57–71) (56–69) (7.3–17) (51–75) (72–100) (59–86) (66–96) (55–80) (40–58) (47–69) (47–68) (51–74) (52–76) (51–74) (55–79) (92–220) (22–33) (57–84) (40–59) (51–74) (64–92) (61–88) (5.1–12) (19–31) (27–46) (22–32) (28–41) (27–40) (27–40) (53–110) (47–69) (49–72) (50–74) (59–85) (59–85) (52–75) (53–77) (57–84) (57–84) (55–80) (44–63) (36–52) (62–90) (51–74) (34–49) (50–73) (51–74) (51–74) (49–71) (8.3–26) (14–41) (20–48) (36–65) (50–75) (56–84) (57–85) (33–45) (51–69) (60–77) (69–80) (72–82) (71–81) (74–84) (27–34) (47–57) (64–75) (70–83) (66–80) (65–80) (62–75) (18–55) (40–79) (45–71) (40–63) (43–69) (38–62) (37–60)

<0.01 <0.01 <0.01 0.011 0.087 0.45 2.3 4.2 4.3 3.9 2.5 25 140 300 330 330 330 0.38 1.6 6.3 11 13 12 13 0.18 0.44 0.89 1.2 1.2 1.2 1.2 79 81 68 50 38 36 35 14 31 41 40 33 31 32 35 49 52 47 39 38 35 18 46 79 83 63 58 55

(<0.01–<0.01) 1.8 (<0.01–0.011) 5.8 (<0.01–<0.01) 2.7 (<0.01–0.016) 0.3 (0.067–0.11) 2.2 (0.33–0.58) 11 (1.9–2.7) 44 (3.4–5.0) 73 (3.5–5.2) 73 (3.2–4.8) 66 (1.7–3.4) 6.7 (21–30) 61 (110–170) 311 (250–360) 622 (270–390) 640 (270–390) 635 (270–390) 631 (0.23–0.56) 44 (1.3–1.9) 161 (5.2–7.6) 595 (8.7–13) 962 (11–15) 1 070 (10–15) 1 020 (11–15) 1 040 (0.15–0.21) 4.7 (0.37–0.53) 10 (0.73–1.1) 18 (1.0–1.5) 22 (0.99–1.4) 19 (0.97–1.4) 18 (0.98–1.4) 18 (41–130) 449 (44–130) 390 (41–100) 280 (36–66) 173 (31–46) 113 (29–44) 102 (28–42) 95 (12–16) 56 (26–36) 103 (36–46) 121 (37–43) 104 (31–35) 72 (29–33) 68 (30–34) 68 (31–40) 449 (45–54) 559 (48–56) 513 (43–51) 409 (35–43) 292 (34–42) 277 (32–39) 251 (9.5–29) 170 (32–62) 392 (62–97) 629 (66–100) 657 (48–79) 480 (45–73) 433 (42–69) 399

(<0.1–8.0) (1.6–12) (<0.1–10) (0.17–0.40) (1.7–2.8) (8.0–14) (36–53) (60–87) (59–88) (53–81) (4.6–9.2) (50–73) (254–374) (508–746) (528–763) (524–756) (521–752) (27–64) (132–194) (486–714) (787–1 150) (882–1 270) (844–1 220) (856–1 240) (3.8–5.6) (8.5–12) (15–22) (18–26) (16–23) (15–22) (15–21) (236–729) (214–619) (170–417) (125–228) (91–137) (83–124) (77–115) (47–64) (88–119) (106–137) (96–112) (68–77) (63–72) (64–72) (395–507) (510–611) (475–551) (375–445) (264–322) (250–305) (226–276) (91–273) (272–535) (496–777) (521–809) (371–603) (335–543) (308–501)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

162

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN 5 735 8 328 8 654 8 299 7 790 7 510 3 804 9 053 20 410 21 146 21 703 21 124 1 410 1 839 2 277 2 739 2 973 3 331 3 171 1 903 3 091 3 170 3 295 2 669 2 426 1 028 1 545 2 290 3 041 3 450 3 583 1 121 3 159 3 262 4 590 4 060 4 075 2 896 3 960 13 001 14 464 14 927 15 016 111 135 186 182 189 1 794 2 153 3 638 3 479 4 641 2 002 2 516 3 833 4 434 3 849 103 87 79 62 71 2 013 4 218 3 640 3 568 3 716 3 984 8 254 10 276 12 496 14 131 14 416 14 660 20 914 36 513 65 040 73 653 71 321 71 124 219 2 256 2 019 1 651 1 770 1 753 1 702 1 631 5 367 12 467 17 285 18 380 23 056 310 281 130 96 296 329 305 2 885 4 789 5 166 2 055 1 983 2 208 195 196 367 736 692 662 908 1 489 1 160 963 799 746 142 625 5 021 5 437 4 941 5 204 150 93 98 127 151 964 608 1 598 964 1 752 518 2 419 3 746 4 211 4 809 10 14 14 13 24 849 2 016 3 249 3 545 3 930 3 937 1 508 1 616 2 315 2 381 2 316 2 818 7 953 8 089 9 959 14 039 13 471 13 214 45 5 065 7 758 10 216 11 770 11 444 12 294 266 1 102 2 569 3 780 4 399 4 776 182 212 199 285 367 398 316 720 1 231 1 220 1 210 1 213 1 151 195 502 571 729 742 617 1 116 1 568 2 089 1 826 1 649 1 887 18 415 2 461 3 157 3 597 3 524 12 43 54 54 66 393 286 1 079 876 1 356 463 1 055 1 217 1 033 1 113 7 15 16 28 23 675 2 810 2 665 2 692 2 990 3 110 1 577 2 756 4 235 5 179 4 729 5 344 9 112 13 785 18 494 22 340 21 579 20 669 41 0 24 60 0 0 0 451 467 548 497 442 374 134 540 1 729 2 444 2 758 2 863 172 68 91 150 120 154 174 147 181 502 453 738 376 45 88 160 217 227 194 181 205 74 224 229 210 236 251 1 016 1 015 1 068 1 058 30 21 18 17 14 188 163 304 232 335 203 321 463 578 634 7 4 2 9 2 78 169 299 345 339 272 649 446 635 1 017 1 015 940 2 891 2 637 3 582 4 138 3 761 3 977 1 194 245 269 215 128 117 113 199 13 9 10 5 451 547 713 691 610 576 134 540 2 871 7 776 4 444 4 470 221 68 280 337 205 262 283 147 1 239 548 1 072 868 438 45 178 327 552 484 389 181 225 116 332 315 305 236 251 1 590 1 494 1 661 1 616 30 34 27 27 19 188 291 421 345 534 203 515 708 847 849 7 5 3 11 4 78 819 407 516 507 481 649 893 980 1 519 1 459 1 400 2 891 2 637 6 065 8 604 7 919 7 492 1 0 0 0 0 0 0 – 72 80 84 82 82 82 – 70 63 62 55 54 48 82 87 95 97 91 91 91 – 40 39 38 62 57 52 – 84 89 86 81 83 84 – 55 68 74 83 84 85 – 95 86 72 73 75 74 – 43 – 59 65 59 56 – 65 – 78 69 78 73 – 79 – 51 51 51 44 – 91 86 85 – 83 75 – 70 68 53 50 49 50 – 85 86 84 86 86 84 – 72 82 87 84 84 84 – 83 – – 86 84 –

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Algeria YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSE 11 607 13 507 18 572 21 336 22 336 21 429 21 880 10 271 5 143 16 062 37 175 44 655 47 240 51 819 2 074 2 400 2 697 3 270 3 756 4 212 3 966 2 938 5 665 9 292 10 058 7 013 6 603 6 161 1 497 2 572 2 331 3 478 4 800 5 286 5 210 4 575 3 326 6 421 6 585 7 611 6 742 6 921 5 892 3 292 5 251 21 499 24 073 24 533 24 802 221 303 292 356 380 420 2 124 3 339 3 210 6 643 5 611 8 084 2 591 3 186 6 311 9 452 10 505 10 585 140 123 120 111 117 120 591 3 615 9 239 9 853 10 150 10 975 11 303 7 841 11 988 15 094 19 681 22 708 22 476 23 762 21 131 42 819 61 024 97 075 114 170 110 132 108 984 260 306 b

• 44 Angola

57 •

267 0 0 0

80 165 194 168 202

0 0 0

• 99 Benin

249 •

0 0

1 142 5 332 1 686 1 607 49 189 187 85 108 109

0

• 41 Botswana

39 •

0 0 0

0 0 0

• 212 Burkina Faso

307 •

• 17 Burundi

32 •

90 77 175 154

90 167 335 257 195

0 0 0 0 0

• 82 Cameroon

70 •

0 0 8 5 3

20 42 108 86 95

0 0 0 0 0

• 49 Cape Verde

114 •

0 0 0 0

574 479 593 558

0 0 0 0

• 63 Central African Republic

85 •

• 73 Chad

179 •

• 44 Comoros

85 •

193 249 180

0 0 0

0 5

1 1 2 2

0 0

• 34 Congo

17 •

• 25 Côte d'Ivoire

261 •

0 0

650 108 171 168 209

0 0

• 65 Democratic Republic of the Congo

120 •

0 0 0 0 0

447 345 502 444 460

0 0 0 0 0

0

• 61 Equatorial Guinea

166 •

2 483 4 466 4 158 3 515

0

820 883

579 611

98 118

109 131

0 0

34 23

33 30

67 53

0 0

• 70

0•

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

163

African region

0 0 0

1 058 46 619 130 62

0 0 0

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE NEW PULM RELAPSE RETREAT UNKNOWN POSITIVE UNKNOWN PULMONARY 18 205 5 332 1 764 1 115 1 163 1 154 8 888 30 565 39 816 54 979 55 497 49 413 517 1 071 1 366 1 959 2 353 171 515 749 462 673 643 1 225 2 500 3 068 5 068 5 875 5 979 527 430 524 1 472 1 446 1 510 714 600 522 636 644 521 9 676 24 143 43 772 41 962 39 810 36 697 2 685 2 838 4 063 5 331 5 296 5 142 119 285 575 1 385 1 967 1 946 987 1 287 1 657 1 726 1 804 5 827 7 054 8 846 10 132 8 245 6 612 6 550 609 797 482 481 491 487 800 687 454 390 222 354 8 14 4 5 3 3 3 248 683 1 001 836 888 1 093 7 763 28 907 43 675 50 417 49 305 46 854 68 241 379 384 414 68 99 78 143 199 169 109 615 1 019 1 400 1 471 1 301 620 938 629 2 077 2 284 2 434 19 57 24 22 63 43 3 468 9 118 15 265 17 382 17 069 15 934 653 2 520 2 020 2 222 2 095 1 877 120 187 657 1 363 1 612 1 749 2 219 3 634 4 545 4 851 4 964 1 885 5 257 5 734 5 823 4 857 5 076 4 886 459 653 492 926 984 1 081 455 580 403 524 458 628 12 23 8 6 8 5 0 0 0 – – 10 28 43 42 40 – 50 50 49 46 47 49 – 48 – 49 53 47 43 – 82 64 60 74 67 69 – 68 75 71 60 56 54 – 81 90 91 83 83 82 – 57 47 68 69 66 72 100 59 54 48 46 48 50 – 34 52 51 40 41 39 – 91 78 79 73 68 69 – 89 – 91 91 91 91 42 47 48 45 47 51 51 – 75 76 88 88 88 88 – 72 70 72 78 82 81 – 93 89 96 95 97 98

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Eritrea YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSE 3 699 21 453 6 652 3 585 2 870 3 049 3 143 88 634 26 034 91 101 124 262 154 694 156 539 145 323 917 1 115 2 512 3 790 4 404 4 929 1 023 1 553 2 031 1 989 2 302 2 333 6 407 8 636 10 933 12 124 14 607 15 389 14 753 1 988 3 523 5 440 6 863 11 038 11 359 11 407 1 163 1 613 1 273 1 774 2 183 2 063 1 939 11 788 28 142 64 159 102 680 99 272 97 320 92 987 2 525 5 181 9 746 10 802 11 674 11 561 10 776 1 393 1 500 3 432 6 597 7 906 8 093 6 261 21 616 18 993 24 432 26 019 25 782 12 395 19 155 23 604 25 491 21 092 19 361 20 335 2 933 3 087 4 216 4 704 5 291 5 428 5 446 5 284 3 849 3 067 2 162 2 461 1 804 2 616 119 131 160 125 122 114 128 b

• 113 Ethiopia

51 •

590 687 832 835 779 9 040 30 510 38 525 46 634 49 594 47 236 486 1 042 1 560 1 740 1 745 778 919 1 127 1 344 1 375 1 429 2 638 7 316 7 505 7 656 7 616 7 097 2 263 3 920 5 479 7 041 6 934 6 653 956 526 1 132 1 409 1 230 1 324 6 800 13 934 28 773 40 389 36 260 37 085 36 937 1 361 3 041 4 280 3 600 3 666 3 298 1 154 1 021 2 167 3 750 4 261 4 342 8 026 13 056 16 795 17 927 17 206 4 301 6 285 8 260 8 443 7 240 7 003 6 951 1 866 2 527 3 530 3 686 3 777 3 724 2 074 1 583 1 155 1 422 1 009 1 522 113 115 110 105 100 118

0 60 0

47 97 87 103 117 343 1 119 2 246 2 664 2 143 1 820 44 158 168 321 175 6 20 77 40 51 92 159 502 532 483 427 376 55 152 231 362 422 489 59 90 96 116 126 51 1 064 1 773 3 254 3 668 3 356 3 419 147 385 439 521 504 459

20 27 121 44 111

67 124 208 147 228 343 2 777 3 119 4 898 4 621 4 089 44

36 0 0 0

• 184 Gabon

158 •

0 0 0

1 658 873 2 234 2 478 2 269

0 0

• 97 Gambia

302 •

0 0 0

99 390 512 486

257 558 833 661 6 53 166 81 82 146 159 502 532 1 021 878 830 55 446 458 648 669 723 59 90 138 192 133 62 1 064 2 477 8 975 10 479 10 017 9 581 147 1 481 1 041 1 985 1 728 1 654

317 0 242

•0 Ghana

130 •

0 0 4 0

33 89 41 31 54

0 0 0

0

• 44 Guinea

58 •

538 451 454

0

• 33 Guinea-Bissau

100 •

86 273 321

294 227 286 247 234

0 0

• 114 Kenya

117 •

0 0 0 0

42 76 7 11

0 0 0 0

• 50 Lesotho

215 •

0 0 0

704 5 721 6 811 6 661 6 162

0 0 0

• 158 Liberia

525 •

1 096 602 1 464 1 224 1 195

•0 Madagascar

193 •

0 0 0

7 33 99 66 56 596 1 016 1 435 1 515 1 519 382 551 764 1 093 750 670 694 153 239 200 198 176 154 520 580 150 125 87 112 2 8 3 6 3 2

25 24 71 59 39

32 57 170 125 95 596

0 0 0

• 54 Malawi

116 •

482 674 703 427

0 0

• 131 Mali

128 •

0 2 119 1 444 1 493 128

1 498 2 109 2 218 1 946 382 551 764 3 212 2 194 2 163 822 153 239 380 355 321 310 520 938 206 153 103 132 2 12 5 7 5 4

0 0 289

1 254

0 0

• 37 Mauritania

37 •

180 157 145 156

0 0 0

• 261 Mauritius

69 •

0 0 0 0

358 56 28 16 20

0 28 0

• 11

10 •

0 0 0

4 2 1 2 2

0 0 0

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

164

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN 10 566 13 257 17 877 20 097 19 537 20 951 697 4 012 5 222 4 464 4 503 4 333 1 492 3 045 5 050 6 283 6 604 6 848 9 476 17 423 35 048 45 416 47 436 52 901 1 840 3 681 4 166 3 785 3 811 3 571 5 054 4 037 9 184 16 408 18 159 19 797 507 4 724 4 455 3 309 3 034 2 473 116 699 1 193 1 730 1 856 1 989 3 364 6 613 22 705 32 616 33 034 32 972 676 845 859 1 072 1 017 858 1 363 2 262 4 771 5 621 5 504 5 542 248 1 459 1 907 2 330 2 039 2 063 372 702 1 227 1 492 1 489 1 689 280 1 069 2 836 3 422 3 793 4 432 338 1 289 1 727 1 577 1 300 1 247 899 917 1 399 1 432 1 427 1 451 88 604 849 1 178 1 230 1 134 899 1 463 1 886 4 048 4 252 4 537 88 1 534 1 823 2 522 2 362 2 276 – 68 77 66 55 52 51 – 58 46 54 57 60 64 – 93 81 81 78 78 77 – 74 72 61 58 59 62 – 73 81 83 78 79 81 – – 35 40 43 52 61 – 83 81 81 84 85 83 – 75 61 73 53 13 53 – 81 75 72 58 63 65 – 24 82 62 47 47 47 – 49 36 35 37 36 45 – 74 92 91 93 91 93 – 70 66 58 63 64 65 100 62 58 55 54 54 54 – 75 34 38 38 38 43 – 45 34 31 32 40 41

NEW AND RELAPSE NOTIFICATION RATE 1990–2012 Mozambique a

YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

NEW AND RELAPSE 15 899 17 882 21 158 33 231 43 558 44 627 47 741 2 671 1 540 10 799 14 920 11 281 10 806 10 003 5 200 1 980 4 701 7 873 10 130 10 510 10 989 20 122 13 423 25 821 63 990 84 121 86 778 92 818 6 387 3 054 6 093 7 220 6 703 6 623 6 091 17 97 136 121 136 115 4 977 7 561 8 508 9 765 11 061 11 022 12 265 41 8 20 14 17 21 20 632 1 955 3 760 6 737 12 859 12 734 13 074 80 400 73 917 151 239 270 178 354 786 362 453 323 664 2 050 5 877 8 705 10 101 8 337 7 165 1 324 1 520 1 409 2 541 2 791 2 888 2 843 14 740 25 316 30 372 41 040 42 885 46 306 44 663 22 249 39 847 54 442 61 022 61 098 59 357 62 178 16 863 35 958 49 806 49 576 44 154 43 583 40 726 9 132 30 831 50 855 50 454 44 209 38 404 35 760 b

• 117 Namibia

189 •

0 0 0

546 487 2 616 2 825 3 086

0 0 0

2 487 0

• 189 Niger

443 •

930 974 1 344 1 132 1 142

0

173 116

• 67 Nigeria

64 •

255 403 452 376 347 303 716 2 009 2 667 2 515 2 513 200 278 371 269 253 212

351 215 204 218

255 754 667 580 565 303 2 356 4 867 8 993 8 787 7 548 200 374 831 631 414 329

0 0 185 0

• 21 Rwanda

55 •

97 242 203

• 89 Sao Tome and Principe

53 •

96 460 362 161 117

0 0

• 14 Senegal

61 •

30 49 47 53 59 5 421 5 823 6 722 7 688 7 765 8 448 6 11 8 9 2 9 1 454 2 472 4 370 6 898 7 435 8 031 23 112 75 967 125 460 132 107 129 770 119 898 660 1 823 2 187 3 011 2 408 2 548 887 984 1 798 2 096 2 087 2 112 13 631 17 246 20 559 23 456 25 614 24 916 11 553 19 955 24 049 25 264 24 769 24 115 25 138 10 038 12 927 14 857 12 639 12 046 12 645 8 965 14 392 13 155 11 654 12 596 12 163

56 75 63 49 37 1 073 1 370 1 557 1 470 1 389 1 755 2 7 3 8 13 8 339 821 1 679 4 919 4 358 4 241 74 399 16 392 76 680 151 772 148 266 134 631 687 3 198 4 106 5 064 4 228 3 111 304 91 170 164 205 168 5 912 9 003 15 040 13 567 14 389 13 270 12 362 17 624 20 810 21 184 20 438 21 393 3 268 25 222 24 327 20 412 20 004 17 050 10 934 27 626 29 074 25 157 19 172 17 316

7 1 10 28 16 504 800 921 1 404 1 315 1 524 1 2 1 0 6 2 121 400 551 831 775 570 10 636 17 486 39 739 52 095 47 285 42 467 219 583 1 458 1 631 1 395 1 209 236 287 484 397 475 444 2 070 2 618 3 780 4 571 5 001 5 143 6 195 10 997 13 094 13 715 13 725 14 595 656 10 202 8 587 9 255 9 908 9 174 5 040 8 837 6 721 6 061 5 192 4 912

0 0 0 0

4 11 1 6 3 563 515 565 499 553 538 0 0 2 0 0 1 41 67 137 211 166 232 179

16 1 10 12

4 27 2 16 15 563 1 056 920 1 029 1 119 1 092 0 0 2 0 0 2 41 441 330 547 375 512 179 56 202 60 588 60 580 45 915 52 586 489 1 249 470 1 440 1 149 871 93 133 179 240 213 188 955 1 505 2 430 3 952 4 014 3 882 1 335 1 772 5 032 3 785 2 870 2 766 243 1 455 5 496 6 310 6 636 6 408 737

0 0 0

0 0 0 0

• 66 Seychelles

89 •

541 355 530 566 554

0 0 0

• 59 Sierra Leone

22 •

0 0 0 0

0 0 0 1

0 0 0

• 16 South Africa

219 •

374 193 336 209 280

• 219 Swaziland

618 •

0 0 0 0

28 299 18 812 18 394 26 668 489 273 311 395 306 297 93 47 85 134 121 119 955 1 505 1 661 1 291 1 302 1 334 1 335 1 772 1 854 1 430 1 079 1 052 243 1 455 1 805 1 848 1 625 1 857 737

56 202 32 289 41 768 27 521 25 918

0 0 18 738 0

•0 Togo

582 •

0 0

976 159 1 045 843 574

643 0 0

• 35 Uganda

43 •

0 0 0

86 94 106 92 69

4 0 0 0

0 0 0

• 84 United Republic of Tanzania

123 •

0 769 2 661 2 712 2 548

0 0

• 87 Zambia

130 •

0 0

3 178 2 355 1 791 1 714

0 0

0

• 215 Zimbabwe

289 •

3 691 4 462 5 011 4 551

0

• 87

261 •

0 0 0 0

1 504 1 337 1 444 1 369

4 437 3 348 2 901 2 960

5 941 4 685 4 345 4 329

0 0 0

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

165

African region

0 0 0

1 640 2 858 6 326 6 272 5 035

1 392 0 0

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Algeria

•0 Angola

92 •

•0 Benin

55 •

• 71 Botswana

90 •

• 67 Burkina Faso

81 •

• 25 Burundi

78 •

• 45 Cameroon

92 •

• 53 Cape Verde

80 •

•0 Central African Republic

77 •

• 37 Chad

68 •

• 47 Comoros

68 •

• 90 Congo

25 •

•0 Côte d'Ivoire

71 •

• 68 Democratic Republic of the Congo

78 •

• 74 Equatorial Guinea

87 •

• 89 Eritrea

0•

•0 Ethiopia

87 •

• 61 Gabon

90 •

• 86 a

51 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

5 735 8 328 8 654 8 402 8 299 7 790 3 804 9 053 20 410 22 488 21 146 21 703 1 839 2 277 2 739 2 960 2 973 3 331 1 903 3 091 3 170 3 144 3 295 2 669 1 028 1 545 2 290 3 061 3 041 3 450 1 121 3 159 3 262 3 974 4 590 4 060 2 896 3 960 13 001 14 635 14 464 14 927 111 135 172 186 182 1 794 2 153 5 132 3 638 3 479 2 002 2 516 3 820 3 833 4 434 103 87 79 76 62 2 013 4 218 3 640 3 433 3 568 3 716 8 254 10 276 12 496 14 300 14 131 14 416 20 914 36 513 65 040 73 078 73 653 71 321 219

8 328 8 379 8 438 7 894 7 364 6 392 20 113 21 627 21 145 21 703 1 839 2 277 2 766 2 963 2 987 3 324 2 060 3 991 3 335 3 492 3 314 3 107 1 200 1 574 2 290 3 061 3 057 3 442 1 798 3 465 3 424 3 974 4 590 4 060 2 740 3 164 13 169 14 428 14 464 14 927 14 135

182 692 1 366 3 217 5 132 3 569 3 205 529

3 820 3 780 4 430 113 85 70 87 4 3 114 4 121 3 634 3 447 3 716 7 221 10 631 12 496 14 300 14 131 14 416 16 247 36 123 65 066 72 367 73 448 71 321 219

490 579 611 590 687 802 832 835 9 040 30 510 38 525 44 396 46 634 49 594 486 1 042 1 244 1 560 1 740

490 590

765 688 804 804 835 5 087 29 662 39 430 44 807 46 634 41 351 249 1 165 1 163 1 671 1 654

– 100 97 100 95 95 – 71 99 96 100 100 100 100 101 100 100 100 108 129 105 111 101 116 117 102 100 100 101 100 160 110 105 100 100 100 95 80 101 99 100 100 – – 100 – – 100 39 – 149 100 98 92 26 – – 100 99 100 110 98 89 – – 6 – 74 113 106 97 100 87 103 100 100 100 100 78 99 100 99 100 100 100 – – 100 102 – – 130 100 100 97 100 56 97 102 101 100 83 51 – 112 93 107 95

80 74 81 79 81 68 45 47 30 36 50 57 74 82 84 84 13 22 37 57 50 36 22 53 66 72 74 74 25 42 52 83 87 88 45 67 66 65 64 67 64 56

7 13 10 10 11

1 2 2 2 2 3 3 4 8 7 6 6 7 5 5 6 5 6 7 5 5 6 5 13 14 10 9 9 3 4 4 3 4 4 7 7 6 6 6 6 7 3

2 0 1 1 0 2 3 2 1 2 1 2 2 2 2 3 1 0 1 3 2 2 1 2 7 9 7 6 0 0 0 1 1 1 1 2 1 1 1 1 0 2

5 3 3 4 4 26 19 18 8 13 17 11 3 1 1 1 12 7 8 4 3 3 3 16 6 4 6 6 14 13 17 5 3 3 35 13 14 10 10 9 0 19

5 8 3 4 2 2 3 5 35 23 5 3 1 0 1 0 15 10 15 9 8 9 67 9 1 2 1 1 38 1 1 0 0 0 4 1 5 5 5 4 29 12

28 25 18 19 21 20 13 9 7 6 54 55 33 22 32 46 2 7 5 4 3 4 20 39 27 7 4 4 8 10 7 13 14 13 0 8

55 16 36 38 33 45 44 17

23 21 21 28 20 23 23 30

4 7 0 6 3 6 4 6

0 0 3 2 1 1 1 1

9 53 34 8 13 19 18 43

10 3 5 19 30 7 10 3

55 39 45 90 91 91 91 25 57 24 66 63 59 63 47 62 69 66 69 55 69 80 85 86 82 89

22 28 23 0 2 0 0

4 4 4 4 4 3 3 75 4 0 1 2 2 4 5 8 8 7 7 5 6 6 4 4 4 3

2 2 1 0 4 4 2

15 21 19 6 0 0 1

3 5 8 0 0 1 2 0 5 58 7 8 14 9 20 6 4 5 3 9 7 4 4 3 5 0

12 4 12 13 12 6 10 11 10 12 9 20 8 5 3 4 5 0

0 1 0 1 2 1 2 2 3 2 2 1 1 1 1 1 1 0

22 13 13 12 11 17 16 10 7 8 9 10 8 4 3 3 4 8

47 50

19 20

3 5

1 1

16 17

14 7

64 83 83 81 83 56 63 64 65 66 70 63 35 37 34 26

12 5 2 4 4 5 17 14 19 17 19 22 12 18 29 25

8 7 5 7 4 5 6 5 3 3 3 1 10 1 2 2

1 1 3 3 4 2 1 1 1 1 1 2 1 1 3 1

9 2 2 1 1 13 9 4 3 3 2 9 42 25 26 36

6 1 5 5 5 19 4 12 10 10 4 2 1 18 6 11

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

166

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Gambia

• 76 Ghana

88 •

• 54 Guinea

86 •

• 78 Guinea-Bissau

82 •

• 65 Kenya

73 •

• 75 Lesotho

88 •

• 47 Liberia

74 •

• 79 Madagascar

86 •

• 55 Malawi

83 •

• 71 Mali

85 •

• 59 Mauritania

68 •

•0 Mauritius

73 •

•0 Mozambique

90 •

• 39 Namibia

0•

•0 Niger

84 •

•0 Nigeria

80 •

• 49 Rwanda

85 •

•0 Sao Tome and Principe

89 •

•0 a

72 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

778 919 1 127 1 313 1 344 1 375 2 638 7 316 7 505 8 255 7 656 7 616 2 263 3 920 5 479 5 377 7 041 6 934 956 526 1 132 1 310 1 409 1 230 13 934 28 773 40 389 37 402 36 260 37 085 1 361 3 041 4 280 3 976 3 600 3 666 1 154 1 021 2 167 3 796 3 750 4 261 8 026 13 056 15 729 16 795 17 927 6 285 8 260 8 443 7 623 7 240 7 003 1 866 2 527 3 530 5 163 3 686 3 777 2 074 1 583 1 155 1 555 1 422 1 009 113 115 110 98 105 100 10 566 13 257 17 877 19 579 20 097 19 537 697 4 012 5 222 4 608 4 464 4 503 1 492 3 045 5 050 6 347 6 283 6 604 9 476 17 423 35 048 44 863 45 416 47 436 1 840 3 681 4 166 4 184 3 785 3 811 30 49 52 47 53

686 1 127 1 296 1 344 1 375 361 7 316 7 584 8 255 7 656 7 623 2 263 3 920 5 811 5 597 7 250 5 152 959 1 167 1 498 1 271 1 308 6 470 28 376 40 436 37 402 36 260 36 717 1 788 5 542 4 070 3 852 3 666 1 595 924 2 167 3 796 3 853 9 101 10 506 15 298 15 709 16 789 17 602 6 293 8 296 8 443 7 624 7 240 7 012 1 290 3 530 4 454 3 778 3 777

1 761 1 563 1 422 1 450 160 110 98 105 100 10 566 13 296 17 877 19 579 20 097

4 012 5 222 4 702 4 538 4 502 3 193 5 050 6 313 6 266 6 604 9 476 16 372 35 080 44 863 45 416 47 436 3 776 4 175 4 165 3 806 3 811 97 49 50 45 53

88 – 100 99 100 100 14 100 101 100 100 100 100 100 106 104 103 74 100 – 103 114 90 106 46 99 100 100 100 99 131 – 129 102 107 100 138 90 100 100 – 90 113 – 117 100 100 98 100 100 100 100 100 100 69 – 100 86 102 100 – – 152 101 100 144 – 139 100 100 100 100 100 100 100 100 100 – – 100 100 102 102 100 – 105 100 99 100 100 100 94 100 100 100 100 – 103 100 100 101 100 – 323 100 96 96 100

69 81 88 86 86 41 45 68 79 76 75 62 59 65 72 76 76 42 51 51 54 60 60 66 71 78 81 83 32

7 6 1 2 2 13 5 5 8 10 11 17 9 7 6 4 6 23 18 17 18 14 14 14 11 8 6 5 14 73 11 10 11 9 16 26 22 8 9 7 3 4 4 6 3 2 2 2 4 18 6 12 0 13

5 7 6 5 6 11 6 9 7 7 8 6 7 6 5 4 4 6 12 6 6 6 9 5 5 4 3 3 7 8 11 10 11 5 2 3 5 4 6 7 6 4 4 4 19 19 15 7 7 7 5 11 10 8 7

1 1 1 1 2 2 3 2 1 1 1 2 1 2 2 2 2 0 1 1 0 0 1 0 0 1 1 1 0 1 2 2 2 5 6 0 1 1 2 1 1 1 1 1 1 1 1 1 1 2 0 4 4 3 3

13 3 2 3 2 11 14 11 3 3 3 9 15 10 7 6 7 23 11 21 14 13 9 9 8 6 5 4 9 4 5 8 6 12 10 12 9 6 16 17 13 9 9 8 0 4 3 2 2 2 22 7 7 9 7

5 2 1 3 2 22 27 5 3 3 2 5 9 10 8 9 5 6 7 5 7 7 7 6 5 4 4 3 36 14 12 12 7 0 3 8 3 4 20 5 5 5 4 4 10 3 7 1 2 4 14 3 2 4 15

59 58 63 79 71 60 57 64 47 61 67 78 78 79 65 70 72 87 86 81 41 69 66 76 55

44 51 55 57 0 86 88 90 90 34 73 78 84 83

11 12 14 16 92 0 0 0 5 2 1 1 2

2 3 2 2 2 3 4 4 5 3 10 12 9 8

1 1 1 0 2 0 1 0 1 1 1 1 1

19 10 13 16 3 6 4 5 5 9 11 5 3 4

24 23 15 9 0 5 4 0 0 48 3 2 2 1

41 59 74 74 74 42 49 66 69 66 34 65 50 73 73 77 52 73 77 80 84 52 98 98 20 45

15 16 11 11 10 22 25 13 13 15 15 14 25 10 10 9 9 10 8 8 5 27 0 0 58 26

6 7 5 5 5 8 5 7 7 5 5 6 9 5 5 5 6 6 5 5 5 9 2 0 9 4

2 2 4 4 5 4 2 2 2 3 2 2 4 1 1 1 1 2 4 4 4 5 0 2 0 19

15 10 4 3 5 12 14 7 6 9 9 11 11 8 8 7 4 3 3 2 2 7 0 0 13 6

21 7 2 2 0 11 5 5 3 3 35 2 1 4 2 2 28 6 3 1 1 0 0 0 0 0

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

167

African region

        % OF COHORT TREATMENT SUCCESS (%) 1995–2011 a

YEAR

NUMBER NOTIFIED

SIZE OF COHORT

COHORT AS % NOTIFIED

CURED

COMPLETED

DIED

FAILED

DEFAULTED

NOT EVALUATED

Senegal

• 44 Seychelles

85 •

• 89 Sierra Leone

67 •

• 69 South Africa

88 •

• 58 Swaziland

79 •

•0 Togo

73 •

• 60 Uganda

85 •

• 44 United Republic of Tanzania

77 •

• 73 Zambia

88 •

• 70 Zimbabwe

88 •

• 53

81 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

5 421 5 823 6 722 7 883 7 688 7 765 6 11 8 11 9 2 1 454 2 472 4 370 6 092 6 898 7 435 23 112 75 967 125 460 139 468 132 107 129 770 660 1 823 2 187 3 498 3 011 2 408 887 984 1 798 2 267 2 096 2 087 13 631 17 246 20 559 23 113 23 456 25 614 19 955 24 049 25 264 24 895 24 769 24 115 10 038 12 927 14 857 12 995 12 639 12 046 8 965 14 392 13 155 10 195 11 654 12 596

5 421 5 823 6 722 7 883 7 855 7 898 9 11 11 7 9 1 315 2 296 4 370 6 083 6 897 7 351 28 209 86 276 134 782 139 458 134 250 132 867

2 187 3 498 3 011 2 499 856 1 796 2 267 2 096 2 075 15 301 13 874 20 559 23 113 23 456 25 614 19 955 23 923 25 324 24 895 24 373 24 218 5 957 7 014 14 857 12 995 12 639 12 711 9 702 14 392 12 860 10 195 11 654 12 596

100 100 100 100 102 102 150 100 – 100 78 450 90 93 100 100 100 99 122 114 107 100 102 102 – – 100 100 100 104 97 – 100 100 100 99 112 80 100 100 100 100 100 99 100 100 98 100 59 54 100 100 100 106 108 100 98 100 100 100

35 43 70 81 81 82 89 82 55 100 56 55 70 77 68 77 79 40 54 58 67 73 74

9 9 6 3 4 3 0 0 9 0 11 15 7 8 10 9 9 18 9 13 6 6 5

4 3 4 4 4 3 11 0 18 0 0 5 6 6 6 4 3 4 6 7 7 6 6

6 1 2 2 2 2 0 0 0 0 0 7 2 1 1 1 1 4 1 2 2 2 2

16 21 11 5 6 7 0 9 0 0 11 16 13 6 11 6 6 15 13 10 7 7 6

31 22 8 5 4 3 0 9 18 0 22 2 2 2 4 3 2 19 17 10 12 6 7

22 51 51 48 42 66 77 81 81 26 33 32 30 35 39 69 72 79 82 84 80 47 48 76 85 83 82 32 61 59 70 72 73

20 19 22 25 18 5 4 3 3 18 30 41 38 36 38 5 6 4 6 6 7 23 19 8 6 6 5 21 8 9 9 10 8

6 10 11 8 9 12 10 8 7 7 7 6 5 5 5 9 10 9 5 5 4 7 7 8 6 6 4 10 12 12 8 8 8

2 7 9 8 3 4 4 3 2 1 0 0 1 1 1 1 0 0 0 0 0 2 6 1 1 1 1 0 0 2 1 1 1

5 7 6 5 17 11 3 4 5 13 17 16 12 11 12 6 6 4 2 2 2 14 6 2 3 3 3 10 7 7 7 5 4

45 7 2 5 11 2 2 1 1 36 12 5 16 13 5 11 5 4 5 3 6 8 14 5 0 1 4 26 13 12 6 5 6

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

168

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%) 1995–2011 a

YEAR

NUMBER NOTIFIED

SIZE OF COHORT

COHORT AS % NOTIFIED

CURED

COMPLETED

DIED

FAILED

DEFAULTED

NOT EVALUATED

Algeria

•0 Angola

80 •

•0 Benin

0•

• 67 Botswana

84 •

•0 Burkina Faso

70 •

• 77 Burundi

75 •

• 46 Cameroon

85 •

•0 Cape Verde

70 •

•0 Central African Republic

37 •

•0 Chad

55 •

• 48 Comoros

60 •

• 43 Congo

0•

•0 Côte d'Ivoire

51 •

•0 Democratic Republic of the Congo

67 •

• 72 Equatorial Guinea

74 •

• 83 Eritrea

0•

•0 Ethiopia

69 •

• 79 Gabon

78 •

•0 a

40 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

451 547 713 612 691 610 134 540 2 871 3 863 7 776 4 444 68 280 337 271 205 262 147 1 239 548 1 122 1 072 868 45 178 327 608 552 484 181 225 116 238 332 315 236 251 1 590 1 569 1 494 1 661 30 34 33 27 27 188 291 629 421 345 203 515 676 708 847 7 5 3 6 11 78 819 407 451 516 507 649 893 980 1 436 1 519 1 459 2 891 2 637 6 065 8 666 8 604 7 919 1

512 713 553 598 588

1 613 3 044 2 272 4 444 139 282 341 270 203 262 395 219 1 126 1 027 998 26 166 272 509 475 481 265 92 238 332 315 347 1 611 1 516 1 489 1 661

34

27 353 291 629 284 275 92

676 704 847 7 5 5 5

187 477 418 235 528 507 980 1 436 1 519 1 459 1 202 5 448 7 193 5 583 4 572 6

44 67 53 67 124 207 208 147 343 2 777 3 119 3 544 4 898 4 621 44 257 655 558 833

44 41

157 120 147 193 1 556 3 116 2 942 3 934 1 796

150 611 147 200

– 94 100 90 87 96 – – 56 79 29 100 204 101 101 100 99 100 – 32 40 100 96 115 58 93 83 84 86 99 146 41 – 100 100 100 – 138 101 97 100 100 – – 100 – – 100 – – 100 100 67 80 45 – – 100 99 100 100 100 167 – – – – 23 117 93 46 104 – 57 100 100 100 100 42 – 90 83 65 58 600 – – 100 61 – – – – 76 58 100 56 56 100 83 80 39 – – 58 93 26 24

61 48 72 69 65

16 24 12 14 15

5 2 4 4 3

4 1 2 2 4

5 6 5 5 11

10 19 5 6 3

23 45 42 48 61 60 70 76 80 21 33 22 20 15 65 57 71 70 72 70 25 50 81 78 80 50 49 51 55 54

24 21 23 0 19 21 21 11 9 4 54 28 43 46 55 12 4 4 5 4 4 21 13 3 4 4 10 7 18 16 16

5 5 8 0 9 5 10 11 6 8 8 11 13 14 11 8 13 6 9 9 10 6 15 6 7 6 9 6 9 9 9

17 4 4 0 4 1 3 6 6 5 1 5 4 3 3 12 5 10 8 8 8 2 3 3 5 5 5 3 2 3 3

26 21 16 0 19 11 6 1 1 1 11 12 8 7 6 0 15 6 5 6 6 28 17 4 6 4 26 16 13 12 12

4 3 7 100 1 0 1 1 1 1 6 11 10 10 10 4 7 4 3 1 1 18 1 2 0 0 2 19 7 6 6

41

15

0

0

24

21

22 33 53 19 35 33 29

15 16 30 12 24 21 18

4 1 9 5 7 11 5

4 4 0 2 4 4 2

11 39 8 8 25 20 40

44 8 1 53 6 11 4

49 38 29 43 100 100 80

21 35 31 0 0 0 0

4 4 4 29 0 0 0

3 2 1 0 0 0 20

15 18 27 29 0 0 0

8 3 7 0 0 0 0

49 12 59 40 51 45 43 50 51 56 56 71 54 72 68 83

13 2 22 17 0 10 14 14 14 11 16 4 23 5 5 0

3 0 2 3 5 8 8 13 12 10 8 10 8 7 8 0

3 0 1 2 4 9 7 11 8 8 2 4 2 3 2 17

28 3 14 21 10 21 13 9 11 12 12 6 4 6 5 0

4 83 2 18 31 7 15 3 3 3 6 5 8 8 12 0

36 32

14 15

14 22

2 0

16 27

18 5

70 81 67 71 60 41 47 56 57

12 8 3 8 11 15 21 27 21

7 9 7 3 10 9 5 4 4

6 2 10 5 4 2 2 3 0

2 1 1 8 8 5 3 5 3

3 0 13 5 7 28 23 6 15

18 12 32 18

12 67 33 21

5 2 3 2

3 1 3 2

60 17 26 30

3 1 2 26

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

169

African region

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Gambia

• 69 Ghana

78 •

• 74 Guinea

77 •

• 67 Guinea-Bissau

64 •

•0 Kenya

68 •

• 72 Lesotho

82 •

•0 Liberia

58 •

•0 Madagascar

82 •

•0 Malawi

80 •

• 69 Mali

82 •

•0 Mauritania

69 •

•0 Mauritius

53 •

•0 Mozambique

80 •

•0 Namibia

0•

•0 Niger

80 •

•0 Nigeria

76 •

•0 Rwanda

82 •

•0 Sao Tome and Principe

80 •

•0 a

31 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

6 53 166 99 81 82 159 502 532 860 1 021 878 55 446 458 589 648 669 59 90 138 76 192 133 1 064 2 477 8 975 10 711 10 479 10 017 147 1 481 1 041 1 970 1 985 1 728 32 57 123 170 125 596 1 498 2 089 2 109 2 218 551 764 3 212 2 470 2 194 2 163 153 239 380 425 355 321 520 938 206 182 153 103 2 12 5 5 7 5 899 1 463 1 886 3 630 4 048 4 252 88 1 534 1 823 2 558 2 522 2 362 255 754 690 667 580 303 2 356 4 867 8 151 8 993 8 787 200 374 831 475 631 414 4 27 3 2 16

45

100 81 86 47 540 717 1 021 878 112 299 458 111 121

146 89 140 47 879 1 964 3 794 4 859 4 333 7 235

597 1 931 2 091 1 728 41 57 123 125

1 825 2 073 1 800 1 843 492 797 1 093 788 750 670

379 390 345 321

182 153 133 2 5 5 7 5 1 594 1 855

604 2 009 1 546 2 548 2 361

667 661 580 1 848 3 662 8 151 8 993 8 787 296 506 448 446 415

0 3 12 16

750 – – 101 100 105 30 – 102 83 100 100 204 67 100 – 17 18 – – 106 117 73 35 83 79 42 45 41 72 – – 57 98 105 100 – 128 100 100 – 100 – – 122 99 85 83 89 104 34 32 34 31 – – 100 92 97 100 – – – 100 100 129 – 17 100 100 100 100 – 109 98 – – – – 39 110 60 101 100 – – – 97 99 100 – 78 75 100 100 100 – 79 61 94 71 100 – – 0 100 600 100

69

0

11

2

11

7

67 30 74 68 40 50 38 40 44 63 45 55 56

5 6 3 6 8 26 39 38 23 8 16 14 7

17 6 13 6 6 10 12 12 3 5 10 8 8

2 1 3 9 3 2 2 3 9 3 7 5 3

7 0 3 9 11 3 2 4 13 8 13 13 16

2 57 2 2 32 10 7 5 8 13 11 6 9

44 30 23 47 61 65 68 70 73 77

34 34 31 21 11 11 9 8 6 5

8 2 10 13 9 2 10 8 6 4

0 0 0 2 1 8 1 4 3 4

8 29 27 9 10 10 7 7 8 7

7 4 9 9 8 4 5 4 4 3

20 16 17 39 75 70 72

71 42 42 41 22 9 15 10

11 17 16 18 12 2 8 4

2 2 2 2 7 4 12

2 4 8 10 20 9 2 2

14 15 16 12 0 5 0 0

65 62 71 75 65 61 74 83 77 79

7 11 3 4 4 5 1 2 1 3

7 7 8 7 22 23 19 9 10 10

2 2 2 1 2 1 1 2 3 1

12 8 9 8 1 6 3 2 1 3

6 10 8 4 6 3 3 1 9 5

67 67 87 64

6 8 12 5

10 9 1 7

5 6 0 4

10 7 0 4

3 3 0 15

48 46 43 0 60 60 86 80 69 69

13 13 10 0 20 0 0 0 3 1

3 5 10 50 20 0 0 11 15

1 2 2 50 0 0 0 4 2

20 15 17 0 20 20 14 20 11 10

14 20 19 0 0 0 0 0 2 3

41 24 58 63 67

14 29 15 15 13

8 11 9 6 5

6 3 9 10 9

13 13 6 5 5

17 22 3 2 0

64 64 62 58 48 48 43 42 49 56 62 65 72

12 11 14 13 18 33 39 40 5 9 10 9 8

9 10 6 7 2 6 4 4 14 15 11 9 10

4 3 5 7 11 2 4 4 1 3 7 6 7

5 5 10 11 20 7 7 6 5 4 4 4 2

6 7 4 4 1 4 3 4 25 13 6 6 1

33 0 0

33 50 31

0 8 6

33 17 38

0 8 25

0 17 0

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

170

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Senegal

• 56 Seychelles

68 •

•0 Sierra Leone

0•

• 87 South Africa

70 •

•0 Swaziland

66 •

•0 Togo

59 •

• 33 Uganda

78 •

•0 United Republic of Tanzania

71 •

• 76 Zambia

82 •

•0 Zimbabwe

0•

•0

78 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

563 1 056 920 1 112 1 029 1 119 0 0 2 0 0 0 41 441 330 467 547 375 179 56 202 60 588 65 916 60 580 45 915 489 1 249 470 1 474 1 440 1 149 93 133 179 214 240 213 955 1 505 2 430 4 014 3 952 4 014 1 335 1 772 5 032 4 217 3 785 2 870 243 1 455 5 496 2 485 6 310 6 636 737 5 941 4 685 4 685 4 345

634 931 920 889 1 029 914

0 0 0 69 328 466 543 362 24 847 64 923 34 122 60 580 31 168

1 113 1 474 446 1 151 93 128 237 240 210 1 209 2 856 2 764 2 814 1 455 3 356 5 067 4 217 3 714 2 936 894 5 496 5 444

1 063 4 667 1 203 1 629 1 772

113 88 100 80 100 82 – – – – – – 168 – 99 100 99 97 – 44 107 52 100 68 – – 237 100 31 100 100 – 72 111 100 99 – 80 – 71 70 70 109 189 101 100 98 102 – 61 100 219 – – – – 79 26 35 41

45 40 58 67 56 64

11 8 5 4 4 4

5 4 8 7 6 5

10 3 5 5 3 3

25 23 13 10 7 14

4 23 11 8 24 9

72 68 56 65 63 43 29 53 31 59

14 7 13 11 7 8 29 8 4 7

3 6 10 5 6 8 11 10 5 9

4 3 3 2 3 3 2 3 2 3

4 15 15 15 15 19 16 12 7 12

1 1 4 2 5 19 13 15 52 10

7 14 32 12 16 73 68 78 75 34 31 31 38 66 49 37 34 37 38 52 24 33

21 41 18 46 17 2 3 4 3 30 39 34 33 10 24 39 49 47 43 15 60 53

11 17 17 15 5 14 18 6 8 13 7 8 8 11 14 13 8 9 7 11 9 9

3 9 21 8 4 4 3 4 4 0 1 1 2 1 1 1 1 1 1 4 1 1

5 10 7 5 19 7 4 8 8 13 15 12 14 8 6 4 3 3 3 5 3 4

54 8 6 13 38 0 5 1 1 10 7 13 5 4 6 6 5 4 7 12 4 0

51 13 72 63 63

14 46 8 11 15

17 16 11 13 11

1 0 0 3 4

8 13 5 5 4

9 11 4 5 3

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

171

African region

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS PATIENTS NOTIFIED (NEW AND RETREAT) 21 501 22 530 21 597 22 082 38 317 49 987 48 926 53 426 3 457 3 841 4 320 4 075 10 104 7 632 6 733 6 223 3 645 5 135 5 543 5 405 6 627 7 719 6 828 7 016 22 073 24 552 25 126 25 360 305 365 390 425 3 338 6 760 5 724 8 283 6 505 9 697 10 774 10 800 112 119 122 9 961 10 321 11 143 11 512 20 026 23 210 22 920 24 222 99 558 118 636 114 290 112 499 853 913 3 612 2 991 3 093 3 254 125 135 156 928 159 017 147 592 2 611 4 180 4 916 5 415 2 120 2 030 2 333 2 387 12 124 15 145 15 840 15 207 7 090 11 324 11 606 11 641 1 816 2 259 2 070 1 950 108 401 106 083 103 981 99 149 11 404 13 138 12 785 11 971 3 456 6 668 7 965 8 132 19 475 25 106 26 722 26 209 % OF HIV% OF HIVNUMBER OF POSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Algeria 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS

% OF TESTED TB PATIENTS HIV-POSITIVE

– Angola

–

– Benin

23 •

• 15 Botswana

98 •

• 23 Burkina Faso

95 •

• 33 Burundi

84 •

4.9 10 23 15 98 99 98 23 81 97 95 33 93 89 84 71 71 82 0 78 81 82 98 90 89 39 33 46 39 38 44 100 3.4 3.3 40 20 17 20 73 80 85 1.9 24 27 31 92 100

2 434 5 107 12 022 503 3 774 4 259 4 006 2 291 6 147 6 545 5 940 1 213 4 761 4 944 4 567 5 511 4 817 5 734 0 19 117 20 280 20 810 298 352 378 2 638 1 890 3 839 3 801 4 124 4 766 112 119 4 4 4 106 2 247 1 979 4 079 16 991 18 297 20 663 1 885 28 997 30 636 35 097 786 911

1 620 789 1 149 57 592 727 637 1 829 4 018 4 129 3 759 559 839 829 671 1 260 1 036 1 076 0 8 314 7 731 7 747 14 47 45 862 733 1 483 663 959 960 2 0 4 4 757 687 653 1 551 4 112 4 820 5 482 386 5 273 4 942 5 748 225 234

67 15 9.6 11 16 17 16 80 65 63 63 46 18 17 15 23 22 19 43 38 37 4.7 13 12 33 39 39 17 23 20 1.8 0 100 100 18 31 33 38 24 26 27 20 18 16 16 29 26

43 100 100 97 98

43 100 100 57 74

1 100

339 18 762 738

79 62 90 68 98 97 96 95 95 94 81 87 83

43 53 65 32 60 70 75 40 48 55 51 62 55 100

0 0 0 1 373

– Cameroon

82 •

•0 Cape Verde

82 •

• 98 Central African Republic – Chad

89 •

44 0 12 28 53 39 100 100 100 2.9 24 20 38 80 80 75 74 24 54 61 85

98 62 9.3 20 45 43 65 100

123

46 •

– Comoros

44 •

0 100 100 2.9 26 23 14 27 36 44 0.78 9.3 23 40 31 21 2

• 100 Congo

3•

– Côte d'Ivoire

17 •

• 20 Democratic Republic of the Congo •2 Equatorial Guinea – Eritrea

85 •

31 •

–

0 164 1 321 9 809 5 442 9 819 185 667 578 852 224 302 340 2 676 2 907 2 812 1 483 1 670 1 859 110 396 431 517 8 954 40 069 38 175 35 837 127 8 459 8 519 7 878 14 283 454 772 16 39 40 19 8.6 41 15 8.4 10 100 59 26 16 11 16 40 26 23 24 26 26 25 55 38 42 39 57 41 39 39 81 77 75 75 12 8 10 14 0.91 0.24 0.26 0.13 88 69 62 37 100 52 29 39 39 82 52 66 93 97 100 77 72 72 87 72 83 100 0 0 44 100 97 98 79 96 95 97 0 8.5 26 90 46 48 37 18 28 37 41 49 49 30 0 0 17 48 64 74 27 68 53 0 9.3 15 36 95 1 983 6 636 30 816 30 395 0

– Ethiopia

59 •

•3 Gabon

65 •

•7 Gambia

100 •

59 2.6 43 41 65 7.1 27 46 100 97 74 78 7 67 79 78 51 56 65 11 46 50 68 14 91 93 94 1.4 84 89 88 3.3 53 55 70 9 65 58 54

1 913 3 211 66 955 65 140 96 245 185 1 130 2 252 5 415 1 962 1 726 1 859 844 10 147 12 587 11 825 5 776 6 548 7 575 200 1 046 1 037 1 322 15 658 96 930 97 136 92 890 156 11 005 11 413 10 476 114 3 533 4 355 5 661 1 759 16 439 15 532 14 146

– Ghana

78 •

•7 Guinea

78 •

– Guinea-Bissau

65 •

0

• 11 Kenya

68 •

0

• 14 Lesotho

94 •

•1 Liberia

88 •

16 403

•3 Madagascar

70 •

•9

54 •

172

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 44 88 83 93 42 35 28 0.45 24 0.66 91 95 93 96 88 91 94 16 76 84 89 48 44 46 10 79 81 84 65 98 97 99 100 92 100 99 69 76 78 100 100 100 74 78 87 22 54 83 84 86 92 95 0 77 84 91 25 81 80 86 2.5 90 88 82 2 84 100 100 0 86 90 88 12 243 19 855 17 334 19 009 2 303 1 963 1 544 10 608 12 115 117 108 125 40 554 43 096 47 960 2 547 9 534 10 042 9 927 4 925 4 710 5 166 6 897 71 844 75 772 82 641 5 003 6 914 6 560 6 131 152 112 146 126 8 018 8 757 10 048 17 21 21 9 718 10 159 11 655 67 988 213 006 322 732 294 196 9 536 8 419 7 363 0 2 242 2 513 2 657 10 555 36 742 39 394 40 581 1 613 56 849 53 842 52 499 1 082 40 704 48 594 45 269 0 41 062 37 029 34 212 PATIENTS NOTIFIED (NEW AND RETREAT) 27 610 22 536 20 854 20 463 4 884 5 448 5 573 5 602 2 218 2 489 1 820 2 636 127 123 116 130 33 718 46 174 47 452 50 827 15 894 12 625 11 938 11 145 8 224 10 345 10 714 11 207 66 848 90 447 93 050 97 853 7 680 7 065 6 784 6 208 152 122 146 127 10 120 11 591 11 588 12 819 14 17 21 21 6 930 13 195 12 943 13 354 302 467 396 554 389 974 349 582 8 864 11 146 9 180 7 739 2 635 2 897 2 980 2 912 41 809 45 546 49 018 47 211 64 200 63 453 61 148 63 892 53 267 48 616 48 594 45 277 54 891 47 557 41 305 38 720 % OF HIV% OF HIVNUMBER OF POSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT 92 94 89 88 75 72 42 49 46 60 81 52 69 100 61 100 100 100 100 100 97 91 98 93 98 99 43 37 6.6 31 59 68 80 15 97 97 99 0 92 100 100 85 85 90 100 100 75 67 6.4 25 26 100 74 77 74 93 95 98 72 77 87 25 90 93 94 61 92 95 96 75 87 93 88 94 26 50 75 62 90 25 29 55 44 54 72 34 0 4.8 16 33 43 56 13 72 75 0 54 100 100 37 48 64 100 100 100 100 19 28 69 33 54 46 54 35 51 66 49 67 76 10 24 32 49 22 35 38 54 68 48 53 60 45 60 18 13 164 17 064 17 317 13 989 14 428 11 906

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Malawi 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS 8 447 12 476 10 341 11 296 416 404 425 0 90 12 2 8 8 10 24 574 26 538 27 979 1 465 5 227 4 990 4 688 152 405 334 431 1 241 17 736 19 553 19 342 2 276 2 199 1 855 1 601 5 13 15 18 776 877 882 2 1 4 3 976 902 1 343 35 299 128 457 211 128 190 093 7 788 6 480 5 666 0 632 667 625 7 523 19 836 20 725 20 376 841 21 662 20 632 20 269 614 26 571 26 737 24 309 0 31 849 27 562 23 957

% OF TESTED TB PATIENTS HIV-POSITIVE 69 63 60 59 18 21 28 0 15 100 1.7 6.8 7.4 8 61 62 58 58 55 50 47 8.2 7.1 8.3 18 25 26 23 45 32 28 26 3.3 12 10 14 9.7 10 8.8 5.9 19 14 10 8.9 12 52 60 65 65 82 77 77 28 27 24 71 54 53 50 52 38 38 39 57 65 55 54 78 74 70

• 44 Mali

93 •

20 542 0

– Mauritania

28 •

0

•0 Mauritius

–

• 91 Mozambique

96 •

– Namibia

94 •

• 16 Niger

89 •

– Nigeria

46 •

• 10 Rwanda

84 •

1 750 1 107 2 257

• 65 Sao Tome and Principe • 100 Senegal

99 •

99 •

0 0 0

– Seychelles

78 •

426 0 0

– Sierra Leone

100 •

– South Africa

87 •

• 22 Swaziland

84 •

1 062 1 466 146 247 372 994 369 747

– Togo

95 •

1 934 0

•0 Uganda

91 •

• 25 United Republic of Tanzania •3 Zambia

86 •

82 •

•2 Zimbabwe

100 •

0

•0

88 •

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

173

African region

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 809 b

YEAR Algeria 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

TOTAL CONFIRMED CASES OF MDR-TB 74 56 a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB 9.1 – – – – – 0.13 – 1.1 3.5 0 0.78 – 11 4.5 14 – <0.1 <0.1 0.20 – 0.48 0 <0.1 – 0 – 0 – – 0 0 – 0.25 0 – – 0 0 0 – – – – – – – – 0 0 <0.1 0 – – <0.1 <0.1 – 0 – – – – – – – <0.1 0.15 0.99 – – – – – – – 0 0.62 – 0 0 3.9 <0.1 0.12 – – – – – 0 – 0.25 0.21 – – – 0.15 – 0 – – – 0.36 <0.1 <0.1 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

180 (69–290) 3 40 45 28 15 20 25 106 46 53 3 31 42 38 24 6 24 35 63 153 0 0 0 9 15 28 3 0 0

130 (56–250)

52 (6.5–170)

Angola

29 1 700 (780–2 500) 800 (44–1 500) 31 103 0 26 488 151 349 1 1 7 22 0 1 0 670 (140–1 200) 510 (2.0–1 000) 0

860 (330–1 400)

Benin

54 (26–83)

17 (2.1–70)

37 (23–55)

Botswana

140 (94–190)

120 (70–160)

29 (11–47)

Burkina Faso

150 (71–240)

79 (4.4–150)

75 (29–120)

Burundi

150 (27–280)

120 (0.48–240)

31 (11–52)

Cameroon

160 (57–270)

Cape Verde

9.8 (4.0–16)

6.1 (0.34–12)

0 0 9 0

3.6 (1.4–5.9)

Central African Republic

130 (36–220)

28 (0.72–160) 0 0 0

97 (37–190)

Chad

320 (150–490)

160 (8.8–300)

160 (63–260)

Comoros

0 0

2.5 (0.92–4.0)

1.7 (0.10–3.2)

0.77 (0.30–1.2)

Congo

250 (43–450) 47 50 30 221 87 121 81 0 3 –

200 (0.79–400) 0 0 1 0

49 (17–81)

Côte d'Ivoire

580 (270–890)

440 (190–850)

140 (49–240)

Democratic Republic of the Congo Equatorial Guinea

2 900 (670–5 100)

2 100 (8.4–4 200)

22 12 0

760 (260–1 300)

–

–

Eritrea

11 0 140 212 284 0 0 0 0 0 1 4 7 20 20 31 78 69

79 (38–120)

35 (1.9–66) 42 73 469

44 (17–71)

Ethiopia

2 000 (1 200–2 900)

1 600 (830–2 700)

480 (230–870)

Gabon

170 (57–280)

100 (0.41–200)

67 (23–110)

Gambia

9.9 (0–29)

9.9 (0.25–54)

Ghana

0 50 0 0 215 5 8

0 (0–26)

390 (170–620)

240 (13–440)

160 (61–260)

Guinea

250 (130–380)

47 (9.8–140)

200 (100–340)

Guinea-Bissau

Kenya

2 6 44 112 166 225 117 64 46 0 6 3 9 10

45 (15–75)

33 (1.8–63) 0 92 78

12 (4.6–19)

2 800 (840–4 800)

1 800 (7.4–3 700)

980 (340–1 600)

Lesotho

170 (36–300)

77 (16–220)

5 0

94 (20–260)

Liberia

130 (32–230)

110 (6.3–210) 60 9 7

18 (7.0–29)

Madagascar

170 (32–310)

94 (26–240)

76 (9.3–260)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB 164 23 – – – – – – 45 1.0 107 32 6 2.9 152 58 110 39 – 286 27 90 10 149 34 126 39 117 21 68 14 72 19 – 2 0.60 6 1.9 23 7.5 – 35 2.3 – 80 5.0 – – 0 0 0 0 – 0 0 56 16 – – 0 0 0 0 0 0 – – – – – – – – 0 0 72 4.7 29 2.0 365 26 – 100 1.2 160 2.0 95 1.3 – 0 0 – – – – – – – 510 10 139 3.0 180 4.4 – – – – – – – 0 0 2 0.38 21 2.1 61 6.9 44 5.3 34 7.4 26 4.0 26 3.9 – – – – – 1829 20 706 6.7 1195 12 1183 12 – – – 28 1.7 – 0 0 – – – 24 1.1 64 2.9 63 3.2

a b

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). BACT+VE = bacteriologically positive cases.

174

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 871 102 0 0 0 23 161 3 1 114 105 100 121 113 80 206 205 b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB – 10 1.5 0 0 0 – 0.62 12 – 0.30 <0.1 100 100 100 100 0.63 0.39 1.1 0.98 – – – – – 0 <0.1 0 – <0.1 <0.1 <0.1 1.4 4.0 – – – – 1.9 27 – 0.53 0.18 0.30 – – 0 82 – – – – – – – – – 2.9 – – – – 4.1 0 – 1.5 1.2 0.79 0.60 0.44 0.34 2.5 – – – – – – 0 3.0 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

Malawi

Mali

Mauritania

Mauritius

Mozambique

Namibia

Niger

Nigeria

Rwanda

Sao Tome and Principe

Senegal

Seychelles

Sierra Leone

South Africa

Swaziland

Togo

Uganda

United Republic of Tanzania

Zambia

Zimbabwe

2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

9 40 26 27 2 12 10 12 11 35 8 1 0 2 1 0 115 165 283 266 214 192 210 39 18 35 21 95 107 35 90 76 58 0 4 8 38 50 27 0 0 0

96 (45–150)

56 (18–130)

40 (27–57)

140 (60–210)

76 (4.2–140)

60 (23–96)

59 (26–92)

34 (1.9–64)

25 (9.8–41)

0 (0–0)

0 (0–3.6)

0 (0–2.4)

2 000 (1 300–2 700)

1 400 (900–2 000)

540 (0–1 100)

630 (510–750)

260 (190–350) 0 1 0 27 12 11 57 171

370 (290–470)

270 (110–420)

160 (9.0–300)

110 (42–180)

3 600 (2 700–4 500)

2 500 (1 800–3 400)

1 100 (770–1 500)

240 (170–310)

180 (120–270)

63 (51–76)

15 (11–19)

1.7 (0.10–3.3)

2 16 41 14 25

13 (7.1–15)

400 (170–620)

220 (70–500)

180 (76–340)

0 (0–0)

0 (0–3.9)

0 14

0 (0–1.7)

8 220 (0–460) 2000 7386 10085 15419 326 332 280 2 4 2 46 93 71 89 10 34 68 42 100 (2.7–570)

120 (26–280)

8 100 (6 900–9 400)

4 600 (3 700–5 800) 148

3 500 (2 800–4 300)

730 (560–890)

430 (270–590)

290 (250–340)

77 (35–120)

41 (2.3–78)

86 0 358 316 196 276 201 83 639

36 (14–58)

1 000 (660–1 300)

540 (230–860)

470 (260–750)

500 (13–1 000)

500 (140–1 300)

0 (0–160)

80 17 118 149

620 (290–940)

98 (12–350)

520 (260–900)

930 (430–1 400)

570 (300–960)

0 360

360 (76–970)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB 917 29 449 20 552 26 27 3.3 0 0 12 3.4 – 39 13 30 15 – 4 3.9 – 3 60 7 100 5 100 4 100 305 16 251 6.2 443 10 243 5.4 – – – – – 47 7.0 21 3.6 35 6.2 – 19 0.21 76 0.86 94 1.2 0 0 431 68 – – – – 2 12 8 53 – 66 6.4 97 8.7 113 10 – – 1 – 2 100 – – – – – – – – – 505 35 – – – – 83 39 2 1.1 – 356 9.0 360 9.0 748 19 405 8.0 246 6.5 17 0.59 108 3.9 – – – – – – 0 0 258 6.0

a b

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). BACT+VE = bacteriologically positive cases.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

175

African region

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

Algeria

Angola

Benin

Botswana

Burkina Faso

Burundi

Cameroon

Cape Verde

Central African Republic

Chad

Comoros

Congo

Côte d'Ivoire

Democratic Republic of the Congo

Equatorial Guinea

Eritrea

Ethiopia

Gabon

Gambia

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

59 53 52 42 29 386 186 520 448 501 390 14 19 21 18 21 23 25 27 45 36 40 4 12 18 20 22 25 5 34 56 37 45 20 41 134 106 114 108

927 1 309 1 203 1 147 1 102 724 999 2 549 2 900 3 000 2 804 186 277 306 314 320 314 185 260 256 220 207 67 91 181 231 265 277 128 352 481 484 447 208 518 1 472 1 497 1 580 1 597

1 516 1 841 1 669 1 513 1 467 562 1 003 2 797 3 584 3 792 3 627 352 428 595 631 650 595 605 563 590 464 394 133 274 430 620 708 769 238 591 773 743 801 569 842 2 482 2 750 2 931 2 900

610 919 825 881 857 346 912 1 918 2 415 2 386 2 529 306 327 396 443 497 524 488 506 477 354 333 124 252 370 493 582 631 224 525 651 620 667 323 584 1 766 1 996 2 139 2 182

491 473 513 483 464 224 482 1 255 1 424 1 395 1 427 176 213 270 267 353 329 267 272 239 206 190 62 133 273 328 375 423 73 372 570 504 461 287 284 1 035 1 314 1 283 1 304

234 314 392 345 354 155 312 665 691 680 732 101 103 135 164 210 179 135 135 137 110 79 48 68 144 224 262 250 32 111 270 235 233 204 130 463 559 625 658

299 426 397 347 349 14 194 461 355 455 424 92 74 87 85 107 121 96 97 107 94 75 29 65 113 173 196 198 19 55 157 98 103 164 75 289 329 361 375

0

0

0 0 0

36 102 79 58 60 371 247 704 558 708 592 26 36 25 29 41 39 37 45 68 65 63 7 7 15 33 31 27 19 46 78 56 74 9 63 226 172 178 184

1 005 1 044 1 086 1 050 917 707 1 142 2 926 2 763 2 731 2 501 148 239 249 265 288 264 335 321 338 286 267 76 59 125 158 163 160 109 298 390 345 338 185 368 1 467 1 474 1 461 1 417

1 293 820 826 787 773 443 1 091 2 682 2 594 2 563 2 540 197 275 331 382 385 346 469 491 509 421 402 53 128 248 259 277 288 124 399 421 374 367 313 530 1 788 2 031 2 022 2 053

746 389 417 383 382 264 844 1 797 1 688 1 683 1 617 118 149 145 200 246 221 262 253 301 211 193 39 101 174 198 221 191 89 288 332 263 283 223 293 1 028 1 121 1 177 1 177

314 270 251 211 198 248 417 1 138 958 1 006 1 028 69 76 89 98 119 105 98 97 119 105 109 26 45 109 124 146 156 33 122 225 180 162 153 139 503 642 581 579

208 229 222 202 229 130 200 581 482 457 529 32 45 51 42 42 65 57 55 56 48 43 11 38 54 97 110 106 12 36 99 81 64 106 60 205 290 281 295

312 465 367 341 329 18 120 417 286 346 384 22 25 39 35 52 46 36 48 53 49 31 10 14 40 83 92 82 4 33 87 40 30 93 33 143 183 194 187

0

0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0 38 29 78 70 73

22 17 29 162 40 379 362 502

23 43 36 356 1 136 633 576 799

26 35 34 206 160 468 467 660

9 31 24 120 26 251 269 360

2 3 8 40 35 135 119 158

8 3 2 18 15 63 59 92 0 0

2 4 0 39 30 88 96 101

9 14 19 233 32 367 382 511

16 15 13 350 420 576 530 689

4 4 9 145 145 319 289 370

5 6 8 57 30 155 162 191

3 3 3 21 40 73 62 96

6 4 4 9 15 44 26 39 0 0

1 4

8 6

25 76 92 68 0 0 0 0 16

194 382 469 405 18 18 12 10 9 265

535 850 951 842 13 7 9 13 15 409

409 666 764 634 9 14 6 9 8 221

229 379 418 376 7 9 4 5 4 73

123 173 184 210 8 3 2 2 6 44

82 99 121 88 4 4 4 5 6 15

0 0 0

28 59 84 51 1 1 2 2 1 17

148 274 296 273 13 9 10 8 5 296

298 413 438 403 9 6 7 4 7 353

211 263 298 227 8 12 4 2 5 167

148 158 166 135 6 1 8 1 1 61

59 79 109 91 5 2 3 0 1 38

27 44 44 46 2 1 8 1 3 11

0 0 0

0

0

41 58 46 41 128 159 189 163 373 485 1 321 1 707 1 579 1 439 8

435 453 563 989 1 346 1 751 1 743 1 743 1 572 4 048 6 675 6 859 6 640 6 612 15

672 705 716 2 092 2 449 2 858 3 043 3 087 2 382 5 833 9 808 10 412 9 872 10 274 45

424 462 519 1 344 1 606 1 882 1 852 2 017 1 890 4 151 7 577 9 134 8 932 9 361 37

203 222 276 759 888 1 010 1 072 1 032 1 184 2 549 5 022 6 464 6 415 6 612 15

77 80 113 283 422 505 601 552 634 1 295 2 637 3 641 3 584 3 698 11

55 76 72 130 385 375 348 430 289 602 1 499 1 907 1 911 1 941 7

0

49 72 63 99 193 246 244 204 331 718 1 695 1 987 1 800 1 699 2

409 408 438 810 1 280 1 431 1 358 1 306 1 223 4 422 7 570 7 199 6 802 6 598 18

510 463 482 813 1 756 1 819 1 838 1 870 1 532 5 146 8 501 9 120 8 742 8 406 28

296 332 349 497 989 1 051 1 044 1 120 1 232 3 309 5 832 6 721 6 541 6 471 20

152 200 171 273 528 531 560 536 863 1 724 3 898 4 579 4 537 4 131 4

70 88 68 105 232 304 301 337 427 855 2 054 2 612 2 671 2 625 7

56 97 108 19 201 209 223 263 137 351 951 1 311 1 295 1 257 1

0

0

0

10 11

71 77

80 90

59 89

35 59

16 22

10 12

0 0

13 15

80 76

57 81

45 46

26 21

9 9

6 3

0 0

9 9 10 0 2 247 915 1 109 1 582 1 847 3 13 15 34 42 3 13 9 14 7

70 68 93 84 1 221 5 095 6 726 7 400 7 835 45 123 145 240 236 68 133 194 183 210

75 73 109 105 1 017 5 187 6 181 7 785 9 246 74 199 223 269 286 181 292 314 271 331

57 50 81 90 541 3 082 3 454 4 451 3 881 80 140 208 229 228 88 206 184 181 191

32 45 51 62 276 1 495 1 985 2 746 2 771 54 70 130 144 166 72 62 141 136 107

25 51 37 39 142 610 1 027 1 473 1 218 30 38 89 86 101 29 53 68 87 80

20 39 60 51 51 397 475 822 771 15 25 91 66 41 24 44 39 56 54

0 0

10 8 3 4 283 1 037 1 326 1 608 1 983 9 19 13 25 29 4 2 6 16 16

100 67 88 86 908 4 699 5 885 5 708 6 570 47 128 110 177 185 39 84 104 103 123

87 127 111 98 781 4 424 5 663 6 480 7 917 54 123 164 188 165 61 87 121 112 106

71 72 79 74 382 2 105 2 730 3 439 3 069 28 88 122 125 109 44 64 71 88 89

21 39 43 45 152 976 1 296 1 950 1 564 25 29 100 74 78 25 38 35 63 41

12 21 31 19 64 366 513 855 719 19 29 86 44 45 12 22 40 32 32

8 18 36 20 15 122 155 335 303 3 18 64 39 34 8 27 18 33 42

0 0

0 0 0

0 0 0

0 0 0

0 0 0

MALE:FEMALE RATIO – 1.1 1.6 1.6 1.6 1.6 1.1 1.0 0.99 1.3 1.3 1.3 2.0 1.7 1.9 1.8 1.8 1.9 – 1.4 1.4 1.3 1.3 1.2 2.1 2.3 2.0 2.2 2.3 2.5 1.8 – 1.7 1.8 2.0 2.1 1.6 1.7 1.4 1.4 1.5 1.5 – – 2.0 – 2.6 2.4 1.1 – 2.0 1.2 1.2 1.3 – – 1.7 2.0 2.1 2.1 1.3 1.7 0.88 – 2.4 2.1 1.1 – – 1.2 1.2 1.4 2.2 – 1.4 1.5 1.6 1.6 1.4 1.1 1.1 1.2 1.2 1.3 1.7 – – 1.2 1.4 – – 0.93 0.95 1.1 – 1.3 1.4 1.2 1.2 1.3 1.2 – 1.6 – 1.4 1.4 1.6 1.7 2.4 – 2.5 2.4 2.1 2.2

176

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO 1.7 1.8 2.0 2.0 1.9 2.1 2.0 2.0 1.8 1.6 2.0 2.1 – 2.0 1.6 1.5 1.6 1.6 1.6 1.4 1.3 1.6 1.6 1.6 2.4 2.0 0.72 1.4 1.3 1.2 – 1.2 1.4 1.1 1.4 1.2 1.4 – 1.5 1.4 1.5 1.5 1.2 1.1 1.1 1.3 1.3 1.4 1.7 2.2 2.0 2.1 2.0 2.2 – – – 2.6 2.5 2.4 2.3 1.9 2.9 2.6 2.0 2.0 1.4 – – – – – 2.5 1.4 1.3 1.3 1.3 1.4 – 1.9 2.6 2.9 2.8 3.1 1.0 1.2 1.4 1.5 1.6 1.6 – 2.1 1.6 1.7 1.8 2.0 – 0.73 1.7 2.4 1.8 1.6 2.3 2.1 2.2 2.3 2.2 2.3 3.5 2.7 3.0 3.5 1.0 1.2

Ghana

Guinea

Guinea-Bissau

Kenya

Lesotho

Liberia

Madagascar

Malawi

Mali

Mauritania

Mauritius

Mozambique

Namibia

Niger

Nigeria

Rwanda

Sao Tome and Principe

Senegal

Seychelles

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

42 73 49 63 50 30 18 39 51 61 45 28 2 14 18 6 7 154 264 359 357 356 393 9 8 32 16 19 15 12 26 90 67 65 79 98 204 146 177 25 50 58 50 70 52 27 23 26 94 25 25

223 550 592 570 550 559 244 551 749 679 1 051 761 52 116 164 140 145 2 072 3 739 4 790 4 698 4 773 4 893 108 165 395 222 179 204 133 240 338 382 382 791 1 159 1 721 1 807 1 725 493 653 622 565 519 495 72 206 350 381 370 405

397 1 266 1 201 1 146 1 127 1 051 538 860 1 165 877 1 537 1 104 92 167 219 230 262 3 073 6 653 8 832 7 945 8 376 8 149 214 458 695 607 584 580 196 352 621 595 627 1 289 1 867 1 621 2 764 2 474 1 195 1 476 1 653 1 509 1 486 1 537 357 430 628 707 772 731

398 1 115 1 311 1 301 1 328 1 271 357 570 778 982 955 791 80 153 183 181 183 1 675 3 548 5 069 5 077 5 201 5 302 256 517 397 497 493 427 127 333 510 727 667 1 173 1 732 2 525 2 495 2 460 833 1 113 1 031 985 1 050 1 051 294 396 539 526 515 547

302 811 944 1 030 955 921 189 282 463 876 541 383 64 130 141 104 115 920 1 630 2 521 2 509 2 660 2 493 189 395 148 364 329 295 52 155 295 440 406 630 1 349 1 782 1 938 1 927 519 585 549 485 440 471 181 297 365 354 352 377

190 495 462 540 491 512 98 203 195 565 293 190 39 72 80 65 63 485 630 1 031 994 1 045 1 099 96 198 82 244 245 196 17 74 114 194 129 423 582 960 1 044 1 059 215 245 279 275 238 292 138 235 263 227 267 257

112 426 414 447 456 462 61 103 130 289 197 120 19 42 43 36 38 296 414 590 658 665 669 88 76 37 133 121 114 26 65 21 87 83 242 333 485 522 490 89 114 157 187 201 204 102 144 193 207 230 211

0

40 74 68 64 52 51 28 66 65 51 85 49 4 13 30 12 7 187 416 577 549 629 603 14 11 19 27 23 30 21 37 254 67 61 100 150 323 252 242 65 66 84 103 79 71 31 14 33 31 42 34

199 456 450 446 470 418 202 314 594 549 709 505 30 78 100 119 121 1 802 3 916 5 144 4 044 4 183 4 097 106 222 226 283 311 309 140 232 339 329 354 799 1 012 1 621 1 726 1 720 802 1 038 913 610 601 538 132 174 208 265 255 253

272 791 693 667 699 563 255 446 583 739 688 509 46 110 161 122 157 1 759 4 363 6 521 5 112 4 917 4 975 125 336 721 597 572 571 149 297 488 433 535 1 108 1 451 1 943 2 031 1 848 1 028 1 481 1 598 1 196 1 119 1 057 184 232 348 337 393 344

205 566 527 560 614 468 153 245 354 751 432 323 47 92 133 90 98 741 1 874 2 781 2 372 2 434 2 363 71 195 616 329 307 296 88 171 259 517 605 744 1 047 1 376 1 503 1 420 573 831 859 661 660 609 128 152 245 247 223 239

122 338 366 369 390 332 64 114 203 405 219 134 24 82 80 56 56 411 831 1 266 1 056 1 025 993 49 83 494 169 185 143 28 108 171 285 292 340 614 946 978 914 294 401 386 314 283 298 107 106 152 144 147 137

88 179 207 204 174 188 37 82 94 145 109 61 15 44 38 44 33 242 347 593 544 477 529 17 36 297 64 84 71 16 52 151 88 79 230 248 397 462 474 108 148 180 198 161 156 61 75 101 96 118 89

48 176 221 249 260 271 19 45 55 72 73 57 12 19 19 25 25 117 148 315 345 344 379 19 29 121 48 58 47 16 25 99 50 57 78 129 192 188 199 45 64 74 102 96 120 52 43 72 70 68 77

0

0 0 10

0 0 4

0

0

0

0

0 0 0

0 0 0

0 0 0

0 0 0

0 0

0 0

0

0

17 36 22 2 2 0 0 2 187

192 165 204 17 6 10 9 10 11 1 136

295 185 302 13 9 15 9 13 14 1 475

206 131 195 22 18 21 13 9 16 1 338

137 106 139 27 19 20 23 17 17 1 022

99 58 114 13 14 10 15 10 11 664

76 55 114 8 8 6 7 8 7 320

14 28 25 2 1 0 0 0 0 0 0 226

90 68 112 4 5 4 7 7 11 994

104 72 81 12 8 5 9 12 7 1 314

82 47 88 10 8 5 4 2 8 1 016

52 36 73 8 6 11 4 3 2 551

29 19 46 4 7 2 3 6 8 234

29 20 28 4 4 1 2 3 4 89

0 0 0

0 18 98 36 48 61 29 35 44 50 40 450 157 325 521 529 538 155 45 48 42 22 1 2 0 0 1 94 60 71 81 75 84 0 0 0 0 0

68 269 355 359 337 358 270 557 669 709 702 845 2 173 3 824 4 457 4 549 5 026 466 494 430 423 375 5 5 10 5 6 717 772 1 050 1 351 1 264 1 454 2 2 0 0 0

235 874 1 027 852 844 810 174 1 204 1 587 1 673 1 752 921 3 164 6 758 9 186 9 520 10 382 974 713 741 795 768 11 7 14 9 11 1 219 1 297 1 561 1 793 1 835 2 036 0 2 1 0 1 1

113 665 874 680 660 686 441 819 988 1 025 1 133 937 1 836 4 544 6 218 6 550 7 684 824 592 526 500 519 4 6 7 8 8 813 857 904 972 981 1 121 1 4 2 6 0 2

55 300 365 287 361 292 252 497 615 646 747 557 1 091 2 863 3 804 4 230 4 589 393 408 325 376 341 7 4 1 7 8 408 470 533 590 582 597 1 1 1 0 0 2

21 147 146 146 152 157 151 350 415 436 444 611 566 1 464 1 974 2 248 2 449 129 142 202 210 214 3 5 0 1 2 300 279 274 329 335 365 2 1 0 0 0 0

6 81 120 126 138 137 78 198 342 347 360 515 463 950 1 363 1 443 1 686 56 71 126 124 123 10 2 1 4 0 213 189 236 221 214 224 1 0 1 0 0

5 16 105 67 78 81 31 34 39 50 48 404 239 482 595 578 649 105 73 48 50 40 3 1 0 2 0 84 77 83 81 88 125 0 0 0 0 0

49 352 399 429 427 394 123 214 272 285 260 842 2 934 3 996 4 182 4 198 4 652 396 483 399 358 327 7 4 5 2 6 428 521 709 835 807 836 0 0 2 1 0

78 654 809 685 653 582 206 388 418 449 485 795 2 434 4 884 6 117 6 168 6 762 473 442 448 398 393 15 5 4 10 10 461 540 568 643 664 715 1 1 1 0 0 1

50 348 525 382 410 396 168 330 347 323 302 770 1 110 2 448 3 431 3 574 4 084 309 262 261 235 208 5 3 3 4 6 283 376 351 332 362 383 0 0 1 0 0 1

16 161 213 206 185 198 151 223 238 278 237 724 676 1 350 1 846 2 014 2 243 109 157 128 146 116 7 2 2 1 0 203 217 185 217 208 263 0 1 0 0 0 1

1 76 95 122 100 84 63 131 174 189 214 654 344 745 1 040 1 112 1 290 52 60 65 87 66 4 3 0 0 0 126 107 116 136 144 155 0 1 0 0 0 0

0 52 91 87 110 97 9 70 135 147 124 451 231 415 682 724 867 14 29 38 67 59 15 0 0 0 1 72 61 81 105 74 90 1 0 0 0 1

0 0

0 0

0 0 0

0 0 0

0

0

0 0 0

0 0 0

0 89 0

0 43 0

0 0 0

0 0 0

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

177

African region

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO 1.5 1.5 1.7 1.6 1.6 1.6 – 1.4 1.2 1.2 1.2 1.3 2.4 1.4 0.99 0.98 1.0 1.0 1.9 1.7 1.5 1.6 1.7 1.6 1.4 1.3 1.4 1.8 1.8 1.8 1.8 1.6 1.7 1.7 1.8 1.8 1.0 2.3 1.3 – 1.7 1.7 – – 1.1 1.1 1.2 1.3

Sierra Leone

South Africa

Swaziland

Togo

Uganda

United Republic of Tanzania

Zambia

Z mbabwe

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

10 18 45 64 75 70 116 2 035 1 496 1 472 1 132 4 11 9 30 16 18 7 4 11 21 15 9 370 283 257 268 295 272 183 200 190 232 190 208 91 349 135 105 141

184 287 490 718 825 858 723 10 422 9 925 9 772 9 074 59 130 162 207 161 163 95 101 177 150 169 171 1 193 1 511 1 598 2 055 2 075 2 174 2 108 2 357 2 062 1 975 1 975 2 086 659 2 175 1 240 1 033 1 003

305 486 792 1 176 1 224 1 324 1 999 20 576 20 855 20 487 19 894 117 352 406 537 459 479 151 168 320 350 340 338 2 491 3 497 4 075 4 735 5 044 5 029 4 091 4 836 4 939 4 493 4 405 4 707 1 668 2 610 3 166 2 897 3 088

201 361 651 1 076 1 099 1 213 2 135 19 465 19 842 19 360 18 510 130 249 285 369 318 332 123 144 283 358 350 341 1 797 2 479 3 209 4 133 4 613 4 493 2 916 3 430 4 025 4 141 4 073 4 397 1 124 3 045 2 160 2 194 2 412

99 190 397 663 781 841 1 146 11 143 12 386 12 111 11 331 98 138 139 192 158 168 82 109 125 217 234 237 1 115 1 279 1 576 2 214 2 466 2 479 1 754 2 022 2 310 2 427 2 402 2 435 487 435 917 810 846

47 113 226 320 334 416 435 4 124 5 155 5 220 5 054 40 37 57 109 69 84 64 48 79 116 123 121 602 607 725 905 994 1 015 1 007 1 202 1 279 1 309 1 211 1 293 231 261 358 280 319

22 47 124 254 287 274 212 1 705 2 211 2 164 2 085 16 17 27 50 46 38 49 39 69 80 85 87 323 395 539 613 604 633 640 834 1 054 1 161 1 127 1 114 130 174 321 207 220

0

18 27 54 77 115 80 122 2 561 1 933 1 932 1 545 5 10 14 51 35 39 9 13 23 39 11 17 402 400 371 401 400 364 201 257 271 248 221 282 129 150 168 151 180

165 249 393 648 678 703 1 283 13 632 13 023 12 751 11 547 52 198 318 354 281 284 80 107 157 163 167 165 1 376 1 649 1 811 1 964 2 092 2 194 1 904 2 106 1 852 1 689 1 660 1 651 1 125 932 1 507 940 1 024

193 298 518 742 796 861 1 716 19 343 20 205 19 250 17 452 57 298 453 662 495 535 96 124 236 285 277 287 1 845 2 782 3 099 2 923 2 853 2 912 2 532 3 426 3 521 2 988 2 896 2 906 1 779 1 118 2 463 1 683 1 646

110 225 312 556 543 667 933 11 338 12 910 12 807 11 430 39 62 207 276 220 242 45 50 146 148 146 154 1 104 1 510 1 800 1 691 1 809 1 733 1 324 1 738 1 892 2 013 2 140 2 108 717 1 305 1 433 1 063 1 077

65 92 207 293 343 391 423 5 416 6 873 6 955 5 939 29 62 73 104 86 88 38 36 67 78 89 109 635 671 818 924 973 864 735 868 968 1 044 944 1 022 257 186 569 422 376

24 49 114 180 219 201 167 2 352 3 165 3 266 2 846 8 24 21 54 40 51 23 24 41 62 50 48 312 316 389 365 409 419 380 494 547 578 490 507 117 112 235 162 189

11 30 47 131 116 132 80 1 348 2 128 2 223 2 059 6 5 8 16 24 27 15 15 32 29 38 28 113 163 257 248 313 281 179 269 354 471 381 422 63 75 185 99 124

0

0 0 0

0 0 0

0 0

0 0

0

0

16 423 21

1 252 33

0

0

210 150 152 120

837 710 784 783

2 264 2 208 2 467 2 421

1 855 1 682 2 071 2 086

762 761 780 796

295 350 377 360

656 252 278 271

0 0 0

269 173 174 173

1 136 974 1 084 939

2 242 2 185 2 161 2 053

1 255 1 283 1 386 1 286

578 490 448 483

193 265 274 231

603 171 160 161

0 0 0

178

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           LABORATORIES SECONDNUMBER OF SMEAR LABS % OF SMEAR CULTURE DST b LABS LPAc LABS LABS US NG LABS PER 5M LINE DST LABS USING PER 100K PER 5M PER 5M a POPULATION POPULATION POPULATION POPULATION XPERT MTB/RIF AVAILABLE LED

FREE THROUGH NTP FIRSTLINE DRUGS

NRLd

TB DIAGNOSIS

TB NOTIF. RIFAMPICIN RATE PER USED 100 000 THROUGHOUT HEALTH-CARE TREATMENT WORKERS

Algeria Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo Côte d'Ivoire Democratic Republic of the Congo Equatorial Guinea Eritrea Ethiopia Gabon Gambia Ghana Guinea Guinea-Bissau Kenya Lesotho L beria Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda Sao Tome and Principe Senegal Seychelles Sierra Leone South Africa Swaziland Togo Uganda United Republic of Tanzania Zambia Zimbabwe

0.6 0.6 0.8 2.6 0.7 1.7 1.1 3.2 1.6 0.6 0.8 0.6 2.3

0 – 9 21 0 9 4 0 0 0 – 3 0 0 –

3.8 0.5 0.5 2.5 0.3 0.5 0.9 0 1.1 0

0.3 0.5 0.5 2.5 0.3 0 0.5 0 1.1 0

0.1 0.5 2.5 0.9 0 0.5 0 0 0

1 1 5 0 0 1 1 1 0

In country Yes Yes In and out Yes of country Out of Yes country Out of Yes country Out of country In country Out of country No No Yes Yes Yes Yes Yes Yes

Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) No Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (if TB is confirmed) Yes (for smearpositive TB) Yes (a l suspects) No Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects)

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

1 870

815

No Yes 0.5 0.3 0.5 0.2 0 <0.1 0 26 No Yes In and out Yes of country No Yes No No No No Yes Yes Yes Yes

1.3 2.8 0.9 1.8 1.1 0.5 1.3 4.2 0.9 3.9 1.0 1.4 0.4 1.4

0 0 0 31 1 6 0 8 17 0 6 19 0 – –

0 0.3 3.1 2.8 0.6 0.4 3.0 0.2 2.4 0 0.2 1.3 1.0 1.3

0 <0.1 3.1 2.8 0.6 0.4 0 0.2 2.4 0 0.2 0.6 0.3 1.3

0 0.3 0 0 0.6 0 0 0.2 2.4 0 0.2 0.3 0.3

0 7 0 0 0 1 1 15 5 0 5 19 0

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 104 28 199 0

No Yes Out of country In and out of country Out of country Out of country No No No No Out of country Out of country Out of country Out of country Out of country Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes

1.2 1.4 1.1 0.8 1.7 4.3 0.8

9 100 1 2 13 0 0 –

0.6 2.2 0.3 0.1 0.9 0 1.1

0.4 2.2 0.3 <0.1 0.9 0 0.7

0 2.2 0 0.1 0.9 0 0.7

12 1 0 32 6 0 3

Yes No Yes In country Yes Out of Yes country No Yes In country Yes Yes No Yes Yes Yes In country Yes No Yes

2.7 0.4 1.5 1.7 3.2 2.0 1.5 1.3

0 97 21 0 8 17 1 1

0 1.4 4.1 0.8 0.6 0.4 1.1 0.7

0 1.4 4.1 0.8 0.6 0.1 0.7

0 1.4 4.1 0 0.6 0.3 0

0 100 19 1 25 13 17

a b

LED = Light emitting diode microscopes DST = Drug susceptibility testing LED = Ligh assay emittin c LPA = Line probe p e g d NRL = National ug Reference Laboratory

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

179

African region

              New TB cases Year Source Coverage Percentage Year



Previously treated TB cases Source Coverage Percentage

Algeria Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo Côte d'Ivoire Democratic Republic of the Congo Equatorial Guinea Eritrea Ethiopia Gabon Gambia Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda Sao Tome and Principe Senegal Seychelles Sierra Leone South Africa Swaziland Togo Uganda

2002 2010 2008

Survey Survey Survey

National National National

1.4 (0.60–2.7) 0.5 (<0.1–2.0) 2.5 (1.5–3.5)

2002 2011 2008

Survey Surveillance Survey

National National National

9.1 (1.1–29) 13 (8.2–20) 6.6 (2.4–11)

2009

Survey

Sub-national

0.44 (<0.1–2.5)

1998

Survey

Sub-national

18 (7.0–35)

2006

Survey

National

2.5 (1.1–4.9)

2005 2000 1998

Survey Survey Survey

National National Sub-national

1.6 (0.86–2.8) 0.48 (<0.1–2.6) 0.56 (0.11–1.6)

2005 2000 1998

Survey Survey Survey

National National Sub-national

12 (5.6–21) 0 (0–18) 28 (14–47)

1995 2007 2011

Survey Survey Survey

National National National

0.91 (0.19–2.6) 0.49 (0.13–1.3) 0.42 (0.14–0.97)

1995 2007 2011

Survey Survey Survey

National National National

5.7 (1.2–16) 3.9 (0.48–13) 4.8 (3.2–6.9)

2012 2007 2008 2010 2005 2006 2012 1997 2002 2009 2011

Surveillance Survey Survey Survey Survey Survey Surveillance Survey Survey Survey Survey Survey Survey Survey

National National National National National National National National National National National National National National

0 (0–3.0) 3.5 (2.2–4.8) 3.8 (2.7–5.1) 2.9 (2.1–4.0) 3.9 (2.5–5.8) 2.1 0 0.85 1.8 7.7 (0.69–4.9) (0–23) (<0.1–4.7) (1.4–2.3) (4.8–11)

2012 2007 2008 2010 2010 2012 2006 2012 1997 2002 2009 2011 2007 2008 1995

Surveillance Survey Survey Survey Surveillance Surveillance Survey Surveillance Survey Survey Survey Survey Survey Survey Survey

National National National National National National National National National National National National National National National

0 (0–60) 12 (0–25) 16 (13–21) 14 19 88 17 0 23 6.7 34 (10–19) (15–23) (47–100) (7.0–31) (0–84) (5.0–54) (5.4–8.2) (28–39)

1.4 (0.60–2.2) 1.1 (0.30–2.8) 0.33 (<0.1–1.2) 1.9 (1.0–3.3)

12 (6.8–19) 0 (0–5.9) 8.1 (4.1–14) 8.3 (1.8–22)

United Republic of Tanzania 2007 Zambia Zimbabwe 2008 1995

a

Empty rows indicate an absence of high-quality survey or surveillance data. In the absence of high-quality national data, high-quality sub-national data are used.

180

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

region of the americas Table A4.1 Estimates of the burden of disease caused by TB, 1990–2012 Table A4.2 Incidence, notification and case detection rates, all forms, 1990–2012 Table A4.3 Case notifications, 1990–2012 Table A4.4 Treatment outcomes, new smear-positive cases, 1995–2011 Table A4.5 Treatment outcomes, retreatment cases, 1995–2011 Table A4.6 HIV testing and provision of CPT, ART and IPT, 2005–2012 Table A4.7 Testing for MDR-TB and number of confirmed cases of MDR-TB, 2005–2012 Table A4.8 New smear-positive case notification by age and sex, 1995–2012 Table A4.9 Laboratories, NTP services, drug management and infection control, 2012 Table A4.10 Measured percentage of TB cases with MDR-TB, most recent year available 183 186 189 192 195 198 200 202 205 206

Estimates of mortality, prevalence and incidence Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See ANNEX 1 for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. The main updates implemented in this report are explained in Box 2.1 of Chapter 2. Estimates published in previous global TB control reports should no longer be used.

Data source Data shown in this annex are taken from the WHO global TB database on 1 October 2013. Data shown in the main part of the report were taken from the database in July 2013. As a result, data in this annex may differ slightly from those in the main part of the report. Data for all years can be downloaded from www.who.int/tb/data.

Country notes Caribbean Islands Data collection from Caribbean Islands that are not Member States of WHO was resumed in 2011 after a break of a few years. This includes Aruba, Curaçao, Puerto Rico and Sint Maarten, which are Associate Members of the Pan American Health Organization, plus the territories of Anguilla, Bermuda, Bonaire, Saint Eustatius and Saba, British Virgin Islands, Cayman Islands, Montserrat and Turks and Caicos Islands. Data are not currently independently collected from the US Virgin Islands

USA In addition to the 51 reporting areas, the USA includes territories that report separately to WHO. The data for these territories are not included in the data reported by the USA. Definitions of case types and outcomes do not exactly match those used by WHO.

182

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

1990 1995 2000 2005 2010 2011 2012 Antigua and 1990 Barbuda 1995 2000 2005 2010 2011 2012 Argentina 1990 1995 2000 2005 2010 2011 2012 Aruba 1990 1995 2000 2005 2010 2011 2012 Bahamas 1990 1995 2000 2005 2010 2011 2012 Barbados 1990 1995 2000 2005 2010 2011 2012 Belize 1990 1995 2000 2005 2010 2011 2012 Bermuda 1990 1995 2000 2005 2010 2011 2012 Bolivia 1990 (Plurinational 1995 State of) 2000 2005 2010 2011 2012 Bonaire, Saint 2010 Eustatius and Saba 2011 2012 Braz l 1990 1995 2000 2005 2010 2011 2012 British Virgin 1990 Islands 1995 2000 2005 2010 2011 2012 Canada 1990 1995 2000 2005 2010 2011 2012 Cayman Islands 1990 1995 2000 2005 2010 2011 2012 Chile 1990 1995 2000 2005 2010 2011 2012 Colombia 1990 1995 2000 2005 2010 2011 2012

Anguilla

<1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 33 35 37 39 40 41 41 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 7 8 8 9 10 10 10 <1 <1 <1 150 162 175 186 195 197 199 <1 <1 <1 <1 <1 <1 <1 28 29 31 32 34 34 35 <1 <1 <1 <1 <1 <1 <1 13 14 15 16 17 17 17 33 37 40 43 46 47 48

0 0 0 0 0 0 0 <0.01 0 <0.01 <0.01 <0.01 <0.01 <0.01 1.4 1.2 0.84 0.73 0.54 0.55 0.55 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.043 0.012 <0.01 <0.01 <0.01 <0.01 <0.01 0 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.014 <0.01 <0.01 0.013 0.014 0.014 0 0 0 0 <0.01 <0.01 <0.01 2.7 2.5 2.4 2.3 2.2 2.2 2.2 0 0 0 10 8.6 7.7 5.8 5.4 5.1 4.9 0 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.12 0.12 0.082 0.086 0.074 0.071 0.067 <0.01 0 0 0 0 0 0 0.76 0.5 0.3 0.24 0.23 0.22 0.21 1.7 2 1.3 1 0.9 0.84 0.77

(0–0) (0–0) (0–0) (0–0) (0–0) (0–14) (0–0) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (1.3–1.4) (1.1–1.2) (0.810–0.870) (0.700–0.760) (0.520–0.570) (0.520–0.570) (0.530–0.580) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.043–0.043) (0.012–0.012) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.013–0.016) (<0.01–<0.01) (<0.01–<0.01) (0.013–0.013) (0.014–0.014) (0.014–0.014) (0–0) (0–0) (0–0) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.710–6.0) (1.2–4.4) (1.0–4.3) (0.950–4.1) (0.940–4.0) (0.930–4.0) (0.930–3.9) (0–0) (0–0) (0–0) (7.8–13) (6.8–11) (6.3–9.2) (5.2–6.5) (5.0–5.8) (4.8–5.4) (4.6–5.2) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.110–0.120) (0.120–0.120) (0.081–0.082) (0.086–0.086) (0.074–0.074) (0.070–0.071) (0.067–0.068) (<0.01–<0.01) (0–0) (0–0) (0–0) (0–0) (0–0) (0–0) (0.710–0.820) (0.460–0.540) (0.290–0.310) (0.240–0.240) (0.220–0.230) (0.220–0.230) (0.210–0.220) (1.4–2.0) (1.8–2.2) (1.2–1.4) (1.0–1.0) (0.890–0.910) (0.830–0.850) (0.760–0.790)

0 0 0 0 0 0 0 3.9 0 1.8 1.4 1.4 1.4 1.4 4.2 3.3 2.3 1.9 1.3 1.3 1.3 0.78 0.78 0.78 0.78 0.78 0.78 0.78 17 4.3 2.2 1.1 0.51 0.43 0.37 0 0.63 0.71 0.62 0.69 0.69 0.69 2.5 7 3.3 2.2 4.3 4.3 4.3 0 0 0 0 0.18 0.18 0.18 40 33 28 24 22 21 21 0 0 0 7 5.3 4.4 3.1 2.7 2.6 2.5 0 5.5 5.3 4.6 4.1 4.1 4.1 0.42 0.4 0.27 0.27 0.22 0.21 0.19 4 0 0 0 0 0 0 5.8 3.5 1.9 1.5 1.3 1.3 1.2 5 5.3 3.2 2.4 1.9 1.8 1.6

(0–0) (0–0) (0–0) (0–0) (0–0) (0–100 000) (0–0) (3.5–4.3) (0–0) (1.5–2.2) (1.3–1.4) (1.2–1.5) (1.2–1.5) (1.2–1.5) (4.1–4.2) (3.3–3.4) (2.2–2.3) (1.8–2.0) (1.3–1.4) (1.3–1.4) (1.3–1.4) (<0.1–2.5) (<0.1–2.5) (<0.1–2.5) (<0.1–2.5) (<0.1–2.5) (<0.1–2.5) (<0.1–2.5) (17–17) (4.3–4.3) (2.1–2.3) (1.1–1.1) (0.49–0.53) (0.42–0.45) (0.36–0.38) (0–0) (0.62–0.64) (0.70–0.73) (0.61–0.63) (0.67–0.70) (0.67–0.70) (0.67–0.70) (1.9–3.1) (6.3–7.7) (3.2–3.3) (2.1–2.2) (4.3–4.3) (4.3–4.3) (4.3–4.3) (0–0) (0–0) (0–0) (0–0) (0.18–0.18) (0.18–0.18) (0.18–0.18) (10–89) (15–58) (12–51) (10–44) (9.3–39) (9.1–38) (8.8–37) (0–0) (0–0) (0–0) (5.2–9.0) (4.2–6.6) (3.6–5.3) (2.8–3.5) (2.5–3.0) (2.4–2.8) (2.3–2.6) (0–0) (5.5–5.5) (5.1–5.5) (4.4–4.7) (4.0–4.3) (4.0–4.3) (4.0–4.3) (0.41–0.44) (0.40–0.40) (0.26–0.27) (0.27–0.27) (0.22–0.22) (0.20–0.21) (0.19–0.19) (4.0–4.1) (0–0) (0–0) (0–0) (0–0) (0–0) (0–0) (5.3–6.2) (3.2–3.7) (1.8–2.0) (1.4–1.5) (1.3–1.4) (1.3–1.3) (1.2–1.2) (4.2–5.9) (4.8–5.9) (3.0–3.4) (2.3–2.4) (1.9–2.0) (1.8–1.8) (1.6–1.6)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 33 26 22 18 16 16 15 0.013 0.016 0.018 0.02 0.021 0.021 0.021 0.056 0.064 0.1 0.056 0.037 0.058 0.04 <0.01 <0.01 <0.01 0.016 <0.01 <0.01 <0.01 0.1 0.1 0.13 0.13 0.16 0.17 0.17 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 28 27 25 24 23 23 23

(<0.01–<0.01) (<0.01–<0.01) (<0.01–0.011) (<0.01–0.012) (<0.01–0.012) (<0.01–0.012) (<0.01–0.012) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.012) (<0.01–0.018) (<0.01–0.016) (<0.01–0.015) (<0.01–<0.01) (12–64) (12–46) (9.5–39) (7.8–34) (7.1–29) (6.8–28) (6.5–27) (<0.01–0.024) (<0.01–0.031) (<0.01–0.035) (<0.01–0.038) (<0.01–0.039) (<0.01–0.039) (<0.01–0.039) (0.024–0.100) (0.027–0.120) (0.050–0.170) (0.025–0.100) (0.015–0.068) (0.028–0.098) (0.016–0.076) (<0.01–0.014) (<0.01–<0.01) (<0.01–0.011) (<0.01–0.027) (<0.01–0.013) (<0.01–<0.01) (<0.01–<0.01) (0.033–0.210) (0.037–0.200) (0.047–0.240) (0.055–0.230) (0.073–0.290) (0.073–0.290) (0.071–0.300) (<0.01–<0.01) (<0.01–0.013) (<0.01–<0.01) (<0.01–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.012) (11–55) (14–44) (12–43) (12–41) (11–39) (11–38) (11–38)

60 47 56 54 50 50 49 2.8 4.8 9.3 9.4 5.3 6.8 4.8 102 74 59 48 40 38 36 20 20 20 20 20 20 20 22 23 34 17 10 16 11 2.6 1.5 2.1 5.7 2.8 0.79 1.8 55 49 52 48 53 52 51 3.9 13 1.2 13 3.8 3 11 419 352 299 258 227 221 215

(22–118) (23–81) (24–102) (23–99) (22–89) (22–89) (22–88) (0.83–6.0) (1.4–10) (4.6–16) (2.2–22) (0.24–18) (1.1–18) (1.6–9.9) (38–198) (33–131) (26–107) (20–87) (18–71) (17–68) (16–65) (7.9–38) (7.9–38) (7.9–38) (7.9–38) (7.9–38) (7.9–38) (7.9–38) (9.5–39) (9.7–41) (17–57) (7.6–30) (4.2–19) (7.6–27) (4.2–21) (0.93–5.2) (0.56–3.0) (0.79–4.2) (2.7–9.9) (1.4–4.7) (0.30–1.5) (0.77–3.1) (17–113) (18–95) (20–101) (20–86) (24–93) (23–93) (22–92) (1.2–8.3) (6.6–22) (0.35–2.5) (6.4–22) (0.97–8.6) (0.78–6.7) (5.3–19) (156–810) (180–580) (145–506) (126–436) (113–381) (110–370) (107–360)

<0.01 (<0.01–<0.01) 210 170 150 120 110 120 120 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 3 3 2.6 2.4 2 2.2 2.1 <0.01 <0.01 0.012 <0.01 <0.01 <0.01 0.011 10 6.4 4.6 4 3.7 3.8 3.6 28 30 27 25 24 23 23 (73–420) (76–290) (65–260) (52–220) (47–210) (54–220) (51–210) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (1.3–5.6) (1.3–5.4) (1.1–4.8) (1.0–4.3) (0.770–3.7) (0.950–3.9) (0.900–3.8) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.020) (<0.01–<0.01) (<0.01–0.016) (<0.01–0.010) (<0.01–0.019) (4.4–18) (2.6–12) (1.9–8.6) (1.8–7.1) (1.5–6.7) (1.6–6.9) (1.4–6.7) (10–55) (15–51) (13–46) (12–43) (11–41) (11–40) (11–39)

8.1 (3.2–15) 140 103 84 66 58 62 59 23 23 8.4 2.7 9.2 0.97 1 11 10 8.5 7.3 5.7 6.3 6.1 12 10 28 2.2 15 8 18 76 44 30 25 21 22 21 85 83 68 58 51 49 48 (49–278) (47–180) (37–149) (28–119) (24–106) (27–112) (25–107) (9.3–43) (9.5–43) (2.5–18) (0.82–5.8) (4.3–16) (0.29–2.0) (0.30–2.1) (4.6–20) (4.3–18) (3.5–16) (3.1–13) (2.2–11) (2.7–11) (2.6–11) (3.5–25) (4.4–18) (14–48) (1.1–3.7) (5.5–28) (2.2–18) (8.2–33) (34–136) (18–82) (12–55) (11–44) (8.9–39) (9.5–40) (8.3–38) (31–165) (41–140) (33–116) (28–100) (24–87) (23–85) (22–83)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0 <0.01 <0.01 <0.01 <0.01 <0.01 19 17 15 13 11 11 10 <0.01 0.013 0.014 0.016 0.016 0.016 0.016 0.053 0.066 0.094 0.055 0.036 0.047 0.037 <0.01 <0.01 <0.01 0.014 <0.01 0 <0.01 0.075 0.083 0.095 0.11 0.12 0.13 0.13 0 <0.01 0 <0.01 <0.01 <0.01 <0.01 17 16 16 15 14 14 13 0 <0.01 0 130 120 110 95 91 95 92 <0.01 <0.01 <0.01 0 <0.01 0 0 2.3 2.3 2 1.8 1.6 1.6 1.6 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 7.1 4.8 3.5 2.9 2.7 2.8 2.8 18 18 17 17 16 16 16

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (13–28) (14–21) (12–18) (11–15) (9.1–13) (8.9–13) (8.6–12) (<0.01–0.011) (0.011–0.014) (0.013–0.016) (0.014–0.018) (0.014–0.018) (0.014–0.018) (0.014–0.018) (0.046–0.060) (0.057–0.074) (0.083–0.110) (0.048–0.062) (0.031–0.040) (0.041–0.053) (0.032–0.042) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.012–0.016) (<0.01–<0.01) (0–0) (<0.01–<0.01) (0.052–0.100) (0.068–0.099) (0.078–0.110) (0.094–0.120) (0.100–0.150) (0.100–0.150) (0.110–0.160) (0–0) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (11–24) (14–19) (13–19) (12–18) (11–16) (11–16) (11–16) (0–0) (<0.01–<0.01) (0–0) (79–180) (94–140) (86–130) (80–110) (75–110) (78–110) (76–110) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (0–0) (0–0) (2.0–2.6) (2.0–2.6) (1.7–2.2) (1.6–2.0) (1.4–1.8) (1.4–1.9) (1.4–1.8) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (6.2–8.0) (4.2–5.4) (3.0–3.9) (2.5–3.3) (2.4–3.1) (2.5–3.2) (2.4–3.1) (12–25) (14–21) (14–21) (14–20) (13–19) (13–19) (13–19)

24 23 23 22 21 21 21 1.9 0 5.9 8.4 9.2 7.8 3.9 60 49 40 33 27 26 25 16 16 16 16 16 16 16 21 23 32 17 9.9 13 9.9 2.2 1.3 1.3 5.1 2.5 0 1.6 40 40 40 40 40 40 40 0 7.5 0 8.1 1.8 1.8 5.3 251 215 184 158 135 131 127 0 6.3 0 84 71 60 51 46 48 46 17 17 5.6 0 4.2 0 0 8.3 7.7 6.5 5.5 4.6 4.8 4.6 9.2 7.3 14 1.2 8.3 4.1 12 54 33 22 18 16 16 16 54 48 43 38 34 34 33

(15–35) (20–27) (18–27) (18–26) (18–25) (17–25) (17–25) (1.6–2.1) (0–0) (5.2–6.7) (7.3–9.5) (8.1–10) (6.9–8.9) (3.4–4.4) (39–85) (40–59) (33–49) (27–40) (23–32) (22–31) (21–30) (14–18) (14–18) (14–18) (14–18) (14–18) (14–18) (14–18) (18–23) (21–26) (28–36) (15–19) (8.7–11) (11–15) (8.7–11) (1.9–2.5) (1.1–1.5) (1.1–1.5) (4.4–5.7) (2.2–2.8) (0–0) (1.4–1.8) (28–54) (33–48) (33–48) (34–46) (33–48) (33–48) (33–48) (0–0) (6.6–8.5) (0–0) (7.1–9.1) (1.6–2.0) (1.5–2.0) (4.6–6.0) (166–354) (185–248) (151–221) (129–190) (111–161) (108–156) (105–151) (0–0) (5.5–7.2) (0–0) (53–121) (58–85) (49–72) (43–60) (38–55) (40–57) (38–55) (15–20) (15–20) (4.9–6.3) (0–0) (3.7–4.8) (0–0) (0–0) (7.3–9.4) (6.8–8.7) (5.7–7.3) (4.8–6.3) (4.0–5.2) (4.2–5.4) (4.0–5.2) (8.1–10) (6.4–8.2) (12–16) (1.1–1.4) (7.3–9.4) (3.6–4.6) (11–14) (47–61) (29–37) (20–25) (15–20) (14–18) (14–18) (14–18) (36–75) (39–58) (35–52) (31–46) (28–41) (28–40) (27–39)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

183

region of the americas

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Costa Rica

Cuba

Curaçao

Dominica

Dominican Republic

Ecuador

El Salvador

Grenada

Guatemala

Guyana

Haiti

Honduras

Jamaica

Mexico

Montserrat

Netherlands Antilles

Nicaragua

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 1990 1995 2000 2005 2010 2011 2012

3 3 4 4 5 5 5 11 11 11 11 11 11 11 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 7 8 9 9 10 10 10 10 11 13 14 15 15 15 5 6 6 6 6 6 6 <1 <1 <1 <1 <1 <1 <1 9 10 11 13 14 15 15 <1 <1 <1 <1 <1 <1 <1 7 8 9 9 10 10 10 5 6 6 7 8 8 8 2 2 3 3 3 3 3 86 95 104 111 118 119 121 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 4 5 5 5 6 6 6

0.078 0.11 0.07 0.06 0.043 0.04 0.038 0.062 0.096 0.046 0.033 0.039 0.038 0.038 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1 1 0.76 0.59 0.53 0.49 0.46 2 2 1.8 1.1 0.69 0.53 0.41 0.26 0.22 0.17 0.11 0.076 0.071 0.065 0 0 0 <0.01 <0.01 <0.01 <0.01 0.86 0.63 0.57 0.41 0.34 0.32 0.31 0.054 0.067 0.099 0.12 0.12 0.12 0.12 2.5 3 3.4 3.4 2.9 2.7 2.6 0.31 0.35 0.31 0.26 0.24 0.24 0.23 0.021 0.025 0.016 0.011 <0.01 <0.01 <0.01 6.7 5.3 3.5 2.7 2.6 2.2 2.2 0 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.45 0.41 0.33 0.3 0.26 0.19 0.19

(0.072–0.083) (0.100–0.110) (0.067–0.072) (0.058–0.061) (0.038–0.047) (0.036–0.045) (0.034–0.043) (0.059–0.065) (0.095–0.098) (0.045–0.047) (0.033–0.034) (0.039–0.040) (0.038–0.038) (0.038–0.038) (<0.01–<0.01) (0–<0.01) (0–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.550–1.6) (0.510–1.7) (0.400–1.2) (0.380–0.850) (0.390–0.680) (0.380–0.620) (0.380–0.550) (1.4–2.6) (1.4–2.7) (1.3–2.3) (0.910–1.2) (0.610–0.790) (0.460–0.610) (0.350–0.480) (0.150–0.390) (0.150–0.300) (0.120–0.210) (0.087–0.140) (0.056–0.100) (0.051–0.094) (0.046–0.088) (0–0) (0–0) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.800–0.930) (0.570–0.700) (0.510–0.640) (0.370–0.460) (0.310–0.370) (0.290–0.350) (0.280–0.340) (0.036–0.075) (0.049–0.087) (0.061–0.150) (0.110–0.140) (0.098–0.130) (0.099–0.140) (0.099–0.140) (0.450–6.4) (1.1–6.0) (1.2–6.7) (1.2–6.6) (1.1–5.4) (1.1–5.1) (1.0–4.9) (0.096–0.650) (0.110–0.730) (0.060–0.760) (0.025–0.780) (<0.01–0.840) (<0.01–0.850) (<0.01–0.850) (0.016–0.026) (0.020–0.031) (0.013–0.020) (<0.01–0.013) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (6.4–7.0) (4.9–5.7) (3.3–3.6) (2.6–2.9) (2.5–2.7) (2.1–2.4) (2.1–2.3) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.260–0.680) (0.260–0.600) (0.230–0.440) (0.220–0.380) (0.200–0.330) (0.150–0.240) (0.150–0.230)

2.5 3.1 1.8 1.4 0.92 0.85 0.8 0.58 0.88 0.41 0.3 0.35 0.33 0.33 0.19 <0.1 <0.1 7.6 2.4 3.4 1.3 3.2 2.1 2 14 13 8.7 6.3 5.3 4.9 4.4 19 17 14 7.7 4.6 3.5 2.7 4.8 3.8 2.8 1.8 1.2 1.1 1 0 0 0 1.6 0.76 0.99 0.99 9.7 6.3 5.1 3.3 2.3 2.2 2.1 7.5 9.1 13 16 15 15 15 36 39 40 37 29 27 25 6.4 6.2 5 3.8 3.1 3 2.9 0.87 1 0.63 0.4 0.26 0.24 0.22 7.8 5.5 3.3 2.5 2.2 1.9 1.8 0 11 21 22 21 24 24 0.59 0.57 0.59 0.59 11 8.9 6.4 5.4 4.5 3.3 3.1

(2.3–2.7) (3.0–3.2) (1.7–1.8) (1.3–1.4) (0.82–1.0) (0.76–0.95) (0.70–0.89) (0.55–0.62) (0.87–0.89) (0.40–0.42) (0.30–0.30) (0.35–0.35) (0.33–0.34) (0.33–0.34) (<0.1–0.63) (0–0.19) (0–0.18) (7.3–7.9) (2.2–2.5) (3.1–3.7) (1.3–1.3) (3.2–3.3) (2.1–2.1) (2.0–2.0) (7.6–22) (6.4–21) (4.6–14) (4.0–9.1) (3.9–6.8) (3.8–6.1) (3.7–5.3) (14–26) (12–24) (10–19) (6.6–9.0) (4.0–5.2) (3.0–4.0) (2.3–3.1) (2.8–7.4) (2.6–5.2) (2.1–3.6) (1.4–2.3) (0.90–1.6) (0.81–1.5) (0.73–1.4) (0–0) (0–0) (0–0) (1.6–1.6) (0.75–0.76) (0.95–1.0) (0.95–1.0) (9.0–10) (5.7–7.1) (4.6–5.7) (2.9–3.6) (2.1–2.6) (2.0–2.4) (1.9–2.2) (5.0–10) (6.7–12) (8.2–20) (14–19) (12–17) (12–17) (12–17) (6.3–90) (14–77) (14–78) (13–71) (11–55) (11–51) (10–48) (2.0–13) (1.9–13) (0.96–12) (0.36–11) (0.12–11) (<0.1–11) (<0.1–11) (0.68–1.1) (0.81–1.2) (0.51–0.77) (0.32–0.48) (0.21–0.31) (0.20–0.28) (0.18–0.26) (7.5–8.1) (5.2–5.9) (3.2–3.5) (2.4–2.6) (2.1–2.3) (1.8–2.0) (1.7–1.9) (0–0) (10–11) (21–22) (21–22) (21–22) (24–25) (24–25) (0.56–0.62) (0.54–0.60) (0.58–0.61) (0.57–0.61) (6.4–16) (5.6–13) (4.5–8.7) (4.1–6.9) (3.5–5.6) (2.6–4.1) (2.4–3.8)

3.6 3 2.5 1.7 0.93 0.78 0.6 6.4 3.5 2.2 1.6 1.6 1.6 1.6 <0.01 <0.01 <0.01 0.012 0.014 0.02 0.012 0.013 0.016 0.018 25 17 14 12 11 10 10 34 27 23 20 17 16 15 5.1 3.1 3.3 3.7 2.1 2.1 2.2 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 13 14 14 15 16 16 17 1.4 1.1 1 1.1 1 1 1 27 30 34 36 32 31 30 8.7 9.5 11 7.7 6.4 6.5 6.5 0.23 0.22 0.21 0.23 0.26 0.26 0.26 130 85 53 38 40 41 40 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.013 0.014 <0.01 0.01 7.6 6.4 5.5 4.6 2.9 3.1 3.3

(1.7–6.3) (1.5–5.0) (1.3–4.0) (0.920–2.8) (0.460–1.6) (0.360–1.4) (0.220–1.2) (2.4–12) (1.7–5.9) (0.940–3.9) (0.730–2.8) (0.730–2.8) (0.700–2.8) (0.670–2.8) (<0.01–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.031) (<0.01–0.026) (<0.01–0.034) (<0.01–0.024) (<0.01–0.024) (<0.01–0.033) (<0.01–0.030) (9.4–47) (8.6–29) (6.8–23) (6.0–21) (5.3–18) (5.1–18) (4.9–17) (13–66) (14–46) (12–39) (10–34) (8.5–28) (8.1–27) (7.6–25) (1.7–10) (1.2–6.1) (1.6–5.7) (1.8–6.2) (0.740–4.0) (0.760–4.2) (0.770–4.3) (<0.01–0.020) (<0.01–0.014) (<0.01–0.015) (<0.01–0.014) (<0.01–0.013) (<0.01–0.015) (<0.01–0.015) (4.8–24) (6.8–23) (7.1–24) (7.4–25) (7.9–27) (8.0–28) (8.2–28) (0.520–2.7) (0.550–1.9) (0.490–1.8) (0.470–1.9) (0.430–1.9) (0.430–1.9) (0.430–1.9) (8.2–56) (14–51) (17–58) (17–61) (15–55) (15–53) (14–52) (3.0–18) (3.0–19) (3.4–22) (2.5–16) (2.2–13) (2.2–13) (2.1–13) (0.081–0.440) (0.100–0.380) (0.095–0.370) (0.110–0.400) (0.130–0.430) (0.130–0.440) (0.130–0.440) (61–210) (43–140) (27–87) (19–63) (19–67) (20–69) (19–69) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.024) (<0.01–0.025) (<0.01–0.019) (<0.01–0.021) (2.8–15) (3.0–11) (2.6–9.5) (2.2–8.0) (1.0–5.9) (1.1–6.3) (1.1–6.7)

118 87 63 40 20 16 12 60 32 19 14 14 14 14 5 0.97 0.95 17 19 28 17 19 23 25 339 215 159 131 107 103 98 340 242 187 148 113 106 98 95 55 56 60 33 34 34 11 8.2 8.6 8.1 5.5 7.1 6.8 142 139 129 119 112 111 110 193 153 139 139 132 131 131 376 378 400 388 326 309 296 178 169 169 112 84 84 82 9.5 8.9 8.1 8.7 9.4 9.4 9.5 145 89 51 34 34 34 33 20 8.2 11 42 9.9 4.7 6.7 7.2 5 5.6 183 137 108 85 50 53 55

(54–205) (44–143) (33–101) (21–65) (9.8–33) (7.6–29) (4.7–24) (23–115) (15–54) (8.4–35) (6.4–25) (6.4–25) (6.2–25) (5.9–25) (2.0–9.4) (0.38–1.8) (0.37–1.8) (2.7–43) (7.3–36) (13–49) (6.3–34) (7.9–34) (7.2–46) (12–42) (130–646) (108–360) (78–268) (65–220) (53–181) (50–173) (48–165) (127–655) (121–403) (93–313) (74–248) (57–187) (53–176) (49–163) (32–191) (21–105) (27–96) (29–103) (12–65) (12–67) (12–68) (3.9–21) (4.1–14) (4.1–15) (3.9–14) (1.3–13) (2.2–15) (2.1–14) (53–274) (69–233) (63–217) (59–200) (55–189) (55–188) (54–187) (72–372) (75–258) (66–239) (62–248) (55–241) (54–241) (54–242) (115–787) (180–648) (193–681) (187–659) (156–556) (148–528) (140–509) (60–358) (54–348) (54–347) (36–228) (29–170) (28–169) (27–168) (3.4–19) (4.1–15) (3.7–14) (4.1–15) (4.6–16) (4.6–16) (4.7–16) (71–246) (46–146) (26–84) (17–57) (16–57) (16–58) (16–57) (10–33) (2.5–17) (3.3–23) (21–69) (2.9–21) (1.4–10) (2.5–13) (3.1–13) (1.5–11) (1.7–12) (68–354) (65–236) (51–186) (39–146) (17–101) (18–106) (19–112)

1.5 1.5 1.4 1 0.65 0.59 0.51 2.6 2 1.4 1 1 1 1 <0.01 <0.01 <0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 11 9.7 8.6 7.7 6.7 6.6 6.4 18 15 13 11 9.7 9.4 9.1 3.4 2.6 2.2 2.4 1.8 1.7 1.6 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 6.6 7.1 7.6 8.2 8.8 9 9.1 0.65 0.65 0.78 0.88 0.87 0.87 0.87 18 19 23 25 23 22 22 5.6 6.4 7.1 5 4.1 4.2 4.3 0.15 0.16 0.17 0.18 0.18 0.18 0.18 57 44 32 25 26 27 27 <0.01 <0.01 0 <0.01 0 0 0 <0.01 0.01 <0.01 <0.01 4.5 4 3.4 2.9 2.5 2.4 2.3

(1.3–1.7) (1.3–1.7) (1.2–1.5) (0.880–1.1) (0.570–0.740) (0.510–0.660) (0.440–0.580) (1.6–3.9) (1.7–2.5) (1.1–1.8) (0.850–1.3) (0.840–1.3) (0.830–1.3) (0.840–1.3) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.015) (<0.01–0.012) (<0.01–0.012) (<0.01–0.011) (<0.01–0.011) (<0.01–0.011) (<0.01–0.011) (6.6–16) (7.9–12) (7.1–10) (6.3–9.2) (5.6–8.0) (5.4–7.8) (5.3–7.6) (11–26) (13–19) (11–16) (9.4–14) (8.0–12) (7.8–11) (7.5–11) (2.3–4.7) (2.3–2.9) (1.8–2.6) (1.9–2.9) (1.5–2.0) (1.4–1.9) (1.4–1.8) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (4.1–9.7) (5.8–8.5) (6.2–9.1) (6.7–9.9) (7.3–11) (7.4–11) (7.5–11) (0.400–0.960) (0.530–0.780) (0.630–0.930) (0.720–1.1) (0.720–1.0) (0.720–1.0) (0.710–1.0) (11–26) (16–23) (19–28) (21–30) (19–27) (18–27) (18–26) (3.6–7.9) (4.1–9.2) (4.6–10) (3.2–7.2) (2.7–5.9) (2.7–6.0) (2.8–6.1) (0.110–0.210) (0.130–0.190) (0.140–0.200) (0.140–0.210) (0.150–0.210) (0.150–0.220) (0.150–0.220) (49–66) (38–51) (27–37) (21–28) (23–30) (23–31) (23–32) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (0–0) (0–0) (0–0) (<0.01–0.011) (<0.01–0.012) (<0.01–<0.01) (<0.01–<0.01) (2.9–6.3) (3.2–4.8) (2.8–4.1) (2.4–3.5) (2.1–2.8) (2.0–2.7) (2.0–2.7)

48 43 35 23 14 12 11 25 19 13 9.2 9.3 9.3 9.3 3.9 0.76 0.74 15 14 14 13 13 13 13 148 121 100 82 67 65 62 174 136 107 83 65 62 59 63 45 37 39 28 27 25 4.6 4.5 4.4 4.2 4.1 4.1 4.1 74 71 68 65 62 61 60 89 89 104 115 111 110 109 247 247 271 272 230 222 213 113 115 114 73 54 54 54 6.5 6.5 6.5 6.5 6.6 6.6 6.6 67 46 31 22 22 23 23 11 4.1 0 24 0 0 0 5.3 5.3 3.2 4.7 108 85 68 53 42 40 38

(42–54) (37–48) (31–39) (20–26) (12–16) (11–14) (9.3–12) (15–37) (15–23) (10–16) (7.5–11) (7.4–11) (7.4–11) (7.4–11) (3.4–4.4) (0.67–0.86) (0.65–0.84) (9.3–21) (12–17) (11–17) (11–16) (11–16) (11–16) (11–15) (91–218) (99–146) (82–120) (67–98) (55–80) (53–77) (51–74) (108–257) (111–164) (87–128) (68–100) (54–77) (51–74) (48–70) (43–88) (39–50) (30–44) (32–47) (24–33) (23–31) (22–29) (2.9–6.8) (3.8–5.2) (3.6–5.2) (3.5–5.1) (3.4–4.9) (3.4–4.9) (3.4–4.9) (47–109) (58–85) (55–81) (53–78) (51–73) (50–73) (50–72) (55–132) (73–107) (85–125) (94–138) (91–132) (91–131) (90–130) (153–365) (202–297) (221–325) (222–326) (190–275) (183–265) (176–254) (73–162) (74–164) (74–163) (47–104) (35–77) (35–77) (35–77) (4.7–8.8) (5.4–7.9) (5.4–7.9) (5.4–7.9) (5.4–7.8) (5.4–7.8) (5.4–7.8) (57–77) (40–53) (26–36) (19–26) (19–26) (19–26) (19–26) (9.4–12) (3.6–4.7) (0–0) (21–27) (0–0) (0–0) (0–0) (4.6–6.0) (4.6–6.0) (2.8–3.7) (4.1–5.3) (71–152) (70–102) (55–81) (44–64) (36–49) (35–46) (33–44)

a

Rates are per 100 000 population.

184

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Panama

Paraguay

Peru

Puerto Rico

Saint Kitts and Nevis

Saint Lucia

Saint Vincent and the Grenadines

Sint Maarten (Dutch part) Suriname

Trinidad and Tobago

Turks and Caicos Islands

United States of America

Uruguay

US Virgin Islands

Venezuela (Bolivarian Republic of)

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

2 3 3 3 4 4 4 4 5 5 6 6 7 7 22 24 26 28 29 30 30 4 4 4 4 4 4 4 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 1 1 1 1 1 1 1 <1 <1 <1 <1 <1 <1 <1 255 268 285 298 312 315 318 3 3 3 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 20 22 24 27 29 30 30

0.2 0.2 0.2 0.22 0.19 0.19 0.19 0.2 0.23 0.23 0.28 0.19 0.2 0.2 7.5 6.2 3.7 2.7 1.8 1.7 1.5 0.069 0.081 0.017 0.017 0.01 <0.01 <0.01 0 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.012 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.027 0.016 <0.01 <0.01 0.014 0.014 0.014 0.032 0.034 0.025 0.018 0.028 0.028 0.028 0 0 <0.01 <0.01 <0.01 <0.01 <0.01 2.6 1.4 0.81 0.64 0.61 0.47 0.44 0.085 0.076 0.069 0.067 0.054 0.053 0.051 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.85 0.81 0.67 0.63 0.71 0.72 0.73

(0.130–0.290) (0.160–0.250) (0.180–0.230) (0.210–0.230) (0.190–0.200) (0.190–0.190) (0.180–0.190) (0.150–0.250) (0.170–0.290) (0.160–0.310) (0.220–0.350) (0.160–0.230) (0.160–0.230) (0.160–0.240) (2.5–15) (3.3–9.9) (2.3–5.4) (2.1–3.4) (1.3–2.3) (1.2–2.1) (1.1–2.0) (0.069–0.070) (0.080–0.081) (0.017–0.017) (0.017–0.017) (0.010–0.010) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.016) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–<0.01) (0–<0.01) (0–<0.01) (0.019–0.037) (<0.01–0.027) (<0.01–<0.01) (<0.01–<0.01) (0.012–0.015) (0.012–0.015) (0.012–0.016) (0.031–0.033) (0.033–0.034) (0.024–0.025) (0.018–0.018) (0.028–0.028) (0.028–0.028) (0.028–0.028) (0–0) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (2.5–2.6) (1.4–1.4) (0.790–0.820) (0.640–0.650) (0.590–0.630) (0.440–0.500) (0.390–0.480) (0.078–0.092) (0.073–0.078) (0.066–0.072) (0.064–0.070) (0.051–0.057) (0.050–0.056) (0.048–0.054) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.830–0.870) (0.790–0.830) (0.650–0.690) (0.630–0.630) (0.410–1.1) (0.410–1.1) (0.420–1.1)

8.1 7.4 6.6 6.6 5.2 5.1 4.9 4.6 4.8 4.3 4.7 3 3 3 34 26 14 9.7 6.1 5.6 5.1 2 2.2 0.45 0.45 0.28 0.25 0.23 0 2.1 2.4 2.2 2.5 2.5 2.5 4 8.3 0.81 3.5 1.4 1.3 1.2 1 3.7 3.3 0.86 4.8 2.6 2.6 0.4 0.26 0.13 6.7 3.6 1.2 1.7 2.6 2.6 2.6 2.6 2.7 1.9 1.4 2.1 2.1 2.1 0 0 6.1 3.9 3.5 3.5 3.5 1 0.51 0.28 0.22 0.2 0.15 0.14 2.7 2.3 2.1 2 1.6 1.6 1.5 3 2.4 2.8 0.94 0.96 0.96 0.96 4.3 3.7 2.7 2.4 2.4 2.4 2.4

(5.2–12) (5.8–9.2) (5.9–7.4) (6.3–6.9) (5.1–5.4) (5.0–5.2) (4.8–5.0) (3.5–5.9) (3.6–6.1) (3.1–5.8) (3.7–5.9) (2.5–3.6) (2.5–3.6) (2.5–3.6) (11–70) (14–41) (8.9–21) (7.4–12) (4.6–7.8) (4.1–7.2) (3.8–6.7) (2.0–2.0) (2.2–2.2) (0.45–0.45) (0.45–0.46) (0.27–0.28) (0.25–0.25) (0.23–0.23) (0–0) (2.1–2.2) (2.3–2.5) (2.1–2.3) (2.3–2.6) (2.3–2.6) (2.3–2.6) (3.8–4.2) (6.3–11) (0.71–0.92) (3.3–3.6) (1.3–1.5) (1.2–1.4) (1.1–1.4) (0.95–1.1) (3.6–3.8) (3.0–3.6) (0.86–0.87) (4.7–4.8) (2.5–2.6) (2.5–2.6) (0–2.0) (0–1.4) (<0.1–0.43) (4.6–9.2) (1.7–6.2) (0.98–1.5) (1.5–1.9) (2.3–2.9) (2.3–2.9) (2.3–2.9) (2.5–2.7) (2.7–2.7) (1.9–2.0) (1.4–1.4) (2.1–2.1) (2.1–2.1) (2.1–2.1) (0–0) (0–0) (5.7–6.6) (3.9–4.0) (3.4–3.7) (3.4–3.7) (3.4–3.7) (0.99–1.0) (0.50–0.52) (0.28–0.29) (0.21–0.22) (0.19–0.20) (0.14–0.16) (0.12–0.15) (2.5–3.0) (2.3–2.4) (2.0–2.2) (1.9–2.1) (1.5–1.7) (1.5–1.6) (1.4–1.6) (3.0–3.1) (2.4–2.4) (2.8–2.8) (0.94–0.95) (0.94–0.97) (0.94–0.97) (0.94–0.97) (4.2–4.4) (3.6–3.8) (2.7–2.8) (2.3–2.4) (1.4–3.8) (1.4–3.8) (1.4–3.8)

1.9 1.6 1.6 1.8 2.2 2.3 2.4 4.2 3.7 3.8 4.1 4.2 4.2 4.2 120 85 70 54 37 37 36 0.22 0.4 0.27 0.15 0.12 0.07 0.11 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.027 0.035 0.024 0.023 0.015 0.011 <0.01 0.071 0.061 0.055 0.049 0.035 0.031 0.027 <0.01 <0.01 <0.01 0.53 0.69 0.6 0.47 0.35 0.33 0.31 0.21 0.23 0.29 0.2 0.26 0.26 0.37 <0.01 0.016 0.013 <0.01 0.015 0.01 38 35 24 21 17 16 15 1.5 0.91 0.96 0.89 0.96 1.2 1.1 <0.01 <0.01 0.011 0.011 0.011 0.011 0.011 11 12 12 13 15 15 15

(0.740–3.6) (0.600–3.0) (0.600–3.0) (0.670–3.4) (0.920–3.9) (1.0–4.0) (1.2–4.2) (2.0–7.0) (1.9–6.2) (1.9–6.4) (2.1–7.0) (2.0–7.1) (2.1–7.1) (2.1–7.1) (42–240) (37–150) (30–130) (23–99) (12–77) (12–74) (12–73) (0.064–0.460) (0.170–0.740) (0.110–0.490) (0.066–0.270) (0.055–0.210) (0.026–0.140) (0.053–0.200) (<0.01–<0.01) (<0.01–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.051) (0.014–0.065) (<0.01–0.044) (<0.01–0.044) (<0.01–0.033) (<0.01–0.022) (<0.01–0.018) (0.025–0.140) (0.028–0.110) (0.026–0.094) (0.020–0.092) (0.011–0.071) (0.010–0.064) (<0.01–0.061) (<0.01–0.011) (<0.01–<0.01) (<0.01–<0.01) (0.200–1.0) (0.230–1.4) (0.180–1.3) (0.150–0.980) (0.120–0.700) (0.130–0.620) (0.120–0.590) (0.099–0.350) (0.090–0.440) (0.140–0.490) (0.073–0.390) (0.096–0.500) (0.096–0.520) (0.170–0.650) (<0.01–0.015) (<0.01–0.029) (<0.01–0.021) (<0.01–0.015) (<0.01–0.026) (<0.01–0.022) (15–71) (15–62) (10–45) (9.3–38) (7.1–30) (6.7–28) (6.5–27) (0.690–2.6) (0.340–1.8) (0.410–1.7) (0.390–1.6) (0.400–1.8) (0.560–2.1) (0.490–2.1) (<0.01–0.011) (<0.01–0.016) (<0.01–0.020) (<0.01–0.020) (<0.01–0.020) (<0.01–0.020) (<0.01–0.020) (3.9–20) (5.4–20) (5.5–21) (6.2–23) (7.3–25) (7.3–25) (7.6–26)

77 57 52 53 59 61 64 98 78 72 70 65 64 63 554 355 268 195 127 124 121 6.1 11 7 4 3.2 1.9 3 0.56 17 7.3 3.7 5.6 5.1 5.1 19 24 15 14 8.6 6.1 4.8 66 57 51 45 32 29 24 11 7.4 3.3 129 157 128 94 66 62 58 17 19 23 15 20 20 28 47 86 47 24 47 32 15 13 8.6 7.2 5.3 5 4.7 48 28 29 27 29 36 34 5.6 7.3 9.9 9.9 9.9 9.9 9.9 53 53 50 50 52 50 52

(30–146) (22–110) (20–99) (20–101) (25–107) (28–108) (30–110) (48–165) (39–129) (36–120) (35–118) (32–110) (32–108) (31–106) (191–1 100) (156–634) (116–481) (82–357) (40–263) (42–248) (41–243) (1.8–13) (4.5–20) (2.9–13) (1.7–7.1) (1.5–5.6) (0.69–3.7) (1.4–5.3) (0.17–1.2) (6.2–32) (2.2–15) (1.1–7.9) (1.6–12) (1.3–12) (1.7–10) (7.2–37) (9.6–44) (5.9–28) (5.4–26) (2.5–18) (2.0–13) (1.5–9.9) (24–129) (26–99) (24–87) (18–84) (10–65) (9.1–59) (5.6–56) (3.0–25) (1.6–17) (1.3–6.3) (50–245) (52–320) (38–273) (30–195) (22–133) (24–117) (22–110) (8.1–29) (7.2–35) (11–39) (5.7–30) (7.2–38) (7.2–39) (13–48) (14–100) (37–156) (24–79) (7.5–50) (21–82) (9.1–68) (5.9–28) (5.7–23) (3.6–16) (3.1–13) (2.3–9.6) (2.1–9.0) (2.0–8.4) (22–83) (11–54) (12–53) (12–48) (12–53) (17–62) (14–61) (2.1–11) (2.2–15) (3.8–19) (3.9–19) (3.9–19) (3.8–19) (3.9–19) (20–103) (25–92) (22–88) (23–87) (25–87) (25–85) (25–87)

1.2 1.3 1.4 1.6 1.8 1.8 1.8 2.8 2.5 2.6 2.9 3 3 3 69 58 48 39 31 30 29 0.18 0.3 0.2 0.13 0.092 0.058 0.082 0 <0.01 0 0 <0.01 <0.01 <0.01 0.021 0.027 0.018 0.018 0.012 <0.01 <0.01 0.029 0.029 0.028 0.027 0.027 0.026 0.026 <0.01 <0.01 <0.01 0.26 0.4 0.4 0.31 0.24 0.23 0.22 0.14 0.19 0.23 0.19 0.25 0.26 0.32 0 <0.01 0.012 <0.01 <0.01 0.01 <0.01 30 26 19 16 13 12 11 1 0.72 0.74 0.72 0.8 0.94 0.93 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 7 7.7 8.4 9 9.7 9.8 9.9

(0.810–1.6) (1.1–1.6) (1.2–1.7) (1.3–1.9) (1.5–2.0) (1.6–2.0) (1.6–2.0) (2.6–3.0) (2.3–2.7) (2.4–2.8) (2.7–3.1) (2.7–3.2) (2.8–3.2) (2.8–3.2) (43–100) (47–70) (39–57) (33–46) (27–35) (26–34) (25–32) (0.160–0.210) (0.260–0.340) (0.180–0.230) (0.110–0.150) (0.081–0.100) (0.050–0.065) (0.072–0.092) (0–0) (<0.01–<0.01) (0–0) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.019–0.024) (0.023–0.030) (0.016–0.021) (0.016–0.020) (0.011–0.014) (<0.01–0.010) (<0.01–<0.01) (0.018–0.043) (0.023–0.035) (0.023–0.033) (0.022–0.033) (0.022–0.032) (0.022–0.032) (0.022–0.031) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.170–0.360) (0.260–0.570) (0.260–0.580) (0.200–0.450) (0.160–0.340) (0.170–0.310) (0.160–0.290) (0.120–0.160) (0.170–0.220) (0.200–0.260) (0.170–0.220) (0.220–0.290) (0.230–0.290) (0.280–0.360) (0–0) (<0.01–<0.01) (0.010–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.012) (<0.01–0.010) (26–33) (23–30) (16–21) (14–18) (11–15) (11–14) (10–13) (0.890–1.2) (0.630–0.810) (0.650–0.840) (0.630–0.810) (0.700–0.910) (0.820–1.1) (0.810–1.1) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (4.9–9.4) (6.3–9.2) (6.8–10) (7.4–11) (8.0–12) (8.1–12) (8.2–12)

47 47 47 47 48 48 48 66 52 49 49 46 45 45 317 242 184 140 106 101 95 5.2 8.2 5.3 3.5 2.5 1.6 2.2 0 13 0 0 4.4 2.2 4.3 15 18 12 11 6.9 5.1 3.3 27 27 26 25 24 24 24 8.1 5.3 2.6 63 92 86 63 46 44 41 11 15 18 15 19 19 24 0 36 63 29 22 33 28 12 9.8 6.6 5.4 4.1 3.8 3.6 33 22 22 22 24 28 27 4.5 4.3 7.7 7.7 7.7 7.7 7.7 35 35 34 34 33 33 33

(33–65) (39–57) (39–56) (39–57) (42–54) (42–54) (42–54) (61–72) (48–56) (45–53) (45–53) (42–50) (42–49) (41–48) (196–468) (198–290) (151–221) (118–164) (93–120) (88–114) (83–108) (4.6–5.9) (7.2–9.2) (4.6–6.0) (3.0–3.9) (2.2–2.8) (1.4–1.8) (1.9–2.5) (0–0) (12–15) (0–0) (0–0) (3.8–5.0) (1.9–2.5) (3.8–4.9) (13–17) (16–21) (10–13) (9.5–12) (6.1–7.8) (4.5–5.8) (2.9–3.7) (17–40) (22–32) (21–31) (20–30) (20–29) (20–29) (20–29) (7.1–9.2) (4.6–6.0) (2.3–2.9) (41–90) (59–131) (56–124) (41–90) (31–65) (32–58) (30–55) (9.9–13) (13–17) (16–20) (13–17) (17–21) (17–22) (21–27) (0–0) (32–41) (55–72) (26–33) (20–25) (29–37) (25–32) (10–13) (8.5–11) (5.8–7.5) (4.8–6.1) (3.6–4.7) (3.4–4.3) (3.2–4.1) (29–37) (20–25) (20–25) (19–24) (21–27) (24–31) (24–31) (3.9–5.0) (3.8–4.9) (6.8–8.7) (6.8–8.7) (6.8–8.7) (6.8–8.7) (6.8–8.7) (25–47) (28–42) (28–41) (28–41) (27–40) (27–40) (27–39)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

185

region of the americas

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSE NUMBER RATEa

b

CASE DETECTION PERCENT

Anguilla

1990 1995 2000 2005 2010 2011 2012 Antigua and 1990 Barbuda 1995 2000 2005 2010 2011 2012 Argentina 1990 1995 2000 2005 2010 2011 2012 Aruba 1990 1995 2000 2005 2010 2011 2012 Bahamas 1990 1995 2000 2005 2010 2011 2012 Barbados 1990 1995 2000 2005 2010 2011 2012 Belize 1990 1995 2000 2005 2010 2011 2012 Bermuda 1990 1995 2000 2005 2010 2011 2012 Bolivia 1990 (Plurinational 1995 State of) 2000 2005 2010 2011 2012 Bonaire, Saint 2010 Eustatius and Saba 2011 2012 Brazil 1990 1995 2000 2005 2010 2011 2012 British Virgin 1990 Islands 1995 2000 2005 2010 2011 2012 Canada 1990 1995 2000 2005 2010 2011 2012 Cayman Islands 1990 1995 2000 2005 2010 2011 2012 Chile 1990 1995 2000 2005 2010 2011 2012 Colombia 1990 1995 2000 2005 2010 2011 2012 a b

<1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 33 35 37 39 40 41 41 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 7 8 8 9 10 10 10 <1 <1 <1 150 162 175 186 195 197 199 <1 <1 <1 <1 <1 <1 <1 28 29 31 32 34 34 35 <1 <1 <1 <1 <1 <1 <1 13 14 15 16 17 17 17 33 37 40 43 46 47 48

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0 <0.01 <0.01 <0.01 <0.01 <0.01 19 17 15 13 11 11 10 <0.01 0.013 0.014 0.016 0.016 0.016 0.016 0.053 0.066 0.094 0.055 0.036 0.047 0.037 <0.01 <0.01 <0.01 0.014 <0.01 0 <0.01 0.075 0.083 0.095 0.11 0.12 0.13 0.13 0 <0.01 0 <0.01 <0.01 <0.01 <0.01 17 16 16 15 14 14 13 0 <0.01 0 130 120 110 95 91 95 92 <0.01 <0.01 <0.01 0 <0.01 0 0 2.3 2.3 2 1.8 1.6 1.6 1.6 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 7.1 4.8 3.5 2.9 2.7 2.8 2.8 18 18 17 17 16 16 16

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (13–28) (14–21) (12–18) (11–15) (9.1–13) (8.9–13) (8.6–12) (<0.01–0.011) (0.011–0.014) (0.013–0.016) (0.014–0.018) (0.014–0.018) (0.014–0.018) (0.014–0.018) (0.046–0.060) (0.057–0.074) (0.083–0.110) (0.048–0.062) (0.031–0.040) (0.041–0.053) (0.032–0.042) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.012–0.016) (<0.01–<0.01) (0–0) (<0.01–<0.01) (0.052–0.100) (0.068–0.099) (0.078–0.110) (0.094–0.120) (0.100–0.150) (0.100–0.150) (0.110–0.160) (0–0) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (11–24) (14–19) (13–19) (12–18) (11–16) (11–16) (11–16) (0–0) (<0.01–<0.01) (0–0) (79–180) (94–140) (86–130) (80–110) (75–110) (78–110) (76–110) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (0–0) (0–0) (2.0–2.6) (2.0–2.6) (1.7–2.2) (1.6–2.0) (1.4–1.8) (1.4–1.9) (1.4–1.8) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (6.2–8.0) (4.2–5.4) (3.0–3.9) (2.5–3.3) (2.4–3.1) (2.5–3.2) (2.4–3.1) (12–25) (14–21) (14–21) (14–20) (13–19) (13–19) (13–19)

24 23 23 22 21 21 21 1.9 0 5.9 8.4 9.2 7.8 3.9 60 49 40 33 27 26 25 16 16 16 16 16 16 16 21 23 32 17 9.9 13 9.9 2.2 1.3 1.3 5.1 2.5 0 1.6 40 40 40 40 40 40 40 0 7.5 0 8.1 1.8 1.8 5.3 251 215 184 158 135 131 127 0 6.3 0 84 71 60 51 46 48 46 17 17 5.6 0 4.2 0 0 8.3 7.7 6.5 5.5 4.6 4.8 4.6 9.2 7.3 14 1.2 8.3 4.1 12 54 33 22 18 16 16 16 54 48 43 38 34 34 33

(15–35) (20–27) (18–27) (18–26) (18–25) (17–25) (17–25) (1.6–2.1) (0–0) (5.2–6.7) (7.3–9.5) (8.1–10) (6.9–8.9) (3.4–4.4) (39–85) (40–59) (33–49) (27–40) (23–32) (22–31) (21–30) (14–18) (14–18) (14–18) (14–18) (14–18) (14–18) (14–18) (18–23) (21–26) (28–36) (15–19) (8.7–11) (11–15) (8.7–11) (1.9–2.5) (1.1–1.5) (1.1–1.5) (4.4–5.7) (2.2–2.8) (0–0) (1.4–1.8) (28–54) (33–48) (33–48) (34–46) (33–48) (33–48) (33–48) (0–0) (6.6–8.5) (0–0) (7.1–9.1) (1.6–2.0) (1.5–2.0) (4.6–6.0) (166–354) (185–248) (151–221) (129–190) (111–161) (108–156) (105–151) (0–0) (5.5–7.2) (0–0) (53–121) (58–85) (49–72) (43–60) (38–55) (40–57) (38–55) (15–20) (15–20) (4.9–6.3) (0–0) (3.7–4.8) (0–0) (0–0) (7.3–9.4) (6.8–8.7) (5.7–7.3) (4.8–6.3) (4.0–5.2) (4.2–5.4) (4.0–5.2) (8.1–10) (6.4–8.2) (12–16) (1.1–1.4) (7.3–9.4) (3.6–4.6) (11–14) (47–61) (29–37) (20–25) (15–20) (14–18) (14–18) (14–18) (36–75) (39–58) (35–52) (31–46) (28–41) (28–40) (27–39)

0 2

0 20

0 88 (75–100)

<0.01 <0.01 <0.01 <0.01 0.16 0.27 0.29 0.28 0.27 0.27 0.27

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.11–0.23) (0.22–0.32) (0.24–0.35) (0.23–0.34) (0.23–0.32) (0.23–0.32) (0.22–0.32)

4.2 7.7 4.9 1.5 0.5 0.8 0.8 0.7 0.7 0.7 0.7

(1.6–7.9) (4.9–11) (2.6–7.9) (0.50–3.0) (0.33–0.71) (0.62–0.91) (0.64–0.95) (0.59–0.87) (0.56–0.80) (0.55–0.80) (0.55–0.78)

1 0 0 1 0 4 6 7 6 3 12 309 13 450 11 767 10 576 7 336 9 733 8 758

7.3 0 0 1.6 0 5.2 7.3 8 6.8 3.4 38 39 32 27 18 24 21

34 (29–41) 0 0 87 (77–99) 87 87 87 87 87 63 79 79 82 67 91 84 (77–99) (77–99) (77–99) (77–99) (77–99) (44–97) (65–96) (66–96) (68–100) (56–80) (76–110) (71–100)

0.019 0.029 0.041 0.022 0.013 0.012 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.011 0.018 0.022 0.025 0.026 0.026

(0.017–0.021) (0.026–0.033) (0.036–0.047) (0.020–0.025) (0.012–0.015) (0.011–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.013) (0.015–0.022) (0.019–0.026) (0.021–0.030) (0.021–0.031) (0.021–0.032)

7.4 10 14 6.8 3.7 3.3 2.3 0.1 0.2 0.3 1.6 1 0.5 2.8 5.3 7.5 8.2 8.2 8.1 8.1

(6.5–8.3) (9.1–12) (12–16) (5.9–7.7) (3.2–4.2) (2.9–3.7) (2.0–2.6) (0.12–0.15) (0.14–0.18) (0.24–0.31) (1.4–1.8) (0.83–1.1) (0.47–0.60) (1.9–3.8) (4.3–6.4) (6.2–9.1) (7.1–9.4) (6.7–9.8) (6.6–9.7) (6.6–9.7)

6 8 28 46 57 82 48 31 41 32 5 3 3 6 0 4 57 95 106 102 145 74 84 0 4 0 1 1 3 11 166 14 422 10 127 9 748 8 363 8 521 8 257 0 1 0 74 570 91 013 77 899 80 675 74 395 77 647 75 122

5.9 7.8 27 18 20 28 15 8.6 11 8.6 1.9 1.1 1.1 2.1 0 1.4 30 46 44 38 47 23 26 0 6.5 0 1.5 1.5 4.6 164 189 119 104 82 83 79 0 5.5 0 50 56 45 43 38 39 38

37 50 170 87 87 87 87 87 87 87 87 87 87

(33–43) (44–57) (150–200) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

87 (77–99) 87 76 110 110 94 120 59 65 (77–99) (56–110) (96–140) (93–140) (82–110) (98–140) (49–72) (54–79)

87 (77–99)

0.86 0.94 0.86 0.77 0.52 0.48 0.43

(0.57–1.2) (0.80–1.1) (0.71–1.0) (0.63–0.92) (0.43–0.62) (0.40–0.57) (0.36–0.52)

13 12 10 8.2 5.1 4.7 4.1

(8.4–18) (11–14) (8.3–12) (6.7–9.8) (4.2–6.1) (3.8–5.5) (3.4–4.9)

87 87 87 65 88 65 66 61 63 62

(77–99) (77–99) (77–99) (46–99) (76–100) (54–79) (55–81) (51–74) (53–76) (52–75)

87 (77–99) 60 79 74 85 82 82 82 (41–94) (66–97) (62–91) (72–100) (69–99) (69–99) (69–99)

5.5 12 12 15 17 17 16

(3.5–8.0) (9.9–15) (9.8–14) (12–18) (14–20) (14–20) (13–19)

3.7 7.5 6.9 8 8.5 8.6 8

(2.3–5.3) (6.1–9.0) (5.6–8.3) (6.7–9.4) (7.1–10) (7.1–10) (6.6–9.5)

0.11 0.17 0.098 0.11 0.11 0.11 0.11

(0.095–0.12) (0.15–0.20) (0.086–0.11) (0.094–0.12) (0.095–0.12) (0.098–0.13) (0.096–0.12)

0.4 0.6 0.3 0.3 0.3 0.3 0.3

(0.34–0.44) (0.52–0.67) (0.28–0.36) (0.29–0.38) (0.28–0.36) (0.28–0.37) (0.28–0.36)

1 0 1 0 0 1 997 1 965 1 723 1 552 1 361 1 430 1 653 2 2 5 4 2 6 6 151 4 150 3 021 2 505 2 376 2 450 2 394 12 447 9 912 11 630 10 360 11 420 11 884 11 424

4.8 0 3.7 0 0 7.2 6.7 5.6 4.8 4 4.1 4.7 8 6.3 12 7.2 3.5 10 47 29 20 15 14 14 14 37 27 29 24 25 25 24

87 (77–99) 87 (77–99)

87 87 87 87 87 87 100 87 87 87 87 87 87 87 87 87 87 87 87 87 70 56 68 62 71 75 73

(77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (91–120) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (50–100) (47–69) (56–83) (52–76) (60–86) (63–91) (61–88)

0.021 0.043 0.072 0.084 0.086 0.088 0.084 0.36 1.2 1.7 1.8 1.8 1.7 1.6

(0.019–0.024) (0.038–0.049) (0.063–0.081) (0.074–0.095) (0.076–0.098) (0.077–0.099) (0.074–0.095) (0.24–0.50) (0.95–1.4) (1.4–2.0) (1.4–2.1) (1.5–2.1) (1.4–2.0) (1.3–1.9)

0.2 0.3 0.5 0.5 0.5 0.5 0.5 1.1 3.2 4.3 4.1 3.8 3.5 3.3

(0.14–0.18) (0.26–0.34) (0.41–0.53) (0.45–0.58) (0.44–0.57) (0.44–0.57) (0.42–0.54) (0.73–1.5) (2.6–3.8) (3.5–5.1) (3.3–4.9) (3.1–4.6) (2.9–4.2) (2.7–4.0)

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

186

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSE NUMBER RATE a

b

CASE DETECTION PERCENT

Costa Rica

Cuba

Curaçao

Dominica

Dominican Republic

Ecuador

El Salvador

Grenada

Guatemala

Guyana

Haiti

Honduras

Jamaica

Mexico

Montserrat

Netherlands Antilles

Nicaragua

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 1990 1995 2000 2005 2010 2011 2012

3 3 4 4 5 5 5 11 11 11 11 11 11 11 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 7 8 9 9 10 10 10 10 11 13 14 15 15 15 5 6 6 6 6 6 6 <1 <1 <1 <1 <1 <1 <1 9 10 11 13 14 15 15 <1 <1 <1 <1 <1 <1 <1 7 8 9 9 10 10 10 5 6 6 7 8 8 8 2 2 3 3 3 3 3 86 95 104 111 118 119 121 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 4 5 5 5 6 6 6

1.5 1.5 1.4 1 0.65 0.59 0.51 2.6 2 1.4 1 1 1 1 <0.01 <0.01 <0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 11 9.7 8.6 7.7 6.7 6.6 6.4 18 15 13 11 9.7 9.4 9.1 3.4 2.6 2.2 2.4 1.8 1.7 1.6 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 6.6 7.1 7.6 8.2 8.8 9 9.1 0.65 0.65 0.78 0.88 0.87 0.87 0.87 18 19 23 25 23 22 22 5.6 6.4 7.1 5 4.1 4.2 4.3 0.15 0.16 0.17 0.18 0.18 0.18 0.18 57 44 32 25 26 27 27 <0.01 <0.01 0 <0.01 0 0 0 <0.01 0.01 <0.01 <0.01 4.5 4 3.4 2.9 2.5 2.4 2.3

(1.3–1.7) (1.3–1.7) (1.2–1.5) (0.880–1.1) (0.570–0.740) (0.510–0.660) (0.440–0.580) (1.6–3.9) (1.7–2.5) (1.1–1.8) (0.850–1.3) (0.840–1.3) (0.830–1.3) (0.840–1.3) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.015) (<0.01–0.012) (<0.01–0.012) (<0.01–0.011) (<0.01–0.011) (<0.01–0.011) (<0.01–0.011) (6.6–16) (7.9–12) (7.1–10) (6.3–9.2) (5.6–8.0) (5.4–7.8) (5.3–7.6) (11–26) (13–19) (11–16) (9.4–14) (8.0–12) (7.8–11) (7.5–11) (2.3–4.7) (2.3–2.9) (1.8–2.6) (1.9–2.9) (1.5–2.0) (1.4–1.9) (1.4–1.8) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (4.1–9.7) (5.8–8.5) (6.2–9.1) (6.7–9.9) (7.3–11) (7.4–11) (7.5–11) (0.400–0.960) (0.530–0.780) (0.630–0.930) (0.720–1.1) (0.720–1.0) (0.720–1.0) (0.710–1.0) (11–26) (16–23) (19–28) (21–30) (19–27) (18–27) (18–26) (3.6–7.9) (4.1–9.2) (4.6–10) (3.2–7.2) (2.7–5.9) (2.7–6.0) (2.8–6.1) (0.110–0.210) (0.130–0.190) (0.140–0.200) (0.140–0.210) (0.150–0.210) (0.150–0.220) (0.150–0.220) (49–66) (38–51) (27–37) (21–28) (23–30) (23–31) (23–32) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (0–0) (0–0) (0–0) (<0.01–0.011) (<0.01–0.012) (<0.01–<0.01) (<0.01–<0.01) (2.9–6.3) (3.2–4.8) (2.8–4.1) (2.4–3.5) (2.1–2.8) (2.0–2.7) (2.0–2.7)

48 43 35 23 14 12 11 25 19 13 9.2 9.3 9.3 9.3 3.9 0.76 0.74 15 14 14 13 13 13 13 148 121 100 82 67 65 62 174 136 107 83 65 62 59 63 45 37 39 28 27 25 4.6 4.5 4.4 4.2 4.1 4.1 4.1 74 71 68 65 62 61 60 89 89 104 115 111 110 109 247 247 271 272 230 222 213 113 115 114 73 54 54 54 6.5 6.5 6.5 6.5 6.6 6.6 6.6 67 46 31 22 22 23 23 11 4.1 0 24 0 0 0 5.3 5.3 3.2 4.7 108 85 68 53 42 40 38

(42–54) (37–48) (31–39) (20–26) (12–16) (11–14) (9.3–12) (15–37) (15–23) (10–16) (7.5–11) (7.4–11) (7.4–11) (7.4–11) (3.4–4.4) (0.67–0.86) (0.65–0.84) (9.3–21) (12–17) (11–17) (11–16) (11–16) (11–16) (11–15) (91–218) (99–146) (82–120) (67–98) (55–80) (53–77) (51–74) (108–257) (111–164) (87–128) (68–100) (54–77) (51–74) (48–70) (43–88) (39–50) (30–44) (32–47) (24–33) (23–31) (22–29) (2.9–6.8) (3.8–5.2) (3.6–5.2) (3.5–5.1) (3.4–4.9) (3.4–4.9) (3.4–4.9) (47–109) (58–85) (55–81) (53–78) (51–73) (50–73) (50–72) (55–132) (73–107) (85–125) (94–138) (91–132) (91–131) (90–130) (153–365) (202–297) (221–325) (222–326) (190–275) (183–265) (176–254) (73–162) (74–164) (74–163) (47–104) (35–77) (35–77) (35–77) (4.7–8.8) (5.4–7.9) (5.4–7.9) (5.4–7.9) (5.4–7.8) (5.4–7.8) (5.4–7.8) (57–77) (40–53) (26–36) (19–26) (19–26) (19–26) (19–26) (9.4–12) (3.6–4.7) (0–0) (21–27) (0–0) (0–0) (0–0) (4.6–6.0) (4.6–6.0) (2.8–3.7) (4.1–5.3) (71–152) (70–102) (55–81) (44–64) (36–49) (35–46) (33–44)

0.031 0.066 0.092 0.074 0.074 0.071 0.064 0.023 0.028 0.033 0.023 0.035 0.037 0.037

(0.027–0.035) (0.058–0.075) (0.080–0.10) (0.065–0.084) (0.065–0.084) (0.062–0.080) (0.056–0.072) (0.014–0.034) (0.023–0.034) (0.026–0.040) (0.019–0.028) (0.028–0.043) (0.030–0.045) (0.030–0.046)

1 1.9 2.3 1.7 1.6 1.5 1.3 0.2 0.3 0.3 0.2 0.3 0.3 0.3

(0.87–1.1) (1.7–2.2) (2.0–2.7) (1.5–1.9) (1.4–1.8) (1.3–1.7) (1.2–1.5) (0.13–0.32) (0.21–0.31) (0.23–0.36) (0.16–0.24) (0.25–0.38) (0.26–0.40) (0.26–0.41)

230 586 585 534 492 514 475 546 1 553 1 183 772 827 805 734 5 1 1 6 8

7.5 17 15 12 11 11 9.9 5.2 14 11 6.8 7.3 7.1 6.5 3.4 0.66 0.64 8.5 11

16 40 43 53 75 88 93 21 76 82 74 79 77 70 87 87 87 57 78

(14–18) (35–45) (38–49) (47–61) (67–86) (78–100) (82–110) (14–34) (63–94) (67–100) (61–91) (65–99) (63–97) (57–88) (77–99) (77–99) (77–99) (40–91) (66–95)

(77–100)

<0.01 (<0.01–<0.01) <0.01 0.14 0.38 0.78 0.99 1.3 1.4 1.5 0.05 0.12 0.24 0.27 0.22 0.22 0.2 3.2 5.6 6.8 6.5 4.6 4.5 4.3 0.24 0.77 0.84 0.37 0.19 0.18 0.17 0.01 0.033 0.052 0.053 0.042 0.041 0.04 2.6 2.6 2 1.5 1.5 1.6 1.6 (0–<0.01) (0.086–0.20) (0.31–0.46) (0.63–0.93) (0.81–1.2) (1.1–1.5) (1.1–1.7) (1.2–1.8) (0.031–0.074) (0.098–0.14) (0.20–0.29) (0.22–0.33) (0.18–0.27) (0.18–0.26) (0.16–0.23) (2.0–4.8) (4.6–6.8) (5.6–8.2) (5.3–7.9) (3.8–5.5) (3.7–5.4) (3.5–5.1) (0.16–0.35) (0.49–1.1) (0.52–1.2) (0.23–0.54) (0.12–0.28) (0.11–0.26) (0.10–0.25) (<0.01–0.013) (0.027–0.040) (0.042–0.062) (0.043–0.064) (0.034–0.050) (0.034–0.049) (0.033–0.048) (2.2–3.0) (2.2–3.0) (1.7–2.3) (1.3–1.7) (1.3–1.7) (1.3–1.8) (1.4–1.8)

1 (<0.1–3.2) 0.5 1.5 3.8 6.9 7.8 9 9.5 10 6.9 16 33 36 28 27 25 45 72 79 71 47 45 42 4.9 14 14 5.4 2.5 2.3 2.1 0.4 1.4 2 2 1.5 1.5 1.5 3 2.7 1.9 1.3 1.3 1.3 1.3 (0–3.0) (0.97–2.3) (3.1–4.6) (5.7–8.3) (6.4–9.4) (7.4–11) (7.8–11) (8.2–12) (4.3–10) (13–20) (27–39) (29–43) (23–34) (22–33) (20–29) (28–67) (59–87) (65–95) (58–85) (39–56) (37–54) (35–50) (3.2–7.1) (8.7–20) (8.4–20) (3.3–7.9) (1.5–3.7) (1.4–3.4) (1.3–3.2) (0.30–0.57) (1.1–1.6) (1.6–2.4) (1.6–2.4) (1.3–1.8) (1.2–1.8) (1.2–1.7) (2.6–3.5) (2.3–3.1) (1.6–2.2) (1.1–1.5) (1.1–1.5) (1.1–1.5) (1.1–1.5)

4 2 1 3 813 3 119 2 913 3 803 3 322 3 040 3 442 168 296 422 639 712 710 748 6 212 10 420 14 311 14 222 14 315 16 568 3 647 4 984 6 406 3 333 2 876 3 233 3 014 123 109 127 90 130 105 91 14 437 11 329 18 434 18 524 20 155 19 857 20 470 1 0 1 0 0 0

3.8 1.9 0.95 43 31 26 30 23 21 23 23 41 57 84 91 90 94 79 121 155 144 143 163 74 89 103 48 38 42 38 5.2 4.4 4.9 3.4 4.7 3.8 3.3 17 12 18 17 17 17 17 9.3 0 21 0 0 0

93 46 23 58 44 38 46 38 34 38 26 45 54 73 82 82 86 32 45 57 62 64 76 66 78 90 66 70 77 70 79 68 75 51 72 58 50 25 26 58 75 77 73 75 87

(78–110) (39–56) (19–28) (39–92) (37–54) (32–47) (39–57) (32–46) (28–41) (32–46) (18–42) (38–56) (45–67) (61–89) (68–99) (68–99) (72–100) (27–39) (37–55) (47–70) (52–76) (54–78) (64–93) (46–100) (54–120) (63–140) (46–100) (49–110) (54–120) (49–110) (59–110) (56–83) (63–92) (43–63) (61–88) (49–70) (42–61) (22–29) (22–30) (50–67) (66–87) (66–89) (63–86) (64–87) (77–99)

87 (77–99)

5 0.015 0.02 0.027 0.034 0.042 0.044 0.047 (<0.01–0.025) (0.011–0.031) (0.015–0.041) (0.020–0.053) (0.025–0.062) (0.027–0.066) (0.028–0.070) 0.4 0.4 0.5 0.6 0.7 0.8 0.8 (0.18–0.61) (0.24–0.66) (0.30–0.81) (0.36–0.97) (0.43–1.1) (0.45–1.1) (0.47–1.2) 2 944 2 842 2 402 1 907 2 448 2 693 2 790

2.8 71 61 47 35 42 46 47

87 (77–99) 66 72 70 65 100 110 120 (47–100) (60–88) (58–85) (54–80) (86–120) (98–130) (110–140)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

187

region of the americas

0.25 0.81 1.1 0.98 0.64 0.59 0.54 0.71 0.96 1.2 1.2 0.97 0.92 0.84 0.082 0.16 0.23 0.27 0.19 0.18 0.2

(0.15–0.37) (0.66–0.98) (0.90–1.3) (0.80–1.2) (0.53–0.76) (0.49–0.71) (0.44–0.64) (0.44–1.0) (0.78–1.2) (0.96–1.4) (0.99–1.5) (0.80–1.2) (0.76–1.1) (0.70–1.0) (0.055–0.11) (0.14–0.18) (0.19–0.28) (0.22–0.32) (0.16–0.21) (0.15–0.20) (0.17–0.23)

3.5 10 13 11 6.4 5.8 5.2 7 8.5 9.4 8.8 6.5 6 5.4 1.5 2.7 3.9 4.4 3 2.8 3.2

(2.1–5.1) (8.3–12) (10–15) (8.6–13) (5.2–7.6) (4.8–7.0) (4.3–6.3) (4.3–10) (6.9–10) (7.7–11) (7.2–11) (5.3–7.7) (5.0–7.2) (4.5–6.5) (1.0–2.1) (2.4–3.1) (3.2–4.7) (3.6–5.2) (2.5–3.4) (2.4–3.2) (2.7–3.7)

8 2 7 2 597 4 053 5 291 5 003 3 964 4 309 4 262 8 243 7 893 6 908 4 416 4 832 5 106 5 456 2 367 2 422 1 485 1 794 1 700 1 896 2 053 0 4 0

11 2.8 9.8 36 51 61 54 40 42 41 81 70 55 32 32 33 35 44 42 25 30 27 30 33 0 4 0

86 22 75 24 42 61 65 59 66 67 47 51 52 38 50 54 60 70 95 68 75 96 110 130 0 89 0

(72–100) (18–26) (63–92) (16–39) (35–51) (51–75) (54–80) (49–71) (55–80) (56–81) (32–76) (43–63) (43–63) (32–47) (42–60) (45–66) (50–73) (50–100) (84–110) (56–83) (63–92) (83–110) (98–130) (110–150)

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSEb NUMBER RATEa

CASE DETECTION PERCENT

Panama

Paraguay

Peru

Puerto Rico

Saint Kitts and Nevis

Saint Lucia

Saint Vincent and the Grenadines

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

2 3 3 3 4 4 4 4 5 5 6 6 7 7 22 24 26 28 29 30 30 4 4 4 4 4 4 4 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 1 1 1 1 1 1 1 <1 <1 <1 <1 <1 <1 <1 255 268 285 298 312 315 318 3 3 3 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 20 22 24 27 29 30 30

1.2 1.3 1.4 1.6 1.8 1.8 1.8 2.8 2.5 2.6 2.9 3 3 3 69 58 48 39 31 30 29 0.18 0.3 0.2 0.13 0.092 0.058 0.082 0 <0.01 0 0 <0.01 <0.01 <0.01 0.021 0.027 0.018 0.018 0.012 <0.01 <0.01 0.029 0.029 0.028 0.027 0.027 0.026 0.026 <0.01 <0.01 <0.01 0.26 0.4 0.4 0.31 0.24 0.23 0.22 0.14 0.19 0.23 0.19 0.25 0.26 0.32 0 <0.01 0.012 <0.01 <0.01 0.01 <0.01 30 26 19 16 13 12 11 1 0.72 0.74 0.72 0.8 0.94 0.93 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 7 7.7 8.4 9 9.7 9.8 9.9

(0.810–1.6) (1.1–1.6) (1.2–1.7) (1.3–1.9) (1.5–2.0) (1.6–2.0) (1.6–2.0) (2.6–3.0) (2.3–2.7) (2.4–2.8) (2.7–3.1) (2.7–3.2) (2.8–3.2) (2.8–3.2) (43–100) (47–70) (39–57) (33–46) (27–35) (26–34) (25–32) (0.160–0.210) (0.260–0.340) (0.180–0.230) (0.110–0.150) (0.081–0.100) (0.050–0.065) (0.072–0.092) (0–0) (<0.01–<0.01) (0–0) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.019–0.024) (0.023–0.030) (0.016–0.021) (0.016–0.020) (0.011–0.014) (<0.01–0.010) (<0.01–<0.01) (0.018–0.043) (0.023–0.035) (0.023–0.033) (0.022–0.033) (0.022–0.032) (0.022–0.032) (0.022–0.031) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.170–0.360) (0.260–0.570) (0.260–0.580) (0.200–0.450) (0.160–0.340) (0.170–0.310) (0.160–0.290) (0.120–0.160) (0.170–0.220) (0.200–0.260) (0.170–0.220) (0.220–0.290) (0.230–0.290) (0.280–0.360) (0–0) (<0.01–<0.01) (0.010–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.012) (<0.01–0.010) (26–33) (23–30) (16–21) (14–18) (11–15) (11–14) (10–13) (0.890–1.2) (0.630–0.810) (0.650–0.840) (0.630–0.810) (0.700–0.910) (0.820–1.1) (0.810–1.1) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (4.9–9.4) (6.3–9.2) (6.8–10) (7.4–11) (8.0–12) (8.1–12) (8.2–12)

47 47 47 47 48 48 48 66 52 49 49 46 45 45 317 242 184 140 106 101 95 5.2 8.2 5.3 3.5 2.5 1.6 2.2 0 13 0 0 4.4 2.2 4.3 15 18 12 11 6.9 5.1 3.3 27 27 26 25 24 24 24 8.1 5.3 2.6 63 92 86 63 46 44 41 11 15 18 15 19 19 24 0 36 63 29 22 33 28 12 9.8 6.6 5.4 4.1 3.8 3.6 33 22 22 22 24 28 27 4.5 4.3 7.7 7.7 7.7 7.7 7.7 35 35 34 34 33 33 33

(33–65) (39–57) (39–56) (39–57) (42–54) (42–54) (42–54) (61–72) (48–56) (45–53) (45–53) (42–50) (42–49) (41–48) (196–468) (198–290) (151–221) (118–164) (93–120) (88–114) (83–108) (4.6–5.9) (7.2–9.2) (4.6–6.0) (3.0–3.9) (2.2–2.8) (1.4–1.8) (1.9–2.5) (0–0) (12–15) (0–0) (0–0) (3.8–5.0) (1.9–2.5) (3.8–4.9) (13–17) (16–21) (10–13) (9.5–12) (6.1–7.8) (4.5–5.8) (2.9–3.7) (17–40) (22–32) (21–31) (20–30) (20–29) (20–29) (20–29) (7.1–9.2) (4.6–6.0) (2.3–2.9) (41–90) (59–131) (56–124) (41–90) (31–65) (32–58) (30–55) (9.9–13) (13–17) (16–20) (13–17) (17–21) (17–22) (21–27) (0–0) (32–41) (55–72) (26–33) (20–25) (29–37) (25–32) (10–13) (8.5–11) (5.8–7.5) (4.8–6.1) (3.6–4.7) (3.4–4.3) (3.2–4.1) (29–37) (20–25) (20–25) (19–24) (21–27) (24–31) (24–31) (3.9–5.0) (3.8–4.9) (6.8–8.7) (6.8–8.7) (6.8–8.7) (6.8–8.7) (6.8–8.7) (25–47) (28–42) (28–41) (28–41) (27–40) (27–40) (27–39)

0.072 0.21 0.29 0.3 0.25 0.24 0.23 0.05 0.1 0.15 0.2 0.2 0.22 0.24 0.58 1.2 1.3 0.89 0.53 0.5 0.49

(0.050–0.099) (0.17–0.25) (0.24–0.34) (0.24–0.36) (0.22–0.28) (0.21–0.27) (0.20–0.26) (0.046–0.055) (0.093–0.11) (0.13–0.16) (0.18–0.21) (0.19–0.22) (0.20–0.24) (0.22–0.26) (0.36–0.86) (0.98–1.4) (1.0–1.5) (0.75–1.0) (0.46–0.60) (0.44–0.57) (0.43–0.55)

2.9 7.5 9.5 8.8 6.7 6.5 6.1 1.2 2.1 2.7 3.3 3.2 3.4 3.5 2.7 5 4.9 3.2 1.8 1.7 1.6

(2.0–4.0) (6.1–9.0) (7.9–11) (7.2–11) (5.9–7.6) (5.7–7.3) (5.3–6.8) (1.1–1.3) (1.9–2.3) (2.5–2.9) (3.1–3.6) (2.9–3.4) (3.1–3.6) (3.3–3.8) (1.6–3.9) (4.1–6.0) (4.0–5.8) (2.7–3.8) (1.6–2.0) (1.5–1.9) (1.4–1.8)

0.039 0.017 0.012 0.013

(0.027–0.054) (<0.01–0.027) (<0.01–0.020) (<0.01–0.024)

1 0.5 0.3 0.4

(0.72–1.4) (0.25–0.72) (0.15–0.53) (0.14–0.65)

<0.01 (<0.01–<0.01) <0.01 (<0.01–<0.01)

0.7 (<0.1–2.7) 0.4 (0–1.7)

<0.01 (<0.01–0.015) <0.01 (<0.01–0.017) <0.01 (<0.01–0.016) <0.01 (<0.01–0.017)

3.6 (<0.1–13) 7.3 (2.0–16) 7.6 (2.9–14) 8.7 (3.9–15)

846 1 300 1 169 1 637 1 496 1 571 1 520 2 167 1 745 1 950 2 075 2 352 2 372 2 416 37 905 45 310 38 661 33 747 31 073 31 241 29 760 159 262 174 113 80 50 71 0 5 0 0 2 1 2 13 11 9 14 9 7 11 2 13 16 7 15 17 30 3 2 1 82 89 117 194 125 128 120 166 198 166 219 224 274 0

34 47 38 49 41 42 40 51 36 36 35 36 36 36 174 189 149 122 106 105 99 4.5 7.1 4.6 3 2.2 1.4 1.9 0 12 0 0 3.8 1.9 3.7 9.4 7.5 5.7 8.5 5.1 3.9 6.1 1.9 12 15 6.4 14 16 27 7.1 4.6 2.3 20 19 23 37 24 24 9.8 13 16 13 16 17 20 0

72 99 81 100 85 88 84 77 70 74 71 79 79 81 55 78 81 87 100 100 100 87 87 87 87 87 87 87

(52–100) (83–120) (68–97) (85–130) (76–97) (78–100) (75–95) (71–84) (65–75) (69–81) (66–77) (73–86) (73–86) (75–88) (37–89) (65–96) (67–98) (74–100) (88–110) (93–120) (92–120) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

87 (77–99)

87 87 87 61 41 49 78 73 76 180 6.8 45 57 26 56 64 110 87 87 87 32 22 37 79 54 58 87 87 87 87 87 87 87

(77–99) (77–99) (77–99) (54–70) (36–47) (43–56) (69–89) (65–84) (67–87) (160–210) (4.6–11) (38–55) (48–70) (21–31) (47–68) (54–78) (96–140) (77–99) (77–99) (77–99) (22–50) (15–34) (26–58) (57–120) (41–74) (44–80) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

Sint Maarten (Dutch part) Suriname

Trinidad and Tobago

0.023 0.12 0.16 0.1 0.06 0.053 0.047 <0.01 0.018 0.049 0.048 0.07 0.069 0.083

(0.015–0.033) (0.077–0.17) (0.10–0.22) (0.066–0.15) (0.040–0.085) (0.038–0.071) (0.033–0.062) (<0.01–<0.01) (0.016–0.021) (0.043–0.055) (0.042–0.054) (0.061–0.079) (0.060–0.078) (0.073–0.094)

5.7 28 34 21 12 10 8.7 0.2 1.5 3.9 3.7 5.2 5.1 6.2

(3.7–8.2) (18–39) (22–48) (13–29) (7.7–16) (7.2–13) (6.2–12) (0.16–0.21) (1.3–1.7) (3.4–4.4) (3.2–4.2) (4.6–5.9) (4.5–5.8) (5.5–7.0)

Turks and Caicos Islands

<0.01 (<0.01–<0.01)

4.5 (0.21–15)

United States of America

Uruguay

1.6 2.2 1.2 1.3 1.2 1.1 1.1 0.013 0.022 0.067 0.11 0.13 0.15 0.14

(1.4–1.8) (1.9–2.5) (1.1–1.4) (1.2–1.5) (1.0–1.4) (1.0–1.3) (0.96–1.2) (0.011–0.014) (0.019–0.025) (0.059–0.076) (0.093–0.12) (0.11–0.14) (0.13–0.17) (0.12–0.16)

0.6 0.8 0.4 0.5 0.4 0.4 0.4 0.4 0.7 2 3.2 3.8 4.4 4.2

(0.54–0.69) (0.71–0.91) (0.38–0.49) (0.39–0.50) (0.34–0.43) (0.32–0.41) (0.30–0.39) (0.35–0.46) (0.60–0.78) (1.8–2.3) (2.8–3.6) (3.3–4.3) (3.9–5.0) (3.7–4.8)

US Virgin Islands

6 9 8 25 701 22 728 16 310 14 080 11 181 10 521 9 945 886 625 645 622 699 817 808 4 4

19 28 25 10 8.5 5.7 4.7 3.6 3.3 3.1 28 19 19 19 21 24 24 3.9 3.7

87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87

(77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

Venezuela (Bolivarian Republic of)

0.24 0.42 0.59 0.76 0.89 1.3 1.2

(0.17–0.33) (0.30–0.56) (0.44–0.78) (0.56–0.98) (0.72–1.1) (1.0–1.5) (0.94–1.4)

1.2 1.9 2.4 2.8 3.1 4.3 3.9

(0.88–1.7) (1.4–2.5) (1.8–3.2) (2.1–3.7) (2.5–3.7) (3.5–5.2) (3.1–4.7)

5 457 5 578 6 466 6 847 6 451 6 282 6 495

28 25 26 26 22 21 22

78 73 77 76 67 64 65

(58–110) (60–89) (64–95) (63–93) (56–81) (54–78) (55–79)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

188

NOTIFIED NEW AND RELAPSE inc udes a es f r whi h he treatm

GLOBAL TUBERCULOSIS REPORT 2013

Data for all tory is unkn wn years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE NEW PULM RELAPSE RETREAT UNKNOWN POSITIVE UNKNOWN PULMONARY 0 2 0 0 0 – 0 – – 0

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Anguilla YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSE 0 2 b

•0 Antigua and Barbuda

0•

•2 Argentina

3•

• 38 Aruba

21 •

1 0 0 1 0 4 6 7 6 3 12 309 13 450 11 767 10 576 7 336 9 733 8 758

0 0 0

1 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

3 6 6 6 1 5 698 4 749 4 709 3 973 5 150 4 661

1 0 0 0 1 4 668 4 110 3 357 2 011 2 705 2 341

0 0 0 0 1 3 067 1 773 1 561 854 1 426 1 291

0 0 0 0

0 0 0 0 0

0 0 2 1

0 0 0 2 1

0 1 0

0 159 138 143

104 143 290 314 322

1 724 666 426 758 848

1 828 809 716 1 072 1 170

806 49

•0 Bahamas

27 •

1 1 8 4 7 7 5 0

0

1 1 0 2 1 1 0

1

2 1 0 4 2 2 0

0

• 18 Barbados

9•

38 56 30 19 23 21 3 3 6 0 4 36 44 59 97 64 36 2 0 1 0 1 7 010 6 458 6 278 5 613 5 746 5 568 0 0 0 45 650 41 186 42 093 37 932 40 294 40 152

11 23 8 3 12 11

1 1 0 0

0 2 1 1 0

0 0 0 0

0 0 0 0 34 55 29 47 0 36 2 0 0 1 1 1 408 1 565 1 250 630 643 571 0 0 0 29 291 23 622 23 990 23 030 20 961 20 770

0 0 0 0 1 1 3 0 0 5 0 0 0

0 0 0 0 4 6 11 1 10 7

0 0 0 0

0 0 0 0 4 6 15 1 12 7 0 0 0

•2 Belize

1•

• 30 Bermuda

26 •

6 0 4 57 95 106 102 145 74 84 0 4 0 1 1 3 11 166 14 422 10 127 9 748 8 363 8 521 8 257 0 1 0 74 570 91 013 77 899 80 675 74 395 77 647 75 122

0 0 0 0

0 4 0 2 0

0 0 0 0

100 – 51 44 67 67 100 50 – 50 – 100 0 50 – 83 80 83 90 90 91

0 0 0 1 1 133 1 288 1 673 1 694 1 721 1 672 0 0 0 13 814 10 457 11 037 10 017 10 067 10 297 0 0 0

0 0 0 0 63 451 547 408 411 446 1 0

0 0 0 0

0 0 0 0 63 2 081 772 665 637 673 1 0 0 0 0

•0 Bolivia (Plurinational State of)

5•

0 0 0 0 0

• 164 Bonaire, Saint Eustatius and Saba Brazil

79 •

1 630 225 257 226 227 0 0

18 0 0 0

• 50 Br tish Virgin Islands

38 •

18 15 11

2 634 3 089 3 398 3 555 3 867

8 700 6 548 7 551 6 490 7 633

11 334 9 637 10 949 10 045 11 500

466 0 2 755 25

•0 Canada

0•

•7 Cayman Islands

5•

1 0 1 0 0 1 997 1 965 1 723 1 552 1 361 1 430 1 653 2 2 5 4 2 6 6 151 4 150 3 021 2 505 2 376 2 450 2 394 12 447 9 912 11 630 10 360 11 420 11 884 11 424

1 0 1 0 0 549 436 492 433 358 407 478 0 5 2 1 5 1 561 1 290 1 186 1 154 1 196 1 173 7 530 8 358 6 870 7 028 6 807 6 523

– 61 64 64 62 66 66 – – 100 100

0 0 0 0 516 656 528 446 472 456 574 2 0 2 1 1 1 284 879 502 502 473 538 1 380 1 446 1 429 1 696 2 355 2 279

0 0 0 0 723 634 482 562 444 469 519 1 0 0 0 0 1 017 694 631 553 594 518 1 002 1 487 1 618 1 985 2 275 2 264

0 0 0 0 0 0 20 4 0 0 0

0 0 0 0 180 195 145 39 48 59 58 0 0

0 0 0 0

64 24 22 33

0 0 0 0 180 195 145 103 72 81 91 0 0 0 0 0 225 158 314 263 272 231

0 0 0 0 29 44 56 68 39 39 24

0 0 0 0

•8 Chile

10 •

0 0 0

0 0 0 225 158 186 167 187 165

0 0 0

• 47 Colombia

14 •

0 0 0

128 96 85 66

0 0 0

• 37 a b

24 •

311 0 0

339 443 400 447 358

469 554 405

339 443 869 1 001 763

0 0 0

52 40 48 49 43 47 45 – 0 100 – 50 50 83 – 55 59 70 70 72 69 – 85 85 83 81 74 74

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

189

region of the americas

6 8 28 46 57 82 48 31 41 32 5 3 3

4 7 6

2 0 20

– – 75 100 100 100 50 – 55 54 58 66 66 67 – – – – 67 100 23 – 78 71 79 86 66 66 – 100 100 – 100

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN 245 349 330 267 285 257 834 675 467 462 437 374 5 0 1 5 71 184 81 89 128 99 520 257 160 212 219 200 0 1 0 31 98 104 108 85 102 199 201 103 98 86 112 0 0 0 0 35 19 25 16 17 54 50 40 45 57 46 0 0 3 0 35 45 32 26 22 54 172 49 56 73 60 0 0 3 – 78 65 80 75 69 72 – 62 72 74 69 67 65 100 0 100 – 100 – – 100 100 83 – 66 70 74 73 75 75 – 72 79 83 89 90 93 – – 78 72 74 74 80 – 100 – 100 50 100 – 81 80 80 89 86 85 – 31 34 41 54 53 48 – – 67 58 66 64 65 – 51 59 74 79 77 79 – 87 82 63 62 47 58 – 84 87 97 82 84 83 – – 100

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Costa Rica YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 NEW AND RELAPSE b

•7 Cuba

10 •

•5 Curaçao

7•

Dominica

230 586 585 534 492 514 475 546 1 553 1 183 772 827 805 734 5 1 1 6 8

1 0 0

26 7 10 5

2 0 0

10 6 2 0 0 0

122 9 11 16 14 0 0

2 0 0 0 0 0

•8 Dominican Republic

10 •

• 36 Ecuador

41 •

• 81 El Salvador

35 •

• 44 Grenada

33 •

8 2 7 2 597 4 053 5 291 5 003 3 964 4 309 4 262 8 243 7 893 6 908 4 416 4 832 5 106 5 456 2 367 2 422 1 485 1 794 1 700 1 896 2 053 0 4 0 4 2 1 3 813 3 119 2 913 3 803 3 322 3 040 3 442 168 296 422 639 712 710 748 6 212 10 420 14 311 14 222 14 315 16 568 3 647 4 984 6 406 3 333 2 876 3 233 3 014 123 109 127 90 130 105 91 14 437 11 329 18 434 18 524 20 155 19 857 20 470 1 0 1 0 0 0

8 2 5 2 787 2 907 2 949 2 159 2 454 2 483 5 890 5 064 3 048 3 373 3 521 3 856

0 0 1 1 418 1 234 1 032 803 809 817 2 237 1 338 635 404 380 285 2 241 278 402 338 371 313

0 0 0 244 540 602 578 655 544 420 400 330 655 808 856 181 108 255 328 384 415

0 0 0

0 0 1 204 610 420 324 342 374

0 1 1

0 1 2 204 610 729 520 505 552

0 0 0

100 49 44

309 196 163 178

0 0 0

0 0 111

106 403 400 397 348

280 392 263 244 315

386 795 663 641 663

0 0

1 008 1 059 972 1 079 1 237 2 0 4 1 1 2 368 2 052 2 420 2 121 1 961 2 212 85 119 240 325 323 309

0 0 0

91 78 62 62 88

180 36 30 21 10

271 114 92 83 98

0 0 0 0

0 0 1 0 546 518 588 265 309 382 187 231 352 274 282 339

0 0 0 0 205 202 256 348 243 311 22 34 33 75 78 77 0 0 0

0 0 0 0 249 141 101 152 112 144 2 38 8 38 27 23

0 0 0 0

0 0 0 0 249 141 159 181 160 201 2 84 25 162 233 244 0 0 0

•0 Guatemala

1•

• 43 Guyana

23 •

436 415 393

58 29 48 57

438 0 0

• 23 Haiti

94 •

6 0 0 0

46 17 124 206 221

0 0 0 0

•0 Honduras

163 •

5 887 7 340 8 242 8 011 9 254 2 306 3 404 2 069 1 842 2 060 1 945 93 90 53 76 35 46 9 220 11 676 11 997 12 572 12 960 13 038

2 930 5 292 4 335 4 553 4 956 2 214 2 396 721 482 616 509 14 20 31 46 39 33 1 807 1 675 421 2 812 2 497 2 681

1 367 1 484 1 307 1 374 1 914 232 370 362 382 377 362 2 4 6 6 6 9 302 2 081 2 657 3 464 3 529 3 839

0 0 0

236 195 338 377 444 100 236 181 170 180 198 2 13 0 2 1 3

110 33 43 46 155

346 228 381 423 599 100 236 181 195 190 230 2 13 5 19 4 6

0 0

• 74 Jamaica

38 •

0 0 0

25 10 32

0 0

•5 Mexico

3•

0 0 24 0

5 17 3 3

0 0 0 0

• 17 Montserrat

17 •

2 831 0 0 139

421 618 722 871 773

914 1 408 544 671 878

1 335 2 026 1 266 1 542 1 651

585 0 0

•9 Netherlands Antilles •0

0•

0 1 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0

5

2

3

0

0

0

0

0

0

0•

– – 40 –

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

190

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN 1 568 1 471 1 253 1 440 1 552 1 484 1 066 460 860 707 830 778 993 748 900 1 260 1 318 1 371 1 391 32 096 22 580 18 490 17 264 17 754 17 653 128 81 60 37 29 41 4 0 0 2 1 2 11 7 11 9 7 11 5 9 6 8 8 27 3 2 0 854 541 395 575 653 817 114 589 505 425 433 434 870 791 665 499 515 494 7 803 6 018 5 592 5 201 5 164 4 556 111 69 37 35 13 17 253 231 160 274 335 339 28 74 216 287 235 248 127 170 150 269 251 221 5 411 5 682 5 335 5 185 5 564 5 233 23 24 16 4 8 10 167 159 99 159 153 150 108 41 56 77 55 60 28 14 86 108 187 105 127 123 167 159 268 286 282 294 108 134 247 211 179 215 28 530 273 214 304 330 – 65 73 76 71 70 64 – 90 44 63 62 66 64 100 46 53 65 73 73 74 – 80 79 77 77 77 79 – 54 54 62 51 69 71 – 100

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Nicaragua YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSE b

• 71 Panama

47 •

• 34 Paraguay

40 •

• 51 Peru

36 •

• 174 Puerto Rico

99 •

•5 Saint Kitts and Nevis

2•

•0 Saint Lucia

4•

•9 Saint Vincent and the Grenadines

6•

•2 Sint Maarten (Dutch part) Suriname

27 •

2 944 2 842 2 402 1 907 2 448 2 693 2 790 846 1 300 1 169 1 637 1 496 1 571 1 520 2 167 1 745 1 950 2 075 2 352 2 372 2 416 37 905 45 310 38 661 33 747 31 073 31 241 29 760 159 262 174 113 80 50 71 0 5 0 0 2 1 2 13 11 9 14 9 7 11 2 13 16 7 15 17 30 3 2 1 82 89 117 194 125 128 120 166 198 166 219 224 274 0

0 0 0

169 127 129 144

0 0 0 0

5 0 0 0

93 191 134 124 155

0 18 0

516 273 109 177 207

75 0 0

0 0

0 0 0 0

0 4 0 3

0 0 0 0

0 4 0 3

0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 0 0

0 0 0 0 0

0 2 0 0 0

0 2 0 0 0

0 0 0

1 1 0 0 0 7 4 1 7 9 3 0 0 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0

1 2 0 0 0 4 3 0 0 0 0 0 0 0

2 0 0 0 0

3 2 0 0 0 4 3 0 2 0 4 0 0 0

0 0 0

0 0 0 0 0 0 0

0 0 2 0 4 0 0

0 0 0 0

0

• 20 Trinidad and Tobago

24 •

37 49 130 64 83 7 115 95 136 121 167

40 54 42 34 28 68 61 50 58 77 81

12 6 14 20 13 12 17 12 20 19 19

2 2 1 2

0 6 6 5 2 22 5 9 5 7 7

1 2 10 6 5

1 8 16 11 7 22 31 22 44 49 54

0 0 1 0

• 10 Turks and Caicos Islands

20 •

0 0 0 0

26 13 39 42 47

0 0 0

•0 United States of America

25 •

• 10 Uruguay

3•

• 28 US Virgin Islands

24 •

6 9 8 25 701 22 728 16 310 14 080 11 181 10 521 9 945 886 625 645 622 699 817 808 4 4

3 8 5 8 093 5 883 5 111 3 695 3 742 3 563 349 348 355 368 467 432 2

1 1 2 10 795 7 204 6 030 4 990 4 556 4 261 178 165 147 218 249 269 2

1 0 1 3 835 3 211 2 939 2 134 2 189 2 100 78 77 73 72 48 59 0

0 0 0 5 12 0 362 34 21

1 0 0

1 1 0

2 1 0

0 0 0

32 0 0 0

20 39 15 41 53 48

4 0 0 7

20 39 19 41 53 55

0 0 0

•4 Venezuela (Bolivarian Republic of)

0•

• 28 a b

22 •

5 457 5 578 6 466 6 847 6 451 6 282 6 495

3 056 3 525 3 653 3 252 3 224 3 446

1 517 1 616 1 853 1 758 1 649 1 617

709 948 1 094 1 077 1 196 1 143

0 0 0

272 377 247 248 213 289

103 194 195 282

272 377 350 442 408 571

116 0 0

100 100 100 – 100 88 92 100 100 100 – 42 69 86 53 47 90 100 100 0 – – 48 48 76 65 75 – 9 65 66 70 61 67 – – – – 75 89 71 – 43 45 46 43 45 46 – 66 68 71 63 65 62 – 50 – – – – – – 67 69 66 65 66 68

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

191

region of the americas

809 647 712 583

4 381 3 195 2 776 2 047 1 735

1 794 1 404 1 603 1 945

4 381 4 989 4 180 3 650 3 680

326

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Anguilla

•0 Antigua and Barbuda

0•

•0 Argentina

17 •

• 12 Aruba

52 •

•0 Bahamas

92 •

•0 Barbados

70 •

•0 Belize

0•

• 52 Bermuda

0•

•0 Bolivia (Plurinational State of)

0•

• 62 Bonaire, Saint Eustatius and Saba Brazil

86 •

• 17 British Virgin Islands

76 •

•0 Canada

0•

•0 Cayman Islands

62 •

•0 Chile

100 •

• 79 Colombia

71 •

•0 Costa Rica

77 •

•0 Cuba

88 •

• 90

88 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

0

0 0 3 6 1 6 6 5 698 4 749 4 709 4 044 3 973 5 150

0 0 0 4 6 3 6 6 5 707 5 177 4 709 5 062 5 088 5 600

6 4 7 38 56 30 26 19 23 3 3 2 6 0 36 44 59 82 97 64 2 0 13

30 26 19 23

11 2 6 0 29 45 59 142

1 0 7 010 6 458 6 278 5 937 5 613 5 746 0 0 45 650 41 186 42 093 39 267 37 932 40 294 1 0 1 0 436 492 433 462 358 407 0 5 1 2 1 1 561 1 290 1 186 1 152 1 154 1 196 7 530 8 358 6 870 7 319 7 028 6 807 245 349 330 271 267 285 834 675 467 418 462 437

1 1 1 7 010 6 212 6 278 5 897 5 571 5 770 0 0 0 45 650 34 007 42 093 40 818 41 840 42 764 1 1 0 0 492 459 850 854 858 5 1 2 2 1 1 111 1 360 1 147 1 365 1 437 1 462 1 634 7 778 6 899 7 364 6 805 349 306 166 297 282 834 673 466 415 458 443

– – – – – – – 133 100 300 100 100 100 109 100 125 128 109 – – – – – 186 – – 100 100 100 100 – – – 100 100 – 81 102 100 – 146 – – – – – 100 – 100 96 100 99 99 100 – – – 100 83 100 104 110 106 – 100 – – 0 – – 100 106 184 239 211 – 100 – 200 100 100 71 105 97 118 125 122 – 20 113 94 105 100 – 100 93 61 111 99 100 100 100 99 99 101

100 50 67 0 5 26 19 19 20 18

0 0 33 17 7 20 34 26 27 33

0 33 33 33 33 1 5 5 4 4 5

0 0 0 0 0 0 0 0 0

0 0 33 50 3 6 5 7 8 8

0 17 0 0 0 84 43 37 43 40 36

92

8

0

17 12 16 4

40 69 53 65

17 8 16 26

7 0 5 0

20 12 11 4

0 0 0 0

45 100 100 52 78 56

45 0 0 0 0 19

9 0 0 10 9 12

0 0 3 0 2

0 0 28 2 12

0 0 0 7 11 0

0 0 0 53 73 76 84 86 84

0 0 0 9 6 2 1 2 2

0 0 0 4 4 3 4 4 3

0 0 0 1 1 1 1 1 1

0 0 0 9 9 5 5 5 5

100 100 100 24 7 12 4 3 5

17 49 31 31 37 37

0 22 44 41 37 38

1 4 5 5 5 5 100

1 0 1 1 0 0

3 9 9 10 11 10

79 16 9 11 10 9 0

0

100

0

0

0

0

22 8 10 12 8 0 0 50 50 100 79 82 83 61 51 50 70 63 68 69 66 43 85 49 75 85 90 91 90 87 89 83

13 59 65 65 54 40 0 0 0 0

5 9 7 8 9 0 0 0 0 0 7 9 9 9 9 7 5 6 6 7 7 10 5 5 7 7 4 4 6 7 7 8

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 1 1 1 2 1 2 1 3 1 1 2 1 2

1 1 0 0 0 0 100 0 0 0 8 6 6 7 6 6 8 7 9 9 10 12 3 1 2 2 2 1 1 1 2 3

59 22 17 15 29 60 0 50 50 0 5 2 2 12 14 15 6 14 6 4 5 19 1 39 2 2 2 1 1 0 0 0

0 11 20 22 10 9 9 10 11 14 4 4 12 3 0 2 2 3 1 5

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

192

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Curaçao

Dominica

•0 Dominican Republic

100 •

• 64 Ecuador

83 •

• 39 El Salvador

78 •

•0 Grenada

93 •

•0 Guatemala

100 •

• 61 Guyana

86 •

• 44 Ha ti

72 •

• 70 Honduras

84 •

• 64 Jamaica

88 •

• 67 Mexico

47 •

• 75 Montserrat

86 •

•0 Netherlands Antilles •0 Nicaragua

0•

• 80 Panama

86 •

• 69 Paraguay

84 •

• 51 Peru

78 •

• 83 Puerto Rico

74 •

• 68 a

73 •

2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

5 5 0 5 1

4 8 2 2 787 2 907 2 949 2 441 2 159 2 454 5 890 5 064 3 048 3 317 3 373 3 521 1 008 1 059 930 972 1 079 2 0 4 4 1 2 368 2 052 2 420 1 609 2 121 1 961 85 119 240 328 325 323 5 887 7 340 8 242 8 011 2 306 3 404 2 069 1 881 1 842 2 060 93 90 53 77 76 35 9 220 11 676 11 997 11 862 12 572 12 960 0 1 0 0 2 1 568 1 471 1 253 1 329 1 440 1 552 1 066 460 860 755 707 830 748 900 1 260 1 498 1 318 1 371 32 096 22 580 18 490 17 391 17 264 17 754 128 81 60 30 37 29

4 3 2 2 007 2 760 2 697 2 441 2 194 2 454 5 236 2 150 3 330 3 373 3 441 1 008 1 059 930 972 1 079

6 4 4 1 2 368 1 908 2 121 2 121 2 056 296 119 257 328 325 323 3 081 5 887 7 340 8 435 8 242 8 390 2 226 2 362 1 905 1 881 1 918 2 004 93 99 53 76 76 59 9 220 11 538 12 172 11 821 12 304 12 622

0 0

5 1 536 1 437 1 496 1 552 1 704 1 565 1 388 460 873 768 717 861 748 900 1 452 1 467 1 317 1 367 28 185 22 230 14 793 14 212 17 264 16 694 128 81 60 37 37 40

– – – – – – 100 38 100 72 95 91 100 102 100 89 – 71 100 100 98 – 100 100 100 100 100 – – – 100 100 100 100 93 – 132 100 105 348 100 107 100 100 100 – 100 100 – 100 105 97 69 92 100 104 97 100 110 100 99 100 169 100 99 101 100 98 97 – – – – – – – 250 – 98 98 119 117 118 101 130 100 102 102 101 104 100 100 115 98 100 100 88 98 80 82 100 94 100 100 100 123 100 138

100 67 100 43 37 80 79 73 76

0 33 0 21 34 5 6 7 7 39 3 4 4 4 1 0 1 1 0

0 0 0 5 5 4 4 5 4 2 3 4 3 3 7 4 5 4 4

0 0 0 2 2 2 2 1 2 8 3 3 3 3 1 1 4 2 1

0 0 0 13 19 7 7 7 8 14 6 8 7 7 5 2 2 2 2

0 0 0 16 4 3 2 6 3 37 5 11 8 10 8 1 0 0 0

81 71 75 73 78 91 88 91 93

67 50 75 100 56 75 77 77 81 10 43 2 13 30 22 57 72 67 72 74 39 81 81 79 79 82 2 5 4 55 13 25 69 64 71 82 82 72

0 5 11 6 6 5 34 13 57 57 41 50 70 14 8 12 10 10 25 5 7 6 6 6 65 40 53 14 34 22 6 12 6 4 4 15

33 50 25 3 5 6 6 5 11 12 7 8 6 7 4 5 6 5 5 4 7 6 5 6 6 5 10 23 13 14 9 7 4 6 5 6 6 5

0 1 1 1 1 1 1 5 1 1 1 1 1 1 1 1 1 0 1 0 1 1 0 1 0 0 0 0 0 3 1 1 1 1 1

0 4 7 9 9 8 38 24 26 19 18 16 21 13 7 8 7 6 4 5 4 6 6 5 17 11 26 11 5 5 12 9 6 5 5 4

0 0 0 0 31 1 1 1 0 6 3 9 2 4 4 3 10 6 7 5 5 25 3 3 2 2 2 5 20 4 5 38 41 6 8 11 2 1 2

20 66 70 73 69 66 68 10 27 68 65 64 68 8 21 46 75 69 70 75 90 91 70 57 68 14 13 12 16 18 18 60 33 12 16 16 16 43 45 33 5 9 8 9 0 11 12 6 68 64 0 0 0 72 4 5 5 4 5 3 14 7 8 7 7 5 3 5 5 7 8 7 3 2 2 3 2 3 23 31 22 16 14 25 2 1 2 1 2 2 1 2 0 1 1 1 0 0 0 0 1 2 2 2 1 5 7 10 9 6 7 6 7 13 22 10 12 12 10 17 22 8 5 5 5 6 3 4 6 5 5 8 5 3 0 5 0

80 4 2 3 3 3 3 3 10 1 0 0 0 29 7 7 7 8 9 6 4 1 9 20 11 2 0 0 3 0 0

75 81 78 0

0 0 3 2

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

193

region of the americas

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Saint Kitts and Nevis

• 60 Saint Lucia

100 •

•0 Saint Vincent and the Grenadines

57 •

•0 Sint Maarten (Dutch part) Suriname

56 •

• 14 Trinidad and Tobago

76 •

• 69 Turks and Caicos Islands

72 •

•0 United States of America

22 •

• 76 Uruguay

78 •

• 68 US Virgin Islands

85 •

• 50 Venezuela (Bolivarian Republic of)

0•

• 74

80 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

4 0 0 4 2 1 11 7 11 7 9 7 5 9 6 3 8 8 3 2 37 49 149 130 64 7 115 95 154 136 121

5

5 2 1 8 13 7 9 7 13 1 8 9 3 2 51 37 143 73 75 78 194 106 154 136 123 2 3

3 8 8 093 5 883 5 111 4 014 3 695 3 742 349 348 355 409 368 467 2

4 9 8 116 5 901 5 136 7 460 7 034 5 955 370 344 345 406 368 467 2

3 056 3 525 3 653 3 436 3 252 3 224

3 056 3 390 3 581 3 433 3 157 3 224

125 – – 125 100 100 – 114 118 100 100 100 – 144 – 33 100 112 – 100 100 – 100 – 96 56 117 1 114 169 112 100 100 102 – – – – 133 112 100 100 100 186 190 159 106 99 97 99 100 100 100 – – – – – 100 96 98 100 97 100

20

40

20

0

20

0

80 100 100 88 15 22 43 100 0 0 44

0 0 0 12 54 57 67 14 0 0 0 11 100 0 4 19 3 0 5 21 46 4 8 4 3 0 33

0 0 0 0 31 29 0 14 0 0 0 11 0 0 12 16 11 12 13 19 11 12 14 9 11 0 0

0 0 0 0 0 0 0 29 0 0 0 0 0 0 0 1 0 0 1 2 1 3 1 0 0

0 0 0 0 0 14 0 0 0 0 0 33 0 0 8 14 16 4 4 10 6 16 14 11 15 100 0

20 0 0 0 0 0 11 0 0 100 100 0 0 0 67 3 5 23 7 0 13 0 1 1 1 0 33 25 11 6 3 6 32 29 15 17 0 1 2 0 0 50

100 10 49 64 60 71 49 22 68 61 72 69 0 33 75

41 85 80 73 80 81 50

22 76 83 84 60 64 78 27 0 4 7 5 4

15 11 8 6 6 6 10 13 11 12 10 8 0

67 4 3 2 1 1 1 4 1 4 6 5 7 0

1 1 0 0 0 0 0

68 76 83 84 83 80

6 0 0 0 0

4 4 5 4 5 5

1 0 0 0 0 0

8 13 10 11 11 12

13 6 2 1 0 3

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

194

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%) 1995–2011 a

YEAR

NUMBER NOTIFIED

SIZE OF COHORT

COHORT AS % NOTIFIED

CURED

COMPLETED

DIED

FAILED

DEFAULTED

NOT EVALUATED

Anguilla

•0 Antigua and Barbuda

0•

•0 Argentina

50 •

•0 Aruba

41 •

•0 Bahamas

0•

•0 Barbados

100 •

•0 Belize

0•

• 23 Bermuda

0•

•0 Bo ivia (Plurinational State of)

0•

• 66 Bonaire, Saint Eustatius and Saba Brazil

73 •

•0 British Virgin Islands

49 •

•0 Canada

0•

•0 Cayman Islands

56 •

•0 Chile

0•

•0 Colombia

43 •

•0 Costa Rica

45 •

•0 Cuba

81 •

• 82

68 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

0

0 0 0 0 2 0 2 1 828 809 827 716 1 072

0 0 0

1 0 2

1 615 893 1 114 1 492

4 5 2 2

25 20 0 0

50 60 100 100

0 20 0 0

0 0 0 0

25 0 0 0

0 0 0 0

0 0 0 0 4 6 15 12 1 12 0 0 0 0 462 804 772 598 589 560 0 0 1 7 859 9 479 10 664 10 721 12 083 0 0 0 13 14 1

23 57

0 29

23 14

8 0

38 0

8 0

0 0 63 2 081 772 732 665 637

57 49 63 73 72 71

9 11 3 5 5 2

7 12 5 7 5 6

5 2 3 2 3 3

15 8 7 7 10 10

7 16 19 7 5 7

1 11 334 9 637 9 818 10 949 10 045

30 26 15 18 19

10 22 28 28 30

4 7 8 8 9

0 2 2 2 2

14 19 23 25 23

41 25 24 19 17

0 0 0 195 145 103 94 72 81 0 0 0 0 0 225 158 314 306 263 272 339 443 616 869 1 001 0 35 45 31 32 26 54 172 49 51 56 73 0 0 0 145 106 95 94 101

16 8 4 15 8

16 59 60 56 49

6 7 7 9 9

1 0 0 0 0

2 3 1 0 0

60 23 27 20 35

0 0 0 0 150 140 219 336 281

32 69 15 14 24

26 3 9 12 19

8 14 7 6 7

1 1 2 2 1

18 9 7 9 15

15 3 60 58 33

0 920 1 001 69 49 2 35 26 55 58 48 61 55 72

11 32 23 55 0 37 54 82 78 67 69 67 53

5 13 9 12 0 43 27 0 7 5 15 15

3 7 10 4 50 11 12 7 10 6 15 4 19

1 4 3 2 0 0 4 5 3 4 5 4 3

7 23 25 24 0 9 4 5 2 2 7 11 10

73 22 30 2 50 0 0 0 0 21 0 0 0

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

195

region of the americas

1 0 4 5 2 2

– – – – – – – – – 50 – 100 – – 200 108 156 139 – – – – – – – – 100 100 100 100 – – – – – – 325 – 93 – 100 – – – – – – – 733 39 100 82 89 88 – – 100 – 69 98 109 98 120 – – – – – – – 100 103 101 131 125 – – – – – – – 95 45 72 128 103 – – 0 – 106 100 – 197 109 6 109 100 102 34 98 120 98 99

100 50

0 0

0 50

0 0

0 0

0 0

7 10 9 9

26 20 23 33

5 4 4 5

0 1 1 0

9 13 15 16

53 52 49 38

       % OF COHORT TREATMENT SUCCESS (%) 1995–2011 a

YEAR

NUMBER NOTIFIED

SIZE OF COHORT

COHORT AS % NOTIFIED

CURED

COMPLETED

DIED

FAILED

DEFAULTED

NOT EVALUATED

Curaçao

Dominica

•0 Dominican Republic

0•

•0 Ecuador

61 •

•0 El Salvador

35 •

•0 Grenada

90 •

•0 Guatemala

0•

• 73 Guyana

64 •

•0 Haiti

49 •

•0 Honduras

72 •

•0 Jamaica

68 •

• 67 Mexico

25 •

•0 Montserrat

61 •

•0 Netherlands Antilles •0 Nicaragua

0•

• 78 Panama

69 •

•0 Paraguay

59 •

•0 Peru

67 •

•0 Puerto Rico

0•

•0 a

0•

2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

0 3

0

1 0 1 204 610 729 452 520 505 386 795 756 663 641 271 114 113 92 83 0 0 0 0 249 141 159 128 181 160 2 84 25 205 162 233 346 228 381 423 100 236 181 225 195 190 2 13 5 20 19 4 1 335 2 026 1 535 1 266 1 542 0 0 0 0 0 167 159 268 282 286 282 108 134 247 235 211 179 28 530 273 177 214 304 4 381 4 989 4 324 4 180 3 650

0 1 1 498 530 434 384 415

554 756 641 181 114 113 92 83

0 0 0 254 164 181 181 182 38 23 205 162 233 55 228 381 381 453 180 169 192 164 165 6 5 19 19 4 138 1 456 1 229 1 272 1 352

0 0

289 230 181 178 204 134 42 237 203 208 203 144 164 188 216 228 4 521 2 299 2 163

0 0 4 0

113 0 4 0

– – – – – – 0 – 100 – 82 73 96 74 82 – – 70 100 – 100 – 67 100 100 100 100 – – – – – – 102 116 – 141 100 114 – 45 92 100 100 100 – 16 100 – 100 107 – 76 93 85 84 87 300 – 100 95 100 100 – 10 72 80 100 88 – – – – – – – – – 173 145 68 63 71 48 – 31 96 86 99 113 – 27 60 106 101 75 – 103 46 50 – – – – – – 100 –

0 0 29 56 47 51 46

100 0 26 5 6 13 15

0 0 3 7 13 9 7

0 100 4 8 5 5 5

0 0 27 19 29 18 20

0 0 11 6 0 4 6

56 46 29 63 68 85 88 90

8 9 6 3 0 3 2 0

5 6 3 9 6 3 2 2

10 8 5 3 4 1 3 0

12 16 10 18 13 8 1 5

9 16 46 3 8 1 3 2

59 63 55 55 51 24 22 0 0 6 42 63 49 60 61 44 59 50 66 64 0

15 16 8 8 14 29 35 51 52 43 15 7 20 14 11 10 9 7 9 5 67 20 58 26 25 4 7 5 7 14

4 4 5 5 11 13 9 14 14 9 5 3 7 5 4 8 6 10 7 9 17

2 4 7 7 4 5 9 0 1 1 7 0 3 2 6 2 2 1 2 2 0

4 10 20 20 20 26 13 18 28 33 22 13 10 10 10 6 17 10 15 16 17 80 21 21 25 12 14 10 11 10

17 2 4 4 1 3 13 17 5 8 9 14 11 8 9 29 7 22 1 4 0 0 0 21 50 36 20 14 10 14

16 5 0 33 48 56 55 47

5 26 0 8 7 9 9 10

0 0 0 7 4 6 6 5

69 65 71 70 60 58 19 23 18 23 24 19 44 47 54 60 78 78 49

10 10 12 6 16 10 24 35 30 34 34 40 26 9 6 7 0 21

4 6 7 3 8 10 2 9 10 11 11 6 4 9 8 4 4 5 4

3 2 2 6 4 2 0 4 0 3 2 1 4 2 4 7 5 2

11 15 7 11 9 14 48 22 37 30 28 25 10 11 9 9 6 11 12

3 2 2 3 2 4 7 7 4 0 0 9 16 20 20 16 4 1 12

73 50 0

23 25

0 25

4 0

1 0

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

196

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Saint Kitts and Nevis

•0 Saint Lucia

0•

•0 Saint Vincent and the Grenadines

0•

•0 Sint Maarten (Dutch part) Suriname

0•

•0 Trinidad and Tobago

64 •

•0 Turks and Caicos Islands

35 •

•0 United States of America

0•

•0 Uruguay

0•

• 76 US Virgin Islands

79 •

•0 Venezuela (Bolivarian Republic of)

0•

•0

80 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

0 2 0 0 0 3 2 3 0 0 4 3 0 2 2 0 0 0 1 8 15 16 11 22 31 22 60 44 49

2 0 0 0 1 3 0 0 3 1 0 0

0

12 11 11 22 21 60 44 49

3 2 1 0 0

20 39 19 37 41 53

25 30 41 41 53

272 377 350 428 442 408

247 261 248 400

– – 100 – – – – 33 – 100 – – – 100 – 50 0 – – – – – – – 80 69 100 – 71 95 100 100 100 – – – – 0 0 – – – – – – 125 – 158 111 100 100 – – – – – – – – 71 61 56 98

50

50

100

0 33

0 67

0 0

0 0

0 0

100 0

0 0

0 0

0 0

0 100

0 0

50 45 45 23 19 48 43 22

0 9 18 45 38 20 20 12

8 27 36 14 29 15 14 12

0 0 0 9 0 0 0

42 0 0 9 14 17 23 51

0 18 0 0 0 0 0 2

33

33

33

0

0

0

56 57 46 56 74

20 17 10 20 6

16 13 34 15 11

0 3 0 0 0

8 7 7 5 9

0 3 2 5 0

80 80 83 80

0 0 0

4 4 6 9

2 2 1 0

12 13 10 10

2 2 0 0

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

197

region of the americas

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 0 0 0 0 6 6 6 4 1 121 1 313 1 434 PATIENTS NOTIFIED (NEW AND RETREAT) 1 0 0 6 7 8 4 11 242 7 762 10 491 9 606 6 8 29 50 32 42 32 6 0 4 106 145 76 84 1 1 3 9 973 8 620 8 747 8 484 0 1 0 87 223 81 946 84 137 82 755 0 1 0 0 1 616 1 385 1 452 1 686 4 2 6 2 633 2 472 2 535 2 460 10 360 11 889 12 438 11 829 560 499 524 480 781 838 821 748 5 1 1 8 3 8 5 312 4 160 4 472 4 440 4 808 5 095 5 350 5 771 1 830 1 730 1 917 2 063 4 2 1 3 861 3 351 3 088 3 499 656 836 916 969 14 344 14 265 14 361 16 723 % OF HIV% OF HIVNUMBER OF POSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Anguilla 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS

% OF TESTED TB PATIENTS HIV-POSITIVE

– Antigua and Barbuda • 100 Argentina

–

100 •

100 86 75 100 14 13 15

0 0 0 3 5 4 2 672 735 685

50 83 67 50 60 56 48

100 40 50 50

100 100 100 100

0 0 5 1

– Aruba

15 •

– Bahamas

3•

3.4 100 100 100 100 100 100 98 84 81 100 100 100 0 22 45 60 0 59 63 64 55 0

1 33 42 32 8 6 0 4 106 142 64 68 1 1 1 3 0 1 897 3 928 5 049 0 0 0 51 552 51 764 53 455 45 733 0 0 0 0 414 658 513 716 1 3 2 6

1 16 12 8 2 2 0 1 25 29 24 19 0 0 0 0 0 130 333 164 0 0 0 8 249 9 338 9 088 9 049 0 0 0 0 63 53 61 57 0 0 0 0

100 48 29 25 25 33 25 24 20 38 28 0 0 0 0 6.9 8.5 3.2 31 42 38 0 0 0 68 100

100 75 67 62 100 100 68 100 100 100

– Barbados

100 •

– Belize

100 •

409

• 100 Bermuda

81 •

– Bolivia (Plurinational State of) •0 Bonaire, Saint Eustatius and Saba Brazil

100 •

50 0 87 36 100

60 •

• 59 British Virgin Islands – Canada

55 •

16 18 17 20

0 0 0

85 92 100 100

674

27

–

• 26 Cayman Islands

42 •

26 48 35 42 75 100 100

– Chile

100 •

15 8.1 12 8 0 0 0 0

– Colombia

16 •

• 53 Costa Rica

66 •

• 67 Cuba

94 •

• 93 Curaçao

83 •

11 16 53 43 53 66 67 99 96 94 93 100 95 83 0 0 100 38 67 75 1.5 60 57 61 0.21 100 68 86 84 96 98 99 100 100 100 16 63 72 85 70 88 93 94 0 67 78 81

286 392 5 537 5 079 6 579 7 791 374 494 505 453 729 862 780 618 0 0 1 3 2 6 78 2 489 2 540 2 721 10 5 183 3 640 4 974 1 544 1 667 1 878 2 036 0 4 2 1 600 2 121 2 223 2 982 456 734 852 914 0 9 518 11 213 13 518

Dominica

– Dominican Republic •1 Ecuador

75 •

61 •

•0 El Salvador

86 •

• 84 Grenada

99 •

– Guatemala

100 •

• 16 Guyana

85 •

• 70 Haiti

94 •

•0

81 •

148 140 353 1 231 1 292 1 400 50 54 36 49 0 56 62 54 0 0 1 0 1 0 0 3 547 460 557 3 427 576 669 188 180 194 214 0 1 0 0 478 255 285 293 80 209 199 284 1 797 1 892 2 320 2 705

52 36 6.4 24 20 18 13 11 7.1 11 0 6.5 7.9 8.7

0 0

35 36 34 84 0 0 0

0 34 81

62 89 94

1 366 1 429 1 339

100 33 0 0 3.8 22 18 20 30 8.2 16 13 12 11 10 11 25 0 0 80 12 13 9.8 18 28 23 31 20 21 20 100 100

0 7.9 58 69 0

0 3.8 93 48 100

953 5 041

20 82 85 66 0

38 63 77 83 0

455

0 0

100 16 0 77 94 71 13 11 59

240 100 30 95 59 83 59 9.8 6.9 46 144 119 154 4 112 15 283

198

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 44 54 75 76 83 87 85 69 6.9 43 56 70 100 1 455 1 557 2 443 2 312 79 128 92 65 1 382 8 915 11 416 15 005 1 0 0 2 0 1 440 1 552 2 117 1 569 1 558 1 608 1 600 817 1 533 1 906 668 9 539 7 052 5 836 93 76 46 61 2 1 2 1 9 7 11 7 10 13 31 3 2 1 87 173 117 121 124 254 252 311 5 5 1 0 8 273 7 404 8 752 8 376 574 646 769 775 PATIENTS NOTIFIED (NEW AND RETREAT) 3 333 2 901 3 243 3 046 95 147 108 94 19 932 20 699 20 528 21 348 1 0 0 0 2 076 2 575 2 822 2 934 1 828 1 630 1 695 1 675 2 348 2 461 2 549 2 623 35 541 32 477 32 844 31 705 113 80 50 71 2 2 1 2 14 9 7 11 7 17 17 34 3 2 1 119 204 131 133 179 258 266 321 7 10 8 14 080 11 181 10 521 9 945 626 699 817 815 % OF HIVNUMBER OF % OF HIVPOSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT 0 90 50 52 43 0 90 72 74 54 100 82 0 27 286

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Honduras 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS 200 201 261 259 28 30 17 13 217 1 645 1 520 1 233 0 0 0 2 30 60 60 105 200 240 241 224 144 174 154 668 853 960 979 28 14 10 11 0 0 0 0 0 1 1 1 3 5 9 0 0 0 20 58 38 36 42 58 84 82 1 1 0 0 1 035 627 668 625 74 104 110 134

% OF TESTED TB PATIENTS HIV-POSITIVE 14 13 11 11 35 23 18 20 16 18 13 8.2 0

• 44 Jamaica

76 •

• 83 Mexico

69 •

•7 Montserrat

70 •

100 70 70

26 25 24

• 100 Netherlands Antilles Nicaragua

–

100 4.2 3.9 5 13 15 15 14 18 11 8.1 100 8.9 14 17 30 18 22 18 0 0 0 0 0 14 9.1 14 30 38 29 0 0 0 23 34 32 30 34 23 33 26 20 20 0 13 8.5 7.6 7.5 13 16 14 17 0 67 67 78 63 94 89 0 25 60 67 67 74 10 84 93 65 67 56 79 1.2 68 87 43 50 82 50 50 36 1 214 1 183 1 416 465 152 230 400

•0 Panama

72 •

• 86 Paraguay

96 •

– Peru

73 •

•2 Puerto Rico

18 •

• 82 Saint Kitts and Nevis – Saint Lucia

86 •

33 60 73 1.9 29 21 18 82 95 92 86 100 100 100 7.1 100 100 100 100 59 76 91 100 100 100 73 85 89 91 69 98 95 97 71 10 0 59 66 83 84 92 92 94 95

100 •

•7 Saint Vincent and the Grenadines • 100 Sint Maarten (Dutch part) Suriname

100 •

100 100 0 80 67

91 •

100 100 0 100 80 67

1

10 18 29 19 24 28 0 100

• 73 Trinidad and Tobago • 69 Turks and Caicos Islands – United States of America • 59 Uruguay

91 •

97 •

10 38 55 69 36 34 19 29 0 100

0 11

0•

84 •

• 92 US Virgin Islands

95 •

0 0 0 0

34 31 24

– Venezuela (Bolivarian Republic of) • 39

–

73 •

39 78 64 73

2 678 5 213 4 133 4 956

6 950 6 645 6 477 6 777

392 479 519 581

15 9.2 13 12

0

39 33 32 89

102

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

199

region of the americas

0 56 55 72 86 96 95 96

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 0 0 0 0 0 0 2369 b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB – – – – – 0 0 0 46 – – – – – 71 – – 95 97 84 – 0 – 0 0 – – 0 – 100 100 200 – 0 1.7 22 – – – – <0.1 <0.1 1.6 – 0 – – 150 130 – 140 – 50 100 100 3.2 4.4 4.8 8.4 – 17 36 33 0.49 64 9.6 95 32 36 60 61 100 100 100 – 12 50 40 – 1.4 0.42 3.1 3.2 10 6.3 13 1.1 0 22 20 – – – – 0.83 – 0 1.4 – 0 0.62 0.97 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

2005 2010 2011 2012 Antigua and 2005 Barbuda 2010 2011 2012 Argentina 2005 2010 2011 2012 Aruba 2005 2010 2011 2012 Bahamas 2005 2010 2011 2012 Barbados 2005 2010 2011 2012 Belize 2005 2010 2011 2012 Bermuda 2005 2010 2011 2012 Bolivia 2005 (Plurinational 2010 State of) 2011 2012 Bonaire, Saint 2010 Eustatius and Saba 2011 2012 Brazil 2005 2010 2011 2012 British Virgin 2005 Islands 2010 2011 2012 Canada 2005 2010 2011 2012 Cayman Islands 2005 2010 2011 2012 Chile 2005 2010 2011 2012 Colombia 2005 2010 2011 2012 Costa Rica 2005 2010 2011 2012 Cuba 2005 2010 2011 2012 Curaçao 2010 2011 2012 Dominica 2005 2010 2011 2012 Dominican 2005 Republic 2010 2011 2012 Ecuador 2005 2010 2011 2012 El Salvador 2005 2010 2011 2012 Grenada 2005 2010 2011 2012 Guatemala 2005 2010 2011 2012 Guyana 2005 2010 2011 2012

Anguilla

0 0 0 0 0 0 276 109 103 63

0 (0–0)

0 (0–0)

0 (0–0)

0.18 (<0.1–0.27)

<0.1 (<0.1–<0.1)

0.14 (<0.1–0.23)

340 (230–440)

160 (88–260)

180 (110–260)

0 0.85 (0.57–1.1) 0 1 1 0 0 0 0 0 0 0 0 0 0 63 106 83 117 0 1 0 373 573 566 684 0 0 0 22 15 19 9 0 0 0 6 10 9 18 131 108 105 3 3 0 1 1 7 10 8 0 0 0 0 0 0 108 117 92 253 176 354 223 14 2 4 8 0 0 0 40 18 27 69 5 3 0 0.57 (0.36–0.81)

5

0.27 (<0.1–0.46)

1.2 (<0.1–6.1)

1.2 (<0.1–6.1)

21 31 27 0 0 0 0

0 (0–0)

<0.1 (<0.1–0.10)

<0.1 (<0.1–0.10)

0 (0–0)

2.5 (1.7–3.4)

1.6 (1.0–2.2)

0 1 1 2 0 98 1376 0 0 22 21 700 0 0 0 1130 987 1244 1 1 5 49 65 71 125 1240 2620 2378 2 203 32 273 169 174 313 269 5 1 1 1 1 2 32 12 79 117 363 239 529 12 0 238 252

0.96 (0.32–1.6)

0 (0–1.7)

0 (0–1.7)

0 (0–0)

150 (88–210)

74 (27–160)

75 (60–94)

0 (0–0)

0 (0–0)

0 (0–0)

1 700 (1 400–2 000)

850 (620–1 100)

860 (660–1 100)

0 (0–0)

0 (0–0)

0 (0–0)

7.4 (2.2–13)

6.0 (2.4–12)

1.4 (<0.1–7.8)

0 (0–3.1)

0 (0–3.1)

0 (0–0)

19 (7.5–30)

12 (4.4–26)

6.7 (2.2–15)

310 (220–400)

210 (140–320)

98 (74–130)

6.4 (0.81–12)

5.4 (1.5–14)

1.0 (<0.1–5.0)

11 (3.4–19)

4.3 (0.52–15)

7.1 (2.7–14)

0 (0–0.98)

0 (0–0.98)

0 (0–0)

0 (0–0)

0 (0–5.9)

0 (0–2.0)

330 (230–430)

220 (140–330)

110 (71–150)

380 (320–450)

210 (150–280)

170 (150–190)

16 (5.9–26)

5.1 (0.61–18)

11 (4.8–20)

<0.1 (<0.1–<0.1)

<0.1 (<0.1–<0.1) 20 0 37 0 2 3

0 (0–0)

140 (100–180)

89 (55–140)

53 (40–69)

48 (25–70)

14 (9.1–20)

33 (11–56)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB – 0 – 0 – 0 – – 0 – 0 0 0 0 1290 160 – – – – – – – – 2 100 1 50 0 – – 0 – 0 – 0 – 3 20 – – 0 0 – 0 – 0 – 0 – – 664 100 597 94 634 94 0 – 1 100 0 – 5917 61 643 5.9 604 6.0 198 1.7 – 0 – 0 – 0 – – 51 71 – 63 69 – 0 – 0 – 0 – 226 72 276 100 277 100 172 74 – 495 57 568 57 391 51 1 2.2 – 16 62 22 100 19 39 31 55 76 100 51 85 – 0 – 0 – – 1 – 1 100 1 50 – 106 20 77 15 193 35 502 63 584 88 284 44 827 120 14 12 2 2.2 69 83 73 74 – – – – 40 25 18 9.9 27 17 74 37 – 0 0 55 24 1 0.41

a b

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). BACT+VE = bacteriologically positive cases.

200

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 53 2 b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB 0.72 <0.1 – – 0.13 3.1 1.5 2.1 19 31 64 28 2.1 0.16 <0.1 <0.1 0 – – – – 0.64 3.5 13 – 3.3 8.2 2.3 0.26 – 8.2 15 15 – – 6.5 79 – 100 110 98 – 0 0 0 – 0 29 0 86 22 12 7.4 – 0 – 44 0.70 0 – 0 – – 2.4 – – – – 110 110 99 100 – 36 75 88 – – – – 4.3 0.78 17 13 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

2005 2010 2011 2012 Honduras 2005 2010 2011 2012 Jamaica 2005 2010 2011 2012 Mexico 2005 2010 2011 2012 Montserrat 2005 2010 2011 2012 Netherlands Antilles 2005 Nicaragua 2005 2010 2011 2012 Panama 2005 2010 2011 2012 Paraguay 2005 2010 2011 2012 Peru 2005 2010 2011 2012 Puerto Rico 2005 2010 2011 2012 Saint Kitts and 2005 Nevis 2010 2011 2012 Saint Lucia 2005 2010 2011 2012 Saint Vincent and 2005 the Grenadines 2010 2011 2012 Sint Maarten 2010 (Dutch part) 2011 2012 Suriname 2005 2010 2011 2012 Trinidad and 2005 Tobago 2010 2011 2012 Turks and Caicos 2005 Islands 2010 2011 2012 United States 2005 of America 2010 2011 2012 Uruguay 2005 2010 2011 2012 US Virgin Islands 2005 2010 2011 2012 Venezuela 2005 (Bolivarian 2010 Republic of) 2011 2012

Haiti

41 86 81 3 9 5 6 0 1 1 0 394 140 140 114 1 0 0 0 50 18 13 21 5 10 7 11 13 1 6 7 2748 1048 1663 1225 0 0 3 1 0 0 0 0 0 0 6 0 0 0 0 0 0 1 0 0 0 3 0 0 1

390 (270–520)

310 (200–440) 3 57 30 41 11 40 28 16 314 21 6 13 0 0 0

82 (28–140)

71 (37–110)

43 (19–84)

28 (13–51)

2.6 (1.7–3.4)

1.7 (1.1–2.4)

0.82 (0.28–1.4)

480 (350–620)

380 (330–440)

100 (84–130)

0 (0–0)

0 (0–0) 8 50 200

0 (0–0)

46 (21–70)

14 (1.7–52) 29 58 25 2 115 227 235

31 (18–49)

56 (35–78)

27 (17–38)

29 (9.9–49)

55 (19–90)

6.5 (0.16–36)

48 (20–92)

2 200 (2 100–2 300)

890 (820–960)

1199 14484 69 44 52 0 0 0 0 2 0 6 2 1 2 0

1 300 (1 200–1 400)

1.0 (0–2.6)

0 (0–3.8)

1.0 (<0.1–2.7)

<0.1 (<0.1–<0.1)

<0.1 (<0.1–<0.1)

0 (0–0)

0.24 (0.15–0.34)

0.24 (0.15–0.34)

0 (0–0)

1.2 (0.78–1.6)

0.66 (0.42–0.93)

0.55 (0.18–0.92)

<0.1 (<0.1–<0.1)

<0.1 (<0.1–<0.1) 49 1 0

0 (0–0)

3.4 (2.4–4.5)

2.5 (1.6–3.5) 0

0.96 (0.32–1.6)

11 (8.4–13)

4.5 (2.2–6.4)

6

6.4 (5.0–7.9)

0.13 (<0.1–0.18) 124 107 119 81 1 1 1

0.13 (<0.1–0.18) 10064 7593 6899 6790 160 422 466

0 (0–0)

81 (63–100)

81 (63–100)

–

1.3 (0–3.8)

0 (0–5.5)

1.3 (<0.1–6.9)

– 28 21 25 21

– 163 26 565 460

–

100 (58–150)

26 (7.2–67)

77 (43–120)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB – 39 10 – 81 14 0 0 62 32 65 34 96 42 2 40 5 26 1 25 0 0 74 3.7 505 40 180 12 148 9.0 0 – 0 – 0 – – – 8 3.0 150 52 67 24 – 48 19 17 8.1 40 22 7 3.3 – 52 24 93 31 89 27 2336 47 – 598 16 1902 52 – 4 100 0 – 3 100 – 0 – 0 – 0 – – 0 – 0 – 0 – 0 – – 0 – 0 0 – – – 0 0 – 0 0 – 3 14 – – 10 19 – – – – 505 – 345 – 304 – 339 – – 22 54 38 72 42 76 – – – – 15 4.3 160 36 195 48 148 26

a b

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). BACT+VE = bacteriologically positive cases.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

201

region of the americas

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO – – – – – – – 0.33 0.50 5.0 7.0 – – 1.2 1.3 1.4 1.4 0.71 – – – – 2.5 0.56 2.4 1.0 – 1.7 2.3 1.3 – 2.0 – 1.0 – – 0.83 2.1 1.8 2.5 3.3 1.5 – – – – – – – 1.5 1.5 1.6 1.6 1.5 – – – – 1.7 2.0 2.2 2.2 2.3 – – – – – – 1.5 1.3 1.5 1.5 1.5 1.7 – – – 1.0 – – 1.7 2.0 2.1 2.2 2.0 2.1 – 1.6 1.4 1.5 1.7 1.5 1.9 1.7 2.1 2.0 1.4 2.4 2.1 3.7 2.8 3.4 3.2 3.7 1.5 – – – – – 1.0 – –

Anguilla

Antigua and Barbuda

Argentina

Aruba

Bahamas

Barbados

Belize

Bermuda

Bolivia (Plurinational State of)

Bonaire, Saint Eustatius and Saba Brazil

British Virgin Islands

Canada

Cayman Islands

Chile

Colombia

Costa Rica

Cuba

Curaçao

Dominica

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 2010 2011 2012 1995 2000 2005 2010 2011 2012

0 0 0 0 0 0 0 97 64 56 143 59

0 0 0 0 0 0 0 278 621 536 664 533

0 0 0 0 2 1 0 594 530 491 657 484

0 0 0 0 1 0 1 0 402 358 309 434 299

0 0 0 0 1 2 3 1 419 384 302 397 180

0 0 0 0 1 1 0 368 340 340 358 182

1 0 0 1 0 1 0 330 348 282 289 181

0 0

0 0 0 1

0 0 0 1 2 0 1 0 544 530 421 587 652

0 0 0 1 2 1 0 0 479 474 426 470 614

0 0 0 0 0 0 0 262 290 233 279 375

0 0 0 0 0 0 0 230 198 184 192 364

0 0 0 0 0 0 0 179 169 153 169 321

0 0 0 0 0 0 0 216 240 176 213 322

0 0

0 0 0

0 0 0 121 90 59 142 67

0 0 0

2 9 15

1 4 13

3 1 0 0 0 0 0 0 0 1 2 0 2 0 1

3 2 2 2 1 0 0 0 0 1 5 8 9 8 2

5 7 3 3 1 0 0 0 0 2 7 8 16 14 7

2 7 9 5 6 6 2 1 0 0 4 2 6 22 9 5

4 3 4 4 0 2 2 0 2 0 0 0 6 8 24 16 4

1 2 3 2 2 0 0 0 0 0 1 3 5 11 2 3 2 2 0 1 2 0 0 0 0 1 5 3 18 0 2 0 0 0 0 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 4 0 0 4 1 5 5 1 2 0 1 0 0 6 2 4 5 2 4

1 7 7 1 3 5 1 0 0 0 2 1 4 7 0 3 2 2 8 1 3 1 0 0 0 0 0 2 4 7 8 4 1 0 2 0 0 1 0 2 0 0 1 4 3 9 4 4 0 3 0 0 0 0 0 0 0 1 1 2 4 1 1

1 1 1 1 0 0 0 0 0 0 0 2 4 4 5 0 0 0 0 0 0 0 0

0

0

0 0 0 166 157 95 100 99 0 0 0 1 894 317 298 336 277

0 0 0 1 182 1 320 1 150 1 231 1 096 0 0 0 7 268 5 074 4 405 4 877 5 027

0 0 0 797 725 622 685 672 0 0 0 11 568 6 119 6 381 6 755 6 811

1 0 0 518 439 415 372 368 0 0 0 11 906 6 128 5 293 5 462 5 387

0 0 0 466 391 395 371 358 0 0 0 8 623 5 259 4 762 5 054 5 128

0 0 0 340 346 338 302 353 0 0 0 5 085 2 803 2 875 3 083 3 103 1

0 0 0 366 415 409 457 380 0 0 0 4 494 2 140 1 947 2 142 2 160

0 0 0

0 0 0 191 160 119 146 101 0 0 0 1 859 355 280 356 303

0 0 0 831 846 744 778 792 0 0 0 6 719 3 496 2 677 2 815 2 798

0 0 1 588 533 471 459 480 0 0 0 7 215 3 663 3 008 3 131 3 013

0 0 0 334 276 238 235 223 0 0 0 5 395 2 626 2 211 2 230 2 173

0 0 0 254 226 191 183 204 0 0 0 3 582 1 897 1 720 1 779 1 785

0 0 0 192 182 162 155 193 0 0 0 2 384 1 112 1 038 1 164 1 113

0 0 0 233 262 264 272 249 0 0 0 2 496 1 104 979 1 069 1 030

0 0 0

0 0

0 0

43 41 38

15 0 6

0 0 0 1 5 3 3 2 1 0 0 0 0 24 6 3 2 4 4 246 178 148 105 92 1 14 1 2 0 2 2 0 2 3 2 1 0 0 0

0 0 0 28 34 37 30 34 33 0 0 0 0 148 81 74 90 88 91 763 623 602 663 613 17 31 43 18 23 18 59 71 20 17 14 15 0 0 0

0 0 0 31 45 45 28 36 32 3 0 0 2 182 160 128 115 139 122 1 030 685 765 714 744 38 53 38 48 24 33 118 167 73 61 51 45 0 0 0

0 0 0 60 46 44 36 31 53 1 1 0 2 204 198 179 144 143 135 963 666 540 558 497 24 62 53 33 29 28 83 90 90 89 83 83 2 0 0

0 0 0 34 41 40 32 40 51 0 0 0 1 155 150 162 159 164 170 743 687 710 702 653 19 39 34 27 33 34 75 74 50 78 86 70 1 0 0

1 0 0 41 32 20 25 33 35 1 0 1 0 141 132 115 122 127 117 610 510 610 594 616 23 28 20 22 22 41 75 55 58 53 50 45 0 0 0

0 0 0 70 79 68 62 70 97 0 0 0 0 163 126 133 157 134 149 746 695 814 753 740 22 49 34 28 36 23 156 75 51 57 48 36 0 0 0

0 0 0

0 0 0

0 0 0 7 4 6 1 3 6

0 0 0 33 33 28 28 23 32

0 0 0 28 40 40 24 29 34

0 0 0 22 30 27 16 28 29

0 0 0 12 25 24 10 14 19

0 0 0 18 12 13 19 9 11

0 0 0 51 66 37 44 55 45

0 0 0

0 0 0

0 0 0

0 0 5

0 0 0 24 10 4 6 6 4 194 179 146 98 79 2 13 1 0 2 2 1 2 2 1 1 0 0 0 0

0 0 0 100 66 55 56 62 59 587 581 560 461 519 17 21 21 18 18 11 17 9 14 15 6 13 1 0 1

0 0 0 120 96 78 76 75 69 758 533 576 535 555 15 33 31 20 27 24 52 22 17 15 18 12 1 0 0

0 0 0 108 70 60 59 66 53 523 457 428 324 376 11 24 18 12 23 11 29 26 26 14 18 16 0 0 0

1 0 0 75 54 56 56 69 56 381 389 374 337 355 7 20 16 14 19 12 39 22 13 16 17 12 0 0 0

0 0 0 73 58 36 40 48 60 304 292 284 278 252 9 23 6 15 12 8 48 23 22 17 17 13 0 0 0

0 0 0 107 83 93 72 71 76 510 395 471 390 432 14 24 14 8 17 5 80 39 29 26 26 13 0 0 0

0 0 0

0 0 3

0 0 0

0 0 0

1 0 2

1 0 3

0 0 0 0 0

0 0 0 0 0

0 0 0

0 0 2

0 0

0 2 0

0 0 1

3 0 2

1 0 0

0 0 0

0 0 0

0 0 0

0 0 0

1 0 0

2 0 0

1 0 0

0 0 0

0 0 0

202

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO – 1.4 1.5 1.5 1.6 1.7 – – 1.5 1.8 1.8 1.8 – 1.5 1.7 1.7 1.8 1.6 – – – 3.0 – – 1.1 1.2 0.92 1.3 1.1 – 1.5 2.0 2.2 2.1 2.7 3.3 – 1.1 1.0 1.1 1.0 1.0 1.6 1.3 1.3 1.4 1.4 1.6 2.1 1.8 2.8 3.5 1.7 2.5 – 1.6 1.6 1.6 1.7 1.7 – – – – – – – 1.5 – 1.2 1.2 1.3 1.3 1.5 – 1.6 1.7 1.6 1.8 1.6 1.7 1.5 1.8 1.9 2.2 2.2 2.3 1.3 1.3 1.4 – – – 2.4 2.4 1.7 1.5 3.1 3.1 – – – 1.0 – 1.0 – 1.3 0.83 2.0 – 4.5

Dominican Republic

Ecuador

El Salvador

Grenada

Guatemala

Guyana

Haiti

Honduras

Jamaica

Mexico

Montserrat

Netherlands Antilles Nicaragua

Panama

Paraguay

Peru

Puerto Rico

Saint Kitts and Nevis

Saint Lucia

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

73 43 29 20 15

410 399 276 333 317

481 483 346 406 489

344 386 292 318 315

173 228 170 200 197

125 123 112 133 126

113 105 85 112 111

0 0 0

65 57 43 30 26

317 339 239 242 230

325 332 207 274 260

212 209 142 159 148

115 119 102 103 119

79 72 54 66 62

75 54 62 58 68

0 0 0

48 32 45 37 13 5 5 3 5

446 499 481 506 99 97 101 114 131

468 529 547 567 124 140 170 183 194

308 314 364 387 114 128 96 106 122

237 309 323 359 92 104 77 96 100

150 227 272 291 62 74 62 77 87

159 246 232 333 107 117 101 115 115

48 52 49 59 28 6 6 6 5

329 298 340 333 81 85 63 61 81

305 308 311 337 76 82 65 61 73

199 178 177 184 63 59 49 44 80

139 158 141 164 63 50 58 52 90

85 113 118 146 39 42 51 69 64

127 110 121 153 47 70 68 92 90

0 0 0

0 0 0

0 51 36 39 60 18 7 4 12 2 8 5 67 69 98 102 126 42 30 13 15 17 18 2 0 0 1 0 1 214 100 125 128 133

0 235 220 251 187 197 8 20 48 32 26 30 836 1 045 1 225 1 155 1 359 280 123 238 177 194 247 9 6 4 7 2 10 1 079 1 095 1 081 1 124 1 153

0 280 236 258 245 205 5 19 130 38 54 39 898 1 035 1 357 1 342 1 563 540 371 280 246 291 285 14 13 6 15 6 8 1 387 1 376 1 375 1 440 1 480

1 0 236 216 185 207 172 6 14 116 65 61 68 613 701 718 670 758 204 246 215 207 227 192 9 13 6 15 3 3 1 162 1 314 1 380 1 503 1 522

1 1 165 177 187 172 162 9 7 81 49 54 64 350 451 469 442 473 130 277 152 165 184 184 11 15 10 8 4 5 1 235 1 238 1 392 1 532 1 484

1 0 142 112 127 143 136 6 6 41 22 19 23 147 222 259 206 271 236 214 134 113 120 129 8 6 6 6 4 5 972 1 042 1 119 1 112 1 153

7 9 20 13 13 8 118 156 160 132 164 58 43 152 157 184 146 9 5 7 7 3 1 1 126 1 288 1 303 1 299 1 284

0 0 0

3 1 14 2 2 4 96 116 158 148 160 54 25 27 28 19 15 2 1 0 0 1 1 176 125 112 136 134

5 11 41 22 17 17 914 1 097 1 268 1 282 1 476 208 21 219 186 181 180 7 8 1 5 3 1 663 771 791 776 778

7 8 62 25 19 10 857 1 099 1 223 1 250 1 415 292 269 222 163 194 157 6 8 5 4 4 5 828 733 763 765 743

6 7 41 19 17 17 513 633 608 595 698 134 258 125 106 138 115 5 7 4 5 0 4 698 710 730 698 686

5 5 30 20 17 12 275 414 358 363 416 76 270 107 103 99 88 5 2 0 1 3 2 832 784 852 889 840

2 5 11 10 7 7 132 170 207 196 219 136 160 81 69 98 75 2 5 1 0 1 0 595 637 713 734 824

4 3 9 6 9 5 71 132 134 128 156 48 38 104 107 126 114 2 1 3 2 1 0 709 784 836 824 824

0 0 0

0 0

0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0 0 23 18 17 22 10 0 86 3 5 6 10 19 18 16 23 18 9 4 147 552 371

0 0 0 0 178 194 163 157 273 0 155 44 76 69 96 88 64 112 168 163 182 180 1 311 5 290 3 802

0 0 0 1 172 174 159 189 235 0 193 78 129 127 104 103 71 103 185 244 238 230 849 2 875 2 670

0 0 0 2 175 147 116 141 156 0 112 61 129 80 91 104 96 105 136 129 135 158 454 1 546 1 513

1 0 0 0 0 126 108 106 115 108 0 126 37 84 62 99 67 74 86 117 143 151 143 322 1 041 1 075

0 0 0 0 96 64 61 82 61 0 42 27 57 61 63 51 57 80 87 103 124 116 200 801 641

0 0 0 0 92 90 79 108 94 0 83 26 49 49 47 61 61 71 99 99 103 129 216 796 708

0 0 0

0 0 0 0 24 34 23 27 4 0 72 6 11 7 11 9 13 12 31 18 14 16 149 633 375

0 0 0 0 176 188 135 154 61 0 120 43 73 51 55 62 65 69 89 106 110 95 1 005 3 686 2 674

0 0 0 1 215 173 122 149 145 0 111 34 81 52 64 57 49 86 98 99 103 98 660 2 472 2 111

0 0 0 0 98 98 103 92 161 0 75 35 62 46 58 45 46 41 69 39 55 60 373 1 156 1 046

0 0 0 0 83 76 61 75 108 0 57 19 33 45 44 46 35 41 52 50 39 55 259 609 699

0 0 0 1 64 46 54 50 64 0 16 12 30 23 40 22 34 30 29 46 36 38 162 499 333

0 0 0 0 46 61 47 79 72 0 40 16 41 29 48 44 53 46 71 45 62 60 152 624 472

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

11 6 7

5 4 2

4 0 0 0 0 0

3 1 4 0 1 1

12 4 4 3 4 5

20 19 7 2 3 1

15 9 9 4 6 6

9 10 7 5 6 8

19 14 7 8 2 10

0 0 0

1 1 0 0 0 0

2 4 3 1 1 0

6 5 2 0 1 3

5 3 5 2 1 1

7 7 4 6 0 2

4 1 1 2 3 3

9 3 7 4 1 1

0 0 0

0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 2

0 0 0 0 0 1 1 0

0 0 0 1 0 2 1 1

1 0 0 0 2 0 0 4

0 1 0 1 1 1 3 0

0 0 1 2 2 2 2 2

0 0 0

0 0 0 0 1 0 0 0

0 0 0 1 1 0 0 1

0 0 1 0 0 0 0 0

1 0 0 1 1 1 0 0

0 0 0 0 1 0 0 0

0 0 0 1 0 1 0 1

0 0 0 0 2 1 0 0

0 0 0

0 0 0

0 0 0

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

203

region of the americas

0 1 139 140 115 165 152

0

0 51 41 38 29 25

0 224 199 339 194 186

1 0 255 167 245 190 192

0 221 175 277 179 154

0 146 135 176 139 154

0 129 87 88 108 102

0 94 111 95 103 106

0

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO – 8.0 2.5 3.0 3.0 2.4 0.50 1.0 – – 1.4 3.6 2.6 4.3 2.3 2.8 2.6 2.4 4.0 3.3 2.0 – – – 0.50 – 0.67 2.3 2.3 2.2 2.0 2.1 2.0 2.3 2.1 2.2 2.5 2.3 2.7 – – – – – – – – 1.4 1.6 1.5 1.6

Saint Vincent and the Grenadines

Sint Maarten (Dutch part) Suriname

Trinidad and Tobago

Turks and Caicos Islands

United States of America

Uruguay

US Virgin Islands

Venezuela (Bolivarian Republic of)

1995 2000 2005 2010 2011 2012 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

0 0 0 0 0

1 0 0 0 1 1 0 6 7 5 4 6 6 7 10 11 14 7

0 0 1 2 5 1 0 6 8 21 7 7 15 18 11 21 27 31

4 2 0 2 1

2 1 3 2 3

0 0 0 0 5

1 2 2 0 4

0 0 0

1 0 0 0 0

0 0 0 0 1

0 1 1 1 3 1 0 6 2 6 1 7 4 7 9 7 7 11

0 0 0 0 1

0 1 0 1 3 2 0 0 2 6 2 7 5 5 5 5 4 8

0 0 1 0 0

0 0 0 0 0

0 0 0

0 1 0 0 0 0 2 0 0 0 1 0

0 3 12 35 15 15 10 27 13 17 13 22

0 2 6 19 18 14 12 17 21 32 15 28

0 0 3 5 3 9 7 7 10 20 16 12

0 4 4 10 5 7 4 7 3 8 7 11

0

0 2 0 1 0 2 0 0 0 0 1 2

1 3 3 4 1 1 6 5 4 4 6 9

0 3 1 10 5 5 2 9 3 7 3 10

0 1 1 2 2 1 3 2 4 2 2 4

0 1 2 8 1 0 0 4 3 2 5 12

0

0 0 0

0 0 2

0 0 0

0 0 0

0 0 0 19 6 14 5 12 10 4 0 1 1 0 3 0

0 2 0 355 365 383 246 235 239 28 36 42 46 58 38 0

0 3 876 602 535 360 403 322 40 48 48 70 93 98 0

1 2 2 1 417 906 666 371 374 333 35 45 39 35 55 56 1

0 0 0 1 121 904 767 505 557 502 49 41 45 46 45 52 1

0 1 0 742 577 499 403 434 455 38 30 34 33 36 39 0

0 0 0 1 099 738 624 466 486 529 50 34 36 31 37 29 0

0 0 0

2 0 0

0 0 0

0 0 0 26 14 11 9 15 14 2 2 1 3 1 2

0 0 0 280 246 241 195 160 161 21 28 33 24 29 25

0 0 2 579 376 348 265 254 262 26 22 30 36 55 26

1 0 0 499 349 276 183 199 169 18 21 17 12 19 21

1 0 1 285 253 242 165 150 175 12 13 9 10 12 15

0 0 0 202 152 161 130 138 148 9 12 8 5 11 13

0 0 0 591 396 322 223 269 243 17 16 12 16 16 15

0 0 0

0 1 1

0 0 0

35 22 28 23

312 320 340 379

395 376 353 405

413 333 303 353

402 391 363 375

265 253 307 319

332 288 241 273

0 0

37 26 25 32

351 269 252 276

299 306 316 281

267 188 178 203

183 145 178 167

146 147 150 161

216 188 190 199

0 0

204

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           LABORATORIES SECONDNUMBER OF SMEAR LABS % OF SMEAR CULTURE DST b LABS LPAc LABS LABS US NG LABS PER 5M LINE DST LABS USING PER 100K PER 5M PER 5M a POPULATION POPULATION POPULATION POPULATION XPERT MTB/RIF AVAILABLE LED

FREE THROUGH NTP FIRSTLINE DRUGS

NRLd

TB DIAGNOSIS

TB NOTIF. RIFAMPICIN RATE PER USED 100 000 THROUGHOUT HEALTH-CARE TREATMENT WORKERS

Anguilla Antigua and Barbuda Argentina Aruba Bahamas Barbados Belize Bermuda Bolivia (Plurinational State of) Bonaire, Saint Eustatius and Saba Brazil British Virgin Islands Canada Cayman Islands Chile Colombia Costa Rica Cuba Curaçao Dominica Dominican Republic Ecuador El Salvador Grenada Guatemala Guyana Haiti Honduras Jamaica Mexico Montserrat Nicaragua Panama Paraguay Peru Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Sint Maarten (Dutch part) Suriname Trinidad and Tobago Turks and Caicos Islands United States of America Uruguay US Virgin Islands Venezuela (Bo ivarian Republic of) <0.1 0.6 3.2 1.4 1.8 4.8 1.9 2.5 2.5 2.1 0.1 1.0 2.0 2.3 3.3 1.0 5.6 2.2 5.1 0.9 1.7

– – 0 – – – 0 – 0 – 2.0 – – – – 0 0 0 – – – 2 0 0 – 18 100 6 0 100 0 – 100 0 23 0 – – – – – 0 – – – 100 – 0.8 0 3.5 0.2 0.2 0 1.5 1.5 1.5 0 9.4 0 0 2 1.7 14.5 8.2 11.0 0.8 1.3 0.7 1.8 1.3 0 0.2 0 3 0 0 3.3 6.3 1.0 3.2 0 2.7 1 6.3 1 0.6 0 0.6 0 6.3 1 0 0 <0.1 0 0 7 0 0 6 5.8 5.8 8.7 1 0.3 0.8 0 0 0 5 1 11.2 124.6 14.6 0.3 0.4 1 0.3 0.5 0 1 4 4 5.5 0.9 0.2 13 24.8 0.5 0 0 0 0 0 0 12.5 1.9 0 0

Yes Yes Yes Yes Yes Yes Yes Yes Yes

Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects)

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 31 7 109 21 33 14 83

Out of Yes country In and out Yes of country Yes Out of Yes country Out of Yes country In and out Yes of country Out of No country Out of Yes country No Yes In country In country Out of country No Out of country Out of country Out of country Out of country In and out of country Yes Yes Yes No Yes Yes No Yes Yes

Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (other criteria) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects)

In country Yes Out of Yes country In country Yes

Yes (a l suspects)

Yes

Yes

2 242

a b

LED = Light emitting diode microscopes DST = Drug susceptibility testing ig g c LPA = Line probe assay p e g d NRL = National ug Reference Laboratory

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

205

region of the americas

No Out of country In country Out of country Out of country Out of country Out of country Out of country Out of country Out of country In country Out of country In country Out of country In country In country No No Out of country Out of country In country In country Out of country

No Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes

No Yes (a l suspects) Yes (a l suspects) No Yes (other criteria) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects)

No Yes Yes No Yes Yes Yes Yes Yes Don't know Yes No Yes Yes

No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

             New TB cases Year Source Coverage Percentage Year

Previously treated TB cases Source Coverage Percentage

Anguilla Antigua and Barbuda Argentina Aruba Bahamas Barbados Belize Bermuda Bolivia (Plurinational State of) Bonaire, Saint Eustatius and Saba Brazil British Virgin Islands Canada Cayman Islands Chile Colombia Costa Rica Cuba Curaçao Dominica Dominican Repub ic Ecuador El Salvador Grenada Guatemala Guyana Haiti Honduras Jamaica Mexico Montserrat Nicaragua Panama Paraguay Peru Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Sint Maarten (Dutch part) Suriname Trinidad and Tobago Turks and Caicos Islands United States of America Uruguay Venezuela (Bolivarian Republic of)

2005 2012

Survey Surveillance

National National

2.2 (1.2–3.6) 3.7 (<0.1–19)

2005 2012

Survey Surveillance

National National

15 (9.8–23) 0 (0–98)

2012 1996 2011 2008 2012 2012 2001 2005 2006 2012 2012 2011 1995 2002 2001 2002

Surveillance Survey Surveillance Survey Surveillance Surveillance Survey Survey Survey Surveillance Surveillance Surveillance Survey Survey Survey Survey

National National National Sub-national National National National National National National National National National National National National

0 (0–84) 1.2 (0.44–2.6) 50 (1.3–99) 1.4 (1.0–1.8) 0.57 0 0.69 2.4 1.5 0.74 0 0 6.6 4.9 0.33 (0.23–1.2) (0–52) (0.25–1.5) (1.6–3.6) (0.42–3.9) (<0.1–2.7) (0–98) (0–98) (4.1–10) (3.5–6.7) (<0.1–1.2)

2012 2012 2011 2008 2012 2012 2012 2012 2012 2012 2012 2012 1995 2012 2012 2002

Surveillance Surveillance Surveillance Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Survey Surveillance Surveillance Survey

National National National Sub-national National National National National National National National National National National National National

0 (0–98) 11 (8.9–14) 100 (2.5–100) 7.5 (5.7–9.9) 1.6 0 2.9 13 4.5 12 0 0 20 26 11 (<0.1–8.5) (0–98) (0.95–6.7) (9.6–17) (0.12–23) (4.4–24) (0–98) (0–98) (13–28) (23–29) (4.9–20)

3 (1.8–4.6)

26 (20–34)

2004 2009 2006 2008 2012 2012

Survey Survey Survey Survey Surveillance Surveillance

National National National National National National

1.8 (0.76–3.4) 2.4 (2.1–2.8) 0.63 (<0.1–2.2) 0.31 (<0.1–1.7) 3.9 (3.6–4.2) 0 (0–6.5)

2004 2009 2010 2008 2012 2012

Survey Survey Surveillance Survey Surveillance Surveillance

National National National National National National

12 (5.8–22) 6.3 (5.1–7.8) 11 (6.2–17) 15 (6.1–28) 35 (33–37) 33 (0.84–91)

2012 2012 1999

Surveillance Surveillance Survey

National National National

1 (0.80–1.3) 0 (0–0.79) 0.52 (0.14–1.3)

2012 2012 1999

Surveillance Surveillance Survey

National National National

2.9 (1.4–5.4) 2.4 (<0.1–13) 13 (7.6–22)

a

Empty rows indicate an absence of high-quality survey or surveillance data. In the absence of high-quality national data, high-quality sub-national data are used.

206

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

eastern mediterranean region Table A4.1 Estimates of the burden of disease caused by TB, 1990–2012 Table A4.2 Incidence, notification and case detection rates, all forms, 1990–2012 Table A4.3 Case notifications, 1990–2012 Table A4.4 Treatment outcomes, new smear-positive cases, 1995–2011 Table A4.5 Treatment outcomes, retreatment cases, 1995–2011 Table A4.6 HIV testing and provision of CPT, ART and IPT, 2005–2012 Table A4.7 Testing for MDR-TB and number of confirmed cases of MDR-TB, 2005–2012 Table A4.8 New smear-positive case notification by age and sex, 1995–2012 Table A4.9 Laboratories, NTP services, drug management and infection control, 2012 Table A4.10 Measured percentage of TB cases with MDR-TB, most recent year available 209 211 213 215 217 219 220 221 223 224

Estimates of mortality, prevalence and incidence Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See ANNEX 1 for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. The main updates implemented in this report are explained in Box 2.1 of Chapter 2. Estimates published in previous global TB control reports should no longer be used.

Data source Data shown in this annex are taken from the WHO global TB database on 1 October 2013. Data shown in the main part of the report were taken from the database in July 2013. As a result, data in this annex may differ slightly from those in the main part of the report. Data for all years can be downloaded from www.who.int/tb/data.

208

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATE a

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Afghanistan

Bahrain

Djibouti

Egypt

Iran (Islamic Republic of)

Iraq

Jordan

Kuwait

Lebanon

Libyan Arab Jamahiriya

Morocco

Oman

Pakistan

Qatar

Saudi Arabia

Somalia

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

12 18 21 25 28 29 30 <1 <1 <1 <1 1 1 1 <1 <1 <1 <1 <1 <1 <1 56 61 66 72 78 79 81 56 60 66 70 74 75 76 18 20 24 27 31 32 33 3 4 5 5 6 7 7 2 2 2 2 3 3 3 3 3 3 4 4 4 5 4 5 5 6 6 6 6 25 27 29 30 32 32 33 2 2 2 3 3 3 3 111 127 144 158 173 176 179 <1 <1 <1 <1 2 2 2 16 19 20 25 27 28 28 6 6 7 8 10 10 10

3.7 8.7 11 9.7 10 10 11 0.034 0.02 0.017 <0.01 <0.01 <0.01 <0.01 0.59 0.4 0.41 0.65 0.68 0.67 0.66 1.8 1.5 1.1 0.76 0.45 0.56 0.38 2.6 3.2 2.5 2.1 2.2 2.3 2.2 1.2 1.2 1.1 1.1 0.98 0.97 0.96 0.041 0.04 0.039 0.036 0.037 0.037 0.037 0.019 0.023 0.015 0.023 0.033 0.018 0.031 0.085 0.067 0.04 0.046 0.065 0.073 0.072 0.44 0.28 0.27 0.23 0.32 0.34 0.42 6.2 5.2 4.3 3.5 3.1 3 3 0.059 0.05 0.041 0.035 0.028 0.029 0.031 80 90 99 84 64 62 62 0.031 0.016 <0.01 <0.01 <0.01 <0.01 <0.01 0.63 0.71 0.79 0.95 1.1 1.1 1.1 5.7 5 5 4.8 5.7 6.1 6.5

(0.860–8.5) (2.9–18) (4.0–21) (3.9–18) (4.2–18) (4.4–19) (4.6–20) (0.032–0.037) (0.018–0.022) (0.015–0.020) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.140–1.3) (0.160–0.750) (0.180–0.740) (0.260–1.2) (0.290–1.2) (0.280–1.2) (0.280–1.2) (1.4–2.2) (1.2–1.9) (0.840–1.4) (0.700–0.830) (0.420–0.490) (0.530–0.600) (0.350–0.400) (0.870–5.3) (1.1–6.5) (0.830–5.1) (0.680–4.2) (0.730–4.5) (0.780–4.7) (0.700–4.7) (0.410–2.4) (0.310–2.6) (0.180–2.9) (0.100–3.1) (0.039–3.4) (0.030–3.5) (0.025–3.5) (0–0.330) (0–0.390) (0–0.410) (0–0.410) (0–0.420) (0–0.420) (0–0.420) (0.017–0.022) (0.021–0.024) (0.014–0.015) (0.022–0.023) (0.033–0.033) (0.018–0.018) (0.030–0.031) (0.046–0.130) (0.034–0.110) (0.020–0.069) (0.025–0.074) (0.035–0.110) (0.039–0.120) (0.038–0.120) (0.170–0.840) (0.120–0.500) (0.120–0.490) (0.120–0.390) (0.140–0.570) (0.140–0.610) (0.180–0.760) (4.8–7.7) (3.7–6.8) (2.8–6.1) (2.0–5.5) (1.5–5.2) (1.5–5.2) (1.4–5.1) (<0.01–0.200) (<0.01–0.230) (<0.01–0.230) (0–0.250) (0–0.260) (0–0.280) (0–0.300) (24–170) (32–180) (36–190) (33–160) (28–110) (27–110) (27–110) (0.030–0.032) (0.016–0.017) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.061–1.9) (0.068–2.1) (0.075–2.3) (0.091–2.8) (0.100–3.1) (0.100–3.2) (0.110–3.2) (1.7–12) (1.8–9.7) (1.9–9.7) (1.9–8.9) (2.3–11) (2.4–11) (2.5–12)

31 49 53 39 35 36 37 7 3.5 2.5 0.85 0.44 0.39 0.34 99 60 57 83 82 79 76 3.2 2.5 1.7 1.1 0.58 0.71 0.46 4.6 5.4 3.8 3 3 3.1 2.9 6.9 5.7 4.7 3.9 3.2 3 2.9 1.2 0.93 0.81 0.7 0.57 0.55 0.53 0.94 1.4 0.76 0.99 1.1 0.58 0.94 3.1 2.2 1.2 1.2 1.5 1.6 1.5 10 5.9 5.3 4.2 5.4 5.5 6.8 25 19 15 12 9.8 9.5 9.2 3.2 2.3 1.8 1.4 1 0.97 0.92 72 71 69 53 37 35 34 6.5 3.3 0.7 0.15 0.22 0.19 0.17 3.9 3.8 3.9 3.9 3.9 3.9 3.9 90 79 68 56 59 61 64

(7.3–72) (17–100) (19–102) (16–73) (15–65) (15–66) (15–68) (6.5–7.4) (3.2–3.8) (2.2–3.0) (0.78–0.93) (0.38–0.51) (0.32–0.46) (0.28–0.41) (24–226) (23–114) (25–102) (33–156) (34–149) (34–144) (33–139) (2.5–3.9) (1.9–3.2) (1.3–2.2) (0.97–1.2) (0.54–0.62) (0.66–0.76) (0.43–0.50) (1.5–9.4) (1.8–11) (1.3–7.7) (0.97–6.0) (0.98–6.0) (1.0–6.3) (0.92–6.1) (2.3–14) (1.5–13) (0.77–12) (0.38–11) (0.13–11) (0.10–11) (<0.1–11) (0–9.9) (0–9.0) (0–8.6) (0–7.8) (0–6.5) (0–6.3) (0–6.0) (0.81–1.1) (1.3–1.5) (0.75–0.78) (0.97–1.0) (1.1–1.1) (0.57–0.58) (0.93–0.95) (1.7–5.0) (1.1–3.7) (0.61–2.1) (0.62–1.8) (0.80–2.4) (0.86–2.6) (0.81–2.5) (3.9–20) (2.6–11) (2.3–9.4) (2.1–6.9) (2.4–9.5) (2.3–10) (2.9–12) (19–31) (14–25) (9.7–21) (6.8–18) (4.9–16) (4.6–16) (4.4–16) (0.14–11) (<0.1–10) (0–10) (0–10) (0–9.4) (0–9.2) (0–9.0) (22–152) (25–139) (25–135) (21–101) (16–66) (15–63) (15–61) (6.3–6.6) (3.1–3.4) (0.62–0.78) (0.12–0.17) (0.15–0.30) (0.12–0.27) (0.10–0.25) (0.37–11) (0.37–11) (0.37–11) (0.37–11) (0.37–11) (0.37–11) (0.39–11) (27–190) (29–153) (26–131) (23–105) (24–111) (24–115) (25–120)

38 79 92 92 99 100 110 0.16 0.081 0.37 0.42 0.34 0.32 0.38 6.2 5.4 5.6 7.1 7.7 7.7 7.7 48 37 28 24 23 23 23 29 35 27 23 24 25 25 17 16 14 19 24 23 24 0.61 0.65 0.48 0.47 0.57 0.57 0.6 0.48 0.46 0.77 0.71 1.7 0.98 1.1 1.2 1.1 0.66 0.61 0.83 0.91 0.95 3.6 2.9 3 2.8 3.5 3.7 4.1 57 64 46 41 44 46 46 0.8 0.4 0.57 0.36 0.45 0.51 0.6 650 740 820 760 670 670 670 0.28 0.54 0.43 0.53 0.82 0.78 1.2 4 3.9 5.3 5.1 7.7 6.1 4.9 46 42 45 45 53 56 59

(13–77) (37–140) (43–160) (46–150) (50–160) (52–170) (54–180) (0.049–0.350) (0.024–0.170) (0.180–0.630) (0.170–0.790) (0.110–0.690) (0.120–0.630) (0.180–0.650) (2.2–12) (2.2–10) (2.4–10) (3.4–12) (3.7–13) (3.6–13) (3.6–13) (22–84) (19–61) (14–46) (12–41) (12–39) (12–39) (12–39) (12–53) (15–64) (11–51) (9.4–42) (9.9–44) (11–47) (10–47) (4.9–35) (4.9–34) (5.0–29) (8.8–33) (13–40) (12–39) (12–40) (0.230–1.2) (0.250–1.2) (0.180–0.930) (0.170–0.910) (0.240–1.0) (0.250–1.0) (0.280–1.0) (0.230–0.830) (0.160–0.930) (0.300–1.5) (0.240–1.4) (0.860–2.9) (0.330–2.0) (0.360–2.1) (0.460–2.3) (0.340–2.2) (0.220–1.3) (0.260–1.1) (0.370–1.5) (0.410–1.6) (0.390–1.7) (1.7–6.4) (1.3–5.1) (1.3–5.4) (1.1–5.5) (1.5–6.3) (1.8–6.4) (1.9–7.0) (24–110) (30–110) (20–84) (17–75) (19–79) (20–82) (19–83) (0.360–1.4) (0.140–0.790) (0.280–0.960) (0.120–0.730) (0.170–0.870) (0.200–0.950) (0.260–1.1) (250–1 300) (330–1 300) (370–1 400) (380–1 300) (330–1 100) (330–1 100) (320–1 100) (0.110–0.520) (0.260–0.910) (0.180–0.780) (0.230–0.950) (0.290–1.6) (0.260–1.6) (0.560–2.1) (1.8–7.0) (1.4–7.6) (2.2–9.7) (1.9–9.8) (3.7–13) (2.5–11) (1.6–10) (17–89) (19–73) (21–76) (23–76) (27–89) (28–94) (29–99)

327 447 449 369 350 352 358 33 14 56 48 27 25 29 1 050 809 775 920 922 911 897 85 60 42 34 30 29 29 51 58 41 32 32 34 33 94 79 61 70 78 73 73 18 15 10 9 8.8 8.5 8.5 23 29 41 31 58 31 33 45 35 20 15 19 20 20 86 61 57 51 58 61 66 232 240 161 137 138 143 140 44 18 26 14 16 17 18 589 584 573 483 389 381 376 59 107 72 64 47 41 60 25 21 26 21 28 22 17 732 663 604 537 555 566 581

(112–655) (208–775) (210–775) (185–617) (177–580) (177–585) (181–595) (9.9–70) (4.3–30) (27–94) (19–89) (9.0–55) (9.0–49) (14–49) (368–2 070) (326–1 510) (333–1 400) (444–1 570) (440–1 580) (430–1 570) (418–1 560) (39–149) (31–99) (20–70) (17–57) (15–50) (15–49) (15–48) (21–93) (24–106) (17–77) (13–60) (13–59) (14–62) (13–61) (28–200) (24–167) (21–121) (32–122) (41–128) (37–123) (36–122) (6.8–35) (5.8–29) (3.8–20) (3.3–17) (3.8–16) (3.7–15) (3.9–15) (11–40) (9.9–59) (16–77) (11–62) (29–98) (11–63) (11–65) (17–87) (11–72) (6.9–41) (6.5–28) (8.6–34) (9.1–36) (8.5–37) (39–150) (27–108) (24–104) (19–98) (25–104) (29–105) (31–113) (97–426) (112–415) (68–292) (57–251) (59–251) (62–257) (58–257) (20–78) (6.5–37) (13–44) (4.9–29) (6.1–31) (6.7–31) (7.8–33) (222–1 130) (262–1 030) (260–1 010) (239–810) (191–657) (185–647) (181–641) (24–108) (52–182) (30–132) (28–115) (17–92) (14–82) (27–105) (11–43) (7.7–41) (11–48) (7.8–40) (13–48) (9.1–40) (5.5–36) (272–1 410) (305–1 160) (291–1 030) (267–900) (279–925) (283–947) (287–975)

22 33 39 47 54 55 56 0.13 0.049 0.24 0.32 0.28 0.26 0.26 3.7 4.1 4.5 4.8 5.2 5.2 5.3 19 19 17 15 14 14 14 18 21 17 14 15 16 16 9.5 11 12 13 14 14 15 0.48 0.51 0.38 0.38 0.41 0.4 0.4 0.32 0.39 0.59 0.59 1.1 0.77 0.85 0.94 0.88 0.56 0.45 0.6 0.67 0.73 1.7 1.9 2.1 2.2 2.4 2.4 2.5 36 41 33 30 32 33 33 0.55 0.32 0.37 0.3 0.35 0.39 0.44 260 290 330 370 400 410 410 0.21 0.35 0.32 0.37 0.67 0.64 0.84 2.8 3.1 4 4.1 5.1 4.5 4.2 18 18 21 24 28 28 29

(14–33) (27–40) (32–47) (38–56) (44–64) (45–66) (47–67) (0.120–0.150) (0.043–0.056) (0.210–0.270) (0.280–0.360) (0.250–0.320) (0.230–0.290) (0.230–0.290) (2.3–5.3) (3.4–4.9) (3.8–5.2) (3.9–5.8) (4.3–6.2) (4.3–6.2) (4.4–6.3) (16–23) (16–23) (14–20) (13–18) (12–16) (12–16) (12–16) (13–23) (16–28) (12–22) (10–19) (11–19) (11–21) (11–21) (8.3–11) (9.4–12) (10–14) (11–15) (12–16) (13–16) (13–17) (0.420–0.550) (0.450–0.580) (0.340–0.440) (0.330–0.430) (0.360–0.460) (0.350–0.460) (0.360–0.460) (0.280–0.360) (0.340–0.440) (0.520–0.670) (0.520–0.670) (0.960–1.2) (0.680–0.870) (0.740–0.960) (0.820–1.1) (0.770–1.0) (0.490–0.630) (0.400–0.510) (0.530–0.680) (0.590–0.760) (0.640–0.830) (1.4–2.0) (1.5–2.3) (1.7–2.5) (1.9–2.6) (2.0–2.9) (2.0–2.9) (2.0–2.9) (27–47) (33–49) (29–38) (26–34) (28–36) (29–37) (29–38) (0.490–0.630) (0.280–0.360) (0.320–0.420) (0.260–0.340) (0.310–0.400) (0.340–0.440) (0.380–0.500) (160–380) (240–350) (270–400) (300–440) (330–480) (340–490) (340–490) (0.190–0.240) (0.310–0.400) (0.280–0.360) (0.330–0.420) (0.580–0.750) (0.560–0.720) (0.730–0.950) (2.4–3.1) (2.7–3.5) (3.5–4.5) (3.6–4.6) (4.5–5.8) (4.0–5.1) (3.7–4.8) (11–27) (15–22) (17–25) (20–29) (23–33) (23–34) (24–35)

189 189 189 189 189 189 189 27 8.8 36 37 23 20 20 619 619 619 619 620 620 620 34 32 26 21 18 17 17 31 35 26 20 20 21 21 54 53 50 48 45 45 45 14 12 8.1 7.2 6.3 6 5.8 15 24 31 26 37 25 26 35 29 17 11 14 15 16 40 40 40 40 40 40 40 147 152 117 100 100 103 103 31 15 17 12 13 13 13 231 231 231 231 231 231 231 44 70 54 46 38 33 41 17 17 20 16 19 16 15 285 285 285 285 286 286 286

(117–279) (155–227) (155–227) (155–227) (156–225) (156–225) (156–226) (24–31) (7.7–9.9) (31–40) (32–41) (20–26) (18–23) (17–22) (395–893) (506–744) (528–718) (506–744) (512–738) (512–738) (512–738) (29–40) (27–37) (22–30) (18–25) (15–21) (15–20) (14–19) (23–41) (26–46) (19–34) (15–27) (14–26) (15–27) (15–28) (47–62) (46–60) (44–57) (42–54) (40–52) (39–51) (39–51) (13–16) (10–13) (7.1–9.1) (6.3–8.1) (5.5–7.1) (5.2–6.8) (5.1–6.5) (14–18) (21–28) (27–35) (23–29) (32–42) (22–28) (23–30) (31–39) (26–33) (15–20) (10–13) (12–16) (13–17) (14–18) (33–48) (33–48) (33–48) (34–46) (33–48) (33–48) (33–48) (110–189) (124–182) (102–132) (88–113) (88–114) (90–117) (90–117) (27–35) (13–17) (15–19) (10–13) (11–14) (11–15) (12–15) (143–341) (189–278) (189–278) (189–278) (190–276) (190–276) (190–276) (39–50) (61–79) (47–61) (40–52) (33–43) (29–38) (36–46) (15–19) (15–19) (17–22) (14–19) (17–21) (14–18) (13–17) (176–421) (233–343) (233–343) (233–343) (236–340) (236–340) (236–340)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

209

eastern mediterranean region

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

South Sudan Sudan

Syrian Arab Republic

Tunisia

United Arab Emirates

West Bank and Gaza Strip

Yemen

2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

10 11 26 30 34 40 46 36 37 12 14 16 18 22 22 22 8 9 10 10 11 11 11 2 2 3 4 8 9 9 2 3 3 4 4 4 4 12 15 18 20 23 23 24

3.1 3.2 11 9 9.3 9.3 10 8 8 0.97 0.85 0.56 0.47 0.47 0.47 0.46 0.24 0.3 0.26 0.25 0.31 0.33 0.32 0.017 0.022 0.029 0.02 0.022 0.015 <0.01 <0.01 0.035 0.018 0.012 <0.01 <0.01 <0.01 3.8 3.5 3.3 2.8 1.4 1.4 1.3

(1.3–5.6) (1.4–5.8) (4.4–22) (3.8–16) (4.0–17) (4.0–17) (4.3–18) (3.4–15) (3.3–15) (0.270–2.1) (0.370–1.5) (0.280–0.930) (0.220–0.810) (0.210–0.830) (0.210–0.830) (0.210–0.820) (0.130–0.370) (0.160–0.470) (0.140–0.410) (0.140–0.400) (0.170–0.500) (0.180–0.520) (0.170–0.500) (0–0.110) (0–0.140) (0–0.190) (0–0.150) (0–0.150) (0–0.097) (<0.01–0.045) (<0.01–<0.01) (0.034–0.036) (0.018–0.019) (0.012–0.012) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (1.1–8.2) (1.5–6.3) (1.4–6.0) (1.2–5.2) (0.640–2.5) (0.630–2.5) (0.600–2.4)

30 30 44 30 27 24 22 22 22 7.8 5.9 3.4 2.6 2.2 2.2 2.1 2.9 3.3 2.7 2.5 2.9 3.1 2.9 0.95 0.95 0.95 0.49 0.26 0.17 0.1 0.45 1.3 0.57 0.34 0.23 0.23 0.23 32 23 19 14 6.2 6 5.6

(13–54) (13–54) (17–84) (13–55) (12–49) (10–42) (9.4–40) (9.3–40) (9.0–40) (2.2–17) (2.6–11) (1.7–5.7) (1.2–4.4) (0.99–3.9) (0.98–3.8) (0.96–3.7) (1.6–4.6) (1.8–5.3) (1.5–4.3) (1.4–4.0) (1.6–4.7) (1.7–4.8) (1.6–4.6) (0–6.1) (0–6.1) (0–6.1) (0–3.6) (0–1.8) (0–1.1) (0–0.49) (0.43–0.46) (1.3–1.4) (0.56–0.58) (0.33–0.35) (0.23–0.24) (0.22–0.23) (0.22–0.23) (9.3–70) (9.8–42) (8.1–34) (5.9–26) (2.8–11) (2.7–11) (2.5–9.9)

28 28 99 89 90 90 96 76 77 11 9.3 7 5.9 5.6 5.5 5.3 3.2 3.9 3.3 3.3 4.1 4.4 4.5 0.39 0.51 0.65 0.44 0.52 0.37 0.22 0.18 0.27 0.45 0.29 0.25 0.34 0.47 35 36 35 29 17 17 17

(13–47) (13–47) (48–170) (45–150) (45–150) (45–150) (48–160) (38–130) (39–130) (3.6–22) (3.9–17) (2.5–14) (2.1–12) (2.1–11) (2.1–10) (2.1–9.9) (1.3–5.8) (1.7–6.9) (1.4–6.0) (1.4–5.9) (1.7–7.6) (1.8–8.1) (1.7–8.5) (0.170–0.710) (0.220–0.910) (0.280–1.2) (0.190–0.800) (0.230–0.930) (0.160–0.660) (0.077–0.440) (0.091–0.320) (0.230–0.800) (0.340–1.3) (0.240–0.910) (0.240–0.870) (0.290–1.1) (0.370–1.4) (13–66) (18–60) (17–59) (14–48) (7.5–29) (7.4–30) (7.1–30)

268 257 386 296 262 226 210 209 207 86 65 43 33 26 25 24 39 43 35 33 39 41 41 22 22 22 11 6.2 4.2 2.4 8.6 10 14 8.1 6.1 8.3 11 293 239 198 142 73 72 70

(129–456) (124–437) (185–659) (149–491) (132–436) (113–378) (105–350) (105–347) (104–345) (29–174) (27–119) (15–85) (11–65) (9.8–50) (9.8–47) (9.7–45) (16–72) (18–77) (15–63) (14–59) (16–71) (17–75) (16–78) (9.2–39) (9.2–39) (9.3–39) (4.5–19) (2.7–11) (1.8–7.4) (0.84–4.8) (4.4–15) (8.7–31) (11–41) (6.8–26) (6.0–22) (7.1–26) (8.7–32) (112–558) (118–401) (97–335) (71–239) (33–129) (32–129) (30–127)

15 16 44 47 50 53 54 42 42 7.5 6.6 5.7 4.8 4.3 4.1 3.9 2.3 2.7 2.4 2.4 3 3.2 3.4 0.22 0.28 0.36 0.21 0.26 0.21 0.16 0.12 0.22 0.33 0.23 0.21 0.26 0.32 16 21 20 16 11 11 12

(13–18) (13–19) (36–52) (39–56) (41–59) (43–63) (45–65) (35–51) (35–51) (5.3–10) (5.4–7.9) (4.9–6.6) (4.0–5.6) (3.5–5.1) (3.4–4.9) (3.2–4.6) (2.0–2.6) (2.4–3.1) (2.1–2.7) (2.1–2.7) (2.6–3.4) (2.8–3.6) (3.0–3.8) (0.160–0.280) (0.200–0.370) (0.260–0.480) (0.150–0.270) (0.190–0.340) (0.150–0.270) (0.120–0.210) (0.110–0.140) (0.200–0.250) (0.290–0.370) (0.200–0.260) (0.190–0.240) (0.230–0.290) (0.280–0.360) (10–24) (17–25) (17–24) (13–19) (9.2–13) (9.4–14) (9.6–14)

146 146 170 158 144 133 119 117 114 61 46 35 26 20 19 18 29 31 25 23 28 30 31 12 12 12 5 3.1 2.3 1.7 6 8.6 10 6.5 5.3 6.3 7.6 137 137 116 81 49 49 49

(121–174) (121–174) (140–203) (130–188) (119–172) (110–158) (98–142) (96–139) (94–136) (43–82) (38–55) (30–40) (22–31) (16–24) (16–22) (15–21) (25–32) (27–35) (22–28) (21–27) (25–32) (26–34) (27–35) (8.7–16) (8.7–16) (8.7–16) (3.6–6.5) (2.3–4.1) (1.7–3.0) (1.2–2.3) (5.2–6.8) (7.5–9.7) (9.0–12) (5.7–7.3) (4.6–6.0) (5.5–7.1) (6.7–8.6) (85–202) (112–165) (94–139) (66–97) (40–58) (40–58) (40–58)

a

Rates are per 100 000 population.

210

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSEb NUMBER RATEa

CASE DETECTION PERCENT

Afghanistan

Bahrain

Djibouti

Egypt

Iran (Islamic Repub ic of)

Iraq

Jordan

Kuwa t

Lebanon

Libyan Arab Jamahiriya

Morocco

Oman

Pakistan

Qatar

Saudi Arabia

Somalia

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

12 18 21 25 28 29 30 <1 <1 <1 <1 1 1 1 <1 <1 <1 <1 <1 <1 <1 56 61 66 72 78 79 81 56 60 66 70 74 75 76 18 20 24 27 31 32 33 3 4 5 5 6 7 7 2 2 2 2 3 3 3 3 3 3 4 4 4 5 4 5 5 6 6 6 6 25 27 29 30 32 32 33 2 2 2 3 3 3 3 111 127 144 158 173 176 179 <1 <1 <1 <1 2 2 2 16 19 20 25 27 28 28 6 6 7 8 10 10 10

22 33 39 47 54 55 56 0.13 0.049 0.24 0.32 0.28 0.26 0.26 3.7 4.1 4.5 4.8 5.2 5.2 5.3 19 19 17 15 14 14 14 18 21 17 14 15 16 16 9.5 11 12 13 14 14 15 0.48 0.51 0.38 0.38 0.41 0.4 0.4 0.32 0.39 0.59 0.59 1.1 0.77 0.85 0.94 0.88 0.56 0.45 0.6 0.67 0.73 1.7 1.9 2.1 2.2 2.4 2.4 2.5 36 41 33 30 32 33 33 0.55 0.32 0.37 0.3 0.35 0.39 0.44 260 290 330 370 400 410 410 0.21 0.35 0.32 0.37 0.67 0.64 0.84 2.8 3.1 4 4.1 5.1 4.5 4.2 18 18 21 24 28 28 29

(14–33) (27–40) (32–47) (38–56) (44–64) (45–66) (47–67) (0.120–0.150) (0.043–0.056) (0.210–0.270) (0.280–0.360) (0.250–0.320) (0.230–0.290) (0.230–0.290) (2.3–5.3) (3.4–4.9) (3.8–5.2) (3.9–5.8) (4.3–6.2) (4.3–6.2) (4.4–6.3) (16–23) (16–23) (14–20) (13–18) (12–16) (12–16) (12–16) (13–23) (16–28) (12–22) (10–19) (11–19) (11–21) (11–21) (8.3–11) (9.4–12) (10–14) (11–15) (12–16) (13–16) (13–17) (0.420–0.550) (0.450–0.580) (0.340–0.440) (0.330–0.430) (0.360–0.460) (0.350–0.460) (0.360–0.460) (0.280–0.360) (0.340–0.440) (0.520–0.670) (0.520–0.670) (0.960–1.2) (0.680–0.870) (0.740–0.960) (0.820–1.1) (0.770–1.0) (0.490–0.630) (0.400–0.510) (0.530–0.680) (0.590–0.760) (0.640–0.830) (1.4–2.0) (1.5–2.3) (1.7–2.5) (1.9–2.6) (2.0–2.9) (2.0–2.9) (2.0–2.9) (27–47) (33–49) (29–38) (26–34) (28–36) (29–37) (29–38) (0.490–0.630) (0.280–0.360) (0.320–0.420) (0.260–0.340) (0.310–0.400) (0.340–0.440) (0.380–0.500) (160–380) (240–350) (270–400) (300–440) (330–480) (340–490) (340–490) (0.190–0.240) (0.310–0.400) (0.280–0.360) (0.330–0.420) (0.580–0.750) (0.560–0.720) (0.730–0.950) (2.4–3.1) (2.7–3.5) (3.5–4.5) (3.6–4.6) (4.5–5.8) (4.0–5.1) (3.7–4.8) (11–27) (15–22) (17–25) (20–29) (23–33) (23–34) (24–35)

189 189 189 189 189 189 189 27 8.8 36 37 23 20 20 619 619 619 619 620 620 620 34 32 26 21 18 17 17 31 35 26 20 20 21 21 54 53 50 48 45 45 45 14 12 8.1 7.2 6.3 6 5.8 15 24 31 26 37 25 26 35 29 17 11 14 15 16 40 40 40 40 40 40 40 147 152 117 100 100 103 103 31 15 17 12 13 13 13 231 231 231 231 231 231 231 44 70 54 46 38 33 41 17 17 20 16 19 16 15 285 285 285 285 286 286 286

(117–279) (155–227) (155–227) (155–227) (156–225) (156–225) (156–226) (24–31) (7.7–9.9) (31–40) (32–41) (20–26) (18–23) (17–22) (395–893) (506–744) (528–718) (506–744) (512–738) (512–738) (512–738) (29–40) (27–37) (22–30) (18–25) (15–21) (15–20) (14–19) (23–41) (26–46) (19–34) (15–27) (14–26) (15–27) (15–28) (47–62) (46–60) (44–57) (42–54) (40–52) (39–51) (39–51) (13–16) (10–13) (7.1–9.1) (6.3–8.1) (5.5–7.1) (5.2–6.8) (5.1–6.5) (14–18) (21–28) (27–35) (23–29) (32–42) (22–28) (23–30) (31–39) (26–33) (15–20) (10–13) (12–16) (13–17) (14–18) (33–48) (33–48) (33–48) (34–46) (33–48) (33–48) (33–48) (110–189) (124–182) (102–132) (88–113) (88–114) (90–117) (90–117) (27–35) (13–17) (15–19) (10–13) (11–14) (11–15) (12–15) (143–341) (189–278) (189–278) (189–278) (190–276) (190–276) (190–276) (39–50) (61–79) (47–61) (40–52) (33–43) (29–38) (36–46) (15–19) (15–19) (17–22) (14–19) (17–21) (14–18) (13–17) (176–421) (233–343) (233–343) (233–343) (236–340) (236–340) (236–340)

0.041 0.072 0.1 0.16 0.25 0.28 0.31

(0.025–0.060) (0.040–0.11) (0.058–0.16) (0.090–0.24) (0.15–0.38) (0.17–0.41) (0.19–0.46)

0.4 0.4 0.5 0.6 0.9 1 1

(0.22–0.52) (0.23–0.65) (0.28–0.77) (0.36–0.96) (0.54–1.3) (0.58–1.4) (0.63–1.5)

4 332 7 107 21 844 28 029 27 983 29 381 117 43 207 280 246 225 225 2 100 3 971 3 109 4 172 3 686 3 474 2 142 11 145 10 762 11 446 9 260 8 974 8 453 9 255 15 936 11 850 9 212 10 362 10 980 11 042 14 735 9 697 9 697 9 454 9 707 8 837 8 664 439 498 306 367 338 328 331 277 336 513 517 957 672 737 983 571 391 513 496 630 442 1 440 1 341 2 098 1 518 1 549 27 658 29 829 28 852 26 269 28 359 28 640 28 635 482 276 321 261 308 337 382 156 759 13 142 11 050 142 017 264 235 264 934 267 475 184 304 279 325 580 553 728 2 415 3 452 3 539 4 465 3 932 3 690 2 504 5 686 12 904 10 139 11 653 11 975

37 35 88 99 96 99 24 7.6 31 32 20 17 17 356 549 400 500 435 404 3.8 18 16 16 12 11 10 16 26 18 13 14 15 14 84 48 41 35 31 28 26 13 12 6.4 7 5.2 4.9 4.7 13 21 27 23 32 22 23 32 18 9.8 12 11 14 10 30 26 38 25 25 112 111 100 87 90 89 88 27 13 15 10 11 11 12 141 10 7.7 90 153 150 149 39 61 47 40 33 29 36 15 17 14 16 14 13 39 77 152 105 118 117

20 (13–32) 18 46 52 51 52 87 87 87 87 87 87 87 57 89 65 81 70 65 11 58 63 75 66 65 62 53 75 70 65 70 70 70 160 90 81 72 69 62 59 91 97 80 98 83 81 82 87 87 87 87 87 87 87 110 100 86 85 74 86 26 76 65 94 62 63 76 73 86 87 89 87 86 87 87 87 87 87 87 87 61 4.5 3.3 39 66 65 65 87 87 87 87 87 87 87 87 87 87 87 87 87 14 27 53 37 41 41 (15–22) (39–57) (44–63) (43–62) (44–63) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (40–90) (76–100) (54–79) (68–98) (59–85) (55–79) (9.4–13) (49–68) (54–75) (64–89) (57–78) (56–76) (54–73) (40–72) (57–100) (53–96) (49–89) (53–96) (53–96) (52–97) (140–180) (80–100) (71–93) (64–82) (61–79) (54–71) (52–68) (80–100) (86–110) (70–91) (86–110) (74–95) (72–93) (72–93) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (98–130) (90–120) (76–98) (75–97) (65–84) (76–99) (22–32) (63–93) (54–79) (81–110) (52–76) (53–77) (59–100) (61–90) (76–98) (77–99) (79–100) (77–99) (75–98) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (41–99) (3.7–5.5) (2.8–4.1) (32–48) (55–80) (54–79) (54–78) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (12–17) (22–33) (44–65) (31–45) (35–50) (34–50)

<0.01 (0–<0.01)

0 (0–0)

<0.01 (<0.01–<0.01) <0.01 (<0.01–<0.01) <0.01 (<0.01–<0.01) <0.01 <0.01 0.012 0.014 0.017 0.031 0.036 0.041

0.2 (<0.1–0.49) 0.2 (<0.1–0.41) 0.1 (<0.1–0.31)

(<0.01–<0.01) <0.1 (0–<0.1) (<0.01–<0.01) 0.3 (0.23–0.30) (0.011–0.014) 0.4 (0.35–0.45) (0.012–0.015) 0.4 (0.37–0.48) (0.015–0.019) 0.4 (0.37–0.47) (0.027–0.035) 0.7 (0.62–0.80) (0.032–0.041) 0.8 (0.71–0.92) (0.036–0.047) 0.9 (0.77–1.0)

0.21 (0.16–0.26) 0.025 0.094 0.19 0.29 0.5 0.55 0.59 <0.01 <0.01 <0.01 <0.01 <0.01 0.011 0.014 0.026 0.059 0.23 0.8 2.4 3.1 3.8

3.4 (2.6–4.3)

(0.019–0.033) 0.1 (<0.1–0.13) (0.076–0.11) 0.4 (0.28–0.42) (0.16–0.21) 0.7 (0.57–0.74) (0.26–0.33) 1 (0.85–1.1) (0.43–0.56) 1.6 (1.4–1.8) (0.48–0.62) 1.7 (1.5–1.9) (0.51–0.67) 1.8 (1.6–2.0) (<0.01–<0.01) 0.1 (0.10–0.14) (<0.01–<0.01) 0.1 (<0.1–0.12) (<0.01–<0.01) 0.1 (<0.1–0.11) (<0.01–<0.01) 0.1 (<0.1–0.12) (<0.01–<0.01) 0.3 (0.26–0.34) (<0.01–0.012) 0.4 (0.31–0.41) (0.013–0.016) 0.4 (0.38–0.49) (0.016–0.038) <0.1 (<0.1–<0.1) (0.048–0.070) <0.1 (<0.1–<0.1) (0.19–0.28) 0.2 (0.13–0.19) (0.65–0.98) 0.5 (0.41–0.62) (2.0–2.9) 1.4 (1.1–1.7) (2.5–3.7) 1.7 (1.4–2.1) (3.1–4.6) 2.1 (1.7–2.6)

<0.01 (<0.01–<0.01) <0.1 (<0.1–0.12) <0.01 (<0.01–<0.01) <0.1 (0–0.12)

0.12 (0.092–0.15) 0.1 (0.077–0.13) 0.3 0.56 0.77 0.85 0.85 0.85 0.85 (0.19–0.44) (0.46–0.68) (0.63–0.93) (0.70–1.0) (0.70–1.0) (0.70–1.0) (0.70–1.0)

0.4 (0.34–0.56) 0.4 (0.28–0.46) 4.8 8.9 10 10 8.9 8.6 8.3 (2.9–7.0) (7.3–11) (8.6–13) (8.2–12) (7.3–11) (7.1–10) (6.9–9.9)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

211

eastern mediterranean region

0.011 0.012 0.012 0.082 0.43 0.74 0.74 0.6 0.57 0.54 <0.01 0.029 0.1 0.18 0.14 0.14 0.13 0.011 0.051 0.15 0.21 0.26 0.28 0.29 0 0 0 0 <0.01 0 0

(<0.01–0.022) (<0.01–0.023) (<0.01–0.025) (0.052–0.12) (0.35–0.52) (0.63–0.86) (0.61–0.89) (0.49–0.71) (0.47–0.68) (0.45–0.64) (<0.01–0.012) (0.024–0.034) (0.085–0.12) (0.15–0.21) (0.12–0.17) (0.12–0.16) (0.11–0.16) (<0.01–0.014) (0.037–0.067) (0.11–0.20) (0.15–0.27) (0.19–0.34) (0.20–0.37) (0.21–0.39) (0–0) (0–0) (0–0) (0–0) (0–0.010) (0–0) (0–0)

0.8 0.9 0.9 14 65 102 96 72 68 63 <0.1 <0.1 0.2 0.3 0.2 0.2 0.2 <0.1 <0.1 0.2 0.3 0.4 0.4 0.4 0 0 0 0 <0.1 0 0

(0.28–1.7) (0.33–1.8) (0.25–1.9) (8.9–20) (53–78) (87–118) (78–115) (59–85) (56–80) (52–75) (<0.1–<0.1) (<0.1–<0.1) (0.13–0.18) (0.21–0.29) (0.16–0.21) (0.15–0.20) (0.14–0.19) (<0.1–<0.1) (<0.1–0.11) (0.16–0.30) (0.21–0.39) (0.25–0.46) (0.27–0.49) (0.28–0.51) (0–0) (0–0) (0–0) (0–0) (0–<0.1) (0–0) (0–0)

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSE NUMBER RATEa

b

CASE DETECTION PERCENT

South Sudan Sudan

Syrian Arab Republic

Tunisia

United Arab Emirates

West Bank and Gaza Strip

Yemen

2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

10 11 26 30 34 40 46 36 37 12 14 16 18 22 22 22 8 9 10 10 11 11 11 2 2 3 4 8 9 9 2 3 3 4 4 4 4 12 15 18 20 23 23 24

15 16 44 47 50 53 54 42 42 7.5 6.6 5.7 4.8 4.3 4.1 3.9 2.3 2.7 2.4 2.4 3 3.2 3.4 0.22 0.28 0.36 0.21 0.26 0.21 0.16 0.12 0.22 0.33 0.23 0.21 0.26 0.32 16 21 20 16 11 11 12

(13–18) (13–19) (36–52) (39–56) (41–59) (43–63) (45–65) (35–51) (35–51) (5.3–10) (5.4–7.9) (4.9–6.6) (4.0–5.6) (3.5–5.1) (3.4–4.9) (3.2–4.6) (2.0–2.6) (2.4–3.1) (2.1–2.7) (2.1–2.7) (2.6–3.4) (2.8–3.6) (3.0–3.8) (0.160–0.280) (0.200–0.370) (0.260–0.480) (0.150–0.270) (0.190–0.340) (0.150–0.270) (0.120–0.210) (0.110–0.140) (0.200–0.250) (0.290–0.370) (0.200–0.260) (0.190–0.240) (0.230–0.290) (0.280–0.360) (10–24) (17–25) (17–24) (13–19) (9.2–13) (9.4–14) (9.6–14)

146 146 170 158 144 133 119 117 114 61 46 35 26 20 19 18 29 31 25 23 28 30 31 12 12 12 5 3.1 2.3 1.7 6 8.6 10 6.5 5.3 6.3 7.6 137 137 116 81 49 49 49

(121–174) (121–174) (140–203) (130–188) (119–172) (110–158) (98–142) (96–139) (94–136) (43–82) (38–55) (30–40) (22–31) (16–24) (16–22) (15–21) (25–32) (27–35) (22–28) (21–27) (25–32) (26–34) (27–35) (8.7–16) (8.7–16) (8.7–16) (3.6–6.5) (2.3–4.1) (1.7–3.0) (1.2–2.3) (5.2–6.8) (7.5–9.7) (9.0–12) (5.7–7.3) (4.6–6.0) (5.5–7.1) (6.7–8.6) (85–202) (112–165) (94–139) (66–97) (40–58) (40–58) (40–58)

0.4 1.5 3.5 5.2 5.6 4.4 4.3

(0.33–0.48) (1.2–1.8) (2.9–4.2) (4.3–6.2) (4.6–6.7) (3.6–5.3) (3.5–5.1)

1.6 5 10 13 12 12 12

(1.3–1.9) (4.1–6.0) (8.5–12) (11–16) (10–15) (10–14) (9.5–14)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

0 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1

(0–0) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1)

7 217 8 403 212 14 320 24 807 27 562 26 131 19 348 18 775 6 018 4 404 5 090 4 310 3 666 3 620 3 003 2 054 2 383 2 038 2 079 2 368 3 015 3 239 285 115 103 131 103 79 64 77 82 28 31 32 32 4 650 14 428 13 651 9 063 8 916 8 636 9 867

70 78 0.82 48 72 70 57 53 50 48 31 31 24 17 17 14 25 27 21 21 22 28 30 16 3.8 2.5 1.6 1.2 0.86 3.1 3 2.6 0.79 0.77 0.78 0.76 39 96 78 45 39 37 41

48 53 0.48 30 50 52 48 46 44 80 67 89 90 86 88 77 89 87 86 88 79 94 96 130 32 50 50 50 50 51 35 25 12 15 12 10 29 70 67 56 80 76 85

(40–58) (45–64) (0.41–0.59) (25–37) (42–61) (44–64) (40–58) (38–55) (37–54) (59–110) (56–82) (77–100) (77–110) (72–100) (74–110) (65–93) (78–100) (77–99) (76–98) (78–100) (70–90) (83–110) (84–110) (100–180) (24–44) (38–69) (38–69) (38–69) (38–69) (45–59) (30–39) (22–28) (11–14) (13–17) (11–14) (8.8–11) (20–47) (58–86) (56–83) (46–68) (67–97) (64–92) (71–100)

0.012 (<0.01–0.030) 0.2 (<0.1–0.35) <0.01 (<0.01–0.021) <0.1 (<0.1–0.23)

<0.01 0.031 0.11 0.18 0.15 0.15 0.16

(<0.01–<0.01) <0.1 (<0.1–<0.1) (0.022–0.042) 0.2 (0.14–0.28) (0.074–0.14) 0.6 (0.42–0.81) (0.12–0.25) 0.9 (0.58–1.3) (0.093–0.21) 0.7 (0.41–0.93) (0.096–0.22) 0.7 (0.41–0.94) (0.098–0.23) 0.7 (0.41–0.95)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

212

NOTI IED NEW AND RELAPSE i c udes REPORT ases fo whic the e tm GLOBAL TUBERCULOSIS 2013

story is unkn wn

Data for all years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN – – 55 62 65 69 64 – 55 59 58 61 65 68 – – 73 60 69 70 68 – 31 63 67 80 81 82 – 45 67 72 72 74 71 11 19 50 52 57 55 54 – 47 56 53 63 56 54 – 81 67 66 70 61 70 – 27 58 64 66 65 65 – – 88 64 – 71 63 – 78 81 86 85 84 83 – 69 82 78 84 85 84 – 40 37 41 50 50 50 – 31 35 57 69 62 35 – – 69 76 77 78 79

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Afghanistan YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSE b

4 332 7 107 21 844 28 029 27 983 29 381 117 43 207 280 246 225 225 2 100 3 971 3 109 4 172 3 686 3 474 2 142 11 145 10 762 11 446 9 260 8 974 8 453 9 255 15 936 11 850 9 212 10 362 10 980 11 042 14 735 9 697 9 697 9 454 9 707 8 837 8 664 439 498 306 367 338 328 331 277 336 513 517 957 672 737 983 571 391 513 496 630 442 1 440 1 341 2 098 1 518 1 549 27 658 29 829 28 852 26 269 28 359 28 640 28 635 482 276 321 261 308 337 382 156 759 13 142 11 050 142 017 264 235 264 934 267 475 184 304 279 325 580 553 728 2 415 3 452 3 539 4 465 3 932 3 690 2 892 9 949 12 947 13 789 13 319 17 23 101 90 89 101 2 358 6 085 7 085 6 155 7 405 14 16 72 58 47 47 1 620 4 954 6 248 6 286 6 906 85 8 107 98 89 77 237 856 1 116 1 130 1 049 0 0 0 0 0 0 0 0 0 0 0 0 0 237 856 1 325 1 314 1 246 0 0 0 0 0 0 0 0 0

• 37 Bahrain

99 •

633 623 702

209 184 197

• 24 Djibouti

17 •

• 356 Egypt

404 •

1 391 1 120 1 181 1 336 1 170 4 229 4 606 5 217 4 679 4 508 4 295 5 347 5 361 4 581 5 188 5 539 5 409 1 587 3 194 3 194 3 096 3 618 3 059 2 760 187 89 86 117 103 85 175 180 187 385 222 328 197 202 131 194 188 240

518 739 538 569 547 9 204 2 693 2 617 1 158 1 055 937 6 432 2 642 1 807 1 985 1 980 2 191 12 394 13 962 3 188 2 887 2 693 2 463 2 315 210 69 76 69 81 73 42 89 95 163 141 140 528 149 75 99 101 131 626 82 474 305 372 4 095 2 934 2 142 2 174 2 272 2 343 60 37 37 28 32 39 3 806 5 578 68 337 105 623 103 824 109 425 135 98 73 101 120 331

1 875 1 058 2 253 1 587 1 567 4 684 2 843 3 163 3 048 3 074 2 915 3 779 3 442 2 530 2 869 3 076 3 105 754 1 367 2 753 2 703 3 009 2 957 3 261 101 145 187 150 128 172 115 244 234 407 309 269 255 214 181 210 206 250 814 652 762 462 533 11 563 13 046 11 370 12 730 13 331 13 522 81 112 89 124 122 131 3 037 1 846 22 789 45 443 45 537 41 410 109 128 156 256 236 217

0 0 0

184 192 200 194 190 753 620 449 375 337 306 477 405 274 320 385 337 68 562 768 387 358 328 6 3 6 2 2 1 4 0 1 2 0 0 3 6 4 10 1 9

61 19 37 72

184 253 219 231 262 753 620 738 703 670 606 477 405 428 760 900 778 68 562 768 777 769 763 6 3 10 18 18 19 4 0 1 2 0 0 3 6 4 12 1 9

0 0 0

•4 Iran (Islamic Republic of)

10 •

• 16 Iraq

14 •

0 0 0

154 440 515 441

20 0 0 0

• 84 Jordan

26 •

0 0 0

390 411 435

0 0 0

• 13 Kuwait

5•

12 0 0 0 0 0 0 0 0 0

4 16 16 18 0 0 0 0 0 0

0 0 14 0 0 0 0 0 0 0

• 13 Lebanon

23 •

0 0 0

0 2 0

0 0 0

•0 Libyan Arab Jamahiriya

14 •

607 860 731 644 14 171 12 872 12 757 12 239 11 822 11 572 135 164 131 152 180 205 2 578 3 285 48 220 104 263 105 733 110 545 60 53 96 223 197 180

2 0 0 20

269 27

271 47

• 10 Morocco

25 •

• 112 Oman

88 •

0 0 0 0

1 216 1 215 1 198 0 8 4 4 3 7 184 341 2 671 5 870 5 947 6 095 1 0 0 0 0

429 1 130 764

1 645 2 345 1 962 0 8 4 9 3 8 184 341 5 425 10 925 11 407 11 717 1 0 0 0 0

0 0 0

• 27 Pakistan

12 •

0 0 0

5 0 1

0 0 0

• 141 Qatar

149 •

0 0 0

2 754 5 055 5 460 5 622

3 036 3 893 0

• 39 Saudi Arabia

36 •

0 0 0

0 0 0

0 0

• 15

13 •

1 595 1 722 2 302 2 055 2 028

722 545 687 586 549

1 023 1 067 1 311 1 227 1 022

0 0

112 205 122 64 91

84 83 143

112 205 206 147 234

43

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

213

eastern mediterranean region

0 0 0 0

289 328 333 300

0 0 0 0

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE RELAPSE RETREAT UNKNOWN NEW PULM POSITIVE UNKNOWN PULMONARY 1 572 3 776 7 068 5 225 5 884 6 127 2 797 3 120 8 761 12 311 12 730 9 958 7 266 6 587 1 295 1 584 1 350 1 122 1 027 809 1 243 1 099 915 1 091 1 031 1 059 692 837 3 168 2 654 3 159 3 188 2 610 3 413 2 655 6 512 9 212 9 144 6 746 6 948 1 507 1 409 796 544 393 364 407 179 239 151 317 282 318 722 2 258 1 885 2 261 2 271 1 639 1 685 1 675 3 843 5 434 6 217 4 624 4 561 1 574 2 000 2 103 1 948 1 915 1 702 733 727 874 1 090 1 616 1 853 134 351 410 375 349 389 171 185 474 2 141 186 812 712 679 28 97 61 52 60 44 134 351 512 705 717 699 537 706 474 2 141 1 802 1 922 1 749 1 735 28 97 144 213 115 76 – 69 82 69 66 65 66 52 48 – 77 65 58 52 52 49 – 46 53 63 67 72 69 – 75 86 79 88 76 79 – – 96 84 67 63 74 – 13 100 54 68 69 74 – 33 57 55 61 57 54

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Somalia YEAR 1990 1995 2000 2005 2010 2011 2012 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSEb 2 504 5 686 12 904 10 139 11 653 11 975 7 217 8 403 212 14 320 24 807 27 562 26 131 19 348 18 775 6 018 4 404 5 090 4 310 3 666 3 620 3 003 2 054 2 383 2 038 2 079 2 368 3 015 3 239 285 115 103 131 103 79 64 77 82 28 31 32 32 4 650 14 428 13 651 9 063 8 916 8 636 9 867

•0 South Sudan Sudan

117 •

0 0 0 0

102 330 368 310 366 521

0 0 0 0 0

0 0 0

•1 Syrian Arab Republic

50 •

1 616 1 110 1 037 1 056

0 0

• 48 Tunisia

14 •

0 0 0 0

83 161 55 32

0 225 84

• 25 United Arab Emirates

30 •

0

61 51 36 51 45

19

61 51 36 51 64

0

• 16 West Bank and Gaza Strip

1•

73 62 56 46 42 9 37 7 13 11 17 3 681 5 565 3 379 3 584 3 135 3 321

3 12 28 27 15 58 6 6 5 6 7 390 4 176 2 780 2 313 2 400 2 808

41 25 47 30 20 10 15 12 13 8 3 082 3 470 2 553 2 715 2 880 3 486

0 0 0 0

0 4 0 0 2

2 1 3 6

0 6 1 3 8

0 0 0 0

•3 Yemen

1•

0 0 0

0 3 1 275 440 351 304 221 252

0 0 0

0 3 1 275 440 351 438 298 335

0 0 0

• 39

41 •

0 0 0

134 77 83

0 0

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

214

NEW AND RE TUBERCULOSIS APSE nc ud ca es for w REPORT ch the eatm nt h st ry GLOBAL 2013

nown.

Data for all years can be downloaded from www.who.int/tb/data

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Afghanistan

•0 Bahrain

91 •

•0 Djibouti

34 •

• 75 Egypt

82 •

• 62 Iran (Islamic Republic of)

88 •

•0 Iraq

85 •

• 80 Jordan

89 •

• 92 Kuwait

92 •

• 71 Lebanon

93 •

• 91 Libyan Arab Jamahiriya

80 •

• 65 Morocco

59 •

• 90 Oman

80 •

• 84 Pakistan

97 •

• 70 Qatar

92 •

• 81 Saudi Arabia

49 •

•0 Somalia

61 •

• 86 South Sudan Sudan

86 •

• 79

70 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2010 2011 1995 2000 2005 2009 2010 2011

2 892 9 949 12 497 12 947 13 789 17 23 101 131 90 89 1 391 1 120 1 377 1 181 1 336 4 229 4 606 5 217 5 201 4 679 4 508 5 347 5 361 4 581 5 152 5 188 5 539 3 194 3 194 3 096 3 347 3 618 3 059 187 89 86 109 117 103 175 180 187 386 385 222 197 202 131 179 194 188 607 860 936 731 14 171 12 872 12 757 11 907 12 239 11 822 135 164 131 164 152 180 2 578 3 285 48 220 101 887 104 263 105 733 60 53 96 220 223 197 1 595 1 722 2 201 2 302 2 055 1 572 3 776 7 068 6 047 5 225 5 884 2 797 8 761 12 311 12 730 10 541 9 958 7 266

3 136 10 013 12 497 12 947 13 789 22 15 192 162 124 1 751 1 391 1 120 1 277 1 177 1 334 2 118 4 611 5 154 5 201 4 682 4 508 5 866 4 581 5 201 5 269 5 532 11 553 3 194 3 096 3 347 3 618 3 059 193 89 86 109 117 103 175 180 187 386 385 222 200 190 131 179 192 188 626 860 792 731 14 171 12 872 12 683 11 935 12 492 11 822 93 112 104 334 152 212 802 4 074 48 205 101 809 104 434 105 733 43 53 96 5 219 294 1 285 1 722 2 201 2 302 2 055 1 278 3 776 7 059 6 047 5 225 5 884 2 114 2 767 8 326 14 599 12 730 10 883 7 729 7 266

– 108 101 100 100 100 – 96 15 147 180 139 – 100 100 93 100 100 50 100 99 100 100 100 – 109 100 101 102 100 362 100 100 100 100 100 103 100 100 100 100 100 100 100 100 100 100 100 102 94 100 100 99 100 – – 100 – – 100 100 100 99 100 102 100 69 68 79 204 100 118 31 124 100 100 100 100 72 100 100 2 98 149 – 81 100 100 100 100 81 100 100 100 100 100 – 99 95 119 100 103 78 100

76 83 83 86 88 73 93 98 96 34 60 48 71 72 68 65 38 75 66 72 59 66 81 78 77 77 79 60 86 76 80 80 83 91 89 71 54 57 46 40 54 53 41 63 84 35 89 81 65 68 65 65 40 43 42 75 82 76 77 77 73 84 93 90 49 97 95 51 58 71 74 75 75 81 66 74 80 63 46 62 60 54 52 53 82 81 85 83 87 84 67 62 44 50 64 62 56 47

9 7 4 3 4 0 0 0 0 0 16 14 9 7 12 17 24 12 13 16 27 21 4 5 6 6 6 20 5 10 10 9 6 1 1 12 21 30 47 31 15 10 44 24 9 56 3 11 17 12 15 0 29 21 17 14 7 5 8 8 7 0 0 49 0 2 20 16 13 17 16 16 0 0 9 0 3 2 11 5 11 10 9 4 2 4 2 2 2 8 11 35 25 18 19 24 23

3 2 2 2 2 27 7 2 4 1 3 2 1 1 1 1 2 3 3 3 3 3 6 7 7 7 8 0 3 3 2 3 3 3 2 5 6 1 3 3 1 1 0 0 0 0 4 2 6 2 2 1 2 2 1 2 3 2 2 2 2 9 4 10 2 3 3 4 4 3 2 2 2 5 8 1 0 0 0 7 7 6 5 6 4 4 4 4 3 4 5 4 2 4 3 3 2 2

3 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 3 2 2 2 3 2 2 3 3 4 4 5 2 2 1 1 2 1 1 7 7 3 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 1 1 1 2 1 1 1 3 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 1 1 1 1 5 2 1 2 2 2 1 1 7 2 1 1 1 1

6 2 2 2 2 0 0 0 0 0 20 21 16 17 16 13 19 5 3 4 4 3 3 3 2 3 3 10 3 7 6 6 5 2 4 6 11 6 5 1 9 7 4 3 3 10 3 6 2 18 2 33 27 31 37 7 7 9 9 9 8 1 0 0 0 0 20 17 9 4 4 4 0 0 0 20 0 32 13 10 10 14 16 5 3 4 3 3 3 15 18 11 9 9 10 12 13

2 5 9 5 5 0 0 0 0 65 1 14 2 3 2 3 14 3 13 3 4 5 3 4 5 3 1 5 1 3 1 1 1 3 2 0 0 3 0 25 21 29 11 9 4 0 1 0 10 0 16 0 2 3 3 1 1 7 2 2 9 5 0 0 0 0 0 4 4 4 2 2 2 14 26 16 0 33 19 6 17 18 18 17 0 9 2 7 4 6 3 4 1 11 5 6 5 14

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

215

eastern mediterranean region

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Syrian Arab Repub ic

• 61 Tunisia

84 •

•0 United Arab Emirates

87 •

•0 West Bank and Gaza Strip

73 •

• 100 Yemen

100 •

• 52

88 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

1 295 1 584 1 350 1 143 1 122 1 027 1 243 1 099 915 931 1 091 1 031 73 62 71 56 46 9 37 7 10 13 11 3 681 5 565 3 379 3 576 3 584 3 135

1 295 1 562 1 350 1 144 1 122 1 009 1 099 910 931 1 091 1 026 73 62 71 55 60 13 12 11 12 11 3 681 5 565 3 566 3 557 3 584 3 174

100 99 100 100 100 98 – 100 99 100 100 100 – 100 100 100 98 130 144 – 171 110 92 100 100 100 106 99 100 101

45 69 76 76 75 65 87 83 72 62 63 56 42 21 24 2 100 58 18 8 18 43 59 69 79 77 79

16 10 13 12 14 19 4 7 11 24 24 18 31 52 45 72

2 4 3 4 3 3 3 2 3 3 3 7 6 11 7 3

9 3 2 1 2 2 2 1 2 1 1 4 0 1 0 0

24 11 6 4 4 10 2 2 3 4 5 5 15 14 24 23

5 4 1 3 2 1 2 4 9 6 5 10 6 0 0 0 0 0 0 0 0 11 10 10 4 7 3

42 64 75 82 9 13 11 9 9 9

0 9 0 0 1 3 3 3 3 2

0 0 17 0 1 1 1 1 1 1

0 9 0 0 35 14 6 4 4 5

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

216

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Afghanistan

•0 Bahrain

77 •

•0 Djibouti

0•

•0 Egypt

63 •

•0 Iran (Islamic Republic of)

72 •

•0 Iraq

72 •

•0 Jordan

75 •

•0 Kuwait

80 •

•0 Lebanon

0•

•0 Libyan Arab Jamahiriya

100 •

•0 Morocco

0•

• 76 Oman

66 •

•0 Pakistan

67 •

• 70 Qatar

80 •

• 67 Saudi Arabia

0•

•0 Somalia

63 •

•0 South Sudan Sudan

72 •

•0 a

55 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2010 2011 1995 2000 2005 2009 2010 2011

237 856 1 290 1 325 1 314 0 0 0 0 0 184 253 210 219 231 753 620 738 748 703 670 477 405 428 773 760 900 68 562 768 751 777 769 6 3 10 20 18 18 4 0 1 1 2 0 3 6 4 10 12 1

304 856 1 325 1 937

0 0 0 268 253 194 213 227 956 738 748 703 599 606 448 708 781 892

953 751 777 769 6 24 5 15

1 1 2 0 5 4 10 12 1

271 23 85 47 1 469 1 650 1 668 2 899 2 623 7 7 9 3 374 907 5 009 8 801 8 394 11 407 3

1 605 1 645 2 345 0 8 4 7 9 3 184 341 5 425 9 200 10 925 11 407 1 0 0 0 0

0 0 0 139 96 151 249 147 351 524 655 705 717 434 527

112 205 144 206 147 134 351 512 655 705 717 537 474 2 141 1 802 1 993 1 922 1 749

1 828 2 147 1 517 1 749

– 128 100 – 100 147 – – – – – – – 146 100 92 97 98 – 154 100 100 100 89 – 150 105 92 103 99 – – 124 100 100 100 – 200 – 120 28 83 – – 100 100 100 – – 83 100 100 100 100 – – – – – – – – – 104 176 112 – 88 – 100 100 100 203 266 92 96 77 100 300 – – – – – – 124 47 105 121 100 – 100 102 100 100 100 – 98 – – 101 108 79 100

73 87 73 58

5 2 6 19

4 3 3 2

4 1 3 2

11 2 1 2

3 5 14 17

27 58 67 53 47 52 41 39 38 35 63 68 48 49 49

9 10 8 17 16 11 17 39 34 36 13 8 25 20 22

0 3 3 6 4 7 10 6 6 6 6 9 8 8 9

3 2 2 2 5 12 12 5 8 6 5 3 3 5 4

22 24 18 19 22 13 8 7 8 10 6 4 5 4 4

37 2 3 3 6 5 12 4 6 7 7 8 11 15 12

60 57 36 39 83 17 0 13

12 27 40 36 17 62 60 67

4 3 4 5 0 4 0 0

8 3 5 7 0 0 20 0

12 9 13 12 0 17 0 20

4 1 3 1 0 0 20 0

0 0 0

100 100 100

0 0 0

0 0 0

0 0 0

0 0 0

80 75 60 58

25 20 17 100

0 0 8

0 0 0

0 0 17

20 0 20 0 0

11 65 55 60 40 38 86 57 44 67 48 37 61 63 68 63 67

22 12 17 9 24 28 0 43 56 0 22 17 15 18 16 17 0

2 4 4 4 4 3 0 0 0 33 2 6 5 4 3 4 0

0 4 5 3 3 3 14 0 0 0 5 3 3 3 3 3 0

45 10 14 16 21 21 0 0 0 0 24 29 11 8 6 8 0

20 7 5 8 9 8 0 0 0 0 0 8 5 3 3 4 33

43 40 45 31 41 53 76 50 48 43 23 20

15 9 15 19 22 1 5 10 14 29 34 38

7 9 8 8 9 5 6 6 6 7 5 7

3 5 1 2 3 5 2 4 5 6 9 2

13 18 17 22 10 3 5 3 4 4 23 28

19 19 14 17 15 34 6 27 23 11 5 5

53 33 28 22

29 38 40 33

3 3 2 3

1 1 1 1

9 15 14 13

6 10 16 27

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

217

eastern mediterranean region

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Syrian Arab Republic

•0 Tunisia

70 •

•0 United Arab Emirates

79 •

•0 West Bank and Gaza Strip

33 •

•0 Yemen

0•

• 43

67 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

28 97 144 176 213 115 61 51 42 36 51 0 6 0 1 3

189 144 176 213 225 42

52

5 0 3 3

2 0 3 275 440 351 314 438 298

0 0

14 437 351 291 298

– 195 100 100 100 196 – 69 – – – 102 – – 83 – 300 100 – – – 0 – – 5 99 100 93 – 100

44 53 48 23 20 74

10 14 22 58 49 0

4 5 9 4 5 5

20 9 4 3 5 2

15 19 15 11 20 10

7 0 3 1 1 10

54

25

2

8

10

2

80 0 0

0 67 33

0 33 0

0 0 0

20 0 67

0 0 0

29 64 48 70 62

14 8 9 7 5

21 7 2 3 5

14 6 3 4 3

14 11 7 7 6

7 4 30 9 19

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

218

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 18 23 25 46 65 66 82 7.1 52 19 36 47 37 17 8.4 12 14 66 84 86 23 99 78 51 100 100 100 100 0.77 52 48 67 5 170 6 445 7 275 128 161 148 184 224 2 163 718 1 289 4 483 3 441 1 514 904 1 343 1 574 6 711 7 754 7 821 86 352 267 177 517 957 672 737 3 269 236 424 2 128 1 498 1 549 215 1 856 5 827 257 313 337 383 0 6 283 8 264 10 419 325 0 0 1 3 278 3 469 3 420 0 2 741 4 140 5 359 3 542 4 584 180 7 532 3 082 3 070 345 85 586 1 601 129 156 360 593 84 81 53 0 31 32 32 0 0 0 612 PATIENTS NOTIFIED (NEW AND RETREAT) 21 844 28 238 28 167 29 578 280 246 225 225 3 170 4 191 3 723 3 546 11 735 9 588 9 307 8 753 9 366 10 802 11 495 11 483 9 454 10 097 9 248 9 099 371 354 344 349 517 957 672 737 391 515 496 630 2 367 1 545 1 549 26 269 28 788 29 770 29 399 261 313 337 383 144 771 269 290 270 394 273 097 325 580 553 728 3 539 4 549 4 015 3 833 13 006 10 469 12 021 12 285 7 583 8 924 29 178 27 241 20 385 19 831 4 393 3 827 3 675 3 035 2 079 2 368 3 015 3 258 105 132 106 85 28 31 32 32 9 063 9 050 8 713 9 950 % OF HIVNUMBER OF % OF HIVPOSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT 100 80 100 0 0 0 0 15 0 100 80 100 0 0 43 100 15 11 22 64 100 100 100 28 37 41 0 50 50

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Afghanistan 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS

% OF TESTED TB PATIENTS HIV-POSITIVE

– Bahrain

25 •

• 46 Djibouti

82 •

•7 Egypt

36 •

2 5 5 6 6 7 1 135 248 177 130 7 12 17 254 291 283 1 2 2 0 0 1 0 3 3 0 3 3 7 9 3 212 128 105 17 41 357 10 4 8 14 0 28 34 30 0 0 0 1 77 77 79 21 231 206 192 428 534 150 247 292 231 0 5 7 5 2 7 10 14 4 3 4 0 0 0 0 0 0 0 26

<0.1 <0.1 <0.1 4.7 3.7 4.7 0.54 60 11 25 10 0.16 0.35 1.1 28 22 18 <0.1 <0.1 <0.1 0 0 0.37 0 0.58 0.31 0 0.41 100 2.6 3.8 0.71 10 8.5 6.8 7.9 2.2 6.1 3.9 1.3 2.4 3.7 0.45 0.41 0.29 0

25

0

0 0

– Iran (Islamic Republic of) – Iraq

17 •

100 100 100 16 20 27 100 100 50

161 155 0

14 •

– Jordan

86 •

0 100 100 100 100 0 100 100 100 1.4 0 100 100 100 100 100 100 100 68 9

• 23 Kuwait

51 •

• 100 Lebanon

100 •

•1 Libyan Arab Jamahiriya – Morocco

67 •

100 •

97 100 0.75 6.2 20 98 100 100 100 0 2.3 3.1 3.8 100 0 0 0.14 72 86 89 0 26 34 44 47 51 0.62 28 15 15 7.9 2.2 16 53 6.2 6.6 12 18 64 76 62 0 100 100 100 0 0 0 6.2

– Oman

20 •

• 98 Pakistan

100 •

100 100 100 100 100 88 100 39 100 100

100 68 100 100 100 88 100 43 56 73

0

•0 Qatar

4•

• 100 Saudi Arabia

0•

100 2.3 2.2 2.3 8.4 5 3.6 12 12 83 3.3 9.5 7.5 0 5.9 1.2 0.31 1.6 4.5 2.8 2.4 4.8 3.7 7.5 0 0 0

100

100

14 38 68 85 79 82 62 10 160 0 0 100 100 100 100 100 100 100 100 100 0 26 20 27 27 28 10 100 25 17 0 100 100 100 100 100 100 100 100

– Somalia

89 •

0

•0 South Sudan Sudan

44 •

•1 Syrian Arab Republic •8 Tunisia

15 •

0

53 •

•6 United Arab Emirates – West Bank and Gaza Strip •0 Yemen

18 •

24 38 54

62 •

100 •

•0

6•

4.2

62

0 0 0

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

219

eastern mediterranean region

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 238 1 100 (0–2 900) 750 (21–2 600) 2 162 154 160 0 b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB – 1.8 – – 2.0 70 99 110 0 – – – – – 0.70 0.59 4.5 4.7 13 6.8 – 0 – 2.5 97 63 30 91 280 100 100 – 37 2.1 9.6 4.2 0.47 – – – 1.4 0.38 0.50 0.85 95 59 100 100 – <0.1 – 0.42 190 100 1.6 2.0 – – – – – 9.3 4.4 0 – – – – 0.29 0.65 0 1.7 12 13 – 0.55 0.19 0.28 – – 5.0 52 – 0 0 0 – 1.5 – 5.5 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

Afghanistan

Bahrain

Djibouti

Egypt

Iran (Islamic Republic of)

Iraq

Jordan

Kuwait

Lebanon

Libyan Arab Jamahiriya

Morocco

Oman

Pakistan

Qatar

Saudi Arabia

Somalia

South Sudan Sudan

Syrian Arab Republic

Tunisia

United Arab Emirates

West Bank and Gaza Strip

Yemen

2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

19 19 31 4 0 9 4 39 0 96

400 (93–700)

2.8 (0.57–8.0)

2.8 (0.57–8.0)

0 (0–0)

81 (40–120)

31 (1.7–58)

50 (19–81)

134 116 27 58 43 50 110 84 62 19 10 4 13 6 5 0 4 3 7 3 6 8 1

330 (270–390)

180 (99–260)

750 (590–910)

380 (260–530)

39 31 205 271 717 411 0

150 (130–180)

380 (270–480)

420 (0–870)

180 (5.1–610)

15 (5.4–25)

10 (3.7–21)

69 98 74 55 77 516 437 282 48 4 18 10 4

240 (57–430)

5.4 (0.70–13)

0 (0–6.1)

0 (0–6.1)

0 (0–0)

9.9 (3.5–16)

3.9 (0.47–14)

6.0 (2.0–8.6)

36 (1.0–120) 180 54 45 80 5 1 4 6 444 344 1602 2 4 4 2 14 22 20 57 20 0 6 3 45 49 62 116 7 25 24 13 12 12 15 4 0 1 2 0 0 0 1 4 8

36 (1.0–120) 180 47 61 103 125 185 219 248 9

–

300 (190–410)

66 (22–150)

240 (150–350)

5.9 (1.2–11)

5.9 (2.2–13)

0 (0–3.0)

11 000 (0–29 000)

7 700 (220–27 000)

6.3 (1.7–16)

6.3 (1.7–16)

461 264 324 9 10

3 700 (880–6 600)

0 (0–0)

84 (64–100)

46 (36–62) 488 261 0

37 (28–48)

770 (600–930) 250 (120–390)

480 (250–720) 120 (6.5–220)

280 (160–410) 140 (52–220)

580 (280–870)

240 (14–460)

97 (65–130)

73 (46–110)

36 43 0 63 408 155 6 2 3

330 (130–540)

24 (16–33)

19 (7.0–30)

11 (0–23)

7.6 (2.9–12)

2.0 (1.5–2.5)

1.0 (0.51–1.5)

3 26 0 0 0 89

0.95 (0.74–1.2)

1.1 (0–3.0)

0.81 (<0.1–2.8)

0.32 (<0.1–0.56)

150 (100–210)

110 (31–180)

183

49 (27–73)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB – 34 2.6 – 38 3.0 0 – 0 – 0 – 1 – 0 0 – – – – – 497 74 438 72 41 9.6 169 22 322 36 207 27 – 185 24 224 29 159 21 33 330 7 39 6 33 6 32 1 100 0 0 0 – – 4 100 14 120 1 100 6 67 – – – – – 403 24 229 9.8 416 21 11 280 8 89 3 100 8 100 – 306 2.8 – 154 1.3 0 – 0 – 0 – – – – – – – 79 11 14 2.0 0 0 8 1.5 – 4 0.22 – 82 4.7 129 7.4 0 0 12 5.6 70 61 23 30 – 6 17 10 20 12 19 – – 0 0 3 38 – 0 – 0 0 0 0 – 34 7.8 – 17 5.1

a

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). b BACT+VE = bacteriologically positive cases.

220

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO – 0.52 0.46 0.49 0.51 0.50 1.7 2.8 1.5 1.7 2.3 2.7 – 2.3 2.0 1.9 1.7 1.9 1.9 2.1 1.7 2.0 1.9 1.9 0.90 0.94 1.1 0.94 1.0 1.1 1.3 1.6 1.6 1.3 1.2 1.1 2.1 2.3 1.3 1.1 1.3 1.2 2.4 2.2 1.9 1.1 1.7 1.1 2.1 1.3 1.4 0.69 0.66 0.56 3.7 3.1 3.9 – 2.2 2.8 1.9 1.8 2.1 2.5 2.4 2.4 1.1 1.2 2.7 1.5 1.2 1.2 0.71 0.99 1.0 1.0 1.1 1.1 6.5 5.6 3.8 7.3 4.8 8.0 – 1.5 1.4 1.8 1.7 1.7 3.6 2.1 1.7 1.9 2.0 1.8 1.7 2.1 1.2 1.4 1.5 1.7 1.9 1.8

Afghanistan

Bahrain

Djibouti

Egypt

0 0 0

0 0 0

Iraq

0

0

Jordan

0 0 0

0 0 0

Kuwait

0 0 0

0 0 0

Lebanon

0

0

Libyan Arab Jamahiriya

Morocco

Oman

Pakistan

Qatar

5 2 142 99 79 51 79 54 1 1 1 2 1 0 29 55 621 1 548 1 216 1 317 0 0 0 0 0 0 8 14 4 13 46 113 125 109 113 129 39 42 250 785 425 209 107 117

85 86 2 508 2 061 2 222 1 982 1 929 1 840 7 8 21 12 17 18 274 498 5 278 11 860 12 143 12 605 8 7 19 59 36 34 131 182 335 227 228 334 740 1 343 1 036 1 147 1 147 251 356 604 1 028 1 358 1 185 899 869

173 136 2 872 2 423 2 515 2 553 2 450 2 426 12 9 11 27 25 33 230 387 4 759 10 462 10 515 10 838 12 19 15 72 64 52 268 276 458 406 394 730 724 1 114 886 1 047 1 014 599 753 796 1 511 1 990 1 781 1 359 1 274

148 136 1 737 1 705 1 583 1 611 1 479 1 423 7 11 24 15 12 23 178 256 4 263 8 320 8 435 8 848 11 9 17 38 36 45 213 201 242 225 214 201 408 725 496 587 560 402 462 634 1 351 1 541 1 335 981 802

54 63 819 855 1 057 1 273 1 175 1 183 7 12 15 16 23 12 140 232 3 834 7 969 8 608 9 026 13 7 19 22 14 21 158 175 210 225 210 127 254 458 355 398 449 259 267 486 1 119 1 151 863 689 466

18 31 573 485 580 712 682 672 10 9 19 8 10 8 124 153 3 332 6 934 7 320 7 753 4 2 5 5 10 8 86 70 116 113 133 278 195 330 266 330 296 135 135 362 638 724 497 386 404

21 22 553 595 591 515 518 561 11 11 5 10 11 19 95 130 2 453 6 066 6 323 6 492 4 1 1 0 3 0 107 107 102 106 96 109 142 319 277 277 307 57 87 337 677 493 391 372 331

0 0

0 0 0

0 0 0

0

8 10 191 170 167 117 100 77 2 2 2 3 5 0 85 130 1 447 3 212 2 679 2 630 1 0 0 0 2 28 31 33 35 28 38 85 169 91 114 121 60 58 359 817 381 195 113 115

0 160

59 47 1 708 1 530 1 330 1 098 1 153 1 162 18 17 13 18 20 20 375 591 6 463 14 481 14 652 15 445 2 0 5 7 9 6 172 205 239 200 207 158 354 752 467 495 553 181 212 490 925 1 102 761 512 536

47 37 1 288 1 121 943 841 794 832 13 5 5 22 21 37 381 416 5 611 10 513 10 684 10 902 3 4 10 16 15 9 182 184 271 245 236 139 319 636 444 465 554 318 302 613 1 134 1 203 979 620 562

37 19 703 672 546 426 433 408 5 7 3 6 9 10 267 274 3 987 7 749 7 880 8 263 1 3 2 2 6 1 79 98 105 110 107 97 219 436 341 348 396 239 221 299 905 978 772 513 470

22 24 461 398 403 386 371 306 5 5 4 4 13 10 178 163 2 866 6 410 6 590 6 876 0 1 1 1 1 1 51 73 70 64 50 40 110 292 188 260 267 172 139 403 771 729 520 352 299

25 18 317 406 343 310 324 286 6 11 5 4 7 9 143 103 2 060 4 879 4 977 5 494 0 0 2 1 2 0 50 51 49 49 49 25 72 212 137 168 165 59 62 342 327 411 279 188 170

29 13 299 352 398 364 335 342 3 6 3 5 6 6 79 56 1 338 4 338 3 711 4 056 1 0 0 0 1 1 70 61 58 46 63 16 41 157 132 135 169 26 24 305 323 244 191 175 172

0 0

0 0 0

0 0 0

0

0 20

Saudi Arabia

0 0 0

0 0 0

Somalia

South Sudan Sudan

0 0 0 0

0 0 0 0

0 0

0 0

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

221

eastern mediterranean region

Iran (Islamic Republic of)

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 2011 2012 1995 2000 2005 2010 2011 2012

52 151 197 204 188 0 0 0 0 1 0 17 18 28 35 22 223 21 25 9 23 23 118 29 16 18 13 16 1 125 21 13 42 35 27 0 0 0 2 0 0 0 0 0 1 0 0 3 5 0 1 1 2 2 5 2

228 606 986 1 010 1 116 0 0 0 10 5 9 302 220 211 212 208 542 641 524 358 382 373 751 438 352 292 289 288 862 627 424 370 304 283 19 8 8 5 9 8 15 10 12 16 13 14 26 16 12 8 14 18 112 101 114

183 560 819 895 801 1 3 0 16 19 28 347 252 243 265 240 665 827 606 617 611 597 754 467 531 487 543 601 1 409 317 644 482 395 317 37 16 17 14 10 12 51 44 45 67 41 59 32 28 19 21 18 21 212 239 293

149 472 491 613 586 2 2 2 11 13 16 139 119 151 149 147 460 667 421 783 596 582 636 387 338 354 398 442 1 085 297 261 384 313 263 17 13 9 10 13 8 32 32 29 50 36 49 30 20 15 15 13 13 78 86 168

129 453 490 570 521 3 5 3 12 14 11 67 62 67 97 81 408 476 414 725 715 698 494 295 281 296 315 303 863 205 245 276 237 203 20 9 4 12 8 5 17 21 26 48 35 35 16 15 10 12 15 14 46 36 52

94 470 641 700 585 1 3 0 4 8 8 60 47 49 45 47 463 307 243 407 387 379 737 344 260 310 351 317 900 135 189 286 223 203 26 14 6 12 13 7 9 11 8 10 11 15 16 17 12 12 6 12 22 29 19

80 419 622 692 651 3 4 4 4 2 2 42 29 20 33 26 160 158 123 217 168 164 921 642 630 760 877 850 271 101 148 228 183 180 11 2 5 6 5 7 0 5 3 11 5 3 10 14 8 10 8 6 21 32 35

0 0

0 0 0

93 320 445 465 400 0 0 1 0 0 1 12 23 20 31 20 134 55 48 8 7 8 234 77 45 54 37 43 725 37 44 73 66 36 1 0 1 3 0 1 0 1 0 4 0 3 1 4 1 0 0 2 5 6 8

414 1 651 2 107 2 167 2 280 1 1 1 8 9 2 147 123 104 139 132 288 457 431 199 192 187 1 039 593 394 433 473 434 304 338 305 394 368 340 15 8 6 14 8 9 8 11 13 41 23 40 16 31 25 36 37 48 34 43 36

565 1 959 2 263 2 325 2 204 1 2 0 15 5 11 156 117 120 118 94 367 343 298 352 355 346 890 410 205 288 313 318 1 208 241 260 294 258 225 4 9 6 24 11 12 24 24 31 78 30 73 18 26 14 48 51 72 31 35 36

339 1 302 1 455 1 564 1 482 2 0 3 7 6 8 47 66 89 104 73 274 257 205 423 387 379 664 322 186 208 184 206 915 136 151 198 164 154 10 1 6 4 8 7 9 12 11 30 15 15 13 9 8 17 12 16 19 24 35

205 869 1 112 1 146 1 150 0 1 1 1 6 4 31 23 36 57 36 256 211 218 292 280 274 613 320 260 276 296 252 800 134 197 205 159 186 14 2 5 3 4 1 4 5 3 10 9 12 8 7 3 7 9 9 20 24 21

99 471 831 903 850 1 1 0 1 0 1 17 13 24 30 26 160 112 132 192 198 193 685 407 382 398 441 374 886 103 135 220 201 174 12 2 8 5 8 3 4 3 1 11 2 6 5 4 3 4 1 4 13 16 21

36 246 488 535 505 1 1 0 1 1 0 10 8 19 21 18 75 48 42 97 94 92 788 647 701 1 014 1 009 965 200 87 80 166 153 169 7 5 5 3 6 5 2 1 5 8 2 4 3 6 1 3 3 3 11 22 20

0 0

0 0

0 0

0 0

0 0 0

0 0 0

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO 2.1 2.1 1.8 1.6 1.6 1.7 – 2.9 2.6 2.7 2.4 2.2 – 1.6 – 2.3 0.92 1.1 3.5 – 2.5 2.2 1.8 3.2 0.87 1.0 1.3 1.3 1.1 1.2

Syrian Arab Republic

Tunisia

United Arab Emirates

West Bank and Gaza Strip

Yemen

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

13 8 9 7 8 7 16 5 9 6 10 2 1 0 0 1

332 359 266 170 139 91 139 103 115 110 88 4 7 3 2 2 1 2 0 2 400 789 493 507 406 436

255 289 237 212 195 146 208 172 194 194 191 4 13 7 4 0

111 125 111 101 116 90 156 133 170 118 149 6 7 3 4 0

70 86 112 80 81 85 109 115 125 126 114 5 3 5 5 1 1 1 1 2 201 314 242 231 193 232

59 76 62 65 49 46 65 53 93 108 93 12 4 1 5 0 3 1 0 4 148 255 149 164 143 172

50 55 63 49 45 41 101 81 88 63 88 10 4 3 2 3

0 0

22 23 27 16 20 5 7 7 4 10 7 3

158 195 182 164 113 104 68 66 64 60 51 16 2 6 5 1

97 101 108 105 97 75 59 61 64 60 56 1 4 6 2 0 1 1 1 1 720 627 410 409 375 381

53 53 59 47 56 35 43 39 39 50 46 3 1 3 2 0

44 46 59 41 35 33 21 36 34 44 48 0 5 2 3 1 1 1 0 0 200 345 181 174 168 207

37 38 32 38 36 32 21 16 40 35 46 0 1 1 4 0

20 28 23 27 37 19 58 28 52 47 72 4 3 2 4 0

0 0

0 0

0 0

0 0 0

1 4 0 0

0 0 0

0 1 0 57 110 48 68 33 30

0 1 2 605 689 553 569 471 472

2 1 1 256 493 366 322 297 315

3 3 2 45 127 78 138 96 122

0 0 0

0 0

0 0 0 83 161 44 98 85 75

0 0 1 420 799 426 471 446 437

0 1 0 348 517 265 264 251 246

2 2 1 106 247 85 106 113 115

0 0 1 92 92 39 63 58 81

0 0 0

0 0

222

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           LABORATORIES SECONDNUMBER OF SMEAR LABS % OF SMEAR CULTURE DST b LABS LPAc LABS LABS USING LABS PER 5M LINE DST LABS USING PER 100K PER 5M PER 5M a POPULATION POPULATION POPULATION POPULATION XPERT MTB/RIF AVAILABLE LED

FREE THROUGH NTP FIRSTLINE DRUGS

NRLd

TB DIAGNOSIS

TB NOTIF. RIFAMPICIN RATE PER USED 100 000 THROUGHOUT HEALTH-CARE TREATMENT WORKERS

Afghanistan Bahrain Djibouti Egypt Iran (Islamic Republic of) Iraq Jordan Kuwait Lebanon Libya Morocco Oman Pakistan Qatar Saudi Arabia Somalia South Sudan Sudan Syrian Arab Republic Tunisia United Arab Emirates West Bank and Gaza Strip Yemen

2.0 1.4 2.1 0.2 0.5 0.8 0.2 0.4 6.0 0.4 0.5 7.5 0.8 <0.1 0.3 0.6 0.6 0.8 1.4 0.7 1.5 1.0

2 11 0 0 0 0 0 0 0 – 13 0 0 0 1 0 – 0 – 0 – 0 –

0.3 7.6 5.8 1.1 3.6 1.5 0.7 1.5 3.2 6.5 2.2 13.6 0.2 2.4 2.1 0

0 3.8 5.8 <0.1 0.5 0.2 0.7 1.5 1.1 1.6 0.3 1.5 0.1 2.4 2.1 0

0 7.6 5.8 0 0 0 0 0 2.2 0 1.5 <0.1 2.4 0.4 0

1 1 1 0 0 5 1 0 3 0 0 15 1 8 3

Out of country Out of country In country In country In country Out of country No No Out of country No No In country

Yes No Yes Yes Yes Yes Yes Yes Yes

Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (if TB is confirmed) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (if TB is confirmed)

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 30 508 0 1 0 0 0

Yes Yes Yes Yes Yes No Yes No No Out of No country No Yes

8 0

0.1 0.2 5.1 1.2 0.8

0.1 0.2 2.3 0 0.4

0 0.2 0.5 0

0 0 2 0

No Yes In country Yes No No Yes No Yes

204 36

a b

LED = Light emitting diode microscopes DST = Drug susceptibility testing LEDprobe = Ligh assay emittin c LPA = Line D ug y e g d NRL = National Reference Laboratory

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

223

eastern mediterranean region

             New TB cases Year Source Coverage Percentage Year

Previously treated TB cases Source Coverage Percentage

Afghanistan Bahrain Djibouti Egypt Iran (Islamic Republic of) Iraq Jordan Kuwait Lebanon L bya Morocco Oman Pakistan Qatar Saudi Arabia Somalia South Sudan Sudan Syrian Arab Republic Tunisia United Arab Emirates West Bank and Gaza Strip Yemen

2012 2011 1998 2009 2011 2003 2006 2012 2010 2010 2011

Surveillance Survey Survey Surveillance Surveillance Survey Survey Surveillance Surveillance Survey Survey

National National National National National National National National National National National

1.9 (0.39–5.4) 3.4 (1.9–4.9) 5 (3.4–7.0) 6.3 (2.4–13) 0 (0–1.3) 1.1 (0.13–3.8) 0.48 (0.15–1.1) 2.4 (0.89–5.2) 1.2 (0.34–3.1) 1.8 (1.4–2.4) 5.2 (2.7–7.7)

2012 2012 1998 2009 2011 2012 2006 2012 2010 2010 2011

Surveillance Surveillance Survey Surveillance Surveillance Surveillance Survey Surveillance Surveillance Survey Survey

National National National National National National National National National National National

100 (2.5–100) 25 (21–29) 48 (35–62) 29 (3.7–71) 0 (0–98) 67 (22–96) 12 (7.8–18) 0 (0–37) 0 (0–98) 16 (12–21) 41 (23–58)

2003 2012

Survey Survey

National National

6.2 (3.9–9.3) 0.82 (0–1.7)

2011 2012

Surveillance Survey

National National

31 (21–44) 12 (4.5–19)

2011

Survey

National

1.7 (0.50–3.0)

2011

Survey

National

15 (8.1–22)

a

Empty rows indicate an absence of high-quality survey or surveillance data. In the absence of high-quality national data, high-quality sub-national data are used.

224

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

european region Table A4.1 Estimates of the burden of disease caused by TB, 1990–2012 Table A4.2 Incidence, notification and case detection rates, all forms, 1990–2012 Table A4.3 Case notifications, 1990–2012 Table A4.4 Treatment outcomes, new smear-positive cases, 1995–2011 Table A4.5 Treatment outcomes, retreatment cases, 1995–2011 Table A4.6 HIV testing and provision of CPT, ART and IPT, 2005–2012 Table A4.7 Testing for MDR-TB and number of confirmed cases of MDR-TB, 2005–2012 Table A4.8 New smear-positive case notification by age and sex, 1995–2012 Table A4.9 Laboratories, NTP services, drug management and infection control, 2012 Table A4.10 Measured percentage of TB cases with MDR-TB, most recent year available 227 231 235 239 242 245 247 249 252 253

Estimates of mortality, prevalence and incidence Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See ANNEX 1 for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. The main updates implemented in this report are explained in Box 2.1 of Chapter 2. Estimates published in previous global TB control reports should no longer be used.

Data source Data shown in this annex are taken from the WHO global TB database on 1 October 2013. Data shown in the main part of the report were taken from the database in July 2013. As a result, data in this annex may differ slightly from those in the main part of the report. Data for all years can be downloaded from www.who.int/tb/data.

Country notes EU/EEA countries Notification and treatment outcome data for European Union and European Economic Area countries are provisional.

Denmark Data for Denmark exclude Greenland.

France Data from France include data from 5 overseas departments (French Guiana, Guadeloupe, Martinique, Mayotte and Réunion).

Russian Federation The reported number of TB patients with known HIV status in 2010–2012 ( Table A4.6) is for new TB patients in the civilian sector only. It was not possible to calculate the percentage of all TB patients with known HIV status.

226

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATE a

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Albania

Andorra

Armenia

Austria

Azerbaijan

Belarus

Belgium

Bosnia and Herzegovina

Bulgaria

Croatia

Cyprus

Czech Republic

Denmark

Estonia

Finland

France

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

3 3 3 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 4 3 3 3 3 3 3 8 8 8 8 8 8 8 7 8 8 9 9 9 9 10 10 10 10 9 9 9 10 10 10 11 11 11 11 5 4 4 4 4 4 4 9 8 8 8 7 7 7 5 5 4 4 4 4 4 <1 <1 <1 1 1 1 1 10 10 10 10 11 11 11 5 5 5 5 6 6 6 2 1 1 1 1 1 1 5 5 5 5 5 5 5 57 58 59 61 63 64 64

0.11 0.023 0.027 0.018 0.012 0.011 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.16 0.19 0.19 0.26 0.23 0.17 0.19 0.14 0.074 0.069 0.05 0.032 0.04 0.035 0.82 1.8 1.8 0.82 0.39 0.39 0.39 0.5 0.76 0.8 1.1 0.76 0.66 0.57 0.1 0.13 0.081 0.062 0.043 0.041 0.04 0.46 0.22 0.23 0.21 0.2 0.2 0.2 0.22 0.34 0.59 0.26 0.19 0.16 0.15 0.39 0.25 0.19 0.11 0.082 0.066 0.061 <0.01 <0.01 0 <0.01 <0.01 <0.01 <0.01 0.19 0.092 0.12 0.065 0.035 0.051 0.037 0.054 0.024 0.021 0.019 0.035 0.017 0.022 0.071 0.15 0.11 0.049 0.036 0.036 0.036 0.13 0.092 0.083 0.037 0.016 0.021 0.015 1 0.79 0.65 0.43 0.33 0.31 0.3

(0.081–0.130) (0.018–0.028) (0.019–0.037) (0.013–0.025) (<0.01–0.018) (<0.01–0.017) (<0.01–0.016) (<0.01–<0.01) (<0.01–<0.01) (0–<0.01) (0–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–<0.01) (0.110–0.200) (0.160–0.230) (0.170–0.220) (0.190–0.320) (0.180–0.280) (0.130–0.210) (0.150–0.230) (0.140–0.140) (0.074–0.074) (0.069–0.069) (0.050–0.051) (0.032–0.033) (0.040–0.041) (0.035–0.036) (0.610–1.1) (1.3–2.3) (1.4–2.2) (0.660–1.0) (0.330–0.440) (0.340–0.450) (0.340–0.450) (0.470–0.540) (0.700–0.830) (0.760–0.850) (0.990–1.1) (0.700–0.820) (0.600–0.720) (0.510–0.630) (0.097–0.100) (0.130–0.130) (0.080–0.083) (0.062–0.063) (0.043–0.044) (0.041–0.042) (0.039–0.040) (0.440–0.480) (0.210–0.230) (0.210–0.240) (0.200–0.230) (0.180–0.220) (0.170–0.220) (0.180–0.220) (0.210–0.220) (0.340–0.350) (0.570–0.600) (0.260–0.270) (0.190–0.190) (0.160–0.160) (0.150–0.150) (0.380–0.410) (0.240–0.270) (0.180–0.200) (0.110–0.110) (0.082–0.083) (0.066–0.067) (0.060–0.062) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.190–0.190) (0.091–0.092) (0.120–0.120) (0.064–0.065) (0.035–0.035) (0.050–0.051) (0.037–0.037) (0.053–0.056) (0.023–0.025) (0.020–0.021) (0.019–0.020) (0.034–0.036) (0.016–0.018) (0.021–0.023) (0.070–0.072) (0.140–0.150) (0.110–0.110) (0.048–0.050) (0.035–0.036) (0.036–0.037) (0.036–0.036) (0.130–0.130) (0.092–0.092) (0.083–0.084) (0.037–0.037) (0.016–0.016) (0.021–0.021) (0.015–0.015) (0.980–1.0) (0.760–0.810) (0.630–0.670) (0.410–0.440) (0.320–0.350) (0.300–0.330) (0.280–0.310)

3.1 0.68 0.82 0.57 0.38 0.34 0.31 2.4 2.1 1.3 0.86 0.58 0.32 0.91 4.4 6 6.3 8.5 7.7 5.6 6.3 1.8 0.93 0.86 0.61 0.38 0.48 0.42 11 23 22 9.6 4.2 4.2 4.2 4.9 7.5 8.1 11 8 7 6 1 1.3 0.79 0.59 0.4 0.38 0.36 10 6.3 5.9 5.5 5.2 5.1 5.2 2.4 4.1 7.3 3.4 2.6 2.2 2 8.2 5.4 4.2 2.5 1.9 1.5 1.4 0.2 0.2 0 0.37 0.11 0.21 0.2 1.8 0.89 1.2 0.63 0.33 0.48 0.35 1.1 0.47 0.38 0.36 0.63 0.3 0.4 4.5 10 8 3.7 2.7 2.8 2.8 2.5 1.8 1.6 0.71 0.3 0.39 0.29 1.8 1.4 1.1 0.7 0.53 0.5 0.46

(2.3–3.9) (0.55–0.83) (0.57–1.1) (0.39–0.79) (0.23–0.58) (0.20–0.53) (0.16–0.49) (0.16–7.6) (<0.1–8.5) (0–6.2) (0–3.9) (<0.1–2.3) (0.16–0.54) (0–4.9) (3.2–5.8) (4.9–7.2) (5.6–7.0) (6.5–11) (6.1–9.5) (4.5–6.9) (5.1–7.6) (1.8–1.9) (0.92–0.93) (0.86–0.86) (0.61–0.61) (0.38–0.39) (0.47–0.49) (0.41–0.42) (8.5–15) (17–29) (17–27) (7.7–12) (3.7–4.9) (3.7–4.9) (3.7–4.9) (4.6–5.2) (6.9–8.1) (7.6–8.5) (10–12) (7.3–8.6) (6.3–7.7) (5.4–6.7) (0.97–1.0) (1.3–1.3) (0.78–0.81) (0.59–0.60) (0.39–0.40) (0.37–0.38) (0.35–0.36) (9.7–11) (5.9–6.6) (5.5–6.3) (5.0–6.0) (4.6–5.7) (4.6–5.7) (4.6–5.8) (2.4–2.5) (4.0–4.2) (7.2–7.5) (3.4–3.5) (2.5–2.6) (2.2–2.2) (2.0–2.1) (8.0–8.5) (5.0–5.7) (4.0–4.4) (2.5–2.5) (1.9–1.9) (1.5–1.5) (1.4–1.4) (0.16–0.25) (0.16–0.25) (0–0) (0.32–0.41) (0.10–0.13) (0.19–0.23) (0.16–0.25) (1.8–1.8) (0.88–0.89) (1.2–1.2) (0.63–0.63) (0.33–0.34) (0.47–0.48) (0.35–0.35) (1.0–1.1) (0.45–0.48) (0.38–0.39) (0.35–0.36) (0.61–0.66) (0.28–0.32) (0.38–0.42) (4.5–4.6) (9.9–10) (7.9–8.2) (3.6–3.8) (2.7–2.8) (2.8–2.8) (2.8–2.8) (2.5–2.5) (1.8–1.8) (1.6–1.6) (0.71–0.71) (0.30–0.30) (0.39–0.39) (0.28–0.29) (1.7–1.8) (1.3–1.4) (1.1–1.1) (0.68–0.72) (0.51–0.55) (0.47–0.52) (0.44–0.49)

1.2 1.1 0.98 0.87 0.74 0.72 0.68 0.034 0.033 0.021 0.017 0.011 <0.01 0.017 1 1.9 2.9 3.5 2.7 2.3 2.4 2.5 2.5 2 1.5 1 1.1 0.91 54 120 140 66 20 16 12 5.2 11 13 11 10 10 10 2.6 2.2 2.1 1.7 1.7 1.5 1.4 6.5 4.6 2.8 2.3 2.6 2.7 2.8 4.2 8.4 7 6.2 3.9 3.5 3.1 4.4 3.3 2.5 1.6 1.1 0.96 0.84 0.038 0.05 0.045 0.051 0.1 0.069 0.069 3.1 2.8 2.2 1.6 0.99 0.9 0.77 0.61 0.64 1 0.67 0.46 0.58 0.56 0.81 0.93 1.3 0.7 0.37 0.44 0.38 1.3 1.1 0.85 0.55 0.48 0.48 0.39 16 16 11 8.5 8.9 8.7 7.4

(0.440–2.4) (0.420–2.1) (0.380–1.8) (0.370–1.6) (0.320–1.3) (0.310–1.3) (0.280–1.3) (0.013–0.064) (0.015–0.058) (<0.01–0.035) (<0.01–0.029) (<0.01–0.020) (<0.01–0.015) (<0.01–0.028) (0.420–1.8) (0.890–3.3) (1.4–4.8) (1.7–6.0) (1.2–4.8) (1.0–4.2) (1.1–4.1) (1.1–4.5) (1.2–4.4) (0.890–3.5) (0.690–2.7) (0.420–1.9) (0.510–2.0) (0.370–1.7) (25–94) (56–220) (62–240) (31–110) (9.9–34) (7.3–28) (4.1–23) (2.2–9.5) (5.1–19) (6.0–23) (4.4–19) (4.6–18) (4.6–18) (4.7–18) (1.1–4.6) (0.930–3.9) (0.920–3.7) (0.690–3.0) (0.740–2.9) (0.660–2.8) (0.560–2.6) (1.9–14) (2.1–8.1) (0.830–5.9) (0.640–5.0) (1.1–4.7) (1.2–4.8) (1.3–4.8) (1.9–7.5) (4.2–14) (3.3–12) (3.0–11) (1.6–7.1) (1.4–6.4) (1.3–5.8) (2.1–7.7) (1.3–6.1) (1.0–4.7) (0.620–3.0) (0.420–2.0) (0.390–1.8) (0.340–1.6) (0.011–0.080) (0.017–0.100) (0.015–0.091) (0.020–0.095) (0.049–0.180) (0.023–0.140) (0.021–0.150) (1.3–5.6) (1.1–5.3) (0.880–4.1) (0.690–2.8) (0.420–1.8) (0.380–1.6) (0.310–1.4) (0.300–1.0) (0.220–1.3) (0.490–1.7) (0.310–1.2) (0.170–0.880) (0.260–1.0) (0.240–1.0) (0.410–1.3) (0.350–1.8) (0.610–2.3) (0.280–1.3) (0.130–0.740) (0.200–0.780) (0.160–0.680) (0.550–2.3) (0.500–1.9) (0.370–1.5) (0.240–0.980) (0.190–0.900) (0.190–0.900) (0.130–0.790) (7.7–26) (8.5–27) (5.6–19) (4.0–15) (4.6–15) (4.5–14) (3.7–12)

36 32 30 27 24 23 22 62 51 31 21 14 9 21 28 59 93 118 92 79 79 33 32 25 19 12 13 11 744 1 600 1 690 776 221 172 124 51 106 130 109 107 107 108 26 21 20 16 15 14 13 145 131 73 59 67 70 73 48 101 88 81 53 48 43 92 70 57 36 24 22 20 5 5.8 4.8 4.9 9.4 6.2 6.1 30 27 21 15 9.4 8.5 7.2 12 12 19 12 8.3 10 10 52 65 97 53 29 34 29 25 22 16 10 9 8.9 7.2 28 28 19 14 14 14 12

(13–70) (12–61) (12–56) (11–49) (10–43) (9.7–42) (8.9–40) (24–118) (23–91) (15–54) (9.8–36) (6.3–26) (2.7–19) (11–36) (12–52) (28–101) (46–158) (58–198) (42–161) (34–142) (37–137) (15–58) (15–55) (11–43) (8.4–33) (5.0–23) (6.0–23) (4.4–20) (343–1 300) (717–2 820) (768–2 970) (366–1 340) (109–371) (79–302) (44–245) (22–93) (51–182) (60–225) (46–199) (48–189) (49–188) (50–188) (11–46) (9.1–39) (9.0–36) (6.6–29) (6.8–27) (6.0–25) (5.1–24) (43–307) (59–229) (22–154) (17–129) (28–123) (31–124) (35–126) (21–85) (51–169) (42–151) (39–139) (22–97) (20–88) (17–80) (43–160) (28–130) (23–105) (14–69) (9.7–46) (9.1–41) (7.9–36) (1.5–10) (2.0–12) (1.6–9.6) (2.0–9.2) (4.4–16) (2.1–13) (1.8–13) (12–54) (11–51) (8.6–40) (6.7–28) (4.0–17) (3.6–16) (2.9–13) (5.8–20) (4.3–24) (9.1–33) (5.7–21) (3.1–16) (4.6–19) (4.2–18) (26–85) (24–125) (45–168) (21–98) (10–57) (15–60) (13–52) (11–45) (9.8–38) (7.2–30) (4.5–19) (3.6–17) (3.6–17) (2.4–15) (14–47) (15–46) (9.4–31) (6.4–24) (7.3–23) (7.1–22) (5.7–20)

0.84 0.82 0.75 0.63 0.53 0.52 0.51 0.026 0.023 0.014 0.012 <0.01 <0.01 0.01 0.63 1.2 1.9 2.3 1.8 1.6 1.5 1.7 1.7 1.4 1.1 0.76 0.77 0.67 22 49 55 29 12 10 8.9 3.5 6.9 8.4 6.9 6.7 6.6 6.6 1.8 1.6 1.5 1.2 1.2 1.1 1.1 4.2 3 2.4 2 1.9 1.9 1.9 2.9 5.2 4.6 4.1 2.8 2.6 2.3 3 2.4 1.9 1.2 0.79 0.71 0.62 0.033 0.041 0.038 0.039 0.07 0.059 0.061 2.2 2.1 1.6 1.1 0.72 0.65 0.57 0.4 0.52 0.68 0.45 0.36 0.41 0.41 0.49 0.72 0.91 0.55 0.33 0.34 0.3 0.89 0.76 0.61 0.39 0.36 0.36 0.3 11 11 7.7 6.3 6 5.9 5.3

(0.600–1.1) (0.680–0.970) (0.630–0.870) (0.530–0.730) (0.450–0.620) (0.440–0.610) (0.430–0.590) (0.023–0.030) (0.020–0.026) (0.012–0.016) (0.010–0.013) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.012) (0.470–0.810) (1.0–1.4) (1.6–2.1) (2.1–2.6) (1.6–2.2) (1.3–1.9) (1.3–1.8) (1.5–2.0) (1.5–1.9) (1.2–1.5) (0.940–1.2) (0.660–0.860) (0.680–0.870) (0.590–0.760) (18–26) (41–59) (46–66) (24–34) (9.8–14) (8.6–12) (7.3–11) (2.8–4.3) (5.9–8.1) (6.9–9.9) (5.3–8.8) (5.3–8.1) (5.4–8.0) (5.4–8.0) (1.6–2.1) (1.4–1.8) (1.3–1.7) (1.1–1.4) (1.0–1.3) (0.990–1.3) (0.940–1.2) (2.6–6.2) (2.4–3.6) (2.0–2.9) (1.7–2.4) (1.6–2.2) (1.6–2.2) (1.6–2.1) (2.5–3.3) (4.5–5.9) (4.0–5.3) (3.6–4.6) (2.5–3.2) (2.2–2.9) (2.0–2.6) (2.6–3.4) (2.1–2.8) (1.6–2.1) (1.1–1.4) (0.690–0.900) (0.620–0.810) (0.540–0.700) (0.029–0.038) (0.036–0.047) (0.033–0.043) (0.034–0.044) (0.061–0.079) (0.051–0.066) (0.053–0.069) (2.0–2.5) (1.8–2.4) (1.4–1.8) (0.980–1.3) (0.630–0.820) (0.570–0.740) (0.500–0.640) (0.350–0.460) (0.450–0.580) (0.590–0.760) (0.400–0.510) (0.320–0.410) (0.360–0.470) (0.360–0.470) (0.430–0.550) (0.630–0.810) (0.800–1.0) (0.480–0.620) (0.290–0.370) (0.300–0.390) (0.260–0.340) (0.780–1.0) (0.670–0.860) (0.530–0.690) (0.340–0.440) (0.310–0.410) (0.310–0.410) (0.260–0.340) (11–12) (10–12) (7.2–8.1) (5.9–6.7) (5.6–6.4) (5.5–6.2) (4.9–5.6)

24 24 23 20 17 17 16 49 37 21 14 10 4.4 13 18 38 61 77 62 55 52 23 21 17 13 9 9.2 7.9 305 637 682 335 131 113 95 34 68 84 72 70 70 70 18 16 14 12 11 10 9.7 94 84 63 52 50 49 49 33 62 58 53 38 35 32 62 52 42 28 18 16 14 4.4 4.8 4 3.8 6.4 5.3 5.4 22 20 16 11 6.8 6.2 5.3 7.8 9.8 13 8.4 6.5 7.4 7.4 31 50 67 42 25 26 23 18 15 12 7.4 6.7 6.7 5.5 20 19 13 10 9.5 9.2 8.2

(18–32) (20–29) (19–26) (17–23) (14–20) (14–19) (14–19) (43–55) (32–41) (18–24) (12–16) (9.1–12) (3.9–5.0) (12–15) (13–23) (32–44) (53–68) (68–87) (53–73) (45–65) (43–61) (20–26) (19–24) (15–19) (11–15) (7.9–10) (8.0–10) (6.9–8.9) (252–363) (526–759) (563–813) (276–398) (108–156) (93–135) (78–114) (27–42) (58–80) (69–100) (55–91) (56–86) (57–85) (57–85) (16–21) (14–18) (13–16) (10–13) (9.5–12) (9.0–12) (8.5–11) (58–138) (69–101) (51–75) (43–63) (43–57) (42–56) (42–56) (29–37) (54–71) (50–66) (46–61) (33–43) (30–40) (28–36) (54–70) (45–59) (37–47) (24–31) (16–21) (14–19) (13–16) (3.8–4.9) (4.2–5.5) (3.5–4.6) (3.3–4.3) (5.6–7.2) (4.6–5.9) (4.7–6.1) (19–24) (18–23) (14–18) (9.6–12) (6.0–7.7) (5.4–7.0) (4.7–6.0) (6.9–8.9) (8.6–11) (11–14) (7.3–9.5) (5.7–7.3) (6.5–8.4) (6.5–8.4) (27–35) (44–57) (58–75) (36–47) (22–28) (23–30) (20–26) (16–20) (13–17) (10–13) (6.5–8.4) (5.9–7.6) (5.8–7.5) (4.9–6.3) (19–21) (18–20) (12–14) (9.5–11) (8.9–10) (8.6–9.8) (7.7–8.7)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

227

european region

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Georgia

Germany

Greece

Greenland

Hungary

Iceland

Ireland

Israel

Italy

Kazakhstan

Kyrgyzstan

Latvia

Lithuania

Luxembourg

Malta

Monaco

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

5 5 5 4 4 4 4 80 83 84 84 83 83 83 10 11 11 11 11 11 11 <1 <1 <1 <1 <1 <1 <1 10 10 10 10 10 10 10 <1 <1 <1 <1 <1 <1 <1 4 4 4 4 4 5 5 4 5 6 7 7 8 8 57 57 57 59 61 61 61 16 16 15 15 16 16 16 4 5 5 5 5 5 5 3 2 2 2 2 2 2 4 4 3 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1

0.48 0.42 0.37 0.17 0.67 0.2 0.2 1.1 1.2 0.49 0.32 0.3 0.29 0.29 0.16 0.16 0.089 0.094 0.074 0.078 0.076 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.55 0.57 0.36 0.18 0.1 0.075 0.073 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.051 0.036 0.059 0.015 0.027 0.02 0.018 0.02 0.072 0.034 0.022 0.017 0.017 0.017 0.61 0.68 0.5 0.37 0.3 0.28 0.26 2.1 5.2 4.8 4.2 2.1 1.7 1.3 0.4 0.72 1.3 0.82 0.61 0.57 0.52 0.19 0.34 0.3 0.18 0.083 0.068 0.053 0.26 0.49 0.37 0.36 0.21 0.15 0.09 <0.01 0 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(0.430–0.550) (0.360–0.470) (0.320–0.420) (0.150–0.200) (0.370–1.1) (0.160–0.240) (0.160–0.240) (1.0–1.1) (1.2–1.2) (0.490–0.500) (0.320–0.330) (0.290–0.300) (0.280–0.290) (0.280–0.290) (0.160–0.170) (0.150–0.170) (0.085–0.092) (0.090–0.098) (0.070–0.078) (0.075–0.082) (0.073–0.080) (<0.01–0.017) (<0.01–0.017) (<0.01–0.017) (<0.01–0.018) (<0.01–0.038) (<0.01–0.038) (<0.01–<0.01) (0.550–0.550) (0.570–0.580) (0.350–0.360) (0.180–0.180) (0.100–0.100) (0.075–0.075) (0.073–0.073) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.051–0.052) (0.036–0.036) (0.058–0.059) (0.015–0.015) (0.027–0.027) (0.019–0.020) (0.018–0.018) (0.020–0.021) (0.069–0.074) (0.034–0.035) (0.022–0.023) (0.017–0.018) (0.017–0.018) (0.017–0.018) (0.590–0.630) (0.660–0.690) (0.480–0.520) (0.370–0.370) (0.300–0.300) (0.280–0.280) (0.260–0.270) (1.9–2.3) (4.8–5.6) (4.3–5.3) (3.8–4.5) (1.9–2.4) (1.5–1.9) (1.0–1.5) (0.340–0.470) (0.620–0.830) (1.1–1.4) (0.810–0.830) (0.610–0.610) (0.560–0.570) (0.510–0.530) (0.190–0.190) (0.340–0.350) (0.290–0.310) (0.180–0.190) (0.080–0.086) (0.066–0.070) (0.052–0.054) (0.260–0.260) (0.490–0.500) (0.360–0.370) (0.360–0.360) (0.210–0.210) (0.150–0.150) (0.088–0.091) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–<0.01) (0–<0.01) (0–<0.01) (0–<0.01) (0–<0.01) (0–<0.01) (<0.01–<0.01)

8.9 8.2 7.7 3.8 15 4.5 4.5 1.3 1.4 0.59 0.39 0.36 0.35 0.35 1.6 1.5 0.81 0.85 0.66 0.7 0.69 9.5 9.5 9.5 9.6 14 14 6.7 5.3 5.5 3.5 1.8 1 0.75 0.73 0.4 0.71 0.36 0.33 0.29 0.28 0.27 1.5 1 1.5 0.37 0.61 0.43 0.39 0.45 1.3 0.57 0.34 0.23 0.23 0.23 1.1 1.2 0.87 0.63 0.49 0.46 0.43 13 33 33 28 13 11 7.8 9.1 16 25 16 11 10 9.5 7.2 14 13 8.1 4 3.3 2.6 7 14 11 11 6.9 5 3 0.55 0 0.24 0.22 0.19 0.19 0.42 0.28 0.27 0.25 0.23 0.25 0.69 0.37 0.27 0.26 <0.1 <0.1 0.21 <0.1 0.1

(7.8–10) (7.2–9.3) (6.7–8.8) (3.3–4.5) (8.4–24) (3.7–5.5) (3.7–5.5) (1.3–1.3) (1.4–1.5) (0.58–0.60) (0.38–0.39) (0.35–0.36) (0.34–0.35) (0.34–0.35) (1.5–1.7) (1.4–1.6) (0.77–0.84) (0.81–0.89) (0.63–0.70) (0.67–0.74) (0.65–0.72) (0.61–30) (0.61–30) (0.61–30) (0.54–31) (<0.1–66) (<0.1–66) (1.8–15) (5.3–5.3) (5.5–5.6) (3.5–3.5) (1.8–1.8) (1.0–1.0) (0.75–0.75) (0.73–0.73) (0.40–0.40) (0.71–0.71) (0.36–0.37) (0.33–0.33) (0.29–0.29) (0.28–0.28) (0.27–0.27) (1.4–1.5) (1.0–1.0) (1.5–1.5) (0.37–0.37) (0.61–0.61) (0.43–0.43) (0.38–0.39) (0.43–0.46) (1.3–1.4) (0.56–0.58) (0.33–0.35) (0.23–0.24) (0.22–0.23) (0.22–0.23) (1.0–1.1) (1.2–1.2) (0.84–0.91) (0.63–0.64) (0.49–0.50) (0.46–0.47) (0.43–0.44) (11–14) (31–36) (29–37) (25–30) (12–15) (9.1–12) (6.3–9.3) (7.6–11) (13–18) (23–28) (16–16) (11–12) (10–11) (9.3–9.8) (7.1–7.3) (14–14) (12–13) (7.9–8.3) (3.8–4.1) (3.2–3.4) (2.5–2.6) (7.0–7.0) (13–14) (10–11) (11–11) (6.8–6.9) (4.9–5.0) (2.9–3.0) (0.54–0.56) (0–0) (0.23–0.24) (0.21–0.22) (0.19–0.20) (0.19–0.19) (0.41–0.43) (0.27–0.29) (0.26–0.28) (0.25–0.25) (0.23–0.23) (0.24–0.25) (0.69–0.69) (0.36–0.37) (0–1.5) (0–1.4) (<0.1–0.17) (0–0.54) (0–1.1) (<0.1–0.24) (<0.1–0.24)

38 29 24 14 8.2 7.9 6.9 23 19 15 9.3 6.4 6.6 6.4 1.5 1.5 1 1.2 0.62 0.7 0.71 0.14 0.14 0.14 0.14 0.2 0.2 0.11 5.5 6.9 5.2 3 2.6 2.9 2.9 0.03 0.017 0.023 0.016 0.046 0.013 0.014 0.94 0.68 0.59 0.68 0.61 0.64 0.5 0.39 0.56 0.85 0.54 0.46 0.63 0.85 7 9.7 5.1 6.1 4.5 5.3 5.7 19 110 97 51 42 50 31 7.5 15 22 17 11 11 12 3 5.9 4.6 2.3 1.3 1.2 1.6 2.5 4.9 5.5 4.2 3.1 3 2.8 0.083 0.045 0.076 0.06 0.045 0.036 0.053 0.025 0.024 0.025 0.031 0.043 0.044 0.069 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(18–67) (15–48) (13–40) (7.5–23) (3.8–14) (3.7–14) (2.9–13) (10–42) (7.8–35) (6.6–26) (4.1–17) (2.7–12) (2.9–12) (2.8–12) (0.690–2.6) (0.620–2.7) (0.390–2.0) (0.590–2.1) (0.200–1.3) (0.280–1.3) (0.310–1.3) (0.053–0.260) (0.054–0.260) (0.053–0.260) (0.056–0.260) (0.092–0.340) (0.092–0.340) (0.032–0.230) (2.3–10) (3.0–12) (2.2–9.6) (1.2–5.5) (1.3–4.5) (1.4–4.8) (1.4–4.8) (0.014–0.053) (<0.01–0.034) (0.011–0.038) (<0.01–0.028) (0.024–0.075) (<0.01–0.027) (<0.01–0.028) (0.360–1.8) (0.260–1.3) (0.240–1.1) (0.290–1.2) (0.250–1.1) (0.280–1.1) (0.180–0.970) (0.130–0.780) (0.190–1.1) (0.370–1.5) (0.200–1.0) (0.150–0.940) (0.260–1.2) (0.400–1.5) (3.2–12) (4.6–17) (1.7–10) (2.6–11) (1.6–9.0) (2.2–9.8) (2.5–10) (8.3–33) (54–180) (50–160) (23–92) (19–75) (25–85) (12–57) (3.8–12) (7.5–25) (11–37) (8.0–29) (4.7–20) (5.2–20) (5.5–21) (1.6–4.9) (3.1–9.6) (2.3–7.6) (0.990–4.1) (0.540–2.4) (0.520–2.3) (0.780–2.6) (1.2–4.4) (2.4–8.5) (2.7–9.3) (2.0–7.2) (1.4–5.6) (1.3–5.2) (1.3–5.0) (0.039–0.140) (0.015–0.091) (0.036–0.130) (0.026–0.110) (0.019–0.083) (0.013–0.071) (0.026–0.089) (<0.01–0.052) (<0.01–0.049) (0.011–0.046) (0.011–0.061) (0.014–0.087) (0.015–0.089) (0.032–0.120) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

704 571 516 315 186 182 158 29 23 18 11 7.7 7.9 7.8 15 14 9.5 11 5.6 6.3 6.3 245 245 245 247 345 346 190 53 67 51 29 26 29 29 12 6.3 8.1 5.3 14 4.1 4.3 27 19 16 16 14 14 11 8.6 10 14 8.1 6.1 8.3 11 12 17 9 10 7.5 8.8 9.4 116 706 668 340 266 312 189 170 326 449 334 204 211 217 114 237 194 102 63 60 76 69 136 157 127 103 97 93 22 11 17 13 8.9 7 10 6.8 6.1 6.2 7.5 10 10 16 6.4 6 1.7 2 5 2.4 2.7

(326–1 220) (290–944) (270–840) (168–508) (87–323) (84–316) (67–288) (13–53) (9.3–42) (8.0–32) (4.9–20) (3.2–14) (3.5–14) (3.3–14) (6.8–25) (5.8–25) (3.6–18) (5.3–19) (1.8–11) (2.6–12) (2.8–11) (96–462) (96–463) (95–464) (98–463) (163–595) (163–596) (57–401) (22–96) (29–120) (22–94) (12–55) (13–45) (14–48) (14–48) (5.5–21) (2.2–13) (4.0–14) (2.4–9.3) (7.5–24) (1.4–8.4) (1.5–8.5) (10–51) (7.1–36) (6.2–29) (7.1–29) (5.5–25) (6.2–25) (4.0–21) (2.9–17) (3.6–21) (6.1–25) (3.1–16) (2.0–13) (3.5–15) (5.2–19) (5.6–22) (8.1–29) (3.0–18) (4.4–19) (2.6–15) (3.6–16) (4.1–17) (51–207) (347–1 190) (344–1 100) (149–608) (118–472) (154–526) (77–350) (86–283) (164–542) (227–747) (159–571) (89–367) (96–370) (101–376) (60–186) (125–385) (99–321) (45–183) (26–117) (25–111) (38–127) (32–118) (65–234) (78–265) (60–219) (46–181) (44–171) (42–164) (10–37) (3.7–22) (8.4–30) (5.7–23) (3.8–16) (2.5–14) (4.9–17) (2.2–14) (2.0–12) (2.7–11) (2.6–15) (3.4–20) (3.4–21) (7.5–28) (3.2–11) (3.0–10) (0.50–3.6) (1.0–3.3) (2.5–8.4) (0.73–5.2) (0.81–5.7)

15 13 12 7.8 5.6 5.5 5 17 14 10 6.6 4.7 4.7 4.6 1 1.1 0.81 0.8 0.51 0.52 0.5 0.11 0.11 0.11 0.11 0.13 0.13 0.097 4 4.9 3.8 2.2 1.7 1.8 1.8 0.021 0.014 0.015 0.012 0.025 <0.01 0.012 0.72 0.53 0.44 0.49 0.46 0.46 0.39 0.27 0.46 0.62 0.43 0.39 0.47 0.58 4.9 6.5 4 4.4 3.7 3.9 4.1 13 50 51 35 29 31 22 4 7.7 12 10 7.5 7.6 7.7 1.5 3.1 2.9 1.7 1 0.99 1.1 1.6 3.2 3.6 2.8 2.2 2.1 2 0.055 0.037 0.051 0.043 0.033 0.029 0.034 0.015 0.013 0.018 0.025 0.033 0.035 0.048 <0.01 <0.01 0 <0.01 <0.01 <0.01 <0.01

(14–17) (12–15) (11–14) (7.0–8.7) (5.0–6.2) (4.9–6.1) (4.5–5.6) (15–19) (12–16) (9.1–12) (5.7–7.4) (4.1–5.3) (4.1–5.3) (4.1–5.3) (0.880–1.1) (0.950–1.2) (0.710–0.920) (0.700–0.900) (0.450–0.580) (0.460–0.590) (0.440–0.570) (0.093–0.120) (0.093–0.120) (0.094–0.120) (0.095–0.120) (0.110–0.150) (0.120–0.150) (0.085–0.110) (3.5–4.5) (4.3–5.6) (3.3–4.3) (1.9–2.5) (1.5–2.0) (1.6–2.0) (1.6–2.0) (0.018–0.023) (0.012–0.016) (0.013–0.017) (0.010–0.013) (0.022–0.029) (<0.01–0.010) (0.010–0.013) (0.630–0.810) (0.460–0.600) (0.390–0.500) (0.430–0.550) (0.400–0.520) (0.400–0.520) (0.340–0.440) (0.240–0.300) (0.400–0.520) (0.540–0.700) (0.370–0.480) (0.340–0.440) (0.420–0.540) (0.510–0.660) (4.3–5.5) (5.7–7.3) (3.5–4.6) (3.9–5.0) (3.2–4.1) (3.4–4.5) (3.6–4.6) (11–15) (42–58) (43–60) (30–41) (24–34) (26–36) (19–26) (3.3–4.8) (6.4–9.2) (10–15) (8.6–12) (6.2–9.0) (6.3–9.1) (6.4–9.2) (1.3–1.7) (2.7–3.5) (2.5–3.2) (1.5–1.9) (0.930–1.2) (0.890–1.1) (1.0–1.2) (1.4–1.9) (2.8–3.7) (3.2–4.0) (2.5–3.2) (1.9–2.5) (1.8–2.4) (1.8–2.3) (0.048–0.062) (0.032–0.042) (0.044–0.057) (0.037–0.048) (0.029–0.038) (0.025–0.033) (0.030–0.039) (0.013–0.017) (0.011–0.014) (0.016–0.021) (0.022–0.029) (0.029–0.038) (0.030–0.039) (0.042–0.055) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

280 263 256 175 128 125 116 21 17 12 7.8 5.6 5.7 5.6 9.9 10 7.4 7.2 4.6 4.7 4.5 191 191 191 191 232 234 170 39 48 37 22 17 18 18 8.1 5.2 5.3 3.9 8 2.9 3.5 20 15 12 12 10 10 8.6 6 8.6 10 6.5 5.3 6.3 7.6 8.6 11 7.1 7.5 6 6.5 6.7 79 318 351 235 182 193 137 92 168 249 208 141 141 141 57 126 121 75 50 48 53 44 89 103 87 73 69 66 14 9 12 9.3 6.6 5.6 6.5 4 3.2 4.5 6.1 7.9 8.1 11 3.9 3.7 0 1.2 3.1 2.1 2.1

(250–312) (234–293) (228–285) (156–195) (114–142) (112–140) (103–130) (18–24) (15–19) (11–14) (6.9–8.8) (4.9–6.4) (5.0–6.4) (4.9–6.4) (8.7–11) (8.9–11) (6.4–8.3) (6.3–8.2) (4.0–5.2) (4.1–5.3) (3.9–5.1) (167–216) (167–216) (167–216) (167–216) (203–262) (205–264) (149–193) (34–44) (42–54) (33–42) (19–25) (15–19) (16–20) (16–20) (7.1–9.2) (4.5–5.8) (4.7–6.0) (3.4–4.4) (7.0–9.0) (2.5–3.2) (3.1–4.0) (18–23) (13–17) (10–13) (10–13) (8.9–12) (8.9–11) (7.5–9.7) (5.2–6.8) (7.5–9.7) (9.0–12) (5.7–7.3) (4.6–6.0) (5.5–7.1) (6.7–8.6) (7.5–9.7) (10–13) (6.2–8.0) (6.6–8.5) (5.3–6.8) (5.7–7.3) (5.8–7.5) (66–92) (269–372) (297–411) (199–275) (154–213) (163–225) (116–160) (76–109) (138–200) (205–296) (171–248) (116–168) (116–168) (116–168) (50–65) (111–142) (106–137) (66–85) (45–56) (43–53) (49–58) (37–52) (77–102) (92–114) (76–97) (63–82) (61–78) (58–75) (13–16) (7.9–10) (10–13) (8.1–11) (5.8–7.4) (4.9–6.3) (5.7–7.4) (3.5–4.5) (2.8–3.6) (4.0–5.1) (5.3–6.9) (6.9–8.9) (7.1–9.2) (9.9–13) (3.4–4.4) (3.3–4.2) (0–0) (1.0–1.3) (2.7–3.5) (1.8–2.4) (1.8–2.4)

a

Rates are per 100 000 population.

228

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Montenegro

Netherlands

Norway

Poland

Portugal

Republic of Moldova

Romania

Russian Federation

San Marino

Serbia

Serbia & Montenegro Slovakia

Slovenia

Spain

Sweden

Switzerland

Tajikistan

2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012 1990 1995 2000 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

<1 <1 <1 <1 15 15 16 16 17 17 17 4 4 4 5 5 5 5 38 38 38 38 38 38 38 10 10 10 11 11 11 11 4 4 4 4 4 4 4 23 23 22 22 22 22 22 148 149 147 144 144 143 143 <1 <1 <1 <1 <1 <1 <1 10 10 10 10 10 11 11 5 5 5 5 5 5 5 2 2 2 2 2 2 2 39 39 40 43 46 47 47 9 9 9 9 9 9 10 7 7 7 7 8 8 8 5 6 6 7 8 8 8

<0.01 <0.01 <0.01 <0.01 0.034 0.044 0.034 0.033 0.032 0.019 0.028 0.026 0.019 0.01 <0.01 0.01 <0.01 <0.01 1.4 1.2 1.1 0.85 0.61 0.7 0.67 0.31 0.35 0.29 0.18 0.13 0.15 0.14 0.25 0.55 0.72 0.75 0.57 0.48 0.63 1.6 2.6 2.1 1.7 1.4 1.3 1.2 12 24 31 32 23 21 19 0 0 0 0 0 0 0 0.28 0.16 0.16 0.14 0.6 0.5 0.41 0.11 0.084 0.054 0.046 0.033 0.034 0.034 0.05 0.032 0.017 0.017 0.019 0.02 0.02 0.89 0.62 0.4 0.35 0.3 0.23 0.27 0.06 0.024 0.018 0.015 0.014 0.014 0.013 0.086 0.047 0.034 0.022 0.019 0.018 0.017 0.34 0.69 1.2 0.96 0.69 0.65 0.61

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.033–0.035) (0.043–0.045) (0.033–0.035) (0.032–0.034) (0.031–0.032) (0.019–0.019) (0.028–0.029) (0.025–0.026) (0.019–0.020) (0.010–0.011) (<0.01–0.010) (<0.01–0.010) (<0.01–<0.01) (<0.01–<0.01) (1.4–1.5) (1.2–1.3) (1.1–1.2) (0.820–0.880) (0.580–0.630) (0.670–0.730) (0.640–0.700) (0.290–0.330) (0.330–0.370) (0.270–0.310) (0.170–0.190) (0.120–0.130) (0.140–0.160) (0.130–0.140) (0.230–0.260) (0.510–0.580) (0.660–0.780) (0.700–0.790) (0.550–0.590) (0.470–0.500) (0.620–0.640) (1.6–1.6) (2.6–2.6) (2.1–2.1) (1.7–1.7) (1.4–1.4) (1.3–1.3) (1.2–1.2) (12–12) (24–25) (31–32) (31–33) (22–24) (21–22) (18–20) (0–0) (0–0) (0–0) (0–0) (0–0) (0–0) (0–0) (0.250–0.300) (0.150–0.180) (0.140–0.170) (0.120–0.160) (0.580–0.620) (0.480–0.520) (0.400–0.430) (0.110–0.110) (0.084–0.085) (0.053–0.054) (0.045–0.046) (0.033–0.033) (0.034–0.035) (0.034–0.035) (0.049–0.051) (0.032–0.033) (0.017–0.017) (0.016–0.017) (0.018–0.019) (0.020–0.020) (0.020–0.020) (0.870–0.900) (0.610–0.620) (0.400–0.410) (0.350–0.360) (0.300–0.310) (0.230–0.230) (0.260–0.270) (0.060–0.061) (0.024–0.024) (0.018–0.018) (0.015–0.015) (0.014–0.014) (0.013–0.014) (0.013–0.013) (0.085–0.087) (0.046–0.047) (0.034–0.035) (0.021–0.022) (0.019–0.020) (0.017–0.018) (0.017–0.018) (0.240–0.460) (0.490–0.930) (0.690–1.9) (0.720–1.2) (0.520–0.880) (0.490–0.830) (0.460–0.780)

0.57 0.19 0.19 0.19 0.23 0.29 0.21 0.2 0.19 0.11 0.17 0.6 0.44 0.23 0.21 0.21 0.12 0.14 3.8 3.2 2.9 2.2 1.6 1.8 1.8 3.1 3.5 2.8 1.7 1.2 1.4 1.3 5.6 13 17 20 16 14 18 6.9 11 9.5 7.8 6.5 5.9 5.6 8.2 16 21 22 16 15 13 0 0 0 0 0 0 0 2.8 1.7 1.6 1.5 5.8 4.5 3.8 2.1 1.6 0.99 0.85 0.61 0.63 0.63 2.5 1.6 0.86 0.83 0.9 0.97 0.97 2.3 1.6 1 0.81 0.66 0.49 0.57 0.7 0.27 0.2 0.17 0.15 0.14 0.14 1.3 0.67 0.48 0.29 0.25 0.22 0.22 6.4 12 20 14 9 8.3 7.6

(0.52–0.62) (0.13–0.25) (0.13–0.25) (0.13–0.25) (0.22–0.23) (0.28–0.29) (0.21–0.22) (0.20–0.21) (0.19–0.20) (0.11–0.12) (0.17–0.17) (0.59–0.62) (0.43–0.45) (0.22–0.23) (0.21–0.22) (0.20–0.21) (0.12–0.13) (0.14–0.14) (3.6–3.9) (3.0–3.3) (2.8–3.0) (2.2–2.3) (1.5–1.6) (1.7–1.9) (1.7–1.8) (2.9–3.3) (3.2–3.7) (2.6–3.0) (1.6–1.8) (1.1–1.3) (1.3–1.5) (1.2–1.4) (5.2–6.1) (12–13) (16–19) (19–21) (15–16) (13–14) (18–18) (6.9–6.9) (11–11) (9.5–9.5) (7.8–7.8) (6.5–6.5) (5.9–6.0) (5.5–5.6) (8.1–8.3) (16–17) (21–22) (22–23) (16–16) (14–15) (13–14) (0–0) (0–0) (0–0) (0–0) (0–0) (0–0) (0–0) (2.5–3.1) (1.5–1.9) (1.4–1.8) (1.3–1.6) (5.6–5.9) (4.4–4.7) (3.6–4.0) (2.1–2.1) (1.6–1.6) (0.99–1.0) (0.84–0.85) (0.61–0.62) (0.63–0.63) (0.63–0.63) (2.5–2.5) (1.6–1.6) (0.85–0.88) (0.82–0.84) (0.90–0.91) (0.96–0.97) (0.96–0.97) (2.2–2.3) (1.5–1.6) (0.99–1.0) (0.80–0.82) (0.65–0.67) (0.49–0.50) (0.57–0.58) (0.70–0.71) (0.27–0.28) (0.20–0.21) (0.16–0.17) (0.14–0.15) (0.14–0.15) (0.13–0.14) (1.3–1.3) (0.66–0.68) (0.47–0.49) (0.29–0.30) (0.24–0.25) (0.22–0.23) (0.21–0.22) (4.5–8.6) (8.4–16) (11–31) (11–18) (6.8–12) (6.2–11) (5.7–9.7)

0.23 0.17 0.18 0.15 2.2 2.6 1.8 1.7 1.7 1.5 1.4 0.43 0.38 0.32 0.42 0.44 0.52 0.51 25 26 17 13 11 13 11 9.8 8.6 5.9 4.6 3.4 3.4 3.6 3.5 8.9 10 9.5 8.8 8.6 8.8 67 81 66 46 34 33 31 120 240 300 320 220 190 170 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 5.1 3.7 3.5 3 11 12 7.7 1.9 2.4 1.5 1.1 0.62 0.61 0.52 1.2 0.81 0.56 0.46 0.27 0.31 0.19 11 13 12 11 10 9.6 8.1 0.87 0.94 0.66 0.97 1.1 0.79 0.92 2.1 1.3 0.83 0.82 0.85 0.9 0.57 6.4 20 30 27 16 14 13

(0.086–0.430) (0.073–0.320) (0.082–0.320) (0.065–0.280) (0.920–3.9) (1.1–4.6) (0.620–3.5) (0.700–3.2) (0.780–3.0) (0.670–2.8) (0.550–2.6) (0.160–0.820) (0.170–0.690) (0.110–0.630) (0.160–0.790) (0.170–0.850) (0.220–0.940) (0.220–0.940) (10–47) (11–46) (6.6–31) (5.1–24) (4.1–20) (6.2–23) (4.2–20) (4.2–18) (3.7–15) (2.2–11) (1.8–8.7) (1.4–6.4) (1.4–6.2) (1.6–6.4) (1.5–6.2) (4.5–15) (5.2–17) (4.1–17) (4.0–15) (4.0–15) (4.2–15) (34–110) (41–130) (32–110) (20–84) (15–62) (15–58) (15–55) (59–200) (120–400) (150–510) (160–540) (100–380) (85–340) (73–320) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (2.1–9.3) (1.5–6.8) (1.5–6.3) (1.2–5.4) (4.5–22) (5.8–20) (3.6–13) (0.600–4.0) (1.0–4.5) (0.590–2.9) (0.450–2.1) (0.250–1.2) (0.260–1.1) (0.220–0.930) (0.550–2.1) (0.330–1.5) (0.220–1.1) (0.210–0.790) (0.110–0.490) (0.150–0.540) (0.061–0.380) (3.8–21) (5.3–24) (5.1–22) (4.4–20) (4.4–18) (4.1–17) (3.2–15) (0.350–1.6) (0.430–1.7) (0.280–1.2) (0.480–1.6) (0.490–1.8) (0.280–1.6) (0.370–1.7) (0.940–3.7) (0.530–2.4) (0.290–1.6) (0.360–1.5) (0.390–1.5) (0.420–1.5) (0.190–1.2) (3.2–11) (9.5–35) (15–52) (13–44) (7.6–27) (6.6–25) (5.8–23)

37 28 29 25 15 17 11 10 10 9.2 8.2 10 8.8 7.1 9 9.1 10 10 66 67 44 33 28 35 28 99 85 57 44 32 32 34 79 206 254 252 245 242 249 287 351 295 209 158 151 144 81 163 206 223 152 135 121 7 15 8.5 1.8 2 2 2 51 38 36 31 111 108 71 36 46 28 21 11 11 9.5 60 41 28 23 13 15 9 28 33 30 25 22 21 17 10 11 7.5 11 11 8.4 9.6 31 18 12 11 11 11 7.1 121 350 493 393 206 181 160

(14–70) (12–51) (13–51) (10–45) (6.2–26) (7.4–30) (3.9–22) (4.3–19) (4.7–18) (4.0–17) (3.3–15) (3.8–19) (3.8–16) (2.5–14) (3.5–17) (3.4–17) (4.4–19) (4.3–19) (27–122) (29–121) (17–82) (13–62) (11–53) (16–61) (11–53) (43–180) (37–152) (21–110) (17–83) (13–61) (13–59) (15–61) (34–142) (104–342) (126–425) (108–454) (112–430) (113–419) (120–424) (145–478) (177–583) (142–504) (88–380) (69–282) (68–266) (67–251) (40–136) (82–271) (101–348) (112–372) (69–266) (59–240) (51–221) (2.1–15) (7.7–25) (4.2–14) (0.55–3.9) (0.82–3.7) (0.83–3.7) (0.79–3.7) (21–93) (16–70) (16–66) (13–57) (43–209) (53–183) (33–123) (11–75) (19–83) (11–54) (8.3–38) (4.5–22) (4.9–20) (4.1–17) (27–106) (16–76) (11–53) (11–40) (5.4–24) (7.3–26) (3.0–18) (9.8–54) (13–60) (13–54) (10–45) (9.5–40) (8.8–37) (6.8–33) (4.1–19) (4.9–19) (3.2–14) (5.3–18) (5.2–20) (3.0–16) (3.9–18) (14–56) (7.5–34) (4.1–23) (4.8–20) (5.0–19) (5.4–19) (2.3–15) (60–203) (164–604) (238–839) (198–654) (99–352) (85–315) (72–283)

0.18 0.13 0.13 0.11 1.6 1.9 1.4 1.3 1.2 1.1 1.1 0.33 0.27 0.25 0.32 0.34 0.37 0.37 19 18 13 9.4 8.1 9.1 8.1 7.1 6.4 4.9 3.8 2.9 2.8 2.8 2.3 4.7 6 6.6 5.9 5.7 5.6 34 43 41 32 24 22 20 70 140 190 190 150 140 130 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 3.7 2.7 2.5 2.2 7 6.7 5 1.7 1.8 1.2 0.82 0.47 0.43 0.37 0.83 0.6 0.42 0.31 0.19 0.21 0.15 8.7 10 9.2 8.4 7.8 7.4 6.5 0.64 0.65 0.48 0.62 0.72 0.63 0.68 1.5 0.95 0.66 0.59 0.58 0.6 0.48 3.7 8.6 14 14 9.8 9.2 8.6

(0.160–0.200) (0.110–0.140) (0.110–0.140) (0.100–0.130) (1.4–1.8) (1.6–2.1) (1.3–1.6) (1.1–1.5) (1.1–1.4) (0.990–1.3) (0.930–1.2) (0.290–0.370) (0.240–0.310) (0.220–0.290) (0.280–0.360) (0.300–0.390) (0.330–0.420) (0.330–0.420) (16–21) (16–21) (11–14) (8.3–11) (7.1–9.1) (8.0–10) (7.1–9.2) (6.3–8.1) (5.6–7.3) (4.3–5.5) (3.3–4.3) (2.5–3.2) (2.4–3.1) (2.4–3.1) (1.9–2.8) (3.9–5.6) (5.0–7.2) (5.4–7.9) (4.9–7.1) (4.7–6.8) (4.6–6.7) (28–41) (36–52) (33–48) (27–39) (20–28) (18–26) (17–24) (59–81) (120–170) (160–220) (160–230) (130–180) (120–160) (110–150) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (3.2–4.2) (2.3–3.0) (2.2–2.8) (1.9–2.4) (5.0–9.4) (5.7–7.9) (4.2–5.8) (1.5–1.9) (1.6–2.0) (1.0–1.3) (0.720–0.920) (0.410–0.530) (0.380–0.490) (0.320–0.420) (0.730–0.940) (0.530–0.680) (0.370–0.480) (0.270–0.350) (0.170–0.220) (0.180–0.240) (0.140–0.170) (7.7–9.9) (8.8–11) (8.1–10) (7.3–9.5) (6.8–8.8) (6.4–8.3) (5.7–7.4) (0.560–0.720) (0.570–0.730) (0.420–0.540) (0.540–0.700) (0.630–0.810) (0.550–0.710) (0.600–0.770) (1.3–1.7) (0.840–1.1) (0.580–0.750) (0.520–0.670) (0.510–0.660) (0.530–0.680) (0.420–0.540) (3.0–4.4) (7.1–10) (11–16) (11–16) (8.1–12) (7.6–11) (7.1–10)

29 20 20 18 11 12 9 8 7.2 6.8 6.3 7.7 6.2 5.7 6.9 7 7.5 7.5 49 48 33 25 21 24 21 72 64 47 36 27 26 26 54 109 147 175 166 161 160 146 189 181 147 109 101 94 47 96 127 135 106 97 91 4.8 9 4.3 1.5 1.5 1.5 1.5 37 28 26 23 68 61 46 32 33 22 15 8.7 8 6.8 41 30 21 15 9.5 10 7.5 22 26 23 19 17 16 14 7.5 7.3 5.4 6.9 7.6 6.6 7.2 22 14 9.3 8 7.5 7.6 6 70 148 220 200 129 118 108

(26–33) (18–23) (18–23) (16–20) (9.3–12) (11–14) (7.9–10) (7.0–9.0) (6.3–8.2) (5.9–7.7) (5.5–7.2) (6.8–8.7) (5.5–7.0) (5.0–6.4) (6.0–7.8) (6.1–7.9) (6.6–8.5) (6.6–8.5) (43–55) (42–54) (29–37) (22–28) (18–24) (21–27) (19–24) (63–82) (56–72) (41–53) (32–41) (24–31) (23–30) (23–30) (44–64) (90–130) (121–175) (144–209) (137–198) (133–192) (132–190) (120–174) (155–226) (149–216) (121–175) (89–130) (83–121) (77–112) (40–55) (81–112) (108–149) (114–158) (89–123) (82–114) (77–106) (4.2–5.4) (7.8–10) (3.7–4.8) (1.3–1.7) (1.3–1.7) (1.3–1.7) (1.3–1.7) (32–42) (24–32) (23–30) (20–26) (48–91) (52–72) (38–54) (28–36) (29–37) (19–24) (13–17) (7.6–9.8) (7.0–9.0) (5.9–7.7) (36–47) (27–34) (19–24) (14–18) (8.3–11) (8.8–11) (6.5–8.4) (20–25) (22–29) (20–26) (17–22) (15–19) (14–18) (12–16) (6.6–8.5) (6.4–8.3) (4.7–6.1) (6.0–7.8) (6.7–8.6) (5.8–7.5) (6.3–8.1) (19–25) (12–15) (8.1–10) (7.0–9.0) (6.5–8.4) (6.7–8.6) (5.2–6.8) (58–83) (122–176) (182–263) (165–238) (106–153) (97–140) (89–128)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

229

european region

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATE a

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

The Former 1990 Yugoslav Republic 1995 of Macedonia 2000 2005 2010 2011 2012 Turkey 1990 1995 2000 2005 2010 2011 2012 Turkmenistan 1990 1995 2000 2005 2010 2011 2012 Ukraine 1990 1995 2000 2005 2010 2011 2012 United Kingdom of 1990 Great Britain and 1995 Northern Ireland 2000 2005 2010 2011 2012 Uzbekistan 1990 1995 2000 2005 2010 2011 2012

2 2 2 2 2 2 2 54 59 63 68 72 73 74 4 4 5 5 5 5 5 52 51 49 47 46 46 46 57 58 59 60 62 62 63 21 23 25 26 28 28 29

0.17 0.1 0.21 0.066 0.034 0.024 0.017 3.4 2.4 2 0.99 0.55 0.47 0.39 0.49 0.83 1.3 1.1 0.6 0.5 0.43 5 7.8 11 12 7.4 7.1 6.1 0.44 0.51 0.43 0.39 0.32 0.34 0.34 1.7 2.7 4.3 3.5 1.5 1.1 0.6

(0.160–0.180) (0.094–0.110) (0.200–0.230) (0.064–0.069) (0.033–0.035) (0.023–0.025) (0.016–0.018) (0.780–7.8) (0.860–4.6) (0.840–3.7) (0.590–1.5) (0.390–0.740) (0.340–0.610) (0.300–0.480) (0.400–0.590) (0.720–0.950) (0.820–1.8) (0.700–1.6) (0.390–0.860) (0.330–0.720) (0.260–0.660) (4.7–5.2) (7.5–8.0) (11–11) (12–12) (7.3–7.5) (7.0–7.2) (6.0–6.2) (0.440–0.450) (0.510–0.520) (0.420–0.440) (0.380–0.390) (0.320–0.330) (0.340–0.340) (0.340–0.340) (1.5–1.9) (2.4–3.1) (3.7–5.0) (3.1–4.0) (0.850–2.3) (0.600–1.6) (0.350–0.930)

8.4 5.1 10 3.2 1.6 1.1 0.82 6.2 4 3.2 1.5 0.76 0.64 0.52 13 20 28 23 12 9.9 8.4 9.6 15 23 25 16 16 13 0.78 0.88 0.73 0.64 0.52 0.54 0.54 8.3 12 17 14 5.3 3.7 2.1

(7.9–9.0) (4.8–5.4) (9.6–11) (3.1–3.3) (1.6–1.7) (1.1–1.2) (0.77–0.87) (1.4–14) (1.5–7.8) (1.3–5.8) (0.86–2.2) (0.53–1.0) (0.47–0.83) (0.41–0.65) (11–16) (17–23) (18–40) (15–33) (7.7–17) (6.4–14) (5.0–13) (9.2–10) (15–16) (23–23) (25–26) (16–16) (15–16) (13–14) (0.77–0.78) (0.87–0.89) (0.72–0.74) (0.63–0.65) (0.52–0.53) (0.54–0.55) (0.54–0.55) (7.2–9.4) (10–13) (15–20) (12–15) (3.1–8.3) (2.1–5.8) (1.2–3.3)

3.3 1.6 1.2 0.69 0.54 0.54 0.54 27 34 28 19 17 17 17 5.6 13 18 16 8.4 6.8 5.1 33 69 81 75 68 66 62 8.6 9.3 9.2 13 11 13 13 54 100 160 130 63 52 39

(0.990–7.1) (0.650–2.9) (0.540–2.2) (0.200–1.5) (0.190–1.1) (0.210–1.0) (0.240–0.970) (11–51) (16–57) (14–48) (8.6–33) (8.1–30) (8.0–30) (7.9–30) (2.5–9.7) (6.1–22) (8.6–31) (7.6–27) (4.0–14) (3.0–12) (1.8–10) (15–60) (35–110) (38–140) (31–140) (32–120) (31–110) (29–110) (3.5–16) (3.9–17) (3.9–17) (6.0–22) (4.2–21) (5.4–23) (5.4–23) (27–90) (50–170) (77–270) (63–210) (32–100) (26–86) (19–65)

167 81 61 33 26 25 26 51 58 45 28 24 24 23 152 302 400 333 166 133 99 65 135 164 159 149 144 137 15 16 16 21 18 20 20 262 447 647 485 227 183 135

(49–354) (33–150) (26–109) (9.8–70) (9.0–51) (10–48) (11–46) (20–95) (28–98) (22–76) (13–48) (11–42) (11–41) (11–40) (69–265) (145–515) (191–685) (160–569) (79–283) (58–238) (35–196) (28–116) (68–223) (77–284) (65–293) (70–257) (68–248) (65–236) (6.0–28) (6.8–29) (6.6–29) (10–37) (6.8–34) (8.6–36) (8.7–36) (130–438) (216–760) (310–1 100) (240–814) (115–376) (92–304) (67–227)

1.6 1.1 0.85 0.62 0.44 0.41 0.39 28 26 21 23 18 17 16 3.5 6.6 9.4 8.3 5.2 4.5 3.9 23 38 53 57 48 46 42 6.6 6.9 7 9.2 8.9 9.5 9.4 26 46 71 61 34 29 22

(1.0–2.4) (0.930–1.4) (0.690–1.0) (0.560–0.680) (0.380–0.510) (0.360–0.480) (0.330–0.450) (25–32) (23–30) (18–23) (20–26) (16–21) (15–20) (14–18) (2.8–4.2) (5.4–7.8) (7.6–11) (6.8–10) (4.3–6.1) (3.7–5.5) (3.1–4.8) (19–27) (31–45) (44–63) (48–68) (41–57) (38–54) (35–51) (6.2–7.1) (6.5–7.4) (6.5–7.4) (8.6–9.8) (8.3–9.4) (8.8–10) (8.8–10) (21–31) (38–55) (59–85) (50–72) (28–40) (24–34) (18–27)

81 58 41 30 21 20 18 52 45 33 34 25 24 22 95 157 209 175 103 89 75 45 74 108 121 105 99 93 12 12 12 15 14 15 15 125 200 287 233 122 101 78

(50–119) (47–69) (34–50) (27–33) (18–24) (17–23) (16–21) (46–59) (40–51) (29–37) (29–38) (22–29) (21–27) (19–25) (76–115) (129–187) (170–252) (144–210) (86–121) (73–107) (59–94) (37–53) (62–88) (90–129) (101–144) (88–123) (83–118) (77–112) (11–12) (11–13) (11–13) (14–16) (13–15) (14–16) (14–16) (103–149) (165–238) (237–342) (193–278) (101–146) (84–121) (65–93)

a

Rates are per 100 000 population.

230

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSE NUMBER RATEa

b

CASE DETECTION PERCENT

Albania

Andorra

Armenia

Austria

Azerbaijan

Belarus

Belgium

Bosnia and Herzegovina

Bulgaria

Croatia

Cyprus

Czech Republic

Denmark

Estonia

Finland

France

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

3 3 3 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 4 3 3 3 3 3 3 8 8 8 8 8 8 8 7 8 8 9 9 9 9 10 10 10 10 9 9 9 10 10 10 11 11 11 11 5 4 4 4 4 4 4 9 8 8 8 7 7 7 5 5 4 4 4 4 4 <1 <1 <1 1 1 1 1 10 10 10 10 11 11 11 5 5 5 5 6 6 6 2 1 1 1 1 1 1 5 5 5 5 5 5 5 57 58 59 61 63 64 64

0.84 0.82 0.75 0.63 0.53 0.52 0.51 0.026 0.023 0.014 0.012 <0.01 <0.01 0.01 0.63 1.2 1.9 2.3 1.8 1.6 1.5 1.7 1.7 1.4 1.1 0.76 0.77 0.67 22 49 55 29 12 10 8.9 3.5 6.9 8.4 6.9 6.7 6.6 6.6 1.8 1.6 1.5 1.2 1.2 1.1 1.1 4.2 3 2.4 2 1.9 1.9 1.9 2.9 5.2 4.6 4.1 2.8 2.6 2.3 3 2.4 1.9 1.2 0.79 0.71 0.62 0.033 0.041 0.038 0.039 0.07 0.059 0.061 2.2 2.1 1.6 1.1 0.72 0.65 0.57 0.4 0.52 0.68 0.45 0.36 0.41 0.41 0.49 0.72 0.91 0.55 0.33 0.34 0.3 0.89 0.76 0.61 0.39 0.36 0.36 0.3 11 11 7.7 6.3 6 5.9 5.3

(0.600–1.1) (0.680–0.970) (0.630–0.870) (0.530–0.730) (0.450–0.620) (0.440–0.610) (0.430–0.590) (0.023–0.030) (0.020–0.026) (0.012–0.016) (0.010–0.013) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.012) (0.470–0.810) (1.0–1.4) (1.6–2.1) (2.1–2.6) (1.6–2.2) (1.3–1.9) (1.3–1.8) (1.5–2.0) (1.5–1.9) (1.2–1.5) (0.940–1.2) (0.660–0.860) (0.680–0.870) (0.590–0.760) (18–26) (41–59) (46–66) (24–34) (9.8–14) (8.6–12) (7.3–11) (2.8–4.3) (5.9–8.1) (6.9–9.9) (5.3–8.8) (5.3–8.1) (5.4–8.0) (5.4–8.0) (1.6–2.1) (1.4–1.8) (1.3–1.7) (1.1–1.4) (1.0–1.3) (0.990–1.3) (0.940–1.2) (2.6–6.2) (2.4–3.6) (2.0–2.9) (1.7–2.4) (1.6–2.2) (1.6–2.2) (1.6–2.1) (2.5–3.3) (4.5–5.9) (4.0–5.3) (3.6–4.6) (2.5–3.2) (2.2–2.9) (2.0–2.6) (2.6–3.4) (2.1–2.8) (1.6–2.1) (1.1–1.4) (0.690–0.900) (0.620–0.810) (0.540–0.700) (0.029–0.038) (0.036–0.047) (0.033–0.043) (0.034–0.044) (0.061–0.079) (0.051–0.066) (0.053–0.069) (2.0–2.5) (1.8–2.4) (1.4–1.8) (0.980–1.3) (0.630–0.820) (0.570–0.740) (0.500–0.640) (0.350–0.460) (0.450–0.580) (0.590–0.760) (0.400–0.510) (0.320–0.410) (0.360–0.470) (0.360–0.470) (0.430–0.550) (0.630–0.810) (0.800–1.0) (0.480–0.620) (0.290–0.370) (0.300–0.390) (0.260–0.340) (0.780–1.0) (0.670–0.860) (0.530–0.690) (0.340–0.440) (0.310–0.410) (0.310–0.410) (0.260–0.340) (11–12) (10–12) (7.2–8.1) (5.9–6.7) (5.6–6.4) (5.5–6.2) (4.9–5.6)

24 24 23 20 17 17 16 49 37 21 14 10 4.4 13 18 38 61 77 62 55 52 23 21 17 13 9 9.2 7.9 305 637 682 335 131 113 95 34 68 84 72 70 70 70 18 16 14 12 11 10 9.7 94 84 63 52 50 49 49 33 62 58 53 38 35 32 62 52 42 28 18 16 14 4.4 4.8 4 3.8 6.4 5.3 5.4 22 20 16 11 6.8 6.2 5.3 7.8 9.8 13 8.4 6.5 7.4 7.4 31 50 67 42 25 26 23 18 15 12 7.4 6.7 6.7 5.5 20 19 13 10 9.5 9.2 8.2

(18–32) (20–29) (19–26) (17–23) (14–20) (14–19) (14–19) (43–55) (32–41) (18–24) (12–16) (9.1–12) (3.9–5.0) (12–15) (13–23) (32–44) (53–68) (68–87) (53–73) (45–65) (43–61) (20–26) (19–24) (15–19) (11–15) (7.9–10) (8.0–10) (6.9–8.9) (252–363) (526–759) (563–813) (276–398) (108–156) (93–135) (78–114) (27–42) (58–80) (69–100) (55–91) (56–86) (57–85) (57–85) (16–21) (14–18) (13–16) (10–13) (9.5–12) (9.0–12) (8.5–11) (58–138) (69–101) (51–75) (43–63) (43–57) (42–56) (42–56) (29–37) (54–71) (50–66) (46–61) (33–43) (30–40) (28–36) (54–70) (45–59) (37–47) (24–31) (16–21) (14–19) (13–16) (3.8–4.9) (4.2–5.5) (3.5–4.6) (3.3–4.3) (5.6–7.2) (4.6–5.9) (4.7–6.1) (19–24) (18–23) (14–18) (9.6–12) (6.0–7.7) (5.4–7.0) (4.7–6.0) (6.9–8.9) (8.6–11) (11–14) (7.3–9.5) (5.7–7.3) (6.5–8.4) (6.5–8.4) (27–35) (44–57) (58–75) (36–47) (22–28) (23–30) (20–26) (16–20) (13–17) (10–13) (6.5–8.4) (5.9–7.6) (5.8–7.5) (4.9–6.3) (19–21) (18–20) (12–14) (9.5–11) (8.9–10) (8.6–9.8) (7.7–8.7)

653 641 604 506 431 422 408 23 12 10 7 3 9 590 1 000 1 333 2 206 1 410 1 261 1 213 1 521 1 481 1 185 928 659 671 620 2 620 1 630 5 187 6 034 7 550 9 146 6 363 3 039 4 854 6 799 5 308 5 098 4 697 4 783 1 577 1 380 1 278 1 076 1 028 985 909 4 073 2 132 2 476 2 111 1 321 1 360 1 409 2 256 3 245 3 349 3 225 2 412 2 172 2 081 2 576 2 114 1 630 1 050 688 619 29 36 33 34 61 51 63 1 937 1 834 1 414 973 627 569 565 350 448 587 395 313 359 423 624 791 479 283 296 259 772 661 527 339 312 312 261 9 030 8 723 6 122 5 003 4 801 4 681

19 19 18 16 14 13 13 42 18 12 9 3.9 11 17 31 43 73 48 43 41 20 19 15 11 7.8 8 7.3 36 21 64 70 83 99 68 30 48 68 55 54 50 51 16 14 12 10 9.4 8.9 8.2 90 61 65 54 34 35 37 26 39 42 42 33 30 29 54 45 36 24 16 14 3.8 4.2 3.5 3.3 5.5 4.6 5.6 19 18 14 9.5 5.9 5.4 5.3 6.8 8.6 11 7.3 5.6 6.4 27 44 58 36 22 23 20 15 13 10 6.5 5.8 5.8 4.8 16 15 10 8.1 7.6 7.4

78 78 81 81 81 81 81 87 87 87 87 87 87 94 82 71 95 76 78 79 87 87 87 87 87 87 93 12 3.3 9.4 21 64 88 72 86 70 81 76 76 71 72 87 87 87 87 87 87 85 96 72 100 100 69 72 76 78 62 72 79 86 85 90 87 87 87 87 87 87 87 87 87 87 87 87 100 87 87 87 87 87 87 99 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 80 80 80 80 80 80

(59–110) (66–94) (69–95) (69–95) (69–95) (69–95) (69–95) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (73–130) (70–98) (63–81) (84–110) (65–90) (65–94) (67–95) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (82–110) (10–14) (2.8–4.0) (7.9–11) (18–26) (53–77) (74–110) (60–87) (70–110) (60–82) (68–98) (61–100) (63–96) (59–87) (60–89) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (75–97) (65–160) (60–88) (86–130) (87–130) (60–81) (63–84) (66–88) (68–89) (55–71) (64–83) (69–91) (75–98) (74–97) (79–100) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (92–120) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (88–110) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (75–85) (75–85) (75–85) (75–85) (75–85) (75–85)

<0.01 0.017 0.13 0.26 0.27 0.28 0.01 0.038 0.041 0.041 0.044 0.042 0.041

(<0.01–<0.01) <0.1 (<0.1–<0.1) (0.014–0.020) 0.2 (0.14–0.20) (0.096–0.16) 1.3 (1.0–1.6) (0.20–0.31) 2.7 (2.2–3.3) (0.22–0.32) 2.8 (2.3–3.4) (0.23–0.34) 3 (2.4–3.6) (<0.01–0.011) 0.1 (<0.1–0.12) (0.033–0.043) 0.4 (0.33–0.42) (0.036–0.046) 0.4 (0.35–0.45) (0.036–0.047) 0.4 (0.34–0.45) (0.038–0.050) 0.4 (0.35–0.45) (0.037–0.048) 0.4 (0.34–0.44) (0.036–0.046) 0.4 (0.32–0.42)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

0 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1

(0–0) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.011 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.021 0.044 0.04 0.043 0.039 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.87 0.76 0.41 0.42 0.42 0.4 0.37

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.013) (<0.01–0.010) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.018–0.024) (0.038–0.050) (0.035–0.045) (0.038–0.048) (0.034–0.044) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.82–0.93) (0.72–0.81) (0.38–0.43) (0.39–0.44) (0.40–0.45) (0.38–0.43) (0.34–0.39)

0 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.1 0.2 0.2 0.1 0.1 0.1 0.1 <0.1 0.2 1.5 3.3 3.1 3.3 3 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 1.5 1.3 0.7 0.7 0.7 0.6 0.6

(0–0) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.12) (0.19–0.24) (0.15–0.20) (0.11–0.14) (<0.1–0.12) (0.11–0.14) (0.11–0.14) (<0.1–<0.1) (0.16–0.21) (1.4–1.7) (2.9–3.7) (2.7–3.5) (2.9–3.7) (2.7–3.4) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (1.4–1.6) (1.2–1.4) (0.64–0.73) (0.63–0.72) (0.63–0.71) (0.60–0.68) (0.54–0.61)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

231

european region

<0.01 <0.01 0.028 0.06 0.048 0.041 0.038 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.035 0.19 0.22 0.12 0.11 0.094

(<0.01–<0.01) (<0.01–<0.01) (0.025–0.032) (0.053–0.068) (0.040–0.056) (0.034–0.049) (0.032–0.045) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.029–0.041) (0.16–0.22) (0.18–0.26) (0.10–0.14) (0.089–0.13) (0.077–0.11)

<0.1 0.2 0.9 2 1.6 1.4 1.3 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.5 2.3 2.5 1.3 1.2 1

(<0.1–<0.1) (0.17–0.24) (0.81–1.0) (1.8–2.2) (1.4–1.9) (1.1–1.6) (1.1–1.5) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.10) (<0.1–<0.1) (<0.1–<0.1) (0.37–0.53) (1.9–2.8) (2.1–3.0) (1.1–1.6) (0.97–1.4) (0.83–1.2)

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSE NUMBER RATE a

b

CASE DETECTION PERCENT

Georgia

Germany

Greece

Greenland

Hungary

Iceland

Ireland

Israel

Italy

Kazakhstan

Kyrgyzstan

Latvia

Lithuania

Luxembourg

Malta

Monaco

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

5 5 5 4 4 4 4 80 83 84 84 83 83 83 10 11 11 11 11 11 11 <1 <1 <1 <1 <1 <1 <1 10 10 10 10 10 10 10 <1 <1 <1 <1 <1 <1 <1 4 4 4 4 4 5 5 4 5 6 7 7 8 8 57 57 57 59 61 61 61 16 16 15 15 16 16 16 4 5 5 5 5 5 5 3 2 2 2 2 2 2 4 4 3 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1

15 13 12 7.8 5.6 5.5 5 17 14 10 6.6 4.7 4.7 4.6 1 1.1 0.81 0.8 0.51 0.52 0.5 0.11 0.11 0.11 0.11 0.13 0.13 0.097 4 4.9 3.8 2.2 1.7 1.8 1.8 0.021 0.014 0.015 0.012 0.025 <0.01 0.012 0.72 0.53 0.44 0.49 0.46 0.46 0.39 0.27 0.46 0.62 0.43 0.39 0.47 0.58 4.9 6.5 4 4.4 3.7 3.9 4.1 13 50 51 35 29 31 22 4 7.7 12 10 7.5 7.6 7.7 1.5 3.1 2.9 1.7 1 0.99 1.1 1.6 3.2 3.6 2.8 2.2 2.1 2 0.055 0.037 0.051 0.043 0.033 0.029 0.034 0.015 0.013 0.018 0.025 0.033 0.035 0.048 <0.01 <0.01 0 <0.01 <0.01 <0.01 <0.01

(14–17) (12–15) (11–14) (7.0–8.7) (5.0–6.2) (4.9–6.1) (4.5–5.6) (15–19) (12–16) (9.1–12) (5.7–7.4) (4.1–5.3) (4.1–5.3) (4.1–5.3) (0.880–1.1) (0.950–1.2) (0.710–0.920) (0.700–0.900) (0.450–0.580) (0.460–0.590) (0.440–0.570) (0.093–0.120) (0.093–0.120) (0.094–0.120) (0.095–0.120) (0.110–0.150) (0.120–0.150) (0.085–0.110) (3.5–4.5) (4.3–5.6) (3.3–4.3) (1.9–2.5) (1.5–2.0) (1.6–2.0) (1.6–2.0) (0.018–0.023) (0.012–0.016) (0.013–0.017) (0.010–0.013) (0.022–0.029) (<0.01–0.010) (0.010–0.013) (0.630–0.810) (0.460–0.600) (0.390–0.500) (0.430–0.550) (0.400–0.520) (0.400–0.520) (0.340–0.440) (0.240–0.300) (0.400–0.520) (0.540–0.700) (0.370–0.480) (0.340–0.440) (0.420–0.540) (0.510–0.660) (4.3–5.5) (5.7–7.3) (3.5–4.6) (3.9–5.0) (3.2–4.1) (3.4–4.5) (3.6–4.6) (11–15) (42–58) (43–60) (30–41) (24–34) (26–36) (19–26) (3.3–4.8) (6.4–9.2) (10–15) (8.6–12) (6.2–9.0) (6.3–9.1) (6.4–9.2) (1.3–1.7) (2.7–3.5) (2.5–3.2) (1.5–1.9) (0.930–1.2) (0.890–1.1) (1.0–1.2) (1.4–1.9) (2.8–3.7) (3.2–4.0) (2.5–3.2) (1.9–2.5) (1.8–2.4) (1.8–2.3) (0.048–0.062) (0.032–0.042) (0.044–0.057) (0.037–0.048) (0.029–0.038) (0.025–0.033) (0.030–0.039) (0.013–0.017) (0.011–0.014) (0.016–0.021) (0.022–0.029) (0.029–0.038) (0.030–0.039) (0.042–0.055) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

280 263 256 175 128 125 116 21 17 12 7.8 5.6 5.7 5.6 9.9 10 7.4 7.2 4.6 4.7 4.5 191 191 191 191 232 234 170 39 48 37 22 17 18 18 8.1 5.2 5.3 3.9 8 2.9 3.5 20 15 12 12 10 10 8.6 6 8.6 10 6.5 5.3 6.3 7.6 8.6 11 7.1 7.5 6 6.5 6.7 79 318 351 235 182 193 137 92 168 249 208 141 141 141 57 126 121 75 50 48 53 44 89 103 87 73 69 66 14 9 12 9.3 6.6 5.6 6.5 4 3.2 4.5 6.1 7.9 8.1 11 3.9 3.7 0 1.2 3.1 2.1 2.1

(250–312) (234–293) (228–285) (156–195) (114–142) (112–140) (103–130) (18–24) (15–19) (11–14) (6.9–8.8) (4.9–6.4) (5.0–6.4) (4.9–6.4) (8.7–11) (8.9–11) (6.4–8.3) (6.3–8.2) (4.0–5.2) (4.1–5.3) (3.9–5.1) (167–216) (167–216) (167–216) (167–216) (203–262) (205–264) (149–193) (34–44) (42–54) (33–42) (19–25) (15–19) (16–20) (16–20) (7.1–9.2) (4.5–5.8) (4.7–6.0) (3.4–4.4) (7.0–9.0) (2.5–3.2) (3.1–4.0) (18–23) (13–17) (10–13) (10–13) (8.9–12) (8.9–11) (7.5–9.7) (5.2–6.8) (7.5–9.7) (9.0–12) (5.7–7.3) (4.6–6.0) (5.5–7.1) (6.7–8.6) (7.5–9.7) (10–13) (6.2–8.0) (6.6–8.5) (5.3–6.8) (5.7–7.3) (5.8–7.5) (66–92) (269–372) (297–411) (199–275) (154–213) (163–225) (116–160) (76–109) (138–200) (205–296) (171–248) (116–168) (116–168) (116–168) (50–65) (111–142) (106–137) (66–85) (45–56) (43–53) (49–58) (37–52) (77–102) (92–114) (76–97) (63–82) (61–78) (58–75) (13–16) (7.9–10) (10–13) (8.1–11) (5.8–7.4) (4.9–6.3) (5.7–7.4) (3.5–4.5) (2.8–3.6) (4.0–5.1) (5.3–6.9) (6.9–8.9) (7.1–9.2) (9.9–13) (3.4–4.4) (3.3–4.2) (0–0) (1.0–1.3) (2.7–3.5) (1.8–2.4) (1.8–2.4)

<0.01 0.012 0.024 0.031 0.043 0.048 0.05 0.081 0.083 0.054 0.043 0.034 0.034 0.034 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(<0.01–<0.01) (0.011–0.013) (0.022–0.027) (0.028–0.035) (0.038–0.048) (0.043–0.054) (0.045–0.056) (0.071–0.092) (0.073–0.094) (0.047–0.061) (0.037–0.048) (0.029–0.038) (0.030–0.038) (0.030–0.039) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

<0.1 0.2 0.5 0.7 1 1.1 1.2 0.1 0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1

(<0.1–<0.1) (0.21–0.26) (0.46–0.57) (0.62–0.78) (0.88–1.1) (0.98–1.2) (1.0–1.3) (<0.1–0.11) (<0.1–0.11) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1)

1 537 1 625 4 397 4 503 4 678 4 547 3 940 14 653 12 198 9 064 5 700 4 059 4 089 4 043 877 939 703 693 445 454

28 32 93 101 107 104 90 18 15 11 6.8 4.9 4.9 4.9 8.6 8.8 6.4 6.3 4 4.1

10 12 36 58 83 83 78 87 87 87 87 87 87 87 87 87 87 87 87 87

(9.0–11) (11–14) (32–41) (52–65) (75–94) (74–93) (70–88) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

0.024 0.028 0.015 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.012 0.019 0.014 0.014 0.018 0.022 0.052 0.13 0.056 0.065 0.055 0.06 0.062 <0.01 0.03 0.23 0.28 0.3 0.35 0.26 <0.01 <0.01 0.016 0.059 0.17 0.22 0.29 <0.01 0.02 0.06 0.089 0.089 0.089 0.1 <0.01 0.013 0.037 0.058 0.067 0.07 0.071 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(0.021–0.027) (0.024–0.031) (0.013–0.017) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.010–0.013) (0.017–0.022) (0.012–0.016) (0.013–0.016) (0.016–0.020) (0.019–0.025) (0.046–0.059) (0.11–0.15) (0.049–0.064) (0.057–0.073) (0.049–0.063) (0.053–0.068) (0.055–0.071) (<0.01–<0.01) (0.025–0.035) (0.19–0.27) (0.24–0.33) (0.26–0.36) (0.29–0.41) (0.22–0.31) (<0.01–<0.01) (<0.01–<0.01) (0.013–0.019) (0.048–0.070) (0.14–0.21) (0.19–0.27) (0.24–0.34) (<0.01–<0.01) (0.018–0.023) (0.053–0.068) (0.078–0.10) (0.079–0.099) (0.079–0.099) (0.093–0.11) (<0.01–<0.01) (0.011–0.015) (0.033–0.041) (0.051–0.065) (0.058–0.076) (0.061–0.079) (0.062–0.080) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

0.2 0.3 0.2 <0.1 <0.1 <0.1 <0.1 <0.1 0.1 0.2 0.2 0.6 0.2 0.2 <0.1 <0.1 <0.1 0.1 0.1 0.1 <0.1 <0.1 0.2 0.3 0.2 0.2 0.2 0.3 <0.1 0.2 0.1 0.1 <0.1 0.1 0.1 <0.1 0.2 1.6 1.9 1.9 2.2 1.6 <0.1 <0.1 0.3 1.2 3.2 4.2 5.3 0.1 0.8 2.6 4 4.3 4.3 5 <0.1 0.4 1.1 1.8 2.2 2.3 2.3 <0.1 <0.1 0.1 0.2 0.1 <0.1 0.1 <0.1 <0.1 <0.1 0.2 0.3 0.3 0.3

(0.20–0.26) (0.23–0.30) (0.13–0.17) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.12) (0.16–0.21) (0.21–0.27) (0.49–0.63) (0.17–0.22) (0.21–0.28) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.11) (<0.1–0.11) (<0.1–0.11) (<0.1–0.10) (<0.1–<0.1) (0.19–0.25) (0.28–0.37) (0.19–0.24) (0.17–0.22) (0.21–0.27) (0.25–0.33) (<0.1–0.10) (0.20–0.26) (<0.1–0.11) (0.10–0.12) (<0.1–0.10) (<0.1–0.11) (<0.1–0.12) (0–<0.1) (0.16–0.22) (1.3–1.9) (1.6–2.2) (1.6–2.2) (1.8–2.5) (1.4–1.9) (<0.1–<0.1) (<0.1–<0.1) (0.27–0.38) (0.96–1.4) (2.7–3.8) (3.4–5.0) (4.4–6.3) (<0.1–0.12) (0.71–0.91) (2.2–2.9) (3.5–4.5) (3.8–4.8) (3.8–4.8) (4.5–5.4) (<0.1–<0.1) (0.31–0.41) (0.95–1.2) (1.6–2.0) (1.9–2.5) (2.0–2.6) (2.0–2.6) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.17) (0.10–0.21) (<0.1–0.15) (<0.1–0.13) (<0.1–0.15) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.10) (0.16–0.20) (0.22–0.28) (0.22–0.28) (0.30–0.39)

114 115 84 3 588 4 339 3 073 1 808 1 543 1 279 1 159 18 12 13 10 22 8 10 624 458 386 423 396 398 341 234 398 537 371 340 412 506 4 246 5 627 3 501 3 844 3 175 3 421 10 969 11 310 25 843 28 629 23 399 25 074 18 006 2 306 3 393 6 205 6 329 5 652 5 980 6 195 906 1 541 1 982 1 409 913 864 959 1 471 2 362 2 657 2 114 1 751 1 748 1 635 48 32 44 37 29 25 45 13 11 16 22 29 30 42 1 1 0 1

202 203 148 35 42 30 18 15 13 12 7.1 4.5 4.6 3.4 6.9 2.5 3.1 18 13 10 10 8.9 8.8 7.5 5.2 7.5 8.9 5.6 4.6 5.5 6.6 7.5 9.9 6.1 6.6 5.2 5.6 68 73 177 190 147 156 111 52 74 125 126 106 111 113 34 62 84 63 44 42 47 40 65 76 64 57 57 54 13 7.8 10 8.1 5.7 4.8 8.6 3.5 2.8 3.9 5.3 6.8 7 9.8 3.4 3.3 0 2.7

87 87 87 90 88 81 82 90 72 65 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 86 23 50 81 81 81 81 57 44 50 60 75 78 80 59 49 69 84 87 87 87 90 73 74 74 79 83 82 87 87 87 87 87 87 130 87 87 87 87 87 87 87 87 87

(77–99) (77–99) (77–99) (79–100) (78–100) (71–92) (72–93) (79–100) (63–82) (57–75) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (74–100) (20–27) (43–60) (69–96) (69–96) (69–96) (69–96) (48–69) (37–53) (42–61) (51–73) (63–91) (66–95) (67–97) (52–68) (44–56) (61–79) (74–96) (78–98) (78–97) (80–95) (77–110) (64–85) (66–83) (66–84) (69–90) (73–95) (72–93) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (120–150) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

87 (77–99)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

232

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSE NUMBER RATEa

b

CASE DETECTION PERCENT

Montenegro

Netherlands

Norway

Poland

Portugal

Republic of Moldova

Romania

Russian Federation

San Marino

Serbia

Serbia & Montenegro Slovakia

Slovenia

Spain

Sweden

Switzerland

Tajikistan

2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012 1990 1995 2000 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

<1 <1 <1 <1 15 15 16 16 17 17 17 4 4 4 5 5 5 5 38 38 38 38 38 38 38 10 10 10 11 11 11 11 4 4 4 4 4 4 4 23 23 22 22 22 22 22 148 149 147 144 144 143 143 <1 <1 <1 <1 <1 <1 <1 10 10 10 10 10 11 11 5 5 5 5 5 5 5 2 2 2 2 2 2 2 39 39 40 43 46 47 47 9 9 9 9 9 9 10 7 7 7 7 8 8 8 5 6 6 7 8 8 8

0.18 0.13 0.13 0.11 1.6 1.9 1.4 1.3 1.2 1.1 1.1 0.33 0.27 0.25 0.32 0.34 0.37 0.37 19 18 13 9.4 8.1 9.1 8.1 7.1 6.4 4.9 3.8 2.9 2.8 2.8 2.3 4.7 6 6.6 5.9 5.7 5.6 34 43 41 32 24 22 20 70 140 190 190 150 140 130 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 3.7 2.7 2.5 2.2 7 6.7 5 1.7 1.8 1.2 0.82 0.47 0.43 0.37 0.83 0.6 0.42 0.31 0.19 0.21 0.15 8.7 10 9.2 8.4 7.8 7.4 6.5 0.64 0.65 0.48 0.62 0.72 0.63 0.68 1.5 0.95 0.66 0.59 0.58 0.6 0.48 3.7 8.6 14 14 9.8 9.2 8.6

(0.160–0.200) (0.110–0.140) (0.110–0.140) (0.100–0.130) (1.4–1.8) (1.6–2.1) (1.3–1.6) (1.1–1.5) (1.1–1.4) (0.990–1.3) (0.930–1.2) (0.290–0.370) (0.240–0.310) (0.220–0.290) (0.280–0.360) (0.300–0.390) (0.330–0.420) (0.330–0.420) (16–21) (16–21) (11–14) (8.3–11) (7.1–9.1) (8.0–10) (7.1–9.2) (6.3–8.1) (5.6–7.3) (4.3–5.5) (3.3–4.3) (2.5–3.2) (2.4–3.1) (2.4–3.1) (1.9–2.8) (3.9–5.6) (5.0–7.2) (5.4–7.9) (4.9–7.1) (4.7–6.8) (4.6–6.7) (28–41) (36–52) (33–48) (27–39) (20–28) (18–26) (17–24) (59–81) (120–170) (160–220) (160–230) (130–180) (120–160) (110–150) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (3.2–4.2) (2.3–3.0) (2.2–2.8) (1.9–2.4) (5.0–9.4) (5.7–7.9) (4.2–5.8) (1.5–1.9) (1.6–2.0) (1.0–1.3) (0.720–0.920) (0.410–0.530) (0.380–0.490) (0.320–0.420) (0.730–0.940) (0.530–0.680) (0.370–0.480) (0.270–0.350) (0.170–0.220) (0.180–0.240) (0.140–0.170) (7.7–9.9) (8.8–11) (8.1–10) (7.3–9.5) (6.8–8.8) (6.4–8.3) (5.7–7.4) (0.560–0.720) (0.570–0.730) (0.420–0.540) (0.540–0.700) (0.630–0.810) (0.550–0.710) (0.600–0.770) (1.3–1.7) (0.840–1.1) (0.580–0.750) (0.520–0.670) (0.510–0.660) (0.530–0.680) (0.420–0.540) (3.0–4.4) (7.1–10) (11–16) (11–16) (8.1–12) (7.6–11) (7.1–10)

29 20 20 18 11 12 9 8 7.2 6.8 6.3 7.7 6.2 5.7 6.9 7 7.5 7.5 49 48 33 25 21 24 21 72 64 47 36 27 26 26 54 109 147 175 166 161 160 146 189 181 147 109 101 94 47 96 127 135 106 97 91 4.8 9 4.3 1.5 1.5 1.5 1.5 37 28 26 23 68 61 46 32 33 22 15 8.7 8 6.8 41 30 21 15 9.5 10 7.5 22 26 23 19 17 16 14 7.5 7.3 5.4 6.9 7.6 6.6 7.2 22 14 9.3 8 7.5 7.6 6 70 148 220 200 129 118 108

(26–33) (18–23) (18–23) (16–20) (9.3–12) (11–14) (7.9–10) (7.0–9.0) (6.3–8.2) (5.9–7.7) (5.5–7.2) (6.8–8.7) (5.5–7.0) (5.0–6.4) (6.0–7.8) (6.1–7.9) (6.6–8.5) (6.6–8.5) (43–55) (42–54) (29–37) (22–28) (18–24) (21–27) (19–24) (63–82) (56–72) (41–53) (32–41) (24–31) (23–30) (23–30) (44–64) (90–130) (121–175) (144–209) (137–198) (133–192) (132–190) (120–174) (155–226) (149–216) (121–175) (89–130) (83–121) (77–112) (40–55) (81–112) (108–149) (114–158) (89–123) (82–114) (77–106) (4.2–5.4) (7.8–10) (3.7–4.8) (1.3–1.7) (1.3–1.7) (1.3–1.7) (1.3–1.7) (32–42) (24–32) (23–30) (20–26) (48–91) (52–72) (38–54) (28–36) (29–37) (19–24) (13–17) (7.6–9.8) (7.0–9.0) (5.9–7.7) (36–47) (27–34) (19–24) (14–18) (8.3–11) (8.8–11) (6.5–8.4) (20–25) (22–29) (20–26) (17–22) (15–19) (14–18) (12–16) (6.6–8.5) (6.4–8.3) (4.7–6.1) (6.0–7.8) (6.7–8.6) (5.8–7.5) (6.3–8.1) (19–25) (12–15) (8.1–10) (7.0–9.0) (6.5–8.4) (6.7–8.6) (5.2–6.8) (58–83) (122–176) (182–263) (165–238) (106–153) (97–140) (89–128)

<0.01 (0–<0.01) <0.01 0.013 0.058 0.05 0.046 0.048 0.046 0.043 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.019 0.051 0.039 0.034 0.031 0.037 0.032 0.11 0.37 0.35 0.38 0.33 0.32 0.33 <0.01 0.018 0.061 0.18 0.31 0.33 0.34 0.075 0.36 0.47 0.66 0.76 0.67 0.6 0.014 0.41 5.8 8.7 9.1 9.3 (0–<0.01) (0.012–0.015) (0.051–0.065) (0.044–0.057) (0.040–0.052) (0.042–0.054) (0.040–0.052) (0.038–0.049) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.016–0.021) (0.045–0.058) (0.034–0.044) (0.030–0.038) (0.028–0.036) (0.032–0.041) (0.028–0.037) (0.094–0.12) (0.33–0.42) (0.31–0.40) (0.33–0.43) (0.29–0.37) (0.28–0.36) (0.29–0.37) (<0.01–<0.01) (0.015–0.022) (0.051–0.073) (0.14–0.21) (0.26–0.37) (0.27–0.40) (0.28–0.40) (0.062–0.089) (0.30–0.43) (0.38–0.56) (0.55–0.79) (0.63–0.91) (0.55–0.80) (0.49–0.72)

0.2 (0–1.2) <0.1 <0.1 0.4 0.3 0.3 0.3 0.3 0.3 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.1 0.1 <0.1 <0.1 0.1 <0.1 1.1 3.7 3.4 3.6 3.1 3 3.1 <0.1 0.4 1.5 4.7 8.7 9.4 9.6 0.3 1.6 2.1 3 3.5 3.1 2.8 (0–0.54) (<0.1–0.10) (0.33–0.42) (0.28–0.36) (0.25–0.32) (0.25–0.33) (0.24–0.31) (0.23–0.29) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (0.12–0.15) (<0.1–0.12) (<0.1–0.10) (<0.1–<0.1) (<0.1–0.11) (<0.1–0.10) (0.95–1.2) (3.2–4.2) (3.0–3.9) (3.1–4.1) (2.7–3.5) (2.7–3.4) (2.7–3.5) (<0.1–0.11) (0.35–0.51) (1.2–1.8) (3.8–5.6) (7.1–10) (7.7–11) (7.9–11) (0.26–0.38) (1.3–1.9) (1.7–2.5) (2.5–3.6) (2.9–4.2) (2.5–3.7) (2.3–3.3)

156 110 110 98 1 369 1 619 1 244 1 127 1 046 981 920 285 236 221 276 297 324 16 136 15 958 10 931 8 203 7 002 7 946 7 054 6 214 5 577 4 227 3 308 2 487 2 406 2 490 1 728 2 925 2 935 5 141 4 135 4 233 4 409 16 256 23 271 27 470 26 106 18 379 16 992 16 036 50 641 84 980 140 677 127 930 125 310 112 910 105 753 1 2 1

25 18 18 16 9.2 10 7.8 6.9 6.3 5.9 5.5 6.7 5.4 4.9 6 6.1 6.6 42 41 29 21 18 21 18 63 55 41 31 23 23 23 40 67 71 136 116 119 125 70 101 123 118 84 78 74 34 57 96 89 87 79 74 4.1 7.8 3.7

87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 89 74 62 49 78 70 74 79 48 54 68 81 77 77 79 73 60 75 66 83 81 81 87 87 87

(77–99) (78–98) (78–97) (78–97) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (79–100) (62–89) (52–75) (41–59) (65–95) (59–85) (62–90) (66–95) (40–58) (45–65) (57–82) (67–98) (65–94) (64–93) (66–95) (62–86) (51–70) (65–89) (56–78) (71–98) (69–95) (70–96) (77–99) (77–99) (77–99)

(0.012–0.017) <0.1 (<0.1–<0.1) (0.35–0.48) 0.3 (0.24–0.33) (4.9–6.8) 4 (3.4–4.7) (7.4–10) 6.1 (5.1–7.1) (7.7–11) 6.3 (5.3–7.4) (7.9–11) 6.5 (5.5–7.5)

<0.01 <0.01 <0.01 <0.01

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

<0.1 <0.1 <0.1 <0.1

(<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.4 0.84 0.71 0.77 0.7 0.66 0.58 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.011 0.015 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.03 0.14 0.25 0.22 0.21 0.2

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.35–0.45) (0.73–0.95) (0.62–0.81) (0.67–0.87) (0.61–0.79) (0.58–0.75) (0.51–0.66) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.013) (0.013–0.017) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.010) (<0.01–0.011) (<0.01–<0.01) (<0.01–<0.01) (0.025–0.036) (0.11–0.16) (0.20–0.30) (0.18–0.26) (0.17–0.25) (0.16–0.24)

<0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 1 2.1 1.8 1.8 1.5 1.4 1.3 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.2 0.2 0.1 0.1 0.1 0.1 <0.1 0.1 0.5 2.2 3.6 2.8 2.7 2.5

(<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.10) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (0.90–1.2) (1.9–2.4) (1.5–2.0) (1.6–2.0) (1.3–1.7) (1.2–1.6) (1.1–1.4) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (0.15–0.19) (0.18–0.24) (0.11–0.14) (<0.1–0.12) (0.10–0.13) (0.10–0.13) (<0.1–0.11) (<0.1–0.12) (0.42–0.62) (1.8–2.7) (3.0–4.3) (2.3–3.4) (2.2–3.2) (2.0–3.0)

3 208 2 333 2 174 1 872 4 194 2 798 2 864 1 448 1 540 1 010 710 409 378 321 722 525 368 269 169 181 134 7 600 8 764 7 993 7 281 6 765 6 392 5 677 557 564 417 539 623 544 593 1 278 830 577 514 508 524 416 2 460 2 029 2 779 5 460 6 994 7 035 6 508

32 24 23 20 41 25 26 27 29 19 13 7.5 6.9 5.9 36 26 18 13 8.2 8.8 6.5 20 22 20 17 15 14 12 6.5 6.4 4.7 6 6.6 5.8 6.2 19 12 8.1 6.9 6.5 6.6 5.2 46 35 45 80 92 90 81

87 87 87 87 60 41 58 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 67 24 20 40 71 76 75

(77–100) (77–100) (77–100) (77–100) (45–84) (35–49) (49–69) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (56–81) (20–29) (17–25) (34–49) (60–86) (64–93) (63–91)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

233

european region

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSE NUMBER RATE a

b

CASE DETECTION PERCENT

The Former 1990 Yugoslav Republic 1995 of Macedonia 2000 2005 2010 2011 2012 Turkey 1990 1995 2000 2005 2010 2011 2012 Turkmenistan 1990 1995 2000 2005 2010 2011 2012 Ukraine 1990 1995 2000 2005 2010 2011 2012 United Kingdom of 1990 Great Britain and 1995 Northern Ireland 2000 2005 2010 2011 2012 Uzbekistan 1990 1995 2000 2005 2010 2011 2012

2 2 2 2 2 2 2 54 59 63 68 72 73 74 4 4 5 5 5 5 5 52 51 49 47 46 46 46 57 58 59 60 62 62 63 21 23 25 26 28 28 29

1.6 1.1 0.85 0.62 0.44 0.41 0.39 28 26 21 23 18 17 16 3.5 6.6 9.4 8.3 5.2 4.5 3.9 23 38 53 57 48 46 42 6.6 6.9 7 9.2 8.9 9.5 9.4 26 46 71 61 34 29 22

(1.0–2.4) (0.930–1.4) (0.690–1.0) (0.560–0.680) (0.380–0.510) (0.360–0.480) (0.330–0.450) (25–32) (23–30) (18–23) (20–26) (16–21) (15–20) (14–18) (2.8–4.2) (5.4–7.8) (7.6–11) (6.8–10) (4.3–6.1) (3.7–5.5) (3.1–4.8) (19–27) (31–45) (44–63) (48–68) (41–57) (38–54) (35–51) (6.2–7.1) (6.5–7.4) (6.5–7.4) (8.6–9.8) (8.3–9.4) (8.8–10) (8.8–10) (21–31) (38–55) (59–85) (50–72) (28–40) (24–34) (18–27)

81 58 41 30 21 20 18 52 45 33 34 25 24 22 95 157 209 175 103 89 75 45 74 108 121 105 99 93 12 12 12 15 14 15 15 125 200 287 233 122 101 78

(50–119) (47–69) (34–50) (27–33) (18–24) (17–23) (16–21) (46–59) (40–51) (29–37) (29–38) (22–29) (21–27) (19–25) (76–115) (129–187) (170–252) (144–210) (86–121) (73–107) (59–94) (37–53) (62–88) (90–129) (101–144) (88–123) (83–118) (77–112) (11–12) (11–13) (11–13) (14–16) (13–15) (14–16) (14–16) (103–149) (165–238) (237–342) (193–278) (101–146) (84–121) (65–93)

<0.01 0.019 0.05 0.033 0.033 0.033

(<0.01–<0.01) (0.016–0.021) (0.044–0.057) (0.029–0.037) (0.029–0.037) (0.028–0.037)

<0.1 <0.1 <0.1 <0.1 <0.1 <0.1

(<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1)

786 641 598 384 335 346 24 468 22 981 18 038 19 744 15 879 15 054 14 139 2 325 1 939 4 038 3 191 3 230

40 31 29 18 16 16 45 39 29 29 22 21 19 63 46 90 67 64

69 75 97 87 81 89 87 87 87 87 87 87 87 67 30 43 38 62

(58–85) (63–92) (88–110) (75–100) (70–94) (78–100) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (55–83) (25–36) (36–53) (32–47) (53–74)

0.15 2.5 5.8 5.7 5.3 4.8 0.071 0.087 0.12 0.25 0.3 0.32 0.33 0.057 0.22 0.57 0.69 0.56 0.51 0.44

(0.12–0.18) (2.0–2.9) (4.8–6.9) (4.8–6.7) (4.4–6.3) (3.9–5.7) (0.066–0.077) (0.061–0.12) (0.088–0.16) (0.19–0.32) (0.23–0.38) (0.25–0.41) (0.25–0.41) (0.047–0.067) (0.18–0.26) (0.47–0.68) (0.57–0.82) (0.46–0.67) (0.42–0.61) (0.37–0.53)

0.3 5 12 12 12 10 0.1 0.2 0.2 0.4 0.5 0.5 0.5 0.3 1 2.3 2.7 2 1.8 1.6

(0.24–0.34) (4.1–5.9) (10–15) (10–15) (9.6–14) (8.6–13) (0.11–0.13) (0.10–0.20) (0.15–0.27) (0.31–0.53) (0.37–0.62) (0.40–0.66) (0.40–0.66) (0.23–0.33) (0.79–1.1) (1.9–2.7) (2.2–3.2) (1.7–2.4) (1.5–2.2) (1.3–1.9)

16 465 21 459 32 945 39 608 33 857 34 237 40 990 5 908 6 176 6 220 8 173 7 907 8 439 8 269 9 414 9 866 15 750 21 513 16 883 15 345 14 832

32 42 67 84 74 75 90 10 11 11 14 13 14 13 46 43 63 83 61 55 52

71 57 62 69 70 75 96 89 89 89 89 89 89 88 37 22 22 35 50 54 66

(60–86) (48–68) (52–75) (58–83) (60–83) (63–90) (81–120) (84–95) (84–95) (84–95) (84–95) (84–95) (84–95) (82–94) (31–44) (18–26) (19–27) (30–43) (42–60) (45–65) (56–80)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

234

NO IF ED NEW AND RELAPSE i clude REPORT ase fo wh ch the treatm GLOBAL TUBERCULOSIS 2013

story is unkn wn years can be downloaded from www.who.int/tb/data Data for all

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN 139 171 196 145 180 185 223 188 134 105 105 100 226 234 167 165 128 106 53 11 9 16 9 17 53 19 43 30 18 29 – 38 48 59 58 63 65 – – 10 83 0 33 40 – 49 55 36 35 36 36 – 38 33 31 26 30 30 – 52 18 38 47 34 36 – 46 46 25 32 33 37 – 43 47 48 42 47 50 – 46 37 37 45 47 51 – 39 100 45 52 50 55 – 63 – 39 32 37 – – 35 29 41 40 44 35 – 32 38 40 38 38 44 – 41 41 47 53 55 – – 75 44 43 42 50 49 – 56 60 53 36 36 43

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Albania YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSE 653 641 604 506 431 422 408 23 12 10 7 3 9 590 1 000 1 333 2 206 1 410 1 261 1 213 1 521 1 481 1 185 928 659 671 620 2 620 1 630 5 187 6 034 7 550 9 146 6 363 3 039 4 854 6 799 5 308 5 098 4 697 4 783 1 577 1 380 1 278 1 076 1 028 985 909 4 073 2 132 2 476 2 111 1 321 1 360 1 409 2 256 3 245 3 349 3 225 2 412 2 172 2 081 2 576 2 114 1 630 1 050 688 619 29 36 33 34 61 51 63 1 937 1 834 1 414 973 627 569 565 350 448 587 395 313 359 423 624 791 479 283 296 259 772 661 527 339 312 312 261 b

• 19 Andorra

13 •

0 0 0

8 34 14 9 12

0 0 0

• 42 Armenia

11 •

1 5 0 1 2 436 621 581 339 329 315 467 324 234 76 94 95 669 890 1 561 1 997 1 426 1 301 1 845 2 547 1 235 1 269 1 217 1 277 400 409 380 244 240 235 865 759 640 441 547 569 1 087 2 524 1 214 806 716 741 1 204 372 183 201

9 1 4 2 3 451 505 1 049 639 582 553 765 652 519 213 217 218 620 3 978 2 508 2 275 2 740 2 313 2 148 2 985 3 710 2 647 2 439 2 184 534 454 406 340 273 237 997 1 287 1 106 529 611 554 1 709 0 1 511 748 708 618 703 575 382 343

2 4 3 0 3 75 153 365 351 289 255 249 209 175 69 85 97 93 245 651 965 1 130 1 002 518 442 363 429 387 381 366 326 290 230 192 179 140 261 258 161 162 176 449 442 376 747 628 606 165 103 87 75

0 0 0

0 0 0 0 0 38 54 211 81 61 90

0 0 0 1 0

0 0 0 1 0 38 76 327 451 382 395

0 0 1

• 17 Austria

41 •

0 0 0

22 116 370 321 305

0 0 0

• 20 Azerbaijan

7•

0 0 0

301 271 198

0 0

• 36 Belarus

68 •

47 74 1 314 1 153 1 201 1 747 343 825

0 1 886 844 954 1 777

47 74 3 200 1 997 2 155 3 524 343 825 1 049 1 114 1 075 1 404 80 89 68 87 59 78 130 193 156 101 65 119

1 160 2 649

0

• 30 Belgium

51 •

658 654 941 80 89

0 1 049 456 421 463

95

• 16 Bosnia and Herzegovina

8•

0 0 0 130 169 107 32 40 108

0 68 87 59 78

214 280 258

• 90 Bulgaria

37 •

158 0 2

24 49 69 25 11

0 0 0 0

• 26 Croatia

29 •

0 0 1

383 124 111 120 115 42 0 36

0 77 237 235 199

383 201 348 355 314 42

0 0 0

94 7

94 43

• 54 Cyprus

0•

•4 Czech Republic

6•

6 4 9 8 11 15 487 420 308 200 188 208 128 171 129 115 124

11 10 13 12 14 28 1 026 679 461 333 307 268 186 244 145 102 100

13 17 12 13 5 11 300 290 204 94 74 89 128 144 121 39 45

0 1 0

0 0 0 0 0 0 21 25 0 0 0 0 6 28 0

3 0 3 6

0 0 3 0 3 6 21 25 34 51 31 40 6 28 29 46 22

28 20 9

• 19 Denmark

5•

0 0 0

0 34 51 31 40

0 0 0

57 90

0 29 46 22

0 0

•7 Estonia

0•

• 27 Finland

20 •

369 255 162 99 123 105 244 205 130 82 82 78

124 320 217 134 124 110 193 136 114 146 143 104

60 67 46 17 18 19 224 157 95 84 87 70

0 0 0

71 116 54 33 31 25

0 40 46 45 31

71 116 94 79 76 56

0 0 0

• 15 a

5•

0 0 0

29 0 0 0 5

0 22 15 13 13

29 22 15 13 18

0 0 0 4

Rates are per 100 000 population. b NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

235

european region

0 0 0 4 12

30 26 29 16 28

30 26 29 20 40

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE RELAPSE RETREAT UNKNOWN NEW PULM POSITIVE UNKNOWN PULMONARY 3 449 1 815 1 941 960 906 2 969 1 364 1 557 1 015 1 016 2 305 1 665 1 389 765 710 – 54 57 55 49 47 – – 17 21 50 66 64 58 – 37 – 33 35 35 37 – – 41 38 58 60 – – – – – 39 32 43 – 19 15 27 19 22 25 – 40 12 40 33 33 29 – – 48 45 41 44 44 – – 50 46 39 39 36 – 34 44 46 43 43 – – 34 44 32 35 34 33 – 33 31 48 45 42 39 – 42 45 49 46 42 44 – 48 42 55 53 51 57 – – 52 41 0 50

NEW AND RELAPSE NOTIFICATION RATE 1990–2012 France a

YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

NEW AND RELAPSEb 9 030 8 723 6 122 5 003 4 801 4 681 1 537 1 625 4 397 4 503 4 678 4 547 3 940 14 653 12 198 9 064 5 700 4 059 4 089 4 043 877 939 703 693 445 454

12 7

0 0 0 0

371 315 261

0 371 315 261

116 2 049 2 042

• 16 Georgia

0•

• 28 Germany

90 •

221 601 1 509 2 140 2 026 1 648 3 852 1 379 910 951 928

1 087 2 213 1 524 1 088 1 141 1 186 6 473 2 801 1 713 1 787 1 580

121 1 324 1 261 1 155 1 056 944 1 873 1 211 789 735 812

0 0 0

196 259 207 291 324 161

422 1 945 1 118 986 1 034

196 681 2 152 1 409 1 310 1 195

2 4 0 1

• 18 Greece

5•

16 17 10

148 96 73 52

345 271 227 195

493 367 300 247

161 535 526 661

235 197 178 236

339 322 129 156

81 107 49 57

0 3

48 0 0 0

74 44 35

48 74 44 35

67 89 2

•9 Greenland

0•

•0 Hungary

148 •

• 35 Iceland

12 •

•7 Ireland

3•

• 18 Israel

7•

•5 Italy

7•

114 115 84 3 588 4 339 3 073 1 808 1 543 1 279 1 159 18 12 13 10 22 8 10 624 458 386 423 396 398 341 234 398 537 371 340 412 506 4 246 5 627 3 501 3 844 3 175 3 421 10 969 11 310 25 843 28 629 23 399 25 074 18 006 2 306 3 393 6 205 6 329 5 652 5 980 6 195 906 1 541 1 982 1 409 913 864 959 1 471 2 362 2 657 2 114 1 751 1 748 1 635 48 32 44 37 29 25 45

38 34 33 796 412 423 270 260 273 2 1 2 6 1 2

59 73 44 3 292 2 361 1 137 1 147 910 831 3 7 3 12 2 5

7 5 5 251 221 117 70 53 35 7 4 5 4 5 3

10 3 2

2

12 3 2

0 0 0

79 131 56 55 20 0 1 0 0 0 0

292 216 198 166 64

371 347 254 221 84 0 1 1 0 1 1

0 1 0

0 0 0

0 1 0 1 1

0 0 0

138 130 84 85 77

150 156 122 110 97

96 99 112 82 75

2 2 1 3 1

20 38 31 27 25

22 40 31 27 25

36 77 118 91

216 142 103 135 142 1 413 687 1 275 586 587

213 168 162 207 254 2 700 891 1 506 779 790

100 55 74 66 102 1 514 522 1 047 328 641

0 0 0 0 0

8 6 1 4 8

0 1 3 6 3

8 7 4 10 11

0 0 0 0 0

0 0

269 0 0 0

356 293 74 100

625 293 74 100

16 1 482 1 403

•7 Kazakhstan

0•

• 68 Kyrgyzstan

111 •

3 022 8 903 6 911 4 769 4 157 3 884 832 1 296 1 972 1 645 1 537 1 594 504 637 536 339 293 342 979 776 964 719 681 726

5 966 11 324 14 472 8 745 8 242 7 892 1 685 2 929 2 141 2 028 2 125 2 448 693 793 554 400 410 438 1 049 1 051 793 633 664 548

1 002 2 555 920 2 127 1 997 1 844 749 1 683 1 805 1 635 1 518 1 809 226 285 148 86 85 100 206 503 357 221 187 156

0 0 9

1 320 3 061 3 209 4 062 4 739 4 377 127 297 411 344 349 344 118 267 171 88 76 79 128 327 0 177 213 204

2 032 11 800 5 151 1 230 3 517

1 320 5 093 15 009 9 213 5 969 7 894 127 555 847 987 1 035 1 065 118 375 205 109 97 113 128 509 460 364 369 350

3 117 3 696 5 939 0

0 0

• 52 Latvia

113 •

258 436 643 686 721

0 451 0

• 34 Lithuania

47 •

0 0 0

108 34 21 21 34

0 0 0

• 40 Luxembourg

54 •

0 0 0

182 460 187 156 146

1 3 1

• 13 a b

9•

21 14 0 4 0

19 20 18 4 0

0 3 6 3 0

0 0 0

4 0 0 0 1

0 0 1 0

4 0 0 1 1

5 14 44

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

236

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE RELAPSE RETREAT UNKNOWN NEW PULM POSITIVE UNKNOWN PULMONARY 5 5 5 4 7 9 4 9 10 6 8 20 2 2 6 10 7 12 0 0 0 0 0 0 0 0 1 3 3 1 – 56 36 33 40 47 31 – – – – – – 49 44 55 56 – 27 35 33 32 33 35 – 52 26 29 31 23 – – 49 33 38 41 37 39 – 57 65 57 54 52 53 – 25 27 43 38 37 39 – 56 50 57 61 62 62 – 47 21 30 32 31 31 – – 100 – – – – 41 58 55 51 55 62 64 61 28 52 42 38 – 62 0 – 59 33 31 37 36 40 – 78 52 50 49 53 42

NEW AND RELAPSE NOTIFICATION RATE 1990–2012 Malta a

YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 1990 1995 2000 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

NEW AND RELAPSEb 13 11 16 22 29 30 42 1 1 0 1

•3 Monaco

10 •

0 0 0

0 1 3 3 1

1 9 8 1

0

0

0 1

0

0

0

•3 Montenegro

0•

16 • Netherlands

Norway

62 37 48 49 40

57 103 119 110 134

89 79 102 115 139

28 2 0 0 1

10 14 42 37

28 12 14 42 37

7 23 10

•7 Poland

0•

• 42 Portugal

18 •

• 63 Republic of Moldova

23 •

• 40 Romania

125 •

• 70 Russian Federation

74 •

• 34 San Marino

74 •

16 136 15 958 10 931 8 203 7 002 7 946 7 054 6 214 5 577 4 227 3 308 2 487 2 406 2 490 1 728 2 925 2 935 5 141 4 135 4 233 4 409 16 256 23 271 27 470 26 106 18 379 16 992 16 036 50 641 84 980 140 677 127 930 125 310 112 910 105 753 1 2 1

6 955 3 180 2 823 2 484 2 587 2 433 2 019 1 863 1 302 912 876 920 665 651 1 696 1 267 1 272 1 346 10 469 10 202 10 801 7 951 7 386 7 077 37 512 27 467 32 605 31 416 29 191 27 467

7 285 6 392 4 591 3 625 4 344 3 729 1 531 1 005 974 791 813 805 1 958 1 788 2 237 2 073 2 140 2 062 8 303 10 180 8 038 5 113 4 528 4 342 42 241 102 228 74 301 67 894 65 106 60 058

647 477 789 501 584 503 1 759 1 178 905 679 629 670 154 122 568 405 424 396 3 422 3 474 3 568 2 899 2 629 2 481 5 227 5 313 12 320 3 513 10 023 10 017

0 0 0

1 071 882 0 392 431 389 268 177 122 89 81 88 148 374 640 377 372 559 1 077 3 614 3 697 2 416 2 449 2 136

0 1 077 507 532 488

1 071 882 1 077 899 963 877 268 481 350 228 215 188 148 374 1 777 1 689 1 480 1 491 1 077 3 770 6 938 5 115 4 669 4 324

0 0 0

16 7 7

304 228 139 134 100

5 0 0 0

0 0 0

0 1 137 1 312 1 108 932

13 25 46

0 0 0

156 3 241 2 699 2 220 2 188

2 0 0 0

7 081 0

5 669 8 704 8 737 8 590 8 211

12 478 26 449 37 243 46 569 44 168

18 147 35 153 45 980 55 159 52 379

6 669 0

1

0

0

0

0

0

•4 Serbia

0•

20 • Serbia (without Kosovo)

Kosovo

Serbia & Montenegro •0 Slovakia

• 27 Slovenia

6•

• 36

6•

3 208 2 333 2 174 1 872 2 146 1 449 1 299 1 170 1 062 884 875 702 4 194 2 798 2 864 1 448 1 540 1 010 710 409 378 321 722 525 368 269 169 181 134

1 105 977 905 819 873 690 654 569 232 287 251 250 1 497 0 788 236 162 112 96 96 303 145 109 64 82 47

1 584 700 745 787 714 431 372 369 596 269 349 404 930 2 486 555 469 356 190 170 144 83 133 110 67 73 64

479 501 401 130 245 202 155 234 299 246

0 0 0

40 148 120 134 119 91 86 29 29 48 198 203 20 102 58 25 29 25 30 31 20 8 10

260 52 42 45

300 200 162 179 119 91 86 29 29 48 198 203 20 120 108 55 50 49 30 47 29 11 11 14

0 7 3 2

173 175 177 203 134 59 57 39 109 59 30 30 26 13

0

0 0 0

18 50 30 21 24

23 26 17

0 0 0

16 9 3 11 4

0 0 0

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

237

european region

•9

6•

156 110 110 98 1 369 1 619 1 244 1 127 1 046 981 920 285 236 221 276 297 324

64 39 48 45 575 289 237 176 177 163

66 49 40 36 1 522 528 491 370 353 300

13 14 12 13 513 427 385 463 425 444

0 0 0

13 8 10 4

14 4 2 9

27 12 12 13

0 0 0

4 3 0

0 14 16 12 11

70 30 27 26 38

70 44 43 38 49

17 11 2

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN NEW PULM 2 605 3 423 2 511 2 076 2 186 1 984 102 118 134 117 99 101 185 86 84 82 90 87 1 042 434 1 745 2 290 2 174 2 041 319 167 178 141 132 147 4 383 4 315 7 450 5 375 4 927 4 585 544 1 017 995 1 153 6 159 4 446 3 880 2 621 2 242 1 855 235 147 208 226 182 233 515 216 187 149 170 124 617 1 918 2 175 2 038 2 148 1 911 376 308 236 135 99 95 17 534 8 544 5 944 4 191 3 925 3 829 1 327 2 709 1 498 1 248 – 30 43 39 44 49 52 – 30 45 39 34 35 30 – 26 28 31 35 35 41 – 63 18 45 53 50 52 – 46 35 43 51 57 61 – 20 34 56 56 56 54 – 29 27 40 48 – – – 46 38 – 36 43 39 – – 37 40 32 30 31 – 32 27 42 41 41 40

NEW AND RELAPSE NOTIFICATION RATE 1990–2012 Spain a

YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

NEW AND RELAPSE 7 600 8 764 7 993 7 281 6 765 6 392 5 677 557 564 417 539 623 544 593 1 278 830 577 514 508 524 416 2 460 2 029 2 779 5 460 6 994 7 035 6 508 786 641 598 384 335 346 24 468 22 981 18 038 19 744 15 879 15 054 14 139 2 325 1 939 4 038 3 191 3 230 b

• 20 Sweden

12 •

124 890 1 680 1 616 1 508 216 152 197 209 173 229 126 102 110 91 119 84

0 0 0

0 0 0 0 0 11 0 0 0 3 0 5

0 1 078 324 370 314

0 1 078 324 370 314 11 40 30 52 45 39 5 63 49 40 54 47 370

388 348 330

•7 Switzerland

6•

0 0 0

40 30 52 42 39

71 87 30

• 19 Tajikistan

5•

63 49 40 54 47 370

173 133 186 145 121

• 46 The Former Yugoslav Republic of Macedonia

81 •

427 1 417 1 631 1 613 1 532 66 150 141 92 76 78 1 064 4 371 5 359 5 617 5 565 5 121 1 241 656 473

0 0 0

123 338 355 327 25 16 43 16 28 22

2 066 647 574 421

2 189 985 929 748 25 16 103 52 55 31

697 745 697

•0 Turkey

16 •

0 0 0

0 60 36 27 9

0 0 4

• 45 Turkmenistan

19 •

0 0 0

808 991 696 637 604 67 71 42 82

1 559 672 625 552

808 2 550 1 368 1 262 1 156 67 1 965 142 82

0 0 0

1 894 100

274

• 63 Ukraine

0•

• 32 United Kingdom of Great Britain and Northern Ireland

90 •

• 10 Uzbekistan

13 •

• 46

52 •

16 465 21 459 32 945 39 608 33 857 34 237 40 990 5 908 6 176 6 220 8 173 7 907 8 439 8 269 9 414 9 866 15 750 21 513 16 883 15 345 14 832

8 263 10 738 9 976 10 502 11 030

9 793 17 258 17 599 14 106 17 398 4 162 2 037 2 752 2 551 2 827 2 751 5 798 10 142 7 857 6 735 5 958 6 137

1 514 1 739 3 355 3 367 3 344 2 014 2 478 3 600 3 443 3 783 3 676 1 333 1 760 6 324 4 288 3 839 3 965 365 3 213

1 889 3 210 2 562 3 049 3 650

0 2 552 8 439 4 579

1 889 3 210 5 114 11 488 8 229

5 568

1 204 1 821 1 201 1 204 1 251 2 735 3 825 5 695 4 711 4 198 4 030

0 0 24 36 53

0 460 576 524 482

0 460 576 524 482

688 589 538

0 0 0

23 1 637 1 149 506 655

324 7 378 3 447 568 1 978

347 9 015 4 596 1 074 2 633

0 844 45

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

238

NEW AND RE TUBERCULOSIS APSE nclud ca s for w REPORT ch the r atm nt h st ry GLOBAL 2013

nown. for all years can be downloaded from www.who.int/tb/data Data

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Albania

•0 Andorra

93 •

•0 Armenia

100 •

• 55 Austria

63 •

• 82 Azerbaijan

71 •

• 65 Belarus

78 •

•0 Belgium

60 •

•0 Bosnia and Herzegovina

77 •

• 97 Bulgaria

70 •

•0 Croatia

86 •

•0 Cyprus

0•

• 100 Czech Republic

64 •

• 60 Denmark

69 •

•0 Estonia

0•

•0 Finland

59 •

•0 France

67 •

•0 Georgia

0•

• 58 Germany

76 •

•0 a

70 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

139 171 196 171 145 180 1 5 2 0 1 436 621 581 440 339 329 467 324 234 90 76 94 669 890 1 561 1 487 1 997 1 426 1 845 2 547 1 235 1 201 1 269 1 217 400 409 380 280 244 240 865 759 640 609 441 547 1 087 2 524 1 214 894 806 716 1 204 372 302 183 201 6 4 9 14 8 11 487 420 308 218 200 188 128 171 129 101 115 124 369 255 162 135 99 123 244 205 130 93 82 82 3 449 1 815 1 941 1 019 960 906 221 601 1 509 2 055 2 140 2 026 3 852 1 379 1 025 910 951

196 171 145 180 2 5 3 0 1 507 447 581 440 339 329 383 298 230 226 206 221 538 890 1 561 1 480 1 919 2 208

2 160 2 184 2 169 358 304 485 473 405 865 756 1 035 852 441 693

1 342 1 055 946 853

391 234 181 6 8 28 20 22 487 396 315 402 361 377 110 128 175 217

257 162 240 191 202

227 184 181

221 807 1 489 2 352 2 500 2 513 454 1 199 2 220 2 064 2 113

– – 100 100 100 100 – 200 100 150 – 100 116 72 100 100 100 100 82 92 98 251 271 235 80 100 100 100 96 155 – – – 180 172 178 – 88 80 173 194 169 100 100 162 140 100 127 – – 111 118 117 119 – – 105 77 99 – 100 – 89 200 250 200 100 94 102 184 180 201 – 64 99 173 189 – – 101 100 178 193 164 – – – 244 224 221 – – – – – – 100 134 99 114 117 124 – – 87 217 227 222

43 64 49 65

35 25 42 28 50 0 67 100 2 6 13 12 16 19 81 73 58 59 59 64 7 0 11 15 30 44

4 2 3 2

2 1 0 0

5 4 3 4 50 0 0 0 1 7 14 8 8 6 7 6 7 8 6 7 19 3 12 16 10 10

11 4 3 1 0 20 0 0 0 0 4 10 1 0 1 11 11 16 23 15 4 4 22 12 6 4

80 33 0 52 81 59 60 55 44 2 0 17 8 6 7 58 89 48 47 47 33

0 0 0 8 4 3 7 4 6 10 9 7 9 6 6 1 4 3 3 3

0 0 0 36 3 5 3 15 25 0 0 0 0 0 0 12 2 4 7 4 6

64 66 59 25 21 14 15 28 97 77 93 97 91 43

0 0 1 41 45 62 61 50 1 18 3 2 7 27

10 8 6 10 10 8 7 7 0 1 1 0 1 5

4 22 31 1 0 0 0 0 1 1 0 0 0 1

1 1 1 17 0 11 11 10 1 2 0 0 0 1

20 2 1 6 24 4 7 6 1 1 2 0 0 24

82 78 84 84

3 7 2 2

4 9 8 8

2 2 2 1

7 4 3 3

1 1 1 2

40 48 58 100 38 29 25 55 57 59 62 66 66 66 37 44 22 31

7 15 17 0 25 0 0 9 3 11 10 2 3 3 49 39 31 33

7 26 14 0 12 0 0 14 0 17 6 21 17 17 5 6 4 11

0 0 0 0 0 0 0 0 3 1 0 0 0 0 0 1 1 2

1 3 4 0 0 0 0 0 2 1 2 7 7 9 0 2 1 0

45 7 7 0 25 71 75 23 35 11 20 4 7 5 9 8 42 22

67 70 57 65 57

2 2 1 3 2

11 8 15 10 11

1 1 2 2 1

6 10 6 4 5

12 10 18 17 23

33 48 39

34 27 29

17 9 18

0 0 1

1 2 0

14 15 14

41 38 60 57 59 57 61 39 33 32 29

18 25 13 19 17 19 16 32 44 44 42

8 3 3 3 3 2 16 9 12 12 11

3 9 5 12 12 15 1 0 0 0 0

29 25 13 7 7 5 2 2 1 2 2

2 0 7 3 2 2 4 18 9 9 17

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

239

european region

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Greece

•0 Greenland

0•

•0 Hungary

0•

•0 Iceland

0•

• 100 Ireland

0•

•0 Israel

64 •

•0 Italy

77 •

• 80 Kazakhstan

0•

•0 Kyrgyzstan

61 •

•0 Latvia

78 •

• 61 Lithuania

73 •

•0 Luxembourg

73 •

• 100 Malta

0•

• 100 Monaco

58 •

•0 Montenegro

0•

86 • Netherlands

• 72 Norway

81 •

• 77 Poland

0•

•0

60 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

235 197 198 178 236

24 38 34 796 412 423 363 270 260 2 1 2 3 6 1 138 130 95 84 85 216 142 119 103 135 1 413 687 1 275 885 586 587 3 022 8 903 6 911 5 213 4 769 4 157 832 1 296 1 972 1 609 1 645 1 537 504 637 536 367 339 293 979 776 964 742 719 681 21 14 0 4 5 5 5 12 4 7 0

651 412 597 515 0 2 2 2 4 16 0 73 107 188 164 153 336 227 202 99 242 295 223

8 781 6 884 5 355 4 919 4 306 1 233 1 897 1 543 1 537 475 637 536 592 596 559 776 958 1 033 959 1 000 37 0 14 6 5 4 5 10 5 12

64 53 39 48 575 289 237 203 176 177 62 37 48 42 49 40 6 955 3 180 2 823 2 658 2 484 2 587

63 78 39 56 715 301 208 454 469 437 87 37 47 146 139

214 2 823 4 391 3 998 4 699

– – – – – – – – – – – – – 158 97 164 191 0 100 200 100 133 267 0 – 53 82 198 195 180 – 156 160 170 96 179 21 32 – – – – – 99 100 103 103 104 – 95 96 96 – 100 94 100 100 161 176 191 – 100 99 139 133 147 – – 0 – – 150 100 80 100 83 125 171 – – – – – – 98 147 100 117 124 104 88 224 266 247 140 100 98 348 284 – – 7 100 165 161 182

28 32 45 64 0 0 0 0 0

36 13 12 5 100 100 100 75 88

10 13 10 12 0 0 0 0 6

3 12 19 0 0 0 0 0 0

12 9 7 10 0 0 0 0 0

11 20 7 9 0 0 0 25 6

33 3 5 0 54 65 69 72 69 69 73 37

51 62 62 73 10 18 15 14 7 9 6 36

12 9 9 7 5 15 11 10 11 10 3 1

0 3 0 0 0 0 0 0 0 0 2 0

4 1 1 1 3 0 3 1 0 2 11 9

0 22 23 19 29 1 2 3 13 10 4 16

76 70 62 61 61 73 81 79 75 61 68 72 72 72 72 73 70 73 68 73 100

3 1 0 0 0 9 4 4 3 0 4 1 3 3 1

5 5 4 3 4 3 3 3 3 9 12 11 9 8 10 10 11 10 11 11 0

10 12 30 7 6 4 5 4 11 3 3 1 1 1 0 4 3 2 1 1 0

3 5 3 2 2 5 5 6 5 21 7 7 5 6 5 12 11 9 11 8 0

3 8 2 27 27 6 2 4 3 7 7 8 11 10 11 2 6 6 8 7 0

0 0 0 0 0

0 0 80 0 0 0 0 0

0 0 20 100 100 80 80 58

7 17 0 0 0 0 0 0

0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 8

93 83 0 0 0 20 20 33

10 49 46 25 17 23 9 11 1 1 43 49 62 45 68

21 37 41 61 55 53 75 69 76 81 34 22 30 37 24

8 5 12 8 6 7 9 7 5 14 14 2 4 3

0 0 0 0 0 0 0 0 1 3 0 1 1

4 3 0 5 3 1 3 4 3 8 3 4 0 0

70 3 5 2 15 15 8 8 12 11 0 11 2 13 5

50 65 48 47 43

22 12 19 19 17

11 5 5 6 9

6 1 0 0 0

6 9 10 9 9

5 8 17 19 22

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

240

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Portugal

• 69 Republic of Moldova

80 •

•0 Romania

62 •

• 51 Russian Federation

85 •

• 65 San Marino

54 •

•0 Serbia

0•

87 • Serbia & Montenegro Slovakia

• 64 Slovenia

91 •

• 90 Spain

81 •

•0 Sweden

73 •

•0 Switzerland

83 •

•0 Tajikistan

0•

• 88 The Former Yugoslav Republic of Macedonia

80 •

• 70 Turkey

95 •

•0 Turkmenistan

90 •

• 73 Ukraine

0•

• 83 United Kingdom of Great Britain and Northern Ireland

58 •

•0 Uzbekistan

80 •

• 78 a

78 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2005 2009 2010 2011 1995 2000 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

2 019 1 863 1 302 1 043 912 876 665 651 1 696 1 318 1 267 1 272 10 469 10 202 10 801 8 987 7 951 7 386 37 512 27 467 32 605 33 351 31 416 29 191 1

1 240 1 924 1 393 1 565 1 387 651 1 690 1 318 1 267 1 272 11 597 10 158 10 929 10 737 9 445 8 886 54 3 616 25 692 32 316 30 123 36 747 1

1 105 1 055 977 905 1 497 0 788 236 162 121 112 96 303 145 109 85 64 82 2 605 3 423 2 511 2 236 2 076 2 186 102 118 134 107 117 99 185 86 84 74 82 90 1 042 434 1 745 1 972 2 290 2 174 319 167 178 198 141 132 4 383 4 315 7 450 6 007 5 375 4 927 544 1 017 995 1 370 1 153 8 263 10 738 13 632 9 976 10 502 1 204 1 821 1 256 1 201 1 204 2 735 3 825 5 695 4 959 4 711 4 198

1 154 1 392 988 894 1 956 267 807 238 158 174 177 138 270 145 109 149 123 151

3 574 3 335 112 133 255 289 247

348 665 1 729 1 972 2 290 2 174 222 152 179 199 143 130 3 461 7 450 6 007 5 375 4 927 544 1 017 995 1 375

9 564

13 111 13 279 13 714

1 348 2 569 2 602 2 952 2 598 1 030 5 336 4 959 4 711 4 198

61 103 107 150 – 158 – 100 100 100 100 100 111 100 101 119 119 120 0 13 79 97 96 126 – 100 – – – – 104 132 101 99 131 – 102 101 98 144 158 144 89 100 100 175 192 184 – – – – 172 153 – 95 99 238 247 249 – – – – – – 33 153 99 100 100 100 70 91 101 101 101 98 – 80 100 100 100 100 100 100 100 100 – – 116 – – 96 133 131 – – 74 205 217 245 95 27 94 100 100 100

45 9 13 9 9 1 60 49 52 57 38 28 71 72 70 71 54 64 55 52 50 48 0

23 71 76 75 72 62 2 5 5 5 13 42 11 14 14 14 11 4 3 3 3 5 0

4 6 6 6 5 0 9 10 11 9 6 4 5 4 5 5 15 6 13 11 12 9 100

4 0 0 0 0 0 11 17 5 18 7 8 4 4 4 3 6 13 14 20 23 10 0

4 5 4 3 3 0 11 14 13 10 6 8 6 6 6 5 11 9 11 8 7 7 0

19 9 2 7 12 37 7 5 13 1 31 9 4 1 2 1 4 4 4 5 5 20 0

72 80 79 80 34 82 64 81 66 82 84 91 64 33 47 24 28 37

13 6 8 7 18 7 0 26 0 0 1 26 51 38 63 57 44

5 6 6 7 2 4 16 14 6 14 12 7 4 8 12 9 11 18

1 1 1 0 3 0 1 0 0 0 0 2 0 0 1 0 0

5 4 4 4 10 6 4 2 1 2 3 0 1 5 1 1 1 1

4 2 2 2 33 1 16 1 1 2 1 2 3 3 3 3 3 1

39 42 0 0 0 70 51

32 31 79 74 85 15 32

6 7 11 6 6 5 5

0 0 0 1 0 0 1

1 1 2 1 1 1 2

23 19 8 18 8 9 9

69 74 74 75 76 74 61 51 62 85 83 78 0 45 61 63 60 55 79 70 83

18 3 9 6 4 6 9 35 22 5 7 16 73 44 30 29 31 18 2 14 1

7 15 4 4 5 5 13 4 2 4 4 3 3 2 3 3 3 11 9 6 5

3 8 6 8 11 11 9 2 0 2 3 0 0 0 1 1 1 7 6 4 6

2 0 7 5 3 3 9 7 14 5 2 2 6 5 2 3 3 2 3 5 5

0 0 0 1 1 1 0 1 0 0 1 0 19 3 3 2 3 7 1 1 1

83

6

7

4

52 51 48

7 9 10

13 13 13

16 17 18

8 8 7

3 3 4

0 0 0 0 78 27 72 77 76 73

68 82 81 80 0 53 9 5 5 5

7 6 5 6 9 3 6 6 6 6

0 0 0 0 7 6 6 5 6 6

1 5 6 6 4 5 7 5 5 6

24 7 8 8 3 6 1 3 3 4

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

241

european region

       % OF COHORT TREATMENT SUCCESS (%) 1995–2011 a

YEAR

NUMBER NOTIFIED

SIZE OF COHORT

COHORT AS % NOTIFIED

CURED

COMPLETED

DIED

FAILED

DEFAULTED

NOT EVALUATED

Albania

•0 Andorra

83 •

•0 Armenia

0•

• 50 Austria

68 •

•0 Azerbaijan

43 •

•0 Belarus

71 •

•0 Belgium

29 •

•0 Bosnia and Herzegovina

61 •

•0 Bulgaria

63 •

•0 Croatia

66 •

•0 Cyprus

0•

•0 Czech Republic

100 •

•0 Denmark

75 •

•0 Estonia

0•

•0 Finland

31 •

•0 France

25 •

•0 Georgia

0•

• 32 Germany

61 •

•0 a

58 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

53 19 43 21 30 18 0 0 2 0 1 38 76 327 542 451 382 30 26 25 29 20 47 74 3 200 2 384 1 997 2 155 343 825 1 049 878 1 114 1 075 80 89 68 87 59 130 193 156 113 101 65 383 201 372 348 355 42 94 62 43 0 0 3 3 0 3 21 25 34 51 31 6 28 29 10 46 22 71 116 94 80 79 76 29 22 15 13 0 371 315 261 196 681 2 152 566 1 409 1 310

30 21 30 18

2 0 1 6 54 327 542 451 382 10 27 37 29 21 74 1 314 1 687 4 194 4 005

616 792 1 020 55 47 76 85 56 122 106 116 101 104

198 384 348 355

92 22 37

2 6 0 3 38 31 62 49 32 15 22 42 35

59 89 82 81 75

14 13 12

298 470 2 037 1 521 1 421 1 321 63 432 344 364 289

493 252 367 300

– – 70 100 100 100 – – – 100 – 100 16 71 100 100 100 100 – 33 104 148 100 105 – 100 41 71 210 186 – – – 70 71 95 – 62 69 – 98 95 – 63 68 103 100 160 – – 99 103 100 100 – – 98 35 86 – – – 67 200 – 100 – 152 91 – 96 103 – 54 76 420 76 – – 51 95 102 103 99 – – – – 87 92 – – – – – – 152 69 95 269 101 101 – – 88 137 99 96

37 38 43 28

37 38 47 56

3 10 3 6

0 0 0 0

10 10 7 6

13 5 0 6

0 0 50 52 13 9 5 5 0 11 3 14 0 59 28 39 14 8

100 0 0 15 28 54 62 63 80 56 38 45 43 7 9 14 49 63

0 0 0 7 7 8 6 4 0 11 5 0 14 5 6 6 3 3

0 0 17 7 12 4 10 9 0 0 0 0 5 11 6 9 4 5

0 0 33 19 37 15 13 15 0 11 30 0 5 14 13 19 15 12

0 100 0 0 4 10 4 3 20 11 24 41 33 4 38 13 15 8

38 20 21 16 17 11 8 16 79 85 52 83 19

4 28 8 45 21 57 55 45 15 8 32 12 43

13 10 7 13 19 9 6 9 3 4 5 2 7

7 36 59 0 0 0 0 0 1 1 3 1 0

1 1 3 15 0 12 12 16 2 2 3 1 3

37 5 3 11 43 12 19 14 0 1 5 1 28

57 32 32 30

10 38 31 36

7 12 13 9

11 5 6 5

14 8 12 11

2 5 5 8

20 27 59

13 23 16

9 36 14

1 5

1 5 3

57 5 8

0 17 67 53 16 34 41 44 27 27 12 20

100 0 33 11 39 34 33 31 60 64 40 40

0 0 0 8 3 18 16 12 7 5 2 11

0 0 0 3 0 0 0 0 0 0 2 3

0 0 0 0 3 2 0 9 0 5 0 0

0 83 0 26 39 13 10 3 7 0 43 26

54 21 34 28 15

2 20 17 11 16

3 3 15 11 21

0 4 6 2 1

3 26 9 15 11

37 25 20 32 36

29 38 25

7 8 0

0 0 8

0 0 0

0 0 0

64 54 67

8 23 19 26 26 27 51 30 21 25 17

24 31 35 34 35 34 21 36 44 47 41

12 10 7 5 5 4 16 9 12 12 10

9 8 10 17 17 23 3 0 0 1 0

45 29 23 15 11 8 5 7 5 6 6

2 0 6 3 4 4 5 18 17 10 27

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

242

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%) 1995–2011 a

YEAR

NUMBER NOTIFIED

SIZE OF COHORT

COHORT AS % NOTIFIED

CURED

COMPLETED

DIED

FAILED

DEFAULTED

NOT EVALUATED

Greece

•0 Greenland

0•

•0 Hungary

0•

•0 Iceland

0•

•0 Ireland

100 •

•0 Israel

54 •

•0 Italy

50 •

• 48 Kazakhstan

0•

•0 Kyrgyzstan

36 •

•0 Latvia

56 •

•0 Lithuania

51 •

•0 Luxembourg

33 •

•0 Malta

0•

•0 Monaco

100 •

•0 Montenegro

0•

83 • Netherlands

•0 Norway

80 •

•0 Poland

0•

•0

53 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

48 74 3 44 35

6 12 3 371 347 211 254 221 0 1 1 1 0 1 22 40 16 31 27 8 7 9 4 10 625 293 74 100 1 320 5 093 15 009 9 371 9 213 5 969 127 555 847 758 987 1 035 118 375 205 147 109 97 128 509 460 404 364 369 4 0 0 1 0 0 1 2 3 3 0 0 0 1 1 2 3 3 122 333 208 254 0 1 1 0 1 10 14 52 33 26 8 7 9 5 10 31 26

2 901 4 085 9 392 8 734 5 026 278 845 924 523 205 205 148 110 97 282 455 404 364 369

27 11 12 12 70 44 46 43 38 28 12 14 42 37 1 071 882 1 077 688 899 963

10 11 14 12 18 28 49 44 46 3 9 30 40

56 985 942 899 963

– – – – – – – – – – – – – 33 96 99 100 0 – 100 – 100 – 100 – 45 35 325 106 96 – 100 100 100 125 100 – 4 – – – – – 57 27 100 95 84 – 50 100 122 – 51 – 55 100 101 101 100 – 55 99 100 100 100 – – – – – 0 – – 100 100 100 100 – – – – – – 37 100 117 100 – 26 64 107 102 121 – 25 64 – 95 – – 6 91 137 100 100

16 12 35 13

20 37 26 49

15 13 13 11

9 8 12 0

11 11 6 17

30 18 8 9

0 0 0 40 7 4 0 50 12 71 56 80 40 42 31

100 100 100 0 57 58 55 4 25 14 11 0 10 6 15

0 0 0 10 7 8 15 15 62 14 11 20 10 26 4

0 0 0 10 0 0 0 0 0 0 0 0 0 10 12

0 0 0 40 0 0 3 0 0 0 0 0 20 13 8

0 0 0 0 29 31 27 31 0 0 22 0 20 3 31

62 46 22 23 36 59 40 28 49 39 50 43 60 45 45 27 30 31 33

4 1 27 24 0 15 31 43 6 2 1 1 2 5 0 2 0 1 0

10 13 9 9 11 8 8 7 9 19 10 14 6 10 21 25 24 18 16

14 14 34 4 4 8 9 6 22 3 1 0 0 1 8 4 5 4 2

5 6 6 5 5 6 11 7 8 8 9 14 12 12 22 22 22 22 23

5 19 3 35 44 4 1 9 5 29 29 28 20 26 5 19 20 25 25

0 0 0 0 0

100 100 50 67 100

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

0 0 50 33 0

45 50 67 28 11 4 5 0 33 44 33 20

20 27 36 17 22 68 67 61 80 0 33 47 52

20 9 0 8 6 4 2 9 0 67 22 13 15

0 0 0 0 0 0 0 0 0 0 0 5

0 0 0 6 7 4 7 2 0 0 0 0

60 18 14 8 39 11 22 18 17 0 0 7 8

64 22 30 28 25

12 31 32 33 28

14 6 5 8 10

0 0 0 0 0

4 32 14 10 12

5 9 18 21 24

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

243

european region

       % OF COHORT TREATMENT SUCCESS (%) 1995–2011 a

YEAR

NUMBER NOTIFIED

SIZE OF COHORT

COHORT AS % NOTIFIED

CURED

COMPLETED

DIED

FAILED

DEFAULTED

NOT EVALUATED

Portugal

• 55 Republic of Moldova

61 •

•0 Romania

38 •

•0 Russian Federation

58 •

• 58 San Marino

42 •

•0 Serbia

0•

78 • Serbia & Montenegro Slovakia

•0 Slovenia

88 •

•0 Spain

100 •

•0 Sweden

56 •

•0 Switzerland

78 •

•0 Tajikistan

0•

•0 The Former Yugoslav Republic of Macedonia

71 •

•0 Turkey

78 •

•0 Turkmenistan

68 •

•0 Ukraine

0•

•0 United Kingdom of Great Br tain and Northern Ireland

34 •

•0 Uzbekistan

80 •

•0 a

72 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2005 2009 2010 2011 1995 2000 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

268 481 350 271 228 215 148 374 1 777 1 663 1 689 1 480 1 077 3 770 6 938 5 401 5 115 4 669 18 147 35 153 32 569 45 980 55 159 0

133 209 293 265 204 1 1 713 1 663 1 702 1 500 2 605 6 737 5 391 5 118 4 667 12 1 694 10 855 16 726 14 609 26 062

300 203 200 162 198 203 20 120 108 79 55 50 30 47 29 8 11 11 0 1 078 324 370 11 40 30 52 45 5 63 49 51 40 54 370 2 189 533 985 929 25 16 103 56 52 55 808 2 550 1 445 1 368 1 262 67 1 965 142 82 1 889 3 210 5 477 5 114 11 488 0 460 576 524 347 9 015 2 451 4 596 1 074

284 244 203 164 21 46 101 79 55 50 24 27 8 11 11

351 388 9 16 45 52 45

1 762 1 618 1 732 1 674

97 56 52 55

1 593 1 459 1 368 1 262 495 142

10 424 9 812 6 413

147 791 576 492 764 3 999 2 451 4 527 1 074

50 43 84 98 – 95 – 0 96 100 101 101 – 69 97 100 100 100 – 9 31 51 32 47 – – – – – – 95 120 101 101 – 10 – 38 94 100 100 100 – 51 93 100 100 100 – – – – 108 105 – 22 53 – 100 100 – – – – – – – – 80 304 176 180 – – 94 100 100 100 – – 62 101 100 100 – 25 100 – – – – – – 190 192 56 – – 32 – 100 94 – 220 44 100 98 100

38 10 8 7 3 0 22 15 15 18 24 39 38 37 39 42 25 33 31 31 20

17 66 66 62 58 0 19 20 17 20 20 13 19 18 19 17 24 4 3 4 22

6 4 10 7 4 0 13 15 14 13 9 10 10 11 11 25 10 16 13 12 10

6 0 1 0 0 100 16 26 5 28 20 10 12 12 11 8 21 26 32 33 15

9 7 9 8 2 0 17 20 17 17 17 14 16 17 15 8 9 16 12 12 10

24 14 6 16 32 0 13 4 32 4 11 14 4 6 5 0 11 5 9 9 23

46 61 55 60 67 78 50 34 44 48 29 44 12 18 27

26 13 21 18 10 0 38 48 40 40 46 41 75 45 73

10 9 9 5 10 11 7 14 15 2 4 4 0 36 0

2 0 1 1 0 2 0 1 0 4 0 0 0 0 0

12 12 10 8 14 4 3 0 0 2 12 4 0 0 0

3 5 3 9 0 4 3 3 2 4 8 7 12 0 0

25 26 0 0 0 21 22

31 30 78 75 69 54 56

9 13 0 0 13 2 2

0 0 0 0 0 0 0

2 2 11 0 7 0 4

33 28 11 25 11 23 16

29 29 33 29

47 43 38 41

9 11 11 10

8 10 11 13

6 6 4 5

1 1 1 1

24 39 29 38

33 39 37 40

7 7 17 9

2 2 4 4

32 11 12 7

2 2 2 2

24 29 25 22 66 42

46 44 43 46 9 26

5 3 5 4 7 13

2 2 2 2 11 10

12 9 7 10 6 9

11 13 17 16 1 0

18 17 26

29 29 8

14 14 16

22 23 33

12 10 9

5 7 7

0 0 0 0 20 28 30 25 40

57 79 74 80 55 41 39 48 32

4 7 7 6 8 9 11 10 9

0 0 0 0 8 7 7 5 10

3 5 7 6 9 14 9 9 8

36 9 12 8 0 1 5 4 1

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

244

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 15 42 39 55 0 0 11 12 70 95 100 81 186 170 233 0 0 1 270 1 242 1 499 1 518 PATIENTS NOTIFIED (NEW AND RETREAT) 540 445 431 420 10 7 4 9 2 322 1 780 1 582 1 518 954 688 687 648 7 920 8 394 10 100 8 140 6 357 5 554 5 118 5 246 1 144 1 115 1 044 987 2 160 1 390 1 385 1 420 3 302 2 649 2 407 2 280 1 144 695 619 37 61 54 69 1 007 678 600 605 424 359 381 519 329 341 290 361 327 325 274 5 374 5 116 4 942 6 448 5 796 5 533 4 974 6 045 4 330 4 316 4 238 767 489 489 % OF HIV% OF HIVNUMBER OF POSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT 5 100 100 100 100 2

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Albania 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS 1 0 2 7 0 0 0 6 17 49 79

% OF TESTED TB PATIENTS HIV-POSITIVE 1.2 0 1.2 3

• 15 Andorra

55 •

– Armenia

11 •

• 12 Austria

100 •

0 2.2 1.4 3.3 5.2

83 47 80 70

33 41 80 70

0

– Azerbaijan

–

– Belarus

96 •

75 74 96 93 100 100 82 87 81 56 0 4.7 3.9 0.7 67 71 66

6 290 7 448 7 849 5 153 5 118 5 246 937 969 845 556 0 65 56 23 1 773 1 698 1 513

– Belgium

100 •

• 82 Bosnia and Herzegovina – Bulgaria

56 •

4•

0 0 0 2 5 3 1 4 0

0 0 0.11 0.29 0.2 0 0 0 100 100 100

0

•1 Croatia

66 •

1 3

– Cyprus

–

0

0

1 2 5 4 6 8 0 10 33 34 46 45 3 3 3 1.1 2.8 2.6 4.4

•0 Czech Republic

–

• 19 Denmark

22 •

19 26 26 22 0 73 94 91 92 93 0.83 0.92 0.92

189 177 153 136 0 277 490 298 315 271 3 3 3

3.6 6.7 11 15 17 100 100 100 0 47 61 62

– Estonia

–

• 94 Finland

93 •

•1 France

–

24 27 10 32 46 38

1 233 1 354 674 1 841 2 550 1 881

121 95 13 35 50 33

9.8 7 1.9 1.9 2 1.8 54 63 56 79 100 77 76 79

– Georgia

–

• 10 Germany

38 •

61 97

– Greece

–

– Greenland

–

– Hungary

–

<0.1 <0.1 91 95 100 100 6.1 23 30 27 85 90 92 99

1 1 10 21 9 11 28 98 128 97 316 308 384 503

– Iceland

–

• 91 Ireland

100 •

•6 Israel

27 •

• 85 Italy

99 •

116 115 84 2 024 1 741 1 445 1 223 11 22 9 11 461 427 425 366 372 343 418 509 4 137 3 249 3 521 40 429 28 550 26 304 21 523 6 765 6 295 6 666 6 916

1 1 1 1 0 0 11 15 21 14 17 13 24 16

100 100 10 4.8 0 0 39 15 16 14 5.4 4.2 6.2 3.2 100 0

100 100 100 0

– Kazakhstan

–

• 77 Kyrgyzstan

98 •

77 84 85 98 2.9 100 100

31 187 23 854 22 480 21 184 183 6 666 6 916

183 333 352 441 183 153 151

0.59 1.4 1.6 2.1 100 2.3 2.2

41 26 20 16 68 60 67

7.7 7.5 9.1 58 37 86 78

1 063 1 329 862

–

100 •

4 5

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

245

european region

48 36 129 139 190 217 229 52 66 44 43

0.76 0.48 1.6 3.7 4.2 4.4 5.5 6.8 5.2 7.7

61 49

62 41 21 257 32 258

29 67

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 85 85 85 85 1 226 794 752 844 PATIENTS NOTIFIED (NEW AND RETREAT) 1 443 934 885 993 2 574 1 938 1 904 1 781 37 29 26 45 23 32 33 43 1 % OF HIV% OF HIVNUMBER OF POSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT 55 76 66 57

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Latvia 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS 53 71 71 114 7 19

% OF TESTED TB PATIENTS HIV-POSITIVE 4.3 8.9 9.4 14

• 85 Lithuania

85 •

41 39

– Luxembourg

–

– Malta

–

•4 Monaco

98 •

4.3 81 91 98

1 26 30 42

0 3 5 4

0 12 17 9.5

0 4

– Montenegro

–

•5 Netherlands

77 •

• 22 Norway

42 •

4.7 74 82 77 22 38 49 42 0

8 84 92 82 252 413 490 407 0

170 114 112 107 1 157 1 073 1 007 958 290 339 361 9 280 7 509 8 478 7 542 3 536 2 626 2 540 2 590 6 278 5 447 5 341 5 341 29 347 21 078 19 212 18 224 154 379 162 553 159 479 149 921

0 1 0 0 61 48 31 28

0 1.2 0 0 24 12 6.3 6.9

0

100

21

•0 Poland

–

3 0.29 0.31 0.34 70 65 86 65 100 95 94 100 37 37 50 53 55 22 26 26 2 485 1 720 2 185 1 672 6 469 5 192 5 017 5 348 10 860 7 833 9 608 9 699 85 537 84 669 79 494 75 995 22 26 571 303 315 291 9 308 285 303 160 241 244 229 3 533 3 633 4 104 4 880 100 100 23 18 14 17 0.14 5.9 5.7 5.7 1.5 3.1 2.5 2.4 4.1

– Portugal

0•

100

100

• 70 Republic of Moldova • 103 Romania

65 •

9.7

31 34

0

100 •

• 37 Russian Federation • 55 San Marino

53 •

41 59 76

89 90 90 200

133 145 174

–

– Serbia

–

•0 Slovakia

2•

• 95 Slovenia

93 •

• 38 Spain

75 •

<0.1 0.67 3.2 2 95 100 99 93 38 76 77 75 69 68 70 0

3 16 72 39 720 439 395 322 107 130 147 104 4 909 4 569 4 179 0

– Sweden

70 •

•0 Switzerland

–

– Tajikistan

–

•9 The Former Yugoslav Republic of Macedonia •0 Turkey

92 •

41 •

•0 Turkmenistan

59 •

8.9 53 82 92 0.3 9.3 12 41 0 3.5 46 59 100

670 4 049 6 241 6 375 2 39 45 145 0 581 7 241 8 646 3 230

3 468 2 385 2 216 1 917 760 439 399 345 278 172 192 138 8 359 7 089 6 762 5 991 569 675 586 632 563 548 578 463 7 526 7 641 7 609 6 929 658 420 362 355 21 303 16 551 15 679 14 691 3 291 3 230

3 12 6 6 1 1 0 0 0 1 0 0 456 414 370

100 75 8.3 15 0.14 0.23 0 0 0 0.77 0 0 9.3 9.1 8.9

430 0 0 0 0 100

400 100 100 100 100 100

4

0 0

1 100 115 88 2 0 0 0 0 14 29 45 0

0.15 2.5 1.8 1.4 100 0 0 0 2.4 0.4 0.52 0

0 73 70 80 0

0 54 57 89 100

0 315 157 0 0 0

36 48 49

64 93 78

– Ukraine

–

– United Kingdom of Great Britain and Northern Ireland – Uzbekistan

75 •

95 74 75

34 621 31 776 34 181

–

• 124

100 •

120 100 100 100

35 801 20 330 15 913 16 810

39 608 36 409 42 676 45 569 8 633 8 483 8 963 8 751 28 891 20 330 15 913 16 810

1 526 5 752 4 157 4 726 378 326 147 427 546 820

0 17 13 14 39 63 71 5 029 14 352

72

0.41 2.1 3.4 4.9

0 92 96 95

0 37 32 13

2 630 2 010

246

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 161 186 194 172 9 4 1 4 576 361 439 420 570 203 257 254 453 801 569 b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB 75 76 87 76 150 100 100 100 99 87 96 94 110 99 95 93 29 19 25 – – 90 94 90 89 97 94 95 100 100 99 97 40 85 62 71 100 – 96 – 84 70 96 93 100 97 96 93 140 98 100 – 110 100 100 100 85 96 97 99 47 120 73 – 53 80 83 84 98 110 91 89 170 37 44 – – – – – 62 92 73 79 140 120 80 100 110 130 85 97 110 120 99 98 – – – – – 100 83 140 20 14 – 99 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

Albania

Andorra

Armenia

Austria

Azerbaijan

Belarus

Belgium

Bosnia and Herzegovina

Bulgaria

Croatia

Cyprus

Czech Repub ic

Denmark

Estonia

Finland

France

Georgia

Germany

Greece

Greenland

Hungary

Iceland

Ireland

Israel

Italy

Kazakhstan

Kyrgyzstan

2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

1 2 5 1 0 0 0 0 162 177 79 92 13 15 19 27 800 552 811 596 1576 1594 1604 11 19 15 20 11 2 7 7 47 56 55 49 6 0 8 1 0 1 0 13 9 7 4 5 2 3 1 79 63 78 62 3 6 5 3 24 23 40 39 195 359 475 346 105 48 56 64 12 2 5

1.7 (0–4.9)

1.7 (<0.1–9.1)

0 (0–6.3)

0 (0–4.9)

0 (0–4.9)

0 (0–0)

250 (220–280)

82 (61–110)

170 (150–190)

18 (6.7–30)

11 (5.1–20)

7.3 (0.91–21)

2 800 (2 600–3 000)

810 (670–960) 1972 2084 2164 588 466 524 503 1035 600 704 724 482 801 588 687 586 353

2 000 (1 800–2 200)

15 (5.8–25)

6.3 (2.5–13)

8.9 (2.5–21)

13 (2.0–24)

1.6 (<0.1–8.9)

12 (3.2–28)

100 (78–130)

32 (18–51)

73 (52–98)

–

– 16 14 25 40 562 352 392 371 307 209 257 316 197 210 193 198 184 237 206 1291 1187 1232 799 1987 2197 1931 3094 2215 2382 2198 497 115 148

–

1.7 (0–5.0)

1.7 (<0.1–8.8)

0 (0–5.1)

9.8 (2.3–17)

7.3 (2.7–16)

2.5 (<0.1–12)

–

–

–

70 (56–85)

42 (31–56)

28 (20–36)

2.7 (0–5.6)

2.7 (0.55–7.6)

0 (0–4.2)

–

–

–

630 (570–690)

260 (220–300)

370 (330–420)

62 (44–81)

37 (25–52)

26 (13–43)

– 1 1.6 (1.0–2.2) 26 19 30 12 0 0 0 1 3 2 3 5 16 12 11 17

–

–

1.4 (0.69–2.0) 442 474 411 411 7 19 4 4 200 200 176 190 259 245 275 318

0.24 (0.18–0.29)

31 (15–46)

23 (11–42)

7.3 (3.0–14)

1.0 (1.0–1.0)

0 (0–4.2)

1.0 (<0.1–1.0)

1.8 (0–4.4)

1.8 (0.22–6.6)

0 (0–4.9)

22 (12–32)

19 (11–30)

3.7 (0.48–8.5)

– 7387 7408 7608 989 566 806 958

– 5214 5293 8154 837 225 1659

–

7 000 (6 900–7 200)

2 700 (2 600–2 800)

4 300 (4 300–4 400)

1 800 (1 600–2 000)

1 100 (910–1 200)

730 (690–770)

a

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). b BACT+VE = bacteriologically positive cases.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

247

european region

2 200 (2 100–2 200)

1 200 (1 100–1 300)

960 (920–1 000)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB 12 28 19 63 11 61 15 52 – 0 – 1 100 0 – 182 56 99 22 90 24 91 23 16 62 15 52 11 55 25 62 366 11 960 48 151 7.0 – – 1697 150 948 88 1183 84 41 60 52 60 35 59 53 68 106 68 47 47 41 63 66 55 691 340 165 47 145 41 142 45 61 65 – 40 – – 0 0 0 – 2 67 2 33 20 59 28 55 16 52 26 65 18 62 30 65 14 64 – 71 76 61 77 52 68 46 82 22 100 7 47 8 62 14 78 112 30 91 29 110 42 – 515 24 558 40 675 52 541 45 251 51 184 50 148 49 116 47 0 0 15 34 11 31 – – – – – 88 25 80 31 68 31 31 37 1 100 0 – 0 0 1 100 10 25 22 71 15 56 17 68 6 86 2 50 9 90 6 55 – – – – – 4655 51 4790 80 10443 130 152 18 264 27 – 831 78

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 873 613 562 666 1293 959 1031 1017 36 17 7 0 11 11 17 13 1 – 2 0 1 0 7 11 15 11 3 8 4 6 72 30 41 31 28 19 22 17 338 1082 1001 894 530 502 530 500 13692 13785 13612 – 82 61 57 58 709 741 695 628 193 139 229 5409 3238 4416 4073 1407 982 1155 1219 536 1381 1379 1264 1594 3338 3855 3645 35862 34007 32647 b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB 100 100 96 97 100 100 100 100 110 120 100 – 140 220 89 81 – – – – 88 100 100 98 130 160 99 99 150 100 97 – 120 81 88 90 77 77 73 72 32 49 74 67 13 39 41 40 – 72 78 79 – – – – 76 67 91 84 82 100 92 95 110 100 100 100 – 34 24 21 150 100 100 100 150 130 98 98 – 7.0 7.4 45 51 110 72 81 38 64 63 71 – 7.0 – – – 66 61 77 100 150 95 97 0 60 9.5 56 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

Latvia

2005 2010 2011 2012 Lithuania 2005 2010 2011 2012 Luxembourg 2005 2010 2011 2012 Malta 2005 2010 2011 2012 Monaco 2005 2010 2011 2012 Montenegro 2005 2010 2011 2012 Netherlands 2005 2010 2011 2012 Norway 2005 2010 2011 2012 Poland 2005 2010 2011 2012 Portugal 2005 2010 2011 2012 Republic of 2005 Moldova 2010 2011 2012 Romania 2005 2010 2011 2012 Russian 2005 Federation 2010 2011 2012 San Marino 2005 2010 2011 2012 Serbia 2005 2010 2011 2012 Slovakia 2005 2010 2011 2012 Slovenia 2005 2010 2011 2012 Spain 2005 2010 2011 2012 Sweden 2005 2010 2011 2012 Switzerland 2005 2010 2011 2012 Tajikistan 2005 2010 2011 2012 The Former 2005 Yugoslav Republic 2010 of Macedonia 2011 2012 Turkey 2005 2010 2011 2012 Turkmenistan 2005 2010 2011 2012 Ukraine 2005 2010 2011 2012 United Kingdom of 2005 Great Britain and 2010 Northern Ireland 2011 2012 Uzbekistan 2005 2010 2011 2012 a

160 87 105 110 338 310 296 271 0 0 2 0 0 1 0 0

120 (100–140)

87 (69–110)

36 (26–48)

300 (270–330)

150 (120–170)

150 (140–170)

0 (0–0.98)

0 (0–0)

0 (0–0.98)

0 (0–0)

0 (0–7.2)

0 (0–0.98)

–

0 (0–0)

0 (0–5.0)

0 (0–6.8)

9.1 (3.5–15)

7.4 (3.5–13)

1.8 (<0.1–9.0)

–

–

–

48 (31–65)

30 (18–47)

18 (9.0–32)

35 (21–50)

25 (15–41)

9.7 (3.2–22)

1 700 (1 600–1 800)

810 (730–890)

930 (880–980)

800 (610–980)

320 (210–480)

480 (350–630)

46 000 (43 000–49 000)

20 000 (18 000–22 000)

25 000 (23 000–28 000)

– 9 12 9 9 8 1 5 4 1 0 0 0 49 41 37 4 18 17 14 5 9 8 8 333 604 694 4 7 1 4 191 250 262 291 38 158 – 5336 4305 6934 39 60 81 81 86 1023 1385 1728

– 1112 811 863 716 248 185 147 142 217 123 171 114 1009 1013 802 425 288 375 453 326 270 304 246 160 161 919 106 153 130 155 3237 4342 4221 4742 81 306 – 9194 10352 11185 3428 3970 4549 4570 0 2845 484 2703

–

20 (7.0–33)

13 (4.9–29)

6.5 (1.3–18)

1.8 (0–5.3)

0 (0–6.2)

1.8 (<0.1–9.3)

0 (0–0)

0 (0–3.5)

0 (0–3.7)

31 (13–49)

8.5 (1.0–31)

22 (10–41)

11 (5.0–18)

8.1 (4.1–14)

3.2 (0.40–11)

8.6 (2.4–15)

2.6 (0.53–7.4)

6.1 (1.7–14)

910 (800–1 000)

490 (390–620)

420 (390–450)

4.8 (0.47–9.1)

0 (0–5.7)

4.8 (1.4–11)

520 (460–580)

270 (230–310)

250 (220–290)

–

6 800 (6 500–7 000)

4 100 (3 900–4 300)

2 600 (2 600–2 700)

69 (54–85)

54 (42–70)

15 (8.1–25)

4 000 (3 700–4 300)

2 400 (1 800–3 000)

1 600 (1 400–1 900)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB 182 89 102 94 82 85 100 88 440 96 360 99 369 100 350 100 – 0 – 1 100 1 100 – 2 67 0 0 1 100 – – – – 14 52 12 100 13 110 5 38 30 68 29 67 22 58 28 57 8 57 21 50 22 59 – – 468 52 577 60 535 61 172 49 94 41 97 45 102 54 652 37 1140 67 1006 68 933 63 1300 19 2011 39 2171 46 1864 43 – 13405 29 13620 25 12324 24 – – – – 121 40 113 56 100 62 83 46 56 52 32 58 29 58 27 55 28 97 9 82 11 100 12 86 – 110 34 96 26 69 22 17 57 24 46 31 69 24 62 30 61 33 82 40 74 31 66 – 223 23 415 45 496 66 19 18 28 54 25 45 26 84 508 20 615 45 602 48 641 55 – 63 77 156 – – – 4840 95 4413 38 5925 72 271 59 247 43 234 45 244 51 435 4.8 1180 26 123 11 798 30

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). b BACT+VE = bacteriologically positive cases.

248

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO 1.8 2.1 3.4 2.7 2.9 2.5 – – 0.67 – – – 5.0 5.5 6.0 3.9 4.2 4.6 2.1 2.5 3.5 2.0 2.2 1.9 2.9 9.2 3.1 3.2 – 2.7 – – 4.1 3.3 3.0 3.1 2.6 2.6 1.7 2.0 3.4 1.6 1.7 1.4 1.2 1.4 1.4 1.5 – 1.6 2.3 2.7 2.7 2.6 2.0 – 2.1 2.7 1.5 – 1.0 – 7.0 0.60 2.7 1.1 2.2 2.7 3.2 2.6 3.8 2.5 2.3 1.4 1.7 1.6 2.5 – – 3.3 2.2 3.3 2.4 3.4 1.6 2.0 1.9 2.6 1.9 2.1 2.1 2.1 1.8 1.7 2.0 – 2.0 2.9 2.9 3.9 3.4 3.0 2.4 – 1.9 1.9 1.6 1.9

Albania

Andorra

Armenia

Austria

0

0

4

230

223

170

176

95

48

0

8

115

89

35

50

35

23

0

Belarus

Belgium

Bosnia and Herzegovina

0 1 0 3 3 1 4 8 3 0 4 1 1 2 1 0 9 1 2 0 6 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 5 0 0 0

71 65 53 44 23 20 26 20 25 25 15 56 22 27 33 23 13 98 40 38 46 38 24 10 12 1 3 2 0 0 10 7 8 12 10 7 7 10 12 8 5

180 173 156 174 49 57 50 39 50 33 61 82 58 37 32 32 16 150 115 100 89 97 27 19 5 1 1 1 3 4 22 31 24 19 29 21 16 20 12 22 14

273 224 228 250 63 39 32 30 33 18 90 99 61 34 52 58 20 195 143 110 130 210 48 18 20 0 1 0 4 2 83 52 57 36 20 24 28 24 18 10 18

287 293 290 266 52 55 27 29 25 27 140 66 78 61 75 74 3 195 133 122 131 132 72 38 31 1 1 0 0 1 88 89 55 29 38 42 18 16 23 13 32

118 163 138 158 54 32 15 21 18 22 139 58 44 46 61 62 9 150 90 92 82 178 47 25 31 1 0 0 0 1 53 61 45 29 28 33 9 11 9 16 16

62 58 48 73 102 56 47 19 27 18 100 77 80 51 62 92 10 136 65 61 57 141 34 24 21 2 1 0 1 0 90 59 46 19 24 22 11 14 7 2 4

0 0

0 0 0 0

1 0 0 1

1 3 1 3 6 2 6 3 5 0 4 2 0 3 0 0 9 3 2 0 10 1 1 0 0

25 28 37 34 12 15 27 13 13 23 40 30 35 27 17 33 11 90 42 41 37 50 12 3 12 1 1 0 1 3 9 15 3 6 4 3 7 16 11 4 5

53 52 67 64 24 15 31 18 14 23 67 46 39 19 27 26 14 111 59 40 50 57 18 8 14 1 0 3 0 2 11 13 14 10 9 11 13 15 5 5 5

50 56 47 47 32 19 15 19 9 17 64 29 33 16 17 21 7 59 43 36 44 57 15 4 14 1 0 1 2 1 20 9 16 11 4 8 8 14 13 15 9

43 37 39 45 17 4 12 11 3 9 49 29 28 10 13 10 3 29 23 28 24 38 11 2 8 2 0 0 0 0 13 10 7 7 4 3 4 6 9 8 7

11 28 27 28 10 13 4 5 5 7 77 48 28 18 25 25 4 37 15 14 16 60 6 1 7 0 0 0 0 0 19 7 5 2 3 7 3 7 3 8 2

62 91 83 93 34 27 23 10 7 5 23 124 130 94 128 116 6 70 34 30 35 130 56 30 26 1 0 0 0 1 88 57 28 20 15 26 2 8 5 4 7

0 0

0 0 0 0

0 0 0 1

Bulgaria

0 0 0 0

0 0 0 0

Croatia

0 0

0 0

Cyprus

0 0 0 0

Czech Republic

0 0 0 0

Denmark

0 0 0

0 0 0 0 0 0 0 0 0 1 2 5 2 0 0

0 1 0 0

0 0 0 0

0 0 0

Estonia

Finland

France

0 0 0 0 0 1 0 1 0 0 0 30 10 12 10 12 2 4 0 5 5 4 14 6 1 1 4

6 9 3 4 6 1 3 5 10 1 2 156 136 127 60 88 20 76 226 340 271 200 179 59 43 43 43

31 25 7 22 15 10 8 4 6 4 9 431 248 212 139 112 30 111 272 529 478 314 453 113 92 96 99

53 19 21 16 13 25 22 3 8 4 7 502 247 222 114 116 25 113 268 341 333 248 539 171 97 106 113

56 40 25 14 21 28 19 14 9 7 5 414 211 196 99 94 40 63 207 264 251 235 460 167 141 141 147

35 12 12 18 17 24 28 11 8 11 9 297 125 134 76 73 18 45 76 143 139 150 442 92 87 69 105

15 7 8 13 9 61 53 25 18 27 21 496 244 205 110 101 12 28 60 77 93 81 625 167 136 131 99

0 0 0 0

0 0 0 0

0 0 0

0 0 0 0 0 1 0 0 0 1 1 36 18 16 10 7 2 1 4 5 8 5 17 4 3 2 5

9 6 3 4 5 1 1 3 3 2 4 138 108 104 47 58 8 49 109 135 136 101 115 51 44 44 49

11 11 5 8 7 6 5 4 2 3 0 226 127 134 76 67 17 37 105 118 132 116 251 104 63 92 99

14 8 3 12 2 7 3 1 4 5 4 176 89 82 49 48 17 33 58 62 59 72 167 73 61 59 37

11 11 3 3 4 4 4 0 1 3 2 90 46 56 45 36 18 17 46 52 32 43 89 43 38 54 47

4 6 6 3 1 10 6 6 2 1 3 92 43 38 25 23 7 10 17 28 35 32 104 37 26 26 24

10 8 3 6 5 65 49 20 11 13 11 365 155 180 97 65 5 5 47 41 54 47 397 103 76 86 55

0 0 0 0

0 0 0 0

0 0 0

Georgia

0 0 0

0 0 0

Germany

0 0 0 0

0 0 0 1

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

249

european region

Azerba jan

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

0 2 0 0 0 0 0 0 0 0 0 1 2 3 0 0 1 4 1 1 0 0 1 0 0 77 0

0 19 26 28 29 33 0 0 0 0 0 18 152 170 36 28 23 37 17 32 4 8 5 13 9 109 328

0 21 21 17 26 34 1 1 0 0 0 16 130 104 75 65 67 95 30 23 4 11 8 29 24 297 371

0 14 16 14 18 16 0 1 0 0 0 11 131 83 49 52 60 82 59 22 12 9 7 14 33 215 267

19 24 31 16 30 15 0 0 0 1 0 10 63 84 68 71 56 89 42 41 13 13 19 6 42 209 280

40 19 20 16 9 11 0 0 0 0 1 8 26 30 27 42 34 71 23 24 8 11 9 4 30 187 30

30 16 37 15 22 23 0 0 0 0 1 1 21 24 15 8 18 73 41 30 10 13 13 1 0 88 27

0 0 0 0

0 3 0 2 1 0

1 11 3 11 14 17

0 10 9 7 10 9

0 8 5 6 6 6

13 8 5 3 2 3

20 5 5 2 1 6

16 11 18 8 12 12

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0 1 1 3 1 0 0 6 1 0 1 0 1 0 0 90 3

1 0 0 0 1 24 27 24 19 13 22 11 13 5 11 10 5 3 64 141

1 0 0 0 7 27 21 17 16 19 52 22 11 4 6 8 18 3 98 100

1 0 0 0 2 24 10 4 9 12 32 12 8 2 4 4 0 6 47 57

0 0 0 0 1 8 11 7 7 2 21 11 3 2 1 4 0 3 32 73

0 0 0 0 1 8 4 8 7 5 18 6 5 5 3 1 0 0 24 9

0 0 0 0 4 7 8 5 5 59 22 10 6 4 5 0 0 24 18

0 0 0 0

0 0 0 0

0 0 0 0

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO – 2.7 1.8 2.8 2.8 – – – – 2.2 1.3 1.8 – 2.9 3.2 2.3 2.7 2.0 1.0 – – 2.0 – 1.0 – 0.74 1.8 2.1 1.6 2.0 – 2.0 1.4 2.3 2.2 1.4 2.0 2.3 1.8 1.2 1.5 – – 1.6 1.7 1.6 1.6 1.7 2.3 1.6 1.4 1.4 1.4 1.6 1.2 3.4 3.1 3.0 2.6 3.1 3.8 2.9 2.8 3.0 2.6 3.1 – – 1.6 – 3.0 – 0.25 – – 3.0 6.0 3.5 – – – – – – 1.9 0.86 2.0 1.8 2.0 2.0 2.4 2.1 2.6 1.7 1.6 2.1 1.8 1.9 0.82 – 2.2 2.4 2.2 2.6 2.5 2.6

Greece

Greenland

Hungary

Iceland

Ireland

Israel

Italy

Kazakhstan

Kyrgyzstan

Latvia

Lithuania

Luxembourg

Malta

Monaco

Montenegro

Netherlands

Norway

Poland

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

1 1 1 2

10 14 19 30

22 25 27 30

32 22 20 26

24 14 18 24

19 12 19 19

46 23 22 38

5 3 2

0 0 3 1

2 13 2 9

9 18 13 14

10 8 4 9

5 7 4 3

6 2 4 5

25 17 15 20

0 1 1

0 0 0 0 0 1 0 2 0 0 0 0 0 0 1 0 0 1 0 1 1 0 0 9 12 8 14 0

5 10 6 8 6 9 11 7 0 0 0 0 0 10 6 8 7 7 20 4 13 29 9 59 63 93 40 51

7 2 3 24 24 15 18 15 0 0 1 0 0 7 10 18 9 9 26 15 28 30 33 202 96 191 75 88

5 0 5 85 67 36 34 29 0 1 0 0 0 7 21 4 10 9 23 18 12 11 20 157 75 137 66 81

5 3 1 104 117 51 46 64 0 0 3 0 1 6 10 11 11 9 23 15 8 5 3 94 58 101 32 52

2 3 5 58 67 52 53 41 0 0 0 0 0 4 7 5 7 12 13 5 4 9 6 124 54 61 31 24

2 1 1 27 39 23 28 25 1 1 0 0 0 12 6 11 8 4 38 26 6 9 13 289 112 115 58 59

0

1 0 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 7 6 3 25 5

5 8 3 7 5 9 3 8 0 0 0 0 0 13 9 7 8 5 10 6 1 10 4 52 38 80 41 41

0 1 0 17 13 16 9 14 0 1 0 1 0 1 8 10 8 7 6 16 14 8 10 20 93 58 145 57 73

0 1 3 19 11 14 8 15 0 0 1 0 0 13 3 2 7 6 6 7 10 7 11 57 33 56 41 37

4 2 1 22 22 9 9 11 0 0 0 0 0 6 3 3 8 4 3 7 2 4 4 40 13 25 22 18

2 3 0 10 15 15 12 14 0 0 0 0 0 7 0 2 2 2 3 5 0 4 2 51 19 19 22 14

0 0 3 30 33 20 29 28 1 0 0 1 0 15 8 5 1 2 32 19 10 7 17 168 39 70 54 43

0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0

24 2 0

9 6 1

36 31 15 6 9 3 4 1 5 6 4 0 0 1 0 0 0 4 1 0 1 1 0

1 057 917 675 602 508 109 128 247 261 225 210 20 53 22 20 11 19 46 38 42 34 25 35

1 409 1 142 754 716 586 171 227 303 260 204 255 44 106 71 44 42 62 132 97 118 75 52 73

1 379 983 595 516 514 165 205 269 188 179 207 71 124 104 65 58 67 225 145 186 128 126 143

923 795 511 515 479 65 115 194 141 168 184 70 111 117 71 50 59 176 155 187 157 158 148

439 274 251 235 233 38 52 66 64 77 86 40 64 55 39 33 36 90 74 108 89 77 91

218 175 127 91 98 30 46 84 48 41 30 30 34 34 15 18 15 77 68 67 54 55 60

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

84 46 33 15 16 1 6 15 5 13 8 0 2 0 0 0 1 5 0 1 1 0 1

999 751 566 439 415 70 128 215 223 200 195 22 25 17 6 7 14 6 20 25 20 20 8

1 079 767 520 495 411 94 146 236 199 191 173 49 41 31 19 16 15 53 37 41 36 31 28

599 436 263 260 241 34 100 141 98 84 108 55 27 31 25 19 14 45 39 57 31 37 55

275 286 205 190 177 18 41 70 71 60 55 47 28 23 12 14 16 32 32 49 43 38 36

202 121 122 109 97 15 30 33 40 50 42 27 7 18 10 12 15 16 22 23 18 16 20

204 187 132 117 100 19 29 98 42 39 37 29 15 12 13 13 9 42 48 54 32 45 28

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0 0 0 0 0 0 1

0 0 1 0 0 1 1 0 2 2

2 0 0 0 0 0 1 3 4 2

2 0 0 0 1 1 1 0 0 2

1 0 1 0 0 1 1 0 0 0

1 0 1 0 0 0 1 0 0 0

2 0 0 0 0 1 0 0 0 0

0 0 0 0

0 0 0 0 0 0 0 0 0

0 0 1 0 0 0 0 1 1

2 0 0 0 1 0 1 0 1

1 0 0 0 0 0 0 0 0

1 0 0 0 0 0 0 0 0

1 0 0 0 1 0 0 0 0

0 0 0 0 2 0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0 22 0 0 0 2 1 0 0 0 0 0 3 1 3 3 5 1

3 1 1 3 79 34 23 22 22 15 4 1 9 9 3 122 99 109 70 69 82

5 1 2 4 119 63 42 29 35 31 8 9 4 9 7 295 303 199 205 187 183

7 4 8 5 75 41 23 22 19 14 6 3 6 7 3 795 812 389 310 314 306

15 4 11 10 28 25 26 20 23 18 3 6 4 1 3 565 782 639 574 560 471

4 7 7 3 9 10 14 9 14 9 5 2 4 4 1 369 361 292 393 439 438

8 1 3 4 10 21 19 17 13 15 12 4 3 2 1 377 434 310 237 275 267

0 0 0 0

0 0 0 0

0 0 0

0 1 1 0 24 4 3 1 2 4 0 1 0 0 0 4 1 3 2 1 1

0 3 4 4 56 29 14 9 13 7 4 3 4 5 14 129 99 95 59 67 54

7 3 2 5 50 22 19 14 13 18 7 1 7 7 6 163 158 142 118 96 96

3 2 4 1 13 16 11 13 7 15 2 2 3 0 225 211 112 82 90 106

4 3 3 2 10 9 9 5 7 4 0 1 2 1 111 170 151 104 130 102

0 1 1 1 8 5 1 4 4 6 3 2 0 0 0 107 82 63 82 99 100

8 8 1 3 7 10 4 11 3 6 8 5 3 0 1 414 421 316 245 255 226

0 0 0 0

0 0 0 0

0 0 0

0 0 0 0

0 0 0 0

250

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO 2.6 2.8 2.9 2.7 2.8 2.5 3.3 1.1 3.8 3.5 3.6 3.3 2.6 2.5 2.5 2.4 2.3 2.4 – 6.7 – 2.8 2.7 2.7 – – – – – – 1.6 1.3 1.6 1.4 1.8 – 1.9 1.8 1.8 2.7 2.6 2.3 2.1 2.5 1.8 3.0 1.8 1.9 2.6 – 2.1 1.9 1.8 2.1 1.2 1.5 1.3 1.5 1.6 1.6 2.0 1.5 1.5 1.3 1.9 1.4 – – 1.2 1.3 1.2 1.2 1.5 1.5 1.7 2.1 1.9 1.5 – – 2.7 2.5 2.4 2.5 1.3 1.6 1.8 1.8 – – 3.9 3.3 – 2.9 2.9 3.0 – 1.5 1.6 1.5 1.6 1.7 – 1.5 1.4 1.3 1.2 1.3

Portugal

Republic of Moldova

Romania

Russian Federation

San Marino

Serbia

Serbia & Montenegro Slovakia

Slovenia

Spain

Sweden

Switzerland

Tajikistan

The Former Yugoslav Republic of Macedonia

Turkey

Turkmenistan

Ukraine

United Kingdom of Great Britain and Northern Ireland

Uzbekistan

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012 1995 2000 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

11 8 5 3 3 1 0 2 2 0 2 0 387 46 36 21 19 17 1 8 15 17

215 147 85 55 56 56 55 52 211 119 94 99 1 662 832 752 669 623 556 295 2 228 1 826 1 568

363 375 227 110 87 103 115 31 337 243 257 234 2 322 1 508 1 511 865 813 764 526 6 276 5 726 5 472

328 349 284 199 177 187 166 36 345 244 250 256 3 608 1 799 1 786 1 336 1 192 1 297 596 5 571 5 338 5 115

200 208 181 152 172 153 95 13 313 248 267 284 2 587 1 684 1 999 1 293 1 104 1 053 402 5 361 4 928 4 446

173 140 90 70 75 79 65 13 106 113 107 131 1 751 916 952 895 837 831 151 2 787 2 664 2 629

164 140 93 76 74 75 15 6 31 21 21 31 784 533 638 567 541 495 54 920 845 839 1

5 0 3 1

0 0 0 0

4 0 0 0

7 5 7 3 4 6 2 1 3 6 3 3 355 53 55 40 26 22 1

139 114 67 54 43 52 42 16 97 47 66 58 1 352 701 758 503 475 431 43 1 247 1 139 997

172 154 109 62 58 62 38 32 92 90 79 95 1 240 766 780 477 513 433 73 2 554 2 394 2 292

87 87 66 54 56 66 31 45 57 46 51 48 871 484 493 400 407 371 74 1 719 1 643 1 595

33 41 29 36 30 28 19 23 61 47 41 56 479 341 374 275 214 188 38 1 182 1 166 1 081

42 25 11 10 12 19 10 14 23 23 20 26 396 207 219 172 196 184 31 745 719 637

85 64 42 28 25 32 12 6 18 20 14 25 417 321 442 438 426 435 44 790 752 748

1 0 1 0

0 0 0 0

2 0 0 0

0 0

28 36 31

0 0

3 2 2 1 10 4 2 0 1 0 0 1 0 0 0 0 0 22 13 6 15 10 1 0 0 1 1 0 0 0 2 0 2 0

62 76 60 70 108 18 6 3 7 6 2 13 3 4 4 3 2 132 166 139 135 112 5 9 7 10 14 8 12 5 8 6 8 3

96 70 73 72 204 44 15 13 7 8 9 39 11 10 7 9 6 337 394 306 325 259 12 10 21 28 15 16 23 17 10 12 16 18

118 93 74 77 317 123 31 16 18 6 17 63 36 16 10 16 4 242 367 291 292 299 8 12 16 8 12 8 26 10 11 9 10 8

156 116 122 98 296 108 50 25 17 20 20 36 22 15 9 12 8 150 230 286 277 276 5 11 10 5 8 9 23 7 11 6 13 6

112 83 112 86 350 63 16 25 17 16 12 26 14 11 6 8 6 112 140 146 162 156 4 4 5 5 3 8 13 6 2 5 7 5

132 109 101 77 386 152 32 20 15 13 7 27 17 14 12 5 5 228 230 184 197 220 27 25 16 13 8 13 27 6 7 8 3 11

0 0 0 0

6 5 5 4 11 5 0 0 0 0 0 0 0 0 0 0 0 23 10 14 15 15 0 1 1 2 0 0 1 1 0 0 2 0

69 66 46 46 127 16 5 1 1 2 2 7 3 4 1 0 2 90 142 130 142 101 10 9 10 9 12 11 13 8 6 7 6 7

76 74 59 66 167 17 9 8 6 3 3 24 9 4 5 5 3 129 252 251 249 202 13 8 15 16 9 10 20 11 11 15 13 15

55 46 43 38 133 22 7 9 7 4 4 11 3 6 2 4 0 64 151 151 161 161 5 10 12 11 10 3 9 7 8 6 2 7

49 39 30 31 83 24 5 5 2 6 6 9 4 5 4 2 1 39 63 54 75 70 5 2 5 4 2 7 1 2 3 4 4 1

22 34 20 35 158 33 4 6 3 1 1 5 3 4 1 1 1 34 24 23 30 24 4 2 3 2 2 2 2 1 1 1 2 2

149 164 129 118 275 159 54 27 11 11 13 42 20 16 3 17 9 98 108 76 100 74 14 15 13 3 3 6 15 5 4 3 2 4

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

2 1 2 3

2 0 0 1

0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0

8 12 8 8 2 5 2 0 3 0

308 398 343 346 15 8 14 6 17 16

279 366 365 320 42 14 20 19 11 14

164 214 181 169 45 20 23 24 19 12

104 129 128 124 33 19 20 24 21 19

54 93 75 75 29 20 18 12 10 15

48 74 77 72 24 14 13 11 6 13

0 0 0 0

1 0 0 0

26 23 31 16 2 1 2 0 1 0

225 320 314 243 32 15 17 9 14 12

185 272 229 243 30 14 13 12 9 14

151 111 104 105 20 17 10 7 6 9

89 109 100 99 11 5 7 7 3 6

43 87 105 94 17 5 5 4 1 10

53 82 114 127 17 10 13 6 11 7

0 0 0 0

0 0 0 0

33 23 22 20 1 16 2 1

1 148 631 550 507 11 103 148 130

1 295 779 693 655 188 185 181 212

1 028 703 608 575 0 144 146 183

963 778 696 650 79 127 97 141

534 514 482 476 30 31 51 51

429 407 412 398 0 21 13 26

0 0 0 0

0

50 33 25 30 2 19 3 2

699 485 409 369 15 73 100 112

474 384 385 308 146 140 101 112

243 193 195 168 0 76 72 74

175 141 117 97 47 31 46 46

166 101 121 105 25 34 27 38

213 203 212 227 0 17 8 25

0 0 0 0

0

10 21

385 693

1 076 1 552

2 064 2 385

1 515 2 007

1 087 1 062

437 532 7 417 0

21 41

314 487

380 590

327 447

182 298

185 218

280 405 2 559 0

8 9 8 9 7 3 8 6 25 8 8 10

539 546 86 135 132 137 156 351 596 487 378 360

1 991 2 028 130 200 169 193 184 749 831 574 493 506

2 209 2 393 96 166 135 137 137 510 723 529 453 403

1 796 1 926 87 95 108 97 118 346 522 479 440 449

881 965 75 95 60 69 88 213 263 293 306 313

377 389 138 124 108 100 88 107 313 297 253 273

11 10 9 14 15 19 17 11 40 22 11 9

348 334 95 115 110 120 109 261 538 365 335 319

741 771 114 163 131 129 141 547 597 512 418 367

603 609 60 80 81 75 81 288 375 308 233 237

388 401 31 39 42 45 55 213 288 248 245 201

230 218 31 28 40 26 17 112 217 239 293 261

380 431 67 83 58 49 52 111 367 350 332 322

0 0 0 0

1 0 0 0

0 0 0

0 0 0

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

251

european region

           LABORATORIES SECONDNUMBER OF SMEAR LABS % OF SMEAR CULTURE DST b LABS LPAc LABS LABS US NG LABS PER 5M LINE DST LABS USING PER 100K PER 5M PER 5M a POPULATION POPULATION POPULATION POPULATION XPERT MTB/RIF AVAILABLE LED

FREE THROUGH NTP FIRSTLINE DRUGS

NRLd

TB DIAGNOSIS

TB NOTIF. RIFAMPICIN RATE PER USED 100 000 THROUGHOUT HEALTH-CARE TREATMENT WORKERS

Albania Andorra Armenia Austria Azerbaijan Belarus Belgium Bosnia and Herzegovina Bulgaria Croatia Cyprus Czech Republic Denmark Estonia Finland France Georgia Germany Greece Greenland Hungary Iceland Ireland Israel Italy Kazakhstan Kyrgyzstan Latvia Lithuania Luxembourg Malta Monaco Montenegro Netherlands Norway Poland Portugal Repub ic of Moldova Romania Russian Federation San Marino Serbia Slovakia Slovenia Spain Sweden Switzerland Tajikistan The Former Yugoslav Republic of Macedonia Turkey Turkmenistan Ukraine United Kingdom of Great Britain and Northern Ireland Uzbekistan

0.5 10.2 1.0 0.8 2.1 1.0 0.4 0.5

0 0 0 – 4 2 – 100 0 – – – – 100 100 – 9 – – – 0 100 27 – – 0 0 0 8 100 0 –

1.6 510.5 1.7 3.8 15.4 51.5 17.0 21.3

1.6 510.5 1.7 1.6 4.3 6.3 3.9 9.6

1.6 0 1.7 0.5 4.3 3.6 0 2.7

0 0 0 7 8 19 0 0

No Yes In and out Yes of country In country Yes Yes In country Yes Yes Out of Yes country In country Yes

Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (other criteria) Yes (a l suspects) Yes (a l suspects)

Yes Yes Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes Yes Yes Yes Yes

25

0.4 0.2 0.4 0.2 0.4 0.3 0.3

21.6 0.9 7.7 10.2 18.0 2.3 11.4

8.9 0.9 7.7 0.9 5.5 1.1 5.1

8.9 0.9 7.7 2.8 1.6 2.3 4.5

2 1 20 1 141

In country In country In country In country In country In country

Yes Yes Yes Yes Yes Yes Yes

Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects)

Yes Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes Yes Yes Yes

12

107

0.1 0.3 0.2 0.2 2.9 2.2 0.8 0.4 0.2 0.2

6.0 15.3 10.9 12.4 6.8 10.0 9.7 9.9 9.5 11.7

3.5 15.3 3.3 1.3 6.8 2.7 2.4 9.9 9.5 0

1 15.3 2.2 0.7 3.4 1.8 2.4 3.3 9.5 0

3 0 3 1 4 7 2 7 0 0

Yes Out of Yes country Out of Yes country In country Yes In country Yes In and out Yes of country In country Yes In and out Yes of country Out of Yes country Out of No country Out of Yes country In country Yes In and out Yes of country Yes Yes Yes In and out Yes of country In country No Out of Yes country In and out Yes of country In and out Yes of country Yes In country Yes In country Yes In country Yes Out of Yes country In country Yes Yes Yes

Yes (all suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects)

Yes Yes No Yes Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 204 34

0.2 0.3 0.3 0.2 0.5 1.7 0.5 0.7 0.3 0.1 0.1 <0.1 0.5 1.1 0.3 0.5 1.8

0 – 0 0 – 0 1 – – 0 14 67 – – – 4 0 – – 5 –

8.1 11.1 9.0 10.6 22.2 5.7 20.9 4.1 15.2 6.4 7.3 2.6 14.4 1.9 7.1 10.7 9.4

8.1 1.5 3 6 10.4 5.7 9.9 3.8 2.1 1.8 2.4 2.6 6.3 0.6 2.4 5.1 4.5

0 1.2 4 1.4 4.3 0.9

0 2 3 3 24 0

Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

56

51

0.5 1.8 2.4 2.6 0.6 0 0.6 0

0 2 1 0 14 3 0 18 15

8

34 22 25 61

1.0

1

1.2

0.5

0.5

7

In country Yes

29

a b

LED = Light emitting diode microscopes DST = Drug susceptibility testing c LPA = Line LED = Ligh assay emittin probe p e g d NRL = National ug Reference Laboratory

252

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

             New TB cases Year Source Coverage Percentage Year

Previously treated TB cases Source Coverage Percentage

Albania Andorra Armenia Austria Azerbaijan Belarus Belgium Bosnia and Herzegovina Bulgaria Croatia Cyprus Czech Republic Denmark Estonia Finland France Georgia Germany Greece Greenland Hungary Iceland Ireland Israel Italy Kazakhstan Kyrgyzstan Latvia Lithuania Luxembourg Malta Monaco Montenegro Netherlands Norway Poland Portugal Republic of Moldova Romania Russian Federation San Marino Serbia Slovakia Slovenia Spain Sweden Switzerland Tajikistan The Former Yugoslav Republic of Macedonia Turkey Turkmenistan Ukraine United Kingdom of Great Britain and Northern Ireland Uzbekistan

2012 2011 2007 2011 2007 2012 2011 2011 2012 2011 2011 2011 2011 2012 2012 2009 2012 2012 2010 2010 2012 2012 2012 2011 2012 2011 2012 2012 2011 2012 2012 2012 2011 2012 2011 2012 2004 2011 2012 2012 2012 2001, 2005 2012 2012 2011 2012 2012 2002 2012 2011 2011

Surveillance Surveillance Survey Surveillance Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Survey Surveillance Surveillance Survey Surveillance Surveillance Survey

National National National National Sub-national National National National National National National National National National National National National National National National National National National Sub-national National National National National National National National National National National National National National Sub-national National National National Sub-national National National National National National Sub-national National National National

0.58 0 9.4 3.5 22 35 1.3 0.14 2.3 0.28 4 1.5 1.2 20 1.5 0.45 9.2 1.5 0.87 2.1 0 1.1 4.7 3.9 23 26 11 11 0 0 0 1.6 1.3 0.49 1.5 24 2.8 23 0.84 0 0 0.22 2.4 1.2 13

(<0.1–3.2) (0–98) (7.0–12) (1.6–6.5) (19–27) (33–37) (0.54–2.7) (0–0.79) (1.3–3.8) (<0.1–1.6) (0.10–20) (0.56–3.3) (0.24–3.4) (14–26) (0.30–4.2) (0.24–0.77) (7.9–11) (1.0–2.0) (<0.1–4.7) (1.0–3.8) (0–60) (0.13–3.8) (2.7–7.7) (2.7–5.6) (22–24) (23–30) (8.8–14) (9.5–14) (0–41) (0–25) (0–6.2) (0.77–2.9) (0.27–3.8) (0.30–0.76) (0.86–2.3) (21–26) (1.8–4.2) (21–25) (0.31–1.8) (0–2.6) (0–3.2) (<0.1–0.80) (1.2–4.3) (0.25–3.5) (9.8–16)

2012 2011 2007 2011 2007 2012 2011 2011 2012 2011 2011 2011 2011 2012 2012 2009 2012 2012 2010 2010 2012 2012 2012 2011 2012 2012 2012 2012 2011 2012 2012 2012 2011 2012 2011 2012 2004 2011 2012 2012 2012 2001, 2005 2012 2012 2012 2012 2012 2002 2012 2011 2011

Surveillance Surveillance Survey Surveillance Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Survey Surveillance Surveillance Survey

National National National National Sub-national National National National National National National National National National National National National National National National National National National Sub-national National National National National National National National National National National National National National Sub-national National National National Sub-national National National National National National Sub-national National National National

0 0 43 18 56 69 11 9.8 23 2.5 0 6.3 0 50 0 13 31 10 6.7 8.8 100 0 33 5.4 55 68 32 44 0 0 0 3.6 0 2.1 5.2 62 11 49 3.6 3.7 0 7.1 8.3 13 56

(0–22) (0–98) (38–49) (2.3–52) (50–62) (66–71) (3.2–27) (2.7–23) (17–31) (<0.1–13) (0–84) (0.16–30) (0–23) (35–65) (0–23) (7.4–21) (27–35) (5.5–17) (0.17–32) (3.6–17) (2.5–100) (0–20) (4.3–78) (3.5–8.0) (54–56) (65–72) (23–42) (39–49) (0–98) (0–98) (0–52) (<0.1–18) (0–15) (1.0–3.6) (1.7–12) (59–65) (8.0–15) (44–53) (0.75–10) (<0.1–19) (0–26) (3.3–13) (1.0–27) (3.6–30) (52–60)

0 (0–2.4) 3.2 (2.7–3.7) 3.8 (1.1–9.5) 14 (14–15) 1.3 (1.0–1.7) 23 (18–29)

15 (4.4–35) 22 (19–25) 18 (11–27) 32 (31–33) 5.6 (3.0–9.3) 62 (52–71)

a

Empty rows indicate an absence of high-quality survey or surveillance data. In the absence of high-quality national data, high-quality sub-national data are used.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

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european region

south-east asia region Table A4.1 Estimates of the burden of disease caused by TB, 1990–2012 Table A4.2 Incidence, notification and case detection rates, all forms, 1990–2012 Table A4.3 Case notifications, 1990–2012 Table A4.4 Treatment outcomes, new smear-positive cases, 1995–2011 Table A4.5 Treatment outcomes, retreatment cases, 1995–2011 Table A4.6 HIV testing and provision of CPT, ART and IPT, 2005–2012 Table A4.7 Testing for MDR-TB and number of confirmed cases of MDR-TB, 2005–2012 Table A4.8 New smear-positive case notification by age and sex, 1995–2012 Table A4.9 Laboratories, NTP services, drug management and infection control, 2012 Table A4.10 Measured percentage of TB cases with MDR-TB, most recent year available 257 258 259 260 261 262 263 264 265 266

Estimates of mortality, prevalence and incidence Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See ANNEX 1 for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. The main updates implemented in this report are explained in Box 2.1 of Chapter 2. Estimates published in previous global TB control reports should no longer be used.

Data source Data shown in this annex are taken from the WHO global TB database on 1 October 2013. Data shown in the main part of the report were taken from the database in July 2013. As a result, data in this annex may differ slightly from those in the main part of the report. Data for all years can be downloaded from www.who.int/tb/data.

Country notes Bangladesh Estimates of TB disease burden have not been officially approved by the national TB programme (NTP) in Bangladesh. A joint reassessment by WHO and the NTP will be undertaken following the completion of the prevalence survey planned for 2014.

India Estimates of TB disease burden for India have not yet been officially approved by the Ministry of Health & Family Welfare, Government of India and should therefore be considered provisional.

256

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Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Bangladesh

Bhutan

Democratic People's Republic of Korea

India

Indonesia

Maldives

Myanmar

Nepal

Sri Lanka

Thailand

Timor-Leste

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012

107 120 132 143 151 153 155 <1 <1 <1 <1 <1 <1 <1 20 22 23 24 25 25 25 869 956 1 042 1 127 1 206 1 221 1 237 179 194 209 224 241 244 247 <1 <1 <1 <1 <1 <1 <1 42 45 48 50 52 52 53 18 21 23 25 27 27 27 17 18 19 20 21 21 21 57 59 62 66 66 67 67 <1 1 1 1

66 72 77 74 69 70 70 1 0.55 0.41 0.35 0.11 0.11 0.1 4.7 4.6 4 3 2.5 2.5 2.2 330 370 400 400 320 300 270 95 120 120 84 67 67 67 0.059 0.033 0.015 <0.01 <0.01 <0.01 <0.01 48 53 51 35 26 26 25 7.5 6.1 5 4.9 5.3 5.4 5.5 1.3 1.6 1.9 1.4 0.59 0.41 0.24 11 11 20 15 10 9.5 9.2 0.67 0.62 0.67 0.82

(20–140) (27–140) (29–150) (29–140) (28–130) (28–130) (29–130) (0.410–2.0) (0.230–1.0) (0.180–0.740) (0.160–0.600) (0.068–0.160) (0.068–0.160) (0.062–0.150) (4.3–5.0) (4.2–5.0) (3.7–4.3) (2.7–3.2) (2.3–2.6) (2.4–2.6) (2.1–2.4) (220–480) (240–520) (260–570) (290–530) (210–460) (190–420) (170–390) (33–190) (42–230) (42–220) (34–160) (30–120) (30–120) (30–120) (0.052–0.067) (0.027–0.040) (0.010–0.019) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (17–97) (19–110) (19–100) (15–65) (12–46) (12–45) (12–44) (2.2–16) (2.5–11) (2.2–8.9) (2.1–8.9) (2.4–9.4) (2.4–9.6) (2.5–9.8) (0.750–2.0) (0.970–2.5) (1.1–2.8) (1.0–1.8) (0.480–0.710) (0.330–0.500) (0.180–0.310) (4.9–20) (4.7–20) (7.9–37) (6.6–27) (4.5–18) (4.1–17) (3.8–17) (0.290–1.2) (0.280–1.1) (0.300–1.2) (0.360–1.5)

61 60 58 52 46 46 45 194 109 73 53 15 15 14 23 21 17 12 10 10 9 38 38 39 36 27 24 22 53 61 55 38 28 27 27 27 14 5.4 2 2.3 1.9 2 115 118 106 70 51 49 48 41 29 21 20 20 20 20 7.5 9 10 6.9 2.8 2 1.1 20 19 31 23 16 14 14 67 57 62 74

(18–130) (22–116) (22–111) (20–98) (19–85) (19–84) (19–84) (77–365) (45–200) (31–132) (25–92) (9.5–22) (9.4–22) (8.4–21) (21–25) (19–23) (16–19) (12–13) (9.5–11) (9.6–11) (8.6–9.5) (25–55) (25–55) (25–55) (26–47) (17–38) (16–35) (14–32) (18–106) (21–120) (20–107) (15–70) (12–50) (12–49) (12–48) (24–31) (11–17) (3.8–7.1) (1.6–2.5) (2.0–2.5) (1.7–2.1) (1.8–2.2) (39–230) (41–234) (39–207) (29–129) (23–89) (23–86) (23–84) (12–88) (12–54) (9.4–38) (8.4–35) (8.8–35) (8.8–35) (9.0–36) (4.3–12) (5.3–14) (6.0–15) (5.2–8.8) (2.3–3.4) (1.6–2.4) (0.84–1.4) (8.6–35) (8.0–34) (13–59) (10–42) (6.8–28) (6.2–26) (5.8–25) (29–121) (26–102) (28–109) (33–132)

560 620 670 670 660 660 670 10 6 4.3 3.5 2.2 2 1.7 97 100 110 110 120 120 130 4 000 4 400 4 600 4 100 3 200 3 000 2 800 790 940 990 830 740 730 730 0.67 0.48 0.22 0.23 0.17 0.14 0.22 380 400 400 320 270 260 260 66 61 58 59 64 64 66 20 23 22 22 22 23 23 130 130 180 150 120 110 110 7.2 7.2 7.6 8.4

(220–1 100) (290–1 100) (320–1 100) (330–1 100) (330–1 100) (340–1 100) (340–1 100) (4.7–17) (3.0–10) (2.2–6.9) (1.8–5.7) (1.1–3.8) (0.840–3.5) (0.580–3.3) (26–210) (28–230) (30–240) (31–250) (33–270) (34–270) (34–280) (3 600–4 500) (4 000–5 000) (4 000–5 200) (3 300–5 000) (2 200–4 500) (2 100–4 200) (1 900–3 900) (330–1 400) (400–1 700) (460–1 700) (410–1 400) (360–1 300) (350–1 200) (350–1 200) (0.260–1.3) (0.230–0.820) (0.082–0.430) (0.100–0.410) (0.065–0.310) (0.051–0.280) (0.100–0.380) (170–650) (190–680) (200–670) (170–530) (210–340) (200–330) (200–320) (25–130) (30–100) (26–100) (26–110) (28–110) (28–110) (29–120) (7.4–40) (11–38) (11–36) (10–37) (11–38) (11–39) (11–39) (63–220) (64–210) (86–300) (77–260) (55–210) (51–200) (47–190) (3.1–13) (2.8–14) (3.1–14) (3.8–15)

525 518 507 469 437 435 434 1 860 1 180 754 536 313 269 225 479 479 479 479 494 505 511 465 465 438 365 269 249 230 442 483 474 369 306 301 297 311 197 81 78 51 43 65 894 881 831 647 525 506 489 364 295 248 235 238 236 241 118 125 115 108 108 108 109 227 217 286 236 179 168 159 722 666 689 758

(202–998) (244–893) (243–866) (231–790) (220–727) (220–722) (218–721) (881–3 190) (599–1 960) (392–1 230) (279–875) (149–536) (115–486) (79–446) (130–1 050) (130–1 050) (130–1 050) (130–1 050) (134–1 080) (137–1 110) (139–1 120) (415–518) (414–519) (382–498) (295–443) (181–374) (168–346) (155–319) (186–806) (205–878) (222–821) (183–621) (148–521) (145–512) (144–506) (119–593) (95–336) (30–157) (34–138) (20–96) (15–85) (30–113) (414–1 550) (421–1 500) (415–1 390) (333–1 060) (404–661) (390–637) (377–616) (140–692) (147–493) (113–436) (101–424) (105–425) (103–423) (106–429) (43–231) (63–207) (57–192) (52–185) (52–184) (52–184) (52–185) (111–383) (109–362) (139–487) (117–395) (83–309) (76–296) (71–282) (306–1 310) (259–1 260) (279–1 280) (342–1 340)

240 270 300 320 340 340 350 4.2 2.9 2.3 1.9 1.5 1.4 1.3 77 83 87 91 97 100 100 1 900 2 100 2 300 2 400 2 200 2 200 2 200 370 400 430 450 450 460 460 0.32 0.29 0.17 0.15 0.12 0.11 0.14 170 180 200 200 200 200 200 30 34 38 41 44 44 45 11 12 12 13 14 14 14 78 77 110 100 85 82 80 5 5.4 5.5 5.6

(150–360) (220–320) (240–360) (260–390) (280–410) (280–410) (290–410) (3.6–4.8) (2.5–3.3) (1.9–2.6) (1.6–2.2) (1.3–1.7) (1.2–1.6) (1.1–1.5) (44–120) (48–130) (50–140) (52–140) (85–110) (92–110) (92–110) (1 600–2 200) (1 800–2 300) (2 000–2 500) (2 100–2 600) (2 000–2 500) (2 000–2 400) (2 000–2 400) (270–480) (310–500) (340–520) (360–540) (380–540) (380–540) (380–540) (0.200–0.480) (0.230–0.350) (0.130–0.200) (0.120–0.180) (0.097–0.140) (0.088–0.130) (0.110–0.170) (120–220) (140–230) (160–240) (170–240) (170–230) (170–230) (170–230) (18–44) (27–40) (31–45) (34–50) (36–52) (37–53) (37–53) (7.2–17) (9.9–14) (10–15) (11–16) (11–16) (11–17) (12–17) (65–93) (63–91) (88–130) (84–120) (70–100) (68–98) (66–95) (4.0–6.0) (4.4–6.4) (4.5–6.5) (4.6–6.6)

225 225 225 225 225 225 225 784 561 402 287 206 192 180 383 383 383 383 395 404 409 216 216 216 209 185 181 176 206 205 204 199 189 187 185 150 118 60 51 36 33 41 393 404 412 403 384 381 377 163 163 163 163 163 163 163 66 66 66 66 66 66 66 138 130 171 154 128 124 119 498 498 498 498

(139–331) (184–270) (184–270) (184–270) (185–268) (185–268) (185–268) (673–903) (482–646) (345–463) (247–331) (177–237) (165–222) (154–207) (219–592) (219–592) (219–592) (219–592) (348–445) (372–437) (373–447) (182–254) (189–245) (195–239) (188–231) (167–204) (163–199) (159–193) (149–271) (159–256) (164–249) (160–242) (156–224) (155–222) (153–220) (92–221) (96–142) (49–73) (42–62) (30–44) (27–39) (33–49) (290–512) (314–505) (333–498) (340–472) (329–444) (326–439) (322–435) (101–241) (133–196) (133–196) (133–196) (135–194) (135–194) (135–195) (42–96) (54–79) (54–79) (54–79) (55–79) (55–79) (55–79) (114–164) (107–154) (141–203) (127–184) (106–153) (102–147) (98–142) (406–601) (409–596) (409–596) (409–596)

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

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south-east asia region

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATEa

NOTIFIED NEW AND RELAPSE NUMBER RATEa

b

CASE DETECTION PERCENT

Bangladesh

Bhutan

Democratic People's Republic of Korea

India

Indonesia

Maldives

Myanmar

Nepal

Sri Lanka

Thailand

Timor-Leste

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012

107 120 132 143 151 153 155 <1 <1 <1 <1 <1 <1 <1 20 22 23 24 25 25 25 869 956 1 042 1 127 1 206 1 221 1 237 179 194 209 224 241 244 247 <1 <1 <1 <1 <1 <1 <1 42 45 48 50 52 52 53 18 21 23 25 27 27 27 17 18 19 20 21 21 21 57 59 62 66 66 67 67 <1 1 1 1

240 270 300 320 340 340 350 4.2 2.9 2.3 1.9 1.5 1.4 1.3 77 83 87 91 97 100 100 1 900 2 100 2 300 2 400 2 200 2 200 2 200 370 400 430 450 450 460 460 0.32 0.29 0.17 0.15 0.12 0.11 0.14 170 180 200 200 200 200 200 30 34 38 41 44 44 45 11 12 12 13 14 14 14 78 77 110 100 85 82 80 5 5.4 5.5 5.6

(150–360) (220–320) (240–360) (260–390) (280–410) (280–410) (290–410) (3.6–4.8) (2.5–3.3) (1.9–2.6) (1.6–2.2) (1.3–1.7) (1.2–1.6) (1.1–1.5) (44–120) (48–130) (50–140) (52–140) (85–110) (92–110) (92–110) (1 600–2 200) (1 800–2 300) (2 000–2 500) (2 100–2 600) (2 000–2 500) (2 000–2 400) (2 000–2 400) (270–480) (310–500) (340–520) (360–540) (380–540) (380–540) (380–540) (0.200–0.480) (0.230–0.350) (0.130–0.200) (0.120–0.180) (0.097–0.140) (0.088–0.130) (0.110–0.170) (120–220) (140–230) (160–240) (170–240) (170–230) (170–230) (170–230) (18–44) (27–40) (31–45) (34–50) (36–52) (37–53) (37–53) (7.2–17) (9.9–14) (10–15) (11–16) (11–16) (11–17) (12–17) (65–93) (63–91) (88–130) (84–120) (70–100) (68–98) (66–95) (4.0–6.0) (4.4–6.4) (4.5–6.5) (4.6–6.6)

225 225 225 225 225 225 225 784 561 402 287 206 192 180 383 383 383 383 395 404 409 216 216 216 209 185 181 176 206 205 204 199 189 187 185 150 118 60 51 36 33 41 393 404 412 403 384 381 377 163 163 163 163 163 163 163 66 66 66 66 66 66 66 138 130 171 154 128 124 119 498 498 498 498

(139–331) (184–270) (184–270) (184–270) (185–268) (185–268) (185–268) (673–903) (482–646) (345–463) (247–331) (177–237) (165–222) (154–207) (219–592) (219–592) (219–592) (219–592) (348–445) (372–437) (373–447) (182–254) (189–245) (195–239) (188–231) (167–204) (163–199) (159–193) (149–271) (159–256) (164–249) (160–242) (156–224) (155–222) (153–220) (92–221) (96–142) (49–73) (42–62) (30–44) (27–39) (33–49) (290–512) (314–505) (333–498) (340–472) (329–444) (326–439) (322–435) (101–241) (133–196) (133–196) (133–196) (135–194) (135–194) (135–195) (42–96) (54–79) (54–79) (54–79) (55–79) (55–79) (55–79) (114–164) (107–154) (141–203) (127–184) (106–153) (102–147) (98–142) (406–601) (409–596) (409–596) (409–596)

0.048 0.054 0.089 0.19 0.31 0.34 0.24 <0.01 <0.01 <0.01 <0.01 0.019 0.021 0.024 0.033 0.087 0.11 0.13 0.13 0.13 19 90 170 170 130 130 130

(0.030–0.071) (0.044–0.065) (0.073–0.11) (0.16–0.23) (0.25–0.36) (0.28–0.41) (0.20–0.29) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.016–0.022) (0.018–0.025) (0.021–0.028) (0.018–0.054) (0.043–0.15) (0.054–0.18) (0.085–0.18) (0.084–0.18) (0.086–0.19) (16–22) (78–100) (150–190) (160–190) (120–150) (120–140) (120–140)

<0.1 <0.1 <0.1 0.1 0.2 0.2 0.2 <0.1 0.2 0.4 1.2 2.6 2.9 3.3 0.2 0.4 0.5 0.5 0.5 0.5 2.2 9.4 16 16 11 11 10

(<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (0.11–0.16) (0.17–0.24) (0.18–0.27) (0.13–0.19) (<0.1–<0.1) (0.14–0.19) (0.38–0.51) (1.0–1.4) (2.3–3.0) (2.5–3.4) (2.8–3.8) (<0.1–0.25) (0.19–0.65) (0.23–0.77) (0.34–0.72) (0.34–0.75) (0.35–0.76) (1.8–2.6) (8.2–11) (14–18) (14–17) (10–12) (9.6–12) (9.4–12)

48 673 56 437 75 557 123 118 153 892 154 358 168 683 1 154 1 299 1 140 1 007 1 311 1 235 1 130

45 47 57 86 102 101 109 215 255 202 155 183 169 152

20 21 25 38 45 45 49 27 45 50 54 89 88 85

(14–33) (17–26) (21–31) (32–47) (38–55) (38–55) (41–59) (24–32) (39–53) (44–59) (47–63) (77–100) (76–100) (73–99)

0.085 1.7 5.7 6.7 7.5 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.9 6.2 15 22 21 20 19 <0.01 0.081 0.52 1.4 1.5 1.4 1.1 <0.01 <0.01 <0.01 0.011 0.014 0.015 0.017 2.4 12 25 19 13 13 12

(0.068–0.10) (1.3–2.1) (4.3–7.3) (5.0–8.5) (5.6–9.7) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.66–1.2) (4.8–7.7) (12–18) (18–25) (18–24) (17–23) (16–21) (<0.01–0.013) (0.066–0.097) (0.42–0.62) (1.1–1.6) (1.2–1.7) (1.1–1.7) (0.94–1.4) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.013) (0.011–0.016) (0.012–0.019) (0.014–0.020) (2.0–2.9) (9.7–14) (21–30) (16–23) (11–16) (11–15) (10–14)

<0.1 0.8 2.4 2.7 3.1 0.2 0.3 0.1 <0.1 <0.1 <0.1 <0.1 2.1 14 30 43 40 38 35 <0.1 0.4 2.2 5.4 5.4 5.1 4.2 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 4.3 20 40 29 20 19 18

(<0.1–<0.1) (0.59–0.94) (1.8–3.0) (2.1–3.5) (2.3–3.9) (0.10–0.43) (0.13–0.40) (<0.1–0.21) (<0.1–0.15) (<0.1–0.10) (<0.1–<0.1) (<0.1–<0.1) (1.6–2.8) (11–17) (24–36) (36–50) (34–46) (32–43) (30–41) (<0.1–<0.1) (0.32–0.47) (1.8–2.7) (4.4–6.5) (4.5–6.5) (4.2–6.1) (3.4–5.0) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1) (<0.1–0.10) (3.5–5.1) (16–24) (33–48) (24–35) (17–24) (16–23) (15–22)

34 131 42 722 84 648 91 433 91 885 1 519 182 1 218 183 1 115 718 1 156 248 1 339 866 1 323 949 1 289 836 74 470 35 529 84 591 254 601 300 659 318 949 328 824 152 231 132 122 95 87 110 12 416 18 229 30 840 107 009 131 590 136 737 141 170 10 142 19 804 29 519 33 448 35 114 35 434 35 195 6 666 5 956 8 413 9 451 9 934 10 181 9 155 46 510 45 428 34 187 57 895 67 128 65 824 60 304 3 767 4 386 3 828

149 179 345 371 371 175 127 107 103 111 108 104 42 18 40 113 125 131 133 70 94 48 41 29 26 33 29 40 64 213 253 261 267 56 96 127 132 131 130 128 38 33 45 47 48 49 43 82 77 55 88 101 99 90 378 400 344

39 47 87 92 91 81 59 49 49 60 60 59 20 8.9 20 57 66 70 72 47 80 80 80 80 80 80 7.5 10 15 53 66 69 71 34 59 78 81 80 80 78 58 49 67 72 72 73 66 60 59 32 57 79 80 76 76

(25–68) (30–82) (78–99) (85–100) (83–100) (69–96) (52–67) (45–55) (44–55) (54–66) (54–66) (54–66) (15–28) (7.1–12) (16–25) (47–71) (56–80) (59–85) (61–87) (32–76) (66–98) (66–98) (66–98) (66–98) (66–98) (66–98) (5.8–10) (8.0–13) (13–19) (45–63) (57–77) (59–80) (62–83) (23–56) (49–72) (65–95) (67–99) (67–97) (67–97) (66–95) (40–92) (41–60) (56–83) (60–88) (61–88) (62–89) (55–80) (50–72) (50–72) (27–39) (48–69) (66–95) (67–97) (64–92) (63–93)

80 (67–98) 69 (58–84)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

258

NOT F ED N W AND REL PSE i cludes REPORT ases fo wh c 2013 the t e tm GLOBAL TUBERCULOSIS

story is un Data fornown all years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN NEW PULM 20 524 38 484 84 848 105 772 98 948 106 790 367 347 308 457 382 420 19 297 29 396 23 076 21 625 21 921 24 451 657 430 272 275 225 127 2 060 5 914 11 318 23 506 27 329 30 549 265 363 387 518 573 519 729 1 763 3 876 2 989 2 701 3 065 10 36 40 61 55 64 729 1 763 3 876 7 795 7 366 8 001 10 36 51 82 70 79 – 52 57 79 83 82 81 – 36 45 53 62 63 77 – – 54 50 46 46 47 – 23 35 56 63 65 66 – 100 78 65 64 66 66 – 56 68 74 67 80 75 – 55 67 51 43 41 37 – 52 60 61 62 61 62 46 65 66 69 68 65 69 – 47 59 61 62 62 64 33 – 40 46

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Bangladesh YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012 NEW AND RELAPSE 48 673 56 437 75 557 123 118 153 892 154 358 168 683 1 154 1 299 1 140 1 007 1 311 1 235 1 130 b

• 45 Bhutan

109 •

0 0 0

4 806 4 665 4 936

0 3 459 3 828

0 0

• 215 Democratic People's Republic of Korea

152 •

11 21 15 15

0 0

•0 India

371 •

• 175 Indonesia

104 •

• 42 Maldives

133 •

• 70 Myanmar

33 •

• 29 Nepal

267 •

• 56 Sri Lanka

128 •

• 38 Thailand

43 •

• 82 Timor-Leste

90 •

34 131 42 722 84 648 91 433 91 885 1 519 182 1 218 183 1 115 718 1 156 248 1 339 866 1 323 949 1 289 836 74 470 35 529 84 591 254 601 300 659 318 949 328 824 152 231 132 122 95 87 110 12 416 18 229 30 840 107 009 131 590 136 737 141 170 10 142 19 804 29 519 33 448 35 114 35 434 35 195 6 666 5 956 8 413 9 451 9 934 10 181 9 155 46 510 45 428 34 187 57 895 67 128 65 824 60 304 3 767 4 386 3 828

16 440 17 796 31 240 31 279 31 904 264 515 349 374 508 890 630 165 642 321 629 589 31 768 52 338 158 640 183 366 197 797 202 319 114 65 66 41 47 52 8 681 17 254 36 541 42 318 42 324 42 909 8 591 13 683 14 617 15 569 15 000 15 057 2 769 3 049 4 314 4 868 4 635 4 490 4 269 20 273 17 754 29 762 33 450 33 169 30 998 1 035 1 610 1 545

13 801 18 123 36 285 37 457 35 959 880 589 650 345 399 066 366 381 340 203 317 616 34 15 035 85 373 101 247 101 750 104 866 89 31 23 20 12 17 7 058 8 659 35 601 56 840 62 038 73 042 7 938 9 074 9 474 9 718 9 662 9 128 3 241 1 677 2 261 2 198 2 145 2 405 1 889 22 606 12 439 18 837 20 927 20 726 17 537 2 142 2 401 1 823

3 787 5 381 13 715 16 828 17 321 68 979 98 006 171 838 231 121 226 965 234 029 0 833 6 142 11 659 14 054 15 697 18 32 29 33 28 41 653 2 304 30 252 27 976 27 769 20 661 2 489 4 955 7 013 7 210 7 484 7 865 656 982 1 561 1 917 2 548 2 612 2 349 1 419 2 953 7 501 10 135 10 014 8 852 554 337 420

58

103 1 364 3 408 5 869 6 701 690 17 993 75 073 110 691 112 508 106 463 106 1 448 4 446 4 387 5 348 5 942 10 4 4 1 0 0 1 837 2 623 4 615 4 456 4 606 4 558 786 1 807 2 344 2 617 2 362 2 280 248 277 266 219 248 245 1 130 1 041 1 795 1 885 1 915 1 887 36 38 40

7 752 11 650 7 638 7 514

103 9 116 15 058 13 507 14 215 690 98 065 223 653 292 972 304 431 284 212 106 1 448 4 446 6 589 7 707 8 542 10 4 5 3 1 1 1 837 2 623 5 597 10 269 11 009 11 537 786 1 807 2 973 3 112 2 882 2 720 248 649 510 380 395 433 1 130 1 041 1 795 2 996 3 767 2 791 52 69 49

1 381 1 508 1 952 2 139

0

0

2 202 2 359 2 600

0

0 0 0 0

0 1 2 1 1

0 0 0 0

0

982 5 813 6 403 6 979

0

0 0 926 865

629 495 520 440

0 0 0

0 0 0 0

372 244 161 147 188

202 387 426 403

0 0

1 111 1 852 904 16 31 9

731 0 1 030

344 •

0 0

0

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

es r wh c all the treatme hist ry i downloaded u known Data for years tcan be from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

259

south-east asia region

80 072 148 580 182 281 191 923 177 749

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Bangladesh

• 71 Bhutan

92 •

• 97 Democratic People's Republic of Korea

91 •

•0 India

90 •

• 25 Indonesia

88 •

• 91 Maldives

90 •

• 97 Myanmar

81 •

• 67 Nepal

86 •

• 73 Sri Lanka

90 •

• 79 Thailand

87 •

• 64 Timor-Leste

85 •

91 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2005 2009 2010 2011

20 524 38 484 84 848 109 402 105 772 98 948 367 347 308 434 457 382 16 440 17 796 29 366 31 240 31 279 264 515 349 374 508 890 624 617 630 165 642 321 31 768 52 338 158 640 169 213 183 366 197 797 114 65 66 45 41 47 8 681 17 254 36 541 41 357 42 318 42 324 8 591 13 683 14 617 15 442 15 569 15 000 3 049 4 314 4 868 4 764 4 635 4 490 20 273 17 754 29 762 32 810 33 450 33 169 1 035 1 206 1 610

10 867 38 484 84 848 109 075 105 659 98 932 433 347 340 434 454 381 14 571 17 796 29 366 31 240 31 279 264 722 349 328 507 204 624 617 630 165 642 321 3 018 52 338 158 640 169 213 183 366 197 797 114 59 70 45 44 48 7 872 16 792 36 652 41 811 42 200 42 310 8 053 12 992 14 617 15 468 15 569 15 000 3 058 4 314 4 841 4 754 4 635 4 490 20 273 23 061 29 919 27 597 30 317 30 711 1 035 1 530 1 610

53 100 100 100 100 100 118 100 110 100 99 100 – 89 100 100 100 100 100 100 100 100 100 100 10 100 100 100 100 100 100 91 106 100 107 102 91 97 100 101 100 100 94 95 100 100 100 100 100 100 99 100 100 100 100 130 101 84 91 93 100 – – 100

66 77 91 91 90 91 78 75 84 86 87 88 73 84 85 86 87 1 31 83 85 85 85 73 70 83 84 84 84 96 97 86 47 82 81 53 73 77 77 77 77 56 79 87 87 88 88 75 75 83 83 83 83 36 65 70 81 79 79 61 80 86

5 4 1 1 1 1 20 15 7 6 3 3 9 5 5 4 3 25 4 2 2 3 3 18 17 8 7 7 6 2 0 0 0 0 0 14 9 7 8 8 9 17 5 1 3 2 2 4 4 3 3 4 3 28 3 5 5 6 6 21 8 5

5 4 4 4 4 4 0 4 5 3 3 3 3 2 2 3 3 0 1 5 4 4 4 2 2 2 2 2 2 3 2 6 2 9 2 4 5 6 6 5 5 3 5 5 4 3 4 3 4 5 6 7 5 2 8 8 7 7 7 5 4 3

2 1 1 1 1 1 0 3 3 3 3 5 7 4 4 4 4 0 1 2 2 2 2 0 1 1 1 1 1 0 0 0 2 2 0 4 2 3 3 3 3 2 1 1 1 1 1 0 1 1 2 1 1 0 2 2 1 2 1 1 1 0

10 9 2 2 2 2 1 3 1 2 1 1 5 2 2 2 2 0 7 7 6 6 5 6 4 4 4 4 4 0 0 3 4 0 0 18 9 5 5 4 4 18 7 3 3 3 3 13 15 6 4 4 5 9 7 7 3 3 3 11 4 3

12 5 2 2 2 2 1 0 0 0 2 1 3 2 2 1 1 75 57 1 1 1 1 1 5 2 2 3 3 0 2 6 44 7 17 7 2 2 2 2 2 6 2 2 2 3 2 4 2 1 3 1 2 24 15 9 2 2 3 2 4 2

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

260

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Bangladesh

• 75 Bhutan

82 •

• 59 Democratic People's Republic of Korea

76 •

•0 India

84 •

• 70 Indonesia

75 •

• 32 Maldives

71 •

•0 Myanmar

0•

• 64 Nepal

72 •

•0 Sri Lanka

85 •

•0 Thailand

75 •

•0 Timor-Leste

69 •

77 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 2005 2009 2010 2011

729 1 763 3 876 4 099 7 795 7 366 10 36 51 76 82 70 103 9 116 14 576 15 058 13 507 690 98 065 223 653 289 756 292 972 304 431 106 1 448 4 446 5 688 6 589 7 707 10 4 5 5 3 1 1 837 2 623 5 597 9 717 10 269 11 009 786 1 807 2 973 3 117 3 112 2 882 248 649 510 409 380 395 1 130 1 041 1 795 3 929 2 996 3 767 52 52 69

1 179 1 815 3 876 6 637 7 814 7 369 22 52 76 81 67 1 285 9 116 14 576 15 058 13 507 551 48 133 224 143 289 756 292 972 304 431 76 2 530 4 812 5 687 6 589 7 707 5 5 1 0 0 1 443 3 001 6 556 9 540 10 106 11 087 2 047 2 973 3 063 3 112 2 882 521 504 408 380 395

2 285 2 542 2 580 2 737 56 56 69

162 103 100 162 100 100 220 – 102 100 99 96 – 1 248 100 100 100 100 80 49 100 100 100 100 72 175 108 100 100 100 – 125 100 20 0 0 79 114 117 98 98 101 – 113 100 98 100 100 – 80 99 100 100 100 – – 127 65 86 73 108 – – 100

71 70 73 66 47 46 50 65 70 78 70 75 70 74 76 77 64 55 47 45 45 43 22 50 63 53 53 53 100 80 0

3 2 6 16 33 36 9 10 12 6 6 11 6 9 8 8 6 15 24 29 30 31 9 22 15 20 20 18

5 4 4 6 5 5 0 6 8 1 7 2 3 2 4 5 4 7 7 7 7 7 0 3 3 4 5 5

8 2 2 2 2 2 23 8 7 7 12 4 12 11 8 7 3 5 4 4 4 4 0 3 4 3 3 3

11 7 5 5 5 4 14 2 3 5 1 2 5 2 3 2 13 16 16 13 13 12 1 7 8 12 11 11

2 14 9 6 8 7 5 10 1 2 3 5 4 2 2 1 9 2 1 1 2 3 67 15 7 8 8 9 0 0 100

20 0

0 0

0 0

0 0

55 65 58 44 41 38 73 81 82 82 83 44 67 66 71 69

8 9 14 28 32 34 3 2 3 3 2 20 5 7 6 6

4 7 10 11 11 12 4 4 6 5 5 6 5 8 7 8

4 4 6 5 5 6 8 6 3 3 4 1 2 1 2 3

19 12 7 7 7 8 7 4 4 4 3 26 18 13 9 9

9 3 5 4 3 3 4 3 3 4 3 3 3 5 4 5

52 58 55 57 96 77 71

6 10 11 12 0 9 6

12 11 12 11 2 2 4

5 5 5 5 0 4 6

7 7 7 7 2 7

18 9 10 8 0 2 13

a

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

261

south-east asia region

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 0 1.1 1.2 1.2 0 0 1 778 1 900 2 086 0 PATIENTS NOTIFIED (NEW AND RETREAT) 123 118 158 698 159 023 173 619 1 018 1 332 1 250 1 145 50 474 96 298 99 071 99 399 1 304 828 1 522 147 1 515 872 1 467 585 254 601 302 861 321 308 331 424 123 97 88 111 107 991 137 403 143 140 148 149 34 077 35 609 35 954 35 635 9 695 10 095 10 328 9 343 57 895 68 239 67 676 61 208 3 783 4 417 3 837 % OF HIVNUMBER OF % OF HIVPOSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT 100 100 100 0 100 100 100 0 64 0 0

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Bangladesh 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS

% OF TESTED TB PATIENTS HIV-POSITIVE

•0 Bhutan

1•

4 53 63 1

0.22 2.8 3

•0 Democratic People's Republic of Korea – India

–

0 0 2.3 32 45 56 0.91 1.9 0.81 0 6.8 0.9 2 3.2 3.1 13 0 0 42 42 10 18 36 82 74 72 0 6.2 20

0 0 29 488 480 752 688 530 821 807 2 751 6 003 2 676 0 6 1 2 109 4 362 4 496 19 219 0 0 15 000 15 057 1 015 1 832 3 379 55 692 49 770 44 035 0 276 766

0 0 6 411 41 476 44 702 44 063 1 106 2 547 754 0 0 1 611 961 900 5 161 0 55 217 2 13 21 23 8 959 7 326 5 807 22 8.6 6.5 5.4 40 42 28

–

•2 Indonesia

56 •

90 91 92 63 67 18

57 59 59 29 39 29 0

– Maldives

1•

– Myanmar

1•

•2 Nepal

13 •

0 100 29 22 20 27

0 50 100 100

0 31 94 80 83

0 0 514 361

•0 Sri Lanka

42 •

0.37 1.4 1.3 1.1 0.68 16 15 13

– Thailand

36 •

100 100 0 100 71 22 71 75 77

100 100 0 54 100 48 54 59 62

3 7 8

– Timor-Leste

72 •

•0

20 •

4 4

1.4 0.52

100 100

262

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB – – <0.1 <0.1 0.65 24 13 12 – – – – – – – – – 0 <0.1 <0.1 – 0 0 0 – – – – – 0.81 0 1.2 12 18 24 23 – – – – – – 0 – b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

Bangladesh

Bhutan

Democratic People's Republic of Korea India

Indonesia

Maldives

1.7 (1.3–2.1)

1.5 (1.1–1.9)

0.16 (0.11–0.21)

Myanmar

192 690 778 229 213 354 32 11 13 5

6 000 (4 600–7 500)

4 900 (3 600–6 500) 126 0 188 659 839 1080 1069

1 200 (790–1 600)

Nepal

990 (660–1 300)

570 (320–950)

420 (270–620)

Sri Lanka

21 (0–43)

11 (0.28–61)

9.6 (4.4–18)

Thailand

510 492 5 2 3

1 800 (1 400–2 200)

800 (480–1 200)

960 (780–1 200)

Timor-Leste

0 82 (62–100) 74 (54–94)

7.9 (5.4–10)

a

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). b BACT+VE = bacteriologically positive cases.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

263

south-east asia region

2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

339 509 513 2 17 21 16

4 200 (3 100–5 200)

1 900 (920–3 300)

25 (20–30)

12 (8.8–15)

71 41 2 108 48 52

2 300 (1 900–2 700)

13 (8.8–17)

37 25 34 2967 4237 16588 182 383 428 0 0 0

3 800 (3 000–4 600)

1 500 (1 100–1 900)

2 300 (1 600–3 000)

64 000 (49 000–79 000)

21 000 (18 000–25 000) 0 5 2 0 0 0

43 000 (32 000–54 000)

6 900 (5 200–8 500)

5 800 (4 300–7 700)

1 000 (690–1 500)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB – 339 4.3 761 10 557 7.0 3 5.9 30 37 26 37 2 2.5 – – 43 0.32 31 0.22 – – – – – 324 4.9 695 9.0 821 9.6 – 0 0 0 0 0 0 – – – – – 193 6.2 0 0 640 24 417 82 378 99 408 100 238 55 – – – – – – 2 2.9 3 6.1

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO 2.6 2.3 2.1 2.0 2.0 1.9 1.4 1.1 1.4 1.1 1.2 1.0 – 1.6 1.4 1.7 1.8 1.7 2.6 2.2 2.2 2.3 2.2 2.2 1.4 – 1.4 1.5 1.5 1.5 1.8 1.1 1.4 2.4 2.6 1.3 1.8 1.8 2.0 1.9 1.9 1.9 – 2.0 2.1 2.2 2.2 2.1 2.7 2.5 2.9 2.9 2.7 2.7 2.5 2.1 2.3 2.3 2.4 2.4 1.5 – 1.2 1.3

Bangladesh

Bhutan

Democratic People's Republic of Korea

India

Indonesia

Maldives

Myanmar

Nepal

Sri Lanka

Thailand

Timor-Leste

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 2005 2010 2011 2012

29 256 524 365 309 316 2 6 1 2 6 293 167 447 314 293 16 1 588 3 185 4 871 4 649 4 697 6 846 714 787 824 1 0 0 0 0 0 42 88 132 106 120 146 170 148 165 245 250 10 25 9 14 12 7 59 27 44 55 38 35 8 14 7

505 3 640 8 170 10 460 9 606 9 479 42 65 47 108 88 82 928 1 409 2 524 2 218 2 439 334 20 963 62 620 78 278 78 096 75 502 203 15 215 16 501 17 406 17 304 28 9 9 8 12 8 713 1 459 3 401 3 043 2 923 2 898 1 904 1 946 2 110 1 914 1 906 163 266 341 268 246 243 1 191 859 1 344 1 506 1 546 1 444 136 199 196

983 5 643 10 443 12 535 11 616 12 021 65 41 58 50 39 56 1 508 2 422 4 046 4 066 4 015 391 31 090 74 678 82 757 82 762 79 594 297 20 906 24 645 25 429 25 460 11 10 8 6 7 6 1 423 2 636 5 877 6 578 6 182 6 263 1 763 1 685 1 832 1 755 1 756 361 459 520 539 459 420 2 936 2 570 3 814 3 695 3 650 3 277 149 177 172

1 001 5 750 11 423 11 409 10 152 10 837 36 30 26 25 26 30 2 927 2 688 4 849 5 493 5 055 287 30 829 76 870 90 440 89 706 88 111 306 18 401 21 090 22 353 23 057 10 2 5 0 3 2 1 401 2 781 5 888 6 688 6 319 6 469 1 713 1 722 1 724 1 723 1 644 519 695 724 602 585 504 2 948 2 380 4 393 5 253 5 139 4 705 116 137 128

748 4 718 11 038 12 758 11 728 12 744 35 24 23 12 14 11 2 519 2 040 4 061 4 542 4 373 216 24 230 64 843 81 210 82 921 82 356 302 17 847 20 977 22 885 23 751 8 5 6 4 8 4 977 2 161 4 585 5 607 5 680 5 837 1 491 1 806 1 856 1 732 1 708 521 793 918 884 828 799 2 434 2 117 4 003 5 042 5 140 4 867 119 114 119

648 3 667 8 476 11 176 10 746 11 843 24 12 14 26 20 17 1 167 1 185 2 629 2 474 2 699 123 15 308 43 038 60 766 63 625 63 814 228 13 509 17 329 19 404 20 204 10 5 6 5 1 5 677 1 235 2 557 3 632 3 954 3 945 1 294 1 759 1 857 1 710 1 773 365 484 657 683 653 672 2 607 1 908 2 831 3 625 3 734 3 780 52 99 114

424 2 837 7 453 11 536 11 301 12 236 11 2 12 13 19 11 651 485 1 153 1 024 1 150 68 8 534 24 726 38 442 42 443 41 322 109 6 390 7 910 9 089 9 554 6 3 5 6 3 4 298 836 1 764 2 308 2 500 2 626 772 820 1 126 1 180 1 203 261 360 424 448 479 456 2 346 2 213 3 407 4 189 4 080 3 863 47 146 129

0 0 0

0

64 495 751 653 623 650 12 7 9 17 2 6 167 166 407 227 227 32 2 250 6 292 8 544 8 336 8 260 16 946 816 927 879 1 0 1 1 0 0 58 72 147 196 187 192 176 195 192 247 210 15 23 19 15 13 17 52 32 57 82 76 82 8 16 12

309 3 029 6 776 9 221 8 849 9 355 43 57 45 104 92 92 683 1 127 1 493 1 390 1 447 179 14 495 45 136 53 415 53 958 53 975 160 13 916 14 800 15 840 15 875 13 11 10 2 4 7 535 1 040 2 376 2 452 2 401 2 357 1 267 1 208 1 177 1 182 1 227 207 312 295 255 270 242 741 624 907 1 087 1 214 995 127 176 154

546 3 238 6 785 8 279 7 679 8 175 44 34 38 45 40 58 1 121 1 756 2 461 2 264 2 475 169 17 287 45 629 49 425 49 227 47 511 244 16 393 17 838 18 703 18 484 8 4 7 3 3 6 729 1 592 3 047 3 454 3 317 3 368 1 078 1 111 1 036 978 1 036 206 264 261 233 217 200 888 1 035 1 662 1 930 1 773 1 491 90 182 143

360 2 247 5 538 6 185 5 683 6 342 25 31 13 18 19 14 2 004 1 890 2 910 3 093 3 005 80 11 768 28 577 34 035 34 698 33 378 282 13 022 14 629 15 900 16 146 4 5 1 4 1 3 729 1 397 2 563 2 752 2 760 2 721 833 797 819 752 666 142 176 189 171 191 162 782 780 1 334 1 749 1 658 1 613 76 113 120

236 1 315 3 960 5 458 4 946 6 044 12 23 11 18 12 18 1 524 1 381 2 276 2 409 2 623 49 7 516 17 042 22 719 23 977 23 267 192 10 927 13 142 14 533 15 215 6 4 2 1 2 3 450 987 2 101 2 525 2 554 2 600 575 658 681 624 638 122 202 200 183 192 211 936 873 1 367 1 467 1 586 1 424 60 85 75

132 778 2 281 3 484 3 457 4 043 9 3 9 10 4 9 591 764 1 347 1 271 1 527 30 4 594 10 513 15 527 17 182 17 300 90 7 539 9 524 10 556 11 321 6 5 2 0 1 2 343 592 1 218 1 838 2 010 2 023 419 532 642 604 643 81 144 154 186 191 200 1 175 1 016 1 259 1 494 1 402 1 364 18 77 84

38 370 1 230 2 250 2 253 2 705 8 2 2 9 5 10 357 336 637 494 576 11 2 697 5 408 9 735 10 731 10 502 33 2 783 3 451 3 985 4 245 2 2 4 1 2 2 154 378 885 1 139 1 407 1 464 228 230 352 354 397 56 113 130 154 154 136 1 178 1 321 1 938 2 276 2 133 2 058 29 75 92

0 0 0

0

0

0

0 0 0

0 0 0

0

0

0 0

0 0

0 0

0 0

0 0

0 0

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GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           LABORATORIES SECONDNUMBER OF SMEAR LABS % OF SMEAR CULTURE DST b LABS LPAc LABS LABS USING LABS PER 5M LINE DST LABS USING PER 100K PER 5M PER 5M a POPULATION POPULATION POPULATION POPULATION XPERT MTB/RIF AVAILABLE LED

FREE THROUGH NTP FIRSTLINE DRUGS

NRLd

TB DIAGNOSIS

TB NOTIF. RIFAMPICIN RATE PER USED 100 000 THROUGHOUT HEALTH-CARE TREATMENT WORKERS

Bangladesh Bhutan Democratic People's Republic of Korea India Indonesia Maldives Myanmar Nepal Sri Lanka Thailand Timor-Leste

0.7 4.7 1.3 1.1 2.3 20.7 0.9 1.9 1.0 1.6 1.6

2 0 0 2 0 0 14 2 0 6 –

<0.1 6.7 0.2 0.3 0.9 14.8 0.2 0.4 0.7 4.9

<0.1 6.7 0.2 0.2 0.1 0 0.2 0.4 0.2 1.3

<0.1

12

0 0.1 <0.1 0 0.2

0 32 9 0 3 9

Out of Yes country Out of Yes country Out of Yes country Yes In country Yes Out of country In and out of country In country Out of country In country No Yes Yes Yes Yes Yes Yes

Yes (all suspects) Yes (if TB is confirmed) Yes (all suspects) Yes (all suspects) Yes (other criteria) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects) Yes (all suspects)

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No 53

0.2 0.9

1 14 1

a b

LED = Light emitting diode microscopes DST = Drug susceptibility testing LEDprobe = Ligh assay emitting c LPA = Line D ug y g d NRL = National Reference Laboratory

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

265

south-east asia region

             New TB cases Year Source Coverage Percentage Year

Previously treated TB cases Source Coverage Percentage

Bangladesh Bhutan Democratic People's Republic of Korea India Indonesia Maldives Myanmar Nepal Sri Lanka Thailand Timor-Leste

2011

Survey

National

1.4 (0.70–2.5)

2011

Survey

National

29 (24–34)

2001, 2004, 2006, 2009 Survey 2004, 2006, 2010 Survey 2008 2011 2006 2006 Survey Survey Survey Survey

Sub-national Sub-national National National National National

2.2 (1.9–2.6) 1.9 (1.4–2.5) 4.2 2.3 0.18 1.7 (3.1–5.6) (1.3–3.8) (0–0.99) (1.0–2.6)

2006, 2009 2006, 2010 2008 2011 2011 2006

Survey Survey Survey Survey Surveillance Survey

Sub-national Sub-national National National National National

15 (11–19) 12 (8.1–17) 10 15 2.2 35 (6.9–14) (10–23) (1.0–4.1) (28–42)

a

Empty rows indicate an absence of high-quality survey or surveillance data. In the absence of high-quality national data, high-quality sub-national data are used.

266

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Data for all years can be downloaded from www.who.int/tb/data

western pacific region Table A4.1 Estimates of the burden of disease caused by TB, 1990–2012 Table A4.2 Incidence, notification and case detection rates, all forms, 1990–2012 Table A4.3 Case notifications, 1990–2012 Table A4.4 Treatment outcomes, new smear-positive cases, 1995–2011 Table A4.5 Treatment outcomes, retreatment cases, 1995–2011 Table A4.6 HIV testing and provision of CPT, ART and IPT, 2005–2012 Table A4.7 Testing for MDR-TB and number of confirmed cases of MDR-TB, 2005–2012 Table A4.8 New smear-positive case notification by age and sex, 1995–2012 Table A4.9 Laboratories, NTP services, drug management and infection control, 2012 Table A4.10 Measured percentage of TB cases with MDR-TB, most recent year available 269 272 275 278 280 282 284 286 288 289

Estimates of mortality, prevalence and incidence Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See ANNEX 1 for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. The main updates implemented in this report are explained in Box 2.1 of Chapter 2. Estimates published in previous global TB control reports should no longer be used.

Data source Data shown in this annex are taken from the WHO global TB database on 1 October 2013. Data shown in the main part of the report were taken from the database in July 2013. As a result, data in this annex may differ slightly from those in the main part of the report. Data for all years can be downloaded from www.who.int/tb/data.

268

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Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATE a

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

1990 1995 2000 2005 2010 2011 2012 Australia 1990 1995 2000 2005 2010 2011 2012 Brunei 1990 Darussalam 1995 2000 2005 2010 2011 2012 Cambodia 1990 1995 2000 2005 2010 2011 2012 China 1990 1995 2000 2005 2010 2011 2012 China, Hong Kong 1990 SAR 1995 2000 2005 2010 2011 2012 China, Macao 1990 SAR 1995 2000 2005 2010 2011 2012 Cook Islands 1990 1995 2000 2005 2010 2011 2012 Fiji 1990 1995 2000 2005 2010 2011 2012 French Polynesia 1990 1995 2000 2005 2010 2011 2012 Guam 1990 1995 2000 2005 2010 2011 2012 Japan 1990 1995 2000 2005 2010 2011 2012 Kiribati 1990 1995 2000 2005 2010 2011 2012 Lao People's 1990 Democratic 1995 Repub ic 2000 2005 2010 2011 2012 Malaysia 1990 1995 2000 2005 2010 2011 2012 Marshall Islands 1990 1995 2000 2005 2010 2011 2012 a

American Samoa

<1 <1 <1 <1 <1 <1 <1 17 18 19 21 22 23 23 <1 <1 <1 <1 <1 <1 <1 9 11 12 13 14 15 15 1 165 1 238 1 280 1 318 1 360 1 368 1 377 6 6 7 7 7 7 7 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 122 124 126 127 127 127 127 <1 <1 <1 <1 <1 <1 <1 4 5 5 6 6 7 7 18 21 23 26 28 29 29 <1 <1 <1 <1 <1 <1 <1

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.061 0.027 0.036 0.041 0.051 0.04 0.045 <0.01 <0.01 0.014 0.011 0.012 0.012 0.013 14 15 16 13 9.8 9.5 9.3 220 170 110 75 52 48 44 0.37 0.38 0.27 0.24 0.19 0.19 0.19 0.036 0.022 0.02 0.015 0.015 0.015 0.015 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.051 0.039 0.03 0.022 0.016 0.015 0.015 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 3.8 3.3 2.8 2.3 2.2 2.3 2.1 0.039 0.044 0.013 0.015 0.016 0.017 0.017 1.7 1.4 1.1 0.91 0.76 0.73 0.72 1.2 1.4 1.6 1.5 1.5 1.6 1.6 0.013 0.018 0.033 0.033 0.047 0.051 0.058

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.061–0.062) (0.027–0.028) (0.035–0.036) (0.041–0.042) (0.050–0.051) (0.040–0.041) (0.044–0.045) (<0.01–<0.01) (<0.01–<0.01) (0.014–0.015) (0.010–0.011) (0.012–0.013) (0.012–0.013) (0.012–0.013) (4.9–28) (5.3–29) (5.7–31) (5.1–23) (4.5–17) (4.4–17) (4.3–16) (190–240) (140–200) (84–140) (72–77) (50–53) (46–50) (43–46) (0.360–0.370) (0.380–0.380) (0.270–0.280) (0.240–0.250) (0.180–0.190) (0.180–0.190) (0.190–0.190) (0.018–0.060) (<0.01–0.050) (<0.01–0.052) (<0.01–0.051) (<0.01–0.058) (<0.01–0.059) (<0.01–0.059) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–<0.01) (<0.01–<0.01) (0.020–0.097) (0.018–0.069) (0.021–0.040) (0.020–0.024) (0.016–0.017) (0.015–0.016) (0.014–0.015) (<0.01–0.016) (<0.01–0.015) (<0.01–<0.01) (<0.01–0.015) (<0.01–<0.01) (<0.01–0.022) (<0.01–<0.01) (<0.01–0.012) (<0.01–0.023) (<0.01–<0.01) (<0.01–0.022) (<0.01–0.036) (<0.01–0.012) (<0.01–<0.01) (3.7–3.9) (3.2–3.3) (2.7–2.8) (2.3–2.4) (2.1–2.3) (2.2–2.3) (2.0–2.2) (0.029–0.051) (0.031–0.058) (<0.01–0.016) (0.015–0.016) (<0.01–0.025) (<0.01–0.026) (<0.01–0.026) (1.1–2.6) (0.860–2.0) (0.700–1.7) (0.560–1.3) (0.470–1.1) (0.450–1.1) (0.430–1.1) (0.370–2.5) (0.480–2.7) (0.710–2.9) (0.810–2.4) (1.0–2.2) (1.1–2.1) (1.2–2.1) (<0.01–0.062) (<0.01–0.069) (<0.01–0.070) (<0.01–0.130) (<0.01–0.200) (<0.01–0.220) (<0.01–0.240)

5.1 2.4 0.82 2.4 0.9 0.95 0.88 0.36 0.15 0.19 0.2 0.23 0.18 0.19 3 3 4.3 2.9 3 3 3 157 139 128 94 68 65 63 19 13 8.7 5.7 3.8 3.5 3.2 6.3 6.2 4 3.5 2.6 2.6 2.6 10 5.4 4.6 3.3 2.8 2.8 2.8 0.79 1.1 0.51 0.62 0.4 0.53 0.6 7 5.1 3.7 2.7 1.9 1.8 1.7 1.9 2.3 1.2 1.6 0.78 1.7 0.98 2.7 3.9 1.9 2.9 4.6 2.7 2.2 3.1 2.6 2.2 1.8 1.7 1.8 1.7 55 57 15 17 17 17 17 41 29 21 16 12 11 11 6.6 6.6 6.9 5.8 5.4 5.4 5.4 28 35 62 64 89 98 111

(2.1–9.5) (0.95–4.4) (0.35–1.5) (0.99–4.5) (0.14–2.3) (0.17–2.4) (0.23–2.0) (0.35–0.36) (0.15–0.16) (0.18–0.19) (0.20–0.20) (0.23–0.23) (0.18–0.18) (0.19–0.19) (2.9–3.2) (2.9–3.2) (4.2–4.5) (2.8–3.0) (2.9–3.2) (2.9–3.2) (2.9–3.2) (54–314) (49–274) (47–251) (38–175) (31–120) (30–114) (29–110) (17–21) (11–16) (6.5–11) (5.5–5.9) (3.7–3.9) (3.4–3.6) (3.1–3.3) (6.2–6.4) (6.1–6.2) (4.0–4.0) (3.5–3.6) (2.6–2.7) (2.6–2.7) (2.6–2.7) (5.1–17) (1.3–12) (0.74–12) (0.16–11) (<0.1–11) (<0.1–11) (<0.1–11) (0.73–0.85) (0.63–1.7) (0.26–0.84) (0.34–0.98) (0.34–0.46) (<0.1–1.9) (0.33–0.97) (2.7–13) (2.3–8.9) (2.6–4.9) (2.4–2.9) (1.9–2.0) (1.7–1.8) (1.6–1.7) (<0.1–7.8) (0.19–6.8) (0.36–2.7) (<0.1–6.1) (0.25–1.6) (0–8.0) (0.12–2.7) (<0.1–9.5) (<0.1–16) (0.22–5.3) (0–14) (<0.1–23) (0.33–7.6) (0.68–4.5) (3.0–3.2) (2.6–2.7) (2.2–2.2) (1.8–1.9) (1.7–1.8) (1.7–1.8) (1.6–1.7) (41–72) (41–76) (11–20) (16–17) (9.5–26) (9.5–26) (9.5–26) (25–60) (18–42) (13–31) (9.7–23) (7.3–17) (6.9–17) (6.5–16) (2.0–14) (2.3–13) (3.0–12) (3.2–9.1) (3.6–7.6) (3.8–7.3) (4.1–7.0) (<0.1–130) (0.72–134) (18–135) (1.3–245) (0.54–385) (0.78–414) (1.4–448)

0.022 0.011 <0.01 0.013 <0.01 <0.01 <0.01 1.7 1.7 1.7 1.6 2 1.9 2 0.2 0.21 0.55 0.23 0.4 0.36 0.37 150 180 200 160 130 120 110 2 500 2 400 2 200 1 800 1 500 1 400 1 400 9.8 8.7 8.2 9 7.7 7.3 7.7 0.6 0.55 0.65 0.66 0.64 0.59 0.65 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1.8 1.3 0.91 0.66 0.39 0.32 0.26 0.095 0.13 0.083 0.099 0.059 0.11 0.071 0.088 0.14 0.077 0.12 0.19 0.13 0.11 83 66 64 43 37 35 33 0.18 0.59 0.4 0.68 0.47 0.66 0.63 63 60 52 43 36 35 34 44 39 35 33 32 31 29 0.12 0.17 0.28 0.34 0.47 0.51 0.57

(0.010–0.037) (<0.01–0.019) (<0.01–0.010) (<0.01–0.023) (<0.01–0.014) (<0.01–0.014) (<0.01–0.012) (0.750–2.9) (0.740–3.0) (0.740–3.0) (0.650–3.0) (0.830–3.6) (0.740–3.5) (0.860–3.7) (0.070–0.400) (0.064–0.440) (0.270–0.930) (0.080–0.470) (0.180–0.700) (0.140–0.660) (0.140–0.700) (96–220) (130–230) (160–240) (140–190) (110–150) (100–140) (96–130) (2 300–2 700) (2 200–2 700) (1 900–2 500) (1 600–2 100) (1 300–1 700) (1 200–1 600) (1 200–1 600) (4.0–18) (3.1–17) (2.8–17) (3.8–16) (3.2–14) (3.0–14) (3.4–14) (0.290–1.0) (0.180–1.1) (0.250–1.2) (0.300–1.2) (0.280–1.1) (0.240–1.1) (0.280–1.2) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.890–3.0) (0.650–2.1) (0.470–1.5) (0.340–1.1) (0.200–0.640) (0.140–0.570) (0.088–0.530) (0.042–0.170) (0.048–0.240) (0.025–0.180) (0.043–0.180) (0.018–0.120) (0.052–0.190) (0.026–0.140) (0.037–0.160) (0.062–0.250) (0.028–0.150) (0.059–0.200) (0.095–0.310) (0.049–0.240) (0.036–0.220) (35–150) (26–120) (28–110) (18–79) (16–66) (15–64) (13–61) (0.080–0.310) (0.260–1.0) (0.140–0.790) (0.300–1.2) (0.160–0.930) (0.300–1.2) (0.270–1.1) (32–110) (32–95) (30–79) (26–63) (23–52) (23–50) (22–48) (23–71) (21–63) (18–56) (18–54) (15–54) (14–54) (13–53) (<0.01–0.470) (<0.01–0.550) (0.099–0.540) (0.027–1.0) (0.019–1.6) (0.022–1.7) (0.028–1.9)

46 21 9.4 23 11 12 11 9.7 9.4 8.7 7.8 8.8 8.2 8.8 78 71 165 64 99 87 90 1 670 1 670 1 620 1 230 875 817 764 215 195 170 140 108 104 99 169 142 120 130 110 103 108 167 137 151 141 119 108 117 12 17 7.6 7.5 6 7.4 7.2 244 165 112 80 45 37 30 48 59 35 39 22 41 26 67 96 49 74 118 78 66 68 53 51 34 29 28 26 249 770 487 747 477 664 628 1 490 1 220 961 737 565 540 514 242 189 148 129 112 107 101 251 332 532 651 903 973 1 080

(22–79) (10–37) (3.6–18) (11–38) (3.0–25) (3.2–25) (3.6–22) (4.4–17) (4.1–17) (3.9–16) (3.2–14) (3.7–16) (3.3–15) (3.7–16) (27–154) (22–150) (81–280) (22–128) (45–174) (36–162) (35–169) (1 060–2 410) (1 220–2 180) (1 310–1 960) (1 020–1 460) (737–1 020) (690–954) (645–892) (201–230) (176–216) (146–196) (121–160) (94–123) (91–119) (86–113) (69–314) (50–280) (40–243) (55–237) (46–202) (42–191) (47–195) (81–285) (45–278) (57–289) (64–249) (52–214) (44–200) (50–211) (3.4–25) (5.0–35) (2.3–16) (2.9–14) (1.8–13) (1.1–20) (2.9–14) (123–407) (84–273) (58–184) (42–131) (23–75) (16–66) (10–61) (21–85) (22–113) (10–74) (17–70) (6.6–46) (19–70) (9.4–51) (28–124) (43–170) (18–96) (37–124) (59–196) (31–148) (22–134) (29–123) (21–99) (23–91) (14–62) (12–52) (12–50) (11–48) (113–437) (347–1 360) (174–957) (335–1 320) (166–949) (298–1 170) (270–1 130) (746–2 490) (664–1 950) (557–1 470) (453–1 090) (366–807) (353–767) (335–729) (128–392) (102–303) (79–239) (68–210) (54–190) (49–186) (43–183) (3.3–1 000) (19–1 080) (190–1 040) (53–1 980) (36–3 100) (43–3 290) (54–3 560)

0.012 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1.2 1.2 1.2 1.2 1.4 1.4 1.5 0.16 0.18 0.35 0.19 0.27 0.26 0.28 53 62 71 68 63 62 61 1 800 1 600 1 400 1 200 1 100 1 000 1 000 7.5 7.1 6.9 6.5 5.7 5.4 5.5 0.39 0.46 0.52 0.46 0.45 0.44 0.46 0 <0.01 <0.01 <0.01 0 <0.01 <0.01 0.81 0.6 0.44 0.33 0.24 0.23 0.21 0.068 0.1 0.071 0.072 0.047 0.074 0.058 0.066 0.099 0.062 0.072 0.12 0.094 0.078 60 50 45 31 26 25 24 0.083 0.39 0.31 0.44 0.36 0.43 0.43 21 20 18 16 14 14 14 23 22 22 22 23 23 24 0.065 0.097 0.14 0.19 0.26 0.28 0.3

(<0.01–0.015) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (1.0–1.3) (1.1–1.4) (1.1–1.4) (1.1–1.4) (1.3–1.6) (1.2–1.6) (1.3–1.7) (0.140–0.190) (0.160–0.210) (0.310–0.400) (0.160–0.210) (0.240–0.310) (0.230–0.300) (0.240–0.320) (38–69) (48–78) (56–87) (57–81) (54–72) (53–71) (52–70) (1 400–2 200) (1 300–1 900) (1 200–1 600) (1 100–1 400) (930–1 200) (900–1 200) (880–1 100) (6.6–8.5) (6.3–8.1) (6.1–7.8) (5.7–7.4) (5.0–6.4) (4.8–6.2) (4.8–6.3) (0.350–0.450) (0.410–0.520) (0.450–0.580) (0.400–0.520) (0.400–0.510) (0.380–0.490) (0.410–0.530) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (0.710–0.920) (0.530–0.680) (0.390–0.500) (0.290–0.370) (0.210–0.270) (0.200–0.260) (0.190–0.240) (0.059–0.077) (0.088–0.110) (0.062–0.081) (0.063–0.082) (0.041–0.053) (0.064–0.083) (0.050–0.065) (0.058–0.075) (0.087–0.110) (0.054–0.070) (0.063–0.082) (0.100–0.130) (0.083–0.110) (0.069–0.089) (52–67) (43–56) (40–51) (27–35) (23–30) (22–29) (21–28) (0.066–0.100) (0.310–0.460) (0.250–0.380) (0.360–0.530) (0.290–0.430) (0.350–0.520) (0.350–0.520) (13–31) (12–29) (11–26) (9.7–23) (8.8–21) (8.6–20) (8.4–20) (21–26) (20–25) (20–24) (20–24) (21–25) (21–25) (22–26) (<0.01–0.190) (0.024–0.220) (0.084–0.200) (0.050–0.420) (0.051–0.650) (0.054–0.690) (0.058–0.740)

26 12 6.9 13 7.8 7.8 7.3 6.8 6.8 6.2 5.9 6.5 6.3 6.5 64 63 106 51 68 65 68 580 578 577 510 437 424 411 153 129 109 92 78 75 73 129 116 101 94 81 77 77 110 116 120 98 85 80 83 0 13 6.5 5.9 0 5.6 5.6 112 77 54 40 28 26 24 34 47 30 28 18 27 21 50 68 40 46 73 59 48 49 40 36 25 20 20 19 116 505 372 488 366 432 429 492 403 330 270 221 213 204 127 108 95 86 82 81 80 137 190 263 363 502 536 572

(21–31) (9.4–14) (5.6–8.4) (10–15) (6.3–9.4) (6.3–9.4) (5.9–8.9) (6.0–7.7) (6.0–7.7) (5.5–7.0) (5.1–6.6) (5.7–7.3) (5.5–7.1) (5.7–7.4) (56–72) (55–71) (93–120) (45–58) (60–77) (57–74) (59–77) (423–761) (448–724) (458–710) (424–604) (376–503) (364–489) (353–474) (121–189) (106–154) (92–126) (80–105) (68–88) (66–85) (64–82) (113–146) (102–132) (89–115) (83–107) (71–91) (67–87) (68–88) (96–124) (102–131) (105–135) (86–111) (74–96) (70–91) (73–94) (0–0) (11–14) (5.7–7.3) (5.2–6.7) (0–0) (4.9–6.4) (4.9–6.3) (98–126) (68–87) (48–62) (35–45) (24–32) (23–29) (21–27) (30–39) (41–53) (26–34) (25–32) (15–20) (24–31) (18–24) (44–57) (60–77) (35–45) (40–52) (64–82) (51–66) (42–54) (43–55) (35–45) (32–41) (22–28) (18–23) (18–23) (17–22) (93–143) (410–609) (296–456) (396–588) (298–441) (351–521) (349–517) (304–725) (249–593) (204–486) (167–398) (137–326) (131–313) (126–301) (113–142) (97–120) (86–103) (79–94) (75–89) (74–88) (74–87) (14–396) (46–432) (161–389) (96–803) (97–1 230) (103–1 320) (110–1 400)

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

269

western pacific region

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATE a

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Micronesia (Federated States of)

Mongolia

Nauru

New Caledonia

New Zealand

Niue

Northern Mariana Islands

Palau

Papua New Guinea

Philippines

Republic of Korea

Samoa

Singapore

Solomon Islands

Tokelau

Tonga

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

<1 <1 <1 <1 <1 <1 <1 2 2 2 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 3 4 4 4 4 4 4 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 4 5 5 6 7 7 7 62 70 78 86 93 95 97 43 45 46 47 48 49 49 <1 <1 <1 <1 <1 <1 <1 3 3 4 4 5 5 5 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1

0.035 0.077 0.07 0.053 0.032 0.028 0.025 0.52 0.42 0.32 0.24 0.2 0.2 0.2 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.019 0.021 0.012 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 3.4 3 2.8 3.4 3.7 3.7 3.9 34 35 31 30 25 24 23 3.7 2.7 1.2 2.7 2.5 2.7 2.6 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.12 0.13 0.12 0.082 0.097 0.087 0.089 0.22 0.2 0.17 0.13 0.09 0.085 0.082 <0.01 <0.01 <0.01 0 0 0 0 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(0–0.220) (0.019–0.180) (0.024–0.140) (0.016–0.110) (<0.01–0.100) (<0.01–0.098) (<0.01–0.093) (0.400–0.650) (0.300–0.560) (0.190–0.470) (0.120–0.400) (0.079–0.390) (0.077–0.390) (0.075–0.390) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.024) (<0.01–<0.01) (<0.01–0.034) (<0.01–<0.01) (<0.01–0.011) (<0.01–0.014) (<0.01–<0.01) (0.018–0.019) (0.021–0.021) (0.012–0.012) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.018) (<0.01–0.019) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (1.2–6.9) (1.0–5.9) (0.910–5.8) (1.1–6.9) (1.2–7.5) (1.2–7.6) (1.3–7.8) (26–44) (30–40) (29–34) (28–32) (24–27) (23–26) (22–25) (0.170–13) (0.044–10) (0.460–2.4) (0.040–11) (0.190–7.5) (0.120–9.1) (0.160–8.5) (<0.01–0.015) (<0.01–0.013) (<0.01–0.011) (<0.01–<0.01) (<0.01–0.010) (<0.01–0.011) (<0.01–0.011) (0.120–0.120) (0.120–0.130) (0.110–0.140) (0.071–0.094) (0.082–0.110) (0.073–0.100) (0.075–0.110) (0.063–0.480) (0.077–0.370) (0.068–0.330) (0.053–0.240) (0.039–0.160) (0.038–0.150) (0.036–0.150) (<0.01–<0.01) (0–<0.01) (<0.01–<0.01) (0–0) (0–0) (0–0) (0–0) (<0.01–0.010) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

36 72 65 50 31 27 24 24 18 13 9.4 7.5 7.4 7.2 9.1 4.7 7.2 23 3.7 8.1 9.5 4.7 2.1 3.3 1.1 1.2 1.3 0.74 0.55 0.58 0.32 0.15 0.12 0.1 <0.1 2.9 3 3.1 1.7 1.4 19 3.1 3.1 4.4 6.9 6.3 3.2 3.6 3.5 3.4 17 26 10 23 8.8 4.4 82 63 52 55 54 53 54 55 50 40 35 27 26 24 8.7 5.9 2.7 5.8 5.1 5.6 5.4 5 4.2 3.1 2.3 3 3.1 3.2 4 3.6 3.2 1.8 1.9 1.7 1.7 71 54 42 27 17 16 15 6.4 4.9 4.1 <0.1 0 0 0 5.9 4.2 3.6 3 2.6 2.6 2.5

(0–227) (18–163) (22–130) (15–104) (1.8–100) (1.1–95) (0.62–90) (18–30) (13–24) (8.1–20) (4.6–16) (2.9–14) (2.8–14) (2.7–14) (5.0–14) (2.5–7.5) (3.5–12) (10–41) (2.3–5.4) (4.1–14) (4.4–17) (0.40–14) (0.56–4.6) (0–16) (0.13–3.1) (<0.1–4.5) (<0.1–5.5) (0.23–1.6) (0.54–0.55) (0.57–0.58) (0.31–0.32) (0.15–0.15) (0.12–0.12) (0.10–0.10) (<0.1–<0.1) (2.8–3.0) (3.0–3.1) (3.1–3.2) (1.7–1.8) (1.3–1.4) (4.7–42) (1.7–4.9) (0.91–6.5) (1.5–8.8) (0.13–26) (<0.1–30) (0.37–8.9) (0.15–13) (0.17–12) (1.0–7.1) (7.3–31) (11–48) (3.8–20) (9.0–43) (3.8–16) (2.9–6.2) (28–165) (22–125) (17–107) (18–112) (18–110) (17–109) (18–109) (42–70) (43–58) (38–43) (32–37) (25–29) (24–28) (22–26) (0.40–29) (0.10–23) (1.0–5.2) (<0.1–23) (0.40–16) (0.25–19) (0.32–17) (2.1–9.0) (1.6–7.9) (1.1–6.3) (0.98–4.1) (1.2–5.6) (1.3–5.8) (1.3–6.0) (3.8–4.1) (3.4–3.8) (2.8–3.6) (1.6–2.1) (1.6–2.2) (1.4–1.9) (1.4–2.0) (20–154) (21–103) (16–79) (11–50) (7.5–30) (7.0–28) (6.6–27) (2.0–13) (<0.1–22) (0.57–11) (0–0.10) (0–<0.1) (0–<0.1) (0–<0.1) (2.7–10) (2.0–7.3) (1.4–6.8) (1.3–5.5) (1.0–5.0) (1.0–4.9) (1.1–4.6)

0.45 0.68 0.6 0.47 0.33 0.32 0.28 20 14 10 8.5 9.6 10 11 0.01 <0.01 <0.01 0.022 <0.01 <0.01 <0.01 0.21 0.11 0.17 0.067 0.076 0.084 0.053 0.58 0.67 0.49 0.51 0.48 0.5 0.47 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.038 0.071 0.12 0.1 0.049 0.054 0.052 <0.01 0.034 0.049 0.022 0.045 0.021 0.014 30 29 32 37 39 38 39 620 630 600 540 470 460 450 96 90 85 79 73 72 71 0.086 0.075 0.059 0.045 0.053 0.055 0.057 2.5 2.9 2.7 2.1 2.3 2.3 3.9 1.9 1.7 1.5 1.2 0.9 0.86 0.83 <0.01 <0.01 <0.01 0

(<0.01–1.9) (0.220–1.4) (0.250–1.1) (0.180–0.900) (0.045–0.870) (0.046–0.870) (0.028–0.810) (9.3–36) (7.1–24) (5.3–17) (4.1–14) (4.9–16) (5.3–16) (5.7–17) (<0.01–0.019) (<0.01–<0.01) (<0.01–0.012) (0.011–0.036) (<0.01–0.012) (<0.01–0.015) (<0.01–0.015) (0.079–0.400) (0.033–0.240) (0.080–0.280) (0.024–0.130) (0.032–0.140) (0.037–0.150) (0.016–0.110) (0.270–1.0) (0.320–1.2) (0.170–0.980) (0.200–0.950) (0.210–0.870) (0.220–0.880) (0.200–0.840) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.011–0.081) (0.021–0.150) (0.050–0.210) (0.052–0.180) (0.019–0.093) (0.023–0.097) (0.022–0.094) (<0.01–0.017) (0.013–0.065) (0.023–0.085) (<0.01–0.039) (0.022–0.076) (<0.01–0.039) (<0.01–0.029) (12–55) (12–54) (12–61) (14–71) (14–76) (14–76) (13–77) (480–790) (480–800) (480–740) (470–630) (410–530) (400–520) (390–500) (78–110) (74–110) (69–100) (64–94) (60–88) (59–87) (58–86) (0.037–0.160) (0.030–0.140) (0.022–0.110) (0.018–0.083) (0.025–0.092) (0.026–0.095) (0.027–0.099) (1.0–4.6) (1.2–5.4) (1.1–4.9) (0.890–3.9) (0.850–4.4) (0.770–4.6) (1.9–6.6) (0.690–3.8) (0.810–2.9) (0.710–2.6) (0.560–2.0) (0.420–1.6) (0.400–1.5) (0.380–1.5) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–<0.01)

464 629 560 446 314 313 270 938 625 431 335 353 364 380 111 54 72 216 55 86 91 123 59 79 29 31 33 21 17 18 13 12 11 11 10 43 45 47 26 20 170 46 86 123 172 163 91 101 97 50 197 256 110 221 100 65 715 620 586 607 568 549 541 1 000 904 775 633 502 484 461 223 202 184 167 152 149 146 53 44 34 25 29 29 30 82 84 68 47 45 44 73 619 473 364 251 171 160 151 85 54 32 0.26

(2.8–2 010) (203–1 290) (237–1 020) (172–848) (44–844) (44–837) (27–782) (425–1 650) (308–1 050) (221–710) (162–569) (181–580) (191–591) (204–608) (43–213) (22–99) (35–122) (109–359) (17–116) (41–147) (46–151) (47–236) (18–125) (38–134) (11–57) (13–56) (15–60) (6.2–44) (7.9–30) (8.7–31) (4.5–25) (4.9–23) (4.8–20) (5.1–20) (4.5–19) (13–91) (13–96) (14–99) (7.6–54) (6.1–43) (59–341) (14–97) (26–183) (36–261) (74–312) (81–273) (35–172) (43–182) (42–175) (12–112) (76–376) (119–444) (48–198) (108–372) (40–187) (19–138) (289–1 330) (250–1 160) (219–1 130) (230–1 160) (208–1 100) (194–1 080) (187–1 080) (768–1 270) (692–1 140) (616–953) (544–729) (441–566) (425–546) (405–520) (182–267) (166–243) (150–221) (136–201) (124–182) (121–179) (119–175) (23–96) (18–81) (12–65) (10–46) (13–50) (14–51) (14–52) (33–152) (35–154) (29–125) (20–86) (17–86) (15–88) (35–125) (222–1 210) (225–810) (173–624) (120–429) (79–297) (74–279) (70–264) (24–185) (2.4–185) (5.3–82) (<0.1–0.54)

0.056 0.045 0.038 0.033 0.029 0.028 0.027

(0.027–0.097) (0.019–0.081) (0.015–0.073) (0.013–0.060) (0.013–0.052) (0.013–0.049) (0.014–0.045)

59 46 39 32 28 27 26

(28–102) (20–84) (15–74) (13–60) (13–50) (12–47) (13–43)

0.36 0.35 0.3 0.25 0.21 0.21 0.2 8.8 7.2 6.1 5.7 6.1 6.1 6.2 <0.01 <0.01 <0.01 0.013 <0.01 <0.01 <0.01 0.16 0.1 0.11 0.054 0.056 0.06 0.044 0.4 0.45 0.4 0.38 0.35 0.35 0.34 0 0 0 0 0 <0.01 <0.01 0.032 0.055 0.086 0.066 0.037 0.038 0.037 <0.01 0.025 0.03 0.013 0.024 0.015 <0.01 13 15 19 22 24 24 25 240 250 260 260 260 260 260 73 48 25 49 51 53 53 0.059 0.051 0.041 0.032 0.031 0.032 0.033 1.8 2.2 2 1.6 1.8 1.9 2.6 0.97 0.86 0.76 0.67 0.57 0.55 0.54 <0.01 <0.01 <0.01 0 0 0 0 0.036 0.032 0.027 0.023 0.017 0.016 0.015

(0.100–0.800) (0.200–0.540) (0.210–0.400) (0.170–0.360) (0.092–0.380) (0.089–0.370) (0.086–0.360) (7.5–10) (6.3–8.2) (5.5–6.7) (5.2–6.1) (5.7–6.5) (5.7–6.6) (5.8–6.7) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.011–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.140–0.190) (0.088–0.110) (0.095–0.120) (0.047–0.061) (0.049–0.064) (0.052–0.068) (0.038–0.049) (0.350–0.450) (0.390–0.510) (0.350–0.450) (0.330–0.430) (0.300–0.390) (0.310–0.400) (0.300–0.380) (0–0) (0–0) (0–0) (0–0) (0–0) (<0.01–<0.01) (<0.01–<0.01) (0.028–0.036) (0.048–0.062) (0.076–0.098) (0.057–0.074) (0.032–0.042) (0.033–0.043) (0.032–0.042) (<0.01–<0.01) (0.021–0.031) (0.024–0.036) (0.011–0.016) (0.019–0.029) (0.012–0.018) (<0.01–<0.01) (8.5–18) (10–21) (12–26) (14–31) (16–34) (16–34) (16–35) (150–360) (200–300) (210–310) (210–310) (210–310) (210–310) (210–310) (64–83) (42–55) (22–28) (43–56) (44–57) (47–60) (46–60) (0.047–0.071) (0.039–0.063) (0.030–0.053) (0.026–0.039) (0.025–0.038) (0.026–0.039) (0.027–0.040) (1.6–2.1) (1.9–2.5) (1.7–2.2) (1.4–1.8) (1.6–2.0) (1.7–2.1) (2.3–3.0) (0.600–1.4) (0.710–1.0) (0.620–0.910) (0.540–0.800) (0.470–0.680) (0.460–0.660) (0.440–0.640) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (0–0) (0–0) (0–0) (0.030–0.042) (0.027–0.037) (0.021–0.034) (0.018–0.028) (0.015–0.020) (0.014–0.019) (0.013–0.018)

379 325 279 240 206 200 194 405 314 254 225 224 223 223 88 40 46 125 34 57 54 98 53 51 24 23 24 17 12 12 10 9.2 7.9 7.9 7.6 0 0 0 0 0 81 37 73 96 126 102 68 71 69 45 147 156 67 116 73 24 308 322 349 358 348 346 348 393 360 329 301 275 270 265 171 108 54 105 105 109 108 36 30 23 18 17 17 18 61 62 51 35 35 36 50 312 240 185 142 108 103 97 72 39 13 0 0 0 0 38 33 28 22 17 16 14

(104–827) (185–505) (200–371) (158–338) (89–371) (86–360) (83–349) (345–470) (274–356) (228–281) (207–243) (209–240) (208–239) (208–239) (77–99) (35–46) (40–52) (110–142) (30–39) (50–65) (47–61) (85–110) (46–60) (45–58) (21–27) (20–26) (21–27) (15–20) (10–13) (11–14) (9.0–12) (8.1–10) (6.9–9.0) (7.0–9.0) (6.6–8.6) (0–0) (0–0) (0–0) (0–0) (0–0) (71–91) (32–42) (64–83) (84–109) (110–143) (89–115) (60–77) (62–81) (60–78) (36–54) (119–178) (127–189) (54–81) (94–140) (59–88) (20–29) (203–435) (212–453) (230–492) (236–505) (229–491) (228–488) (230–490) (243–580) (294–432) (269–395) (246–361) (227–328) (223–322) (219–316) (150–194) (95–123) (48–62) (92–119) (92–118) (96–124) (95–122) (29–44) (23–37) (17–30) (14–22) (13–21) (14–21) (14–21) (53–69) (55–71) (44–57) (31–40) (31–40) (32–41) (44–56) (193–460) (196–288) (151–222) (116–171) (89–129) (85–123) (80–116) (57–90) (13–80) (3.5–28) (0–0) (0–0) (0–0) (0–0) (32–45) (28–39) (22–35) (18–27) (14–20) (13–18) (12–17)

a

Rates are per 100 000 population.

270

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

            MORTALITY (EXCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATEa

PREVALENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

INCIDENCE (INCLUDING HIV) NUMBER (THOUSANDS) RATEa

Tuvalu

Vanuatu

Viet Nam

Wallis and Futuna Islands

a

Rates are per 100 000 population.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

271

western pacific region

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

<1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 69 76 81 85 89 90 91 <1 <1 <1 <1 <1 <1 <1

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.016 0.011 0.03 0.029 0.024 0.022 0.02 36 32 27 23 19 19 18 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(<0.01–0.019) (<0.01–0.021) (<0.01–0.014) (<0.01–0.010) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–0.032) (<0.01–0.019) (0.013–0.054) (0.012–0.052) (0.011–0.043) (<0.01–0.039) (<0.01–0.035) (21–55) (20–47) (18–38) (16–31) (13–26) (13–25) (12–25) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

98 73 68 50 18 12 37 11 6.5 16 14 10 9.1 7.9 52 42 33 27 22 21 20 17 4.2 4.2 4.7 2.8 2.6 13

(27–212) (5.1–227) (19–146) (15–105) (7.3–33) (3.8–24) (16–68) (3.9–22) (2.9–11) (6.9–29) (5.9–25) (4.5–18) (4.1–16) (3.6–14) (30–79) (26–61) (22–47) (19–37) (15–29) (14–28) (13–27) (9.2–27) (2.3–6.6) (3.6–4.9) (2.6–7.5) (1.4–4.6) (1.5–4.1) (5.6–23)

0.083 0.066 0.059 0.047 0.022 0.017 0.037 0.22 0.16 0.31 0.28 0.25 0.24 0.22 360 340 290 240 210 200 200 0.028 <0.01 <0.01 0.01 <0.01 <0.01 0.016

(0.029–0.160) (<0.01–0.170) (0.021–0.120) (0.017–0.089) (<0.01–0.044) (<0.01–0.036) (0.017–0.065) (0.062–0.470) (0.049–0.340) (0.140–0.550) (0.130–0.490) (0.110–0.440) (0.100–0.420) (0.090–0.410) (150–670) (150–610) (130–510) (110–440) (87–390) (82–380) (78–370) (0.011–0.052) (<0.01–0.019) (<0.01–0.019) (<0.01–0.021) (<0.01–0.012) (<0.01–0.011) (<0.01–0.026)

921 711 626 480 222 176 377 148 97 166 134 105 97 89 525 451 353 288 238 227 218 201 62 63 70 42 41 117

(327–1 820) (101–1 900) (226–1 230) (180–923) (75–448) (53–371) (172–658) (43–319) (29–204) (74–295) (63–232) (47–185) (42–175) (36–165) (212–976) (198–805) (156–629) (125–517) (97–440) (91–424) (86–410) (80–378) (19–132) (19–132) (21–148) (13–88) (13–85) (59–193)

0.048 0.04 0.034 0.028 0.018 0.015 0.024 0.19 0.11 0.2 0.17 0.16 0.16 0.16 170 170 160 150 140 140 130 0.022 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(0.031–0.069) (0.017–0.074) (0.022–0.048) (0.019–0.039) (0.014–0.021) (0.012–0.018) (0.019–0.029) (0.150–0.230) (0.085–0.130) (0.160–0.250) (0.140–0.210) (0.130–0.200) (0.130–0.190) (0.130–0.190) (120–240) (120–220) (120–210) (110–190) (100–180) (100–180) (99–170) (0.019–0.024) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

536 437 357 291 178 152 241 127 63 110 83 69 67 65 251 220 197 176 155 151 147 156 49 15 57 36 17 65

(347–766) (181–805) (231–510) (198–402) (145–215) (124–184) (196–290) (103–154) (51–76) (89–132) (68–99) (57–83) (55–80) (53–77) (172–344) (155–295) (142–260) (131–229) (115–201) (112–197) (109–192) (137–176) (43–55) (13–17) (50–64) (31–41) (15–19) (57–74)

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSE NUMBER RATE a

b

CASE DETECTION PERCENT

1990 1995 2000 2005 2010 2011 2012 Australia 1990 1995 2000 2005 2010 2011 2012 Brunei 1990 Darussalam 1995 2000 2005 2010 2011 2012 Cambodia 1990 1995 2000 2005 2010 2011 2012 China 1990 1995 2000 2005 2010 2011 2012 China, Hong Kong 1990 SAR 1995 2000 2005 2010 2011 2012 China, Macao 1990 SAR 1995 2000 2005 2010 2011 2012 Cook Islands 1990 1995 2000 2005 2010 2011 2012 Fiji 1990 1995 2000 2005 2010 2011 2012 French Polynesia 1990 1995 2000 2005 2010 2011 2012 Guam 1990 1995 2000 2005 2010 2011 2012 Japan 1990 1995 2000 2005 2010 2011 2012 Kiribati 1990 1995 2000 2005 2010 2011 2012 Lao People's 1990 Democratic 1995 Republic 2000 2005 2010 2011 2012 Malaysia 1990 1995 2000 2005 2010 2011 2012 Marshall Islands 1990 1995 2000 2005 2010 2011 2012

American Samoa

<1 <1 <1 <1 <1 <1 <1 17 18 19 21 22 23 23 <1 <1 <1 <1 <1 <1 <1 9 11 12 13 14 15 15 1 165 1 238 1 280 1 318 1 360 1 368 1 377 6 6 7 7 7 7 7 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 122 124 126 127 127 127 127 <1 <1 <1 <1 <1 <1 <1 4 5 5 6 6 7 7 18 21 23 26 28 29 29 <1 <1 <1 <1 <1 <1 <1

0.012 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1.2 1.2 1.2 1.2 1.4 1.4 1.5 0.16 0.18 0.35 0.19 0.27 0.26 0.28 53 62 71 68 63 62 61 1 800 1 600 1 400 1 200 1 100 1 000 1 000 7.5 7.1 6.9 6.5 5.7 5.4 5.5 0.39 0.46 0.52 0.46 0.45 0.44 0.46 0 <0.01 <0.01 <0.01 0 <0.01 <0.01 0.81 0.6 0.44 0.33 0.24 0.23 0.21 0.068 0.1 0.071 0.072 0.047 0.074 0.058 0.066 0.099 0.062 0.072 0.12 0.094 0.078 60 50 45 31 26 25 24 0.083 0.39 0.31 0.44 0.36 0.43 0.43 21 20 18 16 14 14 14 23 22 22 22 23 23 24 0.065 0.097 0.14 0.19 0.26 0.28 0.3

(<0.01–0.015) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (1.0–1.3) (1.1–1.4) (1.1–1.4) (1.1–1.4) (1.3–1.6) (1.2–1.6) (1.3–1.7) (0.140–0.190) (0.160–0.210) (0.310–0.400) (0.160–0.210) (0.240–0.310) (0.230–0.300) (0.240–0.320) (38–69) (48–78) (56–87) (57–81) (54–72) (53–71) (52–70) (1 400–2 200) (1 300–1 900) (1 200–1 600) (1 100–1 400) (930–1 200) (900–1 200) (880–1 100) (6.6–8.5) (6.3–8.1) (6.1–7.8) (5.7–7.4) (5.0–6.4) (4.8–6.2) (4.8–6.3) (0.350–0.450) (0.410–0.520) (0.450–0.580) (0.400–0.520) (0.400–0.510) (0.380–0.490) (0.410–0.530) (0–0) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (<0.01–<0.01) (<0.01–<0.01) (0.710–0.920) (0.530–0.680) (0.390–0.500) (0.290–0.370) (0.210–0.270) (0.200–0.260) (0.190–0.240) (0.059–0.077) (0.088–0.110) (0.062–0.081) (0.063–0.082) (0.041–0.053) (0.064–0.083) (0.050–0.065) (0.058–0.075) (0.087–0.110) (0.054–0.070) (0.063–0.082) (0.100–0.130) (0.083–0.110) (0.069–0.089) (52–67) (43–56) (40–51) (27–35) (23–30) (22–29) (21–28) (0.066–0.100) (0.310–0.460) (0.250–0.380) (0.360–0.530) (0.290–0.430) (0.350–0.520) (0.350–0.520) (13–31) (12–29) (11–26) (9.7–23) (8.8–21) (8.6–20) (8.4–20) (21–26) (20–25) (20–24) (20–24) (21–25) (21–25) (22–26) (<0.01–0.190) (0.024–0.220) (0.084–0.200) (0.050–0.420) (0.051–0.650) (0.054–0.690) (0.058–0.740)

26 12 6.9 13 7.8 7.8 7.3 6.8 6.8 6.2 5.9 6.5 6.3 6.5 64 63 106 51 68 65 68 580 578 577 510 437 424 411 153 129 109 92 78 75 73 129 116 101 94 81 77 77 110 116 120 98 85 80 83 0 13 6.5 5.9 0 5.6 5.6 112 77 54 40 28 26 24 34 47 30 28 18 27 21 50 68 40 46 73 59 48 49 40 36 25 20 20 19 116 505 372 488 366 432 429 492 403 330 270 221 213 204 127 108 95 86 82 81 80 137 190 263 363 502 536 572

(21–31) (9.4–14) (5.6–8.4) (10–15) (6.3–9.4) (6.3–9.4) (5.9–8.9) (6.0–7.7) (6.0–7.7) (5.5–7.0) (5.1–6.6) (5.7–7.3) (5.5–7.1) (5.7–7.4) (56–72) (55–71) (93–120) (45–58) (60–77) (57–74) (59–77) (423–761) (448–724) (458–710) (424–604) (376–503) (364–489) (353–474) (121–189) (106–154) (92–126) (80–105) (68–88) (66–85) (64–82) (113–146) (102–132) (89–115) (83–107) (71–91) (67–87) (68–88) (96–124) (102–131) (105–135) (86–111) (74–96) (70–91) (73–94) (0–0) (11–14) (5.7–7.3) (5.2–6.7) (0–0) (4.9–6.4) (4.9–6.3) (98–126) (68–87) (48–62) (35–45) (24–32) (23–29) (21–27) (30–39) (41–53) (26–34) (25–32) (15–20) (24–31) (18–24) (44–57) (60–77) (35–45) (40–52) (64–82) (51–66) (42–54) (43–55) (35–45) (32–41) (22–28) (18–23) (18–23) (17–22) (93–143) (410–609) (296–456) (396–588) (298–441) (351–521) (349–517) (304–725) (249–593) (204–486) (167–398) (137–326) (131–313) (126–301) (113–142) (97–120) (86–103) (79–94) (75–89) (74–88) (74–87) (14–396) (46–432) (161–389) (96–803) (97–1 230) (103–1 320) (110–1 400)

9 3 6 4 3 0.028 0.047 0.029 0.028 0.036 0.036 0.038 (0.024–0.031) (0.041–0.053) (0.026–0.033) (0.025–0.032) (0.031–0.041) (0.031–0.040) (0.033–0.043) 0.2 0.3 0.2 0.1 0.2 0.2 0.2 (0.14–0.18) (0.23–0.29) (0.13–0.17) (0.12–0.16) (0.14–0.18) (0.14–0.18) (0.14–0.19) 1 016 1 073 1 043 1 046 1 257 1 239 1 305 143 307 163 237 230 243 6 501 14 603 18 891 35 535 40 460 38 555 40 185 375 481 515 764 454 372 899 729 908 399 899 669 890 645 6 510 6 212 6 015 5 660 4 935 4 739 4 809 343 402 449 398 394 380 404 0 2 1 1 0 1 1 226 203 144 132 189 215 210 59 62 63 41 64 50

19 5.2 10 7.2 5.4 5.9 5.9 5.4 5.1 5.6 5.4 5.7 56 93 44 59 57 59 72 136 155 266 282 264 270 32 42 35 68 67 66 65 112 101 88 82 70 67 67 95 101 104 85 74 70 73 0 11 5.6 5.2 0 4.9 4.9 31 26 18 16 22 25 24 30 26 25 15 24 18

75 (62–93) 75 80 92 70 87 87 87 87 87 87 87 87 87 87 87 87 87 12 23 27 52 64 62 66 21 32 33 74 86 88 89 87 87 87 87 87 87 87 87 87 87 87 87 87 87 (62–93) (66–99) (76–110) (58–86) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (9.4–17) (19–30) (22–34) (44–63) (56–75) (54–73) (57–77) (17–27) (27–39) (28–38) (65–85) (76–98) (78–100) (79–100) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

<0.01 <0.01 <0.01 <0.01 0.99 5.1 7.9 5.8 3.1 3.1 2.7 0.18 1.4 4.2 6.3 7.6 7.6 7.3

(<0.01–<0.01) 0.6 (<0.1–2.0) (0–<0.01) 0.3 (0–1.4) (<0.01–<0.01) 0.9 (0.12–2.3) (0–<0.01) 0.4 (0–2.1) (0.72–1.3) 11 (8.0–14) (4.0–6.4) 48 (37–60) (6.3–9.7) 65 (51–80) (4.8–6.8) 43 (36–51) (2.7–3.6) 22 (19–25) (2.6–3.5) 21 (18–24) (2.3–3.1) 18 (15–21) (0.14–0.22) <0.1 (<0.1–<0.1) (1.2–1.7) 0.1 (0.10–0.14) (3.6–4.9) 0.3 (0.28–0.38) (5.5–7.2) 0.5 (0.42–0.54) (6.7–8.6) 0.6 (0.49–0.63) (6.7–8.6) 0.6 (0.49–0.63) (6.4–8.2) 0.5 (0.47–0.60)

0.054 0.036 0.049 0.044

(0.036–0.075) (0.022–0.053) (0.033–0.069) (0.026–0.067)

0.8 0.5 0.7 0.6

(0.53–1.1) (0.31–0.75) (0.46–0.97) (0.37–0.94)

<0.01 <0.01 <0.01 <0.01

(0–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

0.3 0.6 0.5 0.4

(0–1.3) (<0.1–1.7) (<0.1–1.5) (<0.1–1.5)

87 (77–99) 87 (77–99) 87 (77–99) 87 87 28 34 33 41 79 95 99 87 87 87 87 87 87 (77–99) (77–99) (25–32) (30–39) (29–37) (36–46) (70–90) (84–110) (87–110) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(<0.01–<0.01) <0.1 (<0.1–<0.1) (<0.01–<0.01) <0.1 (<0.1–0.10) (<0.01–<0.01) 0.2 (0.14–0.18) (<0.01–<0.01) 0.2 (0.21–0.27) (<0.01–<0.01) 0.2 (0.13–0.17) (<0.01–<0.01) 0.2 (0.13–0.17) (<0.01–<0.01) 0.2 (0.13–0.17)

<0.01 (0–<0.01) <0.01 0.24 0.22 0.15 0.13 0.1 0.1 0.098 (0–<0.01) (0.21–0.28) (0.20–0.25) (0.13–0.17) (0.11–0.15) (0.091–0.12) (0.089–0.12) (0.085–0.11)

1.2 (0–5.5) 0.3 0.2 0.2 0.1 0.1 <0.1 <0.1 <0.1 (0–2.9) (0.18–0.23) (0.16–0.20) (0.11–0.14) (<0.1–0.11) (<0.1–<0.1) (<0.1–<0.1) (<0.1–<0.1)

54 63 101 82 68 51 821 43 078 39 384 27 194 22 693 22 119 20 857 68 252 332 286 343 346 1 826 830 2 227 3 766 4 061 4 360 4 118 11 702 11 778 15 057 15 415 18 517 19 808 21 851

35 40 63 51 42 42 35 31 21 18 17 16 96 304 367 293 346 343 43 17 41 65 63 67 62 64 57 64 60 65 69 75

87 87 87 87 87 87 87 87 87 87 87 86 82 82 75 80 80 80 8.7 4.2 13 24 29 31 30 51 53 68 69 80 85 93

(77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (76–98) (67–100) (67–100) (62–93) (66–98) (66–98) (66–98) (5.9–14) (2.9–6.8) (8.5–20) (16–39) (19–46) (21–51) (21–49) (45–57) (47–58) (62–75) (64–76) (74–87) (78–93) (85–100)

<0.01 (<0.01–<0.01)

2.5 (1.7–3.4)

<0.01 0.026 0.092 0.17 0.23 0.24 0.25 0.18 1.1 1.9 2.2 2.3 2.3 2.3

(<0.01–<0.01) (0.015–0.039) (0.051–0.15) (0.093–0.28) (0.12–0.37) (0.13–0.39) (0.13–0.41) (0.16–0.20) (0.96–1.2) (1.7–2.1) (2.0–2.3) (2.1–2.5) (2.1–2.5) (2.2–2.6)

0.1 0.5 1.7 3 3.6 3.7 3.8 1 5.2 8 8.3 8.1 7.8 8

(<0.1–0.15) (0.30–0.81) (0.95–2.7) (1.6–4.8) (1.9–5.8) (2.0–6.0) (2.0–6.2) (0.88–1.1) (4.6–5.7) (7.3–8.8) (7.6–9.1) (7.4–8.8) (7.2–8.5) (7.4–8.7)

<0.01 (0–0.019) <0.01 (0–0.015)

6.1 (0–36) 2.6 (0–29)

34 111 193 139 145

65 213 368 265 276

25 59 73 49 48

(17–41) (27–220) (30–380) (20–260) (20–250)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

272

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSE NUMBER RATE a

b

CASE DETECTION PERCENT

Micronesia (Federated States of)

Mongolia

Nauru

New Caledonia

New Zealand

Niue

Northern Mariana Islands

Palau

Papua New Guinea

Philippines

Republic of Korea

Samoa

S ngapore

Solomon Islands

Tokelau

Tonga

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

<1 <1 <1 <1 <1 <1 <1 2 2 2 3 3 3 3 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 3 4 4 4 4 4 4 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 4 5 5 6 7 7 7 62 70 78 86 93 95 97 43 45 46 47 48 49 49 <1 <1 <1 <1 <1 <1 <1 3 3 4 4 5 5 5 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1

0.36 0.35 0.3 0.25 0.21 0.21 0.2 8.8 7.2 6.1 5.7 6.1 6.1 6.2 <0.01 <0.01 <0.01 0.013 <0.01 <0.01 <0.01 0.16 0.1 0.11 0.054 0.056 0.06 0.044 0.4 0.45 0.4 0.38 0.35 0.35 0.34 0 0 0 0 0 <0.01 <0.01 0.032 0.055 0.086 0.066 0.037 0.038 0.037 <0.01 0.025 0.03 0.013 0.024 0.015 <0.01 13 15 19 22 24 24 25 240 250 260 260 260 260 260 73 48 25 49 51 53 53 0.059 0.051 0.041 0.032 0.031 0.032 0.033 1.8 2.2 2 1.6 1.8 1.9 2.6 0.97 0.86 0.76 0.67 0.57 0.55 0.54 <0.01 <0.01 <0.01 0 0 0 0 0.036 0.032 0.027 0.023 0.017 0.016 0.015

(0.100–0.800) (0.200–0.540) (0.210–0.400) (0.170–0.360) (0.092–0.380) (0.089–0.370) (0.086–0.360) (7.5–10) (6.3–8.2) (5.5–6.7) (5.2–6.1) (5.7–6.5) (5.7–6.6) (5.8–6.7) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.011–0.014) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0.140–0.190) (0.088–0.110) (0.095–0.120) (0.047–0.061) (0.049–0.064) (0.052–0.068) (0.038–0.049) (0.350–0.450) (0.390–0.510) (0.350–0.450) (0.330–0.430) (0.300–0.390) (0.310–0.400) (0.300–0.380) (0–0) (0–0) (0–0) (0–0) (0–0) (<0.01–<0.01) (<0.01–<0.01) (0.028–0.036) (0.048–0.062) (0.076–0.098) (0.057–0.074) (0.032–0.042) (0.033–0.043) (0.032–0.042) (<0.01–<0.01) (0.021–0.031) (0.024–0.036) (0.011–0.016) (0.019–0.029) (0.012–0.018) (<0.01–<0.01) (8.5–18) (10–21) (12–26) (14–31) (16–34) (16–34) (16–35) (150–360) (200–300) (210–310) (210–310) (210–310) (210–310) (210–310) (64–83) (42–55) (22–28) (43–56) (44–57) (47–60) (46–60) (0.047–0.071) (0.039–0.063) (0.030–0.053) (0.026–0.039) (0.025–0.038) (0.026–0.039) (0.027–0.040) (1.6–2.1) (1.9–2.5) (1.7–2.2) (1.4–1.8) (1.6–2.0) (1.7–2.1) (2.3–3.0) (0.600–1.4) (0.710–1.0) (0.620–0.910) (0.540–0.800) (0.470–0.680) (0.460–0.660) (0.440–0.640) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (0–0) (0–0) (0–0) (0–0) (0.030–0.042) (0.027–0.037) (0.021–0.034) (0.018–0.028) (0.015–0.020) (0.014–0.019) (0.013–0.018)

379 325 279 240 206 200 194 405 314 254 225 224 223 223 88 40 46 125 34 57 54 98 53 51 24 23 24 17 12 12 10 9.2 7.9 7.9 7.6 0 0 0 0 0 81 37 73 96 126 102 68 71 69 45 147 156 67 116 73 24 308 322 349 358 348 346 348 393 360 329 301 275 270 265 171 108 54 105 105 109 108 36 30 23 18 17 17 18 61 62 51 35 35 36 50 312 240 185 142 108 103 97 72 39 13 0 0 0 0 38 33 28 22 17 16 14

(104–827) (185–505) (200–371) (158–338) (89–371) (86–360) (83–349) (345–470) (274–356) (228–281) (207–243) (209–240) (208–239) (208–239) (77–99) (35–46) (40–52) (110–142) (30–39) (50–65) (47–61) (85–110) (46–60) (45–58) (21–27) (20–26) (21–27) (15–20) (10–13) (11–14) (9.0–12) (8.1–10) (6.9–9.0) (7.0–9.0) (6.6–8.6) (0–0) (0–0) (0–0) (0–0) (0–0) (71–91) (32–42) (64–83) (84–109) (110–143) (89–115) (60–77) (62–81) (60–78) (36–54) (119–178) (127–189) (54–81) (94–140) (59–88) (20–29) (203–435) (212–453) (230–492) (236–505) (229–491) (228–488) (230–490) (243–580) (294–432) (269–395) (246–361) (227–328) (223–322) (219–316) (150–194) (95–123) (48–62) (92–119) (92–118) (96–124) (95–122) (29–44) (23–37) (17–30) (14–22) (13–21) (14–21) (14–21) (53–69) (55–71) (44–57) (31–40) (31–40) (32–41) (44–56) (193–460) (196–288) (151–222) (116–171) (89–129) (85–123) (80–116) (57–90) (13–80) (3.5–28) (0–0) (0–0) (0–0) (0–0) (32–45) (28–39) (22–35) (18–27) (14–20) (13–18) (12–17)

<0.01 <0.01 <0.01 0.011

(<0.01–<0.01) <0.1 (<0.1–<0.1) (<0.01–<0.01) 0.2 (0.21–0.24) (<0.01–<0.01) 0.3 (0.27–0.31) (<0.01–0.011) 0.4 (0.35–0.41)

367 172 91 98 164 148 144 1 659 2 780 3 109 4 601 4 458 4 217 4 128 7 4 11 3 5 143 87 94 47 49 52 38 348 391 344 332 301 305 293 0 0 0 0 0 1 0 28 48 75 57 32 33 32 19 10 19 12 4 2 497 8 041 10 520 12 564 14 531 14 893 20 557 317 008 119 186 119 914 137 100 166 323 195 560 216 627 63 904 42 117 21 782 42 892 44 063 46 253 43 702 44 45 43 24 14 20 22 1 591 1 889 1 728 1 376 1 560 1 641 2 301 382 352 302 397 338 398 361 1 2 0 0 0 0 23 20 24 18 11 9 11

381 160 85 92 158 143 139 76 121 130 182 164 153 148 76 40 109 30 50 85 46 45 21 20 21 15 10 11 8.9 8 6.9 6.9 6.6 0 0 0 0 0 70 0 64 83 110 89 59 62 60 110 50 93 58 19 60 171 196 206 212 212 287 512 171 154 160 178 206 224 149 94 47 91 91 95 89 27 26 25 13 7.5 11 12 53 54 44 31 31 32 43 122 98 73 85 64 74 66 62 132 0 0 0 0 24 21 24 18 11 8.6 10

100 49 30 38 77 72 72 19 39 51 81 73 69 66 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87

(46–370) (32–87) (23–42) (27–58) (43–180) (40–170) (40–170) (16–22) (34–44) (46–57) (75–88) (68–79) (64–74) (62–71) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

<0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

0.1 0.2 0.2 0.1 0.1 0.1 0.1

(<0.1–0.11) (0.17–0.22) (0.13–0.17) (0.12–0.16) (0.11–0.15) (0.11–0.15) (0.11–0.14)

87 0 87 87 87 87 87 87 87

(77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99)

75 (62–93) 75 80 80 80 19 53 56 58 61 61 82 130 48 47 53 65 76 84 87 87 87 87 87 87 82 75 89 110 75 45 62 66 87 87 87 87 87 87 87 39 41 40 60 59 72 67 86 340 0 (62–93) (66–98) (66–98) (66–98) (14–30) (38–80) (40–85) (41–87) (43–92) (44–93) (59–120) (88–210) (40–58) (39–57) (44–65) (54–79) (64–92) (71–100) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (73–94) (62–93) (71–110) (82–140) (62–92) (37–56) (51–78) (55–82) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (77–99) (27–64) (34–50) (33–49) (50–73) (50–72) (60–87) (57–82) (69–110) (160–1 000)

0.1 0.46 1 1.4 1.1 1.2 1.1 0.024 0.025 0.077 0.18 0.39 0.46 0.46 0.051 0.044 0.023 0.089 0.13 0.14 0.15

(0.067–0.14) 2.4 (1.6–3.4) (0.30–0.65) 9.7 (6.4–14) (0.68–1.4) 19 (13–27) (0.92–2.0) 23 (15–32) (0.75–1.6) 17 (11–23) (0.76–1.6) 16 (11–23) (0.71–1.5) 15 (9.9–21) (0.015–0.036) <0.1 (<0.1–<0.1) (0.020–0.030) <0.1 (<0.1–<0.1) (0.063–0.092) 0.1 (<0.1–0.12) (0.15–0.22) 0.2 (0.17–0.25) (0.32–0.46) 0.4 (0.34–0.49) (0.38–0.55) 0.5 (0.40–0.58) (0.38–0.55) 0.5 (0.39–0.57) (0.045–0.058) 0.1 (0.10–0.14) (0.038–0.049) 0.1 (<0.1–0.11) (0.020–0.026) <0.1 (<0.1–<0.1) (0.078–0.10) 0.2 (0.17–0.21) (0.12–0.15) 0.3 (0.24–0.31) (0.13–0.16) 0.3 (0.26–0.33) (0.13–0.17) 0.3 (0.27–0.35)

<0.01 0.044 0.06 0.06 0.07 0.072 0.098

(<0.01–<0.01) (0.038–0.049) (0.053–0.068) (0.052–0.068) (0.061–0.079) (0.063–0.081) (0.086–0.11)

0.2 1.3 1.5 1.3 1.4 1.4 1.9

(0.21–0.27) (1.1–1.4) (1.3–1.7) (1.2–1.5) (1.2–1.6) (1.2–1.6) (1.6–2.1)

64 63 88 79 63 55 73

(54–76) (54–75) (70–110) (65–99) (54–75) (47–66) (62–87)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

273

western pacific region

           INCIDENCE (INCLUDING HIV) YEAR POPULATION (MILLIONS) NUMBER (THOUSANDS) RATE a

INCIDENCE HIV-POSITIVE NUMBER (THOUSANDS) RATE a

NOTIFIED NEW AND RELAPSEb NUMBER RATEa

CASE DETECTION PERCENT

Tuvalu

Vanuatu

Viet Nam

Wallis and Futuna Islands

1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

<1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 69 76 81 85 89 90 91 <1 <1 <1 <1 <1 <1 <1

0.048 0.04 0.034 0.028 0.018 0.015 0.024 0.19 0.11 0.2 0.17 0.16 0.16 0.16 170 170 160 150 140 140 130 0.022 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

(0.031–0.069) (0.017–0.074) (0.022–0.048) (0.019–0.039) (0.014–0.021) (0.012–0.018) (0.019–0.029) (0.150–0.230) (0.085–0.130) (0.160–0.250) (0.140–0.210) (0.130–0.200) (0.130–0.190) (0.130–0.190) (120–240) (120–220) (120–210) (110–190) (100–180) (100–180) (99–170) (0.019–0.024) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01) (<0.01–<0.01)

536 437 357 291 178 152 241 127 63 110 83 69 67 65 251 220 197 176 155 151 147 156 49 15 57 36 17 65

(347–766) (181–805) (231–510) (198–402) (145–215) (124–184) (196–290) (103–154) (51–76) (89–132) (68–99) (57–83) (55–80) (53–77) (172–344) (155–295) (142–260) (131–229) (115–201) (112–197) (109–192) (137–176) (43–55) (13–17) (50–64) (31–41) (15–19) (57–74)

0.083 1.7 7.6 9.2 9.2 9.3

(0.059–0.11) (1.3–2.3) (5.6–9.9) (6.8–12) (6.8–12) (6.9–12)

0.1 2.2 8.9 10 10 10

(<0.1–0.15) (1.6–2.9) (6.6–12) (7.6–13) (7.6–13) (7.6–13)

23 36 16 12 14 12 19 140 79 152 76 116 110 125 50 203 55 739 89 792 94 916 97 448 98 804 102 112 6 7 2

255 390 170 124 142 122 193 95 47 82 36 49 45 51 73 73 111 112 109 110 112 42 49 15

48 89 48 43 80 80 80 75 75 75 44 71 68 78 29 33 56 63 70 73 76

(33–74) (48–220) (33–74) (31–63) (66–98) (66–98) (66–98) (62–93) (62–93) (62–93) (37–54) (59–86) (57–83) (66–95) (21–42) (25–47) (43–78) (49–86) (54–95) (56–98) (59–100)

87 (77–99) 87 (77–99) 87 (77–99)

a b

Rates are per 100 000 population. NOTIFIED NEW AND RELAPSE includes cases for which the treatment history is unknown.

274

NOTIFIED NEW AND RELAPSE nc ude

ases fo whi h 2013 he tre tm GLOBAL TUBERCULOSIS REPORT

story s unk

wn. years can be downloaded from www.who.int/tb/data Data for all

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL HISTORY POS AMONG SMEAR- SMEAR-NEGATIVE/ EXTRAOTHER RELAPSE NEW PULM RELAPSE RETREAT UNKNOWN POSITIVE UNKNOWN PULMONARY – – 100 60 0 0 – – – 41 42 40 41 42 – – 34 77 83 68 60 – 88 93 75 68 67 64 – 40 47 59 50 44 37 – – 38 33 39 38 40 – 60 47 46 41 54 53 100 0 100 100 44 41 60 68 66 63 67 – – 60 46 42 45 72 – – 90 51 43 42 38 – 36 38 52 49 49 50 – – 53 61 56 56 52 – 54 77 85 89 86 86 – 62 60 63 72 72 73

NEW AND RELAPSE NOTIFICATION RATE 1990–2012 American Samoa a

YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012

NEW AND RELAPSE b

9 3 6 4 3 1 016 1 073 1 043 1 046 1 257 1 239 1 305 143 307 163 237 230 243 6 501 14 603 18 891 35 535 40 460 38 555 40 185 375 481 515 764 454 372 899 729 908 399 899 669 890 645 6 510 6 212 6 015 5 660 4 935 4 739 4 809 343 402 449 398 394 380 404 0 2 1 1 0 1 1 226 203 144 132 189 215 210 59 62 63 41 64 50 2 3 0 0 0 2 3 3 1 0 1 0 0 1 0 0 0 1 0 0

0 0 0

0 0 0

0 0 0

• 19 Australia

0•

•6 Brunei Darussalam

6•

251 241 274 301 290

362 339 410 436 408

369 450 457 463 498

5 2 63

17 16 41 20 26

27 24 29 20

17 43 65 49 46

70 17 20

• 56 Cambodia

59 •

84 101 146 109 119 11 101 14 822 21 001 17 454 15 812 14 838 134 488 204 765 472 719 429 899 377 005 316 332

166 30 30 52 79 1 465 1 108 7 057 8 301 7 686 8 509 203 088 229 943 329 157 432 868 481 514 536 050

42 27 43 48 31 1 428 2 147 6 759 14 239 14 690 15 290 1 560 42 845 6 325 6 540 6 479

13 13 0

15 5 5 8 14 605 814 718 466 367 446 18 693 19 664 49 707 39 307 34 610 31 784

0 0 0 0

15 5 5 8 14 605 814 1 306 1 634 1 482 519 18 693 73 144 140 487 54 216 46 825 41 817

0 0 0 0

• 72 China

270 •

0 0 0

0 0 1 102

• 32 China, Hong Kong SAR

65 •

0 0 0

53 480 90 780 14 909 12 215 10 033

5 301 0 0 0

• 112 China, Macao SAR

67 •

1 940 1 561 1 475 1 380 1 463 141 160 136 123 148 156 0 2 0 1 0 1 0 84 68 62 63 89 107 111

3 115 3 179 2 352 2 244 2 206 94 180 162 175 126 139 0 0 1 0 0 0 0 105 99 42 29 45 62 54

772 701 792 815 817 70 50 43 49 46 31 0 0 0 0 0 0 0 37 34 40 40 45 44 40

0 0 0 0

188 219 316 300 323 49 12 14 21 21 26 0 0 0 0 0 0 1 2 0

594 500 197 187 160

782 719 513 487 483 49 12 31 60 23 28 0 0 0 0 0 0 1 2 0 12 7 13

0 0 0 0

• 95 Cook Islands

73 •

•0 Fiji

5•

0 0 0 0 0 0 0 0 0 0 0

17 39 2 2 0 0 0 0 0 0 0 0 0 2 5 8

43 26 39 52 0 0 0 0 0 0 0

• 31 French Polynesia

24 •

0 0 0

10 2 5

0 0 0

• 30 Guam

18 •

29 21 13 22 26

19 25 18 27 10

10 14 6 13 8

0 0 0

1 3 4 2 6

0 0 0 0

1 3 4 2 6

0 0 0 0

•0 Japan

42 •

• 42 Kiribati

16 •

54 63 101 82 68 51 821 43 078 39 384 27 194 22 693 22 119 20 857 68 252 332 286 343 346 1 826 830 2 227 3 766 4 061 4 360 4 118 11 702 11 778 15 057 15 415 18 517 19 808 21 851

43 27 39 28 23 14 367 11 853 10 931 8 237 7 937 7 663

5 26 51 39 37 25 172 19 118 10 056 8 630 8 231 7 675

6 9 9 11 8 2 803 7 046 5 340 4 632 4 826 4 609

0 0 0 0

1 1 2 3 0 736 1 367 867 1 194 1 125 910

1 0 0 0

1 2 2 3 0 736 1 367 1 992 1 762 1 687 1 336

0 0 1 0

0 0 0

1 125 568 562 426

0

• 96 Lao People's Democratic Republic

343 •

54 124 118 140 134 478 1 526 2 801 3 119 3 271 3 062 6 688 8 156 8 446 11 135 11 862 13 311

47 79 91 109 122 404 457 484 394 516 484 4 021 5 517 4 862 4 338 4 501 4 993

106 126 71 87 73 95 180 275 323 349 351 1 069 1 384 1 702 2 545 2 888 2 945

0 0 9

3 3 6 7 8 2 64 139 163 170 168 210 0 332 499 557 602

7 8 11 2

3 10 14 18 10 2 64 180 185 197 206 210 0 983 1 319 1 415 1 461

0 0 0

• 43 Malaysia

62 •

41 22 27 38

67 62 54 53

• 64 a b

75 •

0 0 0 0

651 820 858 859

73 0 0 0

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

275

western pacific region

588 1 168 1 115 73

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN – – 31 61 48 59 50 – 10 18 48 40 38 36 – 25 65 68 72 72 74 – – 100 0 50 75 – – 21 57 52 56 42 54 – 26 36 42 56 52 41 – 0

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Marshall Islands YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSEb

•0 Micronesia (Federated States of)

276 •

• 381 Mongolia

139 •

• 76 Nauru

148 •

34 111 193 139 145 367 172 91 98 164 148 144 1 659 2 780 3 109 4 601 4 458 4 217 4 128 7 4 11 3 5 143 87 94 47 49 52 38 348 391 344 332 301 305 293 0 0 0 0 0 1 0 28 48 75 57 32 33 32 19 10 19 12 4 2 497 8 041 10 520 12 564 14 531 14 893 20 557 317 008 119 186 119 914 137 100 166 323 195 560 216 627 63 904 42 117 21 782 42 892 44 063 46 253 43 702 44 45 43 24 14 20 22 1 591 1 889 1 728 1 376 1 560 1 641 2 301 382 352 302 397 338 398 361

11 48 59 44 54 9 15 32 53 45 43 455 1 389 1 868 1 837 1 723 1 716

25 31 64 30 53 79 69 35 79 73 77 1 330 732 897 701 684 617

9 28 65 57 29 18 4 19 25 28 22 976 862 1 620 1 675 1 578 1 611

0 0 0

0 4 2 8 4 2 3 7 3 2 2 82 126 216 245 232 184

1 8 12 2

0 5 10 20 6 2 3 21 13 4 4 82 126 341 588 548 509

0 3 0 5

5 0 0 0

14 10 2 2

4 0 0

0 0 0 0

125 343 316 325

0 0 0 0

4 0 1 3

0 11 1 1

0 1 1 0 0

0 0 0 0 0

0 0 0 0 0

• 76 New Caledonia

0•

• 85 New Zealand

15 •

21 20 16 20 13 13 78 74 83 86 88 68 0 0 0 0 0 0 14 27 15 17 15 10 9 3 9 4 3 1 652 1 933 1 805 2 584 1 882 2 862 94 768 67 056 81 647 89 198 93 580 94 006 11 754 8 216 11 638 11 596 11 714 12 137 15 13 11 6 6 15 455 248 552 530 592 678 109 109 169 133 159 157

81 15 15 16 18 11 222 133 114 68 81 99 1 0 0 0 0 26 37 35 13 16 17 6 6 10 6 1 3 767 4 405 5 105 5 907 6 494 9 195 140 712 52 858 50 347 72 440 96 529 115 263 19 360 11 304 18 460 18 660 18 386 18 938 30 18 8 5 12 4 1 187 869 570 735 717 1 219 133 128 161 98 108 87

9 29 15 13 19 12 34 130 95 134 121 112

4 4 1 0 0 1 2 1 4 7 11 7 2 11 0

6 8 0 0

4 4 7 8 2 1 4 7 19 11 6 15 0

0 0 0 0

• 10 Niue

7•

29 6 13 3

0 8 4 4 4

0

•0 Northern Mariana Islands

0•

0 0 0 8 11 7 2 2 4 4 1 0 1 0 2 349 3 227 4 198 5 798 6 373 8 277 8 1 149 1 610 2 234 3 274

0 1 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 273 955 1 456 242 144 223 8

0 0 0

0 0 0 0 0 0 0 0 2 0

0 0 0 – 35 42 30 57 48 37 – 60 – 33 47 40 75 – 30 30 26 30 22 24 – 40 56 62 55 49 45 – 38 42 39 38 39 39 – 33 42 58 55 33 79 – 28 22 49 42 45 36 – 45 46 51 58 60 64

• 64 Palau

60 •

0 0 0 1

0 0 0 2

0 0 0 0

•0 Papua New Guinea

19 •

0 0 0

0 0 0 0

0 0 1 0 273 955 1 456 1 824 1 575 2 154 8 3 957 11 141 13 745 17 619 2 082 2 262 7 098 6 876 7 270 9 987 0 0 0 0 0 0 120 55 153 130 162 161 13 0 5 5 11 16

0 0 0

• 60 Philippines

287 •

0 0

1 582 1 431 1 931

0 0

• 512 Republic of Korea

224 •

0 0 0 0

3 957 3 075 3 217 4 084 2 082 2 262 3 021 2 838 3 032 4 157 0 0 0 0 0 0 120 55 60 82 108 98 13 0 5 2 4 5

8 066 10 528 13 535

0 0 0

• 149 Samoa

89 •

5 171 8 795 9 457 8 470 6 12 5 3 2 3 127 165 174 213 224 306 97 65 62 105 127 112

0 0 0 0

4 077 4 038 4 238 5 830

4 602 2 174 3 664 0

• 27 Singapore

12 •

0 0 0 0

0 0 0 0

0 0 0

• 53 Solomon Islands

43 •

0 0 0 0

93 48 54 63

20 0 0 0

• 122 a b

66 •

0 0 0 0

0 3 7 11

0 0 0 0

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

276

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

     NEW CASES % SMEARRE-TREAT EXCL. TOTAL SMEAR- SMEAR-NEGATIVE/ EXTRAHISTORY POS AMONG OTHER RELAPSE NEW PULM POSITIVE UNKNOWN PULMONARY RELAPSE RETREAT UNKNOWN 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 – 50 0 0 0 – – 82 75 79 67 67 90 – 32 0 62 71 50 80 – 53 53 62 57 78 70 – 82 75 77 74 71 70 – 60 – 14 – 100 –

NEW AND RELAPSE NOTIFICATION RATEa 1990–2012 Tokelau YEAR 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 1990 1995 2000 2005 2010 2011 2012 NEW AND RELAPSEb 1 2 0 0 0 0 23 20 24 18 11 9 11 23 36 16 12 14 12 19 140 79 152 76 116 110 125 50 203 55 739 89 792 94 916 97 448 98 804 102 112 6 7 2

0 0 0

0 0 0

• 62 Tonga

0•

• 24 Tuvalu

10 •

9 15 11 6 6 9 6 0 5 5 4 8 30 63 35 44 49 51 37 550 53 169 55 492 52 145 50 751 51 033 3 1 2

2 5 3 3 3 1 13 7 3 2 4 2 27 56 21 33 14 22 8 379 17 993 16 429 18 237 20 373 21 706 2 6 0

9 3 4 2 0 1 16 7 4 7 4 9 21 28 17 35 46 51 6 194 13 137 16 670 17 651 18 077 18 904 0

0 1 0 0 0 0 0 0 1 3 0 1 1 0 0 0

0 1 0 0 0 1 3 0 1 1 1 5 8 1 3 2 3 616 5 493 7 301 8 408 8 639 9 053 1 0 0 0

• 255 Vanuatu

193 •

0 0 0

0 0 0 1 5 3 1 1 1 3 616 5 493 6 325 6 834 6 925 7 259 1

0 0 0

• 95 Viet Nam

51 •

•0 Wallis and Futuna Islands

0•

0 0 2 678 3 210

976 1 574 1 714 1 794

0 2 581

0

0

0

0

0

0

•0

0•

a b

Rates are per 100 000 population. NEW AND RELAPSE includes cases for which the treatment history is unknown.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

277

western pacific region

0 3 0 0

5 0 2 1

0 0 0 0

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

American Samoa

• 100 Australia

0•

•0 Brunei Darussalam

77 •

•0 Cambodia

66 •

• 91 China

93 •

• 93 China, Hong Kong SAR

95 •

•0 China, Macao SAR

69 •

•0 Cook Islands

86 •

• 100 F ji

0•

• 86 French Polynesia

93 •

• 67 Guam

80 •

•0 Japan

79 •

•0 Kiribati

0•

• 87 Lao People's Democratic Republic

94 •

• 70 Malaysia

92 •

• 69 Marshall Islands

79 •

• 25 Micronesia (Federated States of)

88 •

• 80 Mongolia

96 •

• 74 a

86 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

2 3 0 0 0 251 241 267 274 301 84 101 140 146 109 11 101 14 822 21 001 17 863 17 454 15 812 134 488 204 765 472 719 449 152 429 899 377 005 1 940 1 561 1 444 1 475 1 380 141 160 136 116 123 148 2 0 1 1 0 1 68 62 63 83 89 107 29 21 17 13 22 43 27 31 39 28 14 367 11 853 10 931 8 853 8 237 7 937 54 124 145 118 140 478 1 526 2 801 3 034 3 119 3 271 6 688 8 156 8 446 9 981 11 135 11 862 11 48 52 59 44 9 15 32 61 53 45 455 1 389 1 868 1 809 1 837 1 723

4 2 4 3 0

238 241 606 629 527 84 101 164 176 109 4 363 14 775 21 001 17 863 17 454 15 884 131 413 213 766 472 719 449 039 429 790 377 005 1 940 1 561 1 441 1 487 1 378 160 136 115 219 147 2 1 0 0 1 73 62 68 79 89 107 33 62 18 18 13 20 43 27 47 51 28 10 348 10 931 8 772 8 242 31 54 123 144 117 140 343 1 588 2 802 3 034 3 119 3 271 13 398 7 915 8 446 9 981 11 135 11 862 163 11 47 58 71 50 10 14 20 60 59 51 455 1 389 1 868 1 809 1 837 1 723

– 100 133 – – – – 95 100 227 230 175 – 100 100 117 121 100 39 100 100 100 100 100 98 104 100 100 100 100 – 100 100 100 101 100 – 100 100 99 178 99 100 – 100 0 – 100 107 100 108 95 100 100 – 214 86 106 100 91 – 100 100 152 131 100 – 87 100 99 100 – – 100 99 99 99 100 72 104 100 100 100 100 200 97 100 100 100 100 – 100 98 112 120 114 111 93 62 98 111 113 100 100 100 100 100 100

100 0 75 0

0 100 100

0 0 0

0 0 0

0 0 0

0 0 25 0

27 12 6 8 7 42 66 63 61 66 83 88 89 92 91 90 72 93 92 93 94 94 55 60 59 57 59 81 93 86 93 86 100 100

45 68 73 72 70 21 5 8 20 0 8 4 4 3 3 4 22 2 2 2 2 5 3 11 11 10 8 0 2 0 0 0 0

9 10 3 3 6 17 7 9 7 9 2 4 3 2 2 2 2 1 2 1 1 1 5 5 15 15 14 6 4 3 3 5 0 0

0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 2 1 1 1 1 6 9 0 0 0 0 0 0 0 0 0 0

3 2 1 2 1 4 2 0 0 0 4 4 2 1 1 1 1 1 1 1 0 1 4 3 3 4 4 4 1 2 1 1 0 0

16 8 16 15 16 17 20 20 12 25 2 1 2 1 2 3 3 3 3 2 2 2 24 20 12 13 13 1 3 7 3 7 0 0

0 78 81 71 89 65 81 67 0

92 80 93 85 96 84 79 30 38 21 20 45 83 62 84 88 74 62 68 85 91 89 87 69 0 69 78 79 78 3 64 85 71 63 86 80 93 75 65 97 80 66 83 82 84 83 82

0 8 5 0 5 2 12 0 97 89 89 0 0 0 0 0 0 0 15 22 31 32 42 7 31 13 5 21 8 9 5 2 3 5 0 78 1 1 1 1 21 27 2 14 17 2 0 0 5 23 0 16 7 4 6 4 3 3

0 7 5 10 4 6 1 3 2 11 6 8 5 7 11 2 16 14 5 11 19 21 13 7 7 3 5 4 6 7 5 4 6 0 6 8 9 9 9 9 7 0 2 9 8 6 10 7 10 3 3 4 8 3 3 2 2 2

0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 4 3 1 1

0 3 8 10 1 24 3 21 0 0 6 0 15 0 0 0 0 0 1 1 4 3

100 4 2 9 1 3 3 9 0 0 0 0 0 0 4 2 0 7 44 26 24 24 0 0 0 0 0 0 4 7 1 1 0 1 14 4 16 9 7 8 1 0 9 3 10 6 0 0 5 7 0 0 2 3 2 0 0 1

2 0 0 2 1 2 0 1 1 0 5 2 0 0 0 0 0 0 0 0 0 0 0 0 5 2 0 0 6 3 5 7 8 7

0 1 0 0 1 19 9 3 2 2 2 8 10 5 4 4 4 67 9 2 3 1 10 0 0 0 0 0 10 4 3 2 3 4

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

278

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

        % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Nauru

•0 New Caledonia

0•

• 75 New Zealand

35 •

•0 Niue

56 •

•0 Northern Mariana Islands

0•

•0 Palau

89 •

• 67 Papua New Guinea

57 •

• 56 Philippines

69 •

• 60 Republic of Korea

90 •

• 76 Samoa

80 •

• 80 Singapore

83 •

• 86 Solomon Islands

83 •

• 65 Tokelau

90 •

•0 Tonga

0•

• 75 Tuvalu

100 •

•0 Vanuatu

75 •

• 85 Viet Nam

82 •

• 89 Wallis and Futuna Islands

93 •

•0 a

0•

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

27 15 16 17 19 9 3 8 16 7 4 904 422 1 292 2 584 2 530 2 322 90 297 50 196 81 125 88 806 89 198 93 580 11 675 3 231 3 752 3 813 2 828 2 288 15 13 11 10 6 6 122 242 548 937 948 979 368 109 169 138 133 156

81 73 0 0 56 100 62 75 29 39 57 58 48 53 54 73 82 82 85 83 74 81 81 81 85 78 13 85 91 90 100 83 71

0 0 81 82 89 11 0 12 12 29 56 24 14 13 10 16 6 15 7 7 7 7 2 2 2 2 4 2 67 8 0 0 0 0 15 71 83 17 17 14 65 7 30 22 30 36

0 0 0 0 11 0 0 25 12 14 4 2 4 4 3 4 1 2 2 2 2 2 2 2 1 1 1 1 20 8 9 10 0 17 2 14 14 15 17 15 6 5 8 4 1 3

0 0 0 0 0 0 0 0 0 0 0 0 1 2 2 3 1 1 1 1 1 1 3 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 3

0 0 0 0 0 11 0 0 0 14 15 26 19 16 14 19 5 6 4 4 4 4 5 3 4 3 3 3 0 0 0 0 0 0 11 14 2 1 1 1 4 4 4 3 5 1

19 27 19 18 0 22 0 0 0 14 25 9 5 6 23 5 34 3 3 4 2 3 14 12 11 12 6 16 0 0 0 0 0 0 0 0 1 2 3 1 26 11 2 3 4 4

3 6 9 4 1 652 1 933 1 805 2 238 2 584 1 882 94 768 67 056 81 647 88 806 89 198 93 580 11 754 8 216 11 638 11 285 11 596 11 714 15 13 11 8 6 6 455 248 552 552 530 592 109 109 169 138 133 159 1 0 0 0 0 0 9 15 11 6 6 6 6 0 5 8 5 4 30 63 35 47 44 49 37 550 53 169 55 492 51 291 52 145 50 751 3 1 2

65 62 69 73 56 67 57 54

0

20 15 11 6 6 6 7 6 8 5 4 13 26 42 47 44 49 38 189 53 169 55 492 51 387 52 147 50 751

75 93 73 83 83 100

0 0 0 0 0 0 86 0 0

10 0 18 17 17 0

5 7 0 0 0 0

0 0 0 0 0 0 14 0 0

10 0 9 0 0 0 0 0 12 0 0 0 0 0 0 2 2 2 2 2 2 2 2

100 88 100 75 38 77 64 81 66 53 84 90 90 90 91 91

0 0 25 15 8 10 4 16 10 3 3 3 3 3 3

0 0

46 12 17 15 14 29 5 2 2 2 2 2

0 0 7 0 0 4 2 1 1 1 1 1

0 4 2 0 2 2 4 2 1 2 2 2

2 2

0

100

0

0

0

0

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

279

western pacific region

4 0 1 1 3 21 20 16 15 20 13 78 74 83 90 86 88 0 0 0 0 0 0 14 27 15 16 17 15 9

4 3 0 3 32 45 16 15 21 23 73 84 92 86 141

0 0

– 100 – 0 300 – 152 225 100 100 105 177 – 99 101 102 100 160 – – – – – – – 100 100 100 100 127 100 – 100 133 178 175 297 22 72 115 98 123 95 75 99 100 100 100 99 39 32 34 24 20 100 100 100 125 100 100 27 98 99 170 179 165 338 100 100 100 100 98 – – – – – – 222 100 100 100 100 100 – – 120 100 100 100 43 41 120 100 100 100 102 100 100 100 100 100 – – – – – –

25 0 0 75 33 88 0 0 0 5 0

67 67

33 0 12 9 6 0 19 9 23 6 7 17 7

0 0

0 0 3 2 0 7 5 0

75 0 33 9 0 0 0 0 57 47 33 16 8 36

56 6 93 76 35 25 60 76 74 56

0 0 0 0

0

1 1 1

0

0

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

American Samoa

•0 Australia

0•

•0 Brunei Darussalam

66 •

•0 Cambodia

63 •

• 85 China

74 •

• 92 China, Hong Kong SAR

90 •

•0 China, Macao SAR

62 •

•0 Cook Islands

96 •

•0 Fiji

0•

•0 French Polynesia

57 •

• 50 Guam

100 •

•0 Japan

100 •

•0 Kiribati

0•

•0 Lao People's Democratic Republic

74 •

• 100 Malaysia

81 •

•0 Marshall Islands

54 •

•0 Micronesia (Federated States of)

100 •

• 100 Mongolia

100 •

• 61 a

74 •

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

0 1 0 0 0 17 43 61 65 49 15 5 0 5 8 605 814 1 306 1 429 1 634 1 482 18 693 73 144 140 487 59 583 54 216 46 825 782 719 509 513 487 49 12 31 45 60 23 0 0 0 0 0 0 2 0 2 12 7 1 3 5 4 2 1 2 1 2 3 736 1 367 1 992 1 751 1 762 1 687 3 10 4 14 18 2 64 180 184 185 197 210 0 983 1 181 1 319 1 415 0 5 2 10 20 2 3 21 9 13 4 82 126 341 569 588 548

1 0 0

11 43 65 58 67

5 0 5 8 436 827 1 306 1 429 1 524 409 54 052 43 252 89 239 59 853 54 469 46 825 218 716 481 512 453 37 37 46 35 28

0 0 0 0

0 5 12 7 2 4 5 4 4

2 1 2 3 1 169 1 992 1 452 1 466

9 3 6 20 19 1 64 181 184 184 170

1 056 1 181 1 319 1 415

20 8 4 20 9 20 9 16 10 1 23 126 443 380 234 548

– – 100 – – – – 65 100 107 89 137 – – 100 – 100 100 72 102 100 100 93 28 289 59 64 100 100 100 – 28 100 94 100 93 – 308 119 102 58 122 – – – – – – – – – 250 100 100 – – 133 100 100 200 – – 100 100 100 100 – 86 100 83 83 – – 300 30 150 143 106 50 100 101 100 99 86 – – 107 100 100 100 – – 400 400 40 100 450 667 43 178 77 25 28 100 130 67 40 100

100

0

9 16 6 5 1

73 56 60 64 64

9 5 3 5 6

0 2 0 0

0 5 8 3 3

9 19 22 22 25

40 100 62 59 85 49 34 30 66 90 86 85 86 86 87 27 40 26 34 27 68 51 43 51 79

40 0 0 26 5 27 45 44 8 2 2 5 4 4 4 26 18 38 34 35 16 24 35 14 18

20 0 25 5 6 9 3 4 7 2 1 3 2 2 2 4 4 15 12 15 11 11 11 14 4

0 0 0 3 1 2 1 1 5 3 1 3 2 2 3 17 9 0 0 0 0 0 0 0 0

0 0 0 3 4 3 1 1 5 1 1 1 1 1 1 18 7 6 4 7 5 0 7 11 0

0 0 12 4 0 11 15 20 10 1 8 4 4 5 4 8 22 14 16 16 0 14 4 9 0

40 50 29 50

40 17 29 0 75 100 75 25

20 17 14 50 25 0 25 0

0 0 14 0

0 17 14 0

0 0 0 0 0 0 0 0

0 0 75

0 0 0

0 0 0

50 100 100 67 31 29 15 14

0 0 0 33 15 16 32 32

0 0 0 0 5 8 15 17

0 0 0 0 6 2 1 1

50 0 0 0 1 2 6 5

0 0 0 0 41 43 31 31

89 100 83 25 21 100 41 75 85 76 72

0 17 45 53 0 8 12 3 7 9

11 0 30 5 0 11 6 8 12 2

0 0 0 0 0 8 2 2 3 8

0 0 0 21 0 11 5 1 3 3

0 0 0 0 0 0 22 1 0 0 6

46 33 35 34

9 27 24 20

8 9 12 9

1 1 1 1

9 6 12 8

27 23 17 28

60 12 25 30 100 25 11 0 20 0 61 57 39 60 19 39

10 75 25 70 0 60 89 19 10 100 0 14 34 13 61 35

0 50 0 0 5 75 10 0 9 8 9 4 9 5

0 0 0 0 10 0 0 0 13 8 11 17 6 15

12 0 0 0 0 0 20 0 13 7 4 4 2 4

30 0 0 0 0 0 0 6 40 0 4 6 3 2 4 2

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

280

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

       % OF COHORT TREATMENT SUCCESS (%)a 1995–2011 YEAR NUMBER NOTIFIED SIZE OF COHORT COHORT AS % NOTIFIED CURED COMPLETED DIED FAILED DEFAULTED NOT EVALUATED

Nauru

•0 New Caledonia

0•

• 100 New Zealand

0•

•0 Niue

50 •

•0 Northern Mariana Islands

0•

•0 Palau

0•

•0 Papua New Guinea

0•

•0 Philippines

52 •

•0 Republic of Korea

65 •

• 40 Samoa

74 •

•0 Singapore

0•

•0 Solomon Islands

76 •

•0 Tokelau

100 •

•0 Tonga

0•

• 100 Tuvalu

0•

•0 Vanuatu

0•

•0 Viet Nam

100 •

• 81 Wallis and Futuna Islands

82 •

•0 a

0•

1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011 1995 2000 2005 2009 2010 2011

0 0 0 0 4 4 7 9 8 2 4 7 19 9 11 6 0 0 1 0 4 7 9 8 1 23 18 9 11 6

0 0 0 0 0 0 0 0 0 0 0 0 0 1 273 955 1 456 1 388 1 824 1 575 8 3 957 9 575 11 141 13 745 2 082 2 262 7 098 6 880 6 876 7 270 0 0 0 0 0 0 120 55 153 132 130 162 13 0 5 2 5 11 0 0 0 0 0 0 0 1 0 0 0 1 3 0 0 1 1 5 8 3 1 3 3 616 5 493 7 301 8 131 8 408 8 639 1 0

0 0 0 0

0 0 0 0 68 65 530 444 398

4 362 4 554 4 583 2 004 131 3 331 2 420 1 813 1 346

0 0 0 0

149 130 127 160

5 2 5 10

0

9 1 0 0 0 0

0 0 0 0 5 0 3 1 3 2 384 8 806 7 374 357 398 8 641

0 0 0

– – – – – – 100 – 100 100 100 50 – 329 95 100 100 100 – – – – – – – – – – – – – – – – – 0 – 7 4 38 24 25 – – – 46 41 33 96 6 47 35 26 19 – – – – – – – – 97 98 98 99 – – 100 100 100 91 – – – – – – – 100 – – – – – – 0 – – 0 – 100 0 100 100 100 66 160 101 4 5 100 – – – – – –

100

0

100 86 0 0 0 0 0 0 89 88 0 30 67 67 73 50 14 0 12 100 4 0 11 18 0 0 0 0 0 0 0 0 0

0 0 11 0 0 65 33 22 9 50

0

0

0

0

0

29 42 36 35 32

35 14 22 11 20

4 15 5 5 7

1 6 5 5 5

21 20 29 18 22

9 3 3 27 14

48 53 47 39 59 72 69 76 70

13 15 18 1 2 3 3 4 3

4 5 5 1 3 2 2 2 1

4 5 4 2 3 0 1 0 0

5 6 6 3 12 6 5 6 5

26 16 20 53 21 18 21 12 19

37 47 43

79 39 31 33

15 20 17 22

0 0 0 0

5 1 2 2

1 3 3 0

20 50 80 30

40 50 0 70

20 0 20 0

20 0 0 0

0 0 0 0

0 0 0 0

100 100

0

0

0

0

0 0

100 100 100 67 80 74 79 67 61 79

0 0 0 33 2 5 4 6 8 3

0 0 0 0 5 6 5 8 8 5

0 0 0 0 8 5 6 2 4 5

0 0 0 0 2 3 3 10 12 3

0 0 0 0 4 7 3 7 6 5

TREATMENT SUCCESS = percent cured + percent completed then rounded to the nearest digit.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

281

western pacific region

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS 0 75 100 42 54 59 56 100 100 100 100 2.9 77 82 80 16 23 34 68 75 74 75 91 92 94 89 0 100 100 100 82 73 58 48 27 27 44 72 62 65 68 52 49 16 13 54 77 43 38 46 48 73 91 89 97 77 68 91 60 6.2 49 97 100 <0.1 89 80 78 0 0 0 40 0 0 41 60 57 58 0 3 3 448 686 750 740 163 237 230 243 1 044 32 236 32 544 32 359 145 919 208 681 309 385 4 209 3 833 3 656 3 707 378 399 360 360 0 0 1 1 132 157 160 127 30 11 17 22 46 63 53 46 12 098 11 221 3 328 44 159 274 150 1 533 2 012 1 999 11 661 17 577 18 472 22 124 86 137 137 88 7 85 145 146 1 4 256 3 612 3 465 0 0 0 21 0 0 140 183 175 171 0 0 1 56 32 31 27 9 18 10 4 2 122 4 671 3 713 1 634 3 917 2 040 PATIENTS NOTIFIED (NEW AND RETREAT) 6 4 3 1 073 1 281 1 268 1 325 163 237 230 243 36 123 41 628 39 670 40 258 990 509 923 308 911 884 900 678 6 160 5 132 4 926 4 969 415 433 382 406 1 0 1 1 132 191 220 218 63 41 64 50 64 101 82 68 28 319 23 261 22 681 21 283 339 294 354 348 3 807 4 083 4 387 4 156 16 066 19 337 20 666 22 710 112 201 151 147 112 174 150 146 4 726 4 801 4 533 4 453 11 3 5 53 57 52 38 340 305 309 297 0 0 1 0 57 32 33 34 10 19 12 4 12 564 16 113 16 324 22 488 137 100 174 389 206 088 230 162 % OF HIVNUMBER OF % OF HIVPOSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 American Samoa 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS

% OF TESTED TB PATIENTS HIV-POSITIVE

0 0 22 24 19 8 2 1 3 2 86 2 112 1 656 1 433 4 542 4 715 5 866 35 24 28 22 1 3 2 4 0 0 0 0 1 3 3 5 0 0 1 0 0 1 0 0 53 75 62 2 0 0 0 182 222 234 1 468 1 628 1 629 1 347 0 0 1 0 0 0 0 0 1 2 3 4 0 0 0 0 0

0 0 4.9 3.5 2.5 1.1 1.2 0.42 1.3 0.82 8.2 6.6 5.1 4.4 3.1 2.3 1.9 0.83 0.63 0.77 0.59 0.26 0.75 0.56 1.1 9.1 0

•0 Australia

–

• 42 Brunei Darussalam • 100 Cambodia

56 •

100 •

0 100 100 100 65 88 98

0 100 100 100 45 79 88 45 36 59 54 29

2 0 0 491 1 305 1 145

•3 China

80 •

– China, Hong Kong SAR • 68 China, Macao SAR • 91 Cook Islands

34 •

49 17

75 •

89 •

0 33 50 0

100 33 50 25

•0 Fiji

100 •

• 100 French Polynesia

58 •

• 48 Guam

44 •

• 72 Japan

68 •

0 0 0.76 1.9 1.9 3.9 0 0 5.9 0 0 1.6 0 0 0.44 0.67 1.9 4.5 0 0 0 12 11 12 13 9.3 8.8 6.1 0 0 0.73 0 0 0 0 0 100 <0.1 <0.1 0.12

0 100 100 100

0 100 100 60

0 1

100

100

100

100

– Kiribati

16 •

0

0 2

• 13 Lao People's Democratic Republic – Malaysia

43 •

48 •

100 76 78 22 48 22 48 32

303

• 73 Marshall Islands

97 •

1 120

0

100

• 77 Micronesia (Federated States of) •6 Mongolia

60 •

100 •

0 100 100 100 75 100 100 100 75 0 0 0

•0 Nauru

78 •

•0 New Caledonia

–

0

• 40 New Zealand

–

• 41 Niue

58 •

100 98 100 94 79 90 95 83 100 13 29 17 0.94 1.9 0.89

8 3 3 3 0 0 0 0 0 0 1 0 0 1 0 222 531 364 2 9 4

5.7 1.6 1.7 1.8

0 0 0 0 3.7 0 0 10 0 10 11 9.8 0.12 0.23 0.2 0

– Northern Mariana Islands • 98 Palau

–

79 •

0

0

0

0

• 90 Papua New Guinea – Philippines

100 •

17 •

89 0

135 256 325 16 226

–

1•

282

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           – NUMBER OF TB % OF TB PATIENTS WITH PATIENTS WITH KNOWN HIV KNOWN HIV STATUS STATUS PATIENTS NOTIFIED (NEW AND RETREAT) 46 969 48 101 50 491 49 532 24 14 20 22 1 469 1 608 1 695 2 364 397 341 405 372 0 0 0 18 11 9 11 15 14 13 20 81 116 112 126 95 892 99 022 100 518 103 906 7 2 % OF HIVNUMBER OF % OF HIVPOSITIVE TB POSITIVE TB HIV-POSITIVE PATIENTS ON PATIENTS ON PEOPLE CPT ART PROVIDED IPT

% OF TB PATIENTS WITH KNOWN HIV STATUS YEAR 2005–2012 Republic of Korea 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

NUMBER OF HIV-POSITIVE TB PATIENTS

% OF TESTED TB PATIENTS HIV-POSITIVE

135 129 0 0 0 0 50 61 47 0 0 0 0 0 0 0

– Samoa

–

•0 Singapore

0•

0 21 0 0 74 79 84 0 11 17 12

0 3 0 0 1 184 1 332 1 978 0 39 70 45 0 0 0

0

0

– Solomon Islands

84 •

4.2 4.6 2.4 0 0 0 0

•0 Tokelau

12 •

– Tonga

–

Tuvalu

•0 Vanuatu

45 •

0 0 0 0 0 4.2 8.3 7.9 7 0 0

•0 Viet Nam

52 •

• 15 Wallis and Futuna

66 •

62 72 73

43 48 47

1 317 5 663

400

10 8

–

–

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

283

western pacific region

–

100 •

73 100 100 0 0 31 45 0 7.8 45 52 15 43 59 66

8 9 11 0 0 4 9 0 9 50 65 14 128 42 356 59 176 68 259

0 0 0 0 0 0 0 0 0 0 0 595 3 515 4 703 4 775 0 0 0

0 0 0

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB 0 1 – 12 33 28 18 0 0 0 31 56 75 2792 1601 3007 41 28 23 26 9 6 5 8 0 0 1 0 0 0 0 0 0 0 1 2 0 0 68 60 64 1 0 0 0 2 4 10 1 64 141 74 2 1 1 3 1 1 1 3 0 187 185 210 – 868 652 861 181 205 166 5 18 16 b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB – – – – – 160 99 130 – 100 130 100 – <0.1 <0.1 0.11 – – 2.6 3.6 96 61 79 76 190 89 110 110 – – 0 – – 4.5 17 9.1 – 87 110 91 110 110 110 100 – 54 51 66 0.81 0 – 0 – – – 0.46 180 – – – 110 96 100 140 110 70 98 8.6 0 2.2 9.1 11 – – 0 – – 62 140 120 150 180 160 150 – – – – 100 100 100 100 100 58 100 100 – – – – <0.1 <0.1 <0.1 <0.1 b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

American Samoa

Australia

Brunei Darussalam

Cambodia

China

China, Hong Kong SAR

China, Macao SAR

Cook Islands

Fiji

French Polynesia

Guam

Japan

Kiribati

Lao People's Democratic Republic Malaysia

Marshall Islands

Micronesia (Federated States of) Mongolia

Nauru

New Caledonia

New Zealand

Niue

Northern Mariana Islands

Palau

Papua New Guinea

Philippines

2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

0 0

–

17 (9.2–25)

14 (8.1–23)

3.0 (0.36–9.9)

0 (0–0)

0 (0–4.4)

0 (0–3.2)

380 (190–580)

330 (160–590)

56 (21–110)

59 000 (52 000–66 000)

49 000 (38 000–60 000)

48 (30–66)

36 (22–55)

8.3 (3.0–14)

2.3 (0.27–8.1)

9940 11472 3271 1897 1992 2061 265 221 258 261 0 0 0 4 18 15 27 47 30 39 56 43 31 7684 7400 8564 1 0 0

11 000 (9 000–12 000)

12 (4.6–27)

6.0 (2.3–11)

1.0 (<0.1–1.0)

0 (0–0)

1.0 (<0.1–1.0)

0 (0–0)

0 (0–14)

0 (0–13)

0 (0–0)

0 (0–4.2)

0 (0–3.6)

0 (0–6.7)

0 (0–6.7)

0 (0–0)

240 (180–300)

110 (65–170)

130 (96–180)

15 (12–18)

13 (9.5–16)

2.3 (1.9–2.7)

220 (180–260)

170 (130–220)

14 15010

48 (40–56)

18 (0–54)

18 (0.46–100) 52 68 50 73 35 50 44 5 0 40 157 196

0 (0–250)

4.4 (0–9.3)

4.4 (0.92–12)

0 (0–5.9)

6.8 (5.4–8.2)

5.9 (4.3–7.3)

0.93 (0.78–1.1)

170 (140–190)

33 (15–58)

130 (120–150)

0 – 0 0 0 4 4 2 4 0 0 0 2 0 0 0 0 0 1 0 –

0

–

0 (0–0)

0 (0–3.1)

3.7 (0–9.2)

0.75 (<0.1–4.1)

20 24 28 247 243 229 221

0 (0–0.98)

3.0 (<0.1–11)

0 (0–0)

0 (0–0) 24 17 19 15 3 11 8 3

0 (0–0)

0 (0–0)

0 (0–6.1)

0 (0–2.0)

0 (0–2.8)

0 (0–2.8)

0 (0–0)

15 58 274 522 1148 679

1 100 (930–1 300)

590 (430–740) 4 3 25 35

500 (420–590)

12 000 (9 300–15 000)

8 500 (6 000–11 000)

3 700 (2 500–5 100)

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB – 0 – 0 – – – 48 74 26 53 31 67 – 5 100 8 100 14 100 – 93 5.7 190 13 86 17 – – – 4861 12 163 23 211 41 207 43 232 48 19 61 39 65 24 100 28 100 – 0 – 0 – 1 100 – 4 33 0 0 1 7.7 3 100 4 100 1 50 4 67 0 0 2 100 2 67 0 – – 694 39 670 40 583 44 – 0 0 – 0 0 – – – 48 23 1056 110 – – – 3 60 3 30 4 20 0 0 21 100 3 23 0 0 0 0 16 4.7 561 95 602 110 681 130 – – – – – 0 0 0 0 0 0 14 74 10 91 5 83 12 80 – – – – 1 – 0 – 0 – 0 0 0 – 0 – 0 0 0 – – – – – 138 3.5 297 2.7 2325 17 2038 12

a

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). b BACT+VE = bacteriologically positive cases.

284

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

             NEW PULMONARY CASES ESTIMATED CASES OF MDR-TB AMONG NOTIFIED ESTIMATED CASES OF MDR-TB AMONG NOTIFIED NUMBER OF BACT+VE TESTED FOR MDR-TB b

YEAR

TOTAL CONFIRMED CASES OF MDR-TB a

PREVIOUSLY TREATED CASES % OF BACT+VE TESTED FOR MDR-TB – – 17 – – 0 – 79 96 97 97 98 – 0.75 0 5.7 – – – – – 0 0 0 – 0 – 11 – – 0 0 – – – – – – 0 – b

ESTIMATED CASES OF MDR-TB AMONG NOTIFIED

Republic of Korea

Samoa

Singapore

Solomon Islands

Tokelau

Tonga

0.49 (0.36–0.61)

0.49 (0.36–0.61)

0 (0–0)

Tuvalu

0 0 2 0 0 0 101 601 273

0 0.72 (0.60–0.85) 0.49 (0.36–0.61) 1

0.23 (0.19–0.27)

Vanuatu

0.47 (0.39–0.54)

0 (0–8.7)

0 0

0.47 (0.39–0.54)

Viet Nam

3 800 (3 000–4 600)

2 100 (1 500–2 800)

1 700 (1 300–2 300)

Wallis and Futuna Islands

0 – –

0

–

a

TOTAL CONFIRMED CASES OF MDR-TB includes cases with unknown previous treatment history (i.e. not included under NEW CASES or PREVIOUSLY TREATED CASES). b BACT+VE = bacteriologically positive cases.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

285

western pacific region

2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012 2005 2010 2011 2012

450 516 1212 0 0 0 3 3 6 22 0 0 0 0

3431 2 200 (1 800–2 700) 840 (660–1 100) 0 0 (0–4.1) 0 (0–4.1) 15 895 923 952 1178 1 0 9 0 – – 0 0 0

1 400 (1 000–1 900)

0 (0–0)

36 (21–51)

31 (18–48)

5.2 (1.1–15)

12 (9.1–15)

12 (8.8–15)

0 (0–3.3)

–

0 0 0

NUMBER OF % OF NOTIFIED NOTIFIED TESTED FOR TESTED FOR MDR-TB MDR-TB – – 968 13 – – 0 – – – 105 69 79 61 104 64 93 58 – 1 20 0 0 16 100 – 0 – – – – 0 – 0 – 0 – – 0 – – – – – 0 0 0 0 – – – – – – 0 – –

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO – 2.0 – – – – – 2.1 1.6 1.4 1.4 1.3 – 1.6 2.1 1.5 1.6 1.9 0.99 0.99 1.0 1.2 1.2 1.2 1.8 2.0 2.3 2.5 2.6 2.5 – 2.4 2.3 2.1 2.1 2.2 1.6 2.2 2.9 2.0 1.7 2.1 1.0 – – – – – 1.1 1.6 2.0 1.1 1.2 1.2 – 3.1 1.2 1.2 1.8 1.2 – 2.6 2.0 1.8 1.8 3.6 2.3 2.4 2.1 2.0 1.9 1.9 – 1.2 1.2 1.5 0.65 1.7 1.4 1.6 1.5 1.5 1.6 1.6 2.2 2.3 2.1 2.0 2.1 2.0 – 1.1 0.92 0.97 0.83 1.2 2.5 0.36 – 0.71 1.4 1.2 1.4 1.2 1.1 1.2 1.5 1.4

American Samoa

Australia

Brunei Darussalam

Cambodia

China

China, Hong Kong SAR

China, Macao SAR

Cook Islands

Fiji

French Polynesia

Guam

Japan

Kiribati

Lao People's Democratic Republic

Malaysia

Marshall Islands

Micronesia (Federated States of)

Mongolia

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

1 0 0 0 0 0

1 0 0 0 0 0 1 0 0

1 2 0

0

0

0

3 0 2 2 3 0 0 0 0 0 161 26 49 39 34 31 1 102 1 131 1 416 759 645 511 4 3 2 2 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 7 1 0 2 1 0 0 0 0 2 0 0 0 0 15 2 9 1 0 2 2 3 3 4 4 6 7 13 8 8 10 59 32 244 129 63 74 3 2 0 1 0 0 0 3 4 3 37 6 7 3 2 7

16 32 42 38 26 6 9 17 11 10 453 519 894 750 791 673 12 791 19 111 43 005 42 851 37 514 29 018 78 76 52 72 63 7 10 6 17 20 10 0 0 1 0 0 0 8 8 9 7 12 14 3 2 3 3 1 1 2 2 1 1 342 246 197 128 96 94 9 15 27 17 19 56 92 136 157 145 144 640 694 1 179 884 948 1 060 5 4 10 7 3 1 2 8 8 8 99 181 271 285 246 257

35 27 33 44 40 4 19 15 11 13 1 244 1 323 1 600 1 564 1 469 1 256 18 306 29 399 49 558 38 880 34 597 28 324 102 84 84 52 67 19 8 9 5 22 12 0 0 0 0 0 0 10 6 18 15 16 12 3 2 1 1 2 6 4 3 0 0 627 572 488 252 215 209 3 15 13 9 12 71 128 223 254 275 236 879 1 138 2 218 1 438 1 564 1 575 4 4 1 2 8 0 0 1 5 5 111 260 253 255 289 268

25 23 22 26 17 15 19 13 11 15 1 147 1 618 2 349 1 760 1 557 1 414 15 487 25 206 55 400 50 246 43 087 34 505 160 108 99 63 95 20 25 21 7 22 13 0 0 0 0 0 0 9 13 18 11 8 9 4 2 0 1 2 6 4 5 2 4 995 676 605 382 367 309 3 12 10 3 16 68 166 296 287 323 326 775 1 177 2 277 1 599 1 559 1 677 1 5 4 3 6 3 1 2 6 4 68 171 232 231 205 191

24 11 25 19 25 5 12 18 10 13 1 253 1 456 2 043 2 105 1 972 1 904 13 105 25 593 54 872 52 925 47 949 40 428 211 200 184 172 174 13 22 23 22 47 22 0 0 0 0 0 0 4 5 14 6 9 12 4 0 1 5 3 9 2 5 7 5 1 847 1 494 868 469 465 415 3 17 9 10 17 78 201 373 416 474 424 788 908 1 980 1 453 1 594 1 762 3 6 6 3 9 1 0 4 2 2 19 68 147 154 170 184

19 12 9 12 16 7 9 7 11 8 1 257 1 373 1 964 1 531 1 439 1 434 13 489 21 429 53 822 56 754 51 315 44 821 236 168 166 189 178 12 9 17 20 39 32 1 0 0 0 0 0 2 4 16 2 9 5 4 4 1 1 3 6 2 7 4 2 2 059 1 509 1 418 911 812 741 8 4 6 9 11 90 177 300 385 416 381 374 814 1 427 967 1 245 1 409 5 1 6 3 2 0 0 4 0 0 13 38 52 50 71 63

49 30 27 37 37 15 0 18 13 19 707 1 058 1 811 1 599 1 339 1 526 10 130 21 771 69 779 64 514 55 881 49 413 578 453 413 384 430 16 17 22 11 24 17 0 0 0 0 0 0 3 2 6 4 4 7 3 2 1 3 3 9 4 3 4 6 4 089 3 816 3 867 3 326 3 256 3 230 2 1 2 3 5 55 176 352 380 375 365 1 072 891 1 507 981 1 054 1 260 3 1 2 1 2 0 1 0 1 1 15 23 36 40 41 37

0 0 0

0 2 4 3 1 0 0 2 2 0 123 38 45 60 39 22 1 169 1 420 1 864 926 733 580 5 3 3 3 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 7 1 1 2 1 0 0 0 0 0 0 1 0 0 14 5 5 6 5 2 2 5 5 6 4 3 10 7 13 14 11 58 41 208 152 77 105 7 1 5 1 0 0 4 5 5 5 30 32 15 12 10 11

15 18 36 26 27 4 9 7 5 5 388 457 790 752 690 612 10 890 14 536 31 180 27 064 22 859 17 786 65 67 49 56 45 9 10 5 7 28 12 0 0 0 0 1 0 10 7 7 11 13 11 4 2 1 3 2 3 3 0 1 0 258 222 187 89 94 79 5 22 15 26 15 49 59 101 133 141 119 446 464 1 044 704 837 903 7 9 9 5 5 0 3 8 5 6 70 200 320 296 250 250

19 26 43 40 48 6 11 15 9 6 1 133 1 157 1 413 1 321 1 211 1 088 13 250 18 496 27 759 21 022 18 347 15 549 115 81 101 89 110 18 4 9 6 25 11 0 0 0 0 0 0 9 5 9 12 17 10 1 3 1 3 3 1 1 4 1 0 476 464 428 232 213 180 6 12 7 12 11 49 95 186 152 204 197 448 564 1 061 881 876 1 010 3 2 2 8 7 1 1 9 2 2 78 213 270 246 192 208

12 11 12 23 15 9 8 12 6 9 1 435 1 649 2 089 1 303 1 092 957 8 376 12 377 24 728 20 422 17 119 13 485 86 92 76 69 76 12 6 7 10 17 13 0 0 0 0 0 0 2 7 6 5 7 7 0 0 0 0 0 2 1 3 1 0 298 213 249 194 203 169 3 7 4 9 10 69 131 205 215 208 192 345 424 947 592 584 710 0 4 2 2 2 0 1 3 3 3 33 113 145 112 121 97

15 10 2 7 11 6 3 8 7 10 1 426 1 798 2 323 1 732 1 528 1 424 5 679 9 899 19 889 16 075 14 103 11 981 44 57 64 60 51 4 6 8 5 18 3 1 0 0 0 0 0 3 1 4 1 5 6 1 1 3 1 3 5 2 3 0 2 476 292 224 155 148 111 4 7 8 16 7 54 122 244 269 267 246 316 367 816 542 599 693 2 3 4 5 5 0 0 4 1 1 15 41 63 83 61 82

5 6 5 7 9 3 2 4 3 6 1 180 1 459 2 058 1 607 1 473 1 302 4 579 7 102 18 203 17 441 15 218 13 384 45 34 49 53 54 5 3 1 7 6 7 0 0 0 0 0 0 4 4 6 8 2 7 0 1 0 0 4 2 0 0 3 1 637 384 309 183 223 175 1 3 5 12 2 52 91 192 225 215 210 149 356 586 425 459 590 2 4 8 2 3 0 1 2 2 3 9 26 32 42 40 28

14 14 12 17 15 4 0 10 10 5 578 892 1 573 1 331 1 242 1 198 2 841 6 296 21 244 20 020 17 638 16 547 211 135 133 116 115 6 13 5 6 6 3 0 0 0 0 0 0 3 0 5 5 3 7 0 3 1 1 0 2 2 3 4 2 2 234 1 958 2 077 1 909 1 840 1 947 3 1 4 4 1 26 71 178 225 206 201 339 286 572 388 403 483 0 2 0 1 2 1 1 0 1 0 25 17 25 28 25 33

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0

0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

286

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

           MALE YEAR 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

FEMALE 0–14 15–24 25–34 35–44 45–54 55–64 65+ UN KNOWN

MALE:FEMALE RATIO – 0.50 – – 2.0 – 1.7 0.90 0.60 2.3 2.2 2.7 1.6 1.3 1.3 1.1 1.2 1.6 – – – – – – 1.9 0.92 2.8 0.89 1.5 1.2 8.0 – – 2.3 3.0 – – 1.4 1.0 1.0 1.0 1.0 2.2 – 2.3 2.4 2.4 2.3 2.1 1.9 1.6 1.4 1.4 1.5 1.1 2.2 1.2 1.0 0.20 2.0 2.8 3.5 2.7 2.6 2.9 2.7 0.73 0.91 0.97 1.0 0.85 0.99 – – – – – – 0.80 2.0 1.2 5.0 0.50 0.80 1.0 – 0.67 4.0 3.0 0.60 2.0 0.86 1.3 0.91 1.1 0.50 – 2.2 2.7 2.9 3.0 3.0 – – – – – –

Nauru

New Caledonia

New Zealand

Niue

Northern Mariana Islands

Palau

Papua New Guinea

Philippines

Republic of Korea

Samoa

Singapore

Solomon Islands

Tokelau

Tonga

Tuvalu

Vanuatu

Viet Nam

Wallis and Futuna Islands

1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012 1995 2000 2005 2010 2011 2012

1 0 0 3 1 0 0 0 0 0 4 0 1 0 0 0 2 1 2 1 0 4 6 6 6 12 7 0 0 3 3 1 2 0 2 3 5 10 13 5 9 0 1 4 4 0 3 3 3 6 6 4 5 2 0 1 2 2 0 1 1 3 5 8 6 6 7 4 0 0 2 3 3 4 2 2 7 10 5 5 7 6 0 0 3 4 0 3 3 1 7 7 10 11 11 14 0 0 0 0 2 1 0 0 0 1 1 1 2 4 3 0 0 1 8 1 1 0 2 6 11 12 8 4 0 0 1 1 2 0 1 3 6 9 7 8 8 1 0 3 1 1 1 1 4 5 6 6 4 2

1 0 0 3 3 2 0 0 1 2 0 6 5 5 3

1 0 0 0 2 0 1 1 1 2 4 1 3 3 1 0 1 1 4 4 3 1 1 4 10 2 6 8 5 0 0

0 0

0 0

0 0 0

0 0 0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0 0 0

0 0 0

0 0 0 8 28 37 50 54 2 482 511 573 583 27 19 22 22 13 11 0 0 0 0 0 0 1 0 0 0 1 2 3 4 4 3 3

1 0 0 87 183 279 278 415 43 7 358 9 320 9 725 9 754 1 131 821 687 537 491 500 1 3 4 1 1 4 9 8 8 11 21 31 14 13 14 16 15 20

2 2 0 0 70 205 260 265 387 56 11 275 12 224 12 804 12 576 1 613 1 085 1 171 705 712 699 1 1 0 1 0 3 40 9 25 21 21 36 6 4 18 18 22 19

1 1 0 30 108 196 152 250 61 13 253 13 716 14 474 14 140 1 425 988 1 326 1 049 1 019 956 1 1 1 0 1 60 34 61 38 44 54 5 8 9 16 12 10

1 0 0 21 94 135 122 182 46 12 531 13 651 14 002 13 996 1 207 853 1 336 1 496 1 414 1 562 0 1 1 0 1 62 51 94 105 108 106 7 8 15 8 7 12

1 2 0 12 48 87 71 121 47 7 646 8 923 9 568 9 676 1 307 731 1 005 1 029 1 145 1 238 3 2 0 1 0 1 70 26 96 86 119 124 9 10 12 3 8 8

1 1 0 0 5 12 27 18 37 26 4 279 4 742 4 845 5 097 1 225 901 1 669 1 997 2 132 2 255 2 1 0 0 0 94 64 118 120 126 143 3 6 11 3 6 6

0 0 0

1 0 0 6 38 64 53 55 1 374 454 448 466 46 25 27 23 37 22 1 0 0 0 1 1 1 0 1 0 0 3 8 9 4 3 5

0 0 0 77 200 313 302 398 20 3 710 4 825 5 155 5 104 908 546 590 472 446 436 2 2 2 2 1 8 9 5 15 11 26 17 15 23 19 13 20

1 1 0 45 204 292 272 395 32 5 268 5 489 5 848 5 954 863 544 842 686 688 664 2 1 0 1 0 18 8 20 21 25 46 11 13 21 17 27 18

1 0 1 21 124 191 146 208 26 5 565 5 301 5 521 5 584 431 393 491 509 520 444 0 1 2 2 0 1 21 7 33 26 23 27 7 7 12 11 15 11

0 0 1 15 65 97 97 156 20 4 603 4 643 4 880 5 068 296 220 370 487 432 377 0 0 0 1 1 22 9 29 21 23 26 12 7 11 5 10 8

0 0 0 5 35 52 55 95 19 3 274 3 329 3 501 3 605 408 295 373 368 421 397 1 0 1 1 0 0 19 5 20 21 20 19 13 5 9 4 16 12

0 0 1 1 2 9 15 29 11 2 029 2 070 2 236 2 380 867 795 1 729 2 216 2 244 2 569 1 0 0 1 1 31 16 43 44 51 39 0 2 1 5 2 5

0 0 0

0

80

0

0

0 0 5

0 0 2

3 0 0

3 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0 0 0 0 0 1

1 2 2 0 0 0 0

0 1 1 0 1 0 1

0 1 0 1 0 0 0

0 2 0 0 2 0 1 1 1 3 10 0 5 5 2 6 713 8 606 8 564 8 474 8 481

1 1 1 1 0 0 1 1 2 1 4 5 4 2 4 2 5 150 4 958 5 790 6 107 6 315

2 5 0 3 1 2 0

0 0 0 2 0 0

0 0 0

0 1 2 0 0 2 1 1 0 1 5 3 5 5 5 12 1 334 1 747 1 870 1 863 1 841

1 1 1 0 1 0 1

1 1 0 0 1 0 0

0 0 1 0 1 0

2 1 2 0 0 1 1 2 0

1 1 0 0 0 1 0

0 0 0

0 1 0 2 1 4 2 0 51 54 59 61 58

1 1 1 6 7 4 6 3 4 2 367 3 408 3 205 3 099 2 993

0

0 1 5 1 5 1 6 4 8 209 8 738 7 851 7 763 7 680

0

0 2 0 5 0 3 0 3 64 47 53 64 84

1

0

2 5 5 3 4 3 6 147 7 105 7 036 6 677 6 689

0 2 1 0 2 2 7 712 7 573 6 248 5 821 5 920

0 0 0

0 15 1 3 7 5 2 320 2 293 2 454 2 325 2 481

2 7 2 3 5 5 2 754 2 116 1 681 1 681 1 626

0 1 2 3 3 4 5 4 4 2 594 2 298 1 864 1 814 1 683

0

0 3 1 3 2 2 2 847 2 023 1 863 1 878 1 884

0 1 2 1 0 3 4 907 4 604 3 751 3 124 3 298

0 0 0

0 0 0

0 0 0

2

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

287

western pacific region

0 1 1 0 0 0 0 0

0 1 4 0 2 0 0 2

0 3 8 1 0 0 0 3

0 5 9 3 0 0 3 0

0 10 9 4 3 1 1 2

0 3 3 1 3 5 1 1

0 3 2 2 0 3 0 0

0

0 0 0 0 0 0 0 0

0 0 10 0 2 0 0 0

0 2 17 0 0 1 3 0

0 6 7 1 1 0 1 0

0 4 3 1 3 2 0 1

0 1 1 1 2 3 0 0

0 1 1 1 1 0 0 0

0

           LABORATORIES SECONDNUMBER OF SMEAR LABS % OF SMEAR CULTURE DST b LABS LPAc LABS LABS US NG LABS PER 5M LINE DST LABS USING PER 100K PER 5M PER 5M a POPULATION POPULATION POPULATION POPULATION XPERT MTB/RIF AVAILABLE LED

FREE THROUGH NTP FIRSTLINE DRUGS

NRLd

TB DIAGNOSIS

TB NOTIF. RIFAMPICIN RATE PER USED 100 000 THROUGHOUT HEALTH-CARE TREATMENT WORKERS

American Samoa Austra ia Brunei Darussalam Cambodia China China, Hong Kong SAR China, Macao SAR Cook Islands Fiji French Polynesia Guam Japan Kiribati Lao People's Democratic Republic Malaysia Marshall Islands Micronesia (Federated States of) Mongolia Nauru New Caledonia New Zealand Niue Northern Mariana Islands Palau Papua New Guinea Philippines Repub ic of Korea Samoa Singapore Solomon Islands Tokelau Tonga Tuvalu Vanuatu Viet Nam Wallis and Futuna Islands 4.0 0.9 1.5 9.6 1.6 2.7 1.0 2.0 2.4 2.6 5.7 3.9 1.4 0.5 0.2 1.4 0.2 0.4 0.4

– – 0 10 2 3 0 – 0 – – – 0 0 4 33 0 8 – – – – – 0 0 0 – – – 0 – – – 100 0 – 0 1.4 0 0.1 0 0.1 0 22 0 0 0 0 240.9 0 0.7 51.0 240.9 0 0.2 0.7 240.9 0 <0.1 2 1 6 17 2 49.6 2.3 6.2 95.1 0 3.6 0 0.8 0.2 95.1 0 1.8 0 0.8 0.3 95.1 0 1.8 0 0 0 1 0 0 5.7 0 0 3 12.1 1.0 3.7 9.1 9.0 12.1 0.3 0.7 1.4 9 12.1 0 <0.1 1.4 0 0 6 16 9 0

In country Out of country No In country In country In country Out of country No Out of country Out of country In and out of country Out of country

Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes

Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (other criteria) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) No Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (if TB is confirmed) Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) No Yes (a l suspects)

Yes Yes Yes Yes Yes Yes No Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 0 204 0 53 106 93 41 26

No Yes In country Yes Out of No country In and out Yes of country In country Yes Out of Yes country In country Yes Out of No country Out of Yes country Yes In country Yes Yes Out of Yes country In country Yes Out of Yes country Out of Yes country Out of Yes country Out of Yes country In country Yes

Yes (a l suspects) Yes (a l suspects) Yes (a l suspects) Yes (for smearpositive TB)

Yes Yes Yes Yes

Yes Yes Yes No 111

a b

LED = Light emitting diode microscopes DST = Drug susceptibility testing ig g c LPA = Line probe assay T g d NRL = National Reference Laboratory LP Li b

288

GLOBAL TUBERCULOSIS REPORT 2013

Data for all years can be downloaded from www.who.int/tb/data

             New TB cases Year Source Coverage Percentage Year

Previously treated TB cases Source Coverage Percentage

2004 2004 2012 2012

Survey Survey Surveillance Surveillance

National National National National

4 2.7 0 1.6

(2.9–5.5) (2.1–3.4) (0–22) (0.97–2.5)

2004 2004 2012 2012 2012

Survey Survey Surveillance Surveillance Surveillance

National National National National National

21 14 0 3.2 0

(14–29) (10–19) (0–98) (0.67–9.1) (0–21)

2006 2006

Surveillance Survey

National National

0 (0–12) 2.7 (2.0–3.7)

2006

Survey

National

19 (14–25)

a

Empty rows indicate an absence of high-quality survey or surveillance data. In the absence of high-quality national data, high-quality sub-national data are used.

Data for all years can be downloaded from www.who.int/tb/data

GLOBAL TUBERCULOSIS REPORT 2013

289

western pacific region

American Samoa Australia Brunei Darussalam Cambodia China China, Hong Kong SAR China, Macao SAR Cook Islands Fiji French Polynesia Guam Japan Kiribati Lao People's Democratic Republic Malaysia Marshall Islands Micronesia (Federated States of) Mongolia Nauru New Caledonia New Zealand Niue Northern Mariana Islands Palau Papua New Guinea Phi ippines Republic of Korea Samoa Singapore Solomon Islands Tokelau Tonga Tuvalu Vanuatu Viet Nam Wallis and Futuna Islands

2012 2012 2007 2007 2012 2012 2012 2006 2012 2012 2002

Surveillance Surveillance Survey Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance

National National National National National National National National National National National

1.9 0 1.4 5.7 0.97 0.77 0 0 0 0 0.7

(1.1–3.0) (0–2.2) (0.71–2.5) (4.5–7.0) (0.59–1.5) (<0.1–2.7) (0–98) (0–8.2) (0–12) (0–11) (0.42–1.1)

2012 2012 2007 2007 2012 2012 2012 2006 2012 2012 2002

Surveillance Surveillance Survey Survey Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance Surveillance

National National National National National National National National National National National

6.5 0 11 26 2.6 21 100 0 0 12 9.8

(0.79–21) (0–23) (4.0–22) (22–30) (0.95–5.5) (8.3–41) (2.5–100) (0–98) (0–60) (9.2–15) (7.1–13)

1997 2012

Survey Surveillance

Sub-national National

0.1 (0–0.56) 4.1 (0.86–12)

1997 2012

Survey Surveillance

Sub-national National

0 (0–17) 0 (0–98)

2007 2012 2011 2012 2012

Survey Surveillance Surveillance Surveillance Surveillance

National National National National National

1.4 (0.66–2.5) 0 (0–12) 0.44 (<0.1–2.4) 0 (0–22) 0 (0–71)

2012 2012 2011 2012 2012

Surveillance Surveillance Surveillance Surveillance Surveillance

National National National National National

26 (23–30) 0 (0–98) 20 (0.51–72) 0 (0–98) 23 (20–27)



Доклад о глобальной борьбе с туберкулезом 2013

Доклад о глобальной борьбе с туберкулезом 2013

WHO Library Cataloguing-in-Publication Data Global tuberculosis report 2013. 1.Tuberculosis – epidemiology. 2.Tuberculosis, Pulmonary – prevention and control. 3.Tuberculosis – economics. 4.Tuberculosis, Multidrug-Resistant. 5.Annual reports. I.World Health Organization. ISBN 978 92 4 456465 3 (NLM classification: WF 300)

© Всемирная организация здравоохранения, 2014 г. Все права защищены. Публикации Всемирной организации здравоохранения имеются на веб-сайте ВОЗ (www.who.int) или могут быть приобретены в Отделе прессы ВОЗ, Всемирная организация здравоохранения, 20 Avenue Appia, 1211 Geneva 27, Switzerland (тел.: +41 22 791 3264; факс: +41 22 791 4857; эл. почта: bookorders@who.int). Запросы на получение разрешения на воспроизведение или перевод публикаций ВОЗ — как для продажи, так и для некоммерческого распространения — следует направлять в Отдел прессы ВОЗ через веб-сайт ВОЗ (http://www.who.int/about/licensing/copyright_form/ en/index.html). Обозначения, используемые в настоящей публикации, и приводимые в ней материалы не отражают какого-либо мнения Всемирной организации здравоохранения относительно юридического статуса какой-либо страны, территории, города или района, или их органов власти, либо относительно делимитации их границ. Пунктирные линии на географических картах обозначают приблизительные границы, в отношении которых пока еще может быть не достигнуто полное согласие. Упоминание конкретных компаний или продукции некоторых изготовителей не означает, что Всемирная организация здравоохранения поддерживает или рекомендует их, отдавая им предпочтение по сравнению с другими компаниями или продуктами аналогичного характера, не упомянутыми в тексте. За исключением случаев, когда имеют место ошибки и пропуски, названия патентованных продуктов выделяются начальными прописными буквами. Всемирная организация здравоохранения приняла все разумные меры предосторожности для проверки информации, содержащейся в настоящей публикации. Тем не менее, опубликованные материалы распространяются без какой-либо четко выраженной или подразумеваемой гарантии. Ответственность за интерпретацию и использование материалов ложится на пользователей. Всемирная организация здравоохранения ни в коем случае не несет ответственности за ущерб, возникший в результате использования этих материалов. Информация доклада действительна на дату выпуска доклада, т. е. ноябрь 2013 года, и не должна более использоваться после выхода следующего выпуска доклада, который публикуется ежегодно на веб-сайте ВОЗ: http://www.who.int/tb/publications/global_report/ru/. Дизайн обложки сделали Tom Hiatt, Региональное бюро ВОЗ для стран западной части Тихого океана и Irwin Law, штаб-квартира ВОЗ. Передняя сторона обложки иллюстрирует самую последнюю информацию о глобальных достижениях по выполнению пяти показателей в рамках программы Целей тысячелетия в области развития (ЦТР). К ним относятся показатели заболеваемости туберкулезом (ТБ) на 100 000 населения в год, показатель распространенности туберкулеза на 100 000 населения, уровень смертности от ТБ на 100 000 населения в год, уровень выявления случаев заболевания ТБ (число вновь выявленных и зарегистрированных национальными программами по борьбе с ТБ случаев заболевания ТБ, деленное на оценочный показатель заболеваемости) и показатель успешности лечения вновь выявленных больных ТБ, начавших лечение. Каждая пара фигур представляет самый последний уровень показателей и базовый год, против которого ведется измерение достигнутых результатов. Для показателя заболеваемости (зеленый и темно оранжевый цвета), распространенности (серый и розовый) и смертности (светло оранжевый и голубой) вершина общей высоты каждой пары фигур показывает уровень 1990 года. Нижняя из двух фигур в каждой паре показывает уровень 2012 года. Для показателя выявления заболеваемости общая высота каждой пары фигур (темно синий и коричневый) показывает уровень 2012 года и нижняя из двух фигур (темно синий) показывает уровень 1995 года. Для показателя успешности лечения (красный и желтый) общая высота каждой пары показывает уровень 2011 года и нижняя из двух фигур (красный) показывает уровень 1995 года. Более подробная информация об этих показателях и достигнутом прогрессе в выполнении глобальных целей дана в Главе 2 и Главе 3 Доклада о глобальной борьбе с туберкулезом 2013. Министерство здравоохранения Российской Федерации финансировало перевод и печать этой публикации на русском языке. Дизайн minimum graphics Printed in Russia WHO/HTM/TB/2013.11

Содержание

Список сокращений Краткое резюме Глава 1. Введение Глава 2. Бремя туберкулеза Глава 3. Регистрируемая заболеваемость туберкулезом и результаты лечения Глава 4. Туберкулез с лекарственной устойчивостью возбудителя Глава 5. Диагностика туберкулеза и развитие лабораторной службы Глава 6. Мероприятия по борьбе с туберкулезом, сочетанным с ВИЧ-инфекцией Глава 7. Финансирование Глава 8. Научные исследования и научно-практические разработки Приложение 1. Методы, используемые для оценки глобального бремени туберкулеза Приложения «2. Профили стран», «3. Профили регионов», и «4. Ключевые показатели для мира, регионов ВОЗ и отдельных стран» не включены в перевод «Доклада о глобальной борьбе с туберкулезом 2013» на русский язык. Новейшую статистическую информацию можно загрузить с веб-сайта ВОЗ http://www.who.int/tb/country/ [Прим. ред.]

iv ix 1 6 28 45 59 68 75 86

Благодарности v

99

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Список сокращений ACSM ACTG AFR AMR DOTS DRS DTLC Информационно-пропагандистская деятельность, информирование и социальная мобилизация (Advocacy, Communication and Social Mobilization) Группа по организации клинических испытаний по ВИЧ-инфекции (AIDS Clinical Trials Group) Регион Африки (African Region) Регион Америки (Region of the Americas) стратегия ДОТС (Directly Observed Treatment Strategy) исследование по изучению распространенности лекарственной устойчивости (drug resistance survey) координатор по оказанию помощи больным туберкулезом и лепрой на районном уровне (District TB and Leprosy Coordinator) Европейский центр по профилактике и контролю заболеваний (European Centre for Disease Prevention and Control) Регион Восточного Средиземноморья (Eastern Mediterranean Region) электронные учетно-отчетные формы (electronic recording and reporting) Европейский регион (European region) Управление по контролю качества продовольствия и медикаментов, США (Food and Drug Administration, USA) Фонд развития новых инновационных методов диагностики (Foundation for Innovative New Diagnostics) Научно-исследовательский институт инфекционных болезней (Infectious Disease Research Institute) тест-система для анализа индукции интерферонагамма (interferon-gamma release assay) Инициатива по обеспечению доступных, качественных тестов на туберкулез (Initiative for Promoting Affordable, Quality TB Tests) методы амплификации нуклеиновых кислот (nucleic acid amplification test) Национальная программа по борьбе со СПИДом и ВИЧ-инфекцией (national AIDS programme) практический подход к здоровью легких (Practical Approach to Lung Health) персональный цифровой помощник (personal digital assistant) Чрезвычайный план Президента США по борьбе со СПИДом (US President’s Emergency Plan for AIDS Relief) система управления качеством (quality management system) Регион Юго-Восточной Азии (South-East Asia Region) Интегрированная информационная система по туберкулезу (Integrated Tuberculosis Information System) Стратегическая техническая и консультативная группа экспертов по туберкулезу (Strategy and Technical Advisory Group for TB) Инициативная группа действий по лечению туберкулеза (Treatment Action Group) Консорциум по моделированию и анализу эпидемиологии туберкулеза (TB Modelling and Analysis Consortium) Механизм технического содействия программам по борьбе с туберкулезом (Tuberculosis Technical Assistance Mechanism) Инициатива по обеспечению вакцинами против туберкулеза (Tuberculosis Vaccine Initiative) Отдел народонаселения ООН (United Nations Population Department) Регион Западной части Тихого океана (Western Pacific Region) Циль-Нельсен (Ziehl Neelsen) Агентство США по международному развитию АОЗ анализ олигонуклеотидными зондами, или молекулярные тесты с типоспецифичными зондами АРТ антиретровирусная терапия БРИКС группа из пяти стран: Бразилия, Российская Федерация, Индия, Китай, Южно-Африканская Республика БЦЖ бацилла Кальметта-Герена (Bacille-Calmette-Guérin, BCG) ВВП валовой внутренний продукт ВИЧ вирус иммунодефицита человека ВНД валовой национальный доход ВОЗ Всемирная организация здравоохранения ВОМП всеобщий охват медицинской помощью ГИРЛ Глобальная инициатива по развитию лабораторий ГРИ годовой риск инфицирования ГЧП государственно-частное партнерство ЕС Европейский союз (European Union) ЗАГС запись актов гражданского состояния КА когортный анализ КЗС Комитет Зеленого Света КОЕ колониеобразующие единицы КУМ кислотоустойчивые микобактерии ЛТИ латентная туберкулезная инфекция лекарственно-устойчивый туберкулез ЛУ ТБ лекарственно-чувствительный туберкулез ЛЧ ТБ международная классификация МКБ-10 болезней (10-я редакция) туберкулез с множественной МЛУ-ТБ лекарственной устойчивостью организация медицинской помощи на местном уровне МПМ неблагоприятные побочные реакции НПР лекарственного средства Национальная программа по борьбе с туберкулезом НПТ наднациональная референс-лаборатория НРЛ новый финансовый механизм НФМ охрана здоровья матери и ребенка ОЗМР относительная инцидентность ОИ место оказания медицинской помощи ОМП Обновленная национальная программа ОНПТ по борьбе с туберкулезом (Индия) Организация Объединенных Наций ООН относительный риск ОР Организация экономического ОЭСР сотрудничества и развития показатель выявления случаев заболевания ПВЗ прикладные исследования ПИ показатель летальности ПЛ Программа развития ООН ПРООН профилактическая терапия изониазидом ПТИ профилактическая терапия ко-тримоксазолом ПТК переходный финансовый механизм ПФМ полимеразная цепная реакция ПЦР ранняя бактерицидная активность РБА Региональный Комитет Зеленого Света рКЗС рибосомная рибонуклеиновая кислота рРНК рифампицин-устойчивый туберкулез РУ TБ страны с высоким бременем туберкулеза СВБ свето-излучающий диод СИД стандартное отклонение СО синдром приобретенного иммунодефицита СПИД отношение рисков ОР ТБ туберкулез туберкулиновая кожная проба ТКП тест на лекарственную чувствительность ТЛЧ Цели тысячелетия в области развития ЦТР ЮНИТЭЙД Международный механизм закупки лекарств (International Drug Purchase Facility) Объединенная программа ООН по ВИЧ/СПИДу ЮНЭЙДС

ECDC

EMR ERR EUR FDA

FIND IDRI IGRA IPAQT

NAAT NAP PAL PDA PEPFAR QMS SEAR SITT STAG-TB

TAG TB-MAC

TB-TEAM

TBVI UNPD WPR ZN АМР США

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Благодарности

Этот доклад о глобальной борьбе с туберкулезом (ТБ) был подготовлен основной группой в составе 15 человек: Annabel Baddeley, Anna Dean, Hannah Monica Dias, Dennis Falzon, Katherine Floyd, Inés Garcia, Philippe Glaziou, Tom Hiatt, Irwin Law, Christian Lienhardt, Linh Nguyen, Charalambos Sismanidis, Hazim Timimi, Wayne van Gemert и Matteo Zignol. Руководитель группы Katherine Floyd. Общее руководство осуществлял Директор Глобальной программы ВОЗ по борьбе с ТБ Mario Raviglione. Индивидуальные регистрационные карты (длинная и краткая версии) были разработаны Philippe Glaziou и Hazim Timimi, при участии сотрудников Глобальной программы ВОЗ по борьбе с ТБ. Hazim Timimi провел и организовал работу по всем аспектам управления данными. Inés Garcia и Andrea Pantoja провели весь анализ и последующую работу с финансовыми показателями. Обзор и последующая работа со всеми другими данными была сделана группой экспертов, в которую вошли Annabel Baddeley, Annemieke Brands, Andrea Braza, Katsura Danno, Anna Dean, Hannah Monica Dias, Dennis Falzon, Wayne van Gemert, Soleil Labelle, Knut Lönnroth, Linh Nguyen, Salah Ottmani, Hazim Timimi, Fraser Wares и Matteo Zignol из штаб-квартиры ВОЗ в Женеве; Amal Bassili из Регионального Офиса ВОЗ стран Восточного Средиземноморья; и Suman Jain, Sai Pothapregada, Nino Mdivani, Eliud Wandwalo и Mohammed Yassin из Глобального Фонда. Данные для Европейского региона были собраны и проверены совместно Европейским региональным Офисом ВОЗ и Европейским центром по профилактике и контролю заболеваний (ECDC); мы, в частности, благодарим Encarna Gimenez, Vahur Hollo и Csaba Ködmön из ECDC за предоставление файлов с проверенными данными и Andrei Dadu из Европейского регионального офиса ВОЗ за его значительный вклад в мониторинг и проверку данных для всех стран Европейского региона. Анализ данных по ТБ/ ВИЧ был проведен в сотрудничестве с Michel Beusenberg, Chika Hayashi, Lisa Nelson и Michelle Williams из Департамента ВОЗ по борьбе с ВИЧ-инфекцией. Victoria Bendaud, Josephine Dy и Taavi Erkkola из ЮНЭЙДС руководили сбором данных из национальных программ по борьбе со СПИДом, предоставили пакет данных по TБ/ВИЧ и тесно работали с сотрудниками ВОЗ по проведению анализа и проверки данных по ТБ/ВИЧ. Philippe Glaziou и Charalambos Sismanidis подготовили расчетные оценки бремени ТБ и связанные с ними количественные показатели и таблицы (Глава 2), при поддержке Tom Hiatt. Особая благодарность Carel Pretorius (Институт прогнозов), тесно работавшей с Philippe Glaziou в области анализа и связанных с ним оценок смертности от ТБ среди ВИЧ-инфицированных людей, а также Dennis Falzon за координацию систематического анализа, используемого для расчета показателей смертности, связанной с туберкулезом с множественной лекарственной устойчивостью (МЛУ-ТБ), и Harish Nair и Luciana Brondi из Эдинбургского Университета за проведение этого обзора. Tom Hiatt подготовил все показатели и таблицы по данным регистрации случаев ТБ и результатов лечения (Глава 3). Anna Dean, Dennis Falzon и Matteo Zignol провели анализ данных и подготовили показатели и таблицы по данным в отношении лекарственно-​ устойчивого ТБ (Глава 4). Свой вклад внесла также Charalambos Sismanidis. Tom Hiatt и Wayne van Gemert подготовили количественные показатели и таблицы по укреплению лабораторий

и внедрению новой диагностики (Глава 5). Annabel Baddeley, Katsura Danno, Tom Hiatt и Linh Nguyen провели анализ программных данных по ТБ, сочетанному с ВИЧ-инфекцией и подготовили связанные с ними количественные показатели и таблицы (Глава 6). Inés Garcia и Andrew Siroka проанализировали данные по финансам и подготовили связанные с ними количественные показатели и таблицы (Глава 7). Christian Lienhardt, Christopher Gilpin и Karin Weyer подготовили показатели по каналам поставки новых противотуберкулезных лекарств, диагностических средств и вакцин (Глава 8), свой вклад внесли также соответствующие Рабочие группы Партнерства «Остановить ТБ». Tom Hiatt координировал окончательную доработку всех показателей и таблиц и был ответственным лицом по связи с графическим дизайнером. Написание основной части доклада велось под руководством Katherine Floyd, при участии Dennis Falzon, Philippe Glaziou, Irwin Law, Ikushi Onozaki и  Charalambos Sismanidis (Глава 2); Hannah Monica Dias, Wayne van Gemert, Haileyesus Getahun, Thomas Joseph, Mukund Uplekar и Lana Tomaskovic (Глава 3); Inés Garcia и Christian Gunneberg (Глава 7). Глава 4 по лекарственно-устойчивому ТБ была подготовлена Anna Dean, Dennis Falzon и  Matteo Zignol, при участии Katherine Floyd, Philippe Glaziou и Charalambos Sismanidis. Глава 5, по средствам диагностики и укреплению лабораторий была подготовлена Wayne van Gemert при участии Christopher Gilpin, Fuad Mirzayev и Karin Weyer. Глава 6 была подготовлена Annabel Baddeley, Haileyesus Getahun, Linh Nguyen и Katherine Floyd. Составление Главы 8 по исследованиям и развитию велось под руководством Christian Lienhardt при участии Christopher Gilpin, Karin Weyer и Katherine Floyd. Глава 8 была тщательно проверена председателями и секретариатами Рабочих групп Партнерства «Остановить ТБ». Особая благодарность Michael Brennan, Uli Fruth и Jennifer Woolley (новые вакцины); Daniela Cirillo (новые средства диагностики); Barbara Laughon и Mel Spigelman (новые противотуберкулезные препараты). Группа по подготовке доклада также благодарна Emily Bloss (Центры по профилактике и контролю заболеваний США) and Hillary Kipruto (Офис ВОЗ в Кении) за их вклад в содержательную часть по укреплению надзора за туберкулезом в Главе 2, включая тематическое исследование по введению электронной регистрации и отчетности в Кении; Rajendra Yadav и Masami Fujita (Офис ВОЗ в Камбодже) за их вклад в анализ интеграции ТБ, ВИЧ и услуг по охране здоровья матери и ребенка в Камбодже (Глава 6); и различным внутренним и внешним рецензентам за полезные комментарии и предложения к предварительным наброскам текста данной Главы. Специальное приложение «Обратный отсчет до 2015 года», сопровождающее глобальный доклад, было подготовлено Anna Dean, Hannah Monica Dias, Katherine Floyd, Irwin Law, Mario Raviglione и Diana Weil, при участии и полезной информации от многих сотрудников на глобальном, региональном и национальном уровнях. В частности мы благодарим Sai Pothapregada и Eliud Wandwalo из Глобального фонда, которые способствовали обсуждению и получению информации от многих менеджеров Фонда. Приложение 1, в котором разъясняются методы, используемые для производства оценки бремени болезни, вызванной v

Доклад о глобальной борьбе с туберкулезом 2013

туберкулезом, было написано Philippe Glaziou и Charalambos Sismanidis с очень полезной информацией от Carel Pretorius. Мы благодарим Colin Mathers из группы ВОЗ по оценке смертности и бремени болезни за его тщательный обзор. Обзоры по странам, которые даются в Приложении 2 1 и обзоры по регионам, которые даются в Приложении 3 2, были подготовлены Hazim Timimi. При3, в котором содержится информация на глобальном, ложение 4  региональном и национальном уровнях из глобальной базы данных по ТБ, было подготовлено Tom Hiatt и Hazim Timimi. Благодарим Pamela Baillie из группы по мониторингу и оценке Глобальной программы за безупречную административную поддержку, Doris Ma Fat из Группы ВОЗ по оценке смертности и бремени болезни за предоставление данных по смертности от ТБ, взятых из базы данных ВОЗ о смертности и Peter Ghys, Mary Mahy и Karen Stanecki (ЮНЭЙДС) за предоставление эпидемиологических данных, которые были использованы для оценки смертности от ТБ, сочетанноro с ВИЧ-инфекцией. Весь доклад был отредактирован Tim France (ИНИС связь). Мы благодарим его за отличную работу. Мы также благодарим, как всегда, Sue Hobbs за ее отличную работу по дизайну и верстке этого доклада. Ее вклад, как и в предыдущие годы, был очень высоко оценен. Основным источником финансовой поддержки работы ВОЗ по глобальному мониторингу и оценке ТБ является Агентство США по международному развитию (ЮСЭЙД), без которого было бы невозможно сделать Доклад о глобальной борьбе с ТБ. Подготовка доклада была осуществлена также при поддержке правительств Японии и Республики Кореи. Мы с благодарностью принимаем их поддержку. В дополнение к основной группе и вышеупомянутым специалистам в доклад внесли вклад многие сотрудники ВОЗ из региональных офисов и офисов в странах, а также сотни людей, работающих в национальных программах по борьбе с туберкулезом или в национальных системах эпиднадзора путем предоставления отчетных данных и анализа материалов доклада до его публикации. Эти люди перечислены ниже по регионам ВОЗ. Мы благодарим всех за их неоценимый вклад и сотрудничество, без помощи которых этот доклад не мог бы быть подготовлен. Среди сотрудников ВОЗ, не упомянутых выше мы благодарим, в частности Khurshid Alam Hyder, Daniel Kibuga, Rafael López Olarte, André Ndongosieme, Wilfred Nkhoma и Henriette Wembanyama за их огромный вклад в сбор данных, их проверку и анализ.

Регион Америки Monica Alonso Gonzalez, Angel Manuel Alvarez, Luis Gerardo Castellanos, Gerardo de Cossio, Rachel Eersel, Marcos Espinal, Ingrid García, Mirtha Del Granado, Rosalinda Hernández, Vidalia Lesmo, Rafael López Olarte, Wilmer Marquiño, Thais dos Santos, Alfonso Tenorio, Jorge Victoria, Anna Volz.

Регион Восточного Средиземноморья Mohamed Abdel Aziz, Ali Akbar, Samiha Baghdadi, Amal Bassili, Najwa El Emam, Hamida Khattabi, Aayid Munim, Ghulam Nabi Kazi, Ali Reza Aloudel, Gabriele Riedner, Karam Shah, Sindani Ireneaus Sebit, Bashir Suleiman, Rahim Taghizadeh.

Европейский регион Martin van den Boom, Brenda van den Bergh, Andreea Cassandra Butu, Silvu Ciobanu, Pierpaolo de Colombani, Andrei Dadu, Irina Danilova, Masoud Dara, Jamshid Gadoev, Gayane Ghukasyan, Sayohat Hasanova, Arax Hovhannesyan, Saliya Karymbaeva, Mehmet Kontas, Kristin Kremer, Dmitriy Pashkevich, Valiantsin Rusovich, Bogdana Shcherbak-Verlan, Javahir Suleymanova, Szabolcs Szigeti, Melita Vujnovic.

Регион Юго-Восточной Азии Mohammad Akhtar, Vikarunnesa Begum, Erwin Cooreman, Deki, Khurshid Alam Hyder, Navaratnasingam Janakan, Kim Tong Hyok, La Win Maung, Jorge Luna, Partha Mandal, Amaya Maw-Naing, Giampaolo Mezzabotta, Bo Myint, Ye Myint, Eva Nathanson, Rajesh Pandav, Razia Pendse, Sri Prihatini, K Rezwan, Rim Kwang Il, Hwang Kum Ryong, Mukta Sharma, Aminath Shenalin, Achuthan Nair Sreenivas, Chawalit Tantinimitkul, Wangchuk Lungten.

Регион Западной части Тихого океана Shalala Ahmadova, Niño Dayanghirang, Asaua Faasino, Salu Failauga, Ogtay Gozalov, Cornelia Hennig, Tom Hiatt, Tauhid Islam, Narantuya Jadambaa, Ridha Jebeniani, Sung Hye Kim, Miwako Kobayashi, WooJin Lew, Katsunori Osuga, Khanh Pham, Fabio Scano, Jacques Sebert, Catharina van Weezenbeek, Rajendra Yadav, Dongbao Yu.

Национальные респонденты, внесшие вклад в отчетность и проверку данных Регион Африки Abdou-Salam Abderemane, Ouédraogo Adama, Abdelrahim Barka Abderramane, Jean Louis Abena Foe, Sofiane Alihalassa, Arlindo Amaral, Kouamé Amenan, Séverin Anagonou, Younoussa Assoumani, Georges Bakaswa, Adama Marie Bangoura, Jorge Noel Barreto, Ballé Boubakar, Victor Bonkoungou, Frank Adae Bonsu, Miguel Camara, Evangelista Chisakaitwa, Ernest Cholopray, Nkemdilim Chukwueme, Catherine Cooper, Swasilanne da Silva, B. de Sousa Bandeira, Isaias Dambe, Davi Kokou Mawulé, Serge Diagbouga, Aicha Diakité, Awa Helene Diop, Sicelo Dlamini, Themba Dlamini, Thaddée Ndikumana, Oumou Fofana, Susan Gacheri, Evariste Gasana, Michel Gasana, Sandile Ginindza, Martin Gninafon, Nii Nortey Hanson-Nortey, Adama Jallow, Saffa Kamara, Madou Kane, Henry Kanyerere, Nathan Kapata, Biruck Kebede, Kerram Aziza, Deogratias Kibambazi, Patrick Konwuloh, Jacquemin Kouakou, Popaul Kulonga, Rossin Lebeke, Lillian Ishengoma, Llang Bridget Maama-Maime, Marcel Lougue, Maxime Lunga, Ghislaine Mabeluanga Tshitenge, Jocelyn Mahoumbou, Angelo Makpenon, David Mametja, Ivan Manhiça, Tseliso Marata, Farai Mavhunga, Mba Bekolo Frenk José Mathieu, Salem Salem Mohameden, Louine Morel, Youwaoga Isidore Moyenga, James Mpunga, Frank Mugabe, Kenneth Mugisha, Clifford Munyandi, Lindiwe Mvusi, Aboubacar Mzembaba, Ronald Ncube, Fulgence Ndayikengurukiye, Yvon Martial Ngana, Antoine Ngoulou,

Сотрудники ВОЗ в региональных офисах и в офисах в странах Регион Африки Harura Adamu, Boubacar Ould Abdel Aziz, Esther Aceng, Inacio Alvarenga, Balde Amadou, Ayodele Awe, Sanni Babatunde, Bazie Babou, Nayé Bah, Marie Barouan, Abera Bekele, Norbert Bidounga, Gaël Claquin, Augusto da Cruz Claudina, Peter Clement, Noel Djemadji, Ismael Hassen Endris, Amos Omoniyi Fadare, Louisa Ganda, Boingotlo Gasennelwe, Patrick Hazangwe, Joseph Imoko, Michael Jose, Joel Kangangi, Katherine Lao, Nzuzi Katondi, Bah Keita, Daniel Kibuga, Hillary Kipruto, Désiré Aristide Komangoya Nzonzo, Sharmila Lareef-Jah, Frank Lule, Mwendaweli Maboshe, Mbemba Leonard, Richard Mbumba, Julie Mugabekazi, André Ndongosieme, Denise Nkezimana, Wilfred Nkhoma, Nicolas Nkiere, Ghislaine Nkone Asseko, Ishmael Nyasulu, Laurence Nyiramasarabwe, Samuel Ogiri, Daniel Olusoti, Amos Omoniyi, Chijioke Osakwe, Felicia Owusu-Antwi, Philips Patrobas, Kalpeshsinh Rahevar, Bacary Sambou, Kefas Samson, Neema Simkoko, Desta Tiruneh, Alexis Tougordi, Henriette Wembanyama. 1,2,3 http://www.who.int/tb/country/data/download — см. примеч. на стр. iii

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Lourenço Nhocuana, Blasdus Franz Njako, Emmanuel Nkiligi, M Nkou, Joshua Obasanya, Davidson Ogunade, Hermann Ongouo, Abdelhadi Oumar, Issoufou Ousmane, Maria Conceição Palma, Victor Pereira, Thato Raleting, Sahondra Jeanine Randriambeloson, Rujeedawa Mohammed Fezul, Samey Agbenyegan, Charles Sandy, Kebba D Sanneh, Marie Sarr Diouf, Mineab Sebhatu, Mamie Shoma, Angele Shoma Matota, René Simalo, Joseph Sitienei, Nicholas Siziba, Philippe Takongo, Celstino Francisco Teixeira, Mohamed Abdallahi Traoré, Nassiama Traoré, Kassim Traoré, Alie Wurie, Eucher Dieudonné Yazipo, Ranivomahefa Myrienne Bakoliarisoa Zanajohary, Abbas Zezai, Eric Ismaël Zoungrana.

Регион Америки Christian Acosta, Shalauddin Ahmed, Valentina Antonieta Alarcon Guizado, Xochil Alemán de Cruz, Kiran kumar Alla, Valeria Almanza Torrez, Mirian Alvarez, Raúl Álvarez, Aisha Andrewin, A. Alister Antoine, Chris Archibald, Carlos Alberto Marcos Ayala Luna, Wiedjaiprekash Balesar, Draurio Barreira, Patricia Bartholomay, Soledad Beltrame, María del Carmen Bermúdez, Lynrod Brooks, Marta Calona de Abrego, Martín Castellanos Joya, Jorge Castillo Carbajal, Kenneth Castro, Judith Cazares, Gemma Chery, Carlos Cuadra, Ofelia Cuevas, D’Auvergne Cleophas, Jose Davy, Cecilia de Arango, Eva de Weever-Lista, Camille Deleveaux, Dy-Juan De Roza, Roger Duncan, España Cedeño Mercedes, Manuel Salvador España Rueda, Fernandez Hugo, Cecilia Figueroa Benites, Victor Gallant, Julio Garay Ramos, Sarita Aguirre García, Izzy Gerstenbluth, Margarita Godoy, Roscio Gómez, Ilse Maria Góngora Rivas, Silvino González, Yaskara Halabi, Kevin Harvey, Dorothea Hazel, Maria Henry, Tania Herrera, Carla Jeffries, Dihadenys Lemus Molina, Athelene Linton, Maria Josefa Llanes Cordero, Marvin Andres Maldonado Rivera, Maldonado Saavedra Andrea, Marcelino Belkys, Eva Martìnez, María de Lourdes Martínez Olivares, Zeidy Mata Azofeifa, Joan McLeod-Simon, Timothy McLaughlin-Munroe, Roque Miramontes, Leilawatie Mohammed, Jeetendra Mohanlall, Ernesto Moreno, Francis Morey, Willy Morose, Michael Owen, Cheryl Peek-Ball, Janelle Pickering, Tomasa Portillo, Irad Potter, Manohar Singh Rajamanickam, Dottin Ramoutar, Anna Esther Reyes Godoy, Paul Ricketts, Jorge Rodriguez De Marco, Myrian Román, Nilda de Romero, Carolyn Russell, Wilmer Salazar, Deborah Stijnberg, Sutton Jackurlyn, Torres Clarita, Maribelle Tromp, William Turner, Melissa Valdez, Daniel Vázquez, Nestor Vera, Michael Williams, David Yost, Oritta Zachariah.

Domnica Ioana Chiotan, Ana Ciobanu, Nico Cioran, Andra Cirule, Thierry Comolet, Radmila Curcic, Manfred Danilovitš, Edita Davidaviciene, Hayk Davtyan, Pava Dimitrijevic, António Diniz, Francis Drobniewski, Raquel Duarte, Mladen Duronjic, Connie Erkens, Jennifer Fernandez Garcia, Lyalya Gabbasova, Viktor Gasimov, Lárus Jón Guðmundsson, Gennady Gurevich, Walter Haas, Hasan Hafizi, Evgeny Hanyukov, Armen Hayrapetyan, Peter Helbling, Sven Hoffner, Daniela Homorodean, Jahongir Jurakhonovich Ismoilov, Mamuka Japaridze, Vincent Jarlier, Soledad Jiménez Pajares, Jerker Jonsson, Abdullat Kadyrov, Gulmira Kalmambetova, Dmitry Klymuk, Maria KorzeniewskaKosela, Ainura Koshoeva, Košnik Mitja, Gabor Kovacs, Tiina Kummik, Nino Lomtadze, Stevan Lučić, Jasminka Maglajllic, Turid Mannsåker, Mathys Vanessa, Rafail Mehdiyev, Rukije Mehmeti, Donika Mema, Vladimir Milanov, Alvard Mirzoyan, Gjyle Mulliqi, Gulnora Murmusaeva, Seher Musaonbasioglu, Ucha Nanava, Zdenka Novakova, Joan O’Donnell, Analita Pace Asciak, Clara Palma Jordana, Elena Pavlenko, Olga Pavlova, Monique Perrin, Edita Pimkina, Monika Polanova, Georgeta Gilda Popescu, Gordana Radosavljevic Asic, Bozidarka Rakocevic, Thomas Rendal, Vija Riekstina, Jerome Robert, Elena Rodríguez Valín, Tom Rogers, Elena Romancenco, Kazimierz Roszkowski-Sliz, Sabine Rüsch-Gerdes, Branislava Savic, Gérard Scheiden, Hasia Kaidar Shwartz, Anabela Silva, Girts Skenders, Cathrine Slorbak, Erika Slump, Hanna Soini, Ivan Solovic, Dick van Soolingen, Flemming Stenz, Sergey Sterlikov, Jana Svecova, Svetina Šorli Petra, Silva Tafaj, Talevski Stefan, Odorina Tello Anchuela, Mirzagaleb Tillyashaykhov, Aida Ustamujic, Gulnoz Uzakova, Tonka Varleva, Piret Viiklepp, Cveta Vragoterova, Gerard de Vries, Jiri Wallenfels, Wanlin Maryse, Pierre Weicherding, Aysegul Yildirim, Zakoska Maja, Oksana Zalutskaya, Ilona Zemanová, Manca Žolnir Dovč, Hasan Zutic.

Регион Юго-Восточной Азии Shina Ahmed, Aminath Aroosha, Choe Kum Song, Emdadul Hoque, RS Gupta, Sirinapha Jittimanee, Suksont Jittimanee, Niraj Kulshrestha, Constantino Lopes, Thandar Lwin, Dyah Erti Mustikawati, Tin Zar Naing, Chawetsan Namwat, Md Nuruzzaman Haque, Nirupa Pallewatta, Rajendra Prasad Pant, Kiran Rade, Dyah Armi Riana, Chewang Rinzin, Sudath Samaraweera, Gamini Senevirathne, Janaka Thilakarathne, Sabino Viegas, Bimal Kumar Yadav.

Регион Западной части Тихого океана Paul Aia, Cecilia Teresa T. Arciaga, Nemia Bainivalu, Christina Bareja, Risa J. Bukbuk, Cheng Shiming, Phonenaly Chittamany, Chou Kuok Hei, Nese Ituaso Conway, Du Xin, Mayleen J. Ekiek, Fanai Saen, Rangiau Fariu, Ludovic Floury, Louise Fonua, Jiloris Frederick Dony, Anna Marie Celina Garfin, Go Un-Yeong, Shakti Gounder, Anie Haryani Hj Abdul Rahman, Noel Itogo, Tom Jack, Seiya Kato, Khin Mar Kyi Win, Lamar Daniel, Leo Lim, Liza Lopez, Sakiusa Mainawalala, Henri-Pierre Mallet, Tan Eang Mao, Markleen Tagaro, Serafi Moa, Suzana Mohd Hashim, Nguyen Binh Hoa, Nguyen Viet Nhung, Nou Chanly, Ochirbat Batbayar, Connie Bieb Olikong, Park Yoon-Sung, Nukutau Pokura, Waimanu Pulu, Purev Nasanjargal, Rabauliman Marcelina, Bereka Reiher, Bernard Rouchon, Temilo Seono, Tokuaki Shobayashi, Vita A. Skilling, Grant Storey, Phannasinh Sylavanh, Kenneth Reuee Tabutoa, Tam Cheuk Ming, Kyaw Thu, Tieng Sivanna, Tong Ka Io, Rosalind Vianzon, Wang Yee Tang, Wang Lixia.

Регион Восточного Средиземноморья Fadhil Abbas, Mohammad S Abouzeid, Khaled Abu Ruhman, Nadia Abu Sabra, Ahmadi Shahnaz, Mohamed Redha Al Lawati, Al Saidi Fatmah, Samia Ali Alagab, Abdelbary Abdullah Ahmed Al-Hammadi, Abdullatif Al-Khal, Saeed Al Saffar, Kifah Alshaqeldi, Bahnasy Samir, Bennani Kenza, Kinaz Cheikh, Walid Daoud, Mohamed Furjani, Amal Galal, Dhikrayet Gamara, Assia Haissama Mohamed, Hiba Kamal Hamad Elneel, Kaalthoom Hassan, Hawa Hassan Guessod, Lou Joseph, Onwar Otien Jwodh Chol, Basharat Khan, Joseph Lasu, Sayed Daoud Mahmoodi, Khadiga Adam Mohammed, Mokhtar Alaa, Mulham Mustafa, Nasehi Mahshid, Ejaz Qadeer, Mohammad Khalid Seddiq, Sghiar Mohammed, Mohemmed Tabena, Tamara Tayeb, Najib Abdul aziz Abdullah Thabit, Seddik Walha, Yaacoub Hiam.

Европейский регион Abildaev Tleukhan Shildebaevich, Mokhonim Abdulloeva, Ibrahim Abubakar, Rafig Abuzarov, Nurhan Albayrak, Natavan Alikhanova, Avtandil Alisherov, Ewa AugustynowiczKopeć, Ekkehardt Altpeter, Laura Anderson, Delphine Antoine, Trude Margrete Arnesen, Rusudan Aspindzelashvili, Andrei Astrovko, Elizabeta Bachiyska, Anna Ivanovna Barbova, Yana Besstraschnova, Venera Lazarevna Bismilda, Oktam Ikramovich Bobokhojaev, Olivera Bojovic, Eric C. Böttger, Bonita Brodhun, Noa Cedar, Daniel Chemtob, Доклад о глобальной борьбе с туберкулезом 2013

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Краткое резюме

Туберкулез (ТБ) остается одной из основных глобальных проблем здравоохранения. В 2012 году по оценкам, 8,6 млн человек заболели ТБ, а 1,3 млн — умерли от этой болезни (в том числе 320 000 ВИЧ-инфицированных людей) 1. Число смертей от туберкулеза является недопустимо большим, если учесть, что бóльшая часть из них предотвратима. Почти через 20 лет после провозглашения Всемирной организацией здравоохранения туберкулеза в качестве глобальной проблемы общественного здравоохранения, сделан существенный прогресс в достижении глобальных целевых показателей 2015 года, установленных в контексте Целей тысячелетия в области развития (ЦТР). За два года до окончательного срока в  «Докладе о глобальной борьбе с туберкулезом 2013» и в прилагаемом к нему «Обратном отсчете до 2015 года» дается оценка хода достижения целевых показателей 2015 года, а также указываются главные приоритетные меры, необходимые для достижения этих целевых показателей и/или дальнейшего движения.

•• Продвижение к достижению целевых показателей по диагностике и лечению ТБ с множественной лекарственной устойчивостью (МЛУ-ТБ) заметно отстает от графика. В мире в целом и в большинстве стран с высоким бременем МЛУ-ТБ, по оценкам, в 2012 году менее 25% людей были выявлены с МЛУ-ТБ. •• Многие страны добились значительного прогресса по преодолению эпидемии ТБ, сочетанного с ВИЧ-инфекцией. Однако целевые показатели глобального уровня по тестированию на ВИЧ среди больных ТБ, и обеспечению антиретровирусной терапии (АРТ) ВИЧ-инфицированным, не достигнуты.

Пять первоочередных мер, необходимых для ускорения достижения целевых показателей 2015 года: 1. Охватить упущенные случаи. Около 3 млн человек, заболевших ТБ в 2012 году, были упущены национальными системами уведомления. В число ключевых мер, необходимых для выявления лиц с этим заболеванием, и обеспечения получения ими правильного лечения и ухода входят: расширение услуг (включая быстрое тестирование) во всех системах здравоохранения при поддержке неправительственных организаций, социальных работников и добровольцев при диагностике случаев и представлении докладов о них; более активное сотрудничество с государственными больницами и частными медико-санитарными учреждениями, которые лечат пациентов, но не представляют отчетность; введение обязательного уведомления о случаях ТБ в большем числе стран; усовершенствование сбора данных. 2. Подходить к МЛУ-ТБ как к кризису общественного здравоохранения. В странах, где велико бремя МЛУ-ТБ, усиление потенциала по диагностике МЛУ-ТБ должно соответствовать запасам качественных лекарственных препаратов и наращиванию потенциала страны по обеспечению эффективного лечения и ухода. Для этого потребуется политическая воля и лидерство на высоком уровне, а также более активное сотрудничество между партнерами, включая органы, регулирующие лекарственные препараты, доноров и технические агентства, гражданское общество и фармацевтическую отрасль. 3. Ускорить реагирование на ТБ/ВИЧ. Главным приоритетом является расширение охвата ВИЧ-инфицированных больных ТБ посредством АРТ до 100%-го целевого показателя. Вторым приоритетом является расширение охвата профилактическим лечением ТБ ВИЧ-инфицированных людей. 4. Увеличить финансирование для ликвидации нехватки ресурсов. По оценкам, ежегодно требуется 7–8 млрд долл. США для обеспечения полного реагирования на эпидемию ТБ в странах с низким и средним уровнем доходов в 2014 и 2015 годах (не включая научные исследования и разработки по новым средствам диагностики ТБ, лекарственным препаратам и вакцинам). В 2013 году сумма финансирования составила около 6 млрд долл. США. Для ликвидации дефицита, достигающего 2 млрд долл. США в год, необходимо наращивать как внутреннее, так и донорское финансирование, в том числе за счет пополнения Глобального фонда в 2013 году. Без ix

ОБРАТНЫЙ ОТСЧЕТ ДО 2015 ГОДА: ключевые выводы В графике: •• Показатель вновь выявленных случаев ТБ уже около 10 лет снижается во всем мире, достигнув глобального целевого показателя ЦТР. Показатели заболеваемости ТБ также сокращаются во всех шести регионах ВОЗ. Темпы сокращения (2% в год) остаются медленными. •• В глобальном масштабе к 2012 году показатели смертности от ТБ сократились на 45% с 1990 года. Целевой показатель по сокращению смертности на 50% к 2015 году почти достигнут. •• В двух регионах ВОЗ уже достигнуты целевые показатели 2015 года по сокращению заболеваемости, распространенности и смертности: это регион Америки и регион Западной части Тихого океана. •• Из 22 стран с высоким бременем ТБ (СВБ), на которые приходится около 80% случаев ТБ 2 в мире, семь уже достигли всех целевых показателей 2015 года по сокращению заболеваемости, распространенности ТБ и смертности от него. Еще четыре СВБ идут по графику выполнения к 2015 году.

Отставание от графика: •• К 2012 году уровень активного заболевания ТБ среди населения (распространенность) в  мире упал на 37% после 1990 года. Не ожидается, что целевой показатель 50%-го сокращения к 2015 году будет достигнут. •• Регион Африки и Европейский регион в настоящее время выбились из графика достижения целевых показателей по смертности и распространенности ТБ. •• Из 22 СВБ 11 отстают от графика по сокращению заболеваемости, распространенности и смертности в соответствии с целевыми показателями. Это происходит по ряду причин, включая ограничения ресурсов, конфликты и нестабильность, а также эпидемии ВИЧ.

Доклад о глобальной борьбе с туберкулезом 2013

адекватного финансирования прогресс остается хрупким и может повернуть вспять. 5. Обеспечить быстрое внедрение инноваций. Быстрое внедрение новых средств и стратегий улучшения диагностики, лечения и профилактики всех форм ТБ можно ускорить за счет оперативных исследований с учетом специфики стран, а также воплощения результатов таких исследований в политике и на практике.

ДОПОЛНИТЕЛЬНЫЕ ВЫВОДЫ Доклад основан, главным образом, на данных, которые были представлены государствами-членами ВОЗ. В 2013 году данные были представлены 178 государствами-членами ВОЗ и в целом 197 странами и территориями, на которые коллективно приходится более 99% случаев ТБ в мире.

Бремя болезни Текущая глобальная ситуация ТБ свидетельствует о продолжающемся прогрессе, но он идет недостаточно быстрыми темпами. •• По оценкам, 1,1 млн (13%) из 8,6 млн человек, заболевших ТБ в 2012 году, были ВИЧ-инфицированными. Около 75% из этих случаев — в регионе Африки. •• В глобальном масштабе в  2012  году, согласно оценкам, 450 000 человек заболели МЛУ-ТБ и 170 000 человек умерли от МЛУ-ТБ. •• В большинстве случаев заболевают ТБ и умирают от него мужчины, но ТБ остается и одним из трех главных факторов смертности среди женщин во всем мире. По оценкам в 2012 году от ТБ умерло 410 000 женщин, включая 160 000 из числа ВИЧ-инфицированных. Половина из ВИЧ-инфицированных лиц, умерших от туберкулеза в 2012 году, были женщинами. По оценкам, из 8,6 млн вновь выявленных случаев ТБ во всем мире в 2012 году, 2,9 млн были среди женщин. •• По оценкам, в 2012 году было 530 000 случаев заболевания детей ТБ (в возрасте до 15 лет) и 74 000 случаев смерти от ТБ (среди ВИЧ-отрицательных детей) (6% и 8% от общего глобального количества соответственно). •• Большинство случаев в мире в 2012 году отмечалось в регионах Юго-Восточной Азии (29%), Африки (27%) и Западной части Тихого океана (19%). Лишь на долю Индии и Китая пришлось 26% и 12% от общего числа случаев ТБ соответственно. •• Показатели заболевания ТБ на уровне стран значительно варьируются, причем в Свазиленде и ЮАР отмечается порядка тысячи или более случаев на 100 000 населения, а в некоторых частях Американского континента, в ряде стран Западной Европы, в Японии, Австралии и Новой Зеландии отмечается менее 10 случаев на 100 000 населения.

•• В 2011 году сохранялись высокие показатели успешного лечения на уровне 87% по всем вновь выявленным случаям ТБ. •• Уведомления о случаях ТБ в глобальных масштабах стабилизировались. Согласно оценкам в 2012 году около 66% (5,7 млн человек) из 8,6 млн человек, заболевших ТБ, были включены в уведомления в качестве вновь диагностированных случаев. •• По оценкам, около 75% из 2,9 млн «упущенных случаев» — людей, которые были либо не диагностированы, либо диагностированы, но без уведомления НПТ, — пришлось на 12 стран. Этими странами, в порядке общего количества «упущенных случаев», были: Индия (31% глобального общего числа), Южно-Африканская Республика, Бангладеш, Пакистан, Индонезия, Китай, Демократическая Республика Конго, Мозамбик, Нигерия, Эфиопия, Филиппины и Мьянма. •• Тест быстрой молекулярной диагностики Xpert MTB/RIF быстрыми темпами внедряется в странах для выявления ТБ и ТБ с устойчивостью к рифампицину. По состоянию на конец июня 2013 года 88 из 145 стран, имеющих право на льготные цены, приобрели 1402 тестовых аппарата и 3,2 млн тестовых картриджей. •• Показатели успешного лечения ТБ по-прежнему являются самыми низкими в Европейском регионе, где в 2011 году было успешно пролечено лишь 72% вновь выявленных случаев.

Результаты выявления и лечения МЛУ-ТБ и ШЛУ-ТБ Невыявленные случаи и пробелы в охвате лечением создают кризис общественного здравоохранения. •• В глобальном масштабе в 2012 году данные обследований лекарственной устойчивости и непрерывного эпиднадзора случаев ТБ, по которым поступили уведомления, говорят о том, что МЛУ-ТБ наблюдался в 3,6% вновь диагностированных случаев ТБ и в 20% случаев с предшествующим лечением ТБ. Самые высокие уровни МЛУ-ТБ наблюдались в Восточной Европе и Центральной Азии, где в некоторых странах более 20% вновь выявленных случаев ТБ и более 50% ранее пролеченных случаев ТБ имели МЛУ-ТБ. •• В 2012 году было выявлено в общей сложности 94 000 больных ТБ, подлежащих лечению МЛУ-ТБ: 84 000 человек с подтвержденным МЛУ-ТБ (т. е. устойчивостью как к рифампицину, самому мощному лекарственному препарату против ТБ, так и к изониазиду); плюс 10 000 человек с устойчивостью к рифампицину были выявлены с использованием Xpert MTB/ RIF. По сравнению с 2011 годом произошло увеличение на 42% числа выявленных случаев, подлежащих лечению. Наибольший прирост между 2011 и 2012 годом наблюдался в Индии, Южно-Африканской Республике и Украине. •• Лечение препаратами второго ряда в 2012 году было начато для немного более 77 000 человек с МЛУ-ТБ, что эквивалентно 82% от 94 000 впервые выявленных случаев, подлежащих лечению в глобальном масштабе. Пробелы в охвате лечением выявленных случаев были значительно больше в некоторых странах, особенно в регионе Африки (51% зарегистрированных для лечения), и эти пробелы расширились в Китае, Пакистане и Южно-Африканской Республике. •• По состоянию на конец 2012 года 92 страны сообщили, по крайней мере, об одном случае туберкулеза с  широкой лекарственной устойчивостью (ШЛУ-ТБ). В среднем, по оценкам, 9,6% случаев МЛУ-ТБ имеют ШЛУ-ТБ. •• В глобальном масштабе лишь 48% пациентов с МЛУ-ТБ из выявленной в 2010 году когорты случаев были успешно пролечены, что отражает высокие показатели смертности и потерь для дальнейшего наблюдения. В 34 из 107 стран был достигнут показатель в 75% или более успешного лечения пациентов с МЛУ-ТБ.

Результаты выявления и лечения ТБ Ежегодно миллионы людей получают доступ к эффективному лечению ТБ, однако успехи ограничены из-за «упущенных случаев». •• В период с 1995 по 2012 годы 56 млн человек были успешно пролечены от ТБ в тех странах, которые перешли на глобальную стратегию ВОЗ по ТБ, в результате чего было спасено 22 млн жизней. •• В 2012 году национальные программы по борьбе с ТБ (НПТ) были уведомлены о 6,1 млн случаев ТБ. Из этого числа 5,7 млн пришлось на новые диагнозы в 2012 году, а 0,4 млн были ранее диагностированными больными ТБ, для которых изменился курс лечения.

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Меры против ТБ-ВИЧ Совместные услуги по ТБ-ВИЧ расширяются, но глобальные целевые показатели пока еще далеки. •• Основными мерами по сокращению бремени ВИЧ-инфекции у больных ТБ являются тестирование на ВИЧ и обеспечение АРТ и профилактической терапии котримоксазолом (ПТК) для ВИЧ-инфицированных пациентов. Основными мерами по снижению ТБ у ВИЧ-инфицированных людей являются регулярный скрининг на ТБ у пациентов, наблюдающихся по поводу ВИЧ-инфекции и проведение профилактической терапии изониазидом (ПТИ) для пациентов, не имеющих активной формы ТБ, и удовлетворяющих соответствующим критериям (по оценкам, это 50% новых пациентов, проходящих лечение ВИЧ-инфекции). •• В 2012 году произошло дальнейшее упрочение прогресса в реализации мер по борьбе с ТБ/ВИЧ. В глобальных масштабах 46% больных ТБ знали о своем ВИЧ-статусе (по сравнению с 40% в 2011 году). В регионе Африки, где самое высокое бремя ТБ/ВИЧ, 74% больных ТБ знали о своем ВИЧ-статусе (по сравнению с 69% в 2011 году). Если взять 41 страну с самым высоким бременем ТБ/ВИЧ, то более 85% больных ТБ знали свой ВИЧ-статус в 15-ти странах, и более 90% больных знали свой ВИЧ-статус в 7-ми из этих стран. •• Охват АРТ больных ТБ, зарегистрированных в  качестве ВИЧ-инфицированных, достиг 57% в 2012 году по сравнению с 49% в 2011 году. Как и в последние несколько лет около 80% ВИЧ-инфицированных больных ТБ получали ПТК. •• В 2012 году 4,1 млн человек, проходивших лечение ВИЧ-инфекции, как сообщалось, прошли скрининг на ТБ по сравнению с 3,5 млн человек в 2011 году. Из 1,6 млн человек, которые, как сообщалось, были подключены к  лечению ВИЧ-инфекции в 2012 году, 0,5 млн (31%) были обеспечены ПТИ.

•• В период после 2002 года четко документирован рост внутреннего и  международного донорского финансирования. Имеются возможности для дальнейшего увеличения внутреннего финансирования, особенно в странах БРИКС (Бразилия, Российская Федерация, Индия, Китай и Южно-Африканская Республика), на которые приходится почти 50% глобального числа случаев ТБ. •• По сообщениям НПТ, международное донорское финансирование составило в 2013 году 0,8 млрд долл. США, причем порядка трех четвертей из этой суммы поступило из Глобального фонда. Для ликвидации пробелов в финансировании в 2014 и 2015 годах требуется, по меньшей мере, 1,6 млрд долл. США. •• Международное донорское финансирование является жизненно важным во многих странах, и на его долю приходится более 50% общего финансирования в группе 17 СВБ, за исключением стран БРИКС, и во всех странах с низким уровнем доходов. В некоторых отдельных странах этот показатель еще выше.

Научные исследования и разработки Чтобы положить конец глобальной эпидемии ТБ, жизненно важное значение имеют новые средства диагностики ТБ, лекарства и вакцины. •• Более 50 компаний участвуют в разработке новых диагностических тестов. •• На завершающих этапах клинической разработки находятся 10 новых или перепрофилированных препаратов против ТБ. В конце 2012 года бедаквилин (bedaquiline) стал первым новым препаратом против ТБ, который был утвержден за прошедшие 40 лет. В июне 2013 года ВОЗ опубликовала временные руководящие указания относительно его использования при лечении МЛУ-ТБ. •• В настоящее время идет процесс подготовки 10 вакцин для профилактики ТБ и двух иммунотерапевтических вакцин. В начале 2013 года были опубликованы результаты этапа IIb концептуального исследования одной из профилактических вакцин-кандидатов. Хотя эффективность не превосходила вакцину БЦЖ (бацилла Кальметта-Герена) при индивидуальном применении, исследование продемонстрировало, что испытание новой вакцины против ТБ осуществимо в условиях высокого бремени ТБ. •• Для того, чтобы помочь положить конец глобальной эпидемии ТБ необходимы краткие, эффективные и легко переносимые курсы лечения латентной инфекции ТБ, диагностический тест для применения на месте оказания помощи, а также эффективная пост-экспозиционная вакцина.

Финансирование борьбы с ТБ Ключевыми факторами являются международное донорское финансирование и увеличение внутренних инвестиций. •• Из 7–8 млрд долл. США, необходимых ежегодно странам с низким и средним уровнем доходов в 2014 и 2015 годах, около двух третей из этой суммы требуется на выявление и лечение чувствительного к лекарственным препаратам ТБ; 20% — для лечения МЛУ-ТБ; 10% — для тестов быстрой диагностики и соответствующего укрепления лабораторий и 5% — для совместной деятельности по ТБ/ВИЧ.

1

По оценкам, среди ВИЧ-инфицированных людей в 2011 году умерли от туберкулеза 336 000 человек. Оценки за весь период с 1990 по 2012 годы относительно смерти от ТБ среди ВИЧ-инфицированных людей были обновлены в 2013 году с использованием программного обеспечения Спектрум (Spectrum), которое уже более 10 лет используется для подготовки оценок по бремени болезни, вызванной ВИЧ-инфекцией. В 2013 году в программном обеспечении Спектрум впервые появился модуль по туберкулезу, который предназначен для использования в странах в консультациях по оценкам бремени ВИЧ, проводимых раз в два года ЮНЭЙДС. В этот процесс была включена оценка числа больных ТБ, сочетанным с ВИЧ-инфекцией, а также числа смертей от туберкулеза среди ВИЧ-инфицированных. 2 22 СВБ являются: Афганистан, Бангладеш, Бразилия, Вьетнам, Демократическая Республика Конго, Зимбабве, Индия, Индонезия, Камбоджа, Кения, Китай, Мозамбик, Мьянма, Нигерия, Объединенная Республика Танзания, Пакистан, Российская Федерация, Таиланд, Уганда, Филиппины, Эфиопия и Южно-Африканская Республика.

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глава 1

Введение Вставка 1.1 Туберкулез (ТБ) остается основной глобальной проблемой здравоохранения. Он ежегодно наносит значительный ущерб здоровью миллионов людей в мире и занимает второе место среди причин смерти от инфекционных заболеваний после вируса иммунодефицита человека (ВИЧ). По последним оценкам, которые приводятся в настоящем докладе, в 2012 году 8,6 млн человек заболели туберкулезом и 1,3 млн человек умерли от этой инфекции (из них 0,3 млн человек умерли от туберкулеза, сочетанного с ВИЧ-инфекцией, и около 1,0 млн лиц с отрицательным ВИЧ-статусом). Большая часть случаев заболевания и смерти от туберкулеза приходится на мужское население, тем не менее, бремя болезни у женщин также является высоким. По оценочным данным, в 2012 году было 2,9 млн случаев заболеваний туберкулезом, из них 410 000 женщин умерли от этого заболевания; аналогичные показатели среди детей составили соответственно — около 530 000 случаев заболеваний и 74 000 смертей 1. Число смертей от ТБ является недопустимо высоким, поскольку их можно предотвратить при условии доступности лечебно-диагностической помощи. Стратегия лечения ТБ с помощью ускоренного курса химиотерапии препаратами первой линии, которая позволяет вылечить около 90% больных, является доступной уже в течение нескольких десятилетий. Спустя 20 лет после того, как в 1993 году ВОЗ провозгласила ТБ глобальной чрезвычайной ситуацией в общественном здравоохранении, несмотря на сохраняющиеся высокие показатели заболеваемости и смертности, удалось достичь существенных успехов. С 1990 года показатель смертности от ТБ в мире (число случаев смерти на 100 000 населения в год) снизился на 45% и в большинстве регионов мира снижаются показатели заболеваемости ТБ (число новых случаев на 100 000 населения в год). В течение 18 лет с момента запуска Всемирной организацией здравоохранения новой международной стратегии лечения и борьбы с ТБ в середине 1990-х годов (стратегии DOTS) и последующего глобального внедрения DOTS и его преемника Стратегии «Остановить ТБ» 2 (Вставка 1.2) за период с 1995 по 2012 годы, в общей сложности, 56 млн человек успешно прошли курс лечения от ТБ, что спасло около 22 млн жизней. Главной целью Стратегии «Остановить ТБ» является достижение глобальных целей к  2015  году (см. Вставку 1.2) для сокращения бремени ТБ. Цель тысячелетия в области развития, поставленная Организацией Объединенных Наций (ООН), заключается в том, чтобы добиться значительного сокращения заболеваемости туберкулезом к 2015 году (ЦТР 6.с). Помимо заболеваемости еще четыре других показателя по ТБ включены в рамки мониторинга ЦТР: уровень распространенности, смертности, выявления (отношение числа зарегистрированных случаев заболевания к числу случаев заболевания за тот же год, в процентах) и показатель эффективности лечения (доля больных туберкулезом, успешно завершивших курс лечения). 1

Основные факты о туберкулезе Туберкулез — инфекционное заболевание, вызываемое микобактериями туберкулеза Mycobacterium tuberculosis, обычно поражает легкие (туберкулез легких), но может также затрагивать и другие органы (внелегочный туберкулез). Инфекция, как правило, передается воздушно-капельным путем, когда больные туберкулезом легких выделяют бактерии, например, при кашле. В общем, у относительно небольшой части людей, инфицированных M. tuberculosis, может развиться туберкулез; однако вероятность развития активной формы болезни значительно выше у больных ВИЧ-инфекцией. ТБ также чаще встречается среди мужчин, чем у женщин и поражает главным образом экономически-активные группы взрослого населения. Наиболее распространенным методом диагностики туберкулеза во всем мире является микроскопия мазка мокроты (впервые применен более 100 лет назад), которая позволяет выявить бактерии в образцах мокроты, исследуемой под микроскопом. После недавних прорывов в области методов диагностики туберкулеза расширяется практика использования ускоренных молекулярных тестов для диагностики ТБ и ТБ с лекарственной устойчивостью, как подчеркивается в Главе 5 и Главе 8 настоящего доклада. В странах с развитой лабораторной службой ТБ также диагностируется с помощью культуральных методов (в настоящее время — референтный метод диагностики). При отсутствии лечения показатели смертности от туберкулеза высоки. В исследованиях по изучению естественного течения туберкулеза легких с бактериовыделением, подтверждаемым микроскопией мазка мокроты, и при отрицательном ВИЧстатусе около 70% больных умирали в течение 10 лет; а в группе больных с бактериовыделением, подтверждаемым посевом (но, при отрицательном результате бактериоскопии), 20% умирали в течение 10 лет a. Эффективные медикаментозные лечения были впервые разработаны в 1940-х годах. Наиболее эффективный противотуберкулезный препарат первой линии — рифампицин — стал доступен в 1960-х годах. В настоящее время для лечения новых случаев заболевания лекарственно-чувствительным туберкулезом (ЛУ ТБ) рекомендуют применять шестимесячный курс химиотерапии, включающий четыре препарата первой линии: изониазид, рифампицин, этамбутол и пиразинамид. Показатель успешности лечения впервые выявленных больных, равный 85% или более, регулярно сообщается в отчетах, представляемых государствами-членами в ВОЗ (Глава 3). Лечение туберкулеза с множественной лекарственной устойчивостью (МЛУ-ТБ), которая определяется, как устойчивость к изониазиду и рифампицину (два наиболее эффективных противотуберкулезных препарата), является более длительным и требует более дорогих и более токсичных препаратов. Согласно рекомендациям ВОЗ лечение больных МЛУ-ТБ в среднем продолжается 20 месяцев, и показатели успешности лечения гораздо ниже (Глава 4). Впервые, за последние четыре десятилетия, появились новые противотуберкулезные препараты и новые режимы лечения, которые проверяются в клинических испытаниях, как описано в Главе 8. Разработано несколько противотуберкулезных вакцин, которые проходят I и II этапы клинических испытаний (Глава 8). Однако на настоящий момент не существует эффективной вакцины, которая могла бы предотвратить заболевание ТБ у взрослых. a

Tiemersma EW et al. Natural history of tuberculosis: duration and fatality of untreated pulmonary tuberculosis in HIV-negative patients: A systematic review. PLoS ONE, 2011, 6(4): e17601.

В расчетное число случаев смерти от ТБ среди детей не включаются случаи смерти от ТБ, сочетанного с ВИЧ-инфекцией, расчетные данные по последним еще не получены. Дополнительная информация представлена в Главе 2. 2 Raviglione M, Uplekar M. WHO’s new Stop TB strategy. The Lancet, 2006, 367: 952–5.

Доклад о глобальной борьбе с туберкулезом 2013

1

Вставка 1.2

Краткий обзор Стратегии «Остановить ТБ» Стратегия «Остановить ТБ» ВИДЕНИЕ ЦЕЛЬ ЗАДАЧИ Мир, свободный от туберкулеза Существенно сократить к 2015 году глобальное бремя туберкулеза в соответствии с Целями тысячелетия в области развития (ЦТР) и задачами Партнерства «Остановить туберкулез» n Обеспечить всем больным туберкулезом всеобщий и равный доступ к качественной медицинской помощи n Уменьшить социально-экономическое бремя и человеческие страдания, связанные с туберкулезом n Защитить уязвимые группы населения от туберкулеза, в том числе от туберкулеза, сочетанного с ВИЧ-инфекцией и лекарственно-устойчивого туберкулеза (ЛУ ТБ) n Поддерживать разработку новых подходов и методов борьбы с туберкулезом и создавать возможности для их своевременного и эффективного использования n Способствовать защите прав человека в области профилактики, лечения и борьбы с туберкулезом Целевые показатели n ЦТР 6, Задача 6.с: к 2015 году остановить рост и положить начало снижению заболеваемости туберкулезом n Задачи, связанные с ЦТР и одобренные Партнерством «Остановить туберкулез» – к 2015  году: снизить на 50% распространенность и смертность от туберкулеза по сравнению с показателями 1990 года – к 2050  году: ликвидировать туберкулез как проблему общественного здравоохранения (менее одного случая заболевания на миллион населения в год)

КОМПОНЕНТЫ СТРАТЕГИИ 1. Продолжение распространения и внедрения высококачественной стратегии DOTS a. Политическая приверженность в сочетании с адекватным и устойчивым финансированием b. Раннее выявление и диагностика случаев заболевания с помощью бактериологических исследований гарантированного качества c. Стандартная контролируемая химиотерапия в сочетании с оказанием поддержки пациентам d. Эффективная система управления и снабжения лекарственными средствами e. Мониторинг и оценка эффективности противотуберкулезных мероприятий 2. Борьба с ТБ-ВИЧ, МЛУ-ТБ с учетом потребностей больных из малоимущих и уязвимых групп населения a. Расширение совместных мероприятий по борьбе с туберкулезом и ВИЧ-инфекцией b. Расширение мероприятий по профилактике и борьбе с туберкулезом с множественной лекарственной устойчивостью возбудителя (МЛУ-ТБ) c. Принятие во внимание потребностей лиц, находившихся в контакте с больными туберкулезом, а также из малоимущих и уязвимых групп населения 3. Содействие укреплению системы здравоохранения на основе развития первичной медико-санитарной помощи a. Оказание помощи в совершенствовании политики здравоохранения, развитии кадровых ресурсов, финансировании, снабжении, оказании услуг и информационном обеспечении b. Усиление мер инфекционного контроля в учреждениях здравоохранения, других местах массового нахождения людей и в местах проживания c. Модернизация лабораторных сетей и внедрение стратегии практического подхода к здоровью легких (ППЗЛ) d. Адаптация подходов, успешно применяемых в других областях здравоохранения, и активизация действий, направленных на социальные детерминанты здоровья 4. Привлечение всех поставщиков медицинских услуг a. Обеспечение участия всех государственных, добровольных, корпоративных и частных поставщиков услуг с использованием смешанных государственно-частных структур (ГЧС) b. Содействие применению Международных стандартов оказания медицинской помощи больным туберкулезом (ISTC) 5. Расширение прав и возможностей больных туберкулезом и общественных организаций через партнерское сотрудничество a. Разъяснительная деятельность, информирование и социальная мобилизация b. Поощрение участия общества в мероприятиях по лечению и профилактике туберкулеза, пропаганде здорового образа жизни c. Содействие в использовании Хартии пациентов по медицинской помощи больным туберкулезом 6. Обеспечение и развитие научных исследований a. Проведение прикладных исследований в рамках программы борьбы с туберкулезом b. Поддержка и участие в проведении научных исследований, направленных на разработку новых диагностических средств, лекарственных препаратов и вакцин

2

Доклад о глобальной борьбе с туберкулезом 2013

рисунок 1.1

Семнадцать ежегодных докладов ВОЗ о глобальной борьбе с туберкулезом, 1997–2012 годы 1997 год: Первый доклад: Эпидемиология и надзор 2002 год: Дополнительное финансирование и стратегия для 22 стран с высоким бременем туберкулеза (СВБ)

2003 год: Финансирование и стратегия (все страны)

Июль 2009 года: Введение сбора данных в режиме онлайн Декабрь 2009 года: Краткая обновленная информация к докладу 2009 года в процессе перехода к более раннему предоставлению данных и к публикации доклада

Партнерство «Остановить ТБ» приняло цели ЦТР как руководство к действию и дополнительно установило глобальные цели по сокращению вдвое показателей распространенности ТБ и смертности от ТБ к 2015 году, в сравнении с уровнем 1990 года. Масштабы работы по осуществлению мероприятий, включенных в Стратегию «Остановить ТБ», которые должны быть осуществлены для достижения целей 2015 года по сокращению бремени болезни и связанные с ними финансовые потребности, были описаны в Глобальных планах, разработанных партнерством «Остановить ТБ». Последний план охватывает период с 2011 по 2015 годы и расходы по его реализации оцениваются в 47 млрд долл. США 1. Все большее значение приобретает необходимость разработки рамочных программ, в пределах которых будет продолжена работа после 2015 года, намеченного как рубеж для достижения ЦТР. Для подготовки рекомендаций по содержанию рамочных программ развития после 2015 года, включая возможные цели и задачи, Генеральным секретарем ООН была учреждена группа экспертов высокого уровня, которая в июне 2013 года предоста2. Для достижения одной из двенадцати вила ООН свой доклад  предложенных целей на 2030 год «Обеспечение здоровой жизни» предлагается задача — «Уменьшить бремя болезни от ВИЧ/ СПИДа, туберкулеза, малярии, забытых тропических болезней и приоритетных неинфекционных заболеваний». Наиболее важные темы доклада основываются на необходимости достижения ЦТР и справедливости, а в отношении здоровья людей особенно подчеркнута важность стабильного прогресса в обеспечении всеобщего охвата медицинской помощью (ВОМП). В соответствии с разработкой Рамочной программы развития после 2015 года и в ответ на просьбу государств-членов ВОЗ, Всемирная организация здравоохранения в 2012 году начала процесс разработки глобальной стратегии по ТБ на период после 2015 года. После серии консультаций, состоявшихся с июня 2012 года по июль 2013 года, в проект стратегии была включена цель о ликвидации глобальной эпидемии туберкулеза к 2035 году, и соответствующие глобальные задачи по значительному сокращению случаев заболевания и смерти от ТБ к 2035 году, а также определены промежуточные ориентиры на 2020, 2025 и 2030 годы.

The Global Plan to Stop TB, 2011–2015. Geneva, World Health Organization, 2010 (WHO/HTM/STB/2010.2). Доступно на: http://www.stoptb.org/assets/documents/global/plan/TB_ GlobalPlanToStopTB2011-2015.pdf 2 http://www.un.org/sg/management/beyond2015.shtml 1

Достижение предложенных целей основано на трех стратегических принципах: комплексный, пациенто-ориентированный подход к профилактике и лечению туберкулеза; решительная политическая линия и системы поддержки; и активные научные исследования и инновации. Ожидается, что стратегия будет рассмотрена Исполнительным комитетом ВОЗ в январе 2014 года и вынесена на обсуждение на Всемирной ассамблее здравоохранения в мае 2014 года. В контексте глобальных стратегий и задач по туберкулезу ВОЗ публикует Доклад о глобальной борьбе с туберкулезом ежегодно, начиная с 1997 года (Рисунок 1.1). Основная цель доклада заключается в том, чтобы обеспечить всестороннюю и обновленную оценку эпидемиологической ситуации по туберкулезу и отразить прогресс в области профилактики, диагностики и лечения заболевания на глобальном, региональном и национальном уровнях, основываясь в первую очередь на данных, которые представляются странами и территориями ВОЗ в ежегодных циклах глобального сбора данных по ТБ (Вставка 1.3). Настоящий Доклад о глобальной борьбе с туберкулезом за 2013 год является восемнадцатым в серии ежегодных докладов и содержит данные, которые предоставили в общей сложности 197 стран и территорий, включая 178 государств-членов ВОЗ, которые по оценкам несут бремя более 99% случаев заболевания ТБ в мире (Таблица 1.1). До конца 2015 года остается немногим более двух лет, поэтому особенностью этого Глобального доклада 2013 является то, что он сопровождается дополнением, под названием «Обратный отсчет до 2015 года» (Вставка 1.4). Основная часть доклада содержит семь глав. Каждая глава представляет собой самостоятельное исследование, но ссылки на другие главы указаны там, где это необходимо. Глава 2 содержит последние оценочные данные бремени заболевания ТБ и динамику достижения задач, установленных на 2015 год, на глобальном, региональном и национальном уровнях. Особое внимание уделяется данным по ТБ у женщин и детей. На основе новых аналитических исследований и моделирования процессов в 2013 году в главе также приведены новые оценки числа случаев заболевания и смерти от МЛУ-ТБ и от ТБ, сочетанного с ВИЧ-инфекцией. Описаны самые последние работы по совершенствованию способов измерения количества случаев ТБ и случаев смерти на национальном уровне, под руководством и при поддержке Глобальной целевой группы ВОЗ по измерению воздействия ТБ. В Главе 3 представлены данные о числе случаев заболеваемости туберкулезом, зарегистрированных НПТ и включенных в отчетность для ВОЗ, а также о результатах их лечения, в том числе с разбивкой случаев заболевания по типу, полу и возрасту. В данной главе подробно освещены последние успехи 3

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 1.3

Данные, собранные ВОЗ в 2013 году в рамках глобального сбора данных по ТБ Требовалось представить следующие данные: число зарегистрированных случаев заболевания ТБ и результаты лечения с разбивкой по формам ТБ, по возрасту, полу и ВИЧ-статусу; общие сведения о доступности услуг по диагностике и лечению туберкулеза; о сети лабораторий, участвующих в диагностике туберкулеза; о фармацевтическом менеджменте; о мониторинге и оценке; об эпиднадзоре и исследованиях по мониторингу ТБ с лекарственной устойчивостью; о лечении ТБ с лекарственной устойчивостью; о комплексных мероприятиях по лечению ТБ, сочетанного с ВИЧинфекцией; об инфекционном контроле; об участии медицинских организаций всех форм собственности в противотуберкулезных мероприятиях; о бюджетах национальных программ по борьбе с туберкулезом (НПТ) в 2013 и 2014 годах; об использовании общих медицинских услуг, оказанных в учреждениях первичной медико-санитарной помощи (число госпитализаций и амбулаторных посещений) во время лечения; и о расходах НПТ в 2012 году. Сокращенная версия Интернет-вопросника была использована для стран с высоким уровнем доходов (то есть стран с валовым национальным доходом (ВНД) на душу населения > 12 616 долл. США в 2012 году по определению Всемирного Банка) a и стран с низким уровнем заболеваемости ТБ (по определению, страны с уровнем заболеваемости менее 20 случаев на 100 000 населения или менее 10 случаев в целом). Страны представили данные, с помощью онлайн веб-системы (www.stoptb.org/tme). Система была открыта для отчетности 14 марта с датой окончания предоставления данных 15 мая для всех регионов ВОЗ, за исключением региона Северной и Южной Америки (29 мая) и Европейского региона (30 мая). Страны Европейского Союза (ЕС) представляют данные о зарегистрированных случаях заболевания через систему, управляемую Европейским центром по профилактике и контролю заболеваний (ECDC). Данные из системы ECDC были загружены в онлайн систему ВОЗ. Данные были проанализированы и, при необходимости, обсуждены с респондентами группой экспертов ВОЗ (из штаб-квартиры и региональных отделений) и Глобального фонда по борьбе со СПИДом, туберкулезом и малярией (Глобальный фонд). Респондентам также было предложено провести проверку правильности данных с использованием ряда встроенных программ в режиме реального времени и получить краткий отчет о явных несоответствиях или неточностях (подобный отчет можно в любое время составить в онлайн системе). После исправления и обновления данных по странам, они были использованы для основной части настоящего доклада. Эти данные по состоянию на июль 2013 года. Приложение 4 b было подготовлено к 1 октября, однако, к этому времени несколько европейских стран сообщили дополнительные данные c. Кроме данных, собранных с помощью стандартного вопросника по ТБ, были собраны данные о скрининге на туберкулез среди больных ВИЧинфекцией, а также данные о проведении профилактической терапии изониазидом (ПТИ) при отсутствии признаков активного туберкулеза. Эти данные собирались Департаментом по борьбе с ВИЧ-инфекцией ВОЗ и Объединенной программой Организации Объединенных Наций по ВИЧ/ СПИДу (ЮНЭЙДС). Совместно была осуществлена проверка данных и они были внесены в глобальную базу данных о ТБ. a. c. b.

http://data.worldbank.org/about/country-classifications http://www.who.int/tb/country/data/download По этой причине могут быть незначительные расхождения между основной частью доклада и Приложением 4

Таблица 1.1

Информация о глобальном сборе данных по туберкулезу в 2013 году Страны и территории Количество стран Регион ВОЗ или группа стран Количество стран, представивших данные Государства-члены ВОЗ Количество стран Количество стран, представивших данные

AFR EMR EUR a AMR SEAR WPR Страны с высоким бременем туберкулеза (СВБ) b Во всем мире a

46 23 54 46 11 36 22 216

45 23 42 46 11 30 22 197

46 22 53 35 11 27 22 194

45 22 41 35 11 24 22 178

Странами, не представившими данные в установленные сроки, были главным образом, страны Западной Европы с низким уровнем заболеваемости. b Странами с высоким бременем туберкулеза (СВБ) являются: Афганистан, Бангладеш, Бразилия, Вьетнам, Демократическая Республика Конго, Зимбабве, Индия, Индонезия, Камбоджа, Кения, Китай, Мозамбик, Мьянма, Нигерия, Объединенная Республика Танзания, Пакистан, Российская Федерация, Таиланд, Уганда, Филиппины, Эфиопия и Южно-Африканская Республика.

в регистрации случаев ТБ, выявленных в частных медицинских организациях (путем привлечения крупных больниц в пяти странах), а также за счет участия в выявлении, регистрации и лечении ТБ местных медицинских работников и добровольцев в 13 странах, и обращается внимание на исключительно высокий показатель регистрируемой заболеваемости в тюрьмах в некоторых частях Европейского региона ВОЗ. Глава 4 посвящена проблеме лекарственно устойчивого ТБ. В первой части главы говорится об успехах эпиднадзора ТБ с лекарственной устойчивостью и связанных с ним показателях — оценочное число случаев и доли больных туберкулезом с МЛУ-ТБ и широкой лекарственной устойчивостью (ШЛУ-ТБ). Во второй части главы содержатся и обсуждаются последние 4

данные по программным мерам борьбы с МЛУ-ТБ, включая охват обследованием путем теста на лекарственную чувствительность (ТЛЧ) новых и ранее пролеченных больных туберкулезом, приводится число выявленных случаев с МЛУ-ТБ, число больных МЛУ-ТБ, взятых на лечение, и описаны результаты их лечения. Глава 5 посвящена диагностике туберкулеза и укреплению лабораторий, в ней рассматриваются три темы. Это разработка политических решений в период с середины 2012 года и до середины 2013 года, статус лабораторного потенциала и внедрение Руководства ВОЗ в национальную политику в 2012 году. Далее описаны последние успехи в укреплении лабораторий и связанных с ними диагностических возможностей. В главу включены последние данные об использовании современной

Доклад о глобальной борьбе с туберкулезом 2013

молекулярной тест-системы Xpert MTB/RIF, рекомендованной в 2010 году, и информация о двух многонациональных проектах (EXPAND-ТБ и TBXpert). Глава  6 содержит самые последние данные об успехах, достигнутых в осуществлении совместных мероприятий по ТБ/ ВИЧ для направления совместных усилий на борьбу с эпидемией туберкулеза и ВИЧ. К ним относится тестирование на ВИЧ для больных туберкулезом, предоставление антиретровирусной терапии (АРТ) для ВИЧ-инфицированных больных туберкулезом, активное проведение скрининга на туберкулез среди людей, живущих с ВИЧ и лечение профилактической терапией изониазидом (ПТИ) для тех, кто не имеет активной формы туберкулеза. Глава 7 содержит оценку финансирования, необходимого для лечения и борьбы с туберкулезом. Потребности пополнения финансирования Глобального Фонда, необходимые для полноценного реагирования на глобальную эпидемию туберкулеза до 2015 года, были обновлены в начале 2013 года в рамках подготовительной работы и представлены впервые. Затем суммировались основные выводы из исследования долгосрочных тенденций (2002–2011 годов) с использованием данных, представляемых в ВОЗ путем ежегодного цикла сбора данных и недавно опубликованных в журнале The Lancet Global Health, с последующим подробным анализом новых данных, поступивших в 2013 году. В Главе 8 обсуждаются исследования и разработки для новых методов диагностики туберкулеза, лекарств и вакцин. После нескольких лет застоя в последнее десятилетие достигнут значительный прогресс и приводится описание хода развития исследований по состоянию на середину 2013 года. Доклад также содержит четыре приложения. Приложение 1 объясняет методы, используемые для оценки бремени ТБ. Приложение 2 1 содержит обзоры по 22 странам с высоким бременем болезни, на которые в совокупности приходится около 80% случаев заболевания ТБ в мире (данные по всем странам доступны онлайн 2). Приложение 3 3 содержит региональные данные. Приложение 4 4 состоит из кратких таблиц, которые представляют данные о ключевых показателях для отдельных стран мира и шести регионов ВОЗ.

Вставка 1.4

Специальное приложение «Обратный отсчет до 2015 года» ЦТР были установлены Организацией Объединенных Наций на рубеже XXI века на 2015 год (www.un.org/millenniumgoals). Одобренные всеми странами и предназначенные стимулировать прогресс во всем мире, ЦТР были в центре работы по развитию, как на международном, так и на национальном уровнях, более десяти лет. ТБ был частью ЦТР 6. Помимо целей и показателей по ТБ, которые включены в ЦТР, в рамках Глобального плана «Остановить ТБ на 2011–2015 годы» были установлены целевые показатели для мониторинга решения проблем, специфических для эпидемии МЛУ-ТБ и ТБ/ВИЧ, на период до 2015 года. До конца 2015 года остается немногим более двух лет, поэтому особенностью этого Глобального доклада 2013 является то, что он сопровождается приложением под названием «Обратный отсчет до 2015 года». В приложении представлены промежуточные данные по достижению показателей, установленных к 2015 году в рамках ЦТР, и показателей, касающихся мероприятий по борьбе с ТБ/ВИЧ и МЛУ-ТБ. Главные усилия должны быть направлены на ускорение темпов достижения или превышение этих целей. Краткие обзоры представлены на глобальном и региональном уровнях и по 22 СВБ, на которые приходится около 80% случаев заболевания ТБ в мире и которым уделялось самое большое внимание на глобальном уровне с 2000 года. Эти краткие обзоры основаны на данных, представленных в основных главах доклада и приложениях, они дополняются рекомендациями из последних оценок программ и опубликованной литературы, а также материалами дискуссии с экспертами на глобальном, региональном и национальном уровнях.

1,3,4 2

http://www.who.int/tb/country/data/download — см. примеч. на стр. iii www.who.int/tb/data

Доклад о глобальной борьбе с туберкулезом 2013

5

Глава 2

Бремя туберкулеза Основные факты и выводы ■■ Глобальное бремя туберкулеза остается крайне тяжелым. В 2012 году было зарегистрировано 8,6 млн новых случаев ТБ и 1,3 млн человек умерли от этой болезни (940 000 случаев смерти составили ВИЧ-отрицательные больные и 320 000 — больные ВИЧ-инфекцией). Из числа умерших, по оценкам 170 000 случаев смерти приходится на пациентов с МЛУ-ТБ, что составляет сравнительно большую долю от 450 000 новых случаев заболевания МЛУ-ТБ. ■■ Несмотря на то, что число случаев заболевания и смерти от ТБ остается неоправданно высоким для излечимого, в большинстве случаев, заболевания, наметился значительный прогресс в реализации глобальных целей по сокращению бремени болезни. Цель тысячелетия в области развития (ЦТР) — к 2015 году «остановить и обратить вспять заболеваемость ТБ» достигнута; заболеваемость ТБ последовательно снижается во всем мире на протяжении последних лет (на 2% в год в 2012 году). В глобальном масштабе показатели смертности от ТБ снизились на 45% с 1990 года, и скоро будет достигнута цель Партнерства «Остановить ТБ» по сокращению вдвое смертности к 2015 году. Показатели смертности и заболеваемости снижаются во всех шести регионах ВОЗ и в большинстве из 22 СВБ, в которых регистрируется более 80% всех случаев ТБ в мире. ■■ В этом году впервые было получено оценочное число случаев смерти от ТБ среди больных ВИЧ-инфекцией с помощью заложенной модели в программу Spectrum, разработанную ЮНЭЙДС. В связи с получением новых данных были пересмотрены ранее опубликованные оценочные данные за период с 1990 по 2011 годы. Оценочная доля случаев ТБ у больных ВИЧ-инфекцией осталась на прежнем уровне и составила 13% в мире в 2012 году. ■■ Несмотря на то, что большинство случаев заболевания и смерти от ТБ приходится на мужчин, бремя болезни высоко и среди женщин. В 2012 году, по оценочным данным, около 410 000 женщин умерли от ТБ (250 000 среди них — ВИЧотрицательные и 160 000 — больные ВИЧ-инфекцией). Расчеты свидетельствуют о 74 000 случаях смерти от ТБ среди ВИЧ-отрицательных детей (расчеты по числу случаев смерти среди детей больных ВИЧ-инфекцией пока недоступны). ■■ В регионе Юго-Восточной Азии и в регионе Западной части Тихого океана насчитывалось 58% всех случаев ТБ в мире в 2012 году. На регион Африки приходилась приблизительно одна четверть всех случаев и самый высокий показатель заболеваемости (в среднем 255 случаев на 100 000, что более, чем вдвое превосходит средний мировой уровень — 122 случая). На Индию и Китай приходилось самое большое число случаев (26% и 12% от мирового показателя соответственно). В Свазиленде и Южно-Африканской Республике самые высокие оценочные показатели заболеваемости из расчета на душу населения (около 1 нового случая на каждые 100 человек ежегодно). ■■ Продолжает повышаться качество данных и охват населения системой эпиднадзора для расчета бремени ТБ. В 2012 году начали использовать данные системы записей актов гражданского состояния (ЗАГС) для оценки смертности от ТБ в 121 стране (в 2008 году это были только 3 страны); беспрецедентный успех наблюдался в деле осуществления национальных исследований по изучению распространенности ТБ после 2008 года; расширились меры по совершенствованию систем мониторинга заболеваемости ТБ путем укрепления информационных систем здравоохранения и проведения исследований по изучению полноты регистрации для оценки количества диагностированных, но не зарегистрированных в системе эпиднадзора случаев ТБ. ■■ В 2012 году было проведено пять национальных исследований распространенности ТБ (в Гамбии, Нигерии, Объединенной Республике Танзании, Руанде и Таиланде) и еще пять подобных исследований будут завершены в 2013 году (в Гане, Замбии, Индонезии, Малави и Судане). Результаты этих исследований дают возможность непосредственно оценить бремя болезни; часто впервые в истории, они будут использоваться для уточнения оценочных данных по бремени туберкулеза по мере получения результатов. Они также дают обширный материал для разработки политики и стратегии программ.

Бремя туберкулеза можно измерить заболеваемостью (определяется, как число новых случаев и рецидивов ТБ, возникающих за определенный период времени, обычно за один год), распространенностью (определяется, как число случаев заболевания ТБ в определенный момент времени) и смертностью (определяется, как число случаев смерти от ТБ за определенный период времени, обычно за один год). В данной главе представлены расчетные данные по заболеваемости, распространенности и смертности от ТБ (абсолютные числа и показатели) за период с 1990 по 2012 годы и прогнозы (по распространенности и смертности) до 2015 года (в Разделах 2.1–2.3). Эти данные используются для оценки темпов достижения глобальных задач по сокращению бремени ТБ до 2015 года: заболеваемость должна начать снижаться (ЦТР 6.c), а распространенность и смертность должны сократиться вдвое к 2015 году по сравнению с показателями 1990 года (Вставка 1.2 в Главе 1). Ключевые моменты использованных методик проведения оценок приводятся в начале каждого раздела 1. Оценки числа случаев ТБ, сочетанного с ВИЧ-инфекцией, МЛУ-ТБ и смертности от МЛУ-ТБ и ТБ с разделением по ВИЧ-статусу включены в соответствующие разделы. Расчеты произведены на глобальном уровне, для шести регионов ВОЗ, а также на национальном уровне, причем особое внимание уделено 22 СВБ. В качестве ответа на растущую потребность в данных и глобальное внимание к проблеме, особый акцент сделан на оценку бремени ТБ среди женщин и детей. Обновленные источники данных и методы расчетов бремени ТБ и их сравнение с опубликованными в 2012 году методами приводятся во Вставке 2.1. Существует некоторая неопределенность во всех оценках бремени ТБ. Раздел 2.4 содержит описание усилий по совершенствованию расчетов этого бремени, которые предпринимаются в рамках работы Глобальной целевой группы ВОЗ по оценке воздействия ТБ. Подводятся итоги новейших и беспрецедентных общенациональных исследований по изучению распространенности ТБ и описываются действия по усилению эпиднадзора за случаями заболевания и смерти от ТБ через системы регистрации случаев и системы ЗАГС.

2.1 Заболеваемость туберкулезом Изучение заболеваемости ТБ на национальном уровне никогда не проводилось в связи тем, что это является долгосрочным, высокозатратным 1

Подробное описание приводится в Приложении 1.

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Вставка 2.1

Уточнение методов оценки бремени туберкулеза, использованных в настоящем докладе, и ожидаемые изменения методики в ближайшей перспективе Ежегодно появляются новые данные по оценке бремени туберкулеза. Периодически разрабатываются новые подходы к использованию имеющихся данных. Эта вставка содержит краткое описание изменений, которые были сделаны в 2013 году. В ряде стран завершаются исследования по изучению распространенности туберкулеза, по результатам которых, будет произведено уточнение оценочных показателей.

Уточненные данные в настоящем докладе 1. Оценки бремени туберкулеза у больных ВИЧ-инфекцией В 2013 году оценочные показатели заболеваемости ТБ и смертности от ТБ среди больных ВИЧ-инфекцией были впервые рассчитаны при помощи программного обеспечения Spectrum a. Spectrum используется более десяти лет для оценки бремени ВИЧ-инфекции, моделирования эпидемии ВИЧ-инфекции и оценки потенциального воздействия принимаемых мер. Модуль по ТБ был разработан в период с 2012 по 2013 годы на основе сотрудничества между Futures Institute, Консорциумом по моделированию и анализу эпидемиологии туберкулеза (TB-MAC), ЮНЭЙДС и ВОЗ. Данная методика была апробирована в ходе работы двух региональных семинаров, которые состоялись в Йоханнесбурге, ЮжноАфриканская Республика (март 2013 года) и далее на семинаре для стран Западной Африки. Математические методы и данные, использованные для моделирования в Spectrum, описаны в Приложении 1. Предполагается, что модуль ТБ будет применяться для определения прогноза будущего развития эпидемии туберкулеза и потенциального воздействия отдельных мероприятий на этот процесс, опираясь на имеющиеся данные оценки бремени ТБ, проведенной ВОЗ. Уточненные оценочные показатели заболеваемости туберкулезом среди больных ВИЧ-инфекцией, опубликованные в настоящем докладе, как правило, вполне согласуются с ранее опубликованными оценками, особенно для стран с генерализованными эпидемиями и действенными системами эпиднадзора за ТБ/ ВИЧ. Серия уточненных оценочных показателей смертности от ТБ больных ВИЧ-инфекцией в мире в целом и для региона Африки ниже оценочных показателей, опубликованных в 2012 году. В результате использования программы Spectrum впервые стали доступными оценочные показатели смертности от ТБ среди больных ВИЧ-инфекцией в разрезе отдельных стран, которые полностью согласуются с оценкой общей смертности от ВИЧ-инфекции. Данные содержатся в Приложении 2 b и в интернете онлайн, в разделе, описывающем ситуацию в отдельных странах (country profiles). 2. МЛУ-ТБ: смертность и заболеваемость Последние оценочные показатели заболеваемости и смертности от МЛУ-ТБ были рассчитаны в 2008 году и опубликованы в Докладе ВОЗ об эпидемии МЛУ-ТБ в 2010 году. Подготовка систематического обзора публикаций по смертности, связанной с МЛУ-ТБ, была выполнена по поручению ВОЗ в 2013 году. Результаты были использованы для расчета глобальных показателей заболеваемости и смертности от МЛУ-ТБ в 2012 году. Оценочный a

показатель смертности от МЛУ-ТБ несколько выше, чем полученный ранее показатель, но доверительный интервал в значительной степени перекрывает предыдущий. Вновь рассчитанный оценочный показатель заболеваемости МЛУ-ТБ находится на уровне полученного ранее показателя. 3. Новые отчетные данные Наблюдаются лишь небольшие изменения в оценочных показателях заболеваемости, смертности и распространенности ТБ для многих стран, которые связаны с поступлением данных из системы ЗАГС, представленных в ВОЗ в период с середины 2012 года до середины 2013 года; произведено уточнение оценочного числа случаев смерти (общая смертность); уточнены данные оценки бремени ВИЧ-ассоциированного ТБ и по вновь регистрируемой заболеваемости ТБ, а также внесены исправления в ранее опубликованные данные. В большинстве случаев новые данные находятся в рамках доверительных интервалов ранее опубликованных оценочных данных бремени ТБ и сохраняются тенденции временных ́ рядов. Вновь поступившие данные являются основанием для внесения небольших изменений в оценочные числа случаев смерти от ТБ среди женщин и детей. 4. Углубленные эпидемиологические исследования В январе 2013 года, в тесном взаимодействии с национальной противотуберкулезной программой и другими заинтересованными сторонами, были уточнены оценочные показатели бремени ТБ для Вьетнама. В результате этой работы изменились оценочные показатели и тенденции в заболеваемости, распространенности и смертности от ТБ по сравнению с соответствующими данными, опубликованными в Докладе о глобальной борьбе с туберкулезом за 2012 год. Уточнение оценочных показателей стало возможным в связи с получением результатов исследования распространенности туберкулеза с учетом влияния совершенствования системы регистрации случаев туберкулеза НПТ за счет включения случаев, выявленных в частном и пенитенциарном секторах здравоохранения, а также дополнительного анализа более широкого воздействия на бремя ТБ таких факторов как: экономический рост, эффективность системы здравоохранения и охват медицинским страхованием. 5. Включение новых зарегистрированных больных с неизвестным анамнезом заболевания в оценочный показатель заболеваемости В предыдущие годы пациенты, регистрируемые с диагнозом ТБ, при отсутствии информации в отношении лечения туберкулеза, не учитывались при расчете заболеваемости (показатель заболеваемости рассчитывался путем сложения числа впервые выявленных

случаев и рецидивов). В настоящем Докладе регистрируемые случаи туберкулеза у лиц с неизвестным анамнезом в отношении лечения туберкулеза, учитываются как впервые выявленные больные. Это изменение оправдано по двум причинам: первая — в странах, где имеются проблемы с ведением медицинской документации, подавляющее большинство таких случаев являются новыми случаями или рецидивами; вторая — ВОЗ получила ряд запросов от НПТ (или аналогичных структур) включать всех пациентов без документально оформленной истории болезни в число впервые выявленных больных и рецидивов для исключения вероятности занижения истинного бремени ТБ. Это изменение отразится лишь на нескольких странах, большинство из которых расположено в Западной Европе.

изменения, ожидаемые в ближайшее время Ожидается, что в нескольких странах, которые недавно завершили, или завершат в ближайшее время национальные исследования по изучению распространенности ТБ, появятся обновленные данные для оценки бремени туберкулеза. К ним относятся пять стран с высоким бременем ТБ (СВБ): Индонезия, Нигерия, Объединенная Республика Танзания, Пакистан, и Таиланд. В дополнительный список вошли Гамбия и Руанда, в которых исследования завершены в 2012 году, а также Гана, где работа началась в марте 2013 года. В Пакистане в 2012 году, наряду с исследованием по изучению распространенности туберкулеза, завершено исследование по изучению полноты регистрации случаев ТБ (см. также Раздел 2.4); углубленное изучение эпидемической ситуации было проведено в Таиланде в августе 2013 года. В штаб-квартире ВОЗ в ноябре 2013 года проведен семинар для всестороннего анализа и обсуждения полученных данных с участием представителей шести стран, завершивших исследование по изучению распространенности ТБ до июля 2013 года (Гамбия, Нигерия, Объединенная Республика Танзания, Пакистан, Руанда и Таиланд), и их технических партнеров. По окончании этого семинара можно уточнить оценочные показатели бремени ТБ. Эти данные и результаты исследования распространенности ТБ будут размещены в интернете онлайн в разделе, описывающем ситуацию в отдельных странах. В 2014 году Глобальная целевая группа ВОЗ по оценке воздействия ТБ будет проводить тщательное изучение используемых в настоящее время методик проведения эпидемиологической оценки и моделирования, которые применяются для оценки бремени ТБ. Рекомендации этой группы могут потребовать уточнения некоторых данных в Докладе о глобальной борьбе с ТБ за 2014 год.

http://www.futuresinstitute.org/spectrum.aspx

b. http://www.who.int/tb/country/data/download — см. примеч. на стр. iii

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и трудоемким мероприятием с массовым осмотром населения. Регистрируемая заболеваемость туберкулезом является надежным косвенным показателем истинной заболеваемости в странах с надежной системой эпиднадзора, гарантирующей практически полную регистрацию выявленных больных, а качество и охват медицинской помощью таковы, что можно предположить минимальный уровень гиподиагностики заболевания. Во многих странах, где эти критерии еще не соблюдены, заболеваемость туберкулезом может быть оценена с помощью исследования по изучению полноты регистрации туберкулеза, в рамках которого оценивается недоучет больных в сочетании с методом первичного и повторного обследования определенной выборки для оценки масштабов гиподиагностики, при соблюдении определенных условий 1. До настоящего времени, такие исследования были проведены лишь в нескольких странах, а именно: в Египте, Ираке и Йемене (см. Раздел 2.4). Конечной целью является возможность рассчитать показатель заболеваемости ТБ, непосредственно исходя из показателя регистрируемой заболеваемости во всех странах. Для достижения этого требуется не только укрепление самой системы эпиднадзора, но и наличие возможности количественного учета случаев туберкулеза, не зарегистрированных в системе эпиднадзора, а также обеспечение всеобщего доступа к медицинской помощи. В Контрольном списке для систем эпиднадзора за ТБ, разработанном Глобальной целевой группой ВОЗ по оценке воздействия ТБ, определены необходимые для соблюдения стандарты по заполнению извещений о случае заболевания, позволяющие проводить прямую оценку заболеваемости ТБ по

данным регистрируемой заболеваемости из системы эпиднадзора (подробнее в Разделе 2.4). В настоящее время, для большинства стран, оценка показателя заболеваемости рассчитывается на основании данных эпиднадзора в сочетании с мнениями экспертов из соответствующих стран в отношении результатов углубленного анализа данных эпиднадзора, специальных исследований и программных данных, с целью определения числа недоучтенных и не диагностированных случаев. Информация о 96 странах (на которые приходится 89% всех случаев ТБ), в которых подобные консультации были проведены, начиная с 2008 года, приводится на Рисунке 2.1. Для остальных стран, представители которых не участвовали в тематических семинарах, и в которых данные системы эпиднадзора не могут служить косвенным показателем для определения истинной заболеваемости ТБ, последняя получена путем продления имеющихся временных ́ рядов, анализа показателей смертности по данным органов ЗАГС в сочетании с данными летальности, или расчеты получены с помощью экологического моделирования (см. Приложение 1 с подробным изложением методик). В 2012 году, по оценкам, в мире число случаев заболевания ТБ составило примерно 8,6 млн (в диапазоне 8,3 млн — 9,0 млн), что составляет 122 случая на 100 000 населения ( Таблица 2.1, Таблица 2.2). Абсолютное число случаев заболевания сокращается, хотя и медленно (Рисунок 2.2). Большинство случаев заболевания ТБ в 2012 году приходится на Азию (58%); и регион Африки (27%) 2; меньшая часть — на регион Восточного Средиземноморья (8%), Европейский регион

рисунок 2.1

Страны, с национальными экспертами которых были согласованы данные по оценке бремени туберкулеза, 2008–2013 годы

1

Исследование по изучению полноты регистрации туберкулеза может применяться для определения числа диагностированных, но не зарегистрированных случаев, но использование результатов для расчета общего числа случаев заболеваемости с применением метода первичного и повторного обследования требует соблюдения определенных условий. Разъяснение этого метода можно найти в Руководстве по изучению полноты регистрации ТБ, недавно опубликованном ВОЗ, на сайте по ссылке: www.who.int/tb/publications/inventory_studies/en/index.html 2 Азия относится к двум регионам ВОЗ: региону Юго-Восточной Азии и региону Западной части Тихого океана.

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Доклад о глобальной борьбе с туберкулезом 2013

Таблица 2.1

Оценочные показатели эпидемиологического бремени ТБ, 2012 год. Количество в тыс. a cмертность b население (в тыс.) лучш. c низк. высок. смертность от ТБ ВИЧ-инфицированных лучш. низк. высок. распространенность лучш. низк. высок. заболеваемость лучш. низк. высок. распространенность ВИЧ-инфицированных среди заболевших ТБ лучш. низк. высок.

Афганистан Бангладеш d Бразилия Вьетнам ДР Конго Зимбабве Индия e Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире а

29 825 154 695 198 656 90 796 65 705 13 724 1 236 687 246 864 14 865 43 178 1 377 065 25 203 52 797 168 834 47 783 179 160 143 170 66 785 36 346 96 707 91 729 52 386 4 432 959 892 529 961 103 616 591 904 540 1 833 359 1 845 562 7 053 684

11 70 4,9 18 36 4,6 270 67 9,3 9,5 44 13 25 27 6,1 62 19 9,2 4,7 23 16 31 780 230 19 100 36 450 110 940

4,6 29 4,6 12 16 0,2 170 30 4,3 5,4 43 1 12 1,6 3,2 27 18 3,8 0,8 22 12 3,7 630 160 16 63 35 330 96 790

20 130 5,2 25 64 16 390 120 16 15 46 41 44 86 9,9 110 20 17 12 25 21 86 940 310 21 150 36 590 120 1 100

< 0,1 < 0,1 2,5 2,1 6,3 18 42 2,1 0,6 7,7 1,2 45 4,6 19 7 1,2 1,8 2,2 9,2 0,1 5,6 88 270 250 6,4 4,2 3,9 51 4,8 320

< 0,1 < 0,1 2,2 1,8 5,5 15 37 1,8 0,4 6,6 0,9 35 3,8 11 5,8 0,8 1,5 1,9 8 < 0,1 4,6 75 250 230 5,6 3,8 3,4 46 4,2 300

0,3 0,1 3 2,7 8,1 20 48 3 0,7 8,9 1,5 53 5,3 25 8 1,3 2,2 2,8 12 0,1 7,3 100 280 270 7,2 4,7 4,4 56 5,4

110 670 120 200 380 59 2 800 730 110 130 1 400 140 260 270 84 670 170 110 64 450 210 450 9 600 2 700 390 1 100 510 4 800 2 400

54 340 51 78 200 13 1 900 350 96 71 1 200 28 200 43 45 320 73 47 24 390 170 160

180 1 100 210 370 620 140 3 900 1 200 130 210 1 600 340 320 710 140 1 100 320 190 120 500 250 880

56 350 92 130 210 77 2 200 460 61 120 1 000 140 200 180 79 410 130 80 65 260 230 530 7 000 2 300 280 670 360 3 400 1 600 8 600

47 290 76 99 190 60 2 000 380 52 110 880 96 170 85 74 340 110 66 53 210 170 430 6 700 2 100 260 590 340 3 200 1 500 8 300

67 410 110 170 250 97 2 400 540 70 120 1 100 190 230 310 84 490 150 95 79 310 290 630 7 400 2 500 300 750 390 3 700 1 800 9 000

0,3 0,2 16 9,3 16 55 130 7,5 2,7 45 7,3 83 19 46 32 3,8 9,3 12 35 0,5 23 330 880 830 31 11 19 170 24 1 100

0,2 0,2 13 6,9 14 42 120 5,6 2,3 44 6,4 58 16 21 30 3,1 7,9 10 28 0,4 17 270 810 760 28 10 17 160 21 1 000

0,5 0,3 19 12 19 69 140 9,7 3,1 47 8,2 110 21 80 34 4,6 11 14 42 0,6 30 390 960 910 34 12 21 180 27 1 200

8 200 11 000 2 100 300 730 380 3 700 2 100 3 300 490 1 600 650 6 100 2 600

340 12 000 11 000 13 000

Количества по смертности, распространенности и заболеваемости показаны до двух значащих цифр. Итоговые количества (СВБ, региональные и в мире) вычисляются до округления. Смертность за исключением смертей среди ВИЧ-инфицированных ТБ больных. Смерти среди ВИЧ-инфицированных ТБ больных классифицируются, как смерти от ВИЧ-инфекции в соответствии с МКБ-10 и показаны отдельно в этой таблице. с Лучший, низкий и высокий показатели указывают точечную оценку и нижние и верхние границы 95% интервала неопределенности. d Оценки бремени ТБ не были утверждены НПТ в Бангладеш и совместная переоценка (НПТ и ВОЗ) будет сделана после завершения национального исследования по распространенности ТБ, запланированного в 2014 году. е Оценки для Индии не были официально утверждены Министерством здравоохранения и семейного благополучия правительства Индии и поэтому могут рассматриваться как предварительные. b

Доклад о глобальной борьбе с туберкулезом 2013

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Таблица 2.2

Оценочные показатели эпидемиологического бремени ТБ, 2012 год Показатели на 100 000 населения, если иное не указано a cмертность b население (в тыс.) лучш. низк. высок. смертность от ТБ ВИЧ-инфицированных лучш. низк. высок. распространенность лучш. низк. высок. заболеваемость лучш. низк. высок. распространенность ВИЧ-инфицированных среди заболевших ТБ (%) лучш. низк. высок.

Афганистан Бангладеш c Бразилия Вьетнам ДР Конго Зимбабве Индия d Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире а b

29 825 154 695 198 656 90 796 65 705 13 724 1 236 687 246 864 14 865 43 178 1 377 065 25 203 52 797 168 834 47 783 179 160 143 170 66 785 36 346 96 707 91 729 52 386 4 432 959 892 529 961 103 616 591 904 540 1 833 359 1 845 562 7 053 684

37 45 2,5 20 54 33 22 27 63 22 3,2 53 48 16 13 34 13 14 13 24 18 59 18 26 1,9 16 3,9 25 5,8 13

15 19 2,3 13 24 1,2 14 12 29 13 3,1 3,9 23 0,9 6,8 15 13 5,8 2,3 22 13 7 14 18 1,7 10 3,9 18 5,2 11

68 84 2,6 27 97 117 32 48 110 34 3,3 163 84 51 21 61 14 25 33 26 23 164 21 35 2,2 24 4 32 6,4 16

0,3 < 0,1 1,3 2,4 9,7 132 3,4 0,9 3,8 18 < 0,1 177 8,8 11 15 0,7 1,2 3,3 25 0,1 6,1 168 6 28 0,7 0,7 0,4 2,8 0,3 4,6

< 0,1 < 0,1 1,1 2 8,3 111 3 0,7 2,7 15 < 0,1 138 7,3 6,7 12 0,5 1 2,9 22 < 0,1 5 144 5,6 26 0,6 0,6 0,4 2,5 0,2 4,3

1,1 < 0,1 1,5 2,9 12 147 3,9 1,2 4,7 21 0,1 209 10 15 17 0,8 1,5 4,2 32 0,1 8 192 6,4 30 0,7 0,8 0,5 3,1 0,3 4,8

358 434 59 218 576 433 230 297 764 299 99 553 489 161 176 376 121 159 175 461 224 857 216 303 40 180 56 264 128 169

181 218 25 86 301 92 155 144 645 164 86 111 377 25 95 181 51 71 67 405 180 305 186 239 31 118 42 203 115 149

595 721 107 410 938 1 030 319 506 892 475 113 1 340 616 420 283 641 221 282 334 520 272 1 680 248 373 51 256 72 333 142 190

189 225 46 147 327 562 176 185 411 272 73 552 377 108 165 231 91 119 179 265 247 1 000 159 255 29 109 40 187 87 122

156 185 38 109 282 434 159 153 353 261 64 383 322 50 154 190 77 98 145 219 183 827 151 235 27 96 38 174 80 117

226 268 55 192 375 706 193 220 474 283 82 753 435 186 175 276 106 142 216 316 321 1 190 166 275 31 122 43 200 95 127

0,55 < 0,1 17,3 6,97 7,66 70,9 5,95 1,65 4,34 38,7 0,73 59,7 9,33 25,2 41,2 0,92 7,14 15,2 53,2 0,18 10,2 63,0 7,37 36,6 11,4 1,88 5,26 4,94 1,49 12,8

0,41 < 0,1 17,1 6,94 7,65 70,7 5,93 1,65 4,21 38,7 0,73 59,6 9,32 24,8 41,2 0,84 7,03 15,2 52,9 0,18 10,1 62,9 7,35 34,7 8,67 1,34 3,80 4,31 0,92 11,6

0,68 < 0,1 17,4 6,99 7,66 71,4 5,97 2,33 4,44 38,7 0,73 59,8 9,33 25,7 41,3 0,96 7,25 15,3 53,3 0,18 10,2 63,0 7,40 38,4 14,4 2,52 6,93 5,62 2,18 14,0

Лучший, низкий и высокий показатели указывают точечную оценку и нижние и верхние границы 95% интервала неопределенности. Смертность за исключением смертей среди ВИЧ-инфицированных ТБ больных. Смерти среди ВИЧ-инфицированных ТБ больных классифицируются, как смерти от ВИЧ-инфекции в соответствии с МКБ-10 и показаны отдельно в этой таблице. c Оценки бремени ТБ не были утверждены НПТ в Бангладеш и совместная переоценка (НПТ и ВОЗ) будет сделана после завершения национального исследования по распространенности ТБ, запланированного в 2014 году. d Оценки для Индии не были официально утверждены Министерством здравоохранения и семейного благополучия правительства Индии и поэтому могут рассматриваться как предварительные.

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Доклад о глобальной борьбе с туберкулезом 2013

рисунок 2.2

рисунок 2.3

Оценочное число случаев заболевания и смерти от туберкулеза (млн), 1990–2012 годы Заболеваемость ТБ 10.0

Расчетный уровень заболеваемости ТБ: страны первой десятки, 2012 год a. Заболеваемость: абсолютные показатели Индия G

Все случаи ТБ 7.5

Китай ЮАР Индонезия G G

G

Миллионы

Пакистан 5.0

G

Бангладеш Филиппины G

G

2.5 Случаи ТБ, сочетанного с ВИЧ-инфекцией

Эфиопия ДР Конго Мьянма

G

G

G

0 1990 1995 2000 2005 2012

0.5

1.0

1.5 Миллионы

2.0

2.5

Случаи смерти от ТБ 2.0 Свазиленд

b. Заболеваемость: показатель на 100 000 населения G

Случаи смерти от ТБ среди ВИЧ-отрицательных пациентов 1.5 Миллионы

ЮАР Сьерра-Леоне Намибия G

G

G

1.0

Лесото Джибути

G

G

Случаи смерти от ТБ, сочетанного с ВИЧ-инфекциейa 0.5

Зимбабве Мозамбик Восточный Тимор G

G

G

0 1990 a

Габон

G

1995

2000

2005

2012

400

800

1200

1600

Случаи смерти от ТБ, сочетанного с ВИЧ-инфекцией, классифицируются как смерти от ВИЧ-инфекции в соответствии с МКБ-10.

Показатель на 100 000 населения в год

(4%) и регион Америки (3%). С 2000 года приоритетное внимание уделяется 22 СВБ (список стран приведен в  Таблице 2.1 и Таблице 2.2); на эти страны приходится 81% всех случаев заболевания ТБ в мире. Среди пяти стран с самым высоким уровнем заболевания в 2012 году оказались Индия (2,0 млн —2,4 млн), Китай (0,9  млн  —1,1  млн), Южно-Африканская Республика (0,4 млн — 0,6 млн), Индонезия (0,4 млн — 0,5 млн) и Пакистан (0,3 млн — 0,5 млн); данные по этим странам и еще по пяти странам, которые занимают следующие пять позиций в списке десяти стран с наиболее высоким числом случаев ТБ, приведены на Рисунке 2.3. Только Индия и Китай соответственно насчитывают 26% и 12% от общего числа случаев ТБ в мире. Из общего числа равного 8,6 млн случаев, 0,5 млн составили дети и 2,9 млн (2,7 млн — 3,1 млн) — женщины (Вставка 2.2). Среди 8,6  млн случаев ТБ в  2012  году насчитывалось от 1,0 млн до 1,2 млн (12–14%) больных ВИЧ-инфекцией, лучшая оценка составляет 1,1 млн (13%) ( Tаблица 2.1, Tаблица 2.2). По оценочным данным, самая высокая доля больных туберкулезом, сочетанным с ВИЧ-инфекцией, приходится на страны региона Африки (Рисунок 2.4), составляя 37% в этом регионе

и 75% в мире, соответственно, а в некоторых частях юга Африки составляет более 50% случаев ТБ (Рисунок 2.4). По итогам систематического анализа данных по смертности, вызванной МЛУ-ТБ (Вставка 2.3), глобальная оценка бремени МЛУ-ТБ была уточнена в 2013 году (Bставка 2.1). Лучшая оценка составляет 450 000 (диапазон 300 000–600 000) новых случаев МЛУ-ТБ во всем мире в 2012 году с учетом как первичных (выявленных среди новых случаев), так и приобретенных случаев МЛУ-ТБ (случаев, взятых на повторное лечение — ред.). Показатель заболеваемости ТБ (т. е. число случаев туберкулеза в соотношении к численности населения) значительно различается между странами (Рисунок 2.5). Наиболее низкие значения показателя заболеваемости наблюдаются преимущественно в странах с высоким уровнем доходов, включая большинство стран Западной Европы, Канаду, Соединенные Штаты Америки, Японию, Австралию и Новую Зеландию. В этих странах показатель заболеваемости составляет менее 10 случаев на 100 000 населения. Большинство стран региона Америки имеют показатели ниже 50 на 100 000 населения, и в среднем, этот регион является регионом с самым низким показателем 11

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 2.2

Бремя туберкулеза среди женщин и детей Бремя заболеваемости и смертности от ТБ среди женщин (женщины в возрасте 15 лет и старше) и детей (в возрасте до 15 лет) выше, чем предполагалось ранее. Второй год подряд в Докладе ВОЗ о глобальной борьбе с туберкулезом приводятся данные о бремени болезни среди детей и впервые включаются оценочные данные по бремени болезни среди женщин с разбивкой по регионам и по ВИЧ-статусу. В 2012 году по оценкам насчитывалось примерно 2,9 млн новых случаев ТБ и 410 000 смертей от этого заболевания среди женщин. В 2012 году по оценкам насчитывалось 530 000 новых случаев заболевания и 74 000 смертей среди ВИЧ-отрицательных детей. Ниже приводится описание методов, используемых для получения этих данных, и более подробная информация о результатах. Оценочные показатели заболеваемости и смертности от туберкулеза среди детей несколько выше, чем те, которые опубликованы в Докладе ВОЗ о глобальной борьбе с ТБ за 2012 год, так как они были уточнены в соответствии с новыми данными эпиднадзора по регистрации случаев ТБ среди детей в мире, а также дополнительной информации из органов ЗАГС. смертности от ТБ среди мужчин и женщин использовалась экологическая статистическая модель. Модель учитывает набор факторов, которые, как известно, ассоциируются со смертностью от ТБ (ВВП на душу населения, доля новых случаев МЛУ-ТБ, распространенность ВИЧ-инфекции среди населения в целом и показатель «успешности лечения»). В мире, среди ВИЧ-отрицательных взрослых, на каждый случай смерти от туберкулеза среди женщин приходится 2,55 (диапазон 1,92–3,18) случаев смерти от туберкулеза среди мужчин (Рисунок B2.2.1). Региональные различия очевидны (Таблица B2.2.2), на регионы Африки и Юго-Восточной Азии приходится 69% от общего числа случаев смерти. Главным недостатком использованной методики является то, что все 120 стран, представивших детальные данные по смертности из органов ЗАГС, являются странами со средним или высоким уровнем доходов. Прогнозы для стран с низким уровнем доходов пришлось строить путем экстраполяции данных, полученных из этих стран. Распределение числа случаев смерти от туберкулеза, сочетанного с ВИЧ-инфекцией по полу, было произведено используя допущение, что оно соответствует таковому среди больных, умерших от ВИЧ-инфекции, по оценкам ЮНЭЙДС. В мире, число случаев смерти от туберкулеза, сочетанного с ВИЧ-инфекцией, среди мужчин и женщин равно (Рисунок B2.2.2). Однако существуют поразительные региональные различия (Таблица B2.2.2). По оценочным данным, в регионе Африки больше случаев смерти приходится на женщин, в то время как в других регионах — среди мужчин.

Бремя туберкулеза у женщин: оценочные показатели заболеваемости и смертности, 2012 год

Заболеваемость Региональные оценочные показатели среди женщин: по данным 2012 года получено соотношение числа зарегистрированных новых случаев ТБ среди женщин к таковому среди мужчин (все типы случаев) в разбивке по регионам и сделано допущение, что это соотношение соответствует распределению в оценочной заболеваемости ТБ в 2012 году (см. Приложение 1 для более подробной информации). Результаты глобальной и региональной оценки заболеваемости показаны в Таблице B2.2.1. На долю женщин приходилось 34% от общего числа случаев ТБ равного 8,6 млн в 2012 году. На долю региона Африки и региона Юго-Восточной Азии приходилось 68% случаев заболевания среди женщин.

Таблица B2.2.2

Оценочное число случаев смерти от туберкулеза среди женщин с разбивкой по регионам ВОЗ, 2012 год ВИЧ-отрицательные Лучшая оценка Интервал неопределенности Больные ВИЧ-инфекцией Лучшая оценка Интервал неопределенности

Таблица B2.2.1

AFR AMR EMR EUR SEAR

80 000 5 900 32 000 10 000 93 000 26 000 250 000

53 000–110 000 5 000–6 700 18 000–46 000 9 700–10 000 65 000–120 000 24 000–29 000 210 000–290 000

140 000 2 000 1 400 1 200 18 000 1 200 160 000

130 000–150 000 1 900–2 200 1 300–1 600 1 000–1 300 16 000–20 000 1 000–1 300 150 000–170 000

Общее число зарегистрированных новых случаев туберкулеза (все формы) и оценочное число случаев туберкулеза среди женщин в разбивке по регионам ВОЗ, 2012 год Регион ВОЗ Число зарегистрированных случаев Оценочное число новых случаев туберкулеза Лучшая оценка Интервал неопределенности

WPR В мире

AFR AMR EMR EUR SEAR WPR В мире

361 645 63 626 101 910 79 279 431 470 392 030 1 429 960

860 000 100 000 280 000 120 000 1 100 000 510 000 2 900 000

780 000–940 000 91 000–110 000 240 000–330 000 110 000–130 000 990 000–1 200 000 460 000–550 000 2 700 000–3 100 000

Бремя туберкулеза у детей: оценочное число зарегистрированных случаев туберкулеза, истинная заболеваемость и смертность от туберкулеза (среди ВИЧ-отрицательных детей), 2012 год

Регистрируемая и истинная заболеваемость ТБ Оценочное число новых зарегистрированных случаев туберкулеза среди детей в мире (в возрасте до 15 лет) составило 349 000 в 2012 году (Таблица В2.2.3). Этот показатель включает собственно зарегистрированные случаи среди детей, представленные в отчетах стран, и оценочное число случаев туберкулеза у детей в странах, которые не представили данные с разделением по возрасту. Для последних (Рисунок В2.2.3) сделано допущение, что соотношение случаев регистрации среди детей и взрослых было такое же (для каждой формы туберкулеза), как и в тех странах, которые представили данные регистрации случаев с разделением по возрасту (альтернативный метод, основанный на предположении, что соотношение между случаями заболевания среди детей и взрослых одинаковы, дал аналогичные результаты). ВОЗ не запрашивает данные с разбивкой по возрасту по рецидивам или по тем случаям, которые классифицируются как «история заболевания неизвестна», и число детей в этих категориях принимается за ноль. При оценке заболеваемости туберкулезом среди детей, сделано допущение, что в мире в целом, в 2012 году, показатель выявления заболевания для представителей всех возрастов был на одном уровне (лучшая оценка 66%, диапазон 64%–69%). Исходя из этого, оценочное число случаев туберкулеза среди детей составило 530 000 (диапазон 510 000–550 000) в 2012 году, или около 6% от общего числа случаев, равного 8,6 млн.

Смертность В целом, оценочное число случаев смерти от ТБ среди женщин в 2012 году составило 410 000, в том числе 250 000 (в диапазоне 210 000–290 000) среди ВИЧ-отрицательных женщин (29% всех смертей от ТБ среди ВИЧотрицательных взрослых) и 160 000 (в диапазоне 150 000–170 000) случаев смерти от туберкулеза, сочетанного с ВИЧ-инфекцией (50% всех смертей от ТБ, сочетанного с ВИЧ-инфекцией). Новые отчетные данные и снижение общей смертности от ТБ объясняют снижение оценочного числа случаев смерти от ТБ среди женщин по сравнению с показателями за предыдущие годы (см. также Вставку 2.1). Данные о числе случаев смерти, с разбивкой по возрасту и полу, полученные из органов ЗАГС, были использованы для расчета оценочного числа случаев смерти от ТБ среди ВИЧ-отрицательных взрослых для 120 стран (данные органов ЗАГС были получены из 121 страны; Китай соответствующие данные с разбивкой по полу и возрасту не представил). Был проведен расчет числа случаев смерти от ТБ по полу с поправкой на неполный охват и долю ошибочно определенных причин смерти (см. Приложение 1 для более подробной информации). Для стран, не направивших данные из органов ЗАГС, для прогнозирования соотношения

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Доклад о глобальной борьбе с туберкулезом 2013

Ограничения использованной методики:

Рисунок B2.2.1

Рисунок B2.2.2

•• Предположение о том, что случаев смерти от ТБ среди ВИЧ-отрипоказатель выявления случаев цательных больных (в возрасте 15 лет одинаков для взрослых и детей, и старше), в мире и по регионам ВОЗ в отсутствие данных по полноте регистрации диагностированных AFR случаев отдельно для детей и взрослых. AMR •• Предположение, что все EMR зарегистрированные случаи, действительно были случаями EUR туберкулеза. Ошибочный диагноз возможен, учитывая трудности SEAR диагностики туберкулеза у детей. WPR •• Доля случаев среди детей может отличаться в странах, по которым В мире отсутствуют данные с разделением по возрасту. Тем не менее, 1 2 3 4 отчетность по заболеваемости Соотношение между полами (М: Ж) с разбивкой по возрасту улучшается и в 2012 году число стран, предоставивших отчеты без разделения Таблица B2.2.3 данных по возрасту, было сравнительно небольшим. G G G G G G G

Соотношение между полами в числе

Соотношение между полами в числе случаев смерти от ТБ, сочетанного с ВИЧ-инфекцией (в возрасте 15 лет и старше), в мире и по регионам ВОЗ AFR AMR EMR EUR SEAR WPR В мире G

G

G

G

G

G

G

1

2

3

Соотношение между полами (М: Ж)

Смертность от туберкулеза среди ВИЧ-отрицательных детей Данные о смертности, полученные ВОЗ из органов ЗАГС, разделенные по возрастным группам, поступили из 120 стран. Эти данные были использованы для расчета показателей смертности от ТБ на 100 000 населения среди детей и взрослых, с поправкой на неполный охват или ошибочно установленные причины смерти (см. Приложение 1 для уточнения деталей). К расчету показателей по странам, не представившим данные из органов ЗАГС, была применена экологическая статистическая модель прогнозирования соотношения уровня смертности от ТБ среди детей и взрослых. Общее оценочное число случаев смерти от ТБ среди ВИЧ-отрицательных детей составило 74 000 (диапазон 59 000–90 000), или около 8% от общего числа 940 000 случаев смерти от ТБ среди ВИЧ-отрицательного населения в 2012 году. Оценка смертности от ТБ, сочетанного с ВИЧ-инфекцией, среди детей не включена в данный отчет в силу сложностей, которые возникли из-за неправильного кодирования причин смерти: случаи смерти от ВИЧ-инфекции регистрируются как случаи смерти от туберкулеза. Тем не менее, разделение по возрасту случаев смерти от ТБ, сочетанного с ВИЧ-инфекцией, станет одним из результатов работы над блоком по ТБ программы Spectrum (см. Вставку 2.1). Шаги в направлении совершенствования методов оценки числа случаев ТБ среди детей предполагают:

Число зарегистрированных новых случаев туберкулеза по типу случая и по полу, 2012 год С положительной микроскопией С отрицательной микроскопией a Внелегочный туберкулез

Всего зарегистрировано Страны, представляющие данные по возрастным группам Страны, не представляющие данные по возрастным группам (% от общего числа зарегистрированных случаев, разделенных по возрастным группам) Число стран, представляющих отчетность о зарегистрированных случаях с разделением по возрастным группам (число СВБ) b Общее число случаев регистрации ТБ у детей в странах, представляющих данные с разделением по возрастным группам

2 568 789 2 551 136 17 653 (99%)

1 935 971 1 597 530 338 441 (83%)

817 462 678 953 138 509 (83%)

204 (22)

184 (14)

184 (14)

46 488

163 477

91 308

•• глобальные консультации по дальнейшему развитию аналитических Общее оценочное число случаев методов, определению и приоритизации действий, необходимых для регистрации ТБ среди детей по 349 000 получения новых данных в сентябре 2013 года; всем странам •• внедрение персонифицированной a Включая зарегистрированные случаи, по которым нет результата электронной системы учета микроскопии мазка мокроты, или исследование не проводилось. и отчетности, которая упрощает b Дополнительно об отсутствии случаев ТБ в 2012 году отчитались девять составление и анализ данных стран, три страны не представили отчетов в ВОЗ к июлю 2013 года. с разбивкой по возрастным группам; •• общенациональные исследования Рисунок B2.2.3 по изучению полноты регистрации Отчетность по регистрируемой заболеваемости с разбивкой по возрасту, 2012 год туберкулеза среди детей; •• более активная работа с лицами, находящимися в контакте с больными ТБ, и интеграция противотуберкулезных мероприятий в деятельность служб по охране материнства и детства для выявления случаев туберкулеза у детей, которые не были бы диагностированы при иных обстоятельствах.

Разделение по возрасту Все типы случаев дезагрегированы Дезагрегированы только случаи с положительной микроскопией Нет разделения по возрасту Данные не представлены

Доклад о глобальной борьбе с туберкулезом 2013

13

рисунок 2.4

Оценочная распространенность ВИЧ-инфекции среди новых случаев ТБ, 2012 год

Распространенность ВИЧ-инфекции среди новых случаев ТБ, все возрастные группы (%) 0–4 года 5–19 лет 20–49 лет 50 лет и более Нет данных Не применимо

рисунок 2.5

Оценочные показатели заболеваемости туберкулезом, 2012 год

Оценочные новые случаи ТБ (все формы) на 100 000 населения в год 0–9.9 10–19 20–49 50–124 125–299 300–499 ≥500 Нет данных Не применимо

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Доклад о глобальной борьбе с туберкулезом 2013

рисунок 2.6

Глобальные тенденции в оценке уровня заболеваемости, распространенности и смертности от ТБ. Слева: Глобальные тенденции в оценках заболеваемости, включая ТБ, сочетанный с ВИЧ-инфекцией (зеленый), и оценки заболеваемости ТБ, сочетанным с ВИЧ-инфекцией (красный). Центр и правая сторона: тенденции в оценках распространенности ТБ и смертности в 1990–2012 годы и прогноз распространенности ТБ и смертности на 2013–2015 годы. Горизонтальные пунктирные линии представляют собой цели Партнерства «Остановить ТБ», предполагающие 50% сокращение распространенности и смертности к 2015 году по сравнению с 1990 годом. Затененные участки представляют собой доверительный диапазон. В данных о смертности исключаются смерти от ТБ среди ВИЧ-инфицированных больных. Заболеваемость 150 Показатель на 100 000 населения в год Показатель на 100 000 населения 300 Показатель на 100 000 населения в год 1990 1995 2000 2005 2010 2015 Распространенность 30 Смертность

100

200

20

50

100

10

0 1990 1995 2000 2005 2010

0

0 1990 1995 2000 2005 2010 2015

бремени туберкулеза. Большинство стран с высоким бременем ТБ имеют показатели от 150 до 300 случаев на 100 000 населения ( Таблица 2.2); среди СВБ достаточно низкие показатели демонстрируют Бразилия и Китай; обращают на себя внимание показатели свыше 500 на 100 000 населения в Зимбабве, Мозамбике и Южно-Африканской Республике. Другие страны из первой десятки стран с самым высоким уровнем заболеваемости ТБ находятся, главным образом, в Африке (Рисунок 2.3).

В Южно-Африканской Республике и Свазиленде по «лучшим» оценкам на каждые 100 человек населения приходится 1 заболевший (1000 или более на 100 000 населения ежегодно). В мире, показатель заболеваемости был относительно стабильным с 1990 по 2001 годы, а затем начал снижаться (Рисунок 2.6), что говорит о досрочном достижении цели ЦТР, запланированной к 2015 году. С 2011 по 2012 годы темп снижения составил 2%. Эту тенденцию необходимо закрепить

рисунок 2.7

Оценочные показатели заболеваемости ТБ по регионам ВОЗ, 1990–2012 годы. Региональные тенденции в оценочных показателях заболеваемости ТБ (зеленый) и оценочных показателях заболеваемости ТБ, сочетанным с ВИЧ-инфекцией (красный). Затененные участки представляют собой диапазоны неопределенности. 400 300 200 Показатель на 100 000 населения в год 100 0 Европа Африка 80 60 40 20 0 Юго-Восточная Азия Америка 200 150 100 50 0 Регион Западной части Тихого океана Восточное Средиземноморье

100 75

300

200 150

200 50 100 25 0 1990 1995 2000 2005 2012 0 1990 1995 2000 2005 2012 50 0 1990 1995 2000 2005 2012 100

Доклад о глобальной борьбе с туберкулезом 2013

15

рисунок 2.8

Оценочные показатели заболеваемости ТБ, 22 страны с высоким бременем туберкулеза, 1990– 2012 годы. Тенденции в оценочных показателях заболеваемости ТБ (зеленый) и оценочных показателях заболеваемости ТБ, сочетанным с ВИЧ-инфекцией (красный). Затененные участки представляют собой диапазоны неопределенности. 300 200 200 100 100 0 50

Афганистан

400 300

Бангладешa

150 100

Бразилия

400 300 200 100 0

Вьетнам

500 400 300 200 100 0

ДР Конго

0 1250 1000 750 500 250

0

Зимбабве

300 200 100

Индия

300 200 100

Индонезия

1000 750 500 250 0

Камбоджа

400 300 200 100 0

Кения

Показатель на 100 000 населения в год

0

0

0

200 150 100 50 0

Китай

1250 1000 750 500 250 0

Мозамбик

600 400 200

Мьянма

600 400 200

Нигерия

300 200 100

ОР Танзания

0

0

0

400 300 200 100 0

Пакистан

200 150 100 50 0

Российская Федерация

250 200 150 100 50 0

Таиланд

1250 1000 750 500 250 0

Уганда

600 400 200

Филиппины

0 1990 1995 2000 2005 2012 1990 1995 2000 2005 2012

1990 800 600 400 200 0 1990 a

1995

2000

2005

2012

Эфиопия

1250 1000 750 500 250 0

ЮАР

1995

2000

2005

2012

1990

1995

2000

2005

2012

Оценка бремени ТБ не была одобрена НПТ Бангладеш; совместная переоценка будет проводиться после завершения исследования по изучению распространенности ТБ, запланированного на 2014 год.

для достижения ЦТР к 2015 году. Показатели заболеваемости снижаются во всех шести регионах ВОЗ (Рисунок 2.7); самые высокие темпы снижения в Европейском регионе (6,5% в год) и самые низкие — в регионах Восточного Средиземноморья и Юго-Восточной Азии (менее 1% в год и 2% в год, соответственно). Показатели заболеваемости снижаются с середины 1990-х годов в регионе Восточного Средиземноморья, а с 2000 года — в регионе Юго-Восточной Азии; они достигли самых высоких показателей примерно в 1997 году в Европейском регионе и около 2002 года в регионе Африки. Начиная с 1990 года, наблюдается снижение показателя в регионе Америки и Западной части Тихого океана. По последним оценкам в большинстве из 22 СВБ наблюдается снижение заболеваемости туберкулезом (Рисунок 2.8).

2.2 Распространенность туберкулеза В странах с относительно высоким бременем ТБ (около 100 случаев и  более на 100 000 населения) распространенность туберкулеза легких с бактериовыделением может быть непосредственно измерена при проведении общенациональных исследований по изучению распространенности туберкулеза на выборке из 50 000 человек. Результаты исследования могут 16

быть использованы для расчета оценочного показателя распространенности туберкулеза с учетом всех форм заболевания. Стоимость исследования обычно колеблется от 1 до 4 млн долл. США. Для проведения подобного исследования имеются теоретические и практические руководства, содержащие материалы для планирования и осуществления исследования, анализа данных и составления отчетности 1. Повторные исследования, проводимые с периодичностью примерно раз в 10 лет, позволяют оценить тенденции в бремени туберкулеза. За последние 10 лет, следующие страны с высоким бременем болезни провели повторные исследования: Камбоджа, Китай, Таиланд и Филиппины; повторные исследования также планируются во Вьетнаме и Мьянме. На Рисунке 2.9 показаны страны, в которых были осуществлены исследования по изучению распространенности ТБ или их проведение планируется в ближайшем будущем. В период с 2008 по 2017 годы было и будет проведено

1

TB prevalence surveys: a handbook. Geneva, World Health Organization, 2011 (WHO/HTM/TB/2010.17). Доступно на: www.who.int/tb/advisory_ bodies/impact_measurement_taskforce/resources_documents/ thelimebook/

Доклад о глобальной борьбе с туберкулезом 2013

рисунок 2.9

Страны, которые провели общенациональные исследования по изучению распространенности туберкулеза, с использованием последних рекомендаций по проведению скрининга и диагностики a, начиная с 1990 года, или в которых планируется проведение данных исследований в ближайшее время: по состоянию на июль 2013 года

Национальное исследование не запланировано Национальное исследование запланированоb Национальное исследование проводится Одно национальное исследование завершено Планируется повторное национальное исследование Завершено одно и более национальных исследований Не применимо a b

При проведении скрининга используются рентгенологические методы исследования органов грудной клетки; культуральные исследования используются для подтверждения диагноза. «Планируется проведение национального исследования» означает, что страна как минимум представила проект протокола и бюджета в Глобальную целевую группу ВОЗ по измерению последствий ТБ.

2.3 Смертность от туберкулеза беспрецедентное количество национальных исследований по изучению распространенности ТБ (см. также Раздел 2.4). В странах с низким и средним бременем туберкулеза размеры выборки и расходы являются непомерно большими. Если не имеется данных по исследованию распространенности, то их можно определить косвенно как произведение показателя заболеваемости и средней продолжительности заболевания, но эти данные будут со значительной погрешностью (Приложение 1). Для большинства стран распространенность туберкулеза можно оценить только с помощью косвенных методов. По оценочным данным, в 2012 году в мире было примерно 12 млн случаев ТБ (диапазон 11 млн — 13 млн) ( Таблица 2.1), что составляет 169 случаев на 100 000 населения (Таблица 2.2). К 2012 году показатель распространенности туберкулеза в мире снизился на 37% по сравнению с 1990 годом. Текущие прогнозы показывают, что цель Партнерства «Остановить ТБ» по сокращению вдвое масштабов распространенности туберкулеза к 2015 году по сравнению с базовым уровнем 1990 года, в мире в целом не будет выполнена (Рисунок 2.6). На региональном уровне распространенность ТБ снижается во всех шести регионах ВОЗ (Рисунок 2.10). В регионе Америки показатель распространенности сократился вдвое еще в 2004 году, задолго до 2015 года, и наилучшая оценка свидетельствует о том, что в регионе Западной части Тихого океана был достигнут целевой показатель сокращения на 50% распространенности туберкулеза в 2012 году. Достижение этой цели к 2015 году представляется возможным в регионе Юго-Восточной Азии, а также в Европейском регионе при условии относительно небольшого ускорения нынешних темпов снижения. Цель представляется недостижимой в регионе Африки и регионе Восточного Средиземноморья. Оценочные показатели смертности от туберкулеза среди ВИЧ-отрицательных людей могут быть рассчитаны на основании данных о смертности из органов ЗАГС, если данные из этой системы являются достаточно полными и причины смерти кодируются согласно последней редакции Международной классификации болезней (МКБ-10). Расчеты на основе данных из органов ЗАГС по репрезентативной выборке территорий страны (например, как в Китае) является лишь временным решением. Специальные исследования по изучению смертности также можно использовать для определения числа случаев смерти от туберкулеза. В 2012 году большинство стран с высоким бременем ТБ не располагало данными из системы ЗАГС ни в целом по стране, ни по выборке территорий страны и только несколько стран провели специальные исследования по изучению смертности. В отсутствие системы регистрации смертности по линии ЗАГС или данных специальных исследований по изучению смертности, смертность от ТБ можно рассчитать как произведение заболеваемости туберкулезом и летальности, а также при помощи экологического моделирования на основе данных о смертности в странах с системами ЗАГС. Смертность от ТБ ВИЧ-инфицированных больных трудно определить даже при наличии системы регистрации смертности по линии ЗАГС, потому что причины смерти у больных ВИЧ-инфекцией часто кодируют как «смерть от ВИЧ-инфекции», и дополнительные причины смерти (например, ТБ) учитываются недостоверно. Впервые для настоящего доклада за 2013 год были подготовлены данные по отдельным странам об оценочном числе случаев смерти от ТБ среди ВИЧ-инфицированных больных при помощи программного обеспечения Spectrum, которое используется для оценки бремени ВИЧ-инфекции более десяти лет (Вставка 2.1). 17

Доклад о глобальной борьбе с туберкулезом 2013

рисунок 2.10

Тенденции в расчетных показателях распространенности туберкулеза за период 1990–2012 годы и прогноз по распространенности ТБ на 2013–2015 годы по регионам ВОЗ. Затененные участки представляют собой диапазоны неопределенности. Горизонтальные пунктирные линии представляют собой цели Партнерства «Остановить ТБ» по снижению распространенности на 50% к 2015 году, по сравнению с 1990 годом. Другие пунктирные линии показывают перспективные оценки до 2015 года. Африка Америка 400 100 300 200 Показатель на 100 000 населения 200 50 100 0 Европа 150 400 100 200 0 Юго-Восточная Азия 0 Западная часть Тихого океана Восточное Средиземноморье

400

50

200

100

0 1990 1995 2000 2005 2010 2015

0 1990 1995 2000 2005 2010 2015

0 1990 1995 2000 2005 2010 2015

Вставка 2.3

Смертность от МЛУ-ТБ — методы, используемые для уточнения оценочных данных В части Доклада о глобальной борьбе с ТБ за 2010 год приводились данные об эпидемии МЛУ-ТБ и глобальных ответных мерах, так оценочное число случаев смерти от МЛУ-ТБ составляло 150 000 (диапазон: 53 000–270 000) в 2008 году a. Тогда впервые ВОЗ опубликовала глобальные оценочные данные о смертности от МЛУ-ТБ, и, учитывая ограниченность имеющихся доказательств, ежегодные уточнения более не производились. Теоретически число смертей от МЛУ-ТБ можно оценить как произведение общего числа смертей от ТБ, доли МЛУ-ТБ среди всех заболеваний ТБ (5,7%), и показателя относительного риска (ОР) смерти среди больных с МЛУ-ТБ по сравнению с больными, не имеющими МЛУ-ТБ. Следует отметить, что приблизительные оценки общего уровня смертности от ТБ и распространенности МЛУ-ТБ были доступны в течение нескольких лет из систем ЗАГС (то есть из этой системы известно общее число случаев смерти от ТБ), а по данным эпиднадзора или специальных исследований были получены репрезентативные данные о доле МЛУ-ТБ, но при этом оценка относительного риска смерти от МЛУ-ТБ не проводилась. В 2013 году ВОЗ поручила провести систематический обзор ОР смерти от МЛУ-ТБ по сравнению с ТБ. Были выбраны двадцать пять исследований, которые содержали данные о смертности среди больных, поступивших на лечение с МЛУ-ТБ и ТБ (без МЛУ-ТБ), во время и после лечения. Это позволило осуществить расчеты по глобальной оценке ОР смерти от МЛУ-ТБ (2,36, диапазон: 1,67–3,05). Упомянутые двадцать пять исследований имеют широкий географический охват, включая страны с высоким и низким бременем МЛУ-ТБ и ВИЧ-инфекции, но этого было недостаточно для оценки ОР по отдельным регионам. Основываясь на результатах мета-анализа, предполагается, что в мире в 2012 году от МЛУ-ТБ умерло 170 000 больных (диапазон: 100 000– 240 000). a

Multidrug- and extensively drug-resistant TB (M/XDR-TB): 2010 global report on surveillance and response (WHO/HTM/TB/2010.3). Geneva, World Health Organization, 2010. Доступно на: http://www.who.int/tb/publications/2010/978924599191/en/

18

Доклад о глобальной борьбе с туберкулезом 2013

рисунок 2.11

Страны (оранжевый), для которых смертность от туберкулеза оценивается с помощью данных системы записей актов гражданского состояния (n = 121) и/или исследований по изучению причин смерти (n = 2, Вьетнам и Индия)

До 2008 года ВОЗ при проведении оценки смертности от ТБ использовала данные систем ЗАГС только для трех стран. В 2009 году положение значительно улучшилось, так как данные стали предоставлять 89 стран, расположенных в Европейском регионе и регионе Америки, в которых насчитывалось менее 10% случаев заболевания ТБ в мире. В 2011 году впервые были использованы выборочные данные из органов ЗАГС из Китая и данные специальных исследований из Индии, что позволило значительно улучшить качество оценочных данных по смертности от ТБ. Для настоящего доклада данные систем ЗАГС, достаточные по полноте охвата и качеству были представлены из 121 страны. Это позволило, в сочетании с данными специальных исследований из Индии и Вьетнама, произвести расчет смертности от ТБ с применением прямых методов оценки для 123 стран (см. Рисунок 2.11). В сумме на эти 123 страны приходится 45% от расчетного числа случаев смерти от ТБ в мире. Существуют большие проблемы с получением данных из систем ЗАГС из стран региона Африки и части стран из региона Юго-Восточной Азии; в последнем, в Индонезии в настоящее время создается система регистрации данных по линии ЗАГС. Всего в 2012 году насчитывалось около 1,3 млн расчетных случаев смерти от ТБ (Таблица 2.1, Рисунок 2.2): 940 000 среди ВИЧ-отрицательных людей и 320 000 больных ВИЧ-инфекцией (случаи смерти от ТБ среди больных ВИЧ-инфекцией кодируются 1. Общее число случаев как смерть от ВИЧ-инфекции в МКБ-10)  смерти включает 410 000 случаев смерти среди женщин и 74 000 среди детей (Bставка 2.2). Это число также включает около 170 000 случаев смерти от МЛУ-ТБ (диапазон: 102 000–242 000): методы, используемые для расчета этой новой глобальной оценки смертности от МЛУ-ТБ описаны во Вставке 2.3. Примерно 75% от общего числа случаев смерти от ТБ приходилось на Африку и Юго-Восточную Азию в 2012 году (как включая, так и исключая смерть от ТБ среди больных ВИЧ-инфекцией). На Индию и Южно-Африканскую Республику приходилось около одной трети всех случаев смерти от ТБ в мире. Показатель смертности от туберкулеза в мире составил 13 на 100 000 населения в 2012 году ( Таблица 2.2) или 17,6 на

100 000, если учитывать число смертей от ТБ ВИЧ-инфицированных больных. Отмечается значительная вариабельность показателя между странами (Рисунок 2.12), начиная от 1 случая смерти от ТБ на 100 000 населения (например, большинство стран в Западной Европе, Канада, Соединенные Штаты Америки, Австралия и Новая Зеландия) до более 40 случаев на 100 000 населения в большинстве стран региона Африки и в трех странах в Азии с высоким уровнем бремени ТБ (Бангладеш, Камбоджа и Мьянма). Глобальные показатели смертности от ТБ (за исключением случаев смерти среди ВИЧ-инфицированных больных) 2 снизились на 45% с 1990 года; текущий прогноз говорит о том, что намеченная Партнерством «Остановить ТБ» цель сократить вдвое уровень смертности от туберкулеза к 2015 году, по сравнению с базовым уровнем 1990 года, будет достигнута (Рисунок 2.6). Отмечается снижение смертности от ТБ во всех шести регионах ВОЗ (Рисунок 2.13). Задача, намеченная на 2015 год, уже выполнена в странах региона Америки (с 2004 года) и Западной части Тихого океана (с 2002 года); она также может быть достигнута в регионе Восточного Средиземноморья. Среди других трех регионов большие шансы для выполнения поставленной задачи имеет Юго-Восточная Азия. Показатель смертности от ТБ снижается в большинстве из 22 стран с высоким уровнем бремени ТБ (Рисунок 2.14), хотя существует значительная неопределенность в отношении показателей и тенденций в показателях смертности в некоторых странах, особенно в Зимбабве, Мозамбике, Нигерии и Южно-Африканской Республике.

International statistical classification of diseases and related health problems, 10th revision (ICD-10), 2nd ed. Geneva, World Health Organization, 2007. 2 Тенденции в показателях смертности ограничены данными о смерти от ТБ среди ВИЧ-отрицательных людей, учитывая, что смерть от ТБ среди ВИЧ-инфицированных людей кодируется как смерть от ВИЧ-инфекции в МКБ-10. 1

Доклад о глобальной борьбе с туберкулезом 2013

19

рисунок 2.12

Оценочные показатели смертности от ТБ, за исключением случаев смерти от туберкулеза, сочетанного с ВИЧ-инфекцией, 2012 год

Расчетное число случаев смерти от ТБ на 100 000 населения 0–0.9 1–3.9 4–9.9 10–19 20–39 ≥40 Нет данных Не применимо

рисунок 2.13

Тенденции в оценочных показателях смертности от туберкулеза за период 1990–2012 годы и прогноз по показателям смертности от туберкулеза на 2013–2015 годы по регионам ВОЗ. В расчетные показатели смертности от ТБ не входят данные о смертности от ТБ, сочетанного с ВИЧ-инфекцией. Затененные области представляют собой диапазоны неопределенности a. Горизонтальные пунктирные линии показывают цели Партнерства «Остановить ТБ» по снижению на 50% показателя смертности от ТБ к 2015 году по сравнению с 1990 годом. Другие пунктирные линии демонстрируют перспективную оценку до 2015 года. Африка 60 Америка Восточное Средиземноморье

6 40

40 Показатель на 100 000 населения в год

4 20 2

20

0 Европа 7.5

0 Юго-Восточная Азия

0 Регион Западной части Тихого океана 20

60

40 5.0 20

15 10

2.5

5 0 1990 1995 2000 2005 2010 2015 1990 1995 2000 2005 2010 2015 0 1990 1995 2000 2005 2010 2015

0

a

Диапазон неопределенности сужается по мере увеличения доли данных ЗАГС в показателе региональной смертности или по мере совершенствования точности и качества первичных данных.

20

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рисунок 2.14

Тенденции в оценочных показателях смертности от туберкулеза за 1990–2012 годы и прогноз по показателям смертности от туберкулеза на 2013–2015 годы, 22 страны с высоким бременем туберкулеза. Оценки показателей смертности от ТБ исключают случаи смерти от ТБ, сочетанного с ВИЧ-инфекцией. Горизонтальные пунктирные линии представляют собой цели Партнерства «Остановить ТБ» по сокращению на 50% показателя смертности к 2015 году, по сравнению с 1990 годом. Другие пунктирные линии показывают прогнозы до 2015 года а. Неопределенность обусловлена изменениями, внесенными в данные о смертности из систем ЗАГС, которые сообщили страны (данные о смертности из систем ЗАГС отмечены символом «x»). Дальнейшее разъяснение методов приводится в Приложении 1. Афганистан 90 60 30 0 50 0 100

Бангладешb 7.5 5.0 2.5 0

Бразилия 60 40 20 0

Вьетнам 100 50 0

ДР Конго

Зимбабве 100 50 40 20 0

Индия 100 75 50 25

Индонезия 300 200 100 0

Камбоджа 40 20 0

Кения

Показатель на 100 000 населения в год

0

0

Китай 20 15 10 5 0 300 200 100 0

Мозамбик 200 150 100 50 0

Мьянма 150 100 50 0

Нигерия 60 40 20 0

ОР Танзания

Пакистан 20 100 50 0 15 10 5 0

Российская Федерация 40 20 0

Таиланд 200 100 0 1990 1995 2000 2005 2010 2015

Уганда 60 40 20 0 1990 1995 2000 2005 2010 2015

Филиппины

Эфиопия 60 40 20 0 1990 1995 2000 2005 2010 2015

ЮАР 150 100 a

1990 1995 2000 2005 2010 2015

50 0 1990 1995 2000 2005 2010 2015

b

Диапазон неопределенности сужается по мере повышения качества и обеспечения полноты данных из систем ЗАГС. Оценка бремени ТБ не была одобрена НПТ Бангладеш; совместная переоценка будет проводиться после завершения исследования по изучению распространенности ТБ, запланированного на 2014 год.

2.4 Cовершенствование методов оценки бремени туберкулеза: Глобальная целевая группа ВОЗ по оценке воздействия туберкулеза Оценочные данные по заболеваемости, распространенности и смертности от туберкулеза и тенденции в динамике показателей, представленные в  Разделах 2.1–2.3, основаны на использовании наиболее точных имеющихся данных и применении аналитических методов. Тем не менее, остаются значительные возможности для улучшения качества данных и определения более точных тенденций в эпидемическом процессе по туберкулезу. Заключительный раздел этой главы содержит описание последних предпринятых мер по улучшению оценки бремени ТБ, под эгидой Глобальной целевой группы ВОЗ по оценке воздействия ТБ. Эта Целевая группа была создана в 2006 году и включает в себя представителей ведущих технических и финансовых партнеров и представителей стран с высоким бременем ТБ 1. На своем втором совещании в декабре 2007 года, Глобальная целевая группа ВОЗ по оценке воздействия ТБ определила три стратегических направления деятельности 2:

•• совершенствование деятельности органов статистического наблюдения по проведению расчетов с использованием прямых методов: заболеваемости — на основе данных системы регистрации случаев туберкулеза и смертности — на основе данных о смертности из органов ЗАГС; 1

Многие страны с высоким бременем ТБ участвуют в работе Целевой группы. В числе партнеров, которые активно участвуют в работе Целевой группы, Центры по контролю заболеваний и профилактике США, Европейский центр по профилактике и контролю заболеваний, Глобальный фонд, Министерство здравоохранения Великобритании, Фонд по туберкулезу KNCV, Лондонский институт гигиены и тропической медицины, Научно-исследовательский институт туберкулеза Японии, Международный союз по борьбе с туберкулезом и легочными заболеваниями (IUATLD) и Агентство США по международному развитию (USAID). 2 TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper no. 2; WHO/ HTM/TB/2009.416). Доступно на: www.who.int/tb/publications/2009/ impactmeasurementpolicy/

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•• проведение специальных исследований по изучению распространенности ТБ в ряде стран мира, которые находятся в фокусе внимания и соответствуют эпидемиологическим и другим установленным критериям; и •• периодический пересмотр и уточнение методов, используемых для преобразования данных эпиднадзора и специальных исследований, в оценочные показатели заболеваемости, распространенности и смертности от ТБ. В 2008 и  2009 годах методы были тщательно рассмотрены и уточнены приглашенной Целевой группой экспертов. В марте 2010 года на совещании группы в полном составе были обсуждены и  одобрены обновления. Текущие методы подробно описаны в  Приложении 1, а проведение пересмотра методов планируется в 2014 году (Bставка 2.1). В следующих разделах основное внимание сосредоточено на двух других стратегических областях работы: укреплении эпиднадзора и проведении национальных специальных исследований по изучению распространенности ТБ. Дополнительные сведения доступны на веб-сайте Целевой группы 1.

может внести реальные изменения в процесс формирования системы эпиднадзора за ТБ в мире. Был определен первоначальный перечень из 25 приоритетных стран.

Исследования по изучению полноты регистрации для измерения или оценки занижения отчетности по туберкулезу Одним из стандартов в контрольном списке по оценке системы эпиднадзора за ТБ является требование информировать национальную систему эпиднадзора о всех выявленных случаях туберкулеза. Для этого необходимо выполнить два критерия, а именно: отчетность по ТБ должна быть обязательной по закону, регистрация выявленных случаев ТБ в стране должна быть равна или превышать 90%, эти данные должны поступать в национальные органы здравоохранения, что должно подтверждаться с помощью проведения специальных исследований по изучению полноты регистрации на национальном уровне. К настоящему времени, лишь немногие страны провели подобные исследования, но их число растет, поэтому оценка уровня и тенденций заболеваемости туберкулезом будут совершенствоваться. Даже при условии получения данных о значительном занижении регистрируемой заболеваемости и соответственно отсутствии возможности использовать эти данные для расчета показателя истинной заболеваемости, проведение исследований по изучению полноты регистрации больных может быть использовано для определения уровня недоучета и получения более точных оценок бремени болезни, а также для определения направлений для сотрудничества между государственными и частными медицинскими организациями (см. также Главу 3, Раздел 3.2.1). В 2012 году Глобальная целевая группа по оценке воздействия ТБ завершила работу над руководством по организации исследования по изучению полноты регистрации больных, содержащим информацию о том, как проводить анализ полученных данных и составлять отчеты о результатах 2. За последние 10 лет исследования по изучению полноты регистрации были проведены в Великобритании, Египте, Ираке, Йемене, Нидерландах, Пакистане и Французской Гвиане в сочетании с методом первичного и повторного обследования. Во Вставке 2.6 кратко излагаются результаты исследования в Ираке.

2.4.1 Совершенствование систем эпиднадзора В числе причин неопределенности в текущих оценочных показателях заболеваемости ТБ лежит необходимость использовать экспертное мнение о числе диагностированных, но не зарегистрированных в системе эпиднадзора случаев, и числе не диагностированных случаев (Раздел 2.1). Основные проблемы при оценке смертности от ТБ заключаются в отсутствии эффективно функционирующих общенациональных систем ЗАГС во многих странах, особенно в странах Африки и в некоторых странах Азии (Рисунок 2.11). Для выполнения перспективной цели по непосредственному измерению бремени ТБ и его тенденций в части заболеваемости ТБ по данным эпиднадзора и для оценки смертности от ТБ на основании данных ЗАГС, необходимо всемерно укреплять системы статистического наблюдения во многих странах. На Рисунке 2.11 показаны страны, в которых наиболее надежные данные о смертности были доступны в 2012 году.

Контрольный список стандартов и критериев для оценки систем эпиднадзора за туберкулезом Для совершенствования работы системы эпиднадзора в части усиления ее возможности давать оценки уровней заболеваемости и смертности от ТБ с использованием прямых методов требуется четкое понимание того, как должна выглядеть идеальная система эпиднадзора и методы для оценки работы существующих систем эпиднадзора за ТБ. Итогом большой работы, проделанной в 2011 и 2012 годах, стала разработка Контрольного списка для оценки системы эпиднадзора за ТБ (далее — Контрольный список), который определяет стандарты и соответствующие критерии, обязательные для того, чтобы данные из систем эпиднадзора и систем ЗАГС можно было использовать для измерения уровней заболеваемости и смертности от ТБ в данной стране с помощью прямых методов (Вставка 2.4). Использование Контрольного списка началось в январе 2013 года, и он применяется во все большем количестве стран (Рисунок 2.15) как основа для определения, каким стандартам данные уже соответствуют и какие нужны инвестиции, чтобы восполнить оставшиеся пробелы. Эта работа проводится в тесном сотрудничестве с Глобальным фондом и данные, полученные благодаря контрольным спискам, можно использовать в процессе подготовки заявки на грант Глобального фонда; с выводами также могут ознакомиться национальные правительства и другие партнеры (Bставка 2.5) при рассмотрении вопросов о возможных инвестициях. Более 100 стран с низким и средним уровнем доходов получают гранты Глобального фонда на ТБ программы; этот подход имеет большой потенциал, он 22

Электронная система регистрации и отчетности Некоторые стандарты в контрольных списках по оценке системы эпиднадзора за ТБ касаются качества данных. На всех региональных и национальных семинарах, которые прошли в период с 2008 по 2013 годы, было подчеркнуто, что гораздо проще оценивать качество данных систем эпиднадзора за ТБ в тех странах, где внедрены системы учета больных ТБ по индивидуальным данным и отчетность в электронном виде. Помимо того, что эти системы весьма полезны для регистрации и отчетности, они имеют существенные преимущества по сравнению с системами, работающими исключительно на бумажных носителях. А именно: •• Более совершенная программная деятельность и управление ресурсами на основе использования сотрудниками интерактивных данных. Это может помочь персоналу предотвратить прерывание лечения и способствовать лучшему фармацевтическому менеджменту (в том числе помогает избежать нехватки лекарственных препаратов). 1 2

www.who.int/tb/advisory_bodies/impact_measurement_taskforce Assessing tuberculosis underreporting through inventory studies. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2012.12). Доступно на: www.who.int/tb/publications/inventory_studies/en/index.html

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Вставка 2.4

Контрольный список стандартов и критериев для оценки системы эпиднадзора за ТБ Основная цель эпиднадзора за ТБ — обеспечить точный ежегодный учет числа новых случаев заболевания ТБ и числа случаев смерти от ТБ и иметь возможность оценить тенденции эпидемического процесса во времени. В некоторых странах эпиднадзор за ТБ уже соответствует этим требованиям, но в ряде стран существуют значительные пробелы. Например, не регистрируются данные о диагностированных случаях ТБ в частном секторе в странах с низким и средним уровнем доходов; не все больные туберкулезом могут получить доступ к медицинской помощи, и поэтому такие случаи не диагностируются вообще. Более того, во многих странах система ЗАГС не работает с таким охватом и качеством, как это необходимо для точного определения числа случаев смерти от ТБ (Раздел 2.3). Контрольный список стандартов и критериев для оценки системы эпиднадзора за ТБ и систем ЗАГС был разработан для решения следующих задач: •• Оценка способности общенациональной системы эпиднадзора за ТБ осуществлять полный учет случаев ТБ и смертей от ТБ. •• Выявление пробелов в организации работы общенациональной системы эпиднадзора, которые следует ликвидировать. Информацию, полученную благодаря контрольным спискам, можно использовать для определения стран, в которых система эпиднадзора ежегодно обеспечивает точную регистрацию случаев заболевания ТБ и смерти от ТБ, и для определения мер, необходимых для усиления эпиднадзора в странах, в которых выявлены пробелы в этой работе a. Страны, принадлежащие к первой категории, могут рассматриваться как страны, имеющие данные эпиднадзора, необходимые для прямой оценки заболеваемости и/или смертности от ТБ. Контрольный список был разработан группой экспертов в области эпиднадзора с учетом предложений специалистов, высказанных на совещаниях, организованных ВОЗ в сентябре 2011 года и в мае 2012 года. Контрольный список прошел два раунда полевых испытаний в одиннадцати странах: Бразилии, Египте, Кении, Китае, Нидерландах, Соединенном Королевстве (Великобритании), Соединенных Штатах Америки, Таиланде, Уганде, Эстонии и Японии. Контрольный список содержит десять страниц и состоит из двух частей. Часть А состоит из 18 вопросов, которые используются для характеристики национальной системы эпиднадзора за ТБ; они обеспечивают основу для части B, которая состоит из тринадцати стандартов и связанных с ними критериев. Стандарты представляют собой общие характеристики, которые определяют высокую эффективность системы эпиднадзора за ТБ; девять стандартов связаны с регистрацией случаев ТБ и один связан с регистрацией случаев смерти от ТБ. Есть три дополнительных стандарта, которые могут быть использованы для оценки того, способна ли национальная система эпиднадзора за ТБ обеспечить прямой показатель числа случаев ЛУ ТБ, выявить случаи ТБ у ВИЧ-инфицированных больных и случаи туберкулеза среди детей. Для каждого из тринадцати стандартов определены контрольные показатели (в количественном выражении везде, где это возможно), которые позволяют определить, насколько уровень работы системы соответствует стандарту. В приложении — Руководстве для пользователя — разъясняется суть каждого стандарта и соответствующих эталонных показателей и методы, которыми следует пользоваться для определения соответствия тем или иным стандартам и нормативам. В Руководстве также приводятся иллюстрации. На основе заполненных контрольных списков страны могут определить основные действия, необходимые для решения выявленных проблем в работе систем эпиднадзора и систем ЗАГС. Предполагается, что оценка эпиднадзора за ТБ с помощью контрольных списков будет проходить каждые три-пять лет, но такая работа может проводиться и чаще. На основе рекомендаций 2012 года Контрольной группы технической оценки Глобального фонда и Соглашения о сотрудничестве между Фондом и ВОЗ оценка эпиднадзора за ТБ с использованием контрольного списка все чаще включается в механизм предоставления грантов Фонда. Таким образом, оценки с использованием контрольного списка следует совместить с миссиями по оценке ТБ программ, продлением грантов Глобального фонда и разработкой концепции заявки, необходимой для доступа к финансированию в соответствии с новой моделью финансирования Фонда (НФМ), запущенной в 2013 году. Результаты затем могут быть использованы для подготовки или обновления плана инвестиций в мониторинг и оценку, которые могут получить поддержку от Глобального фонда, а также от национальных бюджетов и других партнеров. Эта совместная работа с Глобальным фондом имеет огромный потенциал для укрепления эпиднадзора за ТБ в более, чем ста странах мира, которые получают гранты. Проведение оценок в 15 странах с высоким уровнем бремени ТБ рассматриваются в качестве приоритета на 2013 и 2014 годы; к августу 2013 года в одиннадцати странах с высоким бременем болезни, в том числе в восьми странах, которые получают гранты фонда, оценка была завершена (Рисунок 2.15). С Контрольным списком и Руководством для пользователя можно ознакомиться на сайте Глобальной целевой группы ВОЗ по оценке воздействия ТБ: http://www.who.int/tb/advisory_bodies/ impact_measurement_taskforce/en/ a

Контрольный список не позволяет проводить оценку других программных мероприятий, например, ухода за больными, получения результатов лабораторных исследований или фармацевтический менеджмент.

•• Более эффективный эпиднадзор, который упрощает для учреждений, традиционно не связанных с НПТ, таких как больницы, медицинские учреждения пенитенциарной системы и частного сектора, подготовку и предоставление информации о случаях ТБ, поскольку избавляет от необходимости подготовки ежеквартальных отчетов на бумажных носителях. •• Совершенствуется процесс анализа и использования данных, поскольку появляется возможность вносить готовые данные в статистические пакеты. Затем результаты делаются доступными политикам значительно быстрее, они также позволяют очень быстро определить возникновение эпидемической вспышки. •• Повышается качество данных, поскольку можно применять автоматические проверки, которые помогают выявлять дублированные данные или неправильно классифицированные случаи и удалять их из системы (что очень сложно или невозможно сделать на национальном уровне при использовании бумажных носителей). Также это упрощает внедрение новых параметров данных.

•• Электронные системы позволяют определить кластеры случаев по месту и времени, в том числе и кластеры лекарственно устойчивых случаев, что позволяет обеспечить раннее расследование и сдерживание эпидемий. Информация о  странах, располагающих национальными электронными системами регистрации больных ТБ по индивидуальным данным, приводится на Рисунке 2.16. Недавний пример внедрения электронной системы учета и отчетности по индивидуальным данным в Кении описан во Bставке 2.7. С разработанным недавно руководством по внедрению системы электронного учета и отчетности по случаям ТБ, подготовленным ВОЗ и партнерскими организациями в 2011 году, можно ознакомиться на сайте Консультативной группы 1.

1

Electronic recording and reporting for TB care and control. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2011.22). Доступно на: www.who.int/tb/publications/electronic_recording_reporting

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Вставка 2.5

Контрольный список стандартов и критериев для оценки системы эпиднадзора за туберкулезом и систем ЗАГС в Индонезии: от внедрения до мобилизации ресурсов Оценка национальной системы эпиднадзора за ТБ в Индонезии, с помощью Контрольного списка стандартов и критериев для оценки системы эпиднадзора за ТБ и систем ЗАГС (см. Вставку 2.4) была проведена в феврале 2013 года, одновременно с оценкой национальной программы по борьбе с ТБ (НПТ). Был осуществлен тщательный анализ всех доступных на национальном, региональном и районном уровне статистических данных по регистрируемой заболеваемости туберкулезом в динамике, и других доступных данных эпиднадзора. Были рассмотрены руководства НПТ, методические рекомендации, учебные материалы, годовые отчеты, журналы регистрации и другие формы отчетности. Другая информация была собрана с помощью интервью с сотрудниками НПТ, партнерами и другими заинтересованными сторонами. Система эпиднадзора за туберкулезом основывается на ежеквартальной отчетности по выявленным случаям с уровня медицинских учреждений, направляемой последовательно на уровень районов, регионов и наконец, на национальный уровень. В настоящее время работа переводится на оперативный режим (онлайн) — ведутся электронные записи по каждому индивидуальному случаю заболевания и в системе отчетности в целом. Определения случаев ТБ согласуются с международными дефинициями. В целом 483 из 497 районов страны представили все квартальные отчеты на национальном уровне в 2011 году. Система обеспечивает данными, которые соответствуют внешним требованиям, но не согласуются с национальными требованиями. Поскольку отчетность по случаям туберкулеза не является обязательной по закону, НПТ получает неполную информацию, так как на национальный уровень не доводятся сведения о всех случаях ТБ; уровень недоучета числа больных от частного до общественного сектора никогда не был исследован в общенациональном масштабе. В стране происходит неуклонное улучшение доступа к медицинскому обслуживанию, но этот уровень еще не достаточен для обеспечения доступа к диагностике и лечению туберкулеза для всего населения. В репрезентативной выборке территорий внедряется система регистрации случаев смерти через систему ЗАГС с обеспечением стандартного кодирования причин смерти. До настоящего времени исследования по изучению распространенности лекарственноустойчивых штаммов возбудителя туберкулеза были проведены только на уровне отдельных провинций; охват тестированием на ВИЧ больных ТБ увеличивается, но все еще остается на низком уровне. Наконец, диагностика ТБ среди детей проводится лишь в ограниченном числе населенных пунктов. Были намечены мероприятия для устранения недостатков, которые были определены в процессе использования контрольных списков (см. Таблицу B2.7.1). Одним из главных приоритетов является обеспечение функционирования системы ЗАГС в отношении регистрации случаев смерти в выборке районов, стоимость внедрения которой составляет 0, 5–1 долл. США на душу населения (эквивалентно примерно 2,5–5 млн долл. США в год для населения в 5 млн человек). Объем необходимого финансирования других мероприятий, изложенных в Таблице B2.7.1, составляет 1 млн долл. США, причем одним из основных приоритетов (в соответствии с ключевыми рекомендациями, вытекающими из оценки программы в 2013 году) является осуществление политики обязательного уведомления о случаях заболевания. Посредством постоянных консультаций между НПТ, ВОЗ и Глобальным фондом были определены и обеспечены необходимые объемы финансирования для реализации инвестиционного плана. На этом примере показано, как контрольный лист может использоваться для проведения стандартизованной оценки системы эпиднадзора за ТБ для определения достигнутых успехов, а также для выявления оставшихся пробелов, которые предстоит восполнить, и обеспечения финансирования инвестиционного плана для ликвидации пробелов при поддержке со стороны Глобального фонда.

Таблица B2.7.1

Инвестиционный план для укрепления эпиднадзора в Индонезии, составленный по результатам применения Контрольного списка и перечня стандартов и критериев для оценки систем эпиднадзора за ТБ и систем учета по линии ЗАГС (всего бюджет $ 1 млн долл. США, за исключением системы регистрации по линии ЗАГС, которая финансируется отдельно) Мероприятие n Система ЗАГС: совершенствование регистрации данных по линии ЗАГС путем обеспечения сбора данных на национальной репрезентативной выборке территорий, охваченных системой полной регистрации n Специальное исследование для определения уровня неучтенных случаев в системе эпиднадзора n Создание потенциала для управления данными и статистического анализа путем подготовки специалистов на курсах и выделения дополнительных ставок на центральном уровне n Применение на практике Пособия по проведению оценки доступности и готовности медицинских служб и проведение оценки качества данных, предоставляемых медицинскими учреждениями n Оценка комплексной системы информации по туберкулезу. Этап 2 в 2014 году n Реализация политики обязательной регистрации случаев в системе эпиднадзора n Анализ доступных данных о смертности n Специальное исследование по изучению распространенности ЛУ ТБ или внедрение системы дозорного эпиднадзора n Специальное репрезентативное исследование по изучению распространенности ВИЧ-инфекции среди больных ТБ n Корректирующие действия, необходимые для свода всех отчетов из Папуа

2.4.2 Национальные исследования по изучению распространенности туберкулеза До 2007 года лишь немногие страны осуществили исследования по изучению распространенности в национальном масштабе. В 1990-х годах они были проведены лишь в Китае, Мьянме, Республике Корея и Филиппинах. До 2009 года, национальные исследования в Африке были проведены в период с 1957 по 1961 годы, за исключением Эритреи, где исследование проводилось в 2005 году. С 2002 по 2008 годы обычно проводилось по одному исследованию в год. В 2007 году Глобальная целевая группа ВОЗ по оценке воздействия ТБ определила 53 страны, которые соответствуют 24

эпидемиологическим и другим критериям для проведения исследований по изучению распространенности туберкулеза. Была определена группа из 22 стран мира для получения конкретной поддержки в период до 2015 года, в которую вошли страны Африки: Гана, Замбия, Кения, Малави, Мали, Мозамбик, Нигерия, Объединенная Республика Танзания, Руанда, Сьерра-Леоне, Уганда, Эфиопия и Южно-Африканская Республика; и страны Азии: Бангладеш, Вьетнам, Индонезия, Камбоджа, Китай, Мьянма, Пакистан, Таиланд и  Филиппины. С  начала 2008 года были предприняты значительные усилия для оказания поддержки странам в разработке, осуществлении, анализе и подготовке отчетности о результатах исследований. По итогам

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рисунок 2.15

Страны (оранжевый), использующие Контрольные списки и перечни стандартов и критериев для оценки систем эпиднадзора за туберкулезом, по состоянию на август 2013 года

Вставка 2.6

Изучение полноты регистрации случаев туберкулеза: пример из Ирака Для изучения полноты регистрации проводится сравнение числа случаев ТБ, соответствующих стандартному определению, диагностированных во всех или в выборке из государственных и частных медицинских учреждений с данными эпиднадзора по зарегистрированным случаям ТБ, то есть по которым поступили извещения в местные и национальные органы эпиднадзора. Это позволяет количественно определить уровень занижения регистрации диагностированных случаев. В определенных обстоятельствах результаты проведенной «инвентаризации» могут быть объединены с методом моделирования с использованием данных первичного и повторного обследования определенных групп населения под названием «capture–recapture analysis» для оценки заболеваемости. Руководство ВОЗ по разработке и осуществлению подобных исследований, проведению анализа и составлению отчетности по их результатам было опубликовано в 2013 году. Результаты исследования в Ираке a, которое было завершено в 2011 году, показаны ниже. Число случаев ТБ, выявленных тремя типами организаций, предоставляющих медицинские услуги населению, было изучено в течение трех месяцев в восьми случайно выбранных провинциях страны (из общего количества равного 18). Общее количество выявленных случаев составило 1 980. Количество выявленных случаев, которые не попали в отчетность НПТ, составило 16% от общего числа выявленных случаев, то есть уровень неполной отчетности составил 16%. Моделирование на основе модели первичного и повторного обследования позволило определить дополнительные 473 случая (95%, доверительный интервал: 394–565), не выявленные ни одной из трех групп организаций, предоставляющих медицинские услуги. Эти результаты позволили сделать оценку, что в Ираке в 2011 году имели место 14 500 новых случаев ТБ (что меньше по сравнению с предыдущей оценкой) и что около 60% случаев были выявлены (что выше по сравнению с предыдущей оценкой в 48%). Оценка результатов обследования была выше обновленных оценок заболеваемости ТБ. Примеры включают:

Рисунок B2.6.1

Результаты исследования по изучению полноты регистрации (случаев туберкулеза) в Ираке, 2011 год НПТ (n=1 673) 988 416 25 244 Общее количество выявленных случаев (N=1 980) 99 9 Государственный сектор (n=377) 199

Частный сектор (n=649)

•• Обновленные оценки имели решающее значение для разработки национального стратегического плана и для оценки прогресса в достижении ЦТР к 2015 году. •• Национальный стратегический план включает в себя мероприятия, предназначенные для устранения причин занижения данных, которые были выявлены в ходе исследования. •• Картирование всех медицинских учреждений, оказывающих помощь больным с заболеваниями органов дыхания в районе проведения исследования (которое охватило 50% территории страны), представляет собой основу для устойчивого вовлечения медицинских организаций всех форм собственности в оказание медицинской помощи посредством инициатив государственночастных структур. a

Huseynova S et al. Estimating tuberculosis burden and reporting in resourcelimited countries: a capture-recapture study in Iraq. International Journal of Tuberculosis and Lung Disease. 2013;17(4):462–7.

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рисунок 2.16

Наличие национальных персонифицированных электронных баз данных о больных туберкулезом, 2012 год

Все пациенты с ТБ Только пациенты с МЛУ-ТБ Нет Нет данных Не применимо

рисунок 2.17

Глобальный прогресс в осуществлении национальных исследований по изучению распространенности туберкулеза, проведенные (2002–2012 годы) и запланированные (2014–2017 годы) 9 8 Азия – ГФС   Африка – ГФС   Нет – ГФС Кения Мозамбик

Количество обследований

7 6 5 4 3 2 1 0 Филиппины Камбоджа Малайзия Индонезия Эритрея Таиланд Вьетнам Бангладеш Мьянма Китай

Глобальные фокусные страны (ГФС), выбранные Глобальной целевой группой ВОЗ по измерению последствий ТБ Эфиопия Камбоджа Пакистан ЛНДР

ЮАР Уганда Нигерия Руанда ОР Танзания

Гана Малави Замбия Индонезия Судан

Бангладеш КНДР Монголия Непал Зимбабве Мьянма Филиппины Вьетнам

Таиланд Гамбия

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014–2015

2016–2017

была подготовлена новая редакция руководства 1, осуществлялась координация технического содействия, проводилась экспертная оценка протоколов исследований, организовывались учебно-ознакомительные поездки и промежуточные обзоры исследований, глобальные и региональные семинары по разработке планов исследований и их реализации, обмену опытом и результатами наблюдений между странами. Получила развитие и серьезную поддержку концепция Азия–Азия, Азия–Африка и Африка–Африка (‘AA’). В результате шести лет значительных усилий на национальном, региональном и глобальном уровнях был достигнут беспрецедентный прогресс (Рисунок 2.17). Если обследования 1

TB prevalence surveys: a handbook. Geneva, World Health Organization, 2011 (WHO/HTM/TB/2010.17). Доступно на: www.who.int/tb/advisory_bodies/impact_measurement_taskforce/resources_documents/ thelimebook/

будут осуществляться по графику, то более 20 исследований будет проведено в период с 2011 по 2015 годы. Пять национальных исследований распространенности ТБ были проведены в 2012 году (в Гамбии, Нигерии, Объединенной Республике Танзании, Руанде и Таиланде) и еще пять начнутся или будут завершены в 2013 году (в Гане, Замбии, Индонезии, Малави и Судане). Эти исследования обеспечивают объективную оценку бремени болезни, часто впервые в истории, их итоги будут использоваться для уточнения оценки бремени болезни по мере поступления результатов (Вставка 2.1). Исследования распространенности ТБ также представляют богатый источник данных для обоснования программной политики и стратегии. Несмотря на то, что результаты носят предварительный характер до завершения анализа в конце 2013 года (Bставка 2.1), результат последнего исследования распространенности ТБ в Нигерии в 2012 году достоин самой высокой оценки (Bставка 2.8). Что касается других недавно

26

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 2.7

Внедрение и использование инновационной электронной системы эпиднадзора и управления в Кении НПТ в Кении развернула инновационную электронную систему для укрепления эпиднадзора и управления, которая получила название TIBU (в переводе с языка суахили это означает лечение). Кроме запуска электронной версии стандартных систем регистрации случаев ТБ по регионам, система TIBU широко использует обширные сети мобильной связи страны и мобильных телефонов, с которых можно производить платежи для больных МЛУ-ТБ; мобильные телефоны также используются в помощь тем, кто проходит лечение, поскольку при помощи телефонов можно осуществлять платежи через популярную в стране систему мобильных платежей M-Pesa. Система TIBU будет использоваться и для управления поставками лекарственных препаратов, сбора лабораторных данных и обеспечения расходных материалов. В основу TIBU заложена общенациональная персонифицированная база данных по случаям ТБ, в которой сохраняются все данные по каждому конкретному пациенту (в том числе и с МЛУ-ТБ). Пользователи имеют доступ к системе через Интернет браузер, или при помощи приложения к Android. НПТ предоставила каждому региональному координатору по ТБ и лепре планшетный компьютер с операционной системой Android и с SIM-картой для подключения к Интернету через телефонную мобильную сеть. Координаторы имеют доступ к системе во время плановых посещений всех учреждений, которые осуществляют диагностику и лечение ТБ и могут вводить в нее данные по пациентам с ТБ, которые они получают во время таких посещений. Данные передаются непосредственно в национальную базу через сеть мобильной связи. Данные сохраняются на планшете, если прямая связь недоступна, и затем передаются в общенациональную базу данных при первой возможности выйти в сеть. Система позволяет автоматически генерировать разного рода отчетные документы, такие как стандартные квартальные отчеты, диаграммы и карты для всех уровней административных единиц страны. Сотрудники НПТ и разработчики работают в тесном взаимодействии с другими ведомствами Министерства здравоохранения для того, чтобы обеспечить полное соответствие TIBU национальным стандартам и возможность взаимодействовать с другими информационными системами Минздрава a. TIBU использует схему кодирования, которая применяется в Кении (http://www. ehealth.or.ke/facilities/facilitytypes.aspx), поэтому разработчики имели возможность выстроить беспрепятственное взаимодействие системы с Информационной системой охраны здоровья Кении b, которая обеспечивает руководителей здравоохранения страны на районном, региональном и национальном уровне показателями по всему спектру системы здравоохранения, в том числе и по ТБ. Это позволяет систематически ежеквартально обновлять стандартные показатели по ТБ в системе министерства. TIBU разрабатывалась поэтапно. Начало было положено в 2007 году и первоначально предполагалось запустить систему на персональных цифровых электронных записных книжках (PDAs). Однако сложности на первоначальном этапе запуска системы совпали с быстрым развитием, доступностью и снижением стоимости мобильных устройств типа Android, а также с широким распространением мобильных телефонов, что привело к решению о переходе на приложение к Android, которое можно использовать на смартфонах и планшетных компьютерах. На будущее намечено использование системы не только для работы по ТБ и лепре, но также с больными астмой и другими легочными заболеваниями, интеграция с системой управления лабораториями и, наконец, если позволят ресурсы, распространить планшеты на более, чем 4 000 медицинских учреждений, где осуществляется диагностика и лечение ТБ. a

В мае 2013 года Всемирная Ассамблея здравоохранения приняла резолюцию WHA66.24 по продвижению такой стандартизации и оперативной совместимости информационных систем здравоохранения (http://apps.who.int/gb/ebwha/pdf_files/WHA66/A66_ R24-en.pdf).  b Разработана на основе платформы DHIS2 с открытым исходным кодом http://www.dhis2.org/

Вставка 2.8

Национальное исследование по изучению распространенности туберкулеза в Нигерии в 2012 году: выводы для программной деятельности Проведение первого в истории Нигерии национального исследования по изучению распространенности ТБ началось в феврале 2012 года, мероприятия на местах (в обследовании приняли участие 70 географических территорий) были завершены к октябрю 2012 года. Нигерия, вслед за Эфиопией (2011 год), стала второй страной Африки, успешно завершившей национальное исследование о распространенности ТБ в соответствии с действующим руководством ВОЗ. В целом обследование охватило 43 439 человек в возрасте пятнадцати лет и старше. Результаты показали, что 75% ранее не выявленных случаев ТБ, которые были диагностированы в ходе исследования, имели положительный результат микроскопии мокроты и классические симптомы туберкулеза, которые удовлетворяют критериям для проведения скрининга на ТБ, утвержденным в стране (этот показатель был выше, чем во всех предыдущих исследованиях, начиная с 2002 года). Сравнение числа случаев ТБ с положительной микроскопией и числа зарегистрированных случаев в той же возрастной группе показал коэффициент «распространенность: число зарегистрированных случаев» равный 5 (что также выше, чем в других исследованиях, начиная с 2002 года). Данные исследования также свидетельствуют о том, что географически распространенность туберкулеза неравномерна, начиная от очень низких показателей до чрезвычайно высокого уровня распространенности в разных кластерах, участвовавших в исследовании бремени туберкулеза. По результатам исследования был сделан важный вывод, что главным приоритетом является улучшение качества основных диагностических и лечебных услуг и расширение доступа к ним. При наличии качественных услуг DOTS можно предположить, что распространенность случаев с типичными симптомами туберкулеза и коэффициент «распространенность: число зарегистрированных случаев» будет намного ниже. Второй вывод заключается в том, что особое внимание требуется уделять географическим «горячим точкам», где бремя болезни является самым высоким.

проведенных исследований о распространенности, то по некоторым из них национальные доклады уже являются общедоступными (например, из Камбоджи, Китая, Мьянмы и Эфиопии), а другие находятся в процессе подготовки. По этим и другим недавно проведенным исследованиям о распространенности ТБ готовятся статьи для рецензируемых журналов. ВОЗ, а также страны-члены ВОЗ и технические партнеры, начали подготовку или планирование подведения итогов и обобщения основных результатов и выводов, полученных в процессе проведения национальных исследований по изучению распространенности туберкулеза в 2012 году, в мире и по

регионам ВОЗ. Работа над документом, обобщающим результаты и уроки, извлеченные из исследований, проведенных в 1990– 2012 годах в Азии, близится к завершению, и планируется подготовить аналогичный документ о последних исследованиях в Африке. Обобщенный синтез основных результатов недавних исследований распространенности ТБ, проведенных в Азии и Африке, будет использован для выработки глобальной политики по ТБ после 2015 года и стратегии действий. Сейчас ведется работа над этими документами. Эти глобальные и региональные итоговые документы будут широко распространяться по мере готовности, начиная с 2014 года.

Доклад о глобальной борьбе с туберкулезом 2013

27

Глава 3

Регистрируемая заболеваемость туберкулезом и результаты лечения Основные факты и выводы ■■ В 2012 году 6,1 млн больных ТБ были зарегистрированы НПТ и сообщены в ВОЗ, из них: 5,7 млн вновь выявленных больных ТБ и 0,4 млн ранее диагностированных пациентов, режим лечения которых был изменен. На Индию и Китай пришлось 39% зарегистрированных в 2012 году случаев туберкулеза в мире, на африканские страны — 23%, и на 22 СВБ — 82%. ■■ В 2011 году показатель успешности лечения достиг 87% как для всех новых случаев ТБ, так и для новых случаев туберкулеза легких с положительной микроскопией мокроты (наиболее заразные случаи). Необходимо усилить работу по повышению эффективности лечения в Европейском регионе, где уровень успешности лечения в 2011 году составил 72% для новых случаев и 65% для новых случаев с положительным мазком. ■■ Предоставление диагностики и лечения в соответствии со стратегией DOTS/«Остановить ТБ» привело к серьезным достижениям в сфере борьбы с ТБ. В период с 1995 по 2012 годы 56 млн человек успешно завершили лечение от ТБ в странах, которые приняли к руководству стратегию DOTS/«Остановить ТБ», что помогло спасти 22 млн жизней. ■■ Уровень выявления больных ТБ стабилизировался в последние годы, и в 2012 году составил 66% (диапазон 64–69%) от оценочного числа случаев заболевания. Разрыв между числом зарегистрированных случаев и оценочным числом случаев заболевания ТБ можно объяснить неполной регистрацией диагностированных случаев (например, диагностируемых в частном секторе) и гиподиагностикой в связи с ограниченным доступом к медицинской помощи и/или у больных, обратившихся в медицинские организации. Основные усилия необходимо направить на выявление максимально возможного числа больных, обеспечение регистрации случаев туберкулеза в национальных системах эпиднадзора и обеспечение выявленных больных лечением в соответствии с международными стандартами. ■■ В 2012 году большинство зарегистрированных больных туберкулезом относились к возрастной группе от 15 до 44 лет. На детей (в возрасте до 15 лет) пришлось 6% от всех зарегистрированных случаев. Соотношение мужчины: женщины составило 1,7 на глобальном уровне, колеблясь от 1,0 до 2,1 в шести регионах ВОЗ.

Наличие официальной системы статистического наблюдения за всеми выявленными больными ТБ, включая мониторинг лечения (учетные и отчетные формы), является одним из пяти компонентов глобальной стратегии борьбы с ТБ (DOTS), разработанной ВОЗ в середине 1990-х годов, и которая остается одним из основных элементов следующего этапа развития стратегии борьбы с ТБ — Стратегии «Остановить ТБ» (Глава 1). Глобальный мониторинг тенденций в регистрируемой заболеваемости и результатов лечения стал возможным, начиная с 1995 года, благодаря применению стандартизованных определений случаев туберкулеза и результатов лечения, рекомендованных ВОЗ, и внедрению в практику связанных с ними учетных и отчетных форм. Данные о числе лиц, зарегистрированных с диагнозом ТБ, взятых на лечение, и результаты лечения которых были документированы, регулярно собираются НПТ почти во всех странах и представляются в ВОЗ в рамках ежегодных циклов глобального сбора данных по ТБ (Глава 1). Данная глава состоит из четырех частей. Раздел 3.1 содержит информацию о регистрируемой заболеваемости ТБ по данным, представленным НПТ в 2012 году, в том числе стратификацию данных по типам случаев, возрасту и полу. В данном разделе также отражена доля больных, зарегистрированных в пенитенциарном секторе в Европейском регионе, и высокая заболеваемость туберкулезом в этом секторе. В Разделе 3.2 представлен и рассматривается вклад в общую регистрируемую заболеваемость случаев, зарегистрированных в рамках государственно-общественных и смешанных государственно-частных (ГЧС) инициатив в 29 странах, а также роль организации медицинской помощи на местном уровне в 13 странах. В Разделе 3.3 приводятся тенденции в регистрируемой заболеваемости в период с 1990 по 2012 годы и сравниваются эти тенденции с таковыми в оценочной заболеваемости ТБ. Оценочный коэффициент «зарегистрированные: оценочные случаи заболевания» (известный как «показатель выявления случаев туберкулеза» (ПВЗ) за отдельные годы также приведен в данном разделе. В  Разделе 3.4 приводятся последние данные о результатах лечения (для когорты пациентов, зарегистрированных в 2011 году), а также результаты лечения по всем когортам ежегодно, начиная с 1995 года.

3.1  Регистрируемая заболеваемость по типу заболевания, возрасту и полу в 2012 году Определения случаев заболевания ТБ, рекомендованных ВОЗ до конца 2012 года и использованных в глобальном сборе данных о ТБ в 2013 году, приведены во Вставке 3.1, несмотря на то, что данные определения не используются в Докладе о глобальной борьбе с ТБ в этом году. Следует отметить, что после двухлетних обсуждений, в марте 2013 года ВОЗ выпустила обновленное руководство по определению случаев и результатов лечения 1. Эти и связанных с ними алгоритмов предоставления отчетов  обновления были необходимы для учета случаев заболевания, 1

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/HTM/TB/2013.2). Geneva, World Health Organization, 2013. (Доступно на: www.who.int/iris/bitstream/10665/79199/1/ 9789241505345_ eng.pdf).

28

Доклад о глобальной борьбе с туберкулезом 2013

Таблица 3.1

Зарегистрированные случаи туберкулеза, 2012 год Новые случаи Доля бактериологически подтвержденных случаев легочного ТБ Случаи повторного лечения

всего зарегистрировано

Положительный мазок

Отрицательный мазок

Мазок не сделан

внелегочный

История болезни не документирована

Легочный ТБ бактериологически подтвержденный

рецидивы

Случаи повторного лечения, исключая рецидивы

Новые случаи и рецидивы a

Афганистан Бангладеш Бразилия Вьетнам ДР Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире

29 578 173 619 82 755 103 906 112 499 38 720 1 467 585 331 424 40 258 99 149 900 678 50 827 148 149 97 853 63 892 273 097 149 921 61 208 47 211 235 608 147 592 349 582 5 005 111 1 412 639 232 695 430 789 337 167 2 331 455 1 345 466 6 090 211

13 319 106 790 40 152 51 033 71 124 12 163 629 589 202 319 14 838 36 937 316 332 20 951 42 909 52 901 25 138 110 545 27 467 30 998 24 916 93 586 47 236 119 898 2 091 141 600 355 122 606 173 963 78 336 1 065 852 500 171 2 541 283

4 740 24 451 12 178 21 706 13 214 14 354 317 616 104 866 8 509 28 574 533 977 19 797 73 042 32 972 21 393 109 425 59 019 17 537 11 487 115 263 47 340 63 210 1 654 670 345 947 35 606 135 346 118 614 586 455 691 714 1 913 682

2 665 0 8 592

6 906 30 549 10 297 18 904 20 669

702 0 11 3 210 0 2 139 0 0 0 0 0 0 0 0

13 319 106 790 42 489 51 033 71 124 12 163 637 273 202 319 14 838 36 937 316 332 20 951 42 909 52 901 25 138 110 545 41 123 30 998b

62 81 70 67 84 41 67 66 64 50 37 51 37 62 54 50 47 64 65 45 49 71 56 63 76 55 55 62 42 57

1 049 3 065 3 867 7 259 3 977 1 369 106 463 5 942 446 3 419 31 784 1 451 4 558 2 513 1 052 6 095 8 211 1 887 1 334 4 080 1 820 26 668 228 309 60 497 9 949 11 208 25 185 131 245 45 277 283 361

197 4 936 7 633 1 794 3 515 2 960 177 749 2 600 73 6 162 10 033 3 086 6 979 5 035 1 714 5 622 44 168 904 2 548 19 409 2 269 25 918 335 304 67 770 13 862 10 020 67 662 201 335 34 740 395 389

29 381 168 683 75 122 102 112 108 984 35 760 1 289 836 328 824 40 185 92 987 890 645 47 741 141 170 92 818 62 178 267 475 105 753 60 304 44 663 216 199 145 323 323 664 4 669 807 1 344 869 218 833 420 769 269 505 2 130 120 1 310 726 5 694 822

2 962

4 912 234 029 15 697

0 8 123 2 073 0 0 0 1 039

15 290 15 934 6 479 5 542 20 661 4 432 14 595 41 410 10 017 8 852

1 783 0 2 073 71 421 100 731 100 537 14 564 8 523 6 257 0 9 751 139 632

5 143 3 270 46 854 42 467 582 909 234 539 34 400 90 943 39 029 338 303 59 294 796 508

0 0 0 0 6 062 977 1 669 702 30 3 004 3 287 9 669

24 916 93 586 47 236 180 857 2 144 779 656 272 132 070 175 025 112 577 1 027 902 502 652 2 606 498

Пустые ячейки означают — данные не представлены. a НОВЫЕ И РЕЦИДИВЫ включают случаи с неизвестной историей заболевания. b БАКТЕРИОЛОГИЧЕСКИ ПОДТВЕРЖДЕННЫЕ случаи для Таиланда включают только случаи, подтвержденные микроскопией. Данные о случаях, подтвержденных другими лабораторными методами, не представлены.

подтвержденных с помощью теста Xpert MTB/RIF и другими одобренными ВОЗ методами молекулярно-генетической диагностики (Глава 5), а также существующих с 2006 года алгоритмов, например, включение более подробных отчетов о случаях ТБ среди детей. Пересмотренные определения, которые будут использоваться ВОЗ во время глобального сбора данных о ТБ в 2014 году, приведены во Вставке 3.2. В 2012 году 6,1 млн больных ТБ было зарегистрировано НПТ и сообщено в ВОЗ, из них 5,7 млн составили больные с «новым эпизодом» ТБ (показаны как сумма впервые выявленных больных и больных с рецидивом заболевания в  Таблице 3.1). Из этих 5,7 млн, 5,4 млн составили случаи впервые выявленного ТБ и 0,3 млн случаев рецидива ТБ, то есть эпизодов заболевания, развившегося после ранее излеченного туберкулеза.

Оставшиеся 0,4 млн случаев составили случаи повторного лечения (исключая рецидивы), в которые не вошло небольшое число случаев заболевания без документированной истории предыдущего лечения. Среди впервые выявленных больных: у 2,5 млн диагностирован туберкулез легких, подтвержденный положительной микроскопией мазка мокроты (далее ТБ легких с положительной микроскопией — ред.), у 1,9 млн туберкулез легких с отрицательной микроскопией и у 0,8 млн  — внелегочный ТБ; в остальных случаях микроскопия мазка мокроты не проводилась или форма ТБ была неизвестна (Таблица 3.1). На Индию и Китай пришлось 39% от 5,7 млн новых случаев и рецидивов ТБ, которые были зарегистрированы в 2012 году (23% и 16% соответственно), а на регионы Юго-Восточной Азии и Западной части Тихого океана, 29

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 3.1

Определения ВОЗ случаев туберкулеза, которые использовались до конца 2012 года (и в данном докладе) a Подтвержденный случай туберкулеза (определенный случай ТБ). Случай ТБ у больного с положительным тестом на Мycobacterium tuberculosis complex, полученным в результате классического культурального исследования или с помощью более современных способов, таких как метод молекулярного анализа олигонуклеотидными зондами (АОЗ) или молекулярной гибридизации с типоспецифическими зондами. В странах, где нет возможности для проведения лабораторных исследований на выявление M. Tuberculosis одним из вышеуказанных методов, случай ТБ легких с однократным или более обнаружением кислотоустойчивых микобактерий (КУМ) может также считаться достоверным случаем при условии наличия надежно функционирующей системы обеспечения качества, включающей повторный «слепой» просмотр мазков мокроты. Случай туберкулеза. Подтвержденный случай ТБ (описанный выше) или случай, когда медицинский работник (врач или другой медицинский работник) поставил диагноз ТБ и было принято решение о прохождении больным полного курса противотуберкулезной терапии. Случай туберкулеза легких. Случай ТБ с вовлечением в патологический процесс паренхимы легких. Случай туберкулеза легких с бактериовыделением, подтвержденным положительной микроскопией. Случай ТБ, подтвержденный одним или несколькими первоначальными положительными результатами микроскопии мазка мокроты на КУМ (прямая микроскопия мазка мокроты), или одним положительным результатом микроскопии мазка мокроты на КУМ и установленными врачом рентгенологическими признаками активного ТБ легких. Случаи туберкулеза с бактериовыделением, подтвержденным положительной микроскопией, наиболее заразны и имеют приоритет с позиций общественного здравоохранения. Случай ТБ легких с отрицательной микроскопией. Случай ТБ легких у больного при отсутствии вышеуказанных критериев заболевания ТБ с положительной микроскопией. Диагностические критерии должны включать: по крайней мере два отрицательных результата микроскопии мазка мокроты на КУМ; рентгенологические признаки активного ТБ легких; отсутствие эффекта от курса антибиотиками широкого спектра действия (кроме пациентов с лабораторным подтверждением или выраженными клиническими признаками ВИЧ-инфекции), а также решение врача о назначении полного курса противотуберкулезной химиотерапии. Случай ТБ у больного с положительным результатом культурального исследования, но отрицательными результатами исследования мокроты на КУМ также рассматривается как случай ТБ легких с отрицательной микроскопией. Случай внелегочного ТБ. Случай ТБ у больного с поражением органов за пределами легочной паренхимы (например, плевры, лимфатических узлов, органов брюшной полости, мочеполовой системы, кожи, костей и суставов, мозговых оболочек). Диагноз должен быть установлен на основании одного положительного культурального исследования клинического образца, или положительного результата гистологического исследования, и убедительных клинических признаков внелегочного туберкулеза, а также решения врача назначить полный курс противотуберкулезной химиотерапии. Если имеются обе формы ТБ, легочная и внелегочная, то случай классифицируется как ТБ легких. Новый случай туберкулеза. Случай ТБ у больного, никогда не получавшего противотуберкулезного лечения или принимавшего противотуберкулезные препараты менее одного месяца. Повторный случай туберкулеза. Существуют три категории больных, регистрируемых для повторных курсов лечения: (I) случай повторного лечения больного с неэффективным курсом предыдущего лечения (повторное лечение после «неэффективного курса химиотерапии»); (II) случай повторного лечения больного ТБ после завершения последнего курса лечения с исходом «прервал лечение»; и (III) случай повторного лечения по поводу рецидива ТБ с бактериовыделением, подтвержденным методом микроскопии или культуральным методом (т. е. у больного, завершившего предыдущий курс химиотерапии с исходом «излечен» или «лечение завершено»). Случай ТБ с множественной лекарственной устойчивостью (МЛУ-ТБ). ТБ, устойчивый к двум препаратам первого ряда: изониазиду и рифампицину. Для большинства больных с диагнозом МЛУ-ТБ ВОЗ рекомендует лечение в течение 20 месяцев с назначением режима лечения, содержащего противотуберкулезные препараты второго ряда a См. Treatment of tuberculosis guidelines, 4th ed. Geneva, World Health

Organization, 2010 (WHO/HTM/STB/2009.420). Доступно на: http://whqlibdoc.who.int/publications/2010/9789241547833_eng.pdf

в которых расположены эти страны, в совокупности пришлось 60% таких случаев в мире. На Африканские страны пришлось 24% новых случаев и рецидивов ТБ в мире (из них, четвертая часть на одну страну — Южно-Африканскую Республику). Доля новых случаев и рецидивов ТБ, зарегистрированных в странах Восточного Средиземноморья, Европейском регионе и регионе Америки ВОЗ составила 16% в 2012 году (7%, 5% и 4% соответственно); на 22 СВБ пришлось 82% таких случаев. Среди 22 СВБ доля новых случаев туберкулеза легких с лабораторно подтвержденным бактериовыделением была самой высокой в Бангладеш (81%) и Демократической Республике Конго (84%), и относительно низкой в Зимбабве (41%), Китае (37%), России (47%) и Филиппинах (45%). Почти все (96%) новых случаев туберкулеза легких с положительной микроскопией были стратифицированы по полу и возрасту (Таблица 3.2); 88% случаев пришлось на возраст 15–64 лет, 59% — 15–45 лет и 2% были представлены детьми (в возрасте до 15 лет). Глобальное соотношение мужчины:женщины соответствует 1,9, а среди стран с высоким бременем туберкулеза величина этого показателя варьировалась от 0,5 в Афганистане до 3,0 во Вьетнаме. Вариация между странами может отражать как реальные различия в эпидемиологическом процессе, так и быть отражением различного доступа или использования медицинской помощи в рамках НПТ. 30

Отчетные данные о  регистрируемой заболеваемости, дезагрегированные по возрасту и полу, были намного менее полными для больных туберкулезом легких с отрицательной микроскопией и для больных внелегочным ТБ. Например, 11 СВБ не представили данные с разбивкой по возрасту и полу в соответствии с категориями, указанными в Таблице 3.2. Анализ имеющихся данных по новым случаям показал, что большинство случаев (82%) составляют лица в возрасте 15–64 лет, 55% — 15–45 лет и 6% — среди детей до 15 лет; соотношение мужчины:женщины равнялось 1,7 (в диапазоне 1,0–2,1) в шести регионах ВОЗ. Необходимы дальнейшие усилия для улучшения отчетности в плане повышения доли данных, дезагрегированных по возрасту и полу. В Европейском регионе, ВОЗ и Европейский центр по профилактике и контролю заболеваний (ECDC) также просят страны регистрировать заболевания в гражданском и пенитенциарном секторах отдельно. Эти данные показывают, что регистрация заболеваний в пенитенциарном секторе может составлять значительную долю от всех случаев заболеваний, и что показатели заболеваемости среди населения в тюрьмах могут быть пора­ зительно высокими. Краткая информация о последних данных в Европейском регионе и по отдельным странам, а также пример успешного снижения показателя заболеваемости в Российской Федерации, изложены во Вставке 3.3.

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 3.2

Определения ВОЗ случаев туберкулеза, рекомендованные для применения, начиная с 2013 года, и которые будут использованы в глобальном докладе о туберкулезе в 2014 году a Бактериологически подтвержденный случай туберкулеза. Туберкулез с бактериовыделением, подтвержденным с помощью исследования клинического образца одним из следующих методов: микроскопия мазка мокроты, культуральное исследование или один из одобренных ВОЗ ускоренных диагностических тестов (например, Xpert MTB/RIF). Все подобные случаи должны быть зарегистрированы в системе эпиднадзора, независимо от того, начался ли курс лечения ТБ или нет. Клинически диагностированный случай туберкулеза. Случай ТБ у больного, не соответствующий критериям бактериологически подтвержденного случая ТБ, но при этом диагноз активного ТБ устанавливается врачом или другим медработником, который принял решение о применении полного курса лечения ТБ. Это определение включает случаи, диагностированные на основе рентгенологических или гистологических изменений, а также случаи внелегочного ТБ без лабораторного подтверждения. Клинически диагностированные случаи, впоследствии получающие бактериологическое подтверждение (до или после начала лечения), следует характеризовать, как подтвержденные бактериологически. Случай туберкулеза легких. Бактериологически подтвержденный или клинически диагностированный ТБ с вовлечением паренхимы легких или трахеобронхиального дерева. Милиарный туберкулез классифицируется как легочный туберкулез, так как наблюдаются патологические изменения в легких. Туберкулез внутригрудных лимфатических узлов (медиастинальных и/или прикорневых) или туберкулезный плеврит без рентгенологических изменений в легких классифицируются, как случаи внелегочного ТБ. При сочетании легочного и внелегочного ТБ, случай определяется как легочный ТБ. Случай внелегочного ТБ. Любой бактериологически подтвержденный или клинически диагностированный случай ТБ органов и тканей за пределами паренхимы, кроме легких, например плевры, лимфатических узлов, органов брюшной полости, мочеполовых органов, кожи, костей и суставов, мозговых оболочек. Новый случай ТБ. Туберкулез, развившийся у больного, никогда не получавшего противотуберкулезное лечение или принимавшего противотуберкулезные препараты менее одного месяца. Повторный случай ТБ. Пациент, в прошлом получавший противотуберкулезные препараты в течение одного месяца и более. Повторные случаи в дальнейшем подразделяются в зависимости от результатов последнего курса лечения на четыре категории. 1. Случай повторного лечения по поводу рецидива туберкулеза (истинный рецидив или реинфекция) у больного, завершившего последний курс лечения от туберкулеза с исходом «излечен» или «лечение завершено». 2. Случай повторного лечения больного ТБ с неэффективным курсом предыдущего лечения (повторное лечение после «неэффективного курса химиотерапии»). 3. Случай повторного лечения больного ТБ после завершения последнего курса лечения с исходом «потерян для наблюдения» (соответствует категории «прервал лечение», во Вставке 3.1) 4. Другие случаи повторного лечения больных, исходы последнего курса лечения которых неизвестны или не документированы. Случай ТБ с множественной лекарственной устойчивостью (МЛУ-ТБ). См. определение во Вставке 3.1 Случай туберкулеза с устойчивостью возбудителя к рифампицину (РУ-ТБ). Туберкулез с устойчивостью возбудителя к рифампицину, подтвержденной при помощи фенотипических или молекулярно-генетических исследований с наличием или отсутствием устойчивости к другим противотуберкулезным препаратам. Данная категория подразумевает любую устойчивость к рифампицину: монорезистентность, полирезистентность, множественную или широкую лекарственную устойчивость. a

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/ HTM/TB/2013.2). Geneva, World Health Organization, 2013. Доступно на: www.who.int/iris/bitstream/10665/79199/1/9789241505345_eng.pdf

3.2 Вклад государственно-общественных и государственно-частных партнерств и различных организаций на уровне местных сообществ в обеспечение полноты регистрации случаев туберкулеза в 2012 году 3.2.1 Партнерство между государственными и общественными организациями и государственно-частными структурами Обеспечение правильной диагностики, стандартизированного лечения и оперативной регистрации в НПТ всех случаев ТБ требует сотрудничества между медицинскими учреждениями всех форм собственности. Привлечение всех медицинских организаций к противотуберкулезной работе является четвертым компонентом Стратегии «Остановить ТБ» (Глава 1). Двумя составляющими данного компонента являются: •• участие в процессе всех государственных, общественных, корпоративных и частных медицинских организаций через государственно-частные инициативы; и •• применение всеми участниками Международных стандартов лечения ТБ 1. Во многих странах сотрудничество в рамках государственно-частных инициатив было расширено. Принимая во внимание вклад не входящих в систему НПТ медицинских учреждений в обеспечение полноты регистрации туберкулеза, требуется систематический учет организаций, осуществляющих лечение

ТБ или направляющих больных на лечение ТБ на местном уровне, а также отчетность и анализ сводных данных на национальном уровне 2. В 2013 году 73 страны сообщили ВОЗ сводные данные; данные для 29 из этих стран (в том числе 14 СВБ) приведены в Таблице 3.3. В большинстве этих стран доля больных, зарегистрированных благодаря государственно-частным инициативам, составила от 10% до 40% от общего числа зарегистрированных случаев ТБ. Учитывая, что частный сектор здравоохранения в Африке намного меньше такового в Азии, вклад частных коммерческих и некоммерческих медицинских организаций (в выявление больных ТБ и их регистрацию в системе эпиднадзора) в Кении, Нигерии, Объединенной Республике Танзании и  Эфиопии заслуживает особого внимания. Прогресс в некоторых частях Азии также значителен — почти каждый четвертый случай в Индонезии и на Филиппинах был зарегистрирован в 2012 году в системе эпиднадзора медицинскими учреждениями, не входящими в систему НПТ. Значительная доля случаев заболевания ТБ была зарегистрирована по информации, представленной крупными больницами государственного сектора в Индонезии, Китае и на Филиппинах, поэтому совершенствование выявления и регистрации случаев ТБ в указанных учреждениях является одним из основных направлений работы по обеспечению полноты выявления и регистрации случаев ТБ. Результаты проекта,

1 2

http://www.istcweb.org/ISTC_Documents.html ВОЗ рекомендует, чтобы источники информации и места лечения регулярно регистрировались и включались в отчетность.

Доклад о глобальной борьбе с туберкулезом 2013

31

Таблица 3.2

Зарегистрированные случаи туберкулеза, дезагрегированные по возрасту и полу, 2012 год Новые случаи с положительной микроскопией % больных в возрасте <15 лет КОЭФФ. мужчины: женщины Все новые случаи a % больных в возрасте <15 лет Коэфф. мужчины: женщины

0–14 лет

15–44 лет

45–64 лет

≥65 лет

0–14 лет

15–44 лет

45–64 лет

≥65 лет

Афганистан Бангладеш Бразилия Вьетнам ДР Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире

588 966 580 142 3 138 293 12 957 1 703 53 996 1 091

8 469 56 209 25 209 23 310 47 722 9 568 378 071 116 326 6 000 29 779 138 667

3 106 34 674 11 129 18 363 17 066 1 870 186 737 70 491 6 064 5 114 110 614

1 156 14 941 3 190 9 218 3 198 432 51 824 13 799 2 724 1 048 65 960 –

4 <1 1 <1 4 2 2 <1 <1 3 <1

0,5 1,9 2,3 3,0 1,3 1,3 2,2 1,5 1,2 1,6 2,5 – 1,9 1,6 1,8 1,1 2,7 2,4 1,8 2,3 – 3 688 62 298 26 302 5 254 5 368 5 625 58 234 397 615 13 853 284 934 3 994 170 687 27 343 172 706 100 254 22 579 – 2 911 23 541 5 954 1 985 4 842 2 388 88 156 42 306 48 190 20 056 20 602 6 322

15 3 3 – – 8 7 8

0,6 1,6 2,0 – – 1,2 – 1,4 –

7 <1 13 – – 9 10 4 – – – 16

1,4 2,2 – – – 1,5 1,0 2,2 – – 1,9 1,2 1,2 1,7 1,3 1,6 1,0 1,9 1,8 2,1 1,7

338 1 187 490 3 947 48 117 636 1 032

24 076 38 590 17 855 66 901 17 039 13 525 18 535 49 736

14 405 10 571 5 257 29 149 8 793 11 435 4 777 29 617

4 090 2 553 1 536 10 548 1 587 5 921 914 6 943

<1 2 2 4 <1 <1 3 1 –

2 650 32 952 14 340 2 012 5 641 325 17 116 2 693 42 127

86 899 1 172 486 387 286 61 956 107 871 46 286 617 926 230 572 1 451 897

24 964 604 196 106 782 27 462 43 608 24 440 336 069 172 377 710 738

4 151 205 733 22 983 11 282 16 843 7 355 94 741 88 191 241 395

2 2 3 2 3 <1 2 <1 2

1,3 1,9 1,5 1,7 1,2 2,4 2,0 2,4 1,9

38 578 231 674 97 629 9 646 41 847 10 042 119 186 13 945 292 295

187 239 1 724 885 571 919 98 753 133 536 129 898 739 149 498 524 2 171 779

58 762 894 852 167 236 45 899 53 351 60 455 397 219 351 268 1 075 428

11 183 343 231 38 997 19 974 21 545 20 575 112 503 195 965 409 559

13 6 9 5 10 5 6 1 6

a

Пустые ячейки означают, что данные не могут быть представлены по указанным возрастным группам. – означает, что значения не могут быть рассчитаны. Значения по возрастным группам представлены только в случае, если были получены данные для всех случаев туберкулеза по всем четырем возрастным группам. В связи с этим, имеется небольшое расхождение между данными в этой таблице и данными в таблицах во Вставке 2.2 и Главе 2.

который был недавно завершен в пяти странах, приведены во Вставке 3.4. Подходы по привлечению медицинских организаций, не входящих в систему НПТ, могут меняться в зависимости от местных условий, но следует подчеркнуть важность некоторых общих принципов. Первый принцип заключается в необходимости предоставления со стороны этих организаций стандартного лечения в соответствии с национальными рекомендациями в обмен на бесплатное предоставление противотуберкулезных препаратов, открытость для контроля и обеспечение качества медицинской помощи, а также финансовых и нефинансовых 32

стимулов указанным организациям со стороны НПТ. Второе условие — следование Международным стандартам лечения ТБ, что обеспечивает применение передовых практик диагностики и лечения ТБ во всех учреждениях, предоставляющих противотуберкулезное лечение, особенно в частном секторе. В Европейском регионе и регионе Америки вклад в регистрируемую заболеваемость ТБ за счет больных, зарегистрированных в учреждениях социального обеспечения и в пенитенциарном секторе, является довольно значительным.

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 3.3

Туберкулез в тюрьмах Туберкулез является инфекцией, передающейся воздушно-капельным путем, поэтому во многих частях мира в переполненных и плохо вентилируемых условиях тюремного заключения создаются условия для распространения этой инфекции. Условия тюремного заключения также нередко сопровождаются плохим питанием и стрессом, что также может способствовать более высокому риску развития заболевания, а неадекватная или недоступная медицинская помощь может привести к плохим результатам лечения и приобретению лекарственной устойчивости. Заключенными в большей части являются выходцы из маргинальных социально-экономических слоев населения, включая наркоманов, бездомных, больных психическими заболеваниями, этнических меньшинств, беженцев и иммигрантов — поэтому у них еще до поступления в пенитенциарную систему уже имеется высокая распространенность ТБ инфекции или активная форма заболевания. Туберкулез в тюрьмах также усугубляет общее бремя ТБ, так как тюрьмы не являются полностью закрытыми системами: инфекция может передаваться тюремному персоналу и посетителям, и после освобождения из заключения большие контингенты лиц интегрируются в общество. Европейский регион ВОЗ в настоящее время является единственным регионом, который систематически собирает и анализирует данные от государств-членов ВОЗ о бремени ТБ в тюремном секторе a. Как и в большинстве стран мира, бремя ТБ в тюрьмах европейских стран непропорционально высоко по сравнению с гражданским сектором и часто составляет значительную долю от общего числа зарегистрированных случаев. Регистрируемая заболеваемость в тюрьмах во всех странах, предоставляющих отчетность, была в несколько раз выше, чем у населения в целом (относительный риск колеблется от 4 до 180), и составила более 1000 на 100 000 заключенных в Азербайджане, Грузии и Кыргызстане (2500, 3300 и 3000 случаев на 100 000 заключенных, соответственно) в 2011 году. Среди стран, предоставляющих данные, доля случаев ТБ в тюрьмах составила свыше 10% от общего числа новых случаев в целом по стране, в Грузии (19%) и в Российской Федерации (11%) в 2011 году. Принимая во внимание, что некоторые страны региона не смогли предоставить данные по числу случаев ТБ в тюрьмах и имеются лишь ограниченные данные о тенденциях, доля зарегистрированных случаев ТБ в тюрьмах в общем числе зарегистрированных случаев ТБ в данном регионе остается неопределенной. Для уменьшения бремени ТБ в тюрьмах требуется полный комплекс мер b, c. К ним относятся: ранняя диагностика путем систематического скрининга d и применения ускоренных методов диагностики, внедрение мер инфекционного контроля, улучшение условий жизни и питания, проведение полных курсов лечения ТБ с применением адекватных режимов, лечение сопутствующих заболеваний, включая ВИЧ-инфекцию, сахарный диабет, гепатиты, наркотическую зависимость, и обеспечение преемственности в лечении в государственных медучреждениях гражданского сектора после освобождения заключенного. В Российской Федерации был обеспечен ряд мер, которые значительно уменьшили бремя ТБ в пенитенциарной системе (Рисунок B3.3.1) е. Благодаря проведению систематического скрининга на туберкулез, усилению мер инфекционного контроля, улучшению лечебного процесса и сотрудничеству между Министерством юстиции, учреждениями Министерства здравоохранения, а также международными партнерами, заболеваемость ТБ резко снизилась с 4347 случаев на 100 000 заключенных в 1999 году (то есть, ТБ был диагностирован у 1 из 25 заключенных в 1999 году) до 1387 случаев на 100 000 заключенных в 2006 году. Снижение с 2006 года стало менее заметным в пенитенциарной системе, что отражает существующие проблемы, а именно: повышение доли больных туберкулезом, сочетанным с ВИЧинфекцией и ТБ с лекарственной устойчивостью, а также высокую долю лиц из маргинальных социально-экономических слоев населения. Следует отметить высокий уровень регистрации заболеваемости в следственных изоляторах по сравнению с исправительными учреждениями в 2011 году (1588 по сравнению с 1179 на 100 000 заключенных, соответственно), что отчасти объясняется высокой распространенностью ТБ инфекции и заболевания среди маргинальных социально-экономических слоев населения, попадающих в следственные изоляторы из гражданского сектора. В Восточной Европе лекарственно-устойчивый ТБ ассоциируется с тюремным заключением и, поэтому во многих странах пенитенциарное здравоохранение столкнулось со значительным числом пациентов с МЛУ-ТБ f–h. Поэтому предоставление эффективной помощи при МЛУ-ТБ для заключенных имеет особую важность. Возможность тщательного мониторинга туберкулеза у заключенных также может способствовать достижению хороших результатов лечения. Например, данные по пенитенциарному сектору Азербайджана демонстрируют показатели «успешности лечения» в диапазоне 65% –81% для когорт пациентов, зарегистрированных в 2007–2009 годах и пролеченных в соответствии с рекомендованными ВОЗ стандартами i.

Рисунок B3.3.1

Показатель регистрируемой заболеваемости туберкулезом в пенитенциарном секторе в целом и по следственным изоляторам и исправительным учреждениям Российской Федерации (1999–2011 годы) Показатель регистрируемой заболеваемости ТБ на 100 000 задержанных в год 5000 4000 3000 2000 1000 0 1999

a

b См. Guidelines for the control of tuberculosis in prisons. Geneva, World Health c

Tuberculosis surveillance and monitoring in Europe 2012. Stockholm, European Centre for Disease Prevention and Control/WHO Regional Office for Europe, 2012. Organization, 1998 (WHO/TB/98.250). Dara M, Chadha SS, Melchers NV, van den Hombergh J, Gurbanova E, Al-Darraji H, van der Meer JBW. Time to act to prevent and control tuberculosis among inmates. International Journal of Tuberculosis and Lung Disease, 2013 Jan; 17(1):4–5. Systematic screening for active tuberculosis: principles and recommendations. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2013.04). Туберкулез в Российской Федерации, 2011 год: аналитический обзор статистических показателей, используемых в РФ и в мире (на русском языке). Москва, Министерство здравоохранения РФ, 2013 год Skrahina A, Hurevich H, Zalutskaya A, et al. Multidrug-resistant tuberculosis in Belarus: the size of the problem and associated risk factors. Bulletin of the World Health Organization, 2013;91:36–45. Aerts A, Habouzit M, Mschiladze L, et al. Pulmonary tuberculosis in prisons of the ex-USSR state of Georgia: results of a nation-wide prevalence survey among sentenced inmates. International Journal of Tuberculosis and Lung Disease, 2000 Dec; 4(12):1104–10. Shin SS, Pasechnikov AD, Gelmanova IY, Peremitin GG, Strelis AK, Mishustin S, et al. Treatment outcomes in an integrated civilian and prison MDR-TB treatment program in Russia. International Journal of Tuberculosis and Lung Disease, 2006 Apr; 10(4):402–8. Review of tuberculosis prevention, control and care in Azerbaijan. Copenhagen, World Health Organization, 2013.

d e

f

g

2001

2003

2005

2007

2009

2011

h

Все учреждения Исправительные учреждения Следственные изоляторы

i

Доклад о глобальной борьбе с туберкулезом 2013

33

Таблица 3.3

Вклад государственно-общественных и государственно-частных партнерств (ГЧП) в регистрируемую заболеваемость туберкулезом в 29 странах, 2012 год Число случаев ТБ, зарегистрированных государственными нетуберкулезными организациями a Число случаев ТБ, зарегистрированных частными организациями b Вклад в общее число зарегистрированных случаев ТБ в 2012 году (%)

страна

Тип организаций, предоставляющих помощь

РЕГИОН АФРИКИ (AFR)  Гана Кения Лесото Нигерия ОР Танзания Свазиленд Эфиопия РЕГИОН АМЕРИКИ (AMR)  Перу Сальвадор Организации социальной защиты и другие не-НПТ государственные организации Различные не-НПТ государственные и частные организации 6 576 761 – 50 22 40 Различные не-НПТ государственные и частные организации Частные амбулаторные и больничные организации, пенитенциарная система Различные частные организации Государственные не-НПТ и НПО больницы и частные клиники Частные и религиозные организации Различные не-НПТ государственные и частные организации Различные частные организации – 14 096 – 1 489 – 1 107 817 832 10 364 1 044 8 121 13 734 841 17 133 13 12 10 24 22 33 12

РЕГИОН ВОСТОЧНОГО СРЕДИЗЕМНОМОРЬЯ (EMR)  Афганистан Египет Ирак Иран (Исламская Республика) Йемен Частные клиники, больницы, лаборатории и аптеки Страховые медицинские организации, НПО и другие государственные не-НПТ организации Различные не-НПТ государственные и частные организации Страховые медицинские организации, тюрьмы, военные госпитали и частные организации Государственные больницы, включая университетские клиники, военные госпитали, ведомственные больницы полиции, тюремный сектор и частные больницы Частные клиники и больницы Различные частные и не-НПТ государственные организации Различные частные и не-НПТ государственные организации 1 362 1 993 2 693 1 205 2 128 213 2 938 3 189 12 26 65 40

3486 925 175 450

– 56 363 2 400 1 475

35 21 86 10

Пакистан Сирийская Арабская Республика Судан ЕВРОПЕЙСКИЙ РЕГИОН (EUR)  Грузия Таджикистан

Различные не-НПТ государственные и частные организации, тюремный сектор Различные не-НПТ государственные организации, тюремный сектор

673 1 549

1628 –

58 24

РЕГИОН ЮГО-ВОСТОЧНОЙ АЗИИ (SEAR) Бангладеш Индия c Индонезия Мьянма Непал Таиланд Шри-Ланка Различные частные, не-НПТ государственные и НПО организации Различные частные, не-НПТ государственные и НПО организации Государственные и частные больницы Различные частные, не-НПТ государственные и НПО организации Различные частные организации Различные не-НПТ государственные и частные организации Различные не-НПТ государственные и частные организации 2 429 13 572 77 376 8 999 – 1 532 5 004 14 934 3 533 5 432 26 879 5 366 1 267 445 10 – 25 23 15 4,6 60

РЕГИОН ЗАПАДНОЙ ЧАСТИ ТИХОГО ОКЕАНА (WPR) Вьетнам Китай Филиппины a

Различные не-НПТ государственные и частные организации Общие государственные больницы Частные клиники и больницы

3 404 388 487 11 804

4 724 – 36 744

8,0 44 24

Включает все вклады от не-НПТ организаций¸ включая государственные больницы, государственные медицинские учебные заведения, изоляторы временного содержания, военные госпитали, ведомственные железнодорожные и медицинские страховые организации. Частные организации включают частные индивидуальные и ведомственные организации, организации корпоративного и бизнес сектора, миссионерские больницы, НПО и религиозные организации. c Данные по Индии для туберкулеза легких с бактериовыделением в 14 городах, где имеется ГЧП. b

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Вставка 3.4

Вовлечение больниц в проведение мероприятий по профилактике и лечению туберкулеза В 2009 году ВОЗ приступила к осуществлению проекта в пяти странах Африки и Азии, направленного на активизацию выявления ТБ за счет усиления роли больниц, в основном, крупных городских больниц. В общей сложности 86 больниц, оказывающих стационарную помощь 10 млн населения, были вовлечены в проект через консультации с участием НПТ, департаментов министерств здравоохранения, ответственных за стационарную помощь, главных врачей больниц, участвующих в проекте, и ВОЗ. В проекте участвовали 3 крупнейшие государственные больницы общего профиля в трех городах Вьетнама (Ханой, Хо Ши Мин и Хюэ), 10 больниц в г. Аккре, Гана, 20 больниц г. Киншаса в Демократической Республике Конго, 36 больниц в Свазиленде и 17 в г. Маниле, на Филиппинах. Данный проект был осуществлен при финансовой поддержке Министерства иностранных дел, торговли и развития Канады. До реализации проекта, в больницах не соблюдались стандартные национальные подходы к выявлению, диагностике и лечению ТБ, а также не функционировала система регистрации случаев туберкулеза и взаимодействия со специализированной противотуберкулезной службой. Конкретные цели проекта заключались в улучшении диагностики ТБ и улучшении ведения пациентов в больницах посредством создания механизмов внутренней и внешней координации в вопросах выявления и регистрации случаев ТБ. Основными направлениями деятельности были улучшение системы выявления лиц с симптомами, подозрительными на ТБ; стандартизация диагностических процедур и внедрение систем обеспечения качества в больничных лабораториях; создание «больничных DOTS блоков»; обеспечение систематической работы по направлению больных из разных отделений стационаров в «больничные DOTS блоки»; упорядочение процедур направления больных в другие медицинские центры и обеспечение обратной связи с этими центрами; обеспечение надлежащего лечения и преемственности в работе с пациентами, начавшими лечение в больницах, а также введение системы эпиднадзора (ведение учетных и отчетных форм). После успешного внедрения проекта, общее число зарегистрированных в больницах случаев туберкулеза в пяти территориях увеличилось примерно с 2 000 в год до начала проекта до примерно 12 000 в год в 2012 году. Число лиц, прошедших документально подтвержденное тестирование при помощи бактериологических исследований на ТБ, увеличилось во всех территориях проекта примерно в четыре раза (Рисунок B3.4.1). Внедрение системы направлений на лечение и обратной связи о начале лечения показало, что число больных потерянных для наблюдения в начале проекта было достаточно большим в двух азиатских странах (Вьетнам и Филиппины). Эти потери были значительно сокращены к концу третьего года проекта посредством улучшения связи между больницами и учреждениями первичной медико-санитарной помощи, в которые направлялись больные для лечения. Показатели успешности лечения среди тех, кто начал лечение в больницах, были аналогичны показателям при лечении в учреждениях НПТ. Этот проект помог описать исходную ситуацию, при которой больницы не были вовлечены в противотуберкулезную работу. Затем он показал, что можно активно привлекать больницы к противотуберкулезной работе и обеспечить применение национальных рекомендаций по лечению туберкулеза в их деятельности, что в свою очередь, позволяет улучшить выявление случаев ТБ и предоставление данных в НПТ. Все страны, участвовавшие в проекте, разработали новые национальные руководства по вовлечению больниц (или находятся в процессе их разработки) на основе результатов проекта. Проведение аналогичных проектов в других странах необходимо и ожидается в ближайшем будущем.

Рисунок B3.4.1

Тенденции в количестве бактериологических исследований на туберкулез и регистрации случаев туберкулеза в территориях, участвующих в проекте, 2010–2012 годы 100 000 80 000 Количество 60 000 40 000 20 000 0 2010

2011

2012

Количество проведенных бактериологических исследований Общее количество диагностированных и зарегистрированных случаев ТБ Количество диагностированных бактериологически-положительных случаев

3.2.2 Вклад местных сообществ в выявление и лечение туберкулеза Мероприятия по борьбе с туберкулезом могут быть организованы за пределами медицинских учреждений в местах, максимально приближенных к домохозяйствам, например, в школах или религиозных организациях и других объектах. Такие мероприятия могут осуществляться местными медицинскими работниками 1 и волонтерами, 2 как из правительственных, так и из неправительственных организаций. Подобные мероприятия вносят существенный вклад в медицинскую помощь, включая профилактику, диагностику, лечение, уход и социальную поддержку. Учитывая специфику противотуберкулезной работы, с помощью мероприятий на местном уровне можно увеличить число выявляемых случаев и улучшить результаты лечения, особенно в тех местах, где пациенты с ТБ имеют ограниченный доступ к учреждениям здравоохранения. Как показано в  Разделе 3.3, примерно треть случаев ТБ составляют диагностированные, но не зарегистрированные в системе эпиднадзора или не выявленные случаи.

Точное документирование вклада местных сообществ в выявление и лечение ТБ представляло определенные трудности. Одной из причин данной проблемы было отсутствие стандартизированных показателей, которые можно использовать для текущего учета и отчетности. Для решения этой проблемы ВОЗ недавно разработала минимальный набор

1

Местные медицинские работники могут быть определены как люди с минимальным формальным образованием, получившие подготовку по оказанию медицинских услуг, в том числе по профилактике, лечению ТБ и уходу за больными на уровне местных сообществ. Их характеристики, роли и обязанности сильно варьируются в разных странах; время, затраченное ими на оказание услуг, часто компенсируется стимулами в натуральном или финансовом выражении. 2 Местные волонтеры могут быть определены как члены местных сообществ, которые периодически проходят подготовку по вопросам профилактики и лечения ТБ в рамках краткосрочной, специализированной программы подготовки или на базе регулярных контактов с профессиональными медицинскими работниками.

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Вставка 3.5

Подход ENGAGE-TB Подход ENGAGE-ТБ a показывает необходимость участия неправительственных организаций и других организаций гражданского общества в борьбе с ТБ и интеграции этой работы в их деятельность. Пилотные проекты в пяти африканских странах (Демократическая Республика Конго, Кения, Объединенная Республика Танзания, Эфиопия и Южно-Африканская Республика) продемонстрировали многообещающие результаты. В этих странах были выбраны неправительственные организации, которые начали интегрировать противотуберкулезную работу в местные программы по борьбе с ВИЧ-инфекцией, программы охраны здоровья матери и ребенка (ОЗМР), и программы выявления онкологических заболеваний при финансовой поддержке Bristol Myers Squibb Foundation. НПО Страна Цель проекта

Femmeplus

ДР Конго

Интеграция противотуберкулезных служб в местные мероприятия по борьбе с ВИЧ-инфекцией в двух крупных городах (Киншаса и Киквит) Интеграция служб ТБ/ВИЧ в местные программы охраны здоровья матери и ребенка (ОЗМР) в сельских регионах Интегрированный в рамках общины проект по борьбе с ТБ, ВИЧ-инфекцией и обследований на выявление онкологических заболеваний Интеграция в рамках общины программ по борьбе с ТБ, ВИЧинфекцией в программы охраны здоровья матери и ребенка (ОЗМР) в сельских регионах Усиление интеграции противотуберкулезных служб в местные программы по борьбе с ВИЧ-инфекцией Интеграция противотуберкулезных служб в местные программы по борьбе с ВИЧ-инфекцией.

AMREF

Эфиопия

CUAMM

Эфиопия

Save the Children

Эфиопия

Centre for Positive Care

ЮАР

Pathfinder

ОР Танзания

НПО: неправительственные организации

Задача подхода состоит в том, чтобы распространить этот опыт и значительно увеличить количество местных медицинских работников и волонтеров, которые могут проводить скрининг на ТБ и направление больных с симптомами, подозрительными на ТБ, на обследования, а затем обеспечить лечение и уход за больными ТБ. ВОЗ завершает работу над практическим руководством для неправительственных организаций и НПТ, которое будет содержать методические основы для обеспечения процессов интеграции противотуберкулезной работы в программы по охране здоровья матери и ребенка, борьбе с ВИЧ-инфекцией, в деятельность первичной медико-санитарной помощи, проекты по развитию сельского хозяйства, инфраструктуры и системы образования. a

стандартизированных показателей в рамках подхода ENGAGEТБ (Вставка 3.5). В 2013 году эти показатели были применены для сбора стандартизированных и сопоставимых данных в группе из 13 стран, в которых заполнялась учетная и отчетная документа1. ция, по крайней мере, в некоторых географических областях  Сбор данных в указанном формате проводился отдельно от основного глобального сбора данных по ТБ, так как в большинстве стран не ведется учетно-отчетная документация по данной деятельности или она ведется не во всех юрисдикциях. Данные по 13 странам свидетельствуют о том (Таблица 3.4), что доля случаев, выявленных в результате работы добровольцев местных сообществ в общем числе зарегистрированных больных, составила от 2% в Мьянме (в 92 из 330 районов) до 33% в Эфиопии (в 98 из 821 округов). Вполне возможно, что эти цифры занижены и свидетельствуют о необходимости совершенствования системы учета и отчетности. Тем не менее, тот факт, что вклад местных сообществ в выявление ТБ в ряде стран был ниже 10%, показывает, что существуют возможности для использования ресурсов местных сообществ в профилактике, диагностике и лечении ТБ. В условиях, когда доступ к медицинским учреждениям ограничен, необходимо больше внимания уделять повышению роли сообществ в выявлении лиц с симптомами, подозрительными на ТБ, как можно раньше. Доля пациентов, получающих поддержку во время лечения на уровне общин, была в целом значительной: например, 50% в Индии и 88% в Кении. Кения также представляет собой интересный пример нереализованного потенциала в плане участия местных сообществ. В то время как 88% всех больных ТБ, по отчетным данным, получили поддержку при продолжении лечения, что свидетельствует о наличии большого числа медицинских работников и волонтеров в стране, только 5% зарегистрированных случаев ТБ были направлены на обследование в связи с подозрением на туберкулез членами местных общин. Это говорит о том, что требуются большие усилия, чтобы увеличить вовлечение сообществ на местах в выявление лиц с симптомами, подозрительными на ТБ, и направление этих лиц на обследование в медицинские учреждения. Очевидно, что данные о вкладе местных сообществ в выявление и поддержку во время лечения ТБ не собираются стандартизованно и регулярно даже в 13 странах, представленных в  Таблице 3.4. Только три из 13 стран предоставили данные, которые отражали ситуацию во всех районах страны, по обоим показателям (Буркина-Фасо, Кения и Руанда). Остальные страны предоставили данные, которые охватывали только части страны (иногда очень ограниченные территории), или сообщили об отсутствии данных по обеим категориям. Для лучшего понимания вклада сообществ в борьбу с ТБ требуется более активный и регулярный сбор данных. Это особенно актуально в тех условиях, когда вклад сообществ рассматривается как необходимая составляющая противотуберкулезной работы.

ENGAGE-TB – Integrating community-based tuberculosis activities into the work of nongovernmental organizations. Geneva, World Health Organization, 2012.

1

Не было попыток обобщить данные о вкладе сообществ в разработку и осуществление программы (включая информационно-пропагандистскую деятельность на местных уровнях). Такие данные обычно недоступны.

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Таблица 3.4

Роль местных организаций и общин в регистрации туберкулеза и обеспечении приверженности лечению, 2011–2012 годы Зарегистрировано больных по направлению общины, 2012 год Доля от общего числа зарегистрированных больных (%) Больные, ПОЛУЧИВШИЕ поддержку во время лечения на уровне общины (когорта 2011 года, если не указано иное) Доля от числа больных в когорте, по которым были представлены данные (%) Географический охват

Географический охват

Страна

Буркина-Фасо ДР Конго Индия Кения Кот-д’Ивуар Малави Мьянма Нигерия ОР Танзания Руанда Сенегал Уганда Эфиопия a

9% 10% 3% 5% 16% 20% 2% Нет данных 14% 28% 6% Нет данных 33%

Все районы 45/515 районов 374/662 районов Все районы 59/82 районов 2/28 районов 92/330 районов

33% 3% 50% 88% Нет данных 91% 2% 5%

Все районы 8/515 районов Все районы Все районы

2/28 районов 92/330 районов 36/774 районов Все районы Все районы Нет данных

63/162 районов Все районы Все районы

86% 46%

35% 98/821 районов 40%a

Все районы 98/821 районов

Данные для когорты 2012 года

3.3  Тенденции в регистрируемой заболеваемости туберкулезом с 1990 года и оценочный уровень выявления случаев туберкулеза В мире число диагностированных и зарегистрированных случаев туберкулеза на 100 000 населения было относительно стабильным в период с 1990 по 2000 годы, затем оно резко возросло в период с 2000 по 2008 годы и впоследствии начало медленно снижаться (Рисунок 3.1). В мире и во всех регионах ВОЗ существует разница между числом зарегистрированных случаев и оценочным числом случаев заболевания, хотя эта разница уменьшилась за последнее десятилетие, как в мире в целом, так и во всех шести регионах ВОЗ (Рисунок 3.2). Тенденции в 22 СВБ показаны на Рисунке 3.3. Тенденции для других стран продемонстрированы в разделах, посвященных ситуации в отдельных странах, которые доступны в интернете 1. Уровень выявления случаев (УВЗ) ТБ 2 является показателем, который включен в Цели тысячелетия в области развития (ЦТР) (Глава 1). Для каждой страны и года УВЗ рассчитывается как число новых случаев ТБ и рецидивов (см. определения во Вставке 3.1), которые были зарегистрированы НПТ (Таблица 3.1), деленное на оценочное число случаев заболевания ТБ в этом году. Уровень выявления, выражаемый в процентах, дает приблизительное 3 представление о доле случаев ТБ, которые были диагностированы, зарегистрированы НПТ и приступили к лечению, от общего оценочного числа случаев. В мире, в 2012 году, «лучшее» оценочное значение УВЗ для всех форм ТБ составило 66% (диапазон, 64–69%), что выше диапазонов 53–59% в 2005 году и 38–43% в 1995 году (с последнего началось внедрение и распространение стратегии DOTS) 1

рисунок 3.1

Глобальные тенденции в показателях регистрируемой (черный) и оценочной (зеленый), заболеваемости туберкулезом 1990–2012 годы Показатель регистрируемой заболеваемости включает новые случаи и рецидивы (все формы). 200

Показатель на 100 000 населения в год

150

100

50

0 1990 1995 2000 2005 2012

www.who.int/tb/data УВЗ — это на самом деле отношение, а не уровень, но термин «уровень» был принят в качестве стандартной терминологии в отношении данного показателя. 3 Приблизительная — из-за неопределенности в уровне истинной заболеваемости ТБ и потому, что зарегистрированные случаи не обязательно представляют собой все те случаи заболевания, которые развились в том же году; см. Главу 2. 2

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37

рисунок 3.2

Показатели регистрируемой и оценочной заболеваемости туберкулезом по регионам ВОЗ, 1990– 2012 годы. Региональные тенденции в показателях регистрируемой (новые случаи и рецидивы, все формы) (черный) и оценочной заболеваемости ТБ (зеленый). Затененные участки представляют собой диапазоны неопределенности. 400 300 200 Показатель на 100 000 населения в год 100 0 Европа Африка 80 60 40 20 0 Юго-Восточная Азия Америка 160 120 80 40 0 Западная часть Тихого океана Восточное Средиземноморье

100 75

300

200 150

200 50 100 25 0 1990 1995 2000 2005 2012 0 1990 1995 2000 2005 2012 50 0 1990 1995 2000 2005 2012 100

( Таблица  3.5). Самые высокие показатели УВЗ в  2012  году наблюдались в регионе Америки (лучшая оценка 79%, диапазон 74–85%), регионе Западной части Тихого океана (лучшая оценка 81%, диапазон 75–89%) и в Европейском регионе (74%, диапазон 70–79%). В других регионах УВЗ находился в диапазоне 55–71%, при лучшей оценке около 60%. Все регионы улучшили свои оценочные УВЗ, начиная с середины 1990-х годов, причем особенно заметное улучшение показателей наблюдалось с 2000 года. В 2012 году среди 22 СВБ наиболее высокие УВЗ рассчитаны в Бразилии, Кении, Китае, в Российской Федерации и на Филиппинах. Самые низкие показатели, с лучшими оценками около 50%, были в Афганистане, Бангладеш, Демократической Республике Конго, Зимбабве, Мозамбике и Нигерии. Разрыв между регистрируемой заболеваемостью по данным национальной системы эпиднадзора и оценочным числом случаев заболевания можно объяснить двумя причинами. Во-первых, занижение числа диагностированных случаев ТБ, например, по причине того, что медицинские работники частного сектора не регистрируют случаи в органах эпиднадзора. Во-вторых, заниженная диагностика ТБ в связи с ограниченным доступом к медицинским услугам и плохая информированность медицинских работников в вопросах выявления ТБ, которая приводит к тому, что лиц с симптомами туберкулеза не направляют на обследование. Достижение цели всеобщего охвата медицинской помощью, реализация государственно-частных инициатив, описанных в  Разделе 3.2, и создание эффективной нормативно-правовой базы, обязывающей направлять извещения обо всех случаях выявления ТБ в органы эпиднадзора, необходимы 38

для снижения числа не зарегистрированных и не диагностированных случаев ТБ. Проведение диагностических тестов на месте оказания медицинской помощи также целесообразно.

3.4 Результаты лечения Определения категорий, используемых для оценки результатов лечения в данном отчете, приведены во Вставке 3.6. Обновленные определения, которые будут использоваться с 2014 года, поясняются во Вставке 3.7.

3.4.1 Новые случаи туберкулеза легких с положительным результатом микроскопии мазка мокроты Данные о результатах лечения новых случаев туберкулеза легких с положительной микроскопией мазка мокроты приведены в  Таблице 3.6 и  Рисунке 3.4. В мире в целом, показатель успешности лечения для 2,6 млн новых случаев туберкулеза легких с положительным мазком мокроты, зарегистрированных в 2011 году, составил 87%. Это был пятый год подряд, когда цель в 85% (впервые поставленная на Всемирной ассамблее здравоохранения в 1991 году) была достигнута или даже превышена в мире. Также впечатляет тот факт, что по мере увеличения размера мировой когорты излеченных больных с 1,0 млн в 1995 году до 2,7 млн в 2009 и 2010 годах и 2,6 млн в 2011 году, уровень успешности лечения неуклонно повышался.

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рисунок 3.3

Показатели регистрируемой и оценочной заболеваемости туберкулезом, 22 страны с высоким бременем туберкулеза, 1990–2012 годы. Тенденции в показателях регистрируемой (новые случаи и рецидивы, все формы) (черный) и оценочной заболеваемости ТБ (зеленый). Затененные участки представляют собой полосы неопределенности. 300 200 200 100 100 0 50 100 0 0

Афганистан

400 300

Бангладеш

150 100

Бразилия

400 300 200

Вьетнам

500 400 300 200 100 0

ДР Конго

0 1250 1000 750 500 250

Зимбабве

300 200 100

Индия

300 200 100

Индонезия

1000 750 500 250 0

Камбоджа

400 300 200 100 0

Кения

Показатель на 100 000 населения в год

0

0

0

200 150 100 50 0

Китай

1250 1000 750 500 250 0

Мозамбик

600 500 400 300 200 100 0

Мьянма

600 400 200

Нигерия

300 200 100

ОР Танзания

0

0

400 300 200 100 0

Пакистан

200 150 100 50 0

Российская Федерация

250 200 150 100 50 0

Таиланд

1250 1000 750 500 250 0

Уганда

600 400 200

Филиппины

0 1990 1995 2000 2005 2012 1990 1995 2000 2005 2012

1990 800 600 400 200 0 1990 1995 2000 2005 2012

1995

2000

2005

2012

Эфиопия

1250 1000 750 500 250 0

ЮАР

1990

1995

2000

2005

2012

рисунок 3.4

Результаты лечения по регионам ВОЗ, когорты 2011 года a. Новые случаи с положительной микроскопией AFR AMR EMR EUR SEAR WPR В мире 0% 20% 40% 60% 80% 100% Излечен Умер

b. Все новые случаи AFR AMR EMR EUR SEAR WPR В мире 0% 20% Неэффективное лечение

40%

60% Лечение прервано

80%

100%

Результат неизвестен

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39

Таблица 3.5

Оценочный уровень выявления новых случаев и рецидивов туберкулеза (%), 1995–2012 годы a 1995 лучш. b Низк. Высок. лучш. 2000 Низк. Высок. лучш. 2005 Низк. Высок. лучш. 2010 Низк. Высок. лучш. 2012 Низк. Высок.

Афганистан Бангладеш Бразилия Вьетнам ДР Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире

– 21 79 33 31 55 59 8,9 23 61 32 23 10 8,9 59 4,5 60 59 23 48 11 56 38 32 67 23 51 44 37 40

– 17 66 25 26 40 52 7,1 19 56 27 11 8,0 2,7 51 3,7 51 50 14 40 7,2 47 36 27 63 21 49 40 32 38

– 26 97 47 38 79 67 12 30 66 39 73 13 170 69 5,5 70 72 41 58 18 69 42 39 72 26 54 49 42 43

18 25 74 56 40 56 49 20 27 72 33 23 15 12 68 3,3 75 32 29 47 33 59 39 39 70 25 59 41 39 41

15 21 62 43 34 45 45 16 22 67 28 13 13 3,9 60 2,8 65 27 20 39 22 49 37 33 65 22 55 38 35 39

22 31 91 78 48 71 55 25 34 77 38 51 19 170 77 4,1 89 39 48 57 55 72 42 48 75 28 62 44 44 44

46 38 85 63 55 50 49 57 52 80 74 30 53 26 74 39 66 57 47 53 48 61 55 52 75 48 65 50 70 56

39 32 72 49 47 40 44 47 44 76 65 20 45 9,6 69 32 56 48 36 44 32 50 51 44 71 43 61 46 63 53

57 47 100 86 64 63 55 71 63 85 85 53 63 200 80 48 78 69 65 65 80 74 58 61 81 54 70 53 77 59

52 45 82 70 56 53 60 66 64 81 86 33 66 40 77 66 83 79 60 65 66 70 66 60 76 64 77 61 80 66

44 38 69 54 49 43 54 56 56 78 76 25 57 23 72 55 71 66 50 54 49 59 63 56 71 57 72 56 73 63

63 55 99 95 65 69 66 80 75 85 98 48 77 82 82 80 98 95 75 79 93 85 69 65 82 72 82 65 87 68

52 49 82 76 51 46 59 72 66 79 89 34 71 51 79 65 81 76 69 84 64 62 66 59 79 63 74 62 81 66

44 41 69 59 44 37 54 61 57 76 79 25 62 29 74 54 70 64 57 71 49 52 63 55 74 56 70 58 75 64

63 59 99 100 59 60 66 87 77 83 100 50 83 110 84 78 96 92 85 100 87 75 70 64 85 71 79 66 89 69

– означает, что данные не могут быть рассчитаны. a Оценочные показатели для всех лет были пересчитаны с учетом новой информации и с помощью усовершенствованных методов, поэтому могут отличаться от ранее опубликованных данных. b Лучший, низкий и высокий уровни — означают наилучшее значение расчетного показателя, и его низкая и высокая границы. Низкая и высокая границы определены как 2,5 и 97,5 центилей результатов распределения, полученных при моделировании (экспериментировании с моделью — ред.).

Среди шести регионов ВОЗ, три достигли или превысили уровень в 85%: регион Восточного Средиземноморья, регион Юго-Восточной Азии и регион Западной части Тихого океана. Уровень успешности лечения составил 82% в регионе Африки (наблюдается стабильное улучшение с 1999 года), 78% в регионе Америки (как и в предыдущие семь лет) и 65% в Европейском регионе (где требуется приложить основные усилия для повышения уровня эффективности лечения). Из 22 стран с высоким бременем туберкулеза, 16 достигли или превысили уровень в 85% в 2011 году, в том числе впервые Нигерия и Эфиопия. Пять стран СВБ сообщили более низкие показатели успешности лечения: Бразилия (76%), Зимбабве (81%), Россия (52%), Уганда (77%) и Южно-Африканская Республика (79%). Тем не менее, среди этих пяти стран все, за исключением Российской Федерации, сохранили уровень или добились прогресса по сравнению с 2010 годом. Данные из Мозамбика не были сообщены в ВОЗ, но уровень успешности лечения в 2010 году составил 85%. В Российской Федерации улучшение 40

результатов лечения было определено в качестве первоочередной задачи Министерством здравоохранения и были определены меры по улучшению данного показателя. К ним относятся: обеспечение раннего выявления МЛУ-ТБ, предоставление пациентам терапии препаратами второго ряда и оказание поддержки пациентам для повышения приверженности лечению (особенно социально и экономически неблагополучным пациентам). Ожидается, что внедрение в ближайшее время системы персонифицированного мониторинга пациентов с МЛУ-ТБ и ШЛУ-ТБ и больных туберкулезом, сочетанным с ВИЧ-инфекцией, будет способствовать улучшению качества лечения.

3.4.2 Все новые случаи Данные о результатах лечения для всех новых случаев ТБ приведены в  Таблице 3.7 и  Рисунке 3.4. В глобальном масштабе показатель успешности лечения составил 87% в 2011 году. Среди шести регионов ВОЗ наиболее высокие показатели наблюдались

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Вставка 3.6

Вставка 3.7

Определения результатов лечения лекарственно-чувствительного туберкулеза, используемые до конца 2012 года и в этом глобальном докладе по ТБ a Излечен. Больной с первоначально положительным результатом микроскопии мазка мокроты и отрицательным результатом микроскопии мазка мокроты в последний месяц лечения и, по крайней мере, одного из предыдущих исследований. Завершил лечение. Больной, который завершил курс лечения, но не отвечает критериям категории «излечение» или «неэффективное лечение». Это определение относится к больным туберкулезом легких с положительным и отрицательным результатами микроскопии и больным с внелегочным туберкулезом. Умер. Больной, умерший от любой причины во время курса лечения. Неэффективное лечение. Больной с первоначально положительным результатом микроскопии мазка мокроты, и у которого мазок остается положительным на 5-м месяце и позже в течение курса лечения. Под данное определение попадают также больные, у которых выделен штамм возбудителя с множественной лекарственной устойчивостью в любой момент времени в течение курса лечения, независимо от результата микроскопии мазка мокроты. Лечение прервано. Больной, лечение которого было прервано на два месяца подряд или более. Результат неизвестен. Больной, результат лечения которого не известен. Успешное лечение. Больной, у которого результат лечения определен как «излечен» или «лечение завершено». Когорта. Группа больных, которым был поставлен диагноз ТБ, и которые начали курс лечения в течение определенного периода времени (например, когорта впервые выявленных больных с положительным результатом микроскопии мазка мокроты, зарегистрированных в 2010 году). Число этих больных составляет знаменатель для расчета показателей результатов лечения. Сумма вышеуказанных результатов лечения, а также любые случаи, для которых результаты лечения не зафиксированы (в том числе те случаи, которые «продолжают лечение» в Европейском регионе) и «выбывшие» должны равняться числу зарегистрированных случаев. Некоторые страны оценивают результаты лечения отдельно для когорт больных с положительным результатом микроскопии и/или с положительным результатом посева и определяют результаты лечения (излечение и неэффективное), в соответствии с лабораторными данными, имеющимися для каждого больного. a См. Treatment of tuberculosis guidelines, 4th ed. Geneva, World Health

Определения результатов лечения лекарственно-чувствительного туберкулеза, рекомендованные ВОЗ для применения, начиная с 2013 года, которые будут использованы в Докладе о глобальной борьбе с туберкулезом в 2014 году a Излечен. Больной с туберкулезом легких с бактериовыделением, подтвержденным любым методом до начала лечения, и у которого имеются отрицательные результаты микроскопии мазка мокроты или культурального исследования в последний месяц лечения или в одном из предыдущих исследований. Завершил лечение. Больной ТБ, который завершил лечение без признаков неэффективного лечения, но у которого отсутствуют документированные результаты культурального исследования или микроскопии мазка мокроты в последний месяц лечения и, по крайней мере, в одном из предыдущих исследований, как по причине того, что тесты не были проведены, так и при отсутствии результатов. Умер. Больной, умерший от любой причины во время курса лечения. Неэффективное лечение. Больной ТБ, у которого результаты культуральных исследований или микроскопии мазка мокроты остаются положительными через пять месяцев и позже в течение курса лечения. Потерян для наблюдения. Больной ТБ, не начавший курс лечения или прервавший лечение на два или более месяцев подряд. Результат неизвестен. Больной ТБ, результат лечения которого неизвестен. Данная категория включает в себя больных, «выбывших» в другие медицинские учреждения, а также случаи, результаты лечения которых неизвестны в медицинском учреждении, которое отчитывается о больном. Успешное лечение. Больной, у которого результат лечения определен как «излечен» или «завершил лечение». Когорта. Как определено во Вставке 3.6. Кроме того, следует отметить, что любой больной с лекарственно-устойчивым ТБ, получающий лечение препаратами второго ряда, исключается из когорты лекарственно-чувствительного ТБ. Это означает, что ведение журналов регистрации лекарственно-чувствительного и лекарственно-устойчивого ТБ должно быть скоординировано, чтобы обеспечить надлежащий учет результатов лечения. (см. также Вставку 4.4) a

Organization, 2010 (WHO/HTM/STB/2009.420). Доступно на: http://whqlibdoc.who.int/publications/2010/9789241547833_eng.pdf

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/HTM/TB/2013.2). Geneva, World Health Organization, 2013. Доступно на: www.who.int/iris/bitstream/10665/79199/ 1/9789241505345_eng.pdf

Вставка 3.8

Достижения в глобальной борьбе с туберкулезом, 1995–2012 годы ВОЗ запустила систематический мониторинг прогресса в борьбе с ТБ в 1995 году. Данные, ежегодно собираемые с тех пор, позволяют оценить достижения медицинских служб в борьбе с ТБ. В период с 1995 по 2012 годы, 56 млн больных ТБ успешно завершили лечение в странах, которые приняли стратегию DOTS/«Остановить ТБ», что позволило спасти около 22 млн жизней a. Количество спасенных жизней подсчитано с учетом того, что при отсутствии лечения примерно треть больных ТБ умирает от этой болезни. Эта оценка учитывает различия в смертности больных с положительным мазком мокроты по сравнению с другими формами ТБ (см. Главу 1), и различия в смертности между ВИЧ-отрицательными и ВИЧ-инфицированными больными. a

Для оценки дополнительного количества спасенных жизней, что стало результатом успешного применения стратегии DOTS и «Остановить ТБ» по сравнению со стандартами лечения и ухода, которые существовали до 1995 года, см. Glaziou P et al. Lives saved by tuberculosis control and prospects for achieving the 2015 global target for reducing tuberculosis mortality. Bulletin of the World Health Organization, 2011, 89:573–582.

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41

Таблица 3.6

Успешность лечения среди новых случаев с положительной микроскопией (%) и размер когорты (тыс.), 1995–2011 годы a. Успешность лечения (%) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Афганистан Бангладеш Бразилия Вьетнам ДР Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире

– 71 17 89 74 53 25 91 91 75 93 39 67 49 73 70 65 64 44 60 61 58 53 60 50 79 67 33 80 57

– 63 20 89 48 32 21 81 94 77 94 55 79 32 76 – 57 78 33 35 71 61 50 56 51 66 58 31 72 54

45 73 27 85 64 69 18 54 91 65 95 65 82 73 77 67 67 58 40 78 72 68 56 64 58 73 72 29 91 60

33 77 40 92 70 70 27 58 95 77 95 – 82 73 76 23 68 68 62 71 74 72 62 70 67 57 63 40 92 64

86 79 78 92 69 73 21 50 93 79 95 71 81 75 78 70 65 77 61 87 74 57 60 68 79 79 75 34 91 64

85 81 71 92 78 69 34 87 91 80 93 75 82 79 78 74 68 69 63 88 80 63 67 71 76 81 75 50 90 69

84 83 55 93 77 71 54 86 92 80 95 78 81 79 81 77 67 75 56 88 76 61 72 70 69 82 74 63 91 73

87 84 80 92 78 67 60 86 92 79 92 78 81 79 80 78 67 74 60 88 76 68 75 73 81 84 74 68 90 76

86 85 77 92 83 66 76 87 93 80 93 76 81 78 81 79 61 73 68 88 70 67 81 73 80 82 75 79 91 80

89 90 76 93 85 54 82 90 91 80 94 77 84 73 81 82 60 74 70 87 79 69 84 74 79 83 71 84 91 83

90 91 76 92 85 68 86 91 93 82 94 79 84 75 82 83 58 75 73 89 78 71 86 76 79 83 72 87 92 85

84 92 73 93 86 60 86 91 93 85 94 83 84 76 85 88 58 77 70 88 84 74 87 75 76 86 70 87 92 84

87 92 72 92 87 78 87 91 94 85 94 79 85 82 88 91 58 83 75 89 84 74 87 80 79 88 71 88 92 86

88 91 71 92 87 74 87 91 95 85 94 84 85 78 88 90 57 82 70 88 84 76 87 80 77 88 70 88 92 86

86 92 72 92 88 78 88 91 95 86 95 85 85 83 88 91 55 86 67 89 84 73 88 80 76 88 69 89 93 86

90 92 74 92 90 81 88 90 94 87 96 85 86 84 90 91 53 85 71 91 83 79 88 81 75 88 67 88 93 87

91 92 76 93 87 81 88 90 93 88 95 – 86 85 88 92 54 85 77 90 90 79 88 82 78 88 65 89 94 87

b. Размер когорты (тыс.) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Афганистан Бангладеш Бразилия Вьетнам ДР Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире

11 30 46 45 38 48 16 25 9,7 12 265 291 3,0 12 4,4 9,1 6,5 13 131 175 11 13 7,9 9,7 9,5 24 20 21 0,8 0,05 43 20 0,1 15 15 90 126 5,1 11 28 45 739 967 178 233 129 134 46 51 34 94 318 360 296 372 1 001 1 245

2,0 34 43 54 26 12 293 21 12 19 189 11 9,2 11 22 2,8 0,7 3,7 18 27 12 55 879 268 125 60 24 376 294 1 147

2,9 38 30 55 33 13 284 40 13 22 210 10 13 24 29 0,7 8,0 13 21 15 37 912 235 111 89 48 399 313 1 195

2,0 3,1 6,3 7,8 6,8 10 10 12 38 38 41 47 54 63 85 102 27 34 41 29 38 43 42 48 53 53 54 57 56 58 55 56 35 36 41 45 54 62 65 63 13 14 17 16 14 15 13 16 345 349 384 396 420 489 507 553 46 52 54 76 93 129 159 175 16 15 14 17 19 19 21 19 27 28 31 31 34 41 40 39 208 214 190 194 267 385 473 470 12 13 14 15 16 17 18 18 12 17 21 24 27 31 37 40 15 16 17 21 28 34 35 40 24 24 24 24 25 26 25 25 3,0 4,1 6,3 15 20 32 48 66 1,5 3,6 4,1 5,2 6,3 26 26 31 14 23 20 27 28 28 30 29 14 14 17 19 20 21 21 20 37 50 55 59 68 78 81 86 21 30 32 37 40 41 39 37 127 135 140 81 86 101 99 114 1 044 1 119 1 186 1 260 1 450 1 776 1 965 2 087 323 365 409 452 491 552 564 566 110 111 102 105 110 121 119 132 66 64 52 76 81 98 114 132 22 41 50 54 60 80 81 98 473 512 550 604 661 780 856 938 353 360 346 357 439 575 663 663 1 347 1 453 1 510 1 649 1 842 2 206 2 396 2 529

13 13 12 13 14 104 106 109 106 99 38 41 41 42 43 54 53 51 52 51 66 66 72 73 71 11 10 10 12 13 592 616 625 630 642 161 166 169 183 198 19 20 18 17 16 38 37 37 36 37 466 464 449 430 377 18 19 20 20 43 41 42 42 42 44 46 45 45 47 25 24 25 24 24 89 100 102 104 106 32 32 32 30 37 30 33 28 30 31 21 23 23 23 26 87 85 89 89 94 38 41 45 47 41 143 144 139 134 133 2 132 2 181 2 184 2 185 2 140 577 591 606 599 579 116 109 123 126 127 156 167 167 170 171 108 114 105 99 97 974 1 011 1 022 1 045 1 065 661 657 641 622 560 2 591 2 649 2 665 2 662 2 599

Пустые ячейки означают, что данные не представлены. – означает, что значение показателя не может быть рассчитано.

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Доклад о глобальной борьбе с туберкулезом 2013

Таблица 3.7

Успешность лечения среди всех новых случаев (%) и размер когорты (тыс.), 1995–2011 годы a. Успешность лечения (%) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Афганистан Бангладеш Бразилия Вьетнам ДР Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире

– 71 17 89 74 53 25 91 91 75 93 39 67 49 73 70 65 64 44 60 61 58 53 60 50 79 67 33 80 57

– 63 20 89 48 32 21 81 94 77 94 55 79 32 76 – 57 78 33 35 71 61 50 56 51 66 58 31 72 54

45 73 27 85 64 69 18 54 91 65 95 65 82 73 77 67 67 58 40 78 72 68 56 64 58 73 72 29 91 60

33 77 40 92 70 70 27 58 95 77 95 – 82 73 76 23 68 68 62 71 74 72 62 70 67 57 63 40 92 64

86 79 78 92 69 73 21 50 93 79 95 71 81 75 78 70 65 77 61 87 74 57 60 68 79 79 75 34 91 64

85 81 71 92 78 69 34 87 91 80 93 75 82 79 78 74 68 69 63 88 80 63 67 71 76 81 75 50 90 69

84 83 55 93 77 71 54 86 92 80 95 78 81 79 81 77 67 75 56 88 76 61 72 70 69 82 74 63 91 73

87 84 80 92 78 67 60 86 92 79 92 78 81 79 80 78 67 74 60 88 76 68 75 73 81 84 74 68 90 76

86 85 77 92 83 66 76 87 93 80 93 76 81 78 81 79 61 73 68 88 70 67 81 73 80 82 75 79 91 80

89 90 72 92 85 48 81 87 91 77 92 77 82 73 82 80 65 71 70 78 79 65 82 70 76 82 76 83 88 81

90 90 72 92 85 66 87 89 91 81 92 79 83 75 83 82 67 71 73 89 78 69 85 74 75 82 77 87 90 84

84 91 69 92 60 67 87 90 92 83 92 83 83 76 85 86 69 75 68 88 84 70 85 72 73 86 75 87 90 84

87 90 72 91 86 78 88 90 93 83 93 79 84 82 88 90 69 81 72 88 84 71 87 77 78 87 76 88 91 85

88 91 69 92 86 70 88 90 94 84 93 84 84 78 88 89 69 80 67 84 80 73 87 77 73 87 76 88 91 85

86 91 70 92 88 75 89 89 94 84 94 85 84 84 88 91 68 84 64 85 81 68 86 76 73 87 75 89 91 85

86 91 72 92 89 76 89 89 89 86 95 85 88 81 89 90 66 83 68 90 77 53 86 73 73 88 74 89 92 84

88 91 73 93 87 80 89 88 94 87 95 – 88 85 88 92 65 82 73 87 89 77 88 79 75 88 72 89 93 87

b. Размер когорты (тыс.) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Афганистан Бангладеш Бразилия Вьетнам ДР Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация Таиланд Уганда Филиппины Эфиопия ЮАР Страны с высоким бременем ТБ AFR AMR EMR EUR SEAR WPR В мире

11 30 46 45 38 48 16 25 9,7 12 265 291 3,0 12 4,4 9,1 6,5 13 131 175 11 13 7,9 9,7 9,5 24 20 21 0,8 0,05 43 20 0,1 15 15 90 126 5,1 11 28 45 739 967 178 233 129 134 46 51 34 94 318 360 296 372 1 001 1 245

2,0 34 43 54 26 12 293 21 12 19 189 11 9,2 11 22 2,8 0,7 3,7 18 27 12 55 879 268 125 60 24 376 294 1 147

2,9 38 30 55 33 13 284 40 13 22 210 10 13 24 29 0,7 8,0 13 21 15 37 912 235 111 89 48 399 313 1 195

2,0 3,1 6,3 7,8 6,8 10 10 12 13 13 12 26 26 38 38 41 47 54 63 119 141 144 106 156 150 148 27 34 41 29 38 81 78 81 47 73 75 78 71 53 53 54 57 56 92 55 91 91 91 88 88 89 35 36 41 45 54 62 65 92 89 93 106 109 92 13 14 17 16 14 54 43 43 39 40 45 46 40 345 349 384 396 420 1 066 1 071 1 137 1 199 1 226 1 244 1 229 1 209 46 52 54 76 93 206 244 266 263 293 289 296 314 16 15 14 17 19 30 34 34 35 38 39 40 37 27 28 31 31 34 97 98 101 99 99 99 90 82 208 214 190 194 267 644 788 847 889 932 923 877 856 12 13 14 15 16 17 18 18 18 19 20 20 12 17 21 24 27 66 73 84 85 90 91 127 135 15 16 17 21 28 34 35 40 44 46 86 78 84 24 24 24 24 25 61 59 58 25 59 60 59 59 3,0 4,1 6,3 15 20 84 117 149 191 206 212 256 255 1,5 3,6 4,1 5,2 6,3 39 74 97 99 103 101 94 89 14 23 20 27 28 47 49 47 47 54 43 48 49 14 14 17 19 20 21 21 31 37 39 38 40 43 37 50 55 59 68 126 81 123 136 140 141 162 190 21 30 32 37 40 41 39 37 38 139 139 152 91 243 259 271 247 236 367 338 292 81 86 101 99 114 1 044 1 119 1 186 1 260 1 450 3 183 3 430 3 799 3 872 4 134 4 374 4 403 4 252 323 365 409 452 491 846 886 940 930 1 087 1 297 1 215 1 094 110 111 102 105 110 191 187 197 157 168 191 200 188 66 64 52 76 81 178 226 259 307 320 331 391 398 22 42 50 55 60 184 221 274 276 279 248 250 217 473 512 550 604 661 1 530 1 639 1 758 1 835 1 880 1 940 1 980 1 986 353 360 346 357 439 963 1 030 1 163 1 216 1 261 1 259 1 240 1 213 1 347 1 453 1 511 1 649 1 843 3 892 4 188 4 592 4 720 4 995 5 267 5 275 5 096

Пустые ячейки означают, что данные не представлены. – означает, что значение показателя не может быть рассчитано.

Доклад о глобальной борьбе с туберкулезом 2013

43

Вставка 3.9

Результаты лечения ТБ с учетом ВИЧ-статуса В 2013 году 96 стран, в которых зарегистрировано 331 000 больных ТБ, сочетанным с ВИЧ-инфекцией, сообщили результаты лечения больных, взятых на лечение в 2011 году, с разбивкой по ВИЧстатусу. На эти страны пришлось 58% всех больных туберкулезом, сочетанным с ВИЧ-инфекцией, зарегистрированных в 2011 году. Это было значительное увеличение по сравнению с 2010 годом, когда на страны, которые сообщили результаты с разбивкой по ВИЧ-статусу, приходилось 25% больных ТБ, сочетанным с ВИЧинфекцией. Прогресс был связан с предоставлением данных с разбивкой по ВИЧ-статусу странами с высоким бременем ТБ/ВИЧ, такими как Уганда и ЮАР. Из 41 приоритетной страны (перечислены в Таблице 6.1 Главы 6), 19 сообщили результаты лечения с разбивкой по ВИЧ-статусу: Ботсвана, Бразилия, БуркинаФасо, Бурунди, Вьетнам, Гаити, Гана, Индия, Кения, Китай, Лесото, Мали, Мьянма, Намибия, Нигерия, Объединенная Республика Танзания, Свазиленд, Таиланд и Южно-Африканская Республика. Данные за 2011 год показывают, что результаты лечения больных ТБ, сочетанным с ВИЧ-инфекцией, остаются по-прежнему хуже, чем у ВИЧ-отрицательных больных туберкулезом. Показатель успешности лечения для всех новых случаев ТБ, сочетанного с ВИЧ-инфекцией составляет 73% по сравнению с 87% среди ВИЧотрицательных больных ТБ (Рисунок B3.9.1). Если предположить, что все больные ТБ, сочетанным с ВИЧ-инфекцией, которые прервали лечение, умерли от ТБ, смертность составит 19% среди ВИЧ-инфицированных больных ТБ по сравнению с 3% среди ВИЧ-отрицательных больных ТБ. Такие данные согласуются с результатами двух исследований с применением аутопсии, проведенных в Южно-Африканской Республике, которые показали, что не диагностированный ТБ остается основной причиной смерти среди больных ВИЧ-инфекцией a,b. Mutevedzi P et al. Early mortality following initiation of ART in rural South Africa: the contribution of existing co-morbidities. 20th Conference on Retroviruses and Opportunistic Infections. Atlanta, Georgia, USA, 3–6 March 2013 (Paper 832; www.retroconference. org/2013b/Abstracts/46910.htm, по состоянию на 3 июня 2013 года). b Martinson N et al. Undiagnosed infectious TB in adult home deaths: South Africa 2013. 20th Conference on Retroviruses and Opportunistic Infections. Atlanta, Georgia, USA, 3–6 March 2013 (Paper 837; www.retroconference.org/2013b/Abstracts/45780.htm, по состоянию на 3 июня 2013 года). a

Рисунок B3.9.1

Показатели успешности лечения (a) и смертности (b) среди ВИЧ-положительных и ВИЧ-отрицательных больных туберкулезом пациентов, 2011 год 100 80 Доля от когорты (%) 60 40 20 0 ВИЧ+ (117 094) ВИЧ(959 174) ВИЧ+ (163 300) ВИЧ(845 907) ВИЧ+ (79 817) ВИЧ(385 748) a. Показатель успешности лечения, 2011 год

Новые случаи с положительной микроскопией (данные по 88 странам)

Новые случаи с отрицательной микроскопией и случаи внелегочного ТБ (данные по 72 странам)

Случаи повторного лечения (данные по 59 странам)

30

b. Уровень смертности среди больных с документированным исходом лечения в прошедших оценку случаях, 2011 год

Процент (%)

20

10

0 ВИЧ+ (109 137) ВИЧ(925 024) ВИЧ+ (148 798) ВИЧ(811 586) ВИЧ+ (73 354) ВИЧ(370 385)

Новые случаи с положительной микроскопией (данные по 88 странам)

Новые случаи с отрицательной микроскопией и случаи внелегочного ТБ (данные по 72 странам)

Случаи повторного лечения (данные по 59 странам)

в регионах Восточного Средиземноморья (88%), Западной части Тихого океана (93%) и Юго-Восточной Азии (89%). Показатель успешности лечения составил 79% в регионе Африки, и это значительный прогресс в сравнении с 73% в 2010 году. В регионе Америки и в Европейском регионе показатель составил 75% и 72% соответственно. Из 22 стран с высоким бременем туберкулеза, 15 достигли или превысили показатель успешности лечения в 85% среди всех новых случаев в 2011 году, в том числе Эфиопия (серьезное улучшение по сравнению с 77% в 2010 году до

89% в 2011 году) и впервые целевой показатель достигнут в Нигерии. Шесть стран, которые сообщили о более низких показателях успешности лечения, были представлены Бразилией (73%), Зимбабве (80%), Россией (65%), Таиландом (82%), Угандой (73%) и Южно-Африканской Республикой (77%). Данные по Мозамбику не были зарегистрированы. Результаты лечения ТБ хуже среди ВИЧ-инфицированных больных, по сравнению с аналогичными результатами ВИЧ-отрицательных больных ТБ (Вставка 3.9). Для сокращения данного разрыва требуются дополнительные усилия.

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Глава 4

Туберкулез с лекарственной устойчивостью возбудителя Основные факты и выводы ■■ К концу 2012 года были получены данные о распространенности устойчивости к противотуберкулезным препаратам из 136 стран (70% из 194 государств-членов ВОЗ), либо из систем постоянно действующего эпиднадзора (в основном, стран с высоким уровнем доходов и других стран Европейского региона ВОЗ), либо по данным специальных исследований по изучению распространенности лекарственной устойчивости. ■■ Специальные исследования, проводимые в 2013 году в группе 36 стран с высоким бременем ТБ и/или МЛУ-ТБ, результаты которых ожидаются в 2014 году, являются впервые организованными общенациональными исследованиями в Азербайджане, Индии, Пакистане, Туркменистане и Украине, и повторными исследованиями — во Вьетнаме, Кении, Китае, Таиланде, Филиппинах, Эфиопии и Южно-Африканской Республике. ■■ В мире распространенность множественной лекарственной устойчивости ТБ среди впервые выявленных больных составила 3,6% (95%, доверительный интервал (ДИ): 2,1% — 5,1%) и среди случаев, взятых на повторное лечение 20,2% (95%, ДИ: 13,3% –27,2%). В некоторых странах Восточной Европы и Центральной Азии наблюдаются самые высокие уровни распространенности МЛУ к противотуберкулезным препаратам — 20% среди новых случаев и более 50% среди больных, взятых на повторное лечение. ■■ В 2012 году, в мире, оценочное число новых случаев МЛУ-ТБ составило 450 000 (диапазон: 300 000–600 000). Оценочное число больных туберкулезом легких с МЛУ возбудителя, которые могли быть обследованы на лекарственную устойчивость с использованием рекомендованных ВОЗ диагностических тестов и зарегистрированы НПТ, из числа всех зарегистрированных больных туберкулезом легких, составило 300 000 (диапазон: 220 000–380 000) в 2012 году. Более половины из этих случаев пришлись на Индию, Китай и Российскую Федерацию. ■■ Случаи туберкулеза с широкой лекарственной устойчивостью (ШЛУ-ТБ) были сообщены 92 странами. В среднем, оценочная доля больных ШЛУ-ТБ среди больных МЛУ-ТБ составила 9,6% (95% ДИ: 8,1%–11%). ■■ В общей сложности 94 000 случаев заболевания туберкулезом, подлежащих включению в программу лечения МЛУ-ТБ (84 000 случаев МЛУ-ТБ и 10 000 случаев туберкулеза с устойчивостью к рифампицину, обнаруженных с помощью Xpert MTB/RIF), были зарегистрированы в мире в 2012 году, в основном в европейских странах, Индии и Южно-Африканской Республике. Эти данные демонстрируют положительную динамику по сравнению с 2011 годом, когда было зарегистрировано 62 000 случаев; наблюдаемый рост в 2012 году по сравнению с 2011 годом произошел за счет улучшения регистрации случаев в Индии, Украине и Южно-Африканской Республике. Тем не менее, в мире и в большинстве стран с высоким бременем МЛУ-ТБ в 2012 году было выявлено менее одной трети случаев от оценочного числа больных МЛУ-ТБ. ■■ В список стран, выявляющих практически 100% оценочного числа больных МЛУ-ТБ, в 2012 году входили Казахстан, Латвия, Литва, Украина, Эстония и Южно-Африканская Республика. Самый низкий уровень выявления был в Юго-Восточной Азии (21%) и Западной части Тихого океана (6%), что вместе составило 55% мировых случаев МЛУ-ТБ. ■■ Из 94 000 новых больных МЛУ-ТБ, зарегистрированных в мире и подлежащих лечению препаратами второго ряда, немногим более 77 000 (82%) пациентов начали лечение в 2012 году. Разница между числом диагностированных больных к числу включенных в программу лечения препаратами второго ряда значительно выше наблюдалась в некоторых странах, особенно в регионе Африки (51% выявленных случаев приступили к лечению), и эта разница увеличилась в 2012 году по сравнению с 2011 годом в Китае, Пакистане и Южно-Африканской Республике. ■■ Цель, установленная в Глобальном плане «Остановить туберкулез» на 2011–2015 годы — доля больных МЛУ-ТБ, успешно завершивших лечение, должна составлять 75% и выше к 2015 году — была достигнута в 34 из 107 стран, предоставивших данные о результатах лечения больных когорты 2010 года. Однако, в целом, только 48% пациентов успешно завершили лечение. ■■ На глобальном и национальном уровнях срочно должны быть предприняты усилия для повышения уровня выявления и охвата лечением случаев МЛУ-ТБ, а также повышения эффективности лечения в этой группе больных.

Туберкулез с лекарственной устойчивостью (ЛУ ТБ) является одной из основных угроз в глобальной борьбе с туберкулезом и важной проблемой общественного здравоохранения в целом ряде стран. В данной главе изложены успехи в сфере глобального наблюдения за распространенностью лекарственной устойчивости; это демонстрируется с помощью последних данных о МЛУ-ТБ и ШЛУ-ТБ, полученных в рамках специальных исследований и систем непрерывного эпиднадзора, что послужило основой для уточнения оценочных данных глобального бремени МЛУ-ТБ (Раздел 4.1). Данная глава также включает оценку достижений отдельных стран в области диагностики и лечения МЛУ-ТБ, о чем свидетельствуют данные о проведении тестов по определению лекарственной чувствительности возбудителя туберкулеза, данные о лечении больных МЛУ-ТБ с использованием препаратов второго ряда и результаты этого лечения (Раздел 4.2).

4.1 Эпиднадзор за лекарственноустойчивым туберкулезом 4.1.1 Успехи в расширении охвата системой эпиднадзора за лекарственноустойчивым туберкулезом С момента запуска Глобального проекта по наблюдению за распространенностью устойчивости к противотуберкулезным препаратам в 1994 году, данные о лекарственной устойчивости систематически собирали из 136 стран мира и подвергали анализу (70% государств-членов ВОЗ). Семьдесят из указанного числа стран располагают системами непрерывного наблюдения за распространенностью лекарственной устойчивости (далее — эпиднадзор за МЛУ-ТБ), основанного на проведении тестов по определению лекарственной чувствительности (ТЛЧ) у всех больных туберкулезом. Шестьдесят шесть стран проводят специальные эпидемиологические исследования по изучению распространенности лекарственной устойчивости (далее — специальные исследования) на репрезентативных выборках пациентов. Прогресс в достижении цели глобального охвата 45

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рисунок 4.1

Успехи в глобальном мониторинге распространенности лекарственной устойчивости, 1994–2013 годы

Год получения последних данных 1995–1999 2000–2004 2005–2009 2010–2012 Проводится в 2013 г. Нет данных Только суб-национальные данные Не применимо

системой наблюдения за распространенностью лекарственной устойчивости показан на Рисунок 4.1. Эпиднадзор за МЛУ-ТБ, основанный на рутинном проведении ТЛЧ у больных туберкулезом и систематическом сборе, систематизации и анализе данных, является наиболее эффективным подходом для мониторинга тенденций в распространенности лекарственной устойчивости. Кроме того, такие системы наблюдения могут выявлять вспышки заболевания, которые могли бы быть незамеченными, даже в ходе подобного исследования, если область вспышки находится за пределами территорий, выбранных для проведения исследования. Число стран, в которых внедрена система эпиднадзора за МЛУ-ТБ, растет благодаря усилиям, направленным на расширение доступности культуральных исследований и ТЛЧ. Несколько стран с высоким бременем МЛУ-ТБ в Европейском регионе, в том числе Беларусь, Грузия, Казахстан, Республика Молдова, Украина и страны Балтии, ввели в действие эффективную систему эпиднадзора за распространенностью лекарственной устойчивости, как в отношении новых случаев, так и случаев повторного лечения от туберкулеза. Группа стран — Боливия, Египет, Колумбия, Коста-Рика, Кыргызстан, Ливан, Монголия, Никарагуа, Руанда, Сальвадор, Сирийская Арабская Республика, Таджикистан, Чили, Шри-Ланка и Эквадор — ранее располагавшие только данными специальных исследований, к настоящему времени создали системы постоянного эпиднадзора за распространенностью лекарственной устойчивости среди всех больных ТБ, включая больных с повторными курсами лечения. Это стало первым шагом на пути к достижению постоянного охвата ТЛЧ всех больных туберкулезом. Специальные исследования представляют собой наиболее распространенный метод изучения бремени лекарственной устойчивости в условиях ограниченных ресурсов, где стандартное применение ТЛЧ для всех больных туберкулезом не является доступным из-за отсутствия лабораторного потенциала или ресурсов. В период с 2010 по 2012 годы специальные исследования по изучению распространенности лекарственной устойчивости были впервые проведены в 16 странах: Албании, Афганистане (Центральный регион), Бангладеш, Беларуси, 46

Бенине, Болгарии, Йемене, Кыргызстане, Малави, Нигерии, Саудовской Аравии, Сомали, Таджикистане, Тунисе, Уганде и Узбекистане. Кроме того, Бразилия, Египет, Замбия и Непал провели повторные исследования. К середине 2013 года, специальные исследования продолжались в 12 странах с высоким бременем ТБ и высоким бременем МЛУ-ТБ. К ним относятся первые общенациональные специальные исследования в Азербайджане, Индии, Пакистане, Туркменистане, Украине и повторные специальные исследования во Вьетнаме, Кении, Китае, Таиланде, Филиппинах, Эфиопии и Южно-Африканской Республике. Молекулярные технологии все шире используются в исследованиях по определению лекарственной чувствительности с целью упрощения логистики и сокращения нагрузки на лаборатории. GenoType ® MTBDRplus (Hain Lifescience, Германия) был использован в национальном обследовании, проведенном в 2012 году в Нигерии, а Xpert ® MTB/RIF (Cepheid, США) в настоящее время используется в специальных исследованиях, проводимых в Пакистане и Папуа-Новой Гвинее. Еще несколько стран планируют начать использование Xpert MTB/RIF для скрининга в специальных исследованиях по изучению распространенности лекарственной устойчивости. Устойчивость к рифампицину, хотя и не является абсолютным критерием МЛУ-ТБ, особенно в тех местностях, где уровни лекарственной устойчивости являются низкими, тем не менее, остается наиболее достоверным индикатором МЛУ-ТБ, являющимся значительным отягощающим фактором в лечении пациентов. Xpert MTB/RIF может играть важную роль в странах, где еще не существует инфраструктуры для проведения культуральных исследований и ТЛЧ при помощи классических методов или в тех условиях, где лаборатории не могут справиться с большим объемом работы, связанным с проведением специального исследования по изучению распространенности лекарственной устойчивости. Он может быть использован для скрининга образцов на устойчивость к рифампицину и определения тех из них, которые требуют дальнейшего тестирования в национальных или наднациональных туберкулезных референс-лабораториях и, таким образом, снижения стоимости первичного скрининга, который ранее

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осуществлялся при помощи обычных коммерческих систем для проведения ТЛЧ. Пять стран с высоким бременем ТБ и МЛУ-ТБ (Афганистан, Бразилия, Демократическая Республика Конго, Индонезия и Российская Федерация) по-прежнему располагают данными о лекарственной устойчивости, собранными только на региональном уровне. Эти страны должны рассмотреть вопрос о проведении общенациональных исследований по изучению распространенности лекарственной устойчивости в ближайшее время, чтобы лучше оценить бремя МЛУ-ТБ и более эффективно планировать диагностические и лечебные мероприятия. Другие шесть стран (Гвинея, Доминиканская Республика, Зимбабве, Иран, Лесото и Сьерра-Леоне) располагают данными специальных исследований, проведенных в конце 1990-х, и должны рассмотреть возможность проведения повторных исследований. Франкоязычные страны Африки и страны Центральной Африки остаются частью мира с наименее изученной распространенностью лекарственной устойчивости, в основном, в результате слабости лабораторной инфраструктуры. Следует предпринять усилия для увеличения диагностического потенциала и системы эпиднадзора в этих странах для того, чтобы создать возможность проведения исследований по изучению распространенности лекарственной устойчивости. Из 136 стран, представивших данные о распространенности лекарственной устойчивости по данным эпиднадзора, 35% (48 стран) обладают данными только для одного момента времени и должны провести повторные исследования для оценки динамики процесса. Данные о распространенности лекарственной устойчивости в динамике были получены из 88 стран и 10 территорий мира, что в общей сложности составило 870 «страно-лет» (country-year) наблюдения. Среди 36 стран с высоким бременем туберкулеза и МЛУ-ТБ, 11 стран (Вьетнам, Грузия, Камбоджа, Латвия, Литва, Мозамбик, Мьянма, Республика Молдова, Россия (7 субъектов РФ), Таиланд и Эстония) провели, по крайней мере, два исследования в течение пяти лет, что позволяет оценить динамику

процесса во времени. Тем не менее, для пяти из этих стран (Вьетнам, Камбоджа, Мозамбик, Мьянма и  Таиланд) самые последние данные были получены более пяти лет назад. Среди шести стран, для которых имеются данные последнего времени, в Латвии и Эстонии данные демонстрируют снижение темпов распространения туберкулеза и МЛУ-ТБ. Эти данные позволяют предположить, что МЛУ-ТБ действительно можно контролировать только с помощью эффективных политических решений, осуществляемых на практике, и с помощью применения необходимых мер по профилактике и контролю над заболеванием. В Грузии, Литве, Республике Молдове и большинстве федеральных субъектов Российской Федерации уровни заболевания МЛУ-ТБ представляются стабильными, в то время как в Ивановской области и Республике Марий Эл уровни заболевания МЛУ-ТБ растут. Для проведения углубленного анализа динамики процесса в других странах требуется больший объем данных, полученных с помощью повторных исследований или от систем непрерывного наблюдения. НПТ должны планировать проведение повторных исследований по изучению распространенности лекарственной устойчивости, примерно раз в пять лет, пока не будет создана инфраструктура для постоянного наблюдения.

4.1.2 Распространенность туберкулеза с множественной лекарственной устойчивостью возбудителя среди новых случаев и случаев повторного лечения В мире, по оценочным данным, доля больных МЛУ-ТБ составила 3,6% (95%, ДИ: 2,1–5,1%) среди новых случаев заболевания туберкулезом и 20,2% (95%, ДИ: 13,3–27,2%) среди случаев повторного лечения (Таблица 4.1). Эти оценки существенно не изменились с 2011 года. Доли МЛУ-ТБ среди новых и ранее леченых случаев туберкулеза на национальном уровне показаны на Рисунке 4.2 и Рисунке 4.3, а для 27 стран с высоким бременем МЛУ-ТБ в Таблице 4.1. Восточная Европа и  особенно страны Центральной Азии

рисунок 4.2

Доля туберкулеза с множественной лекарственной устойчивостью среди новых случаев туберкулеза a

Процент случаев 0–2.9 3–5.9 6–11.9 12–17.9 ≥18 Нет данных Только суб-национальные данные Не применимо a

Рисунок составлен по данным последнего года, за который была представлена отчетность, которые различаются по странам.

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47

Таблица 4.1

Оценочная доля больных туберкулезом с МЛУ возбудителя в мире, в 27 странах с высоким бременем туберкулеза с МЛУ возбудителя и в регионах ВОЗ оценочная доля МЛУ-ТБ (%) среди новых случаев a оценочная доля МЛУ-ТБ (%) среди случаев повторного лечения a

доверительный интервал

доверительный интервал

Азербайджан Армения Бангладеш Беларусь Болгария Вьетнам Грузия ДР Конго Индия Индонезия Казахстан Китай Кыргызстан Латвия Литва Мьянма Нигерия Пакистан Республика Молдова Российская Федерация Таджикистан Узбекистан Украина Филиппины Эстония Эфиопия ЮАР Страны с высоким бременем МЛУ-ТБ AFR AMR EMR EUR SEAR WPR В мире a

22 9,4 1,4 35 2,3 2,7 9,2 2,5 2,2 1,9 23 5,7 26 11 11 4,2 2,9 3,5 24 23 13 23 14 4,0 20 1,6 1,8 4,2 2,3 2,2 3,5 16 2,2 4,7 3,6

19–27 7,0–12 0,7–2,5 33–37 1,3–3,8 2,0–3,7 7,9–11 0,1–5,0 1,9–2,6 1,4–2,5 22–24 4,5–7,0 23–31 8,8–14 9,5–14 3,1–5,6 2,1–4,0 0,1–12 21–26 21–25 9,8–16 18–30 14–15 2,9–5,5 14–26 0,9–2,8 1,4–2,3 2,1–6,2 0,2–4,4 1,4–3,0 0,1–11 10–22 1,6–2,8 3,3–6,1 2,1–5,1

56 43 29 69 23 19 31 10 15 12 55 26 68 32 44 10 14 32 62 49 56 62 32 21 50 12 6,7 21 11 14 33 45 16 22 20

50–62 38–49 24–34 66–71 17–31 14–25 27–35 3,5–17 11–19 8,1–17 54–56 22–30 65–72 23–42 39–49 6,9–14 10–19 7,5–56 59–65 45–53 52–61 53–71 31–33 14–29 35–65 5,6–21 5,4–8,2 12–30 4,4–17 4,7–22 12–54 39–52 11–21 18–27 13–27

по-прежнему имеют самые высокие уровни МЛУ-ТБ. Доля больных с МЛУ-ТБ среди новых случаев составила в Азербайджане (22,3% в 2007 году), Беларуси (34,8% в 2012 году), Казахстане (22,9% в  2012 году), Кыргызстане (26,4% в  2011 году), Республике Молдове (23,7% в 2012 году), России (в среднем: 23,1%, в Ямало-Ненецком автономном округе самый высокий уровень — 41,9% в 2011 году), Узбекистане (23,2% в 2011 году) и Эстонии (19,7% в 2012 году). Доля больных с МЛУ-ТБ среди случаев повторного лечения составила: в Азербайджане (город Баку: 55,8% в 2007 году), Беларуси (68,6% в 2012 году), Казахстане (55,0% в 2012 году), Кыргызстане (68,4% в 2012 году), Республике Молдове (62,3% в 2012 году), Таджикистане (56,0% в 2012 году), Узбекистане (62,0% в 2011 году) и Эстонии (50,0% в 2012 году). В Российской Федерации, несмотря на то, что в среднем по стране доля случаев МЛУ-ТБ не превышает 50%, в нескольких субъектах РФ доля значительно выше 50% (например, в Ульяновской области самый высокий уровень 74% в 2011 году) 1.

Вставка 4.1

МЛУ-ТБ у детей Установление диагноза туберкулеза у детей представляет сложную задачу в связи с олигобациллярностью процесса в детском возрасте. Образцы, пригодные для проведения культуральных исследований и ТЛЧ, особенно трудно получить у детей младшего возраста, которые не могут откашливать мокроту. По этим причинам о бремени МЛУ-ТБ у детей известно очень мало. Зависимость между МЛУ-ТБ и возрастной группой (дети младше 15 лет в сравнении со взрослыми в возрасте от 15 лет и старше) была недавно изучена при помощи репрезентативных данных исследования распространенности лекарственной устойчивости, предоставленных в ВОЗ, в период с 1994 по 2012 годы. Анализу подлежали 376 293 случая заболевания туберкулезом больных, которые содержали информацию о возрасте и результатах ТЛЧ. Отношения шансов (odds ratios) были получены путем логистической регрессии с учетом серьезной среднеквадратической погрешности, как описано подробно в других источниках a. Из 85 стран, предоставивших данные общенациональных специальных исследований или данные непрерывного эпиднадзора, 34 страны сообщили о наличии, по крайней мере, одного случая детского МЛУ-ТБ. Было доказано, что страдающие ТБ дети и взрослые имеют равный шанс иметь МЛУ возбудителя. Поэтому очень важно, чтобы выявление МЛУ-ТБ у детей было более эффективным. Следует предпринимать усилия для систематического проведения наблюдения за бытовыми контактами всех пациентов с МЛУ-ТБ, включая детей. Кроме того, обследования детей должны быть частью, как системы эпиднадзора, так и специальных исследований по изучению распространенности лекарственной устойчивости. a

Zignol et al. Multidrug-resistant tuberculosis in children: evidence from global surveillance. European Respiratory Journal 2013; 42:701–7.

Наилучшая оценка для последнего года, по которому представлены данные. Оценочные значения, выделенные курсивом, основаны на региональных данных.

Более позитивные данные получены во многих частях мира, где уровень лекарственной устойчивости среди новых случаев остается низким (<3%), в том числе почти во всех странах региона Америки, большинстве африканских стран, где проводятся исследования по изучению распространенности лекарственной устойчивости, большинстве стран региона Юго-Восточной Азии, большинстве стран Западной Европы, и в нескольких странах региона Западной части Тихого океана (включая Австралию, Вьетнам, Камбоджу, Новую Зеландию и Японию).

1

Туберкулез в Российской Федерации, 2011 год: аналитический обзор статистических показателей, используемых в Российской Федерации и в мире (на русском языке). Москва, Министерство здравоохранения РФ, 2013 год

48

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рисунок 4.3

Доля туберкулеза с множественной лекарственной устойчивостью среди случаев повторного лечения a

Процент случаев 0–5.9 6–11.9 12–29.9 30–49.9 ≥50 Нет данных Только суб-национальные данные Не применимо a

Данные за последний год, за который была представлена отчетность, варьируются по странам. Большая доля МЛУ-ТБ среди случаев повторного лечения в Бахрейне, Бонайре-Санкт-Эстатиус и Саба, в Исландии, на островах Кука, Сан-Томе и Принсипи и Ливане обусловлены малым числом зарегистрированных случаев ТБ (<10).

4.1.3 Оценочный показатель заболеваемости МЛУТБ и оценочное число случаев МЛУ-ТБ среди зарегистрированных больных туберкулезом в мире в 2012 году Данные, собранные системой эпиднадзора о лекарственной устойчивости среди больных туберкулезом, позволили получить оценочное число случаев МЛУ-ТБ в мире в 2012 году. Это оценочное число случаев заболевания МЛУ-ТБ включает не только зарегистрированные в системе эпиднадзора случаи, но и те случаи МЛУ-ТБ, которые могли входить в число не зарегистрированных и не выявленных случаев туберкулеза. В мире в 2012 году, по оценочным данным, насчитывалось 450 000 (диапазон: 300 000–600 000) новых случаев заболевания МЛУ-ТБ. Методы, при помощи которых были получены представленные данные, описаны в Приложении 1. Данные, полученные из систем эпиднадзора за лекарственной устойчивостью у больных туберкулезом, позволили также рассчитать число случаев МЛУ-ТБ в мире и по странам среди зарегистрированных случаев туберкулеза легких. Данные случаи МЛУ-ТБ, можно было бы выявить силами НПТ, если бы все зарегистрированные больные туберкулезом легких были обследованы с помощью ТЛЧ к рифампицину и изониазиду, используя рекомендованные ВОЗ диагностические тесты. Доля больных, обследованных ТЛЧ, является также важным индикатором оценки эффективности работы в странах по диагностике и лечению МЛУ-ТБ. В мире в 2012 году, по оценкам, насчитывалось 300 000 (диапазон: 220 000–380 000) случаев МЛУ-ТБ среди всех зарегистрированных больных туберкулезом. Оценочные данные по отдельным странам обсуждаются в Разделе 4.2.

4.1.4 Лекарственная устойчивость к препаратам второго ряда К концу 2012 года 92 страны мира сообщили о наличии случаев туберкулеза с широкой лекарственной устойчивостью возбудителя (ШЛУ-ТБ) (Рисунок 4.4). В общей сложности 75 стран и 4  территории сообщили репрезентативные данные из систем эпиднадзора или специальных исследований о распространенности ШЛУ-ТБ среди МЛУ-ТБ. Если объединить эти данные, то доля случаев ШЛУ-ТБ среди больных МЛУ-ТБ составила 9,6% (95%, ДИ: 8,1% –11%), что приблизительно соответствует оценке 2011 года (9,0%). Тринадцать из этих стран сообщили о более 10 случаях ШЛУ-ТБ за последний период времени, по которому были доступны данные. Среди этих стран доля случаев МЛУ-ТБ с ШЛУ-ТБ была самой высокой в Азербайджане (г. Баку: 12,8%), Беларуси (11,9%), Латвии (16,0%), Литве (24,8%) и Таджикистане (г. Душанбе и район Рудаки: 21,0%). Доля случаев МЛУ-ТБ с устойчивостью к фторхинолонам и инъекционным препаратам второго ряда составила 16,5% (95%, ДИ: 12,3–20,7) и  22,7% (15,4%-30,0%) соответственно. В общей сложности 32,0% (21,9%-42,1%) больных с МЛУ-ТБ имеют устойчивость к фторхинолонам, инъекционным агентам второго ряда или тем и другим одновременно. Эти пациенты имеют право на получение bedaquiline, недавно утвержденного нового бактерицидного препарата для использования у пациентов с МЛУ-ТБ, в случаях, когда возможности лечения при помощи имеющихся лекарств были исчерпаны (см. Вставку 8.2 в Главе 8).

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49

рисунок 4.4

Страны, в которых зарегистрирован как минимум один случай туберкулеза с широкой лекарственной устойчивостью к концу 2012 года

Зарегистрирован как минимум один случай Нет зарегистрированных случаев Не применимо

4.2 Организация медицинской помощи больным туберкулезом с лекарственной устойчивостью возбудителя к противотуберкулезным препаратам 4.2.1 Охват исследованием по определению лекарственной чувствительности возбудителя к противотуберкулезным препаратам Диагноз туберкулеза с устойчивостью возбудителя к противотуберкулезным препаратам (ЛУ ТБ) не может быть установлен без проведения исследования по определению лекарственной чувствительности выделенного возбудителя к противотуберкулезным препаратам (ТЛЧ). Данные по регистрации случаев туберкулеза в сочетании с данными систем надзора за лекарственной устойчивостью дают основание считать, что если бы все зарегистрированные больные туберкулезом легких были обследованы с помощью ТЛЧ, в 2012 году было бы обнаружено около 300 000 случаев МЛУ-ТБ (Раздел 4.1.3). Цели, указанные в Глобальном плане «Остановить туберкулез» на 2011–2015 годы, заключаются в необходимости обеспечить к 2015 году всех новых больных туберкулезом, имеющих высокий риск МЛУ-ТБ (по оценкам, около 20% всех новых больных туберкулезом с бактериовыделением в мире), и больных, взятых на повторное лечение, обследованием с помощью ТЛЧ, по крайней мере, к препаратам первого ряда — рифампицину и изониазиду. Кроме того, все пациенты с МЛУ-ТБ должны быть обследованы на наличие ШЛУ-ТБ. В 2012 году немногим более 50% стран сообщили результаты ТЛЧ к препаратам первого ряда, и средний охват тестированием оставался низким ( Таблица 4.2). В мире только 5% новых больных ТБ с бактериовыделением и 9% больных, взятых на повторное лечение, были обследованы с целью выявления МЛУТБ в 2012 году. Доля новых случаев, имеющих результаты ТЛЧ, 50

незначительно увеличилась в последние годы, но остается ниже целевого показателя Глобального плана, предусмотренного на 2012 год (Рисунок 4.5). Охват был самым высоким в Европейском регионе, где 72% новых случаев и 41% случаев повторного лечения были обследованы с помощью ТЛЧ в 2012 году, что отражает относительно более высокую доступность лабораторной диагностики, чем в других регионах. Охват тестированием был особенно низким в регионе Африки и Юго-Восточной Азии (0,3% и 0,1% новых, бактериологически подтвержденных случаев и 3,1% и 0,7% больных, взятых на повторное лечение, соответственно). Среди 27 стран с высоким бременем МЛУ-ТБ, на долю которых приходится более 85% оценочного числа случаев МЛУ-ТБ в мире, доля больных туберкулезом, которые прошли тестирование, находилась в диапазоне от 56% до 100% среди новых случаев в 13 из 14 европейских стран, предоставивших данные (17% в Таджикистане; данные по Азербайджану отсутствуют), и превысила 60% среди больных, взятых на повторное лечение, в девяти из этих стран. Среди стран с высоким бременем МЛУ-ТБ, не входящих в Европейский регион, охват тестированием на МЛУ-ТБ среди новых случаев был самым высоким в Китае (3,6%). Охват тестированием пациентов, взятых на повторное лечение, был выше и достиг 10% в Индонезии и 12% в Китае и на Филиппинах. В Южно-Африканской Республике 16% больных туберкулезом прошли тестирование на МЛУ-ТБ, но результаты ТЛЧ не были представлены отдельно для новых и ранее леченых случаев. Пять других стран не предоставили данных, включая Индию, страну с наибольшим оценочным числом случаев МЛУ-ТБ среди зарегистрированных больных туберкулезом (Таблица 4.2). В 2012 году сообщалось, что 23% больных туберкулезом, зарегистрированных с подтвержденным диагнозом МЛУ-ТБ, прошли ТЛЧ как к фторхинолонам, так и к инъекционным препаратам второго ряда. Охват ТЛЧ к препаратам второго ряда превысил 90% в Армении, Болгарии, Грузии, Демократической

Доклад о глобальной борьбе с туберкулезом 2013

Таблица 4.2

Охват тестированием по определению лекарственной чувствительности больных туберкулезом и больных МЛУ-ТБ, в мире, в 27 странах с высоким бременем МЛУ-ТБ и в регионах ВОЗ, 2012 год Новые бактериологически подтвержденные случаи Число случаев с результатом ТЛЧ a Доля случаев с результатом ТЛЧ (%) Случаи повторного лечения Число случаев с результатом ТЛЧ a Доля случаев с результатом ТЛЧ (%) Подтвержденные случаи МЛУ-ТБ Число случаев с результатом ТЛЧ b Доля случаев с результатом ТЛЧ (%)

Азербайджан Армения Бангладеш Беларусь Болгария Вьетнам Грузия ДР Конго Индия Индонезия Казахстан c Китай Кыргызстан Латвия Литва Мьянма Нигерия Пакистан Республика Молдова Российская Федерация Таджикистан Узбекистан Украина Филиппины Эстония Эфиопия ЮАР Страны с высоким бременем МЛУ-ТБ AFR AMR EMR EUR SEAR WPR В мире 77 277 2 216 28 625 1 990 85 962 1 352 16 485 136 630 11 461 1 264 32 647 919 2 703 11 185 35 193 469 2 8 154 11 472 958 666 1 017 1 931 12 286 41 2 164 687

– 64 <0,1 90 71 – 84 <0,1 – <0,1 >100 3,6 57 97 100 – <0,1 0,4 67 79 17 56 77 <0,1 100 1,0 – 3,9 0,3 22 1,1 72 0,1 3,3 5,1 42 851 3 969 5 481 1 617 37 774 2 292 8 134 59 267 94 154 933 12 324 496 798 5 925 2 038 46 180 821 10 443 4 861 662 100 350 541 95 108 557 1 183 142

– 27 7,0 84 45 – 45 1,3 – 10 93 12 61 88 100 – 1,2 1,3 63 24 66 30 72 8,7 82 4,4 – 7,7 3,1 23 7,6 41 0,7 10 8,7 11 046 16 225 11 303 1 384 51 2 523 1 619 2 365 19 245 55 345 356 2 042 511 106 210 84 341 65 597 184 49 92 142

– 100 28 – 100 – 99 100 3,6 43 – 68 53 96 77 11 – – – – 50 21 – – 89 – 72 21 62 47 3,2 6,7 8,4 53 23

Пустые ячейки означают, что данные не представлены. – означает, что значение показателя не может быть рассчитано. a ТЛЧ к изониазиду и рифампицину. b ТЛЧ к фторхинолону и инъекционным препаратам второго ряда. c Возможным объяснением того, что доля для новых случаев в Казахстане превышает 100%, является несогласованность между клиническим и лабораторным регистрами.

Республике Конго и Латвии. На Южно-Африканскую Республику пришлась большая часть случаев туберкулеза в мире, по которым были предоставлены результаты ТЛЧ к препаратам второго ряда, так же как и самая высокая доля случаев, зарегистрированных в регионе Африки (региональный показатель падает с 62% до 1%, если исключить Южно-Африканскую Республику). Данные ТЛЧ к препаратам второго ряда были

доступны для 53% случаев МЛУ-ТБ в регионе Западной части Тихого океана, 47% в регионе Америки и 3–8% в других регионах. Необходимо срочно обеспечить повышение охвата обследованием ТЛЧ с целью улучшения выявления МЛУ-ТБ и ШЛУ-ТБ. Для этого требуется укрепление лабораторного потенциала, внедрение новых экспресс-методов диагностики и улучшение отчетности в диагностических центрах (см. Главу 5). Обнаружение 51

Доклад о глобальной борьбе с туберкулезом 2013

рисунок 4.5

Охват обследованием на лекарственную чувствительность среди новых случаев и число больных, взятых на лечение по поводу МЛУ-ТБ, в сравнении с целевыми показателями Глобального плана «Остановить ТБ» на 2011–2015 годы. Линии обозначают плановые показатели, синие квадраты — ситуацию в 2009–2012 годах и оранжевые круги — прогнозируемое число больных, которые будут взяты на лечение в 2013– 2015 годах. Данные по прогнозируемому числу больных, которые будут взяты на лечение в 2015 году, были неполными. 25 20 Процент случаев 15 10 5 0 2009 Число больных a. Охват ТЛЧ бактериологически подтвержденных новых случаев 300 000 250 000 200 000 150 000 100 000 50 000 0 2009 b. Число больных, взятых на лечение от МЛУ-ТБ

2010

2011

2012

2013

2014

2015

2010

2011

2012

2013

2014

2015

Вставка 4.2

Туберкулез с широкой лекарственной устойчивостью возбудителя в Африке В 2006 году, информация о вспышке туберкулеза с широкой лекарственной устойчивостью возбудителя (ШЛУ-ТБ) в сельских районах Южно-Африканской Республики попала в заголовки международной прессы a. Все пациенты из этой группы, прошедшие тестирование на ВИЧ-инфекцию, оказались инфицированными ШЛУ-ТБ. Большинство из этих пациентов вскоре умерли. В ЮжноАфриканской Республике регистрируется наибол ́ ьшая часть случаев ШЛУ-ТБ в мире, и число зарегистрированных случаев увеличилось с 467 в 2009 году до 1596 в 2012 году. Около 10% случаев заболевания МЛУ-ТБ, зарегистрированных в этой стране, имеют также ШЛУ-ТБ.

случаев ШЛУ-ТБ в  странах мира (Вставка  4.2 , Рисунок  4.4) отражает риск приобретения дополнительной лекарственной устойчивости к препаратам второго ряда и передачи устойчивых штаммов в случае, если меры лечения и профилактики (в том числе инфекционного контроля) ТБ являются неадекватными.

4.2.2 Регистрация туберкулеза с множественной лекарственной устойчивостью возбудителя и предоставление лечения Низкий охват обследованием с помощью ТЛЧ является одной из основных причин низкого уровня выявления МЛУ-ТБ во многих странах. В мире 83 715 случаев заболевания МЛУ-ТБ были сообщены ВОЗ в 2012 году. Более половины из этих случаев ( Таблица 4.3) пришлись на Индию, Российскую Федерацию и Южно-Африканскую Республику. Кроме того, было зарегистрировано чуть более 10 000 случаев рифампицин-устойчивого туберкулеза (РУ-ТБ), обнаруженных с помощью быстрых молекулярных методов 1. Каждая из перечисленных стран — Индия, Кыргызстан, Узбекистан и Филиппины — сообщили более 500 случаев. В 2012 году 83 715 зарегистрированных случаев МЛУ-ТБ составили 28% от 300 000 (диапазон: 220 000–380 000) оценочных случаев туберкулеза легких с МЛУ возбудителем (Таблица 4.3), по сравнению с 20% в 2011 году; и 19% от 450 000 (диапазон: 300 000–600 000) оценочных случаев заболевания МЛУ-ТБ в мире в 2012 году. Большая часть прироста случаев, зарегистрированных в 2012 году по сравнению с 2011 годом, приходится на Индию (с 4 237 до 16 588), Украину (с 4 305 до 6 934) и Южно-Африканскую Республику (с 10 085 до 15 419) 2, хотя рост регистрации был отмечен в 17 странах с высоким бременем МЛУ-ТБ и во всех регионах ВОЗ, за исключением региона Америки. Во Вьетнаме, Демократической Республике Конго и на Филиппинах, в которых было выявлено менее 30% случаев от ожидаемого числа в 2012 году, число зарегистрированных случаев МЛУ-ТБ снизилось в 2012 году по сравнению с 2011 годом. Из всех случаев 1

Рисунок B4.2.1

Результаты лечения 623 больных туберкулезом с широкой лекарственной устойчивостью возбудителя в Южно-Африканской Республике в 2010 году Завершили лечение 6% Умерли 49% Излечены 12%

Результат неизвестен 17% Неэффективное лечение 8%

Потеряны для наблюдения 9%

К концу 2012 года 15 стран в регионе Африки выявили и сообщили, по крайней мере, об одном случае ШЛУ-ТБ (Рисунок 4.4). В 2012 году две страны с высоким бременем МЛУ-ТБ в регионе Африки — Демократическая Республика Конго и Нигерия — сообщили о выявлении первых случаев ШЛУ-ТБ. Семь африканских стран сообщили о начале лечения пациентов с ШЛУ-ТБ в 2011 или 2012 году, большинство из них в Южно-Африканской Республике. Результаты лечения, представленные из ЮжноАфриканской Республики, показывают очень низкую вероятность благоприятного исхода у таких больных и высокую долю пациентов, потерянных для наблюдения, или у которых исход лечения не был определен (см. Рисунок B4.2.1). a

Gandhi NR, Moll A, Sturm AW, Pawinski R, Govender T, Lalloo U, et al. Extensively drug-resistant tuberculosis as a cause of death in patients co-infected with tuberculosis and HIV in a rural area of South Africa. The Lancet. 2006; 368(9547):1575–80.

Это дополнительные случаи наряду с другими рифампицин-устойчивыми случаями, обнаруженными Xpert MTB/RIF, которые были включены в число больных МЛУ-ТБ, так как у них была обнаружена устойчивость к изониазиду. 2 В Южно-Африканской Республике число обнаруженных случаев было выше предполагаемого среди больных легочным туберкулезом, что говорит или о сильном занижении предполагаемого числа случаев МЛУ-ТБ среди больных туберкулезом, и/или об отсутствии связи между клиническими и лабораторными корпусами данных.

52

Доклад о глобальной борьбе с туберкулезом 2013

Таблица 4.3

Оценочное число больных МЛУ-ТБ в 2012 году, зарегистрированные случаи МЛУ-ТБ, больные, взятые на лечение по поводу МЛУ-ТБ в период 2009–2012 годы, результаты лечения в когорте 2010 года в мире, в 27 странах с высоким бременем МЛУ-ТБ и регионах ВОЗ Оценочное число случаев МЛУ-ТБ среди зарегистрированных случаев туберкулеза легких, 2012 год Зарегистрированные случаи Случаи, взятые на лечение МЛУ-ТБ Случаи МЛУ-ТБ с документированным исходом лечения, когорта 2010 года

лучш.

Низк.

Высок.

2009

2010

2011

2012

2012 зарегистрированные/ оценочные случаи (%) a

2009

2010

2011

2012

N

%b

Азербайджан Армения Бангладеш Беларусь Болгария Вьетнам Грузия ДР Конго Индия Индонезия Казахстан Китай Кыргызстан Латвия Литва Мьянма Нигерия Пакистан Республика Молдова Российская Федерация Таджикистан Узбекистан Украина Филиппины Эстония Эфиопия ЮАР Страны с высоким бременем МЛУ-ТБ AFR AMR EMR EUR SEAR WPR В мире

2 800 250 4 200 2 200 100 3 800 630 2 900 64 000 6 900 8 800 59 000 1 800 120 300 6 000 3 600 11 000 1 700 46 000 910 4 000 6 800 13 000 70 2 100 8 100 270 000 38 000 7 100 18 000 74 000 90 000 74 000 300 000

2 600 220 3 100 2 100 78 3 000 570 670 49 000 5 200 8 700 52 000 1 600 100 270 4 600 2 700 0 1 600 43 000 800 3 700 6 500 10 000 56 1 200 6 900 180 000 14 000 4 500 0 60 000 71 000 57 000 220 000

3 000 280 5 200 2 200 130 4 600 690 5 100 79 000 8 500 9 000 66 000 1 900 140 330 7 500 4 500 29 000 1 800 49 000 1 000 4 300 7 000 16 000 85 3 000 9 400 350 000 62 000 9 600 42 000 88 000 110 000 91 000 380 000 3 644 474 785 131 322 815 28 49 1 069 14 686 319 654 3 482 1 073 86 233 9 070 40 798 10 741 2 884 496 28 157 2 560 2 059 46 897 1 342 43 217 369 91 1 660 156

552 177 339 1 576 56 101 359 87 2 967 182 7 387 2 792 566 87 310 192 21 444 1 082 13 692 333 1 023 5 336 522 63 140 7 386 47 772 9 340 2 661 873 33 776 3 942 4 295 54 887

811 79 509 1 594 55 601 475 121 4 237 383 7 408 1 601 806 105 296 690 95 344 1 001 13 785 604 1 385 4 305 1 148 78 212 10 085 52 813 12 384 3 474 841 34 199 6 615 4 394 61 907

596 92 513 1 604 49 273 346 65 16 588 428 7 608 3 007 958 110 271 778 107 1 602 894 13 612 694 1 728 6 934 679 62 284 15 419 75 301 18 129 2 967 2 236 36 708 19 202 4 473 83 715

21 37 12 73 49 7,2 55 2,2 26 6,2 86 5,1 53 92 90 13 3,0 15 53 30 76 43 >100 5,2 89 14 >100 28 48 42 12 50 21 6,0 28 43 307 266 176 1 136 20 3 209 458 545 124 322 64 0 368 334 8 143 52 464 3 186 501 86 88 4 143 24 521 5 994 3 153 707 17 169 2 040 1 429 30 492 134 352

286 154 339 200 56 101 618 191 2 967 142 5 705 1 222 566 87 310 192 23 424 791 13 692 245 628 3 870 548 63 120 5 402 38 942 7 209 3 249 967 28 336 3 901 2 210 45 872

592 88 390 1 446 42 578 737 128 3 384 260 5 261 1 155 492 103 296 163 38 344 765 18 902 380 855 4 950 2 397 75 199 5 643 49 663 7 467 3 087 756 36 313 4 597 4 946 57 166

406 101 513 2 478 36 713 665 179 14 143 426 7 213 1 906 790 110 271 442 125 1 045 853 18 452 535 1 491 7 672 1 918 54 289 6 494 69 320 9 303 3 102 1 602 42 399 15 845 5 070 77 321

263 132 329 1 442 56 97 504 105 2 182 140 5 777 1 222 441 88 310 188 23 195

48 75 97 91 100 96 140 121 74 77 78 44 78 101 100 98 110 44 –

4 681 245 628 3 902 783 64 114 4 882 28 793 6 166 2 374 676 19 496 3 113 2 456 34 281

34 74 61 73 150 102 81 66 60 66 89 77 58 79 57 62

Пустые ячейки означают, что данные не представлены. – означает, что значение показателя не может быть рассчитано. a Доля зарегистрированных случаев МЛУ-ТБ в 2012 году от величины наилучшей оценки случаев МЛУ-ТБ среди всех случаев ТБ легких в том же году. Доля может превышать 100%, если оценочное значение случаев МЛУ-ТБ занижено, и если отсутствует достаточная координация при ведении клинического и лабораторного регистров. b Доля случаев МЛУ-ТБ, зарегистрированных в 2010 году, по которым имеются сведения об исходах лечения. Доля может превышать 100% в связи с получением новых данных о числе зарегистрированных больных МЛУ-ТБ в 2010 году, недостаточной координацией между системами регистрации больных ЛЧ ТБ и больных МЛУ-ТБ, а также регистрацией исходов лечения больных, зарегистрированных ранее 2010 года.

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53

рисунок 4.6

Оценочное число случаев туберкулеза с множественной лекарственной устойчивостью возбудителя среди зарегистрированных больных туберкулезом легких, 2012 год

Случаи МЛУ-ТБ 0–199 200–1999 2000–19 999 20 000–49 999 ≥ 50 000 Нет данных Не применимо

МЛУ-ТБ, зарегистрированных в мире в 2012 году, большинство (82%) были обнаружены в Европейском регионе (36 708), Индии (16 588) или Южно-Африканской Республике (15 419). В число стран, выявляющих практически 100% больных с МЛУТБ, в 2012 году вошли Казахстан, Латвия, Литва, Украина, Эстония и Южно-Африканская Республика (Таблица 4.3). В регионе Африки, Европейском регионе и регионе Америки, по оценкам, было выявлено около 50% пациентов с МЛУ-ТБ в 2012 году. Самые низкие показатели были в двух регионах с наибольшим числом случаев: регион Юго-Восточной Азии (21%) и регион Западной части Тихого океана (6%). Индия и Китай, две страны, на которые по оценочным данным приходится наибольшее число больных туберкулезом с МЛУ-ТБ (в каждой более 50 000 больных, Рисунок 4.6), сильно влияют на общие показатели стран Юго-Восточной Азии и Западной части Тихого океана. Китай и Индия вместе с Российской Федерацией, которая занимает третье место в мире по общему числу случаев МЛУ-ТБ, выявили и зарегистрировали менее одной трети от оценочного числа случаев МЛУ-ТБ (5%, 26% и 30% соответственно). Число больных туберкулезом, которые приступили к лечению препаратами второго ряда по режимам лечения МЛУ-ТБ, увеличилось с 30 492 в 2009 году до 77 321 в 2012 году (+154%). В 2012 году по сравнению с 2011 годом наблюдался 40% рост числа больных, получающих лечение по поводу МЛУ-ТБ, в 27 странах с высоким бременем МЛУ-ТБ, что отражает успех в 20 из этих стран, особенно в Индии, Казахстане и Украине ( Таблица 4.3). Отношение числа пациентов, получающих лечение лекарственными препаратами второго ряда по поводу МЛУ-ТБ, к числу пациентов, зарегистрированных с диагнозом МЛУ-ТБ в 2012 году, составило 92% в мире в целом (или 82%, если включить случаи рифампицин-устойчивого ТБ), но было ниже в регионах Африки (51%) и Юго-Восточной Азии (83%) (Таблица 4.3). Число пациентов, находящихся в ожидании предоставления лечения по поводу МЛУ-ТБ, остается неизменным или растет в ряде стран, 54

особенно, если учитывать дополнительные случаи РУ-ТБ, диагностированные с помощью Xpert MTB/RIF. Разница в соотношении диагностированные:начавшие лечение, превышающая 5% или более, наблюдалась в 14 странах с высоким бременем МЛУ-ТБ в 2012 году (Рисунок 4.7), а соотношение числа больных, зарегистрированных с диагнозом МЛУ-ТБ к числу больных, начавших лечение по поводу МЛУ-ТБ, увеличилось в период с 2011 года по 2012 год более, чем на 10% в Китае, Пакистане и Южно-Африканской Республике. Число случаев ШЛУ-ТБ, зарегистрированных в мире, увеличилось с 1 464 до 2230 в период с 2011 года по 2012 год. Все регионы ВОЗ сообщили об увеличении числа случаев ШЛУ-ТБ, получавших лечение в 2012 году, в сравнении с 2011 годом, что составило 1 557 случаев в мире в 2012 году. Типичные препятствия на пути повышения эффективности лечения включают в себя критическую нехватку обученного персонала, недостаточную доступность препаратов второго ряда, нехватку медучреждений для проведения лечения и мониторинга, низкий уровень выявления больных, а также недостатки в ряде других мероприятий, таких как координация деятельности, необходимой для эффективной борьбы с ЛУ ТБ. В мире существует дефицит средств для обеспечения лечением всех больных МЛУ-ТБ, и требуется увеличение объема ресурсов, выделяемых для системной борьбы с МЛУ-ТБ. В нескольких странах, таких, как Грузия, Российская Федерация и Украина, число больных, начавших лечение по поводу МЛУ-ТБ, превышает число зарегистрированных больных МЛУ-ТБ в последние годы. Возможные объяснения — назначение эмпирического режима больным с риском лекарственной устойчивости при отсутствии лабораторно подтвержденного диагноза, неполное предоставление лабораторных данных или предоставление лечения «давним» пациентам или пациентам с МЛУ-ТБ, состоявшим в списках ожидания, диагноз которым был поставлен до 2012 года.

Доклад о глобальной борьбе с туберкулезом 2013

рисунок 4.7

Выявленные случаи туберкулеза с множественной лекарственной устойчивостью (оранжевый) и дополнительные случаи туберкулеза с устойчивостью к рифампицину (синий) в сравнении со случаями МЛУ-ТБ, взятыми на лечение (зеленый) в 2009–2012 годах в мире и в 27 странах с высоким уровнем бремени МЛУ-ТБ, 2009–2012 годы Азербайджан 800 600 400 200 0 150 100 200 50 0 0 1000 500 0 2000 400 1500 200

Армения

600

Бангладеш

2500

Беларусь

60

Болгария

800 600 400

Вьетнам

800

Грузия

200 150 100

ДР Конго

40

600

20

200 0

400 50 200 0

0

Индия 15000

500 400 300 200

Индонезия 8000 6000 4000

Казахстан

3000

Китай

10000

2000

5000 100 0 0

1000 2000 0 0

1000

Кыргызстан

150

Латвия

350 330

Литва 800

Мьянма

Число случаев

750 500 250 0

100

310 290

600 400 200 0

50 270 0 250

Нигерия 300

2000 1500

Пакистан

1100 900 700

Республика Молдова

20000

Российская Федерация

15000

200

1000 500 0

100

10000 500 300 5000

0

800 600 400 200 0

Таджикистан

2000 1500

Узбекистан

8000

Украина

2500 2000 1500

Филиппины

6000 1000 500 0 4000

1000 2000 500

100 80 60 40 20 0

Эстония

300

Эфиопия 15000

ЮАР 100 000 80 000 60 000 40 000 5000 20 000

В мире

200 10000 100

0 2010 2011 2012 2009 2010 2011 2012

0 2009 2010 2011 2012

0 2009 2010 2011 2012

2009

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Вставка 4.3

Фармакологический надзор и борьба с туберкулезом A PRACTICAL HANDBOOK ON THE PHARMACOVIGILANCE OF MEDICINES USED IN THE TREATMENT OF TUBERCULOSIS ENHANCING THE SAFETY OF THE TB PATIENT

Фармаконадзор определяется ВОЗ как: «Научные дисциплины и мероприятия, связанные с выявлением, оценкой, изучением и предупреждением неблагоприятных побочных реакций от лекарственных средств или с любыми другими проблемами, возникшими в результате приема лекарственных препаратов».

Для достижения целей Глобального плана и создания всеобщего доступа к лечению необходимы решительные и согласованные действия по многим направлениям борьбы с туберкулезом, особенно в странах с наиболее высоким бременем болезни. Возможности решения этой проблемы выросли за последние годы в результате усиленной технической поддержки, предоставляемой международными организациями. После реформирования структуры Комитета Зеленого Света (КЗС) в 2011 году и создания комитетов регионального уровня (рКЗС) во всех шести регионах ВОЗ международная поддержка стран в вопросах укрепления борьбы с ЛУ ТБ в настоящее время сосредоточена на повышении доступности ресурсов и оказании технической помощи странам.

Неблагоприятные побочные реакции от лекарственных средств (НПР) могут привести к досрочному прерыванию лечения больными ТБ, тем самым способствуя распространению инфекции, развитию лекарственной устойчивости и неэффективности лечения, снижению качества жизни больного или наступлению смерти. Важно регулярно следить за наличием НПР у больных туберкулезом, находящихся на лечении в НПТ. Это особенно важно при лечении больных с ЛУ ТБ и больных ТБ, сочетанным с ВИЧ-инфекцией. Три подхода, используемые в фармаконадзоре: •• Извещения, направляемые в национальные центры фармаконадзора, по решению лечащего врача (например, об ототоксичности, развившейся в результате приема аминогликозидов). •• Извещения, направляемые в национальные центры фармаконадзора, по решению лечащего врача о серьезных реакциях при лечении определенного заболевания, например при лечении больных с МЛУ-ТБ. •• Мониторинг НПР в когорте пациентов. Представляет собой активную форму наблюдения, схожую по структуре и управлению с таковой при проведении эпидемиологического когортного исследования, и особенно хорошо подходит для пост-маркетингового контроля новых лекарств. В 2012 году ВОЗ подготовила руководство по фармаконадзору при лечении туберкулеза a. ВОЗ предлагает техническую помощь странам для внедрения и укрепления фармаконадзора в их программах. Пособие содержит информацию о том, как фармаконадзор может быть эффективно реализован в рамках программы по борьбе с туберкулезом с участием ключевых заинтересованных сторон, в том числе регулирующих органов и производителей, а также описывает пошаговый подход к выявлению случаев НПР, установлению причинноследственных связей между приемом лекарственного средства и НПР, обеспечению мониторинга НПР и информированию заинтересованных сторон о результатах мониторинга. a

4.2.3 Оценка эффективности лечения туберкулеза с множественной и широкой лекарственной устойчивостью возбудителя Внедрение стандартных методов и показателей мониторинга позволило странам отчитываться о результатах лечения МЛУТБ в сопоставимых показателях в течение последних нескольких лет. В 2013 году были упрощены определения (дефиниции) исходов лечения, а также было принято решение включать случаи рифампицин-резистентного ТБ в когорту больных МЛУТБ (Вставка 4.4). Число регистрируемых для лечения больных МЛУ-ТБ в когортах 2007–2010 годов утроилось, при этом отмечался рост во всех регионах мира (Рисунок 4.8). Начиная с 2007 года и по настоящее время, страны с тяжелым бременем МЛУ-ТБ сообщили результаты лечения, по крайней мере, по одной годовой когорте больных. В общей сложности 107 стран сообщили о результатах лечения более 34 000 больных МЛУ-ТБ, начавших лечение в 2010 году (Таблица 4.3), что составило 62% от числа случаев МЛУ-ТБ, зарегистрированных в том же году. Низкий охват лечением отражает слабые места систем отчетности в части сопоставления данных о результатах лечения с количеством зарегистрированных случаев. Глобальный план предусматривает, что к 2015 году все страны будут сообщать о результатах лечения всех зарегистрированных больных МЛУ-ТБ. Только 71 страна, в том числе 13 стран с высоким бременем МЛУ-ТБ, сообщили о результатах лечения более 80% от всех зарегистрированных в 2010 году случаев МЛУ-ТБ. В целом, доля пациентов с МЛУ-ТБ, завершивших лечение с исходом «успешное лечение», в когорте пациентов 2010 года, составила 48%, а  28% случаев из этой когорты завершили лечение с исходами «потерян для наблюдения» или «результат неизвестен». Доля больных с исходом «успешное лечение» была самой высокой в регионе Восточного Средиземноморья (56%), а также в регионе Америки (54%), в последнем он растет с 2007 года наряду с уменьшением доли пациентов, результаты лечения которых отсутствуют. В когорте 2010 года число умерших было самым высоким в регионе Африки (17%), а доля больных с  неэффективным лечением была самой высокой в Европейском регионе (11%). Цель Глобального плана состоит в достижении успешности лечения пациентов с МЛУ-ТБ на уровне не менее 75% к 2015 году и она была достигнута только в 34 из 107 стран (из них три страны с высоким бременем МЛУТБ: Бангладеш, Вьетнам и Эфиопия), сообщивших о результатах лечения когорты больных 2010 года. Среди 795 пациентов с ШЛУ-ТБ в 26 странах уровень успешности лечения в среднем составил 20%, и 44% пациентов умерли; за исключением Южно-Африканской Республики, где эти показатели составили 27% и 28% соответственно (Вставка 4.2). Для повышения эффективности лечения требуется увеличить охват программным лечением на глобальном уровне, повысить эффективность назначаемых режимов лечения, усилить поддержку больных для обеспечения непрерывности лечения и повысить качество сбора данных. В частности, странам

A practical handbook on the pharmacovigilance of medicines used in the treatment of tuberculosis: enhancing the safety of the TB patient. Geneva, World Health Organization, 2012 (www.who.int/medicines/ publications/pharmacovigilance_tb/).

Среди 119 стран, представивших данные о числе больных, приступивших к лечению, дезагрегированных по полу, отношение числа мужчин к числу женщин было равно 2. Большинство стран, представивших данные о лечении МЛУ-ТБ, не предоставили информацию о лечении детей. В 44 странах, предоставивших данные, доля детей колебалась от менее 1% до 33% в общем числе пролеченных пациентов. Многие страны предусматривают увеличение числа пациентов, которым будет предоставлено лечение от МЛУ-ТБ, в период с 2013 по 2015 годы. Однако глобальные прогнозы остаются значительно ниже целей Глобального плана, отчасти в результате медленных темпов роста, а также неполной информации по темпам охвата лечением, особенно для Китая (2015 год) и Российской Федерации (2013 год) (Рисунок 4.5b). 56

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Рисунок 4.8

Результаты лечения больных туберкулезом с множественной лекарственной устойчивостью по регионам ВОЗ, когорты 2007–2010 годов Общее число случаев с имеющимся исходом лечения отображается рядом с каждой строкой. Африка 2007 2008 2009 2010 4 570 5 496 6 143 6 166 2007 2008 2009 2010 Америка 1 458 1 732 2 298 2 374

Восточное Средиземноморье 2007 2008 2009 2010 128 262 511 676 2007 2008 2009 2010

Европа 4 097 6 904 12 131 19 496

Юго-Восточная Азия 2007 2008 2009 2010 253 413 1 140 3 113 2007 2008 2009 2010

Регион Западной части Тихого океана 453 758 1 027 2 456 0% 20% 40% 60% 80% 100%

В мире 2007 2008 2009 2010 0% 20% 40% 60% 80% 100% 10 959 15 565 23 250 34 281

Излечен Неэффективное лечение

Завершил лечение Потерян для наблюдения

Умер Результат неизвестен

необходимо провести анализ причин низких результатов лечения у пациентов с МЛУ-ТБ, активизировать меры по повышению приверженности лечению и усилить мониторинг. Программы по борьбе с ТБ должны обеспечить комплекс мероприятий по лечению больных с МЛУ-ТБ, который включает бесплатное предоставление диагностических услуг, противотуберкулезных и других лекарственных средств, оказание мер социальной поддержки, а также использование более коротких схем лечения, согласно текущей политике ВОЗ, для отдельных групп пациентов. Лечение больных с ШЛУ-ТБ в целом остается очень неудовлетворительным и требуется разработка более эффективных схем лечения.

4.2.4 Другие аспекты управления программами борьбы с МЛУ-ТБ Лечение больных МЛУ-ТБ может быть организовано как в амбулаторных, так и в стационарных условиях, включая предоставление специализированной и  высокоспециализированной

помощи. ВОЗ рекомендует, при возможности, организовывать лечение больных МЛУ-ТБ в амбулаторных условиях или на дому, а не ставить в основу организации помощи преимущественно стационарное лечение. Модели оказания помощи отличаются большим разнообразием. Среди стран с высоким бременем МЛУ-ТБ, самый низкий уровень госпитализации был сообщен Филиппинами (5% пациентов с МЛУ-ТБ), колебался от 75% до 100% в странах Восточной Европы, и был ниже в Центральной Азии (30–50% в Казахстане, Таджикистане и Узбекистане). В регионе Африки наблюдается значительный разброс в долях больных МЛУ-ТБ, получавших стационарное лечение, начиная с 10% больных (Демократическая Республика Конго) до 100% (Нигерия и Эфиопия). В мире, средняя продолжительность пребывания в стационаре составляла от 7 до 240 дней (медиана: 84 дня). Число амбулаторных посещений, после установления диагноза МЛУ-ТБ, также заметно отличается в разных странах, начиная с 30 или менее (Бангладеш, Вьетнам, Демократическая Республика Конго, Пакистан 57

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и Эстония) до более 600 (Болгария, Индонезия, Латвия, Таджикистан и Узбекистан). Паллиативная помощь и  помощь при терминальных состояниях, предоставляемая на дому или в стационарных учреждениях, является основополагающей мерой для облегчения страданий, связанных с МЛУ-ТБ, особенно у пациентов

Вставка 4.4

Определения ВОЗ для результатов лечения РУ-ТБ, МЛУ-ТБ и ШЛУ-ТБ Излечен. Завершен полный курс лечения в соответствии с рекомендациями НПТ при отсутствии признаков неэффективности лечения и наличии трех или более последовательных отрицательных результатов культуральных исследований, проведенных, по крайней мере, с интервалом в 30 дней после завершения интенсивной фазы лечения. Завершил лечение. Завершен полный курс лечения в соответствии с рекомендациями НПТ при отсутствии признаков неэффективности, но отсутствуют сведения о наличии трех или более последовательных отрицательных результатов культуральных исследований, проведенных, по крайней мере, с интервалом в 30 дней после завершения интенсивной фазы лечения. Неэффективное лечение. Лечение прекращено или имелась необходимость в замене не менее двух противотуберкулезных препаратов из-за: •• Отсутствия конверсии мокроты к концу интенсивной фазы; или •• Возобновления бактериовыделения в фазе продолжения лечения после ранее наступившей конверсии мокроты; или •• Дополнительной приобретенной устойчивости к фторхинолонам или инъекционным препаратам второго ряда; или •• Неблагоприятных побочных реакций на лекарственные средства. Умер. Пациент, умерший от любой причины во время курса лечения. Потерян для наблюдения. Пациент, лечение которого было прервано на два месяца подряд или более. Результат неизвестен. Пациент, данные о результатах лечения которого отсутствуют (данный исход лечения включает пациентов, переведенных в другое медицинское учреждение, в случае если результаты лечения неизвестны). Успешное лечение. Сумма пациентов с результатом лечения «излечен» и «лечение завершено». Когорта. Группа больных туберкулезом с устойчивостью возбудителя к рифампицину (РУ-ТБ, включая МЛУ-ТБ и ШЛУ-ТБ), которая была зарегистрирована для прохождения полного курса лечения препаратами второго ряда по режиму лечения МЛУ-ТБ в течение определенного периода (например, когорта случаев МЛУ-ТБ, зарегистрированных в 2010 календарном году). Число больных, зарегистрированных в этой группе, составляет знаменатель для расчета показателей эффективности лечения. Согласно пересмотренным определениям, все пациенты, которым поставлен диагноз лекарственно-устойчивого туберкулеза и которые получают лечение препаратами второго ряда, удаляются из когорты больных туберкулезом с сохраненной чувствительностью возбудителя. Это означает, что ведение основного регистра (журнала) больных туберкулезом должно быть согласовано с регистром больных туберкулезом, получающих лечение препаратами второго ряда, чтобы обеспечить надлежащий учет результатов лечения. Более подробно определения конверсии мокроты, возобновления бактериовыделения и критерии для завершения интенсивной фазы приведены в руководстве ВОЗ a. a

с прогрессирующим некурабельным заболеванием. Всего одиннадцать стран с высоким бременем МЛУ-ТБ, из которых,10 стран в Европейском регионе и Южно-Африканская Республика, сообщили о предоставлении такой ​​ помощи в рамках НПТ. Принимая во внимание неблагоприятный исход, регистрируемый у больных с МЛУ-ТБ, и особенно с ШЛУ-ТБ, и эти данные, можно сделать вывод о постоянной и масштабной неудовлетворенной потребности в паллиативной помощи в странах с самым высоким бременем лекарственно-устойчивого туберкулеза. Среди 18 стран с высоким бременем МЛУ-ТБ, предоставивших информацию о качестве препаратов второго ряда в государственном секторе в 2012 году, две страны сообщили, что все препараты, которые они использовали, соответствовали только национальным регулятивным нормам. Из остальных 16 стран, большинство сообщили о соответствии международным стандартам всех поставок канамицина (11 стран), капреомицина (9 стран, 2 другие страны не используют этот препарат), левофлоксацина (10 стран, 1 страна не использует), этионамида/ протионамида (12 стран), циклосерина/теризидона (11 стран) и  п-аминосалициловой кислоты (10  стран, 2  страны не используют). Требуется более подробная информация для надлежащего мониторинга больных с МЛУ-ТБ по сравнению с мониторингом больных с лекарственно-чувствительным ТБ. Определения для мониторинга лечения РУ-ТБ и МЛУ-ТБ и его результатов были пересмотрены в 2013 году (см. Главу 3 и  Вставку 4.4). В связи с вышеизложенным, настоятельно рекомендуется ведение данных о пациентах в электронном виде. Одна из целей Глобального плана заключается в том, чтобы все 27 стран с высоким бременем МЛУ-ТБ обеспечили сбор данных по лечению больных МЛУ-ТБ в электронном виде к 2015 году. К 2012 году 19 стран сообщили о создании национальных баз данных больных МЛУ-ТБ (см. Рисунок 2.16 в  Главе 2). Эти системы существенно отличаются от страны к стране, варьируясь от системы, основанной на доступной онлайн персонифицированной информации, до систем, основанных на периодической сверке записей в регистрах, ведение которых организовано по всей стране. Прежде, чем внедрять электронные системы обработки данных о пациентах, ВОЗ рекомендует НПТ провести детальную оценку своих потребностей и ожидаемых результатов, чтобы принять правильное решение по варианту информатизации противотуберкулезной службы. Следует избегать фрагментарного подхода с параллельными системами, занимающимися различными программными компонентами (например, управление данными для пациентов с лекарственно-чувствительным и лекарственно-устойчивым туберкулезом в отдельных системах). В 2012 году ВОЗ с техническими партнерами выпустила руководство по разработке и внедрению электронных систем для записи и предоставления данных 1.

Definitions and reporting framework for tuberculosis – 2013 revision (WHO/HTM/TB/2013.2). Geneva, World Health Organization, 2013 (www. who.int/iris/bitstream/10665/79199/1/9789241505345_eng.pdf).

1

Electronic recording and reporting for TB care and control. Geneva, World Health Organization, 2013 (WHO/HTM/TB/2011.22).

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Глава 5

Диагностика туберкулеза и развитие лабораторной службы Основные факты и выводы ■■ Традиционные лабораторные методы диагностики туберкулеза, которые используются в течение многих десятилетий, представляют собой микроскопическое исследование мазков мокроты и культуральные исследования. Эталонным методом считается культуральное исследование (посев диагностического материала), но получение результатов этого исследования занимает несколько недель. Для определения чувствительности выделенных культур к противотуберкулезным препаратам первого и второго ряда проводится исследование по определению лекарственной чувствительности (ТЛЧ). ■■ В последние годы в диагностике туберкулеза были совершены важные прорывы. В 2010 году ВОЗ одобрила первый экспрессный молекулярно-генетический тест Xpert ® MTB/RIF, который позволяет одновременно подтвердить диагноз туберкулеза и выявить устойчивость к рифампицину. Чувствительность данного теста гораздо выше, чем у микроскопии мазка мокроты, и сравнима с культуральным исследованием на плотных средах. В 2013 году, в связи с появлением новых данных, приступили к пересмотру политики (принятой в 2010 году) использования и возможностей Xpert MTB/RIF для диагностики легочных, внелегочных форм туберкулеза и туберкулеза у детей. Выход обновленного руководства ожидается в 2014 году. ■■ К настоящему времени увеличилось число стран, использующих Xpert MTB/RIF. По состоянию на конец июня 2013 года, 1402 установки GeneXpert и 3,2 млн картриджей Xpert MTB/RIF были закуплены 88 из 145 стран, получивших право на закупку оборудования по льготным ценам. Почти половина (49%) заявленных стран и территорий с низким и средним уровнем доходов сообщили, что рекомендации, изложенные в руководящих указаниях ВОЗ по Xpert MTB/RIF, были учтены при составлении национальных рекомендаций. Южно-Африканская Республика является первой страной, принявшей Xpert MTB/RIF в качестве основного первичного диагностического теста на туберкулез, заменив им микроскопическое исследование мазка мокроты. ■■ Требуется значительное усиление лабораторного потенциала для обеспечения высокого качества проведения микроскопии мазка мокроты. Только 14 из 22 стран с высоким бременем туберкулеза достигли целевого показателя обеспеченности центрами микроскопии (1 центр микроскопии на 100 000 населения) в 2012 году, и только восемь стран сообщили о наличии программы по внешней оценке качества, которая охватила не менее 95% всех центров в стране. ■■ В целом, в мире возможности лабораторной службы по выполнению ТЛЧ ограничены и уровень охвата этим исследованием растет недостаточно быстро, чтобы обеспечить своевременную диагностику МЛУ-ТБ. С 2009 по 2012 год доля больных, обследованных ТЛЧ, среди впервые выявленных больных увеличилась с 4% до 5%, а среди больных, взятых на повторное лечение ТБ, с 6% до 9% соответственно. В рамках Проекта EXPANDTB (Расширение доступа к новым средствам диагностики), начатого в 2009 году, в «фазу регулярного тестирования» вступило 25 стран и была продемонстрирована возможность внедрения рутинного тестирования на лекарственную чувствительность и значительного роста выявляемости МЛУ-ТБ. ■■ Национальная референс-лаборатория Уганды стала новым членом сети наднациональных референс-лабораторий (НРЛ) Глобальной инициативы по развитию лабораторий (GLI) ВОЗ, заполнив важную географическую нишу в регионе Восточной Африки.

Раннее, быстрое и точное выявление и диагностика туберкулеза и лекарственной устойчивости основывается на наличии оптимально организованной и оснащенной сети клинических и бактериологических лабораторий. Лабораторное подтверждение туберкулеза и лекарственной устойчивости имеет решающее значение для подтверждения диагноза у лиц с признаками и симптомами туберкулеза и своевременного назначения адекватного режима лечения. Традиционные (классические) лабораторные тесты для диагностики туберкулеза, которые использовались в течение многих десятилетий, представляют собой микроскопический анализ мазка мокроты (исследование мокроты на кислотоустойчивые микобактерии методом микроскопии) и культуральные исследования. Культуральные методы являются эталоном, но результаты этих исследований бывают готовы в течение нескольких недель. Для выявления устойчивости выделенных культур к противотуберкулезным препаратам первого и второго ряда используется тестирование на лекарственную чувствительность (ТЛЧ). В последнее десятилетие, в результате увеличения объемов инвестиций в научные исследования по борьбе с туберкулезом (Глава 8), достигнуты большие успехи в разработке новых методов диагностики ТБ. В 2008 году ВОЗ рекомендовала применение экспрессного анализа олигонуклеотидными зондами (АОЗ) для выявления туберкулеза с устойчивостью возбудителя к рифампицину и МЛУ-ТБ у больных с положительными результатами микроскопических и культуральных исследований. В 2010 году АОЗ тест-система Xpert  ® MTB/RIF (Cepheid, Sunnyvale, CA, USA), которая позволяет одновременно подтверждать диагноз ТБ и определять устойчивость к рифампицину, была рекомендована для диагностики туберкулеза легких и устойчивости к рифампицину у взрослых. Чувствительность данного метода гораздо выше, чем у микроскопии мазка мокроты, и сравнима с культуральным исследованием на плотных средах 1. Несмотря на то, что лабораторная диагностика играет важнейшую роль в борьбе с ТБ, только 57% из 4,6 млн новых случаев туберкулеза легких в мире были верифицированы с помощью рекомендованного ВОЗ бактериологического метода в 2012 году. Низкий уровень лабораторного подтверждения может приводить к тому, что лица с неправильно установленным диагнозом туберкулеза будут получать лечение, в то время как истинные случаи туберкулеза могут оставаться без лечения. Следует также отметить, что 5,7 млн новых случаев (впервые выявленных и рецидивов) заболевания туберкулезом, диагностированных и зарегистрированных НПТ в 2012 году, составляют лишь 66% от 8,6 млн оценочных новых случаев заболевания туберкулезом в мире. Эта разница отражает, как неполную регистрацию выявленных случаев туберкулеза, так и проблему выявления всех случаев заболевания. Последний фактор может быть частично отнесен к низкому лабораторному потенциалу во многих странах.

1

Steingart KR et al. Xpert® MTB/RIF assay for pulmonary tuberculosis and rifampicin resistance in adults (Review). Cochrane Database of Systematic Reviews 2013, Issue 1. Art. No.: CD009593. 2013.

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Диагностирование туберкулеза без определения лекарственной чувствительности возбудителя и последующее лечение могут приводить к неблагоприятным исходам лечения, дополнительным и неоправданным страданиям, затратам пациентов и дальнейшему распространению лекарственно-устойчивых штаммов. Несмотря на небольшое увеличение с 2011 по 2012 годы, только 5,1% впервые выявленных больных и 8,7% ранее пролеченных больных были обследованы с помощью ТЛЧ в 2012 году. Из 300 000 расчетных случаев МЛУ-ТБ среди зарегистрированных больных туберкулезом легких в 2012 году (то есть больных, известных НПТ, и которые могли быть обследованы для выявления лекарственной устойчивости с помощью рекомендованных ВОЗ диагностических тестов), только у 83 715 больных диагноз МЛУ-ТБ был верифицирован лабораторными методами, и они были поставлены на учет в 2012 году. Кроме того, немногим более 10 000 случаев туберкулеза с устойчивостью возбудителя к рифампицину (РУ-TБ) были выявлены с помощью экспрессных молекулярно-генетических методов, хотя и без результата ТЛЧ к изониазиду на момент предоставления данных. Учитывая большое бремя не диагностированного лекарственно-устойчивого туберкулеза, повышение охвата больных обследованием с помощью ТЛЧ является приоритетной задачей для НПT (см. также Главу 4). Данная глава состоит из трех частей. Раздел 5.1 суммирует основные изменения в методических рекомендациях ВОЗ в  области диагностики туберкулеза и  совершенствования работы лабораторной службы в 2012–2013 годах. Раздел 5.2 представляет состояние лабораторной службы на глобальном, региональном и национальном уровнях на основе данных, представленных в ВОЗ странами в 2013 году. Внимание, главным образом, сосредоточено на 36 странах из объединенного списка, включающего 22 страны СВБ и 27 стран с высоким бременем МЛУ-ТБ. В разделе также освещается инновационное государственно-частное партнерство в области лабораторной диагностики. В Разделе 5.3 описываются последние достижения в развитии лабораторной службы, включая интеграцию методических рекомендаций ВОЗ в политику и практику национальных противотуберкулезных программ и обзор текущего состояния двух международных проектов (EXPAND-ТБ и TBXpert), целью которых является внедрение новых методов диагностики.

5.1 Изменения в методических рекомендациях ВОЗ по методам диагностики туберкулеза и развитию лабораторий, 2012–2013 годы Группа независимых экспертов ВОЗ на регулярной основе занимается разработкой политики по совершенствованию диагностики ТБ, что включает обобщение данных, полученных из систематических обзоров и исследований с применением мета-анализа, в соответствии с методикой GRADE 1, а также разрабатывает рекомендации 2 для распространения в странах-членах ВОЗ и среди других заинтересованных организаций 3. Программные документы пересматриваются каждые 3–5 лет и по мере необходимости вносятся изменения, когда появляются новые данные. Первое издание руководства ВОЗ по использованию диагностического теста Xpert ® MTB/RIF (далее Xpert MTB/RIF) было выпущено в декабре 2010 года. Согласно изложенным в нем принципам, Xpert MTB/RIF следует использовать в качестве первого диагностического теста среди лиц, имеющих риск МЛУ-ТБ или лиц, страдающих туберкулезом, сочетанным с ВИЧ-инфекцией (строгая рекомендация). Xpert MTB/RIF может применяться после проведения микроскопии в территориях с невысокой распространенностью МЛУ-ТБ и/или ВИЧ-инфекции, особенно в группе больных с отрицательным результатом микроскопии мазка мокроты (условная рекомендация, имеющая ограничения, 60

в связи с необходимостью привлечения значительных ресурсов). Рекомендации 2010 года касались тестирования с помощью Xpert MTB/RIF только образцов мокроты, так как информация о точности исследований (чувствительность и специфичность) диагностического материала, полученного из внелегочных локализаций, в то время была ограничена. Эти рекомендации применялись и к детям, но только на основе обобщения данных по взрослым больным. В результате быстрого внедрения Xpert MTB/RIF (см. Раздел 5.2) к 2013 году 4 был получен большой объем новых данных. Было получено намного больше информации по точности теста (чувствительность и специфичность) при применении в разных лабораторных условиях и при разной напряженности эпидемического процесса, дополнительных данных о точности теста при выявлении внелегочного ТБ и ТБ у детей, а также информации о доступности и экономической эффективности, благодаря информации, полученной от тех, кто уже внедрил этот метод в немногочисленных пилотных проектах. В связи с вышеизложенным, в 2013 году ВОЗ приступила к пересмотру методических рекомендаций по использованию упомянутого метода. Три систематических обзора были посвящены определению чувствительности и специфичности Xpert MTB/RIF при диагностике легочной и внелегочной форм ТБ и рифампицин-устойчивого туберкулеза (РУ-TБ) у взрослых и детей. Также был проведен обзор публикаций о результатах исследований по доступности и экономической эффективности Xpert MTB/RIF. Группа экспертов ВОЗ в мае 2013 года провела пересмотр последних данных в соответствии с подходом GRADE. На основании результатов этого пересмотра и рекомендаций, составленных Группой экспертов и поддержанных Стратегической, Технической и Консультативной Группой ВОЗ (STAG-TB) в июне 2013 года, в то время когда данный отчет был уже отправлен в печать, происходило обновление методических рекомендаций ВОЗ. Ожидается, что новые методические рекомендации, окажут значительное влияние на дальнейшее внедрение тест-системы Xpert MTB/RIF в диагностические и клинические алгоритмы во всех странах мира. Несколько других новых диагностических тестов на ТБ находятся на различных стадиях исследования и разработки (см. Главу 8). После того, как данные об их эффективности в различных эпидемических условиях станут доступны, ВОЗ сможет оценить их эффективность и разработать рекомендации по их применению. Полный список существующих программных документов ВОЗ по этой теме, в том числе рекомендации по проведению микроскопических и культуральных исследований, ТЛЧ и некоммерческих и молекулярно-генетических тест-систем, можно найти на сайте: http://www.who.int/tb/laboratory/policy_statements. В дополнение к материалам по собственно лабораторной диагностике, ВОЗ также разрабатывает другие руководства по укреплению системы лабораторного обеспечения. В 2013 году был выпущен Справочник ВОЗ по биологической безопасности в микобактериологических лабораториях. Данный справочник поддерживает подход, основанный на оценке рисков, и указывает на необходимые меры биобезопасности, 1 2

www.gradeworkinggroup.org WHO handbook for guideline development. Geneva, World Health Organization, 2012. 3 Стратегии ВОЗ по диагностике ТБ доступны на: www.who.int/tb/ laboratory/policy_statements 4 Weyer K et al. Rapid molecular TB diagnosis: evidence, policy-making and global implementation of Xpert® MTB/RIF. European Respiratory Journal. November 22, 2012, doi: 10.1183/09031936.00157212

Доклад о глобальной борьбе с туберкулезом 2013

которые должны соблюдаться во время выполнения различных лабораторных процедур. Справочник содержит информацию о принципах надлежащей лабораторной практики и об административных мерах противоэпидемического режима, принципах ликвидации последствий биологических аварий, об оборудовании и инженерных сооружениях, необходимых для обеспечения безопасности и минимизации риска образования инфекционных аэрозолей, что снижает риск инфицирования M. tuberculosis в лаборатории. В справочнике предложена трехуровневая система мер биобезопасности в лабораториях, сопряженная с «низким», «умеренным» и «высоким» риском инфицирования M. tuberculosis при выполнении определенных лабораторных процедур: •• Меры предосторожности при низком риске инфицирования, а именно, при выполнении микроскопии для выявления кислотоустойчивых бактерий и работе с Xpert MTB/RIF. •• Меры предосторожности при умеренном риске инфицирования — при подготовке образцов мокроты для первичного посева на диагностические среды, прямом тестировании (клинических образцов с положительным результатом микроскопии) с использованием прямых некоммерческих тест-систем на лекарственную устойчивость и АОЗ. •• Меры предосторожности при высоком риске инфицирования (включающие систему ликвидации биологических аварий). На этом уровне обеспечены требования безопасности работы с культурами, выделенными на плотных и жидких средах на этапах идентификации выделенных культур и проведения ТЛЧ, а также при непрямом тестировании (т. е. на выделенных культурах) с использованием АОЗ и некоммерческих тест-систем для проведения ТЛЧ.

5.2 Возможности лабораторной диагностики туберкулеза на глобальном, региональном и национальном уровнях Диагностика туберкулеза в большинстве стран с низким и средним уровнем доходов по-прежнему ограничивается возможностями дешевого метода микроскопии мазка мокроты, несмотря на его относительно низкую чувствительность и отсутствие возможности определять лекарственную чувствительность. В  Глобальном плане «Остановить ТБ» на 2011–2015 годы установлена цель — обеспечить население мира центрами микроскопии мокроты из расчета, по крайней мере, один центр на 100 000 населения. На мировом уровне цель была достигнута (1,1 центр на 100 000 населения в 2012 году), но на региональном и национальном уровнях остаются значительные различия ( Таблица 5.1). Восемь из 22 СВБ не достигли цели в 2012 году: Бангладеш, Вьетнам, Китай, Мьянма, Нигерия, Пакистан, Российская Федерация и Южно-Африканская Республика. В целом, в Западной части Тихого океана и в регионе Восточного Средиземноморья количество центров было менее одного на 100 000 населения. Учитывая важную роль микроскопии в выявлении ТБ и мониторинге лечения, обеспечение высокого качества проведения микроскопии мазка мокроты имеет важное значение. Из 153 стран и территорий, которые представили данные о количестве центров, проводящих микроскопию мазка мокроты в 2012 году, только 39% указали на существование внешней программы оценки качества, которая охватывает все центры в стране. Среди 22 СВБ, только три сообщили о наличии такой​​ программы, которая охватывает все центры в 2012 году (Бангладеш, Вьетнам и Индия), пять сообщили о программе, которая охватывает не менее 95% центров (Камбоджа, Китай, Мьянма, Российская Федерация и Южно-Африканская Республика), и 14 сообщили о программе, которая включала по меньшей мере 80% центров.

В 2009 году ВОЗ рекомендовала заменить световую микроскопию более чувствительной флюоресцентной микроскопией с использованием свето-излучающих диодов (далее — СИД-микроскопы). В мире, переход на СИД-микроскопию происходит постепенно и, как сообщалось в отчетах, только 2% центров микроскопии использовали это оборудование в  2012  году. В целом, в 2012 году регион Африки опережал другие регионы в оснащении лабораторий СИД-микроскопами (6% микроскопических центров), а в самом регионе лидирует Южно-Африканская Республика, где ими оснащено 97% центров микроскопии. Некоторые страны с высоким бременем туберкулеза региона Африки показали значительный рост оснащенности СИД-микроскопами центров микроскопии с 2011 по 2012 годы, например, Объединенная Республика Танзания (от 3% до 17%) и Мозамбик (от менее 1% до 9%). Текущая цель Глобального плана «Остановить ТБ» на 2011-2015 годы в отношении возможности проведения культуральных исследований и ТЛЧ (по крайней мере, к рифампицину и изониазиду) заключается в обеспечении функционирования одной лаборатории на 5 миллионов населения. В 2012 году 14 из 27 стран с высоким бременем МЛУ-ТБ не достигли этой цели (см. Вставку 5.1, две страны не представили данных). Из этих 27 стран, 9 стран (страны Европейского региона и Южно-Африканская Республика) сообщили о наличии более одной лаборатории, выполняющей тест АОЗ (молекулярный метод с высокой пропускной способностью, который может использоваться на центральном и региональном уровнях для быстрого выявления устойчивости к рифампицину и, в некоторых случаях, к изониазиду) на 5 миллионов населения. Из 147 стран и территорий, которые ответили на вопрос о количестве лабораторий, выполняющих ТЛЧ, 22 страны указали, что не обладали таким потенциалом в 2012 году. Для стран и территорий с небольшим числом больных туберкулезом представляется более рациональным проводить ТЛЧ в соседних странах, чем создавать собственные лаборатории. Страны с большим контингентом больных ТБ должны стремиться создать собственную лабораторную базу для проведения ТЛЧ на национальном уровне, что позволит своевременно выявлять лекарственно-устойчивые штаммы. Восемь стран, в которых было зарегистрировано более 1000 случаев туберкулеза в 2012 году, сообщили об отсутствии возможности проводить ТЛЧ: Афганистан, Гвинея-Бисау, Либерия, Папуа-Новая Гвинея, Сомали, Сьерра-Леоне, Чад и Эритрея. Проведение ТЛЧ с системой обеспечения качества имеет решающее значение для точного выявления лекарственной устойчивости и назначения адекватного лечения, а также для снижения вероятности ложной диагностики. В отчетах стран с высоким бременем ТБ и МЛУ-ТБ, представивших информацию об участии лабораторий, выполняющих ТЛЧ в системе внешней оценки качества, было указано, что 34 из 36 стран участвуют в этой системе, а 27 стран (79%) сообщили о полном охвате этих лабораторий системой внешней оценки качества. Всего в мире из 117 стран, сообщивших о системе внешней оценки качества лабораторий, выполняющих ТЛЧ, 82 страны (70%) участвуют в этой системе. Xpert MTB/RIF активно внедряется во многих странах мира благодаря высокой чувствительности при обнаружении возбудителя туберкулеза и выявлению устойчивости к рифампицину, а также низким требованиям к лабораториям для его размещения. По состоянию на конец июня 2013 года, 3,2 млн картриджей и 1402 системы GeneXpert (составляющие 7553 модуля) были закуплены 88 из 145 стран, имеющих право на приобретение машин и картриджей по льготным ценам (Рисунок 5.1) 1. Действующая цена одного картриджа составляет 9,98 долл. США, 1

http://www.who.int/tb/laboratory/mtbrifrollout/

Доклад о глобальной борьбе с туберкулезом 2013

61

Таблица 5.1

Лабораторный потенциал, 2012 год a Микроскопия мазка Страны с высоким бременем ТБ Страны с высоким бременем МЛУ-ТБ Доля (%) лабораторий, использующих приставку СИД Культуральные исследования Определение лекарственной чувствительности Число лабораторий на 5 млн населения Число лабораторий, выполняющих АОЗ XPERT MTB/RIF

Да   Нет  

Число лабораторий

Число лабораторий на 100 000 населения

Число лабораторий

Число лабораторий на 5 млн населения

Число лабораторий

Число лабораторий

Число лабораторий на 5 млн населения

ЧИСЛО учреждений

Азербайджан Армения Афганистан Бангладеш Беларусь Болгария Бразилия Вьетнам Грузия ДР Конго Зимбабве Индия Индонезия Казахстан Камбоджа Кения Китай Кыргызстан Латвия Литва Мозамбик Мьянма Нигерия ОР Танзания Пакистан Республика Молдова Российская Федерация Таджикистан Таиланд Уганда Узбекистан Украина Филиппины Эстония Эфиопия ЮАР

                                   

                                   

72 30 603 1 070 196 34 4 000 800 11 1 522 185 13 098 5 566 466 214 1 818 3 328 122 16

0,8 1,0 2,0 0,7 2,1 0,5 2,0 0,9 0,3 2,3 1,3 1,1 2,3 2,9 1,4 4,2 0,2 2,2 0,8 –

4 0 2 2 2 0 – <1 9 <1 1 2 0 0 10 8 2 0 0 – 9 14 2 17 <1 – – 4 6 8 1 5 <1 100 0 97 2 2 6 <1 <1 2 2 2 2 – – – – – – – – –

7 1 2 3 29 31 220 25 2 4 2 70 46 22 3 2 1 014 11 4

3,8 1,7 0,3 < 0,1 15 21 5,5 1,4 2,3 0,3 0,7 0,3 0,9 6,8 1,0 0,2 3,7 10 9,7 –

3 1 0 3 8 14 35 2 1 2 2 38 5 22 1 2 190 3 1

1,6 1,7 0 < 0,1 4,3 9,6 0,9 0,1 1,1 0,2 0,7 0,2 0,1 6,8 0,3 0,2 0,7 2,7 2,4 –

1 1 0 1 8 4 8 2 2 1 0 33 2 11 0 2 21 2 1

0,5 1,7 0 < 0,1 4,3 2,7 0,2 0,1 2,3 < 0,1 0 0,1 < 0,1 3,4 0 0,2 < 0,1 1,8 2,4 –

7 0 1 12 8 0 13 22 1 26 17 32 9 4 6 15 16 7 2

300 458 1 314 945 1 388

1,2 0,9 0,8 2,0 0,8 –

3 2 5 4 7

0,6 0,2 0,1 0,4 0,2 –

2 2 3 1 4

0,4 0,2 < 0,1 0,1 0,1 –

0 2 4 3 2

0 0,2 0,1 0,3 < 0,1 – –

12 3 32 13 15

1 031 89 1 081 1 152 291 821 2 565 5 2 531 187 – – – – – – – – –

0,7 1,1 1,6 3,2 1,0 1,8 2,7 0,4 2,8 0,4 1,0 0,9 1,5 2,2 0,8 0,7 1,2 0,5 1,1

117 3 65 4 7 86 13 2 5 15

4,1 1,9 4,9 0,6 1,2 9,4 0,7 7,7 0,3 1,4 1,8 1,9 0,6 16 1,4 9,8 0,5 3,4 3,8

110 1 18 4 3 41 3 2 1 15 – – – – – – – – –

3,8 0,6 1,3 0,6 0,5 4,5 0,2 7,7 < 0,1 1,4 0,5 0,6 0,4 0,8 0,4 4,6 0,2 0,6 0,9 1 12 4 3 0 1 2 5 15 – – – – – – – – –

0,6 0,9 0,6 0,5 0 < 0,1 7,7 0,3 1,4 0,1 0,2 0,3 0,2 0,1 1,8 0,1 0,1 0,3

3 14 25 7 15 17 2 7 100 – – – – – – – – –

Страны с высоким бременем ТБ Страны с высоким бременем МЛУ-ТБ AFR AMR EMR EUR SEAR WPR В мире

Пустые ячейки означают, что данные не представлены. – означает, что значение показателя не может быть рассчитано. a Региональные и глобальные данные являются агрегированными данными, представленными странами и территориями с низким и средним уровнем доходов. Данные, показанные в таблице, не запрашивались у стран с высоким уровнем доходов в анкетах, рассылаемых ВОЗ.

62

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рисунок 5.1

Успехи в распространении тест-системы Xpert MTB/RIF, к июлю 2013 года

Количество картриджей, заказанных для Xpert MTB/RIF

0 1–1999 2000–9999 10 000–39 999 40 000–99 999 ≥ 100 000 Не имеют доступа к льготным ценам Не применимо

что является результатом последнего соглашения о финансировании между изготовителем и Агентством США по международному развитию (USAID), Чрезвычайным планом Президента США по борьбе со СПИДом (PEPFAR), ЮНИТЭЙД и фондом Билла и Мелинды Гейтс, подписанного в августе 2012 года. ЮАР приобретает 43% модулей и 60% картриджей, закупаемых в мировом масштабе, и стремится принять Xpert MTB/RIF в качестве замены микроскопии для диагностики туберкулеза. После Южно-Африканской Республики в закупках лидируют Зимбабве, Индия, Нигерия и Пакистан. Полная или частичная замена микроскопии тест-системой Xpert MTB/RIF для проведения первичного диагностического теста и прогнозируемое увеличение числа рифампицин-резистентных случаев, обнаруженных с помощью Xpert MTB/RIF, требует продолжения увеличения лабораторного потенциала по проведению микроскопических исследований мазков мокроты, культуральных исследований и ТЛЧ. Внедрение Xpert MTB/ RIF снижает потребность в культуральных исследованиях, как методе подтверждения диагноза туберкулеза, но рост числа выявленных больных туберкулезом, выделяющим штаммы, устойчивые к рифампицину, потребует последующего выделения чистых культур для мониторинга лечения и проведения ТЛЧ к другим противотуберкулезным препаратам, что является необходимым для определения режима химиотерапии. Растущие возможности по диагностике туберкулеза, устойчивого к рифампицину, также требуют укрепления материальной базы противотуберкулезных служб для обеспечения охвата адекватным лечением выявленных больных (см. также Главу 4). Одной из главных причин низкой выявляемости туберкулеза во многих регионах мира (Глава 3) является доминирование частного сектора, в котором медицинские работники при выявлении больного туберкулезом, зачастую не направляют извещение о выявленном случае заболевания в соответствующие национальные органы статистики. Качество диагностики в частном секторе сильно варьируется, и некоторые частные медицинские организации продолжают использовать для диагностики активного туберкулеза тесты, не рекомендованные ВОЗ, в том

числе тесты, основанные на выявлении антител к микобактериям туберкулеза и тесты, основанные на высвобождении гамма-интерферона лимфоцитами (IGRA). Более того, в некоторых странах лаборатории государственного сектора, выполняющие исследования по выявлению и диагностике туберкулеза, но при этом не подведомственные НПТ, не всегда выполняют утвержденные рекомендации и не всегда охвачены системой обеспечения качества. Сотрудничество между НПТ и всеми лабораториями, выполняющими исследования по диагностике туберкулеза, крайне важно для того, чтобы лаборатории следовали национальным рекомендациям, применяли утвержденные диагностические тесты, передавали извещения о выявленных больных в НПТ, а также для обеспечения медицинской помощью выявленных больных. В 2012 году, 20 из 36 стран с высоким бременем ТБ и МЛУ-ТБ сообщили о наличии определенного уровня сотрудничества с лабораториями в частном секторе, а 25 стран сообщили о сотрудничестве с не входящими в НПТ лабораториями в государственном секторе. Кроме того, был инициирован ряд инновационных государственно-частных партнерств по предоставлению частным лабораториям рекомендованных ВОЗ диагностических тестов по льготным ценам, достигнутым в результате договоренности с производителями, при условии повышения доступности этих диагностических возможностей всему населению. Примеры приведены во Вставке 5.1.

5.3  Укрепление лабораторий на глобальном, региональном и национальном уровнях Последние достижения в области лабораторной диагностики туберкулеза позволяют быстро и точно диагностировать туберкулез и лекарственную устойчивость. Одним из главных условий для достижения оптимального эффекта от внедрения новых методов диагностики является надлежащее включение новых тест-систем и методов в диагностические алгоритмы. В  Таблице 5.2 представлена информация о включении рекомендованных ВОЗ методов диагностики туберкулеза в стратегии НПТ на 63

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 5.1

Инновационные инициативы государственно-частных партнерств для повышения доступности рекомендованных ВОЗ методов диагностики Некоторые производители оборудования для экспресс-диагностики, в том числе Becton, Dickenson and Company (производитель BD MGIT ™ 960 автоматизированных систем с использованием жидкой питательной среды), Hain LifeScience (Genotype ® MTBDRplus) и Cepheid (Xpert ® MTB/RIF) предлагают свою продукцию национальным программам по борьбе с туберкулезом и некоммерческим партнерам в странах с низким и средним уровнем доходов по льготным ценам. Частные лаборатории традиционно не были включены в подобные проекты, что приводило к тому, что цены были недоступны для малообеспеченных людей при их обращении за помощью в частный сектор, и способствовало использованию других методов диагностики, которые не рекомендуются ВОЗ. Недавно были основаны две государственно-частные инициативы, направленные на повышение доступности быстрых и точных методов диагностики для уязвимых групп населения в азиатских регионах с крупной долей частного сектора в экономике. В июне 2012 года правительство Индии пошло на беспрецедентный шаг по запрету на ввоз, производство, распространение и продажу тест-систем для серологической диагностики туберкулеза, следуя рекомендации ВОЗ о неприемлемости использования таких лабораторных методов для диагностики туберкулеза. К сожалению, этот запрет создал нишу в частном секторе для других малодостоверных тест-систем, что было еще обусловлено тем, что методы диагностики туберкулеза, рекомендованные ВОЗ, оставались дорогими и недоступными для «среднестатистического» больного туберкулезом. Для преодоления этой диспропорции на рынке, в марте 2013 года в Индии была запущена инициатива по продвижению доступных, качественных тестов для диагностики туберкулеза (IPAQT) a. IPAQT представляет собой консорциум из 42 частных клинических лабораторий, поддерживаемых некоммерческими партнерами (например, Инициатива Клинтона по доступу к здоровью и Международный туберкулезный центр МакДжилл). IPAQT заключила соглашения с Cepheid Inc, Hain LifeScience и Becton, Dickenson and Company, согласно которым были установлены льготные цены на Xpert MTB/RIF, ДНК-зонды для выявления лекарственной устойчивости к препаратам первой линии и жидкие питательные среды для частного сектора, на которые раньше условия о льготных ценах не распространялись. Участвующие лаборатории должны соблюдать несколько условий: быть аккредитованными в соответствующих инстанциях для подтверждения качества своей работы, предоставлять извещения о подтвержденных случаях туберкулеза Обновленной национальной программе по борьбе с туберкулезом (ОНПТ); также они должны придерживаться предельной цены при расчете с пациентами, и, наконец, должны воздерживаться от использования тестов, не рекомендованных ВОЗ или ОНПТ. В целом, лаборатории, участвующие в инициативе IPAQT, располагают приблизительно 3000 франчайзинговых лабораторий и более 10 000 пунктов сбора диагностического материала во всех районах Индии, тем самым увеличивая доступ к быстрым, точным и доступным методам диагностики пациентам, обращающимся за помощью в частный сектор здравоохранения. В рамках недавно запущенного проекта TBXpert, финансируемого ЮНИТЭЙД (Вставка 5.2), и при поддержке инициативы ТB REACH совместно с Партнерством «Остановить туберкулез», финансируемых Министерством иностранных дел, торговли и развития Канады, были сформированы инновационные социальные бизнес-модели в Бангладеш, Индонезии и Пакистане силами Центра интерактивных исследований и разработок (Interactive Research and Development) в сотрудничестве с местными партнерами и НПТ. Учреждения, расположенные в мегаполисах Дакке, Джакарте и Карачи, и участвующие в проекте, будут оснащены максимум 25 системами GeneXpert и будут бесплатно получать картриджи Xpert MTB/ RIF в рамках проекта TBXpert с условием проведения бесплатного скрининга на туберкулез среди лиц с высоким риском туберкулеза, обращающихся в частные медицинские организации и другие партнерские организации. Сотрудничество с НПТ обеспечивает бесплатное лечение от туберкулеза всех выявленных больных. Прибыль участвующих в проекте частных организаций будет формироваться за счет вспомогательных тестов и услуг, предоставляемых пациентам, что позволит компаниям быть устойчивыми с финансовой точки зрения после окончания трехлетнего проекта TBXpert. a

www.ipaqt.org/

глобальном, региональном и национальном уровнях с особым вниманием к 36 странам объединенного списка 22 стран с высоким бременем туберкулеза (СВБ) и 27 стран с высоким бременем МЛУ-ТБ. В целом, страны с высоким бременем туберкулеза быстрее внедряли рекомендованную ВОЗ стратегию диагностики туберкулеза, чем в мире, в среднем. Все представившие отчет страны с высоким бременем МЛУ-ТБ, 95% стран с высоким бременем туберкулеза и 84% от всех стран, представивших отчет, сообщили о включении рекомендованных ВОЗ классических фенотипических ТЛЧ в национальные диагностические алгоритмы к 2012 году. Три четверти (74%) от всех стран мира применяют автоматизированные системы на жидких питательных средах и тест для ускоренной идентификации возбудителя туберкулеза. Страны Европейского региона были особенно активны в реализации рекомендаций ВОЗ — 97% стран Европейского региона сообщили о внедрении данных технологий. Доля стран, принявших рекомендацию ВОЗ по использованию метода АОЗ для выявления устойчивости к рифампицину, остается относительно низкой, и только 58% стран мира к настоящему времени признали этот метод. Однако, данный показатель растет, так 61% стран региона Америки сообщили о включении АОЗ в национальные рекомендации в 2012 году, по сравнению с 17% в 2011 году. Примерно половина стран и территорий мира с низким и средним уровнем доходов (49%) включили в отчет информацию о применении рекомендованного ВОЗ теста Xpert MTB/RIF 64

в диагностические алгоритмы для лиц из групп повышенного риска заболевания туберкулезом, сочетанным с ВИЧ-инфекцией и ЛУ ТБ к концу 2012 года, подтверждая быстрые темпы оснащения этой тест-системой после изданных впервые в декабре 2010 года рекомендаций ВОЗ. Страны с высоким бременем МЛУТБ особенно активно внедряли рекомендации ВОЗ; 84% стран сообщили о включении этого теста в диагностические алгоритмы для лиц высокого риска развития ЛУ ТБ. Финансирование из источников, включая Глобальный фонд, PEPFAR, USAID, REACH ТБ и «Врачи без границ» послужило стимулом для министерств здравоохранения по созданию условий для использования Xpert MTB/RIF. Эти инициативы, вместе с проектами TBXpert и EXPAND-TB, будут способствовать дальнейшему внедрению тестов в целевых странах с низким и средним уровнем доходов с ожидаемым повышением выявляемости ЛУ ТБ и туберкулеза, сочетанного с ВИЧ-инфекцией (Вставка 5.2). Сеть наднациональных референс-лабораторий (НРЛ), функционирующая в рамках Глобальной лабораторной инициативы (ГЛИ) ВОЗ, является движущей силой в укреплении национальных и региональных лабораторий в странах мира, обеспечивая долгосрочную экспертную помощь странам в рамках соглашений о сотрудничестве. Сеть состоит из 29 лабораторий, охватывающих все шесть регионов ВОЗ. Новым участником НРЛ стала Национальная референс-лаборатория Уганды, заполнившая ранее не охваченную сетью важную географическую нишу в Восточной Африке. Лаборатория уже заключила соглашения

Доклад о глобальной борьбе с туберкулезом 2013

Таблица 5.2

Включение рекомендаций ВОЗ в области диагностики туберкулеза в национальные рекомендации, 2012 годa Да   Нет   Страны с высоким бременем ТБ Жидкие культуры и ускоренные тесты по идентификации АОЗ для определения устойчивости к рифампицину Алгоритм диагностики ТБ у больных ВИЧинфекцией XPERT MTB/RIF для диагностики ТБ среди лиц с риском ТБ, сочетанного с ВИЧ-инфекцией XPERT MTB/RIF для диагностики лекарственной устойчивости в группах риска

Страны с высоким бременем МЛУ-ТБ

Классический ТЛЧ

Азербайджан Армения Афганистан Бангладеш Беларусь Болгария Бразилия Вьетнам Грузия ДР Конго Зимбабве Индия Индонезия Казахстан Камбоджа Кения Китай Кыргызстан Латвия Литва Мозамбик Мьянма Нигерия ОР Танзания Пакистан Республика Молдова Российская Федерация Таджикистан Таиланд Уганда Узбекистан Украина Филиппины Эстония Эфиопия ЮАР Страны с высоким бременем ТБ

                                   

                                   

                  

                                    

                  

                  

                  

    

    

    

    

    

    

          95% 100% 81% 91% 77% 100% 82% 61% 84%

          77% 88% 67% 68% 68% 97% 73% 56% 74%

          77% 92% 54% 61% 38% 82% 64% 39% 58%

          95% 96% 74% 82% 75% 81% 82% 78% 78%

          73% 84% 60% 35% 32% 60% 64% 33% 49%

          77% 84% 62% 35% 36% 56% 64% 33% 49%

Страны с высоким бременем МЛУ-ТБ AFR AMR EMR EUR SEAR WPR В мире

Пустые ячейки означают, что данные не представлены. a Региональные и глобальные данные являются агрегированными данными, представленными странами и территориями с низким и средним уровнем доходов. Данные, показанные в таблице, не запрашивались у стран с высоким уровнем доходов в анкетах, рассылаемых ВОЗ.

Доклад о глобальной борьбе с туберкулезом 2013

65

Вставка 5.2

Проекты EXPAND-TB и TBXpert: текущее состояние В рамках проекта EXPAND-TB, запланированного к реализации на период с 2009 по 2014 годы, предполагается увеличить охват пациентов с риском МЛУТБ современными методами диагностики и сократить время ожидания этих исследований в 27 странах. EXPAND-TB стал частью программ министерств здравоохранения стран-получателей и работает по модели передовых практик, обучения на рабочем месте и оптимизации ресурсного обеспечения для совершенствования деятельности лабораторной службы на национальном уровне. Проект является результатом сотрудничества между ВОЗ, Глобальной лабораторной инициативой (ГЛИ), Фондом развития новых инновационных методов диагностики (FIND), Партнерством «Остановить туберкулез» и Глобальным фондом лекарственных препаратов (GDF), и финансируется за счет ЮНИТЭЙД и других партнеров. В рамках проекта EXPANDTB, бюджет которого составляет 87 млн долл. США по линии ЮНИТЭЙД, усилия направлены на максимальную эффективность использования ресурсов и координацию технической помощи со стороны многочисленных партнеров, участвующих в мероприятиях по совершенствованию лабораторной службы, Рисунок B5.2.1 в том числе по проектам Глобального фонда, Всемирного банка, PEPFAR, АМР США, Американского общества микробиологии, Центров США по контролю Рост регистрации случаев туберкулеза за заболеваниями и их профилактике, Университета Джонса Хопкинса, Банка с множественной лекарственной устойчивостью развития KfW, Фонда для борьбы с туберкулезом KNCV, Партнеров во имя в некоторых странах, участвующих в проекте здоровья, проекта Hope, PATH, Международного комитета Красного Креста EXPAND–TB, за период 2009–2012 годы, по и Международного союза по борьбе с туберкулезом и легочными заболеваниями. сравнению с базовым уровнем 2008 года Преодолевая проблемы с установлением необходимой инфраструктуры для лабораторий центрального уровня, способных проводить исследования на Индия автоматизированных системах с использованием жидкой питательной среды 20 000 и АОЗ тестов, проект EXPAND-TB показывает новые возможности выявления 16 588 туберкулеза с МЛУ возбудителя в условиях практического здравоохранения 15 000 и улучшение выявления случаев ЛУ ТБ. Например, 24 870 случаев МЛУ-ТБ были диагностированы в поддерживаемых проектом лабораториях в 24 странах в 2012 году. Совокупное количество диагностированных случаев МЛУ-ТБ 10 000 достигло 36 965 к концу 2012 года, что составляет 32% целевого показателя. Некоторые из стран, участвующих в проекте, сообщили о резком увеличении числа лабораторно подтвержденных случаев ЛУ ТБ, особенно в 2012 году 4237 5000 2967 (Рисунок В5.2.1). В проект недавно были внесены дополнения о включении Xpert 1660 MTB/RIF в список закупаемых диагностических материалов, наряду с жидкими 308 питательными средами и АОЗ тестами. В октябре 2012 года, партнеры по проекту 0 2008 2009 2010 2011 2012 начали разрабатывать стратегию перехода от проектного к государственному финансированию. Опыт пилотных стран будет использоваться в качестве модели для внедрения подобной схемы финансирования во всех странах-бенефициарах Беларусь EXPAND-TB, обеспечивая постепенный переход к государственному 2000 финансированию и устойчивость результатов после окончания проекта EXPAND-TB. 1604 1594 С середины 2013 года началась закупка и установка оборудования 1576 GeneXpert для нового проекта TBXpert, в рамках которого, в течение трех 1500 1342 лет будет предоставлено около 1,4 млн тестовых картриджей Xpert MTB/RIF и 230 машин GeneXpert 21 стране-бенефициару с низким и средним уровнем 923 1000 доходов. Проект, оцениваемый в 25,9 млн долл. США, финансируется ЮНИТЭЙД и реализуется Глобальной Программой ВОЗ по борьбе с туберкулезом и Партнерством «Остановить туберкулез». Для обеспечения эффективной 500 интеграции технологий в существующую практику странами-бенефициарами, проект TBXpert координирует деятельность широкой сети партнеров и существующие инициативы по совершенствованию работы лабораторной 0 службы и инновационным подходам к повышению доступности диагностики 2008 2009 2010 2011 2012 в государственном и частном секторах для уязвимых групп населения (Вставка 5.1). Это приводит к сокращению времени диагностики туберкулеза, Кот-д’Ивуар а также туберкулеза, сочетанного с ВИЧ-инфекцией и рифампицин-устойчивого 300 туберкулеза. Партнерами проекта TBXpert являются GLI, TB REACH, GDF, проект EXPAND-TB, Интерактивные исследования и разработки и Африканское общество 221 лабораторной медицины. Выявленные случаи МЛУ-ТБ

Выявленные случаи МЛУ-ТБ

Выявленные случаи МЛУ-ТБ

200

Рисунок B5.2.2

Страны (коричневый цвет), участвующие в проекте TBXpert 100 24 0 2008 2009 2010 2011 2012 43 50 30

Таджикистан 800 Выявленные случаи МЛУ-ТБ 600 400 200 0 2008 2009 2010 2011 2012 604 694

319

333

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Доклад о глобальной борьбе с туберкулезом 2013

о сотрудничестве с Замбией, Сомали и Южным Суданом для оказания технической помощи. Кроме того, четыре кандидата для получения статуса НРЛ проходят этап получения экспертной помощи, среди них национальные референс-лаборатории Бенина, Дании и Южно-Африканской Республики, а также Университета Ага Хана в Пакистане. После завершения этапа получения экспертной помощи и установления стран-партнеров новые лаборатории расширят географию охвата, в частности, в регионе Африки и регионе Восточного Средиземноморья. Сеть наднациональных референс-лабораторий теперь расширяется за счет создания Центров передового опыта (ЦПО), т. е. новой категории лабораторий, достигших высоких показателей работы и ответственных за состояние и развитие лабораторной службы в крупных странах с низким и средним уровнем доходов. К странам, имеющим лаборатории, которые в настоящее время имеют право получить статус НРЛ-ЦПО, относятся Бразилия, Индия, Китай, Российская Федерация и Южно-Африканская Республика. Чтобы получить на это право, НПТ должны направить рекомендацию на лабораторию-кандидата в представительство ВОЗ в соответствующей стране, заключить соглашение о сотрудничестве с наднациональной референс-лабораторией и пройти оценку возможностей лаборатории со стороны ВОЗ, а также активно внедрять систему менеджмента качества для получения аккредитации.

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Глава 6

Мероприятия по борьбе с туберкулезом, сочетанным с ВИЧ-инфекцией Основные факты и выводы ■■ В 2012 году 1,1 млн (13%) из 8,6 млн человек, заболевших ТБ в мире, страдали туберкулезом, сочетанным с ВИЧ-инфекцией (ТБ/ ВИЧ); 75% случаев сочетанной инфекции приходятся на регион Африки. ■■ Число случаев смерти от ТБ, сочетанного с ВИЧ-инфекцией, уменьшается с 2003 года. Тем не менее, в 2012 году 320 000 человек умерли от сочетанной ТБ/ВИЧ инфекции, поэтому существует необходимость в дальнейших усилиях, направленных на облегчение бремени болезни. ■■ Наибольшая распространенность туберкулеза, сочетанного с ВИЧ-инфекцией, наблюдается в регионе Африки. Доля больных ВИЧ-инфекцией среди больных ТБ в мире составила 43% в 2012 году, варьируясь от 9,6% в Анголе и Эфиопии до 77% в Свазиленде. ■■ Доля зарегистрированных больных ТБ с документированным результатом обследования на ВИЧ-инфекцию в мире составила 46% в 2012 году, что выше уровня этого показателя в 2011 году, равного 40% и превышает в 15 раз уровень 2004 года. В регионе Африки 74% зарегистрированных больных ТБ прошли обследование на ВИЧ-инфекцию в 2012 году, что выше уровня 2011 года, равного 69%. Среди 41 страны с самым высоким уровнем бремени туберкулеза, сочетанного с ВИЧ-инфекцией, 15 стран достигли уровня охвата больных ТБ тестированием на ВИЧинфекцию 85% и более, а 7 из этой группы стран (Замбия, Кения, Малави, Мозамбик, Руанда, Свазиленд и Того) — более 90%. ■■ В мире наблюдалось увеличение охвата больных туберкулезом, сочетанным с ВИЧ-инфекцией, антиретровирусной терапией (АРТ) с 49% в 2011 году до 57% в 2012 году, но учитывая, что в соответствии с рекомендациями ВОЗ все больные ТБ, сочетанным с ВИЧ-инфекцией, подлежат АРТ, требуются дополнительные усилия для обеспечения значительно большего охвата этим лечением. ■■ В 2012 году 80% больных ТБ, сочетанным с ВИЧ-инфекцией, получили профилактическую терапию ко-тримоксазолом (ПТК), что остается на уровне, зафиксированном в последние годы. ■■ Сообщалось, что в 2012 году 4,1 млн состоящих на учете больных ВИЧ-инфекцией, прошли скрининг на ТБ, по сравнению с 3,5 млн в 2011 году. Из 1,6 млн больных ВИЧ-инфекцией, взятых на учет в 2012 году, почти 520 000 получили профилактическую терапию изониазидом (ПТИ). Требуется дальнейшее увеличение охвата ПТИ, так как около 50% больных ВИЧ-инфекцией, взятых под наблюдение с ВИЧ-инфекцией и прошедших скрининг на ТБ, подлежат ПТИ.

У больных ВИЧ-инфекцией, инфицированных М. tuberculosis, вероятность развития туберкулеза гораздо выше, чем у ВИЧ-отрицательных лиц 1. Начиная с 1980-х годов, эпидемия ВИЧ-инфекции привела к значительному росту заболеваемости ТБ и смертности от ТБ во многих странах, особенно в южной и восточной Африке (Глава 2, Глава 3). В 2012 году — 1,1 млн (13%) из 8,6 млн человек, заболевших ТБ в мире, страдали туберкулезом, сочетанным с ВИЧ-инфекцией (Глава 2, Таблица 2.1); 75% случаев сочетанной инфекции приходятся на регион Африки. В мире в 2012 году было 320 000 случаев смерти от туберкулеза, сочетанного с ВИЧ-инфекцией, с приблизительно одинаковым числом случаев среди мужчин и женщин, при этом, как в мире в целом, так и в большинстве регионов, включая Африку, число случаев смерти продолжает уменьшаться (см. Главу 2). ЮНЭЙДС и Партнерство «Остановить туберкулез» поставили общую цель сократить вдвое показатель смертности от ТБ, сочетанного с ВИЧ-инфекцией, к 2015 году в сравнении с 2004 годом 2. В 2004 году были выпущены рекомендации ВОЗ по комплексу совместных мероприятий по профилактике, диагностике и лечению туберкулеза, сочетанного с ВИЧ-инфекцией (совместные мероприятия ТБ/ВИЧ) 3,4. Этот комплекс включает установление и усиление координации мероприятий в области организации медицинской помощи больным туберкулезом и ВИЧ-инфекцией, тестирование больных ТБ на ВИЧ-инфекцию, проведение АРТ и ПТК больным туберкулезом, сочетанным с ВИЧ-инфекцией, проведение профилактики ВИЧ-инфекции среди больных ТБ, совершенствование диагностики ТБ у больных ВИЧ-инфекцией, проведение ПТИ больным ВИЧ-инфекцией при отсутствии признаков активного ТБ и обеспечение мер инфекционного контроля в медицинских учреждениях и других местах скопления людей (три последние меры также иногда называются ТРИ «И» в комплексе мероприятий для больных ВИЧ/ТБ). Начиная с декабря 2010 года, тест быстрой молекулярной диагностики Xpert MTB/RIF был рекомендован в качестве первичного диагностического теста для выявления ТБ среди больных ВИЧ-инфекцией, у которых наблюдаются признаки и симптомы ТБ. ВОЗ начала мониторинг внедрения и  распространения совместных мероприятий ТБ/ВИЧ в 2004 году. Данная глава

1

Отношение вероятности развития ТБ у больных ВИЧ-инфекцией, к вероятности развития ТБ у ВИЧ-отрицательных лиц, представляет собой уровень выявления случаев заболевания (УВЗ). По оценкам, мировой УВЗ (все возрасты) в 2012 году был 29,6 (интервал неопределенности 27,1–32,1). Более подробно методика изложена в Приложении 1. 2 G etting to zero: 2011–2015 strategy. Geneva, Joint United Nations Programme on HIV/AIDS, 2010. 3 Interim policy on collaborative TB/HIV activities . Geneva, World Health Organization, 2004 (WHO/HTM/TB/2004.330; WHO/HTM/ HIV/2004.1). Доступно на: http://whqlibdoc.who.int/hq/2004/who_ htm_tb_2004.330_eng.pdf 4 WHO policy on collaborative TB/HIV activities: guidelines for national programmes and other stakeholders. Geneva, World Health Organi­ zation, 2012 (WHO/ HTM/TB/2012.1). Доступно на: http://whqlibdoc.who. int/publications/2012/9789241503006_eng_Annexes.pdf

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представляет текущее состояние в этой сфере по данным мониторинга с 2004 по 2012 годы.

рисунок 6.1

6.1 Тестирование больных туберкулезом на ВИЧ-инфекцию В 2012 году число зарегистрированных больных ТБ с документально подтвержденными результатами обследования на ВИЧ-инфекцию составило 2,8 млн человек (Рисунок 6.1), что соответствует 46% от всех зарегистрированных случаев заболевания ТБ (Таблица 6.1, Рисунок 6.2), что выше уровня 2011 года (2,5 млн человек и 40%, соответственно); доля обследованных в 2012 году выше уровня 2004 года, составившего 3,1%, в 15 раз. (Рисунок 6.2). Охват больных ТБ тестированием на ВИЧ-инфекцию был достаточно высоким в регионе Африки, где 74% больных ТБ имели документированные результаты теста на ВИЧ-инфекцию в 2012 году, в сравнении с 69% в 2011 году (Рисунок 6.2). Пора­ зительно, что в 29 из 46 африканских стран 75% и более пациентов с ТБ прошли тестирование на ВИЧ-инфекцию в 2012 году (Рисунок 6.3). В целом, в 41 стране, определенной в качестве приоритетной для глобальных мер по борьбе с ТБ/ВИЧ (перечислены в Таблице 6.1), 53% зарегистрированных больных туберкулезом имеют документированные результаты теста на ВИЧ-инфекцию. Пятнадцать из этих стран достигли уровня тестирования ≥ 85%, в том числе 7 из них (Замбия, Кения, Малави, Мозамбик, Руанда, Свазиленд и Того) достигли уровня свыше 90%. Следует добавить, что несмотря на то, что в целом по Китаю охват больных ТБ тестированием на ВИЧ-инфекцию составил 34% в 2012 году, в 294 районах с наиболее тяжелым бременем ТБ/ВИЧ (т. е. в которых рекомендуется осуществлять тестирование на ВИЧ-инфекцию всех зарегистрированных больных туберкулезом), уровень охвата составил 88%. В 87 странах мира, 75% и более пациентов с ТБ имели документированные положительные результаты теста на ВИЧ-инфекцию. рисунок 6.3

Число больных туберкулезом с известным ВИЧ-статусом, 2004–2012 годы 3000 ВИЧ-статус Негативный Позитивный

Больные ТБ (тыс.)

2000

1000

0

2004

2005

2006

2007

2008

2009

2010

2011

2012

рисунок 6.2

Число больных туберкулезом с известным ВИЧ-статусом, выраженное в процентах, 2004–2012 годы 80 Регион Африки Процент больных ТБ 60 В мире 40

20 Регионы за пределами Африки 0 2004 2005 2006 2007 2008 2009 2010 2011 2012

Доля (%) больных с известным ВИЧ-статусом по странам, 2012 год a

Доля зарегистрированных больных ТБ (%) 0–14 15–49 50–74 ≥75 Нет данных Не применимо a

В 294 провинциях Китая, выбранных для проведения тестирования на ВИЧ зарегистрированных больных ТБ, тестирование прошли 100 017 из 113 978 зарегистрированных больных (88%). Данные по Российской Федерации приведены для новых случаев ТБ за исключением случаев заболевания в тюрьмах.

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Таблица 6.1

Обследование на ВИЧ-инфекцию, лечение больных туберкулезом, сочетанным с ВИЧ-инфекцией, и профилактика туберкулеза среди больных ВИЧ-инфекцией в мире, 41 стране с высоким бременем туберкулеза, сочетанного с ВИЧ-инфекцией, и регионах ВОЗ, 2012 год Данные в тысячах, если не указано иное. Оценочное число новых случаев ТБ, сочетанного с ВИЧ-инфекцией Число больных ТБ с известным ВИЧстатусом Доля зарегистрированных больных ТБ, обследованных на ВИЧ-инфекцию (%) Доля больных ТБ, сочетанным с ВИЧ-инфекцией среди обследованных (%) Доля выявленных больных ТБ, сочетанным с ВИЧ-инфекцией, приступивших к ПТК (%) Доля выявленных больных ТБ, сочетанным с ВИЧ-инфекцией, приступивших к АРТ (%) Число больных ВИЧ-инфекцией, обследованных на ТБ

лучш.

низк.

Высок.

Число больных ВИЧинфекцией, получающих ПТИ

Ангола Ботсвана Бразилия Буркина-Фасо Бурунди Вьетнам Гаити Гана Джибути ДР Конго Замбия Зимбабве Индия Индонезия Камбоджа Камерун Кения Китай Конго Кот-д’Ивуар Лесото Малави Мали Мозамбик Мьянма Намибия Нигерия ОР Танзания Российская Федерация Руанда Свазиленд Судан Сьерра-Леоне Таиланд Того Уганда Украина Центральноафриканская Республика Чад Эфиопия ЮАР Страны с высоким бременем ТБ/ВИЧ AFR AMR EMR EUR SEAR WPR В мире

5,5 5,1 16 1,6 2,5 9,3 4,3 2,8 0,54 16 35 55 130 7,5 2,7 19 45 7,3 3,6 8,0 9,9 16 1,2 83 19 7,3 46 32 9,3 2,9 13 4,3 3,9 12 1,2 35 4,8 5,3 4,1 23 330 1 000 830 31 11 19 170 24 1 100

4,7 4,5 13 1,3 2,2 6,9 3,5 2,4 0,45 14 32 42 120 5,6 2,3 16 44 6,4 2,9 6,9 8,7 15 1,2 58 16 5,8 21 30 7,9 2,6 11 3,5 3,2 10 0,98 28 3,9 4,4 3,4 17 270 960 760 28 10 17 160 21 1 000

6,5 5,6 19 1,8 2,8 12 5,1 3,1 0,64 19 39 69 140 9,7 3,1 23 47 8,2 4,3 9,2 11 17 1,3 110 21 8,9 80 34 11 3,2 15 5,1 4,8 14 1,4 42 5,7 6,4 4,8 30 390 1 100 910 34 12 21 180 27 1 200

12 6,0 46 4,6 5,7 68 14 12 1,3 35 45 34 822 2,7 32 21 93 309 2,0 21 10 19 1,5 48 19 9,9 83 52 76b 6,1 7,4 3,1 12 44 2,7 41 34 3,8 4,8 96 294 2 454 1 040 129 58 204 904 451 2 787

23 89 55 84 82 66 81 78 36 31 100 88 56 0,8 80 82 94 34 a 17 85 88 93 28 94 13 88 84 82 99 95 15 87 72 91 86 85 46 44 65 84 53 74 56 14 60 39 34 46

9,6 63 20 15 19 7,0 20 24 10 16 54 70 5,4 28 4,4 37 39 1,9 33 27 75 59 28 58 27 47 23 39 26 77 7,5 12 13 24 50 14 39 20 10 65 21 43 16 3,5 6,3 6,2 3,1 20

100 91 0 96 94 73 59 72 61 93 26 92 18 98 83 98 20 75 97 88 42 98 99 80 96 99 98 0 26 77 87 94 28

100 66 100 75 55 47 46 37 64 40 60 18 59 29 88 55 74 59 23 44 53 81 100 55 83 72 56 54

12

1,1

7,4 0,2 5,7 2,1 15 0

1 324 23 1,1 12 295

21 393

16 21 17

12 140 357 122

12 2,3

66 17 69 62 76 49 94 20 65

69 1,3 8,9

1,9 1,1

14

1,0 272 950 4 024 2 392 4,5 15 24 1 352 308 4 095 30 370 509 473 19 0,2 18 < 0,01 8,6 519

37 74 80 79 61 69 67 89 79 80

82 54 57 55 76 48 74 61 56 57

Пустые ячейки означают, что данные не представлены. a В 294 районах Китая, в которых проводилось обследование больных ВИЧ-инфекцией на ТБ, 100 016 из 113 978 зарегистрированных больных были обследованы на ВИЧ-инфекцию (88%), при этом было выявлено 1 605 больных ВИЧ-инфекцией (1,6%). b Данные по Российской Федерации не включают случаи повторного лечения и пенитенциарный сектор.

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За пределами региона Африки в 2012 году число пациентов, которые имели документированные результаты теста на ВИЧ-инфекцию, достигло 60% в Европейском регионе. Однако, следует отметить, что доля охваченных тестированием на ВИЧ-инфекцию в Российской Федерации занижена, так как национальные статистические данные о тестировании на ВИЧ-инфекцию, представленные ВОЗ, касаются только гражданского сектора (т. е. данные по пенитенциарному сектору не учтены), в то время как в знаменатель при расчете показателя охвата тестированием включены все зарегистрированные случаи ТБ. В регионе Америки число больных туберкулезом, имеющих документированные положительные результаты теста на ВИЧ-инфекцию, достигло 56% в 2012 году. На Бразилию (где для 55% новых случаев ТБ имеются документированные результаты обследования на ВИЧ-инфекцию, что очень близко к среднему региональному уровню) приходится более трети всех зарегистрированных случаев заболевания ТБ в регионе, в сравнении с 12% в Мексике и 11% на Гаити. В других регионах, где уровень тестирования остается низким, данные варьировались от 14% в регионе Восточного Средиземноморья до 39% в регионе Юго-Восточной Азии. Самая высокая распространенность ВИЧ-инфекции среди больных ТБ характерна для региона Африки (Таблица 6.1), где 43% заболевших ТБ имеют положительные результаты тестирования на ВИЧ-инфекцию (в сравнении с 46% в 2011 году). Процентное число больных ТБ, сочетанным с ВИЧ-инфекцией в 28 африканских странах из 41 страны, входящей в список приоритетных стран для глобальных мер по борьбе с ТБ/ВИЧ, колебалось от 10% в Эфиопии и Анголе до 77% в Свазиленде. В регионе Америки число больных ТБ, сочетанным с ВИЧ-инфекцией, составило 16%. В регионе Восточного Средиземноморья, Европейском регионе, регионе Юго-Восточной Азии и регионе Западной части Тихого океана менее 10% больных ТБ имели документированные положительные результаты обследования на ВИЧ-инфекцию. Среднее значение этого показателя в мире составило 20% и 21% в странах, входящих в список 41 страны с высоким бременем ТБ/ВИЧ.

рисунок 6.4

Число больных туберкулезом, сочетанным с ВИЧ-инфекцией, получающих профилактическую терапию ко-тримоксазолом (ПТК) и антиретровирусную терапию (АРТ), 2004–2012 годы 600 500 Больные ТБ (тыс.) 400 300 200 100 0 2004 ПТК Больные ВИЧ-инфекцией

АРТ

2005

2006

2007

2008

2009

2010

2011

2012

6.2 Антиретровирусная терапия и профилактическая терапия ко-тримоксазолом у больных туберкулезом, сочетанным с ВИЧ-инфекцией АРТ представляет собой важную меру, направленную на снижение риска заболеваемости и смерти от ТБ среди больных ВИЧ-инфекцией. АРТ снижает индивидуальный риск развития ТБ на 65% независимо от количества CD4-лимфоцитов 1, а в сочетании с ПТИ профилактический эффект в отношении ТБ усиливается 2. В последних методических рекомендациях ВОЗ, 3, уровень CD4-лимфоцитов, опубликованных в июле 2013 года  при котором рекомендуется начинать АРТ, был повышен с уровня CD4 ≤ 350 до ≤ 500 CD4/мм 3. Соблюдение этих рекомендаций во всех странах мира должно существенно снизить заболеваемость и смертность от ТБ, сочетанного с ВИЧ-инфекцией. Как и в предыдущих рекомендациях, проведение АРТ показано всем больным туберкулезом, сочетанным с ВИЧ-инфекцией, независимо от числа CD4-лимфоцитов. ПТК также помогает снизить смертность среди больных туберкулезом, сочетанным с ВИЧ-инфекцией 4. Число больных ТБ, сочетанным с ВИЧ-инфекцией, охваченных АРТ, выросло с крайне низкого уровня в 2004 году (Рисунок 6.4) до 0,3 млн больных в 2012 году. Среди больных туберкулезом, зарегистрированных в 2012 году 5, и имеющих документированные положительные результаты теста на ВИЧ-инфекцию, 57% получали АРТ в мире в целом ( Таблица 6.1, Рисунок 6.5), что является заметной положительной динамикой по сравнению

с 49% в 2011 году. В регионе Африки 55% зарегистрированных больных ТБ, имеющих документированные положительные результаты теста на ВИЧ-инфекцию, получали АРТ (48% в 2011 году). В 28 странах из 41 страны с наиболее тяжелым бременем ТБ/ВИЧ более 50% зарегистрированных больных ТБ, сочетанным с ВИЧ-инфекцией, получали АРТ в 2012 году (Таблица 6.1, Рисунок 6.6). Несмотря на рост показателя, следует помнить рекомендации ВОЗ о том, что все больные туберкулезом, сочетанным с ВИЧ-инфекцией, имеют право на АРТ, независимо от уровня CD4-клеток и поэтому необходимы дополнительные усилия для достижения цели 100% охвата этой группы больных АРТ к 2015 году, установленной в Глобальном плане «Остановить туберкулез» на 2011–2015 годы. Рекомендуется раннее начало АРТ, а именно в течение первых восьми недель после начала лечения ТБ или в течение первых двух недель у пациентов с выраженным иммунодефицитом (число CD4-лимфоцитов <50). ВОЗ также строго рекомендует интеграцию деятельности служб, предоставляющих лечение ВИЧ-инфекции и ТБ, на базе учреждений, оказывающих помощь ВИЧ-инфицированным или на базе противотуберкулезных учреждений, в странах с высоким бременем ТБ и ВИЧ-инфекции. Во многих случаях, противотуберкулезные службы более децентрализованы, чем службы, занимающиеся лечением ВИЧ-инфекции, поэтому имеют больше возможности организовать интегрированную помощь по лечению туберкулеза и проведению АРТ путем перераспределения и разделения обязанностей 6. Недавний пример интеграции противотуберкулезной службы со службами охраны здоровья матери и ребенка 1

2

3

4

5

6

Suthar AB et al. Antiretroviral therapy for prevention of tuberculosis in adults with HIV: a systematic review and meta-analysis. PLoS Medicine, 2012, 9(7): e1001270. (doi:10.1371/journal.pmed.1001270). Samandari T et al. 6-month versus 36-month isoniazid preventive treatment for tuberculosis in adults with HIV infection in Botswana: a randomised, double-blind, placebo-controlled trial. The Lancet. 2011 May 7;377(9777):1588-98. doi: 10.1016/S0140-6736(11)60204-3. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. Geneva, World Health Organization, 2013. Доступно на: http://apps.who.int/iris/bitstream/ 10665/85321/1/9789241505727_eng.pdf Nunn AJ et al. Role of co-trimoxazole prophylaxis in reducing mortality in HIV infected adults being treated for tuberculosis: randomized clinical trial. British Medical Journal. 2008, 337:a257. В ежегодных формах по сбору данных по ТБ ВОЗ просит страны информировать о числе больных ТБ, сочетанным с ВИЧ-инфекцией, и зарегистрированных в самый последний календарный год, которые «уже начали или продолжают получать АРТ». Global Tuberculosis Report 2012. Geneva, World Health Organization, 2012.

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рисунок 6.5

Доля (%) больных туберкулезом, сочетанным с ВИЧ-инфекцией, от числа больных туберкулезом с известным ВИЧ-статусом и доля (%) больных туберкулезом, сочетанным с ВИЧ-инфекцией, получающих профилактическую терапию ко-тримоксазолом (ПТК) и антиретровирусную терапию (АРТ), 2007–2012 годы a 100 Процент больных ТБ 80 60 40 20 0 2007 % больных ТБ, сочетанным с ВИЧ-инфекцией, от числа больных ТБ с известным ВИЧ-статусом % ВИЧ-положительных больных на ПТК 100 80 60 40 20 0 2007 100 80 60 40 20 0 2007 % ВИЧ-положительных больных на АРТ

a

2008 2009 2010 2011 2012 Сплошные линии показывают значения для стран, представивших данные. Затененные области показывают верхний и нижний пределы значений для стран, которые не представили данных.

2008

2009

2010

2011

2012

2008

2009

2010

2011

2012

рисунок 6.6

Доля (%) больных туберкулезом, сочетанным с ВИЧ-инфекцией, взятых на антиретровирусную терапию, 2012 год

Доля (%) больных ТБ, сочетанным с ВИЧ-инфекцией 0–24 25–49 50–74 75–100 Нет данных Не применимо

(ОЗМР) и службами по лечению ВИЧ-инфекции приводится во Вставке 6.1. В мире 0,4 млн больных туберкулезом, сочетанным с ВИЧ-инфекцией, получили ПТК в 2012 году, по сравнению с незначительным числом в 2004 году. В 2012 году, абсолютное число сократилось по сравнению с 2011 годом, что частично можно объяснить уменьшением числа зарегистрированных случаев ТБ, сочетанного с ВИЧ-инфекцией, в 2012 году (Рисунок 6.4). Охват ПТК больных туберкулезом с документированными положительными результатами обследования на ВИЧ-инфекцию составил 80% в 2012 году, что соответствует уровням, наблюдаемым в 2010 и 2011 годах (Таблица 6.1, Рисунок 6.5). Регион Африки, регионы Юго-Восточной Азии и Западной части Тихого океана достигли особенно высоких уровней охвата ПТК: 79%, 89% и 79%, соответственно ( Таблица 6.1). Из 41 страны с высоким бременем ТБ/ВИЧ число больных ТБ, сочетанным с ВИЧ-инфекцией, получающих ПТК в 2012 году, превысило 90% в Анголе, 72

Ботсване, Буркина-Фасо, Бурунди, Замбии, Индии, Камбодже, Кении, Лесото, Мозамбике, Намибии, Объединенной Республике Танзании, Руанде, Свазиленде и Уганде.

6.3 Усиление мероприятий по активному выявлению туберкулеза и организации профилактического лечения изониазидом у больных ВИЧ-инфекцией Ведение учетной и отчетной документации по активному выявлению ТБ у больных ВИЧ-инфекцией и предоставлению ПТИ при отсутствии признаков активного туберкулеза является особой проблемой во многих странах, и необходимы дальнейшие усилия для совершенствования этого процесса на национальном и глобальном уровнях (Вставка 6.2).

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Вставка 6.1

Координация деятельности между противотуберкулезной службой, службой, оказывающей медицинскую помощь при ВИЧ-инфекции и службой по охране здоровья матери и ребенка в Камбодже В Камбодже наблюдаются значительные успехи в борьбе с эпидемией ВИЧ-инфекции, а также снижается распространенность и смертность от ТБ. Наряду с этим в стране совершенствуются службы охраны здоровья матери и ребенка (ОЗМР). Дородовое посещение женских консультаций и увеличение доли больничных родов привели к сокращению материнской смертности и смертности детей в возрасте до 5 лет. В стране были приложены усилия по созданию и укреплению связей между противотуберкулезной службой, службой, оказывающей медицинскую помощь при ВИЧ-инфекциии и службой по охране здоровья матери и ребенка.

Связи между службами по лечению туберкулеза и ВИЧ-инфекции В 2012 году у 80% зарегистрированных больных туберкулезом был определен ​​ ВИЧ-статус, и 88% больных туберкулезом, сочетанным с ВИЧ-инфекцией, получали АРТ. Число больных ВИЧ-инфекцией, получавших ПТИ, увеличилось в 22 раза в 2012 году по сравнению с 2006 годом, после введения алгоритма обследования ВОЗ, направленного на исключение активного туберкулеза (и связанного с этим удаления предыдущего требования о положительной туберкулиновой кожной пробе перед началом ПТИ).

Связи между службами по охране здоровья матери и ребенка и противотуберкулезными службами Новый механизм координации деятельности между службами по охране здоровья матери и ребенка и программой по борьбе с ТБ предусматривает общую систему направления потоков больных между указанными службами, мониторинга дородового развития и роста детей, установление связей с программой по иммунизации, что обещает дальнейшее снижение бремени ТБ среди женщин и детей.

Расширение сотрудничества между тремя программами Сотрудничество между тремя программами направлено на укрепление связей и взаимодействия в целях достижения лучших результатов. Правительство, при поддержке ВОЗ, приложило усилия по созданию совместного проекта с участием трех программ в двух районах. Выводы, полученные при реализации пилотных проектов, помогают стране максимально использовать потенциал интегрированных программ и повысить эффективность использования ресурсов. Совместная деятельность трех пилотных программ включает:

Связи между службами по охране здоровья матери и ребенка и службами по лечению ВИЧ-инфекции Доля беременных, прошедших тестирование на ВИЧ-инфекцию, увеличилась с 16% в 2007 году до 82% в 2012 году. Охват АРТ больных ВИЧ-инфекцией беременных женщин увеличился с 11% в 2007 году до 65% в 2012 году. Доля детей, рожденных от больных ВИЧ-инфекцией женщин, которые получали АРТ с целью предотвращения передачи ВИЧ от матери к ребенку, вырос с 50% в 2010 году до 73% в 2012 году.

1. Упорядочение транспортировки образцов крови, необходимых для тестирования на ВИЧ-инфекцию, собираемых в местах предоставления медицинской помощи беременным женщинам, больным туберкулезом и группам населения с высоким риском ВИЧ-инфицирования. 2. Гармонизацию информации, образования и коммуникаций, связанных с охраной здоровья матери и ребенка, ВИЧинфекцией и ТБ в местах предоставления медицинской помощи по указанным проблемам. 3. Расширение интегрированной лабораторной сети по обеспечению лабораторными исследованиями при вышеуказанных заболеваниях. 4. Укрепление взаимодействия между тремя программами, включая стандартизацию информационной базы и обеспечение преемственности в оказании медицинской помощи. 5. Оптимизацию взаимодействия с обслуживаемым населением путем распределения затрат и времени, потраченных медицинскими работниками из разных служб, на ежемесячные встречи с добровольцами, вовлеченными в оказание медицинской помощи.

Вставка 6.2

Повышение качества данных по ТБ/ВИЧ: проблемы и решения В последние годы основные усилия были направлены на улучшение качества данных по ТБ/ВИЧ. Показатели, используемые в программах борьбы с ТБ и ВИЧ-инфекцией, были стандартизированы, а также было установлено сотрудничество между программами с четким определением обязанностей в отношении сбора данных по мероприятиям в области ТБ/ВИЧ. ВОЗ и ЮНЭЙДС интенсивно работали со странами, чтобы обеспечить полную отчетность, исключающую несоответствие между данными, полученными по линии двух программ. Несмотря на приложенные усилия, остаются следующие проблемы: •• Отсутствующие или неточные данные (знаменатели), необходимые для расчета доли больных ВИЧ-инфекцией, охваченных мероприятиями по активному выявлению ТБ и ПТИ. Увеличивается число стран, собирающих учетные и отчетные данные по числу больных ВИЧ-инфекцией, информирующих о числе больных ВИЧ-инфекцией, охваченных активным выявлением ТБ, и числе больных ВИЧинфекцией, получающих ПТИ, при отсутствии признаков активного ТБ. Тем не менее, многие из этих стран не сообщают соответствующие данные для включения в знаменатель (о числе больных ВИЧ-инфекцией, состоящих на учете, и числе впервые выявленных больных ВИЧинфекцией), которые необходимы для расчета показателей выявления ТБ и охвата ПТИ соответственно. Существуют также примеры, когда одинаковое число сообщается для обоих знаменателей. •• Противоречивые данные, сообщаемые национальными программами по борьбе с туберкулезом и национальными программами по борьбе с ВИЧ-инфекцией. В некоторых странах указанные службы сообщают разную численность больных туберкулезом, получающих АРТ. В 32 странах данные, предоставленные двумя службами, были различными в отчетах 2011 и 2012 годов. Несмотря на то, что последующие действия по согласованию данных и дополнительные усилия, позволили достичь консенсуса по поводу показателей в большинстве стран, разные данные не удалось согласовать ни по одному году в Анголе, Мьянме и в Объединенной Республике Танзании. Для решения этой проблемы требуется улучшение системы статистического наблюдения и отчетности и дальнейшее укрепление сотрудничества и обмена информацией между НПТ и программой по борьбе с ВИЧ-инфекцией, а также с их партнерами.

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рисунок 6.7

рисунок 6.8

Активное выявление туберкулеза у больных ВИЧ-инфекцией, 2005–2012 годы Число людей, прошедших скрининг (млн) 5 4 3 2 1 0 2005

Профилактическая терапия изониазидом у больных ВИЧ-инфекцией при отсутствии признаков активного туберкулеза, 2005–2012 годы Число больных ВИЧ-инфекцией без признаков активного туберкулеза (тыс.) 600 500 400 300 200 100 0 2005 2006 2007 2008 2009 2010 2011 2012

2006

2007

2008

2009

2010

2011

2012

В 2012 году в общей сложности 4,1 млн человек, которые наблюдались по поводу ВИЧ-инфекции, были обследованы на туберкулез в 61 стране, что превысило предыдущие показатели в 3,5 млн в 58 странах в 2011 году (Рисунок 6.7). В 49 странах, представивших как количество обследованных (прошедших скрининг) на туберкулез, так и число включенных в программу помощи при ВИЧ-инфекции, охват обследования составил 66% (3,9/5,9 млн). Среди 42 стран, представивших данные, ПТИ была предоставлена почти 520 000 человек, впервые зарегистрированных по программе оказания помощи при ВИЧ-инфекции в 2012 году. Это превысило предыдущие показатели, которые составляли менее 450 000 человек в 2011 году (Рисунок 6.8). В одной стране — Южно-Африканской Республике —на которую пришелся 71% от общемирового уровня — 370 000 пациентов была

предоставлена ПТИ в 2012 году, в сравнении с Эфиопией (30 000), Малави (21 000), Мозамбиком (17 000), Лесото (16 000), Гаити (15 000), Украиной (14 000) и Намибией (12 000). Тридцать стран предоставили данные как по общему числу пациентов, впервые включенных в  программу помощи больным ВИЧ-инфекцией (1,6 млн чел.), так и данные по числу больных ВИЧ-инфекцией, которые получили ПТИ (0,47 млн чел.) в 2012 году, т. е. 30% впервые включенных в программу помощи при ВИЧ-инфекции получили ПТИ. В случае, если применяется алгоритм ВОЗ для исключения активного ТБ у больных ВИЧ-инфекцией, основанный на 4-х симптомах, то приблизительно 50% больным ВИЧ-инфекцией потребуется ПТИ 1. Необходимы дальнейшие усилия для достижения целей Глобального Плана к 2015 году по предоставлению ПТИ всем больным, имеющим к ней показания.

1

Getahun H, et al. Development of a standardized screening rule for tuberculosis in people living with HIV in resource-constrained settings: Individual participant data meta-analysis of observational studies. PLoS Medicine, 2011, 8(1): e1000391. doi:10.1371/journal.pmed.1000391.

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Глава 7

Финансирование Основные факты и выводы ■■ Ежегодный объем финансирования, необходимого для эффективного контроля над эпидемией туберкулеза в странах с низким и средним уровнем доходов до 2015 года оценивается в 8 млрд долл. США (за исключением финансирования исследований и разработок новых методов диагностики туберкулеза, лекарств и вакцин). Из этой суммы, около двух третей необходимо использовать на выявление и лечение лекарственночувствительного туберкулеза, 20% на лечение МЛУ-ТБ, 10% на применение ускоренных методов лабораторной диагностики и необходимое для этого оснащение лабораторий и 5% для совместной деятельности по ТБ/ВИЧ. ■■ Результаты последних долгосрочных исследований на основе поступающих в ВОЗ данных свидетельствуют о том, что финансирование противотуберкулезных программ в странах с низким и средним уровнем доходов существенно выросло с 2002 по 2011 годы, особенно в Бразилии, Индии, Китае, Российской Федерации и ЮАР (страны БРИКС). Увеличение самообеспеченности этих и некоторых других стран — это история успеха этих стран и мирового сообщества по борьбе с ТБ. ■■ Несмотря на рост финансирования программ борьбы с туберкулезом, сохраняется дефицит, который необходимо восполнять как из внутренних, так и международных донорских источников. Существует потенциал для увеличения финансирования из внутренних источников в размере более 5,3 млрд долл. США в 2013 году, особенно в странах БРИКС. Финансирование, которое необходимо получить из международных донорских источников оценивается в 1,6–2,3 млрд долл. США в год. ■■ Ожидается, что финансирование из донорских источников составит 0,8 млрд долл. США в 2013 году; большая часть средств поступает из Глобального фонда и Агентства США по международному развитию (АМР США). Донорское финансирование составляет 50% и более от общего финансирования для некоторых групп стран, особенно это относится к 17 странам с высоким бременем болезни, исключая БРИКС, и ко всем странам с низким уровнем доходов; доля донорского финансирования в некоторых странах еще больше. Международные доноры играют решающую роль в поддержании и обеспечении дальнейших успехов в профилактике, диагностике и лечении ТБ в мире. ■■ Средняя стоимость эффективного курса лечения ТБ препаратами первой линии составляет от 100 до 500 долл. США почти во всех странах с высоким бременем туберкулеза.

Для достижения успехов в области профилактики, диагностики и лечения туберкулеза требуется долгосрочное адекватное финансирование. ВОЗ приступила к  ежегодному мониторингу финансирования противотуберкулезных мероприятий в 2002 году, результаты которого публиковались в Докладах о глобальной борьбе с ТБ. Особое внимание всегда уделялось 22 СВБ, на которые приходится около 80% расчетных случаев заболевания (Глава 2). Последние доклады включали комплексный анализ тенденций с 2006 года приблизительно для 100 стран мира. В 2012 году ВОЗ провела всесторонний анализ долгосрочных тенденций в области финансирования программ по ТБ в странах с низким и средним уровнем доходов за десятилетие с 2002 по 2011 годы с использованием данных, предоставленных странами за этот период. Удалось провести анализ данных в 104 из 154 стран, классифицируемых Всемирным банком, как страны с низким или средним уровнем доходов в 2011 году (валовой национальный доход (ВНД) на душу населения менее 12 476 долл. США в год). Именно на эти 104 страны приходилось, по оценкам, 94% случаев заболевания ТБ в мире и 88% случаев МЛУ-ТБ в мире в 2011 году. Уровни финансирования в 2011 году были затем проанализированы с учетом самых последних расчетов ресурсов, необходимых для профилактики, диагностики и лечения туберкулеза и использованы для определения возможностей внутреннего финансирования этих мероприятий и при отсутствии баланса, поиска возможностей финансирования из средств международных финансовых доноров на период до 2015 года. Результаты этого анализа были опубликованы в статье в августе 2013 года в журнале The Lancet Global Health 1. Учитывая вышеуказанную публикацию, объем главы, посвященной финансированию, был сокращен по сравнению с предыдущими годами, чтобы избежать ненужного дублирования. В  Разделе 7.1 представлены самые последние оценки финансовых ресурсов, необходимых до конца 2015 года для всех 154 стран, классифицированных как страны «с низким или средним уровнем доходов» на душу населения в 2011 году, и планируемый объем финансирования из внутренних источников. В Разделе 7.2 приводятся главные выводы, основанные на результатах анализа тенденций в финансировании с 2002 по 2011 годы, в 104 странах с низким и средним уровнем доходов. В вышеизложенном контексте оставшиеся разделы главы включают (Раздел 7.3) подробный анализ финансирования программ ТБ в 2013 году с использованием данных, собранных в 2013 году в рамках очередного раунда глобального сбора данных по ТБ. Уровни финансирования в 2013 году представлены по разным критериям группировки стран, а именно в разрезе регионов ВОЗ, уровня доходов, бремени болезни и географического положения, а также по источникам финансирования (Раздел 7.3.1) и категориям расходов (Раздел 7.3.2). Дефицит в финансировании, о котором сообщили страны, также проиллюстрирован и проанализирован (Раздел 7.3.3). Дополнительные данные по 1

Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middleincome countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15.

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75

странам можно найти в финансовых справках-профилях, которые доступны в интернете 1.

7.1  Оценки объема финансирования, необходимого для полномасштабных мероприятий по борьбе с глобальной эпидемией туберкулеза до 2015 года В Глобальном плане «Остановить ТБ» на 2011–2015 годы 2 содержится список мероприятий и средств, необходимых для полного контроля над эпидемией туберкулеза в соответствии со Стратегией «Остановить ТБ» 3. Целью плана является достижение к 2015 году глобальных задач по сокращению случаев заболевания и смерти от ТБ, а именно: снижение уровня заболеваемости и сокращение вдвое уровня распространенности и смертности от ТБ по сравнению с 1990 годом (Глава 1). Основными компонентами плана являются увеличение числа выявленных и пролеченных в соответствии с рекомендованной ВОЗ стратегией больных с 5,8 млн в 2011 году до 6,9 млн в 2015 году (что составит более 80% прогнозируемых случаев заболевания в этом году). При этом необходимо обеспечить: всех впервые выявленных пациентов с известными факторами риска МЛУ-ТБ и всех ранее лечившихся пациентов тестированием на лекарственную чувствительность к 2015 году (в том числе с помощью недавно одобренной к применению ускоренной тест-системы Xpert MTB/RIF, которая описана в Главе 5); лечение всех больных с подтвержденным диагнозом МЛУ-ТБ противотуберкулезными препаратами второй линии (оценочное число — около 300 000 таких больных в 2015 году); охват тестированием на ВИЧ всех больных туберкулезом; и своевременное назначение антиретровирусной терапии больным туберкулезом, сочетанным с ВИЧ-инфекцией. В 2013 году данные Глобального плана, в сочетании с новыми данными по планированию и разработке бюджетов из девяти стран с высоким бременем ТБ или МЛУ-ТБ, были использованы для пересмотра оценочной потребности в финансовых ресурсах для обеспечения мероприятий по профилактике, диагностике и лечению туберкулеза в странах с низким и средним уровнем доходов 4. Для этого анализа были использованы данные, полученные из следующих стран: Индия, Индонезия, Казахстан, Кения, Нигерия, Пакистан, Украина, Эфиопия и Южно-Африканская Республика. Анализ проводился с целью определения общей потребности в финансировании и дефицита финансирования, которые должны быть учтены при пополнении финансовых ресурсов Глобального фонда в 2013 году 5. ВОЗ впоследствии продолжила эту аналитическую работу для того, чтобы покрыть потребности всех стран с низким и средним уровнем доходов, а не только тех стран, которые подлежат финансированию из средств Фонда 6. Наиболее значимыми странами (по критериям бремени туберкулеза и потребности в финансировании), не подлежащими финансированию из средств Глобального фонда, являются Бразилия, Китай и Российская Федерация. Следует отметить, что при подготовке первого совещания, организованного в апреле 2013 года для обсуждения вопросов обеспечения финансовыми ресурсами, Глобальный фонд, ВОЗ, ЮНЭЙДС и другие партнеры согласились включить средства на проведение антиретровирусной терапии больным туберкулезом, сочетанным с ВИЧ-инфекцией, в расчетный бюджет программы по борьбе с  ВИЧ-инфекцией, чтобы избежать дублирования в финансировании этого направления работы по линии двух программ. По этой причине, расчетный бюджет на мероприятия по лечению больных туберкулезом, сочетанным с ВИЧ-инфекцией, в обновленном варианте бюджета программы по борьбе с ТБ ниже тех показателей, которые опубликованы в Глобальном плане. Расчетная потребность в финансировании была сопоставлена с ожидаемым размером внутреннего финансирования по 76

двум альтернативным сценариям. Первый сценарий заключался в том, что финансирование программы по ТБ может увеличиться (по сравнению с базовыми показателями на 2011 год) с учетом прогнозов Международного валютного фонда в отношении роста общего объема государственных расходов 7. Второй сценарий опирался на допущения первого сценария и, в дополнение, на предположение о том, что страны с уровнем финансирования противотуберкулезных программ, не соответствующим уровню доходов (т. е. способности платить) и бремени болезни, смогут добиться повышения объемов внутреннего финансирования до средних показателей к 2020 году. Эти сценарии были выбраны, поскольку они должны полностью соответствовать методам, которые ранее использовались для оценки потенциала по мобилизации внутренних финансовых средств на профилактику, лечение и уход за больными ВИЧ-инфекцией 8. На Рисунке 7.1 кратко представлены основные результаты изучения вышеизложенных сценариев. Общее финансирование, которое требуется для всех стран с низким и средним уровнем доходов, составит около 8 млрд долл. США в 2015 году, по сравнению с 6 млрд долл. США в 2012 году (Рисунок 7.2) 9. Из общего объема финансирования, примерно две трети необходимы для выявления и лечения больных туберкулезом с сохраненной чувствительностью возбудителя к противотуберкулезным препаратам, 20% для лечения МЛУ-ТБ, 10% для внедрения ускоренных методов диагностики и связанных с этим мероприятий по укреплению лабораторной сети и 5% для совместной деятельности ТБ/ВИЧ (за исключением расходов на АРТ). Объем финансирования, необходимый для каждой из этих четырех категорий, со временем увеличивается. Наибольшее относительное увеличение потребности в финансировании предполагается на мероприятия по лечению МЛУ-ТБ и совершенствованию лабораторной диагностики. Существует потенциал для мобилизации значительной доли этих финансовых потребностей за счет внутренних ресурсов в некоторых группах стран, особенно БРИКС и стран с доходами выше среднего уровня (Рисунок 7.1). В других странах,

1 2

www.who.int/tb/data The Global Plan to Stop TB, 2011–2015. Geneva, World Health Organization, 2010 (WHO/HTM/STB/2010.2). 3 Raviglione M, Uplekar M. WHO’s new Stop TB strategy. Lancet 2006; 367: 952–5. 4 Не учитывалось финансирование, необходимое для проведения исследований и разработок для новых методик диагностики туберкулеза, разработки лекарств и вакцин. В Глобальном плане предполагается, что около 2 млрд долл. США в год необходимы для научных исследований и разработок. 5 The Global Fund to Fight AIDS, Tuberculosis and Malaria fourth replenishment (2014–2016): needs assessment. Geneva, Global Fund to Fight AIDS, Tuberculosis and Malaria, 2013. 6 Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middle-income countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15. 7 World economic outlook database. Washington, International Monetary Fund, 2012 (www.imf.org/external/pubs/ft/weo/2012/02/weodata/index. aspx). 8 Schwartlander B, Stover J, Hallett T, et al. Towards an improved investment approach for an effective response to HIV/AIDS. The Lancet 2011; 377: 2031–41. 9 На Рисунке 7.1 группы стран не все взаимно исключают друг друга. Общемировой показатель можно рассчитать путем сложения итоговых значений в графах для БРИКС, с данными по странам с низким уровнем доходов, по странам с доходами ниже среднего уровня (за исключением Индии и Китая) и выше среднего уровня (за исключением Бразилии, Российской Федерации и Южно-Африканской Республики).

Доклад о глобальной борьбе с туберкулезом 2013

Рисунок 7.1

Прогноз финансирования, которое может быть привлечено из внутренних источников, по сравнению с общим объемом финансирования, необходимого для полноценного ответа глобальной эпидемии туберкулеза в девяти группах стран, 2012–2015 годы. Черная линия показывает общее требуемое финансирование. Синяя полоса представляет собой сценарий 1, и показывает внутреннее финансирование, которое можно было бы мобилизовать, если внутреннее финансирование увеличится по сравнению с исходным финансированием 2011 года в том же объеме, в каком вырастет общий объем государственных расходов по прогнозам Международного валютного фонда. Зеленая полоса показывает дополнительные ресурсы, которые могут быть мобилизованы, по сравнению со сценарием 1, если страны, уровень финансирования которых не соответствует уровню доходов и уровню заболеваемости ТБ, смогут повысить темпы финансирования для достижения среднего уровня финансирования по странам к 2020 году. БРИКС = Бразилия, Российская Федерация, Индия, Китай, ЮАР. 5.0 4.0 Млрд долл. США 3.0 2.0 0.5 1.0 0 2012 0 2012 0 2012 0.10 1.0 0.20 БРИКС 1.5 17 СВБ, исключая БРИКС 0.30 Страны с низким уровнем доходов, исключая СВБ

2013

2014

2015

2013

2014

2015

2013

2014

2015

Страны с низким уровнем доходов 0.8

1.8 1.6

Страны с уровнем доходов ниже среднего, исключая Индию и Китай

1.2 1.0 0.8 0.6 0.4 0.2 0

Страны с уровнем доходов выше среднего, исключая Бразилию, Россию, ЮАР

0.6 Млрд долл. США

1.4 1.2

0.4

1.0 0.8 0.6

0.2

0.4 0.2

0 2012

2013

2014

2015

0 2012

2013

2014

2015

2012

2013

2014

2015

0.9 0.8 0.7 Млрд долл. США 0.6 0.5 0.4 0.3 0.2 0.1

Африка, исключая ЮАР

Азия, исключая Индию и Китай 1.2 1.0 0.8 0.6 0.4 0.2 0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 2012 2013 2014 2015

Остальной мир, исключая Бразилию и Россию

0 2012

2013

2014

2015

0 2012

2013

2014

2015

имеется довольно значительная разница между бюджетом из внутренних источников и необходимым общим объемом финансирования, особенно в трех группах стран: в 17 странах с высоким бременем болезни, исключая БРИКС; в странах с низким уровнем доходов; и странах региона Африки, исключая Южно-Африканскую Республику. Согласно первому сценарию, начиная с 2011 года, объемы внутреннего финансирования будут увеличиваться параллельно с прогнозируемым ростом общего объема государственных расходов; дефицит финансовых ресурсов составит 2,3 млрд долл. США в год к 2015 году. По второму и более оптимистичному сценарию разница составит 1,6 млрд долл. США в год к 2015 году.

Следует отметить, что по второму более оптимистичному сценарию предполагается, что страны, в которых в настоящее время уровень финансирования из внутренних источников не полностью соответствует бремени ТБ, будут стремиться достичь текущего среднего уровня финансирования (т. е. соответствия внутреннего финансирования бремени болезни и уровню дохода) к 2020 году. В частности, это относится к двум странам — Индии и  Индонезии  — которым потребуется существенно увеличить уровень внутреннего финансирования для того, чтобы этот сценарий осуществился на практике, так как они должны получить около двух третей дополнительного финансирования по сценарию 2 в сравнении со сценарием 1. В настоящее время 77

Доклад о глобальной борьбе с туберкулезом 2013

Рисунок 7.2

Общий объем финансирования, необходимого для полноценного ответа на глобальную эпидемию туберкулеза по виду мероприятий, 2013–2015 годы 8 ТБ/ВИЧ Укрепление лабораторий/ диагностики МЛУ-ТБ ЛЧ ТБ

6 Млрд долл. США

4

2

0 2012 2013 2014 2015

тенденции не отвечают параметрам сценария 2. В Индии внутреннее финансирование на 2013 год, как сообщается в отчете, ниже уровня 2012 года, а в отчете по Индонезии было указано об увеличении внутреннего финансирования в 2013 году по сравнению с 2012 годом, но на относительно небольшую величину (см. Приложение 2 1 для получения более подробной информации).

7.2  Тенденции в области финансирования программ по туберкулезу в 2002–2011 годах: резюме Данные, представленные в ВОЗ с 2002 по 2012 годы, позволили провести анализ тенденций <в финансировании> за период с 2002 по 2011 годы в 104 странах. Эти 104 страны приведены в  Таблице 7.1 (еще 21 страна, которая может быть включена в анализ финансирования в 2013 году, описана в Разделе 7.3 и выделена жирным шрифтом). Для 83 из 104 стран имелось шесть и более наблюдений. Для большинства стран имелось от 7 до 10 наблюдений, в том числе для 14 из 22 СВБ имелось по 10 наблюдений в каждой стране, а для 5 из 22 СВБ имелось по 9 из 10 наблюдений. Отсутствующие данные по показателям страна-год по 104 странам были восполнены с помощью модели линейной регрессии для каждой страны. Подробная информация о критериях, используемых для включения или исключения стран, и методы условного расчета доступны в техническом приложении онлайн 2. В 104  странах с  низким и  средним уровнем доходов, на которые приходится 94% случаев заболевания ТБ и 88% случаев МЛУ-ТБ в мире, общее финансирование программ борьбы с туберкулезом (внутренние ресурсы и ресурсы, получаемые из международных донорских источников) выросло в реальном выражении (в долл. США по ценам 2011 года) с 1,7 млрд долл. США в 2002 году до 4,4 млрд долл. США в 2011 году. Рост финансирования варьируется среди групп стран от 100% в странах с низким уровнем доходов до 177% в группе стран с доходами выше среднего уровня. Увеличение финансирования сопровождалось значительным увеличением числа пациентов, успешно завершивших курс лечения от ТБ, от 2,8 млн в 2002 году до 5,0 млн в 2011 году. В общей сложности 43 млн человек были пролечены с 2002 по 2011 годы. Стоимость лечения одного пациента находилась в диапазоне 100–500 долл. США в большинстве стран с высоким бременем туберкулеза. Наличие более 70% различий между странами в стоимости лечения на одного пациента объясняется количеством больных и размером валового внутреннего продукта (ВВП) на душу населения. Объемы внутреннего финансирования (национальные и  местные бюджеты, кредиты) в  104  странах, включенных 78

в анализ тенденций, выросли с 1,5 млрд долл. США в 2002 году до 3,9 млрд долл. США в 2011 году. Кредиты составили небольшую долю (≤ 5%) от общего объема финансирования из внутренних источников на протяжении всех лет. Наибольший рост финансирования из внутренних источников (1,7 млрд долл. США из 2,4 млрд, т. е. 71%) приходится на страны БРИКС (в которых регистрируется почти половина всех случаев туберкулеза в мире) и другие страны с доходами выше среднего уровня в Азии, Латинской Америке и Европе. Масштабы финансирования из внутренних источников в этих группах стран (69–98% от общего объема финансирования в год) и, в особенности, в странах БРИКС (более 95% от общего объема финансирования в год), привели к тому, что финансирование из внутренних источников преобладает в структуре общего финансирования программ по ТБ в мире (88–92% в год). Международное донорское финансирование в 104 странах, включенных в анализ тенденций, выросло с 0,2 млрд долл. США в 2002 году до 0,5 млрд долл. США в 2011 году. Имелись существенные различия между группами стран в долях общего объема финансирования из международных донорских источников. В 2011 году доноры обеспечили 39% от общего объема финансирования в 17 СВБ, исключая БРИКС, на которые приходится около одной трети случаев заболевания ТБ в мире; 42% в странах Африки, исключая Южно-Африканскую Республику; и 67% в странах с низким уровнем доходов (25 из которых находятся в Африке). Согласно отчетам из стран, поступившим за период с 2002 по 2011 годы, Глобальный фонд обеспечивал 64% от общего объема международного донорского финансирования. Большая часть финансовых средств была использована на проведение мероприятий по диагностике и лечению больных туберкулезом с сохраненной чувствительностью возбудителя (более 85% ежегодно). Небольшая доля средств была направлена на обеспечение мероприятий по диагностике и лечению МЛУТБ, хотя начиная приблизительно с 2006 года, финансирование этого направления в странах БРИКС, странах с уровнем доходов выше среднего, а также в странах Европы и Латинской Америки, стало увеличиваться. Несмотря на рост финансирования из внутренних и международных донорских источников, национальные противотуберкулезные программы не смогли мобилизовать в полном объеме необходимые финансовые ресурсы. Дефицит финансирования (т. е. разница между оценками финансовых потребностей национальных противотуберкулезных программ для обеспечения мероприятий по профилактике, диагностике и лечению туберкулеза и фактическим количеством мобилизованных средств на борьбу с ТБ) сохранился и даже увеличился с 257 млн долл. США в 2002 году до 563 млн долл. США в 2011 году. Следует отметить, что дефицит финансирования, о котором сообщают национальные программы по борьбе с туберкулезом, иногда связан со сравнительно консервативной оценкой потребности в финансировании. Когда разрабатываются национальные стратегические планы с более амбициозными целями, как это было сделано для девяти стран, описанных в Разделе 7.1, финансовые потребности и дефицит финансирования неизбежно увеличиваются. Разница между оценочным объемом финансирования, необходимым для осуществления программ по борьбе с эпидемией туберкулеза в полном объеме в 2015 году (Раздел 7.1) в размере 8 млрд долл. США, и реально доступными 6,1 млрд долл. США в 2013 году (см. Раздел 7.3), составляет 1,9 млрд долл. США.

1 2

http://www.who.int/tb/country/data/download — см. примеч. на стр. iii Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middle-income countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15.

Доклад о глобальной борьбе с туберкулезом 2013

Таблица 7.1

Анализ финансирования программ по борьбе с туберкулезом в 2013 году в 125 странах a,b Низкий уровень доходов (21% зарегистрированных в мире случаев) УРОВЕНЬ ДОХОДОВ НИЖЕ СРЕДНЕГО (46% зарегистрированных в мире случаев) УРОВЕНЬ ДОХОДОВ ВЫШЕ СРЕДНЕГО (27% зарегистрированных в мире случаев) БРИКС (47% зарегистрированных в мире случаев) 17 СВБ, исключая БРИКС (33% зарегистрированных в мире случаев) 14 стран с высоким бременем МЛУ-ТБ, не входящие в 22 СВБ (2% зарегистрированных в мире случаев)

Регион Африки

Бенин, Буркина-Фасо, Бурунди, Гамбия, Гвинея, Гвинея-Бисау, ДР Конго, Зимбабве, Кения, Коморские Острова, Либерия, Мадагаскар, Малави, Мали, Мозамбик, Нигер, ОР Танзания, Руанда, Сьерра-Леоне, Того, Уганда, Центральноафриканская Республика, Чад, Эритрея, Эфиопия Гаити

Гана, Замбия, Кабо-Верде, Камерун, Конго, Кот-д’Ивуар, Лесото, Мавритания, Нигерия, Сан-Томе и Принсипи, Свазиленд, Сенегал

Алжир, Ботсвана, Габон, Намибия, ЮАР

ЮАР

ДР Конго, Зимбабве, Кения, Мозамбик, Нигерия, ОР Танзания, Уганда, Эфиопия

Регион Америки

Боливия, Гайана, Гватемала, Гондурас, Никарагуа, Парагвай, Сальвадор

Аргентина, Белиз, Бразилия, Венесуэла, Доминиканская Республика, Колумбия, Мексика, Панама, Суринам, Эквадор, Ямайка Иордания, Ирак , Иран, Ливан, Ливия, Тунис

Бразилия

Регион Восточного Средиземноморья

Афганистан, Южный Судан

Джибути, Египет, Западный берег реки Иордан и сектор Газа, Йемен, Марокко, Пакистан, Сирийская Арабская Республика, Судан Армения, Грузия, Молдавия, Узбекистан, Украина

Афганистан , Пакистан

Европейский регион

Кыргызстан, Таджикистан

Болгария, Босния и Герцеговина, Бывшая Югославская Республика Македония, Казахстан, Румыния, Сербия, Турция, Черногория Мальдивские Острова, Таиланд

Российская Федерация

Армения, Болгария, Грузия, Казахстан, Кыргызстан, Латвия, Республика Молдова, Таджикистан, Узбекистан, Украина, Эстония

Регион Юго-Восточной Азии Регион Западной части Тихого океана

Бангладеш, Корейская Народно-Демократическая Республика, Мьянма, Непал Камбоджа

Бутан, Индия, Индонезия, Тимор-Лешти, Шри-Ланка Вануату, Вьетнам, Кирибати, Лаосская Народно-Демократическая Республика, Микронезия (Федеративные Штаты), Монголия, Папуа-Новая Гвинея, Самоа, Соломоновы Острова, Филиппины

Индия

Бангладеш, Индонезия, Мьянма, Таиланд Вьетнам, Камбоджа, Филиппины

Американское Самоа, Китай, Малайзия, Маршалловы Острова, Палау, Тонга, Тувалу, Фиджи

Китай

Исключены из-за недостаточности данных

Азербайджан, Албания, Ангола, Гренада, Доминика, Коста-Рика, Куба, Палау, Перу, Сент-Винсент и Гренадины, Сент-Люсия, Туркменистан

Азербайджан, Беларусь, Литва

a

Анализ был сфокусирован, главным образом, на странах с низким и средним уровнем доходов. Три страны с высоким уровнем доходов (Латвия, Российская Федерация и Эстония) были включены в анализ в связи с тем, что они входят в состав 22 СВБ и 27 стран с высоким бременем МЛУ-ТБ. b Дополнительные страны, включенные в анализ финансирования программ по туберкулезу в 2013 году для сравнения со странами, включенными в анализ тенденций за 2002–2011 годы, отмечены жирным шрифтом.

Доклад о глобальной борьбе с туберкулезом 2013

79

Рисунок 7.3

Обеспеченные объемы финансирования противотуберкулезных мероприятий в 125 странах, на которые приходится 96% случаев туберкулеза в мире, по источникам финансирования и регионам ВОЗ, 2013 год Млрд долл. США (2013 г. по текущему курсу в долл. США) 3.0 2.5 2.0 1.5 1.0 0.5 0 EUR AFR WPR SEAR AMR EMR

Глобальный фонд Гранты (за исключением Глобального фонда) Правительство, общие расходы системы здравоохранения (стационарное и амбулаторное обслуживание) Правительство, бюджет НПТ (включая займы)

В целом эти результаты показывают, что финансирование мероприятий по борьбе с ТБ значительно увеличилось в период с 2002 по 2011 годы, что принесло существенные результаты и экономическую выгоду. Увеличение самообеспеченности многих стран, включая страны БРИКС, на долю которых приходится почти половина случаев заболевания ТБ в мире, это история успеха для этих стран и для глобального сообщества по борьбе с ТБ. В то же время ясно, что международное донорское финансирование во многих странах, по-прежнему, играет определяющую роль и должно быть продолжено для поддержания и консолидации достижений последних лет.

7.3 Финансирование программ по туберкулезу в 2013 году Отчеты, направленные странами в ВОЗ в 2013 году, в рамках ежегодного цикла глобального сбора данных по ТБ, позволили провести анализ ситуации по финансированию программ по ТБ в разрезе источников финансирования и статей расходов в 122 странах с низким уровнем доходов и в странах с доходами ниже среднего уровня (ВНД на душу населения менее 12 616 долл. США в 2012 году) ( Таблица 7.1; страны, дополнившие список стран, включенных в анализ тенденций за 2002– 2011 годы, выделены жирным шрифтом). Кроме того, в анализ были включены три страны с высоким уровнем доходов (Латвия, Российская Федерация и Эстония), т. к . они состоят в списке 22 стран с высоким уровнем бремени ТБ или в списке 27 стран с высоким бременем МЛУ-ТБ. В целом, на 125 стран приходится 96% случаев заболевания ТБ в мире. Методы, используемые для сбора, проверки и анализа данных, представлены во Вставке 7.1. Общее финансирование, которым располагали 125 стран мира в 2013 году, составило 6,1 млрд долл. США, и 3,1 млрд долл. США, исключая страны Европейского региона (Рисунок 7.3). Примерно 1,3 млрд долл. США приходятся на регион Африки, большая часть этих фондов приходится на долю Южно-Африканской Республики. В других четырех регионах ВОЗ объемы финансирования колеблются от 0,2 до 0,7 млрд долл. США.

Рисунок 7.4

Обеспеченные объемы финансирования противотуберкулезных мероприятий в 125 странах, на которые приходится 96% случаев туберкулеза в мире, по источникам финансирования и уровням доходов, 2013 год Млрд долл. США (2013 г. по текущему курсу в долл. США) 3.0 2.5 2.0 1.5 1.0 0.5 0 Страны Страны с уровнем с высоким доходов уровнем выше среднего доходов Страны Страны с уровнем с низким доходов уровнем ниже среднего доходов

Глобальный фонд Гранты (за исключением Глобального фонда) Правительство, общие расходы системы здравоохранения (стационарное и амбулаторное обслуживание) Правительство, бюджет НПТ (включая займы)

7.3.1 Финансирование в 2013 году по источникам финансирования Согласно отчетам стран за 2013 год, из общего объема финансирования программ по борьбе с ТБ в размере 6,1 млрд долл. США, 87% (5,3 млрд долл. США) были получены из внутренних источников и 13% (0,8 млрд долл. США) из международных донорских источников (Рисунок 7.3, Рисунок 7.4). Оба источника не обеспечивают необходимый уровень финансирования для обеспечения мероприятий по борьбе с эпидемией туберкулеза, которые запланированы до 2015 года (Раздел 7.1). Ожидаемое финансирование из внутренних источников в размере 5,3 млрд долл. США составляет не более 67% от общего объема, необходимого к 2015 году. Финансирование из международных донорских источников в размере 0,8 млрд долл. США составляет не более 50% от расчетных 1,6–2,3 млрд долл. США ежегодно, необходимых к 2015 году и остается гораздо меньше, чем объем международного донорского финансирования программы по борьбе с малярией (1,8 млрд долл. США в 2011 году) 1 и программы по борьбе с ВИЧ-инфекцией (8,2 млрд долл. США в 2011 году) 2. Примерно три четверти от общего объема международного донорского финансирования ТБ в 2013 году поступило из Глобального фонда; остальные средства в основном были предоставлены АМР США. Техническая помощь странам для 1 2

Рисунок 7.5

Обеспеченные объемы финансирования противотуберкулезных мероприятий в странах БРИКС, 17 других странах с высоким бременем туберкулеза и в странах Африки, исключая Южно-Африканскую Республику, по источникам финансирования, 2013 год Млрд долл. США (2013 г. по текущему курсу в долл. США) 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0 БРИКС Африка, без ЮАР Другие СВБ

Глобальный фонд Гранты (за исключением Глобального фонда) Правительство, общие расходы системы здравоохранения (стационарное и амбулаторное обслуживание) Правительство, бюджет НПТ (включая займы)

World malaria report 2012. Geneva, World Health Organization, 2012. World AIDS day report 2012. Geneva, Joint United Nations Programme on HIV/AIDS, 2012 (www.unaids.org/en/resources/presscentre/pressreleaseandstatementarchive/2012/november/ 20121120prresults).

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Вставка 7.1

Методы, использованные для сбора, проверки и анализа финансовых данных, представляемых странами в ВОЗ ВОЗ начала проводить мониторинг финансирования правительствами и международными донорами программ по ТБ в 2002 году. Все данные хранятся в базе данных ВОЗ по глобальной программе борьбы с ТБ. Стандартные методы, используемые для сбора, исследования, проверки и анализа этих финансовых данных, были описаны подробно в других публикациях a,b. В данной вставке содержится резюме по указанной проблеме. Ежегодно ВОЗ запрашивает данные из стран с низким и средним уровнем доходов по финансированию НПТ в разрезе статей расходов и источников финансирования, а также об ожидаемом дефиците финансирования по статьям расходов (в долл. США). Статьи расходов в бюджетах противотуберкулезных программ включают затраты на: препараты первой линии; персонал НПТ; мероприятия по руководству и контролю за осуществлением программы; расходные материалы и оборудование для лабораторий; информационно-пропагандистскую деятельность, коммуникации и мероприятия по социальной мобилизации; обеспечение ухода за больными по месту жительства; государственно-частное партнерство; совместные мероприятия по ТБ/ВИЧ; стратегию «Практический подход к здоровью легких»; прикладные научные исследования, включая специальные исследования; амбулаторные посещения и госпитализации. Статьи расходов на МЛУ-ТБ включают: препараты второй линии; другие статьи расходов, необходимые для ведения пациентов с МЛУ-ТБ; госпитализации; амбулаторные посещения. Источниками финансирования являются национальные или местные бюджеты, кредиты (которые также рассматриваются как национальный источник финансирования), гранты от Глобального фонда и гранты от других доноров (последние два источника классифицируются как источники международного донорского финансирования). Страны с высоким уровнем доходов представляют данные об общем объеме финансирования (бюджете) и общих расходах (без разбивки по источникам финансирования и категориям расходов). При рассмотрении и проверке данных, ВОЗ использует методики, оставшиеся неизменными с 2002 года. Эти методы включают рутинные проверки на правдоподобие и логичность, включая проверки, встроенные в систему интернет отчетности. Примером проверки достоверности данных может быть защита для внесения неправдоподобно больших изменений показателей за год (например, данные об общем объеме финансирования по источникам и по категориям расходов), или неправдоподобно высокие или низкие показатели, связанные с числом больных туберкулезом (например, изменение бюджетов или расходов в расчете на одного больного на приобретение препаратов первой или второй линии, которые значительно превышают цены, указанные Глобальным фондом по лекарственным средствам против ТБ и ВИЧ. Методы рассмотрения и проверки данных также включают в себя беседы с респондентами в странах для разрешения возникших вопросов и сопоставление с другими источниками данных, такими как подробные бюджеты, подготовленные с помощью разработанного ВОЗ пособия по планированию и подготовке бюджетов для программ борьбы с ТБ c, данные экономических исследований, включающие подробную информацию о стоимости различных услуг, данные отчетности кредиторов Глобального фонда и Организации экономического сотрудничества и развития (ОЭСР). Особое внимание всегда уделяется 22 СВБ. В нескольких странах (Китай и Российская Федерация являются яркими примерами), в бюджеты противотуберкулезной программы включают расходы на персонал, инфраструктуру и другие расходы, необходимые для стационарного лечения и амбулаторных посещений во время лечения туберкулеза, потому что лечение осуществляется в специализированных противотуберкулезных организациях, которые имеют самостоятельные бюджеты. Однако в большинстве стран финансирование стационарной и амбулаторной помощи больным туберкулезом не отражается в общем объеме финансирования, о котором сообщают национальные противотуберкулезные программы. Подробное изучение расходов на диагностику и лечение ТБ в различных странах показало, что госпитализация и амбулаторное лечение, включая лечение как ЛЧ ТБ, так и МЛУ-ТБ являются наиболее значимыми статьями расходов, которые не отражаются в финансовых отчетах национальных противотуберкулезных программ. В связи с этим, ВОЗ при проведении глобального мониторинга финансирования противотуберкулезных программ всегда уделяла значительное внимание оценкам финансовых ресурсов, используемых для стационарного и амбулаторного лечения больных туберкулезом. Для всех стран, за исключением Китая и Российской Федерации, размеры финансирования на стационарное и амбулаторное лечение больных туберкулезом были рассчитаны путем умножения среднего количества амбулаторных посещений и дней госпитализации (по информации от национальных противотуберкулезных программ, предоставляемой в ВОЗ ежегодно) на средние затраты на соответствующую услугу, приведенные в базе данных ВОЗ (WHO-CHOICE database) d по отдельным странам. Затем это произведение умножается на количество больных туберкулезом. Это делается отдельно для: а) пациентов с ЛЧ ТБ; и b) пациентов с МЛУ-ТБ, на основе использования данных, предоставляемых отдельно для этих двух групп пациентов в ежегодной форме отчетности ВОЗ по ТБ. a

Floyd K, Pantoja A, Dye C. Financing tuberculosis control: the role of a global financial monitoring system. Bulletin of the World Health Organization; 2007; 85: 334–40. b Floyd K, Fitzpatrick C, Pantoja A and Raviglione M. Domestic and donor financing for tuberculosis care and control in low-income and middle-income countries: an analysis of trends, 2002–11, and requirements to meet 2015 targets. The Lancet Global Health; 1: e105–15. c Planning and budgeting for TB control activities. Geneva, World Health Organization, 2013. (www.whoint/tb/dots/planning_ budgeting_tool). d Choosing interventions that are cost effective (WHO-CHOICE). Geneva, World Health Organization, 2008 (www.who.int/choice/ country/country_specific/).

эффективной мобилизации финансовых ресурсов из средств Глобального фонда и реализации одобренных грантов осуществляется с помощью механизма технического содействия программам по борьбе с туберкулезом (Вставка 7.2). Общий объем финансирования в разбивке по источникам финансирования для различных групп стран приведен на Рисунке 7.4 и  Рисунке 7.5. Полученные данные в значительной мере подтверждают ранее сообщавшиеся данные за десятилетний период 2002–2011 годы (Раздел 7.2). Страны БРИКС в финансовом отношении в целом являются относительно самостоятельными (95% финансирования из внутренних источников), за исключением Индии, где лишь 64% от финансирования в 2013 году поступило из внутренних источников (и как показано в Приложении 1, 37% бюджета НПТ финансировалось за счет внутренних

источников в 2013 году). Страны с высоким уровнем доходов полностью финансируют противотуберкулезные мероприятия из внутренних источников, а страны с доходами выше среднего уровня получают от международных доноров лишь 4% от общего объема финансирования (основная часть которого приходится на Китай). Страны с низким и ниже среднего уровнем доходов на душу населения являются реципиентами большей части международного донорского финансирования (0,7 млрд долл. США, или 88%). В группе стран с низким уровнем доходов донорское финансирование составляет около половины общего объема финансирования. Международное донорское финансирование также играет решающую роль в 17 СВБ, исключая страны БРИКС, и в африканских странах, исключая Южно-Африканскую Республику (Рисунок 7.5), где оно составляет 35% 81

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Техническая помощь Национальным противотуберкулезным программам; роль Механизма технического содействия программам по борьбе с туберкулезом Механизм технического содействия программам по борьбе с туберкулезом (TB-TEAM) был создан для координации и контроля за предоставлением технической помощи национальным программам по борьбе с туберкулезом. Секретариат и специально созданный веб-сайт работают на основе Глобальной программы ВОЗ по ТБ и финансируются АМР США. В середине 2013 года в работе этого объединения активно участвовало 34 технических партнера. Каждый партнер делится информацией о результатах работы своих миссий a в странах, включая отчеты, которые размещаются на страницах вышеуказанного веб-сайта, посвященных отдельным странам. В 2012 году члены TB-TEAM сообщили о результатах 706 миссий. Четверть всех миссий были нацелены на оказание экспертной помощи по вопросам укрепления лабораторной службы и организации борьбы с ШЛУ-ТБ и МЛУ-ТБ на программной основе и расширение объемов помощи в рамках этих программ. Другие 30% миссий были связаны с мониторингом и оценкой/измерением воздействия проводимых мероприятий, оценкой состояния НПТ, включая состояние фармацевтического менеджмента и снабжение другими необходимыми материалами. Большинство миссий проводились ВОЗ (40%) и Нидерландским фондом борьбы с туберкулезом (KNCV) (20%). Еще 24% были проведены Центрами США по профилактике и контролю за заболеваниями, Международным союзом борьбы с туберкулезом и легочными заболеваниями (IUATLD) и Глобальным Фондом по лекарственным средствам против ТБ и ВИЧ (GDF). Основным текущим направлением деятельности TB-TEAM является предоставление технической помощи для поддержки реализации грантов Глобального фонда. В рамках новой модели финансирования Фонда (НМФ), разработанной в 2013 году, виды деятельности расширяются, и будет также оказываться поддержка в разработке надежных национальных стратегических планов и соответствующих концептуальных документов, которые необходимы для мобилизации новых финансовых ресурсов (в отличие от реализации грантов, которые уже были обеспечены) от Глобального фонда. Особое внимание к тем странам, которые являются нынешними или потенциальными реципиентами Глобального фонда, объясняется тем, что Фонд является основным источником международного донорского финансирования во многих странах, особенно в странах с низким уровнем доходов и в нескольких странах с высоким бременем ТБ и с доходами ниже среднего уровня (Раздел 7.2). Партнеры, входящие в TB-TEAM, придерживаются активного подхода к вопросу оказания технической поддержки странам, уделяя особое внимание работе с теми грантами, которые используются недостаточно эффективно. Секретариат TB-TEAM отслеживает эффективность процесса мобилизации финансовых ресурсов и реализации грантов, используя такие показатели, как показатель успешности предложений, соотношение доли средств, выделенных на туберкулез, к общему объему утвержденных грантов, уровень выплат и рейтинг успешности выполнения гранта. Общая статистика по этим показателям за 2012 год: •• Показатель успешности предложений. TB-TEAM помогла 21 стране в мобилизации ресурсов через переходный механизм финансирования (ПФМ) Глобального фонда. Этот механизм был введен в действие на период перехода к НМФ для того, чтобы помочь странам избежать критической нехватки финансирования, которая может сказаться на оказании основных услуг. Среди трех заболеваний, борьбу с которыми поддерживает Фонд, проектные предложения на программы борьбы с ТБ имеют лучшие перспективы для утверждения (Группа технической оценки Глобального Фонда рекомендовала утвердить 87% предложений по ТБ, по сравнению с 79% из общего количества предложений на программы борьбы с малярией и 62% на программы борьбы с ВИЧ-инфекцией). •• Программы ТБ, как доля от общего объема финансирования. В соответствии с ПФМ, 130 млн долл. США были выделены на программы по ТБ, что составляет 25% от всех одобренных к финансированию программ. •• Ставки распределения. Всего, с учетом всех грантов, для 101 страны, на программы борьбы с ТБ в 2012 году было выделено 509 млн долл. США, или 15% от общего объема ассигнований Глобального фонда, составивших 3,4 млрд долл. США. Из оставшихся средств 1,8 млрд долл. США (54%) были выданы на гранты по борьбе с ВИЧ-инфекцией, 1,0 млрд долл. США (30%) на гранты по борьбе с малярией и 32 млн долл. США (1%) на межотраслевые инвестиции. •• Рейтинг эффективности использования грантов. К концу 2012 года дела с реализацией грантов на ТБ обстояли сравнительно хорошо (Рисунок B.7.1.1); по первым трем категориям А1 (отлично), A2 (соответствуют требованиям) и B1 (удовлетворительно) рейтинг эффективности составлял 86%, по сравнению с 53% по программам борьбы с малярией и 79% — при исполнении грантов на борьбу с ВИЧ-инфекцией. Другими категориями являются B2 (удовлетворительно, но не все возможности использованы) и C (неудовлетворительно).

Рисунок B.7.1.1

Самый последний рейтинг качества исполнения грантов Глобального фонда с разделением по болезням для всех 423 действующих грантов (База данных Глобального фонда, по оценкам на январь 2013 года) 100 80 Проценты (%) 60 40 20 0 Малярия (110 грантов) ВИЧ/СПИД ТБ Всего грантов (183 гранта) (130 грантов) (423 гранта) C B2 B1 A2 A1

По прогнозам, на 2013 и 2014 годы, Глобальный фонд предполагает распределить 1,9 млрд долл. США на гранты по борьбе с туберкулезом, что вдвое превышает годовой бюджет за 2012 год. TB-TEAM будет стремиться по возможности обеспечить максимальную поддержку странам, чтобы обеспечить более эффективное распределение и использование выделенных средств. a

www.stoptb.org/countries/tbteam/

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Таблица 7.2

Бюджет национальной программы по борьбе с туберкулезом, обеспеченный объем финансирования в разрезе мероприятий, оценочные затраты на лечение в стационарных и амбулаторных условиях больных лекарственно-чувствительным (ЛЧ ТБ) и МЛУ-ТБ, 36 СВБ или страны с высоким бременем МЛУ-ТБ, 2013 год (млн долл. США по текущему курсу) Обеспеченное финансирование PPM/ PAL/ ACSM/ CBC/ прикладные научные исследования/ специальные исследования Лечение в стационарных и амбулаторных условиях МЛУ-ТБ b

Бюджет НПТ

ЛЧ ТБ

МЛУ-ТБ

ТБ/ВИЧ

Другое

Лечение в стационарных и амбулаторных условиях ЛЧ ТБ b

22 СВБ Афганистан Бангладеш Бразилия Вьетнам Демократическая Республика Конго Зимбабве Индия Индонезия Камбоджа Кения Китай Мозамбик Мьянма Нигерия ОР Танзания Пакистан Российская Федерация c a Таиланд 

13 43 87 66 61 38 182 119 24 55 359 11 36 154 58 73 1 592 44 31 149 145 475 3 814

6,0 4,6 60 4,4 8,7 11 84 39 5,3 19 267 5,6 9,1 17 14 26 1 332 31 6,0 27 47 217 2 241

0,8 1,6 6,3 4,6 1,7 0,1 67 8,3 0,6 0,5 25 1,1 3,5 4,6 0,5 34 129 3,9 2,2 8,9 6,0 41 350

0 0 2,3 1,2 0,3 3,4 0 1,3 0,2 0,5 0,2 0 1,6 1,6 2,1 0,1 27 0,1 0,2 0,4 3,1 124 170

0,7 1,9 5,8 3,4 1,0 0,5 18 8,4 2,2 0,5 12 0,8 0,4 3,6 0,9 1,5 0,4 6,8 3,9 6,9 12 19 111

1,3 0,2 0 4,8 4,5 1,4 2,1 0,6 0,7 0,8 0,5 0 0 22 1,3 5,0 104 0 9,3 2,7 3,6 67 232

2,9 5,0 20 49 0,2 15 84 39 6,7 9 0 5,7 5,6 6,2 1,5 11 0 3,3 0,6 109 11 109 494

0 1,4 1,4 0,6 0 0,1 32 2,0 0,2 0,3 0 0,1 1,6 1,3 0,1 0,8 0 0 0 3,4 0,6 232 279

Уганда Филиппины Эфиопия ЮАР Всего 22 СВБ

Остальные страны с высоким бременем МЛУ-ТБ Азербайджан Армения Беларусь a Болгария Грузия Казахстан Кыргызстан Латвия Литва Республика Молдова a Таджикистан Узбекистан Украина Эстония 27 стран с высоким бременем МЛУ-ТБ 36 стран с высоким бременем ТБ и МЛУ-ТБ 35 46 76 85 0,8 4 011 4 371 2,6 5,0 15 21 0,1 2 312 2 471 2,8 1,1 14 15 0,5 448 464 0 0,6 0 0,6 0 164 172 0,6 1,1 1,5 0 0 108 130 15 8,6 46 7,9 0,2 325 340 16 10 242 35 4,8 14 2,6 149 11 3,7 0,3 2,8 70 5,6 1,1 0 0 1,0 0,3 0 0,6 0 1,7 13 0 0,3 4,8 21 4,0 0,1 5,4 4,5 0,6 0 0,1 0,2 – 22 3,6 192 13 20 – 11 6,6 84 66 0,1 854 919 – 3,2 1,1 5,7 40 0,1 400 402 – 7,5 – 1,5 3,2 57 3,1 7,3 – 1,2

Пустые ячейки означают, что данные не представлены. – означает, что значение показателя не может быть рассчитано. a Базируются на данных для 2013 года, представленных в отчете за 2012 год. В 2013 году Таиланд не смог предоставить данные на суб-национальном уровне. b Данные Китая и Российской Федерации не представлены, так как бюджет НПТ включает затраты на лечение в стационарных и амбулаторных условиях. c Затраты на персонал и инфраструктуру, необходимые для лечения и других противотуберкулезных мероприятий по ЛЧ ТБ и МЛУ-ТБ, не могут быть дезагрегированы, поэтому показаны в графе ЛЧ ТБ. Общие затраты на персонал и другие текущие расходы больничных организаций включены в графу ЛЧ ТБ.

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Рисунок 7.6

Рисунок 7.7

Обеспеченные объемы финансирования противотуберкулезных мероприятий в 125 странах, на которые приходится 96% случаев туберкулеза в мире по виду мероприятий и регионам ВОЗ, 2013 год 3.0 Млрд долл. США, 2013 год 2.5 2.0 1.5 1.0 0.5 0 EURa AFR WPR SEAR AMR EMR Другое ТБ/ВИЧ Стационарное и амбулаторное обслуживание: МЛУ-ТБ МЛУ ТБ Стационарное и амбулаторное обслуживание: ЛЧ TБ ЛЧ ТБb

Обеспеченные объемы финансирования противотуберкулезных мероприятий в странах БРИКС, 17 других странах с высоким бременем туберкулеза и в странах Африки, исключая ЮАР, по виду мероприятий, 2013 год 3.5 3.0 Млрд долл. США, 2013 год 2.5 2.0 1.5 1.0 0.5 0 БРИКС Африка без ЮАР Другие СВБ Другое ТБ/ВИЧ Стационарное и амбулаторное обслуживание: МЛУ-ТБ МЛУ ТБ Стационарное и амбулаторное обслуживание: ЛЧ TБ ЛЧ ТБa

a

Для Европейского региона, ЛЧ ТБ включает затраты на персонал и инфраструктуру, необходимые для лечения и профилактики туберкулеза в Российской Федерации, которые не могут быть разделены на МЛУ-ТБ и ЛЧ ТБ. Объем финансирования, показанный на МЛУ-ТБ в Европейском регионе, является, таким образом, заниженным. b ЛЧ ТБ включает в себя финансирование препаратов первой линии, персонал НПТ, управление программами и контроль, лабораторное оборудование и расходные материалы.

a

Для стран БРИКС данные по ЛЧ ТБ включают затраты на персонал и инфраструктуру, необходимые для лечения и профилактики туберкулеза в Российской Федерации, которые не могут быть разделены на МЛУ-ТБ и ЛЧ ТБ. Объем финансирования, показанный по МЛУ-ТБ в странах БРИКС, является, таким образом, заниженным.

и  54% соответственно от общего объема финансирования в 2013 году. Эта доля еще выше в отдельных странах и превышает 80% в четырех странах с высоким бременем ТБ: Афганистане, Демократической Республике Конго, Пакистане и Уганде (Приложение 2 1).

7.3.2 Финансирование в 2013 году по статьям бюджета Финансирование в 2013 году по статьям бюджета показано по регионам ВОЗ на Рисунке 7.6, для других групп стран — на Рисунке 7.7, для стран с высоким бременем ТБ и высоким уровнем распространения МЛУ-ТБ — в  Таблице 7.2. Следует отметить, что данные об объеме финансирования, необходимого для лечения больных МЛУ-ТБ в Европейском регионе занижены в связи с тем, что в бюджете, представленном Российской Федерацией, статья «лечение туберкулеза с сохраненной лекарственной чувствительностью (ЛЧ ТБ)» содержит расходы на лечение ЛЧ ТБ и МЛУ-ТБ, так как не может быть разбита. Среди 122 стран с низким и средним уровнем доходов, для которых можно рассчитать данные по отдельным статьям, большую часть финансирования в 2013 году составили расходы на диагностику и лечение ЛЧ ТБ. Регионами ВОЗ, в которых наиболее высокая доля финансирования приходится на лечение МЛУ-ТБ, являются регион Африки (в основном, Южно-Африканская Республика), Европейский регион и регион Юго-Восточной Азии. Эти данные коррелируются с распределением бремени МЛУ-ТБ в мире (в основном, страны БРИКС и Европейский регион) и с последними данными о количестве больных МЛУ-ТБ, выявленных и зарегистрированных для лечения (Глава 4). Эти данные также показывают, что наиболее высокая доля от расчетного числа больных МЛУ-ТБ, зарегистрированных для лечения, наблюдается в европейских странах и Южно-Африканской Республике, а также отмечены высокие темпы взятых на лечение больных в Индии (в регионе Юго-Восточной Азии). Низкая доля финансирования на лечение МЛУ-ТБ в регионе Западной части Тихого океана, где большинство расчетных случаев МЛУ-ТБ приходится на Китай, соответствует небольшому числу зарегистрированных случаев заболевания и числу больных, зарегистрированных для лечения 84

в Китае в 2012 году (немногим более 3000 больных, или 5% от общего расчетного количества больных МЛУ-ТБ). В группе 22 СВБ, 85% доступного финансирования на лечение МЛУ-ТБ приходится на страны БРИКС (Таблица 7.2). Большая часть финансирования для осуществления совместных мероприятий по ТБ/ВИЧ приходится на регион Африки (77%), за ним следует Европейский регион (16%). Это согласуется с распределением бремени ТБ/ВИЧ: по последним оценкам, 75% больных туберкулезом, сочетанным с ВИЧ-инфекцией, проживают в регионе Африки (Глава 6).

7.3.3 Дефицит финансирования по отчетам, поступившим в 2013 году В 2013 году национальные противотуберкулезные программы сообщили о том, что дефицит финансирования (т. е., разница между объемом финансирования по расчетам национальных противотуберкулезных программ, необходимого для профилактики, диагностики и лечения, и фактически доступными мобилизованными средствами на программы по ТБ) составляет сумму в 1 млрд долл. США. Это значительное увеличение дефицита средств по сравнению с тем уровнем, который наблюдался в период с 2002 по 2011 годы и составлял от 0,3 до 0,6 млрд долл. США (Раздел 7.2). Этот факт можно объяснить тем, что НПТ разрабатывают более амбициозные и масштабные планы, что приводит к увеличению дефицита в финансировании. На африканские страны приходится почти половина от общего объема дефицита бюджета (Рисунок 7.8a), далее следуют азиатские страны (37% от общего объема). Дефицит финансирования сообщался в отчетах всех групп стран, классифицированных по уровню доходов, за исключением стран с высоким уровнем доходов (Рисунок 7.8b), и по разным мероприятиям по профилактике, диагностике и лечению ТБ (Рисунок 7.8c).

1

http://www.who.int/tb/country/data/download — см. примеч. на стр. iii

Доклад о глобальной борьбе с туберкулезом 2013

Рисунок 7.8

Дефицит финансирования по данным национальных программ по борьбе с туберкулезом в 125 странах, на которые приходится 96% глобальных случаев туберкулеза, 2013 год a. По регионам и уровню доходов Остальные страны мира 15%

Африка 48%

Азия: Другие 30%

Азия: низкий уровень доходов, высокое бремя ТБ 7%

b. По уровню доходов Выше среднего 20% Низкий уровень 36%

Ниже среднего 44%

c. По виду мероприятий ЛЧ ТБ, препараты первой линии 3% Другое 17% ЛЧ ТБ, исключая препараты первой линии 33%

ТБ/ВИЧ 9%

МЛУ-ТБ 13%

ACSM/CBC/PPM/PAL/OR различные виды научных исследований 25%

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85

Глава 8

Научные исследования и научно-практические разработки Основные факты и выводы ■■ В течение последнего десятилетия усиленно разрабатывались новые средства диагностики ТБ, противотуберкулезные препараты и вакцины, что привело к значительным успехам. ■■ Более 50 компаний участвуют в разработках методов диагностики ТБ. Несмотря на то, что многие новые диагностические технологии доступны на рынке, требуется ускоренное проведение оценки точности и надежности данных диагностических тестов в условиях практического здравоохранения. ■■ Увеличение объема непрерывных инвестиций в сферу диагностики ТБ остается важным для разработки точных, простых в использовании, доступных медицинских тестов для ускоренной и ранней диагностики туберкулеза. ■■ На данный момент 10 новых или ранее применявшихся по другим показаниям препаратов находятся на последней стадии клинических испытаний в отношении их противотуберкулезной активности. В декабре 2012 года один из новых препаратов — bedaquiline — был одобрен для использования в лечении больных МЛУ-ТБ Управлением по контролю качества продовольствия и медикаментов США (FDA). Временное руководство по применению bedaquiline в лечении МЛУ-ТБ было опубликовано ВОЗ в июне 2013 года. Bedaquiline является первым новым препаратом, одобренным для лечения туберкулеза за многие годы. ■■ Результаты двух клинических испытаний (III фазы) четырехмесячной схемы лечения ЛЧ ТБ ожидаются в конце 2013 года. Новые комбинации схем лечения также проходят испытания по протоколу изучения ранней бактерицидной активности (РБA) или определения конверсии культуры через 2 месяца лечения в рамках клинических испытаний II фазы. ■■ На данный момент 10 противотуберкулезных профилактических вакцин-кандидатов находятся в фазе I, фазе II или фазе IIb клинических испытаний и две иммунотерапевтические вакцины проходят II или III фазу испытаний. ■■ Результаты фазы IIб предварительного исследования клинической эффективности вакцины-кандидата MVA85А были опубликованы в феврале 2013 года. У детей в возрасте до 1 года, получивших вакцину как дополнение к вакцине Бацилла Кальметта — Герена (БЦЖ), приобретение дополнительной иммунной защиты, по сравнению с самостоятельным применением БЦЖ, не было зафиксировано. Тем не менее, это исследование показало, что вакцина обладает приемлемым уровнем безопасности для данной возрастной группы, а также доказало возможность проведения высококачественных клинических испытаний новых противотуберкулезных вакцин в условиях стран с высоким бременем ТБ и получения надежных результатов. ■■ Научные исследования и разработки являются одним из трех приоритетов Глобальной стратегии ВОЗ «Остановить ТБ» после 2015 года, так как играют решающую роль в ускорении сокращения заболеваемости и смертности от ТБ и способствуют достижению глобальных целей после 2015 года.

Остановить глобальную эпидемию туберкулеза — такую цель ставит Глобальная стратегия по борьбе с ТБ на период после 2015 года (Глава 1). Несмотря на значительный прогресс в оказании противотуберкулезной помощи и проведении других противоэпидемических мероприятий, наблюдаемый с середины 1990-х годов (Главы 2–7), достижение этой цели потребует серьезных технологических прорывов в научных исследованиях и разработках. Ускоренные, эффективные и хорошо переносимые схемы лечения латентной ТБ инфекции, диагностические тесты, позволяющие отличить латентную ТБ инфекцию от активного ТБ и применимые в условиях практического здравоохранения или домашних условиях, а также вакцины для эффективной вакцинации контактных лиц имеют ключевое значение для ликвидации глобальной эпидемии туберкулеза. Третий год подряд в Доклад о глобальной борьбе с туберкулезом включается глава, посвященная научным исследованиям и научно-практическим разработкам. Данные о достижениях в разработке новых методов диагностики ТБ, противотуберкулезных лекарств и вакцин по состоянию на июль 2013 года основываются на информации, предоставленной секретариатами соответствующих Рабочих групп Партнерства «Остановить ТБ», и последних публикациях. Особое внимание уделяется разработкам, проводимым в период с августа 2012 года по июль 2013 года. В заключительном разделе главы освещаются наиболее актуальные направления для исследований и разработок на период после 2015 года.

8.1  Новые методы диагностики туберкулеза Микроскопия мазка мокроты остается наиболее широко используемым диагностическим методом выявления ТБ, несмотря на его относительно низкую чувствительность (особенно, среди больных с олигобациллярным ТБ, например, больных ВИЧ-инфекцией и у детей). В настоящее время эталонным методом лабораторного подтверждения заболевания является посев диагностического материала на жидкие питательные среды. Тем не менее, подтверждение диагноза с использованием данного метода не является широко доступной диагностической процедурой для большинства стран с высоким бременем ТБ, так как для проведения исследований необходимы специализированные лаборатории и условия для соблюдения требований биологической безопасности, а получение результатов данных исследований занимает время до нескольких недель. Последними достижениями являются экспрессные молекулярные тесты, которые могут быть использованы для диагностики ТБ и определения чувствительности возбудителя к рифампицину в первичном звене здравоохранения. Эти тесты в настоящее время внедряются во всех странах мира (см. также Главу 5). Туберкулез, по-прежнему, занимает особое место среди основных инфекционных заболеваний в связи с отсутствием точных и быстрых методов для его диагностики, в основном из-за проблем с определением биомаркеров, несмотря на продолжающиеся исследования в этой области. В современных условиях наиболее важным приоритетом в разработке методов диагностики ТБ является разработка простых, недорогих, экспрессных

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молекулярных тестов, на основе одного или нескольких надежных биомаркеров, которые могут быть применены при первом обращении больных в учреждения первичной медико-санитарной помощи (ПМСП), или могут использоваться для скрининга в местах жительства пациентов, чтобы быстро выявить людей, которым следует пройти подтверждающее тестирование. Информация о статусе разработок новых средств диагностики ТБ и оценке их эффективности, составленная по последним 1 и Инициативной группы действий по публикациям ЮНИТЭЙД  2 лечению ТБ (TAG)  , доступная к июлю 2013 года, приводится на Рисунке 8.1. На Рисунке 8.1 диагностические тесты и методы, присутствующие на рынке, сгруппированы в соответствии с тем, прошли ли они экспертизу со стороны ВОЗ и, если да, то были ли они одобрены. Учитывая быстрое развитие технологий диагностики ТБ, ВОЗ создала систему систематической проверки результатов исследований и разработки методических рекомендаций по применению новых методов диагностики ТБ. Данный процесс описан во Вставке 8.1. Более подробная информация доступна в других источниках. Следует также подчеркнуть, что перечень технологий, находящихся на «ранних стадиях разработки», не обязательно является полным или исчерпывающим 3. Перечисленные технологии публикуются по информации из документов ЮНИТЭЙД и докладов TAG. Разработка молекулярных технологий, основанных на амплификации нуклеиновых кислот (NAATs) является самым перспективным направлением, т. к. основанные на данной технологии тест-системы или уже поступили на рынок, или находятся на поздней стадии разработки. Большинство подобных тест-систем, тем не менее, предназначены для использования только на уровне референс-лабораторий с соответствующими требованиями к оснащению и уровню подготовки персонала. Большинство тестов, основанных на амплификации нуклеиновых кислот, требуют ручной подготовки образцов, что является технически сложным и служит препятствием для использования этих методов в периферийных лабораториях. Проведение исследований в референс-лабораториях позволяет обеспечить большие объемы исследований и/или проведение скрининга образцов на маркеры лекарственной устойчивости, но, как правило, такое тестирование является относительно дорогим. Разработчики молекулярных тестов нового поколения, которые появились до момента завершения строгих полевых испытаний тест-системы Xpert ® MTB/RIF, также столкнулись с типичными для всех проблемами обработки образцов и выделения ДНК в периферийных лабораториях. Технологии диагностики, находящиеся на ранних стадиях разработки (первая часть Рисунка 8.1), включают тесты для выявления возбудителя туберкулеза, лекарственной устойчивости или одновременного выявления возбудителя туберкулеза и лекарственной устойчивости. К ним относятся мультиплексные диагностические платформы на микрочипе для одновременного обнаружения большого числа мутаций, связанных с лекарственной устойчивостью; диагностические системы, сочетающие Tuberculosis: Diagnostics Technology and Market Landscape 2013. Geneva, UNITAID/World Health Organization, 2013. Доступно на: http://www.unitaid.eu/images/marketdynamics/publications/TB-DxLandscape_1-Jul-2013.pdf 2 Clayden P. et al (on behalf of The HIV i-Base/Treatment Action Group) 2013 Pipeline Report: HIV, Hepatitis C Virus (HCV), and Tuberculosis (TB) Drugs, Diagnostics, Vaccines, Preventive Technologies, Research Toward a Cure, and Immune-Based and Gene Therapies in Development. New York, Treatment Action Group, 2013. Доступно на: http://www.treatmentactiongroup.org/pipeline-report 3 Weyer K et al. Rapid molecular TB diagnosis: evidence, policy-making and global implementation of Xpert® MTB/RIF European Respiratory Journal erj01572-2012; published ahead of print 2012, doi:10.1183/09031936.00157212. 1

Рисунок 8.1

Общий обзор достижений в области разработки и оценки методов диагностики туберкулеза, июль 2013 года Технологии на начальном этапе разработки a Летучие органические соединения ••BreathLink, Menssana Research, США ••Prototype breath analyzer device, Next Dimensions Technology, США Молекулярные технологии ••Alere Q, Alere, США ••B-SMART, LabCorp, США ••Gendrive MTB/RIF ID, Epistem, Великобритания ••LATE-PCR, Brandeis University, США ••GeneXpert XDR cartridge, Cepheid, США ••TruArray MDR-TB, Akkoni, США ••INFINITIMTB Assay, AutoGenomics, США Культуральные технологии ••BNP Middlebrook, NanoLogix, США ••MDR-XDR TB Color Test, FIND, Швейцария/Imperial College, Великобритания ••TREK Sensititre MYCOTB MIC plate, Trek Diagnostic Systems/Thermo Fisher Scientific, США Другие технологии ••TB Rapid Screen, Global BioDiagnostics, США ••TBDx, Signature Mapping Medical Sciences, США

Прошли оценку ВОЗ, но не получили одобрения из-за недостаточной доказательной базы Молекулярные технологии ••TB LAMP, Eiken, Япония ••Genotype MTBDRsl, Hain Lifescience, Германия

Имеются на рынке, но доказательства эффективной работы еще не представлены в ВОЗ для оценки Молекулярные технологии ••iCubate System, iCubate, США ••TB drug resistance array, Capital Bio, Китай ••EasyNAT TB Diagnostic kit, Ustar Biotechnologies, Китай ••Truelab/Truenat MTB, Molbio/bigtec Diagnostics, Индия Немолекулярные технологии ••Alere Determine TB-LAM, Alere, США

Прошли оценку ВОЗ, но не рекомендованы к применению ••Коммерческие серологические исследования (все производители) ••Анализ на выделение интерферон-гамма для выявления активного ТБ (все учреждения)

Технологии, рекомендованные ВОЗ Молекулярные технологии ••Тест-система Xpert MTB/RIFb ••Aнализ олигонуклеотидными зондами (при положительной микроскопии на кислотоустойчивые микобактерии или положительном культуральном исследовании) Микроскопия ••Микроскопия с окраской по Циль-Нельсену и флуоресцентная микроскопия Культуральные технологии ••Коммерческие системы для культуральных исследований на жидких средах и ускоренной идентификации ••Некоммерческие тест-системы для культуральных исследований и ТЛЧ a

Это не исчерпывающий перечень технологий на начальном этапе развития. Перечисленные технологии освещены в последних публикациях (2013 год), ЮНИТЭЙД и TAG. b Обновленные методические рекомендации по Xpert MTB/RIF находятся в стадии разработки. Смотрите главу 5 для более подробной информации.

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Вставка 8.1

Доказательства, необходимые для обзора ВОЗ новых методов диагностики •• Перспективные исследования по разработке прототипов; •• Тестирование в лабораторных условиях по международным стандартам, которое завершается созданием окончательного дизайна продукта; •• ВОЗ обсуждает с разработчиками (если от них поступает запрос) требования конечного пользователя к таким характеристикам как биобезопасность, надежность и другие предполагаемые параметры. •• Эффективность работы нового диагностического оборудования должна быть оценена посредством проведения контролируемых клинических испытаний на 3–5 площадках стран с высоким бременем ТБ и ВИЧ-инфекции; •• Оборудование должно пройти регистрацию в глобальных и/или национальных регулирующих органах; •• Спецификации продукта и эффективность впоследствии должны быть проверены в неконтролируемых исследованиях, в полевых условиях на 5–10 площадках в странах с высоким бременем ТБ и ВИЧ, в том числе и на эффективность затрат.

Фаза 1: Исследования и разработки

Фаза 2: Оценка и демонстрация

РНК (рРНК), являются перспективными в этом отношении, так как уровень <мишеней> рРНК в клетке М. tuberculosis намного выше, чем мишеней геномной ДНК, а также в связи с тем, что рРНК может присутствовать только в  жизнеспособных микроорганизмах. Несколько новых диагностических технологий доступны сейчас на рынке, но информация о них не была предоставлена в ВОЗ, поэтому эти технологии не прошли экспертную оценку и, соответственно, ВОЗ не может рекомендовать их применение. В качестве альтернативы методам, основанным на полимеразной цепной реакции (ПЦР) в режиме реального времени (например, Xpert MTB/RIF) или методам молекулярной гибридизации с типоспецифичными зондами (другое название — анализ олигонуклеотидными зондами — АОЗ — ред.) для выявления возбудителя ТБ и определения лекарственной чувствительности, предлагаются следующие технологии: сочетание ПЦР с ДНК-микрочипами, которые позволяют обнаружить большее число аллелей, ответственных за лекарственную устойчивость, и потенциально могут обладать лучшими характеристиками для быстрого обнаружения лекарственной устойчивости. Данные технологии включают: •• iCubate system (iCubate, США). Это мультиплексная автоматизированная ПЦР-тест-система, которая выявляет возбудителя туберкулеза, нетуберкулезные микобактерии и мутации, ответственные за устойчивость к лекарствам. Система позволяет амплифицировать несколько мишеней в одной реакции и таким образом одновременно анализировать несколько параметров. Эта тест-система используется в настоящее время только в рамках научных исследований. •• Capital Bio Corporation (Китай) разработала набор тестов для обнаружения лекарственной устойчивости к противотуберкулезным препаратам, который может обнаруживать 14 из наиболее часто встречающихся мутаций в трех генах, связанных с устойчивостью к рифампицину и изониазиду. Данные тесты в настоящее время подходят для проведения анализов только на уровне референс-лабораторий из-за сложности в использовании. •• Набор для диагностики ТБ EasyNAT, Ustar Биотехнологии (Китай), включает в  себя три изотермических NAAT для обнаружения туберкулеза, а также мутаций, отвечающих за устойчивость к рифампицину и изониазиду. Клинические испытания, проведенные в четырех провинциях центральной и северной частях Китая, показали многообещающие предварительные результаты простого в исполнении и быстрого скрининга для диагностики туберкулеза легких. •• Система микро-ПЦР, разработанная компанией Truelab ™ (Molbio, Индия) была запущена в 2013 году в Индии. Данная система использует микрочипы с нуклеотидной последовательностью микобактерии туберкулеза для количественного определения ДНК возбудителя ТБ в образцах мокроты в течение одного часа, начиная с подготовки образцов до окончательного представления результатов. Оборудование с питанием от аккумуляторной батареи используется на стадиях выделения ДНК, амплификации и детекции. Несмотря на предполагаемую эффективность, к настоящему времени данные об оценке эффективности этого теста ограничены. •• Alere Determine LAM (Alere, США). Данный тест предназначен для обнаружения липоарабиноманнана микобактерии ТБ в моче. Этот тест представляет особую ценность для диагностики туберкулеза у больных ВИЧ-инфекцией, которые имеют низкий уровень CD4. Две новые тест-системы, поступившие на рынок, не получили одобрения ВОЗ после проведения оценки их характеристик. Первой из них является требующая ручной работы тест-система для проведения молекулярного теста, предназначенного для выявления ДНК возбудителя ТБ, непосредственно в образцах

Фаза 3: Оценка доказательств •• Представление пакета документов по данным Фазы I и Фазы II в ВОЗ. •• Документы на соответствие производства стандартам ISO 13:485; •• Демонстрация эквивалентной эффективности — сравнение Наднациональной референс-лаборатории; •• Структурированная доказательная оценка с использованием подхода GRADE (классификация рекомендаций, оценки и разработки); •• ВОЗ не рекомендует технологии, пригодные для использования только в одной стране.

Новые технологии Далее следуют

•• Новый метод диагностики успешно применяется на практике в пилотных проектах в странах с высоким бременем ТБ; •• Проводится систематическая оценка предложенных алгоритмов, нагрузки на лаборатории, практических трудностей и экономической эффективности; •• Опыт, полученный при пилотном применении, используется для адаптации метода к использованию в стране.

Фаза 4: Поэтапное внедрение и сбор доказательств для дальнейшего распространения технологии

•• Расширение масштабов применения новых диагностических методов с последующим использованием получаемых данных для уточнения политики ВОЗ и динамичной подготовки соответствующих руководств в процессе выполнения.

Фаза 5: Расширение масштабов применения и уточнение политики

тестирование нуклеиновых кислот с технологией, основанной на фагах, для определения устойчивости возбудителя непосредственно из диагностического материала; ускоренные культуральные колометрические методы для выявления устойчивости к рифампицину, изониазиду и фторхинолонам в лабораториях промежуточного уровня, второе поколение тест-системы Xpert для выявления устойчивости к другим, нежели рифампицин, препаратам; картриджные технологии, основанные на изотермальной амплификационной платформе, применимые в учреждениях первичного звена. В дополнение к технологиям, позволяющим диагностировать туберкулез и лекарственную устойчивость, необходимы методы, позволяющие оценивать эффективность лечения, что в настоящее время проводится с помощью культуральных исследований. Методы, основанные на амплификации рибосомальной 88

Доклад о глобальной борьбе с туберкулезом 2013

мокроты (TB-LAMP ®, Eiken Chemical Co. Ltd., Япония). Анализ доступной информации об этой тест-системе, проведенный экспертами ВОЗ, показал, что отсутствует доказательная база, достаточная для разработки методических рекомендаций по использованию тест-системы TB-LAMP ®. Дополнительные независимые испытания тест-системы TB-LAMP ® для использования ее в качестве замены культуральным исследованиям в настоящее время ведутся в 16 странах (17 мест). Вторая тест-система, данные по которой были рассмотрены экспертами ВОЗ, но не получили одобрения, представляет собой молекулярный тест с типоспецифичными зондами для определения лекарственной устойчивости к противотуберкулезным препаратам второго ряда АОЗ (GenoType  ® MTBDRsl, Hain Lifescience, Германия). Тест не может быть рекомендован в качестве замены классического фенотипического тестирования на лекарственную устойчивость по причине субоптимальной чувствительности в выявлении устойчивости к фторхинолонам и инъекционным противотуберкулезным препаратам второго ряда. В связи с тем, что имеется перекрестная устойчивость возбудителя к действию инъекционных препаратов второго ряда, наличие результатов тестирования с помощью системы GenoType ® MTBDRsl не позволяет точно определить, какой препарат или препараты связаны с обнаруженной мутацией(ями), и соответственно, результаты тестирования не могут быть использованы для определения индивидуальной схемы лечения МЛУ-ТБ. По этой причине, микробиологическое (фенотипическое) тестирование на лекарственную чувствительность к препаратам второго ряда остается актуальным для всех обнаруженных штаммов, вызывающих МЛУ-ТБ и для подтверждения или исключения ШЛУ-ТБ. Два вида экспрессных молекулярных тестов были рассмотрены и одобрены ВОЗ в последние годы (Рисунок 8.1). Молекулярные тесты с типоспецифичными зондами (АОЗ), позволяющие быстро диагностировать ТБ и лекарственную устойчивость в течение одного дня, были одобрены в 2008 году 1. Их использование в настоящее время ограничивается исследованием образцов диагностического материала с  предварительно полученным положительным результатом микроскопического исследования мокроты на кислотоустойчивые микобактерии или положительным результатом культурального исследования. Xpert MTB/RIF (Cepheid, Sunnyvale, Калифорния, США) был одобрен ВОЗ в 2010 году для экспресс-диагностики (в течение 2 часов) туберкулеза легких и устойчивости к рифампицину у взрослых 2. По состоянию на июль 2013 года Xpert MTB/RIF остается единственной полностью автоматизированной картриджной тест-системой, имеющей в основе ПЦР в режиме реального времени, которая позволяет выявлять возбудителя ТБ и устойчивость к рифампицину, и является единственной испытанной технологией, представляющей новое поколение автоматизированных молекулярных диагностических платформ. С 2010 года было опубликовано около 100 статей, посвященных Xpert MTB/RIF, и ожидается появление новых публикаций 3. В 2013 году, учитывая большой объем дополнительных данных, ВОЗ инициировала три систематических обзора данных по чувствительности и специфичности Xpert MTB/RIF в качестве теста для выявления легочной и внелегочной форм ТБ, как у взрослых, так и у детей. Выводы были рассмотрены экспертной группой и публикация обновленных рекомендаций планируется в 2014 году (см. Главу 5). Доклад ЮНИТЭЙД 2013  года: Туберкулез: Диагностические технологии и ситуация на рынке 4 описывает следующие четыре инновации в технологии Xpert MTB/RIF, которые уже были применены или находились на стадии разработки в 2012 и 2013 годах. •• Совершенствование технологии тестирования. В процессе разработки находится новая технология выявления штаммов с МЛУ-ТБ. Для проведения исследований используют

новые красители и гасители, которые увеличивают спектральный диапазон для обнаружения мишеней с использованием 10 флуорофоров, а не шести, как в настоящее время. •• Дистанционная калибровка. Данная инновация стала доступной к концу 2012 года и уже используется в более, чем 40 странах. Технология позволяет пользователю калибровать оптическую систему, проверять функционирование тепловой системы и проводить серию тестов на уровне системы для обеспечения полного ее функционирования в пределах спе­ цификаций. Предполагается, что более 90% модулей могут быть успешно откалиброваны через интернет. •• Совершенствование управления данными. Внесение результатов исследования (деперсонифицированных), связанных с гео-информационной системой в режиме реального времени в настоящее время подвергается тестированию в Южно-Африканской Республике. Это открывает возможности для существенного улучшения мониторинга эпидемии ТБ и связанных с этим программных ответных мер. •• Картриджи для выявления ВИЧ на платформе GeneXpert. Выпуск данных картриджей запланирован в 2014 году. Индивидуальный картридж для качественного и количественного определения вирусной нагрузки при ВИЧ-инфекции находится на стадии разработки. Более 50 компаний участвуют в разработке диагностического оборудования, которое используется для выявления туберкулеза, то есть в настоящее время поддерживается большой интерес к этой индустрии. Тем не менее, недавнее анкетирование более 25 компаний, разрабатывающих средства диагностики туберкулеза, определило ряд самых часто задаваемых вопросов, интересующих представителей индустрии, чтобы инвестировать в эту сферу (www.tbfaqs.org). Разработчики тестов интересуются наиболее важными характеристиками, на которых следует сосредоточиться при разработке тестов (например, стоимость, чувствительность, специфичность, требования к инфраструктуре, время получения результатов, пропускная способность, мокрота или другой диагностический материал, ручная или автоматизированная система, тестирование на уровне лечебных учреждений или в централизованной лаборатории, интегрированный или последовательный тест на лекарственную чувствительность, а также наиболее важные препараты, к которым должна определяться лекарственная чувствительность возбудителя). Кроме того, крайне необходимо обновление данных о ситуации на рынке, учитывая, что характеристики рынка оборудования для диагностики ТБ значительно изменились с момента проведения последнего глобального исследования спроса на эту продукцию в 2006 году 5. Обновление данных о ситуации на рынке и разработка профиля целевой продукции 1

2

3

4

5

Molecular Line Probe Assay for rapid screening of patients at risk of MDRTB. Policy Statement. Geneva, World Health Organization, 2008. Доступно на: http://www.who.int/tb/features_archive/policy_statement.pdf Policy Statement: Automated real-time Nucleic Acid Amplification Technology for Rapid and Simultaneous Detection of Tuberculosis and Rifampicin Resistance: Xpert MTB/RIF System. Geneva: World Health Organization, 2011 (WHO/HTM/TB/2011.4). Доступно на: http://whqlibdoc.who.int/publications/2011/9789241501545_eng.pdf Weyer K et al. Rapid molecular TB diagnosis: evidence, policy-making and global implementation of Xpert ® MTB/RIF European Respiratory Journal erj01572-2012; published ahead of print 2012, doi:10.1183/09031936.00157212. Tuberculosis: Diagnostics Technology and Market Landscape 2013. Geneva, UNITAID/World Health Organization, 2013. Доступно на: http:// www.unitaid.eu/images/marketdynamics/publications/TB-Dx-Landscape_1-Jul-2013.pdf Diagnostics for tuberculosis. Global Demand and market potential. Geneva, Special Programme for Research and Training in Tropical Diseases (TDR) and Foundation for Innovative New Diagnostics (FIND), 2006. Доступно на: http://www.who.int/tdr/publications/documents/tbdi.pdf

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89

рисунок 8.2

Процесс разработки новых противотуберкулезных препаратов, июль 2013 года a Открытие Доклинические исследования Надлежащая лабораторная практика, Токсичность

Клинические исследования

Поиск активной субстанции Циклопептиды Diarylquinoline Ингибиторы DprE Ингибитор InhA Ингибитор LeuRS Макролиды Ингибиторы микобактериальной гиразы Аналоги пиразинамида Риминофеназины Комплексы рутений (II) Спектинамиды Ингибиторы транслокация-1

Доклинические исследования CPZEN-45 DC-159a Q203 SQ609 SQ641 TBI-166

Фаза I

Фаза II AZD5847 Bedaquiline (TMC-207) Linezolid Novel Regimensb PA-824 Rifapentine SQ-109 Sutezolid (PNU100480)

Фаза III Delamanid (OPC-67683) Gatifloxacin Moxifloxacin Rifapentine

PBTZ-169 TBA-354

Химические классы: фторхинолоны, рифамицин, оксазолидиноны, нитроимидазол, diarylquinoline, бензотиазинон a b

Подробнее с перечисленными проектами можно ознакомиться на сайте: www.newtbdrugs.org/pipeline, с проектами, над которыми ведется работа в настоящее время и по которым перспективные компоненты еще не определены, можно ознакомиться на сайте: www.newtbdrugs.org/pipeline-discovery Комбинированные схемы: NC-001-(J-M-Pa-Z), Phase IIa; NC-002-(M-Pa-Z), Phase IIb; NC-003-(C-J-Pa-Z), Phase IIa; PanACEA-MAMS-TB-01-(H-R-Z-E-Q-M), Phase IIb.

могли бы способствовать большей активности разработчиков диагностических тестов на ТБ. Несмотря на значительный прогресс в разработке новых средств диагностики, необходимы большие усилия и инвестиции, как доноров, так и производителей, для ускорения процесса оценки диагностической точности и надежности новых технологий в различных эпидемиологических и организационных условиях. Существенное дополнительное финансирование в разработку новых методов диагностики ТБ имеет основополагающее значение для обеспечения больных ТБ надежными, простыми в использовании и доступными диагностическими тестами. Сфера диагностики ТБ больше, чем когда-либо, нуждается в существенных инвестициях.

Статус разработок новых противотуберкулезных препаратов по состоянию на июль 2013 года показан на Рисунке 8.2. Семь препаратов проходят Фазу II клинических испытаний (показана ранняя бактерицидная активность и негативация мокроты, подтвержденная методом посева, в течение восьми недель) и четыре препарата проходят клинические испытания III фазы (на клиническую эффективность). В общей сложности 10 новых или ранее применявшихся препаратов (для изучения возможности расширения показаний для применения) проходят клинические испытания II и III фазы; один препарат (рифапентин — рифамицин, обладающий более длительным периодом полувыведения, чем рифампицин) проходит клинические испытания II и III фазы для изучения различных показаний.

8.2  Новые препараты для лечения и профилактики ТБ Противотуберкулезные препараты первого ряда используются уже около 50 лет. Схема лечения новых случаев ТБ с сохраненной чувствительностью возбудителя к противотуберкулезным препаратам (ЛЧ ТБ), рекомендуемая ВОЗ и используемая в настоящее время, обладает высокой клинической эффективностью (показатель излечения около 90% среди ВИЧ-отрицательных пациентов). Тем не менее, данная схема требует шести месяцев лечения препаратами первого ряда (сочетание рифампицина, изониазида, этамбутола и пиразинамида в течение двух месяцев, с последующим лечением рифампицином и изониазидом в течение четырех месяцев фазы продолжения). Рекомендуемые ВОЗ схемы лечения МЛУ-ТБ с использованием препаратов второго ряда, рассчитанные, как минимум, на 20 месяцев лечения для большинства больных, сопровождаются множественными (и иногда серьезными) побочными эффектами и достигаются более низкие показатели эффективности лечения (см. Главу 4). В группе больных туберкулезом, сочетанным с ВИЧ-инфекцией, приходится проводить противотуберкулезную и антиретровирусную терапии. Поиск новых препаратов имеет целью сократить продолжительность лечения, упростить схемы лечения, при этом повысить эффективность и переносимость лечения у больных МЛУ-ТБ и больных туберкулезом, сочетанным с ВИЧ-инфекцией. 90

8.2.1 Клинические испытания III фазы Результаты III фазы клинического испытания «Rifaquin», направленного на оценку безопасности и эффективности двух схем лечения больных с ЛЧ ТБ, в которых моксифлоксацин заменил изониазид в интенсивной фазе лечения, а рифапентин был использован в фазе продолжения лечения, были представлены в марте 2013 года 1. В общей сложности 827 пациентов с ЛЧ ТБ были взяты на лечение в Ботсване, Замбии, Зимбабве и ЮАР. Обе новые схемы были перенесены хорошо. Шестимесячный режим с еженедельной дозой рифапентина (1200 мг) и моксифлоксацином в фазе продолжения не уступал рекомендуемой на данный момент схеме. Тем не менее, четырехмесячная схема лечения с дозой рифапентина (900 мг) два раза в неделю и моксифлоксацином в фазе продолжения явно уступает рекомендуемой на данный момент схеме. В двух клинических испытаниях III фазы оцениваются четырехмесячные комбинации схем, в которых фторхинолоны (гатифлоксацин в клиническом испытании OFLOTUB и моксифлоксацин в клиническом испытании ReMOX) заменяют этамбутол (в случае испытаний OFLOTUB), этамбутол или изониазид (в случае 1

Jindani A et al. 2013. A Multicentre Randomized Clinical Trial to Evaluate High-dose Rifapentine with a Quinolone for Treatment of Pulmonary TB: The RIFAQUIN Trial. Oral abstract and paper 147LB. 20th Conference on Retroviruses and Opportunistic Infections (CROI), March 3–6 2013, Atlanta.

Доклад о глобальной борьбе с туберкулезом 2013

Вставка 8.2

Временное руководство ВОЗ по использованию bedaquiline для лечения МЛУ-ТБ По оценкам ВОЗ, в мире ежегодно развивается около 450 000 новых случаев заболевания МЛУ-ТБ (Глава 2). Современные схемы лечения МЛУ-ТБ, рекомендуемые ВОЗ, обладают недостатками: лечение длится 20 месяцев или более и требуется ежедневный прием препаратов, которые являются более токсичными, менее эффективными, и гораздо более дорогими, чем те, которые используются для лечения ЛЧ ТБ a. В мире, только около 50% пациентов, начавших курс лечения по поводу МЛУ-ТБ, завершают его успешно (Глава 4). Впервые за последние 40 лет, противотуберкулезный препарат с новым механизмом действия — bedaquiline — стал доступен для применения. В декабре 2012 года FDA разрешило его практическое применение после проведения ускоренной процедуры регистрации. В отношении данного препарата имеются большие ожидания в плане лечения МЛУ-ТБ. Тем не менее, данные об этом препарате остаются ограниченными, так как он прошел только два испытания фазы IIб на безопасность и эффективность. По этим причинам, ВОЗ выпустила «временное руководство по применению» b. Это временное руководство содержит рекомендации по включению bedaquiline в комбинированную терапию лечения МЛУ-ТБ в соответствии с существующими рекомендациями ВОЗ по ведению ЛУ TB a. Временное руководство включает пять условий, которые необходимо выполнить для того, чтобы использовать bedaquiline для лечения взрослых с МЛУ-ТБ: 1. Эффективное лечение и мониторинг. В процессе лечения должен проводиться тщательный мониторинг эффективности и безопасности лечения при помощи протоколов ведения больных, утвержденных соответствующими национальными органами. 2. Соблюдение критериев отбора пациентов. При применении bedaquiline у людей в возрасте 65 лет и старше и у взрослых больных с ВИЧ-инфекцией требуется особая осторожность. Не рекомендуется назначать препарат беременным и детям. 3. Информированное согласие. Перед началом лечения больные должны быть проинформированы о всех потенциальных преимуществах и рисках нового препарата и дать информированное согласие в письменной форме. 4. Соблюдение рекомендаций ВОЗ. Все принципы, лежащие в основе рекомендаций ВОЗ по лечению МЛУ-ТБ, должны быть соблюдены. В частности, четыре эффективных препарата второго ряда должны быть частью схемы. В соответствии с общими принципами лечения туберкулеза bedaquiline не должен вводиться в схему, содержащую неэффективные лекарственные средства. 5. Система наблюдения за безопасностью лекарственных средств (фармаконадзор) и борьба с побочными эффектами. Система наблюдения за безопасностью лекарственных средств должна обеспечить раннее выявление и борьбу с побочными эффектами и отслеживать взаимодействие с другими лекарственными средствами. ВОЗ настоятельно рекомендует форсировать начало III фазы клинических испытаний bedaquiline для получения более полных данных, которые послужат основой для разработки методических рекомендаций по его применению. ВОЗ будет пересматривать, вносить изменения или обновлять временное руководство по мере поступления дополнительных сведений об эффективности и безопасности препарата. ВОЗ также разрабатывает документ, который обеспечит оперативное руководство по применению bedaquiline и сотрудничает с партнерами по рациональному внедрению препарата. Guidelines for the programmatic management of drug-resistant tuberculosis – 2011 update. Geneva, World Health Organization, 2011 (WHO/ HTM/TB 2011.6). b The use of bedaquiline in the treatment of multidrug-resistant tuberculosis: interim policy guidance. World Health Organization. Geneva, Switzerland. 2013 (WHO/HTM/TB/2013.6). a

испытания ReMOX). Результаты обоих исследований ожидаются к концу 2013 года. Новое соединение, delamanid (OPC-67683), в настоящее время проходит клинические испытания III фазы в качестве дополнения к существующим оптимизированным схемам лечения МЛУ-ТБ.

8.2.2 Клинические испытания II фазы — отдельные препараты Безопасность, переносимость и антимикробная активность увеличенной суточной дозы рифапентина (в 10, 15 и 20 мг/кг) в сочетании с изониазидом, пиразинамидом и этамбутолом в течение первых двух месяцев лечения изучаются во IIb фазе клинических испытаний (испытание TBTC 29X). Первые результаты были представлены в мае 2013 года 1. В результате клинического испытания было установлено, что схемы, основанные на применении рифапентина, переносятся хорошо, без дополнительной токсичности, связанной с увеличением дозы, и после восьми недель лечения у большей доли пациентов наступила негативация мокроты, определяемая методом посева на жидких и плотных средах, по сравнению с рекомендуемой на данный момент шестимесячной 1

Moro et al. Tolerability and safety of escalating Rifapentine (RPT) doses during the first two months of tuberculosis (TB) treatment. Abstract A6051. American Thoracic Society International Conference, Philadelphia, May 17–22, 2013

схемой лечения. В группе пациентов, получавших самую высокую дозу рифапентина, в 100% случаев прекратилось бактериовыделение, определяемое методом посева после восьми недель лечения (по сравнению с 16 неделями при лечении согласно текущим стандартам). Исследователи пришли к выводу, что высокая антимикробная активность в сочетании с хорошей переносимостью и безопасностью препарата, применяемого в высокой дозе, позволяют перейти к клиническим испытаниям III фазы, включающим ежедневный прием высоких доз рифапентина и продолжительности лечения менее шести месяцев. Среди других препаратов, прошедших II фазу клинических испытаний в  прошлом году, лучшие результаты отмечены у bedaquiline (TMC-207). FDA по ускоренной процедуре одобрило использование bedaquiline в качестве дополнения к существующим схемам лечения МЛУ-ТБ в декабре 2012 года. Bedaquiline стал первым новым противотуберкулезным препаратом, который был разрешен для применения за последние 40 лет. Третья фаза испытаний, направленная на исследование безопасности и эффективности bedaquiline в комбинации с укороченной схемой лечения МЛУ-ТБ, запланирована на конец 2013 года. После выхода результатов испытаний и решения FDA, ВОЗ выпустила временное руководство по использованию bedaquiline в лечении МЛУ-ТБ в июне 2013 года (Вставка 8.2). Пять других препаратов находятся во II фазе разработок. Данные препараты представлены линезолидом, сутезолидом, PA-824, SQ-109 и AZD-5847. 91

Доклад о глобальной борьбе с туберкулезом 2013

Линезолид (Linezolid) (относится к антибиотикам группы линкозамидов) был одобрен в  2000  году для лечения лекарственно­устойчивых, грамположительных бактериальных инфекций. Этот препарат показал хорошую антимикобактериальную активность in-vitro и все чаще используется «не по прямому назначению» для лечения пациентов с высокой степенью лекарственной устойчивости возбудителя ТБ к антибактериальным препаратам. Тем не менее, были зарегистрированы серьезные побочные эффекты (например, периферическая и оптическая невропатия, анемия и тромбоцитопения). Результаты проспективного рандомизированного исследования по изучению действия линезолида при лечении пациентов с ШЛУТБ, в отношении которых комбинации из других доступных антибактериальных препаратов не оказали эффекта, были опубликованы в конце 2012 года 1. В общей сложности 41 пациенту была назначена терапия линезолидом (600 мг в сутки), которая была применена или сразу, или через два месяца без каких-либо изменений в фоновой схеме лечения. После подтверждения конверсии мазка мокроты или после четырех месяцев лечения (в зависимости от того, что произошло раньше) была произведена вторая рандомизация для продолжения терапии линезолидом в дозе либо 600 мг или 300 мг в сутки в течение еще не менее, ​ чем 18 месяцев при проведении тщательного мониторинга токсичности. Результаты показали, что через четыре месяца, 15 из 19 пациентов (79%) в группе, немедленно приступившей к лечению, и 7 из 20 (35%) в группе, отложившей начало лечения, прекратили бактериовыделение, определяемое методом посева (р = 0,001). Большинство пациентов (34 из 39 [87%]) получали отрицательные результаты микроскопии мазка мокроты в течение шести месяцев после того, как линезолид был добавлен к фоновой схеме лечения. Из 38 пациентов, получавших линезолид, 31 (82%) столкнулись с клинически значимыми побочными эффектами, которые вероятно, были связаны с линезолидом, в том числе три пациента, прекратившие терапию. В группе пациентов, получавших 300 мг препарата в сутки после второй рандомизации, частота побочных эффектов была меньше, чем в группе, принимающих 600 мг в сутки. В группе пациентов, завершивших лечение (n=13), до конца периода наблюдения не было зарегистрировано рецидивов заболевания. Наблюдалось четыре случая приобретенной устойчивости к линезолиду. Исследователи пришли к выводу, что линезолид был эффективен в достижении негативации мокроты, определяемой посевом среди пациентов с хронической формой туберкулеза легких с ШЛУ возбудителя, но предупредили, что необходимо проведение тщательного мониторинга побочных эффектов. Ограничениями исследования являются: небольшой объем выборки и развитие устойчивости к линезолиду у 10% пациентов. Необходим больший объем данных, чтобы сбалансировать долгосрочные риски и преимущества линезолида, как части комплексного лечения совместно с другими эффективными противотуберкулезными препаратами. Сутезолид (Sutezolid) (PNU-100480) является линкозамидом (oxazolidinone) и аналогом линезолида. В рамках данного исследования была изучена ранняя бактерицидная активность (РБA) препарата в дозах 600 мг два раза в сутки или 1200 мг один раз в сутки. Согласно результатам исследования, представленным в 2012 году, применение sutezolid в обеих дозировках привело к значительному сокращению колониеобразующих единиц (КОЕ) в течение 14 дней лечения по сравнению с исходным уровнем 2. Полученные результаты свидетельствуют об очень высокой эффективности при применении препарата в дозе 600 мг два раза в сутки. PA-824 принадлежит к группе нитроимидазолов и проходит клинические испытания в рамках нескольких возможных комбинаций лечения (см. ниже). 92

SQ-109, первоначально синтезированный как производное этамбутола, также проходит клинические испытания в качестве части комбинированной схемы лечения (см. ниже). AZD-5847 проходит II фазу клинических испытаний.

8.2.3 Клинические испытания II фазы — новые схемы лечения Наряду с клиническими испытаниями отдельных соединений, новые комбинации препаратов уже проходят или в ближайшее время пройдут испытания II фазы. Доклад о глобальной борьбе с туберкулезом 2012 года привел результаты исследования ранней бактерицидной активности новой схемы лечения (NC001), включающей моксифлоксацин, пиразинамид и новый препарат PA-824 3. В настоящее время проводятся три клинических испытания различных комбинированных схем лечения. Клиническое испытание первой схемы NC-002 основано на изучении применения схемы NC-001 в течение двух месяцев. Испытания проводятся в Танзании и Южно-Африканской Республике. Схема предлагается пациентам с ЛЧ ТБ и пациентам, имеющим лекарственную устойчивость к препаратам, не включенным в новую схему. Испытание схемы NC-002 является знаковым, так как это первое испытание, позволяющее одновременно изучать эффективность одной схемы лечения при ЛЧ ТБ и ЛУ ТБ. Результаты ожидаются в конце 2013 года 4. В рамках второго клинического испытания NC-003 определяется ранняя бактерицидная активность различных комбинаций клофазимина, bedaquiline, PA-824 и пиразинамида у больных с ЛЧ ТБ 5. Клиническое испытание MAMS-ТБ-01, проводимое консорциумом PanACEA, оценивает новую трехмесячную комбинированную схему лечения с применением нового адаптивного дизайна клинического исследования 6. Препараты, включенные в комбинированную схему, представлены изониазидом, рифампицином, пиразинамидом, этамбутолом, моксифлоксацином и SQ-109. Конечным пунктом для оценки эффективности схемы используется время конверсии мокроты, определяемое посевом на жидкие среды. Исследование началось в мае 2013 года 7.

8.2.4 Новые разработки в лечении латентной туберкулезной инфекции На данный момент проходят клинические испытания новые препараты для лечения латентной туберкулезной инфекции (ЛТИ) (при отсутствии признаков активного туберкулеза). Рифапентин был включен в комбинированную схему в рамках исследования TBTC 26, называемого также PREVENT-TB. Первые результаты исследования были опубликованы в декабре 2011 года 8 . Включение в исследование и последующее 1

Lee M et al. Linezolid for Treatment of Chronic Extensively Drug-Resistant Tuberculosis. New England Journal of Medicine 2012;367:1508-18. DOI: 10.1056/NEJMoa1201964 2 Wallis R et al. Safety, tolerability and early bactericidal activity in sputum of PNU-100480 (sutezolid) in patients with pulmonary tuberculosis (Abstract THLBB02). 19th International AIDS Conference 2012, July 22–27, Washington DC. 3 Diacon AH et al. 14-day bactericidal activity of PA-824, bedaquiline, pyrazinamide and moxifloxacin combinations: a randomised trial. The Lancet, 2012 4 См.: http://clinicaltrials.gov/show/NCT01498419 5 См.: http://clinicaltrials.gov/show/NCT01691534 6 Phillips P et al. Innovative trial designs are practical solutions for improving the treatment of tuberculosis. Journal of Infectious Diseases. 2012;205 Suppl 2:S250–7. 7 См.: http://clinicaltrials.gov/show/NCT01785186 8 Sterling T et al. Three Months of Rifapentine and Isoniazid for Latent Tuberculosis Infection. New England Journal of Medicine 2011; 365;23: 2155–66.

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Повышение внимания к лечению латентной туберкулезной инфекции По оценкам, треть населения мира, инфицирована M. tuberculosis. У людей с латентной ТБ инфекцией (ЛТИ) отсутствуют симптомы ТБ и они не являются заразными, но они имеют повышенный риск развития активной формы заболевания и стать заразными. Исследования показывают, что 5–20% инфицированных M. tuberculosis имеют риск развития активной формы ТБ в течение жизни, причем у большинства из них это происходит в течение 2–5 лет после первичного инфицирования. Несколько факторов увеличивают риск прогрессирования от инфицирования до активного ТБ: иммуносупрессия (например, связанная с ВИЧ-инфекцией, или иммуносупрессивным лечением), недоедание, диабет и злоупотребление алкоголем. Таким образом, профилактика активного ТБ с учетом данных факторов, как и своевременная диагностика и лечение латентного ТБ в отдельных группах риска, являются важными для индивидуального и общественного здоровья. Моделирование показало, что диагностика и лечение латентного ТБ может сыграть ключевую роль в ликвидации ТБ. Недавно ВОЗ опубликовала методические рекомендации по расследованию контактов ТБ и по систематическому скринингу активного ТБ a, b, которые содержат критерии для определения групп риска для диагностики и лечения ЛТИ. Профилактическая терапия изониазидом (ПТИ) является основой настоящих рекомендаций ВОЗ по лечению ЛТИ. Лечение рекомендуется в отношении двух особых групп населения: больных ВИЧ-инфекцией, и детей моложе пяти лет, которые имеют домашние или другие тесные контакты с больными ТБ. Недавний Кохрейновский обзор показал, что схемы, содержащие рифампицин и рифапетин, у ВИЧ-отрицательных людей имеют более высокий показатель «завершения лечения» и меньшую частоту побочных эффектов по сравнению со схемами, содержащими только изониазид c. Перед началом лечения ЛТИ, очень важно, чтобы активная форма ТБ была исключена, и диагноз ЛТИ был достоверно установлен. Туберкулиновая кожная проба и исследование высвобождения гаммаинтерферона (IGRA), предназначенные для обнаружения клеточного иммунного ответа на микобактерии туберкулеза, не разграничивают латентную инфекцию от активной формы заболевания и, в случае отрицательного результата исследования, не позволяют исключить ТБ инфекцию. Самое главное, они не могут точно определить риск развития активной формы ТБ у инфицированных лиц, а их использование в повседневной практике представляет операционные и ресурсные проблемы. Есть несколько открытых вопросов, связанных с выявлением и лечением латентного ТБ, требующих проведения срочных научно-исследовательских работ и соответствующего увеличения инвестирования. Фундаментальная природа латентной инфекции на данный момент не до конца изучена и не существует действительно адекватных животных моделей для изучения этого феномена. Также не существует методов диагностики и лечения латентной формы ТБ, вызванной лекарственно-устойчивыми штаммами микобактерий M. tuberculosis у людей. Открытие эффективных методов диагностики и лечения ЛТИ является критически важным для глобальной борьбы с ТБ. Особое внимание должно быть уделено изучению основ патогенеза туберкулеза и выявлению биомаркеров, которые обеспечат надежную диагностику и более короткое и менее токсичное лечение ЛТИ. В связи с последними разработками в лечении ЛТИ, ВОЗ планирует обновить методические рекомендации по контролю над ЛТИ. Для этого потребуется: изучить имеющиеся научные данные с особым акцентом на группы риска, которые имеют наиболее высокую вероятность развития активной формы ТБ после заражения, обратить должное внимание на анализ рискапользы и сопутствующих факторов риска.

a

Recommendations for investigating contacts of persons with infectious tuberculosis in low- and middle-income countries. Доступно на: http:// apps.who.int/iris/bitstream/10665/77741/1/ 9789241504492_eng.pdf b Systematic screening for active tuberculosis – Principles and recommendations. Доступно на: http://apps.who.int/iris/bitstream/ 10665/84971/1/9789241548601_eng.pdf c Sharma SK et al. Rifamycins (rifampicin, rifabutin and rifapentine) compared to isoniazid for preventing tuberculosis in HIV-negative people at risk of active TB. Cochrane Database of Systematic Reviews 2013, Issue 7. Art. No.: CD007545. DOI: 10.1002/14651858.CD007545. pub2.

наблюдение в отношении двух групп, представляющих особый интерес (дети в возрасте от 2 до 11 лет, и больные ВИЧ-инфекцией) было продлено и завершится в сентябре 2013 года. Предварительные результаты показали, что схема, включающая рифапентин и изониазид один раз в неделю в течение трех месяцев (3HP) в целом хорошо переносится и демонстрирует существенные преимущества по сравнению с текущим стандартом приема изониазида в течение девяти месяцев для лечения латентного туберкулеза у детей 1. Исследование 33, называемое также iAdhere, является IV фазой продолжения исследования TBTC 26, имеет целью изучить эффективность комбинации 3HP (проверенной в PREVENT-ТБ) при обеспечении: (1) непосредственно контролируемого лечения (DOT), (2) самоконтроля, (3) самоконтроля с помощью текстовых сообщений-напоминаний по мобильному телефону. Это исследование, как ожидается, будет завершено в марте 2014 года. Второе исследование, проведенное Группой по организации клинических испытаний по ВИЧ-инфекции (ACTG), включало ежедневное применение рифапентина и изониазида в течение одного месяца для лечения латентной ТБ инфекции (ЛТИ) у больных ВИЧ-инфекцией. Третье исследование, направленное на оценку эффекта однократного или повторного применения рифапентина при ежедневной или еженедельной схеме, в сочетании с пролонгированным вариантом комбинации фиксированных

доз эфавиренца, эмтрицитабина и тенофовира в виде (Atripla ™), начало набор пациентов в сентябре 2012 года и завершило его в августе 2013 года. Четвертое исследование, направленное на сравнение безопасности и эффективности четырехнедельной схемы ежедневного приема рифапентина и изониазида со стандартной девятимесячной схемой ежедневного применения изониазида у больных ВИЧ-инфекцией, начало набор пациентов в мае 2012 года и, как ожидается, завершит набор в марте 2018 года. Пятое исследование, направленное на изучение безопасности и переносимости четырехмесячной схемы применения рифампицина один раз в день у детей, проводится Канадским институтом исследований в области здравоохранения и университетом McGill. Результаты ожидаются в 2016 году 2.

Villarino et al. Tolerability among children of three months of onceweekly rifapentine + INH (3HP) vs. 9 months of daily INH (9H) for treatment of latent tuberculosis infection: The PREVENT TB Study (TBTC Study 26/ACTG 5259). IDSA Conference 2012. 2 Clayden P et al, on behalf of the HIV i-Base/Treatment Action Group. 2013 Pipeline Report: HIV, Hepatitis C Virus (HCV), and Tuberculosis (TB) Drugs, Diagnostics, Vaccines, Preventive Technologies, Research Toward a Cure, and Immune-Based and Gene Therapies in Development. Доступно на: http://www.treatmentactiongroup.org/pipeline-report 1

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8.3 Новые противотуберкулезные вакцины Медленное снижение темпов заболеваемости ТБ на глобальном уровне и растущая проблема МЛУ-ТБ вызывают острую необходимость в новых эффективных противотуберкулезных вакцинах (ТБ вакцины). Вакцине БЦЖ для профилактики ТБ почти 100 лет, и хотя вакцина защищает детей от тяжелых форм туберкулеза (туберкулезный менингит и милиарный ТБ), ее эффективность в предотвращении туберкулеза легких у взрослых вариабельна. Вакцинация БЦЖ также не рекомендуется у детей, инфицированных ВИЧ, в связи с риском диссеминированных форм БЦЖ-инфекции. Развитие молекулярно-генетических методов изучения микобактерий, расшифровка последовательности генома M. tuberculosis в 90-х годах прошлого века, и последние достижения в области иммунологии предоставляют исторические возможности для разработки нового поколения ТБ вакцин, которые смогут оказать более существенное влияние на ситуацию. За последние десять лет две основные стратегии были использованы для разработки новых ТБ вакцин 1. Одна из стратегий заключается в разработке вакцин, которые будут иметь более высокую эффективность, чем БЦЖ и смогут заменить ее — такие, как улучшенная версия БЦЖ или новая аттенуированная живая вакцина M. tuberculosis. Вторая стратегия — это стратегия «прайм-буст», при которой БЦЖ по-прежнему назначается новорожденным (как это делается в настоящее время, так как она предотвращает туберкулез у младенцев и детей), а новая вакцина дается как поддерживающая «бустер-доза» для повышения эффективности и продления срока иммунной защиты. Моделирование потенциального воздействия на здоровье населения применения новых ТБ вакцин в регионе Юго-Восточной Азии демонстрирует, что противотуберкулезная вакцина для детей с 60% эффективностью будет способствовать значительному снижению заболеваемости ТБ к 2050 году 2. Кроме того, это моделирование также показало, что, если бы профилактическая ТБ вакцина такой же эффективности применялась в рамках массовой вакцинации подростков и взрослых, воздействие на эпидемию ТБ было бы более значительным. Последние попытки моделирования воздействия новой вакци3 подтвердины на здоровье населения на глобальном уровне  ли этот вывод, демонстрируя то, что вакцина для подростков и взрослых с 60% эффективностью потенциально может предотвратить 30–50 миллионов новых случаев заболевания ТБ в течение 25 лет. Информация о гораздо большем потенциале воздействия вакцины для подростков и взрослых сместила фокус разработок ТБ вакцин к новой парадигме, которая подчеркивает необходимость разработок разнообразных новых вакцин-кандидатов, ориентированных на профилактику ТБ в старших группах населения. Научные достижения также позволили обеспечить более сложные подходы к разработке вакцин, а глобальный выбор вакцин-кандидатов для клинических испытаний является более обширным, чем в любой предыдущий период истории. Спектр вакцин сейчас представлен рекомбинантной БЦЖ, аттенуированными (ослабленными) штаммами M. tuberculosis, рекомбинантными платформами на вирусных векторах, белковыми/адъювантными комбинациями и микобактериальными экстрактами. Статус разработок новых вакцин по состоянию на июль 2013 года показан на Рисунке 8.3. Двенадцать вакцин-кандидатов проходят клинические испытания. Большинство из них предназначены для профилактики ТБ: предотвращения инфицирования (до контакта) или прогрессирования первичного туберкулеза и реактивации латентного ТБ (после контакта). Две вакцины представляют собой замену вакцины БЦЖ и две предлагаются в качестве иммунотерапевтических средств для 94

повышения эффективности химиотерапии или предотвращения рецидива или реинфицирования. Две вакцины проходят фазу IIb клинических испытаний. MVA85A является ослабленной векторной вакциной-кандидатом, содержащим Ag85A из M. tuberculosis. Она была разработана в качестве бустерной вакцины для грудных детей, вакцинированных БЦЖ. Первое испытание фазы IIb этой вакцины было проведено в Южно-Африканской Республике с 2009 по 2012 годы. Результаты были опубликованы в начале 2013 года (Вставка 8.4) 4. Дополнительное испытание IIb фазы MVA85A в настоящее время проводится среди больных ВИЧ-инфекцией в Сенегале и Южно-Африканской Республике. Испытания были недавно переориентированы на проверку безопасности, и ожидается набор до 650 участников. M72 + AS01E является субъединичной белковой вакциной, полученной в новом адъюванте для повышения иммуногенности. Она содержит гибридный белок, содержащий антигены 32A и 39A M. tuberculosis в адъюванте AS01E. Вакцина проходит клинические испытания на безопасность и иммуногенность в трех различных группах населения: грудных детей в Гамбии, больных ВИЧ-инфекцией в Индии и взрослых больных ТБ в Китае (провинция Тайвань) и Эстонии. Испытание IIb фазы станет крупнейшим исследованием новой ТБ вакцины для взрослых и будет включать 4500 ВИЧ-отрицательных взрослых в эндемичных по ТБ странах Африки. Первичной «конечной точкой» будет — эффективность защиты в результате применения двух доз M72 + AS01E от легочного ТБ. Вторичными «конечными точками» приняты безопасность и иммуногенность вакцины. Еще шесть вакцин проходят фазу II клинических испытаний. AERAS-402/Crucell Ad35 аденовирус-векторная вакцина-кандидат, содержащая три антигена M. tuberculosis: Ag85A, Ag85B и TB10.4, разработана как бустерная вакцина для грудных детей, подростков и взрослых. Исследование, было задумано как «испытание для отработки концепции» в рамках фазы IIb, но после получения предварительных данных, трансформировано в менее масштабные испытания фазы II на безопасность и иммуногенность в качестве первичных «конечных точек». Следует отметить, что AERAS-402/Crucell Ad35 и MVA85A также проходят совместные испытания, чтобы попытаться достичь сбалансированного CD4 +/CD8+ иммунного ответа. Схема из одной или двух доз AERAS-402/Crucell Ad35, с последующей одной дозой MVA85A, в настоящее время проходит испытания фазы I/фазы II на безопасность и иммуногенность у взрослых в Великобритании. Три белковые субъединичные адъювантные вакцины были первоначально разработаны Statens Serum Institute в Копенгагене, Дания. Hybrid 1 + IC31 содержит Ag85B и ESAT-6 в адъюванте, IC31. Hybrid 56 + IC31 содержит антигены 85B и ESAT6, а также AgRv2660, которые экспрессируются в латентном периоде. Вакцина Hybrid 4 + IC31, в настоящее время разрабатываемая Sanofi Pasteur, представляет собой гибридный белок, который содержит Ag85B и TB10.4; последний антиген принадлежит к тому же семейству генов, как и ESAT-6. Все три вакцины изучаются в фазе IIa клинических испытаний в Африке. 1

Evans TG, Brennan MJ, Barker L and Thole J. Preventive vaccines for tuberculosis. Vaccine. 31S (2013) B223– B226. 2 Abu-Raddad LJ, et al. Epidemiological benefits of more-effective tuberculosis vaccines, drugs, and diagnostics. Proceedings of the National Academy of Science. 2009. 106:33; 13980–13985. 3 Модель глобального воздействия на здравоохранение новых вакцин против ТБ была инициирована Aeras и развита компанией Applied Strategies. Официальная публикация модели и связанных с ней результатов ожидается. 4 Tameris MD, et al. Safety and efficacy of MVA85A, a new tuberculosis vaccine, in infants previously vaccinated with BCG: a randomised, placebo-controlled phase 2b trial. The Lancet. 2013. 381:9871; 1021–1028.

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рисунок 8.3

Новые вакцины против туберкулеза в процессе разработки, июль 2013 года Фаза I AdAg85A McMaster, CanSino Фаза II VPM 1002 Max Planck, VPM, TBVI, Serum Institute Фаза IIb MVA85A/AERAS-485 Oxford, Aeras, EDCTP Фаза III M. Vaccae Anhui Longcom

P  B  P I MTBVAC TBVI, Zaragoza, Biofabri

P  B H1+IC31 SSI, TBVI, EDCTP, Intercell

B  P I  i t M72+AS01 GSK, Aeras

i t

P ID93+GLA-SE Infectious Disease Research Institute (IDRI), Aeras

B  P I

P  B  P I RUTI Archivel Farma, S.L.

B Crucell Ad35/MVA85A Crucell, Oxford, Aeras

B  P I  i t H56/AERAS-456+IC31 SSI, Aeras, Intercell

P  B

P  B  P I H4/AERAS-404+IC31 SSI, Sanofi Pasteur, Aeras, Intercell

P

Первичная 

B Бустерная  P I Постинфекционная  i t Иммунотерапевтическая

B Crucell Ad35/AERAS-402 Crucell, Aeras

B

Типы вакцин Вакцина на вирусных векторах: MVA85A, AERAS-402, AdAg85A Белковая/адъювантная: M72, Hybrid-1, Hyvac 4, H56, ID93 rBCG: VPM 1002 Убитая WC или Экстрагированная: Mw, RUTI Источник: Новые вакцины против туберкулеза, Рабочая группа по новым вакцинам

VPM 1002 живая рекомбинантная вакцина, полученная из штамма БЦЖ Прага, в которую ген листеролизин из Listeria monocytogenes был клонирован, а ген уреазы удален для улучшения иммуногенности. Испытания фазы IIa этой вакцины были недавно завершены в Южно-Африканской Республике. Второе испытание II фазы будет оценивать безопасность и иммуногенность вакцины при применении в группах новорожденных с ВИЧ-инфекцией и без ВИЧ-инфекции. RUTI инактивированная вакцина на основе фрагментированных клеток M. tuberculosis, находится на испытаниях фазы IIa в Испании и разрабатывается в качестве иммунотерапевтической вакцины. В дополнение к вакцинам-кандидатам, описанным выше, китайская фармацевтическая компания AnHui Longcom проводит исследования Mycobacterium vaccae — инактивированной вакцины из непатогенной микобактерии, для применения в качестве дополнения к стандартной антибактериальной терапии. Фаза III испытаний эффективности находится на стадии реализации. На данный момент три вакцины-кандидата находятся в I фазе клинических испытаний. К ним относятся: первая живая аттенуированная (ослабленная) вакцина М. tuberculosis, MTBVAC, а также новая гибридная белковая вакцина, ID93 с новым адъювантом GLA-SE. MTBVAC разрабатывается в Университете Сарагосы, Институте Пастера, BIOFABRI и Инициативой по разработке противотуберкулезных вакцин (TBVI). Это живая вакцина M. tuberculosis, ослабляется через удаление генов phoP и fadD26. Данная вакцина стала первой живой ослабленной вакциной M. Tuberculosis, вошедшей в I фазу клинических испытаний. ID93 + GLA-SE является рекомбинантной белковой вакциной в новом адъюванте, GLA-SE. Вакцина разрабатывается Научно-исследовательским институтом инфекционных заболеваний (IDRI) в сотрудничестве с Aeras. Она содержит три антигена вирулентности M. tuberculosis (Rv2608, Rv3619 и Rv3620) и один антиген латентной фазы M. tuberculosis (Rv1813). Вакцина

вступила в Ib фазу испытаний у взрослых в Южно-Африканской Республике для оценки безопасности и иммуногенности при применении в этой группе населения. Ad5 Ag85A является вакциной на основе вектора аденовируса 5 серотипа, экспрессирующего Ag85A <микобактерии>. Она была разработана Университетом МакМастер при поддержке Cansino, китайской биотехнологической компании, располагающейся в Тяньцзине. Вакцина была недавно протестирована в I фазе испытаний. В результате испытания вакцины не было зарегистрировано серьезных побочных эффектов и была показана ее большая иммуногенность в группе испытуемых, получивших первичную вакцинацию БЦЖ. Исследование новых противотуберкулезных вакцин сейчас находится на решающем этапе. Несмотря на разнообразие, которое уже существует в глобальной линейке вакцин-кандидатов, проходящих клинические испытания, ученые осознают тот факт, что имеется слишком много сходств в изучаемых иммунологических стратегиях 1. В отсутствие данных о том, какие иммунные механизмы определяют как защитный уровень иммунитета против ТБ, так и в целом контроль инфекции, линейка вакцин должна быть диверсифицированной, чтобы кандидаты заняли совершенно другое и новое иммунологическое «пространство». На данный момент уже существует мощный набор вакцин, которые уже получили предварительную клиническую оценку, в том числе вакцины на основе нуклеиновых кислот (ДНК и РНК). Данная оценка может помочь расширить «клинический портфолио» и заполнить научные пробелы, которые существуют в настоящее время. Для рационализации и упорядочения продвижения вакцин-кандидатов между основными заинтересованными сторонами был достигнут консенсус в отношении критериев для управления менеджментом новых противотуберкулезных

1

Evans TG et al. Preventive vaccines for tuberculosis. Vaccine 31S (2013) B223– B226.

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95

Вставка 8.4

Клинические испытания MVA85A в Южно-Африканской Республике MVA85A является коксовирусной («Модифицированный вирус оспы», MVA) векторной вакциной, которая содержит иммунодоминантный антиген M. tuberculosis 85А. Первоначально эта вакцина была разработана в Оксфордском Университете. Испытания IIb фазы в группе грудных детей были недавно завершены в Южно-Африканской Республике a. Исследуемая популяция, состоящая из 2794 вакцинированных БЦЖ ВИЧ-отрицательных детей в возрасте 4–6 месяцев, была разбита на почти одинаковые по размеру подгруппы: опытную, в которой 1399 детей получили одну дозу MVA85A, и контрольную, в которой 1395 детей получили плацебо (Candin, С. Albicans — производный антиген для кожной пробы). Последующее наблюдение длилось 37 месяцев. Основная цель исследования заключалась в оценке безопасности MVA85A у таких детей. Вторичные цели заключались в оценке эффективности вакцины в отношении: (а) профилактики заболевания и (б) профилактики инфицирования M. tuberculosis, оцененной по конверсии Quantiferon (это различие очень важно, поскольку инфекция приводит к развитию активной формы ТБ лишь у небольшого числа иммунокомпетентных лиц). Дополнительные цели включали оценку иммуногенности. зафиксированных в группах испытуемых, по оценкам исследователей, не было связано с применением вакцины. Единственное патологическое состояние, потребовавшее краткой госпитализации, наблюдалось в группе плацебо. Первичный анализ эффективности был основан на числе случаев ТБ в опытной и контрольной группах, так в опытной (вакцинированной) группе, развилось 32 случая, а в группе плацебо 39 случаев. Исходя из этого, эффективность вакцины в отношении развития первичного туберкулеза составила 17,3% (95% ДИ: от –31,9% до 48,2%), что не было статистически значимым. Кроме того, нет никаких данных, полученных с помощью теста Quantiferon — TB Gold, о защите от туберкулезной инфекции. В общей сложности 349 из 2 792 младенцев были инфицированы (178 в вакцинированной группе и 171 в группе плацебо), таким образом, эффективность вакцины составила –3,8% (95% ДИ: от –28,1% до 15,9%), что также не является статистически значимым. защиты, с очень небольшой, если таковая вообще имелась, дополнительной защитой от MVA85A. Показатели ТБ в Южно-Африканской Республике (и в провинции Западный Кейп, в частности) являются исключительно высокими во всех возрастных группах, в том числе среди детей младшего возраста. В условиях подобной эпидемической ситуации трудно противостоять инфекционному процессу с помощью любой вакцины. Трудно предположить, что аналогичные результаты могли бы быть получены и в других популяциях. Возможно, что взрослые, подростки и дети старшего возраста являются лучшей целевой группой для этой вакцины: есть некоторые данные, показывающие, что вакцина вызывает более сильный иммунный ответ у представителей старших возрастных групп, нежели дети в возрасте до 1 года. Взрослые и подростки являются основным источником заболевания, поскольку они более склонны к развитию инфекционных форм заболевания и составляют наибольшую долю бремени ТБ в мире. Вакцина в настоящее время испытывается по схеме двух доз у ВИЧ-инфицированных взрослых в Сенегале и Южно-Африканской Республике. По всем этим причинам, результаты испытаний не должны рассматриваться как окончательный ответ на вопрос о том, может ли новая вакцина против туберкулеза обеспечить лучшую защиту, чем самостоятельное применение БЦЖ. Требуется дальнейшее исследование этой и других вакцин. Несколько других разработанных вакцин-кандидатов отличаются от MVA85A как по антигенному составу, так и по тому, как эти антигены доставляются. a

Выводы для будущих испытаний данной и других вакцин-кандидатов Фаза IIb клинических испытаний предназначена для «скрининга» вакцинкандидатов и определения целевых групп населения с целью снижения рисков до перехода к чрезвычайно сложной и ресурсоемкой III фазе испытаний. Действующие правила требуют, чтобы фаза IIb клинического испытания была поддержана данными следующей III фазы испытаний, прежде чем вакцина будет лицензирована. Это исследование показало, что вакцина имеет приемлемый уровень безопасности у детей, и что проведение подобных высококачественных испытаний новых вакцин возможно и могут быть получены надежные результаты в регионах с высоким бременем ТБ. Вакцина была применена через несколько месяцев после того, как все дети получили вакцину БЦЖ. И вполне возможно, что БЦЖ смогла обеспечить базовый уровень

Выводы, сделанные по результатам испытания IIb фазы Это было первое клиническое испытание эффективности новой вакцины-кандидата для профилактики активного ТБ или инфекции M. tuberculosis, и поэтому результаты исследования представляют значительный интерес для научного сообщества и для практического здравоохранения. В этом исследовании MVA85A показала безопасность и хорошую переносимость, подтверждая аналогичные выводы из предыдущих I и IIb фаз клинических испытаний этой вакцины. Ни одно из наблюдаемых серьезных патологических состояний (или смертей),

Tameris MD, et al. Safety and efficacy of MVA85A, a new tuberculosis vaccine, in infants previously vaccinated with BCG: a randomized, placebocontrolled phase 2b trial. The Lancet. 2013. 381:9871; 1021–1028.

вакцин. Повышенное внимание уделяется глобальной координации между основными заинтересованными сторонами для продвижения согласованной повестки научных исследований. В дополнение к этим усилиям, вновь становятся приоритетными исследования на ранних стадиях разработки. В соответствии с этим, будет происходить смещение приоритетов, усилий и ресурсов ​​на новые разработки и исследования, ориентированные на изучение иммунологических механизмов и биомаркеров, а также на диверсификацию научных подходов и стратегий для того, чтобы разнообразные вакцины-кандидаты могли быть включены в клинические испытания 1.

8.4  Глобальная стратегия борьбы с туберкулезом после 2015 года: актуальность научных исследований и научно-практических разработок Вклад фундаментальной науки необходим для того, чтобы преобразовывать инновации в новые практические инструменты для совершенствования противотуберкулезных мероприятий. Необходимы фундаментальные исследования по изучению природы M. tuberculosis и взаимодействия между микро- и макроорганизмом, как основы для создания новых концепций, которые должны быть трансформированы в новые медицинские технологии. Исследователи делают большие успехи в переосмыслении патогенеза ТБ и механизмов перехода из латентной формы в активную, включая механизмы поведения M. tuberculosis в организме хозяина. Ожидается, что прогресс в данной сфере обеспечит повышение уровня знаний о патогенезе заболевания и идентификации биомаркеров

1

Brennan MJ and Thole J (editors). Tuberculosis vaccines: A strategic blueprint for the next decade. Tuberculosis. 2012. 92: Supplement 1; S6–S13.

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и био-сигнатур, необходимых для разработки новых методов диагностики ТБ. Кроме того, ожидается, что результаты исследований позволят определить: новые биомаркеры для разработки противотуберкулезных препаратов, ранние показатели иммунного ответа, показатели эффективности вакцины и ранние показатели эффективности лечения. Такие разработки будут способствовать отбору и тестированию новых методик лечения. Чтобы подчеркнуть решающую роль научных исследований в прекращении глобальной эпидемии ТБ, Глобальная стратегия ВОЗ ТБ после 2015 года, разрабатываемая в настоящее время, указывает на «Интенсификацию научных исследований и инноваций», как одно из трех стратегических направлений (Глава 1). Новая стратегия разрабатывается, как новый этап в развитии Стратегии «Остановить ТБ», которая охватывает период 2006–2015 годы. В широких обсуждениях, проведенных в 2012 и 2013 годах, данное направление получило твердую поддержку, в особенности, два основных его субкомпонента: 1. Открытие, разработка и быстрое внедрение новых методик, мероприятий и стратегий; 2. Научные исследования по оптимизации осуществления мероприятий и усиления их воздействия.

Направление «научные исследования» будет иметь важное значение для успеха двух других направлений Глобальной стратегии борьбы с ТБ после 2015 года и для достижения глобальных целей, запланированных на период после 2015 года. Биомедицинские исследования необходимо будет интегрировать в качестве важнейшего компонента новой исследовательской стратегии после 2015 года. Создание связей между научными дисциплинами, которые исторически отсутствовали или были неадекватными (например, медико-биологические исследования, эпидемиологические и оперативные исследования), будет зависеть от тесного сотрудничества, обсуждений и вклада многих сторон, заинтересованных в развитии науки и здравоохранения. Необходимость проведения прикладных научных исследований в расширенном формате для оптимизации внедрения и адаптации инноваций потребует больших усилий на национальном уровне, например для сбора необходимых данных об эпидемиологии ТБ («Знай свою эпидемию»), всеобщего доступа к медицинской помощи и адаптации глобальных рекомендаций на национальном уровне.

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Приложение 1

Методы, используемые для оценки глобального бремени туберкулеза

Данное приложение содержит описание методов, которые использовались для проведения оценки глобального бремени туберкулеза (ТБ) (определяется показателями заболеваемости, распространенности и смертности). Оно состоит из девяти основных разделов: •• Общие положения. Этот раздел содержит некоторую справочную информацию о методах, используемых для проведения оценки бремени болезни. •• Определения. В этом разделе даются определения следующих показателей ТБ: заболеваемость, распространенность, смертность от ТБ, летальность, выявляемость туберкулеза (уровень выявления случаев — CDR). В нем также содержится описание регионов, в которых была проведена оценка бремени болезни, и источников информации по оценке численности населения. •• Оценочные показатели смертности от ТБ, 1990– 2012 годы. Этот раздел содержит описание трех методов, используемых для оценки смертности от ТБ, и перечень стран, в которых они были применены. Также описаны методы оценки количества случаев смерти от туберкулеза, сочетанного с ВИЧ-инфекцией с разбивкой по возрасту и полу. •• Оценочные показатели заболеваемости ТБ, 1990– 2012 годы. В этом разделе разъясняются основные методы, используемые для оценки заболеваемости ТБ, и содержится перечень стран, в которых они были применены. Описаны методы оценки распространенности ВИЧ-инфекции среди больных ТБ. •• Оценочные показатели распространенности ТБ, 1990–2012 годы. Этот раздел содержит пояснение двух методов, используемых для оценки распространенности ТБ, и перечень стран, для которых они были применены. •• Оценочные показатели заболеваемости и смертности от ТБ с множественной лекарственной устойчивостью (МЛУ-ТБ). В этом разделе рассмотрены основные методы, используемые для оценки заболеваемости и смертности от МЛУ-ТБ, основанные на данных эпиднадзора за случаями лекарственно устойчивого ТБ и параметрах, полученных из недавно проведенного обзора литературы. •• Прогнозы заболеваемости, распространенности и  смертности от ТБ. В этом разделе содержится описание методов, примененных для прогнозирования на 2013–2015 годы. •• Общие методы оценки неопределенности. В этом разделе представлен подход к определению интервалов неопределенности в оценках всех показателей.

параметров, основанные на данных систематических обзоров, гораздо более широкое использование данных о смертности, получаемых от систем записей актов гражданского состояния (ЗАГС), и систематическое документирование неопределенности (в настоящем докладе интервалы неопределенности рассчитаны для всех оценок бремени болезней).

2. Определения 2.1 Заболеваемость, распространенность, смертность, летальность, зарегистрированная заболеваемость Заболеваемость определяется как число впервые выявленных и повторных (рецидивов) случаев туберкулеза (все формы), развившихся в течение определенного года. Повторные случаи определяются как новый эпизод ТБ у лиц, которые ранее болели туберкулезом с бактериологическим подтверждением излечения и/или имеющим документальное заключение о завершении полного курса лечения (Вставка 3.1, Глава 3). Далее в настоящем Приложении случаи рецидива заболевания обозначаются как повторные случаи заболевания, поскольку этот термин является более применимым при пояснении оценки заболеваемости. Повторный случай заболевания может быть истинным рецидивом или новым случаем туберкулеза, вызванного реинфекцией. В соответствии с действующими определениями случая ТБ, как рецидивы, так и случаи, взятые на повторное лечение (когда требуется внести изменения в лечение), называются «случаями, взятыми на повторное лечение». Однако больные, взятые для повторного курса в рамках продолжающегося эпизода заболевания, учитываются как случаи, относящиеся к распространенности болезни, а не к заболеваемости. Распространенность определяется как число всех случаев заболевания ТБ (все формы) на данный момент времени. Смертность от туберкулеза определяется как число случаев смерти, вызванных ТБ у ВИЧ-отрицательных людей согласно последней редакции Международной классификации болезней (МКБ-10). В МКБ-10 случаи смерти от ТБ среди больных ВИЧ-инфекцией классифицируются как случаи смерти от ВИЧ-инфекции. По этой причине оценочный показатель смертности от туберкулеза больных ВИЧ-инфекцией и данный показатель среди ВИЧ-отрицательных больных представляются раздельно. Летальность от ТБ — это риск смерти от туберкулеза среди всех больных активной формой туберкулеза 4. Зарегистрированная заболеваемость отражает частоту впервые выявленных и повторных эпизодов ТБ, информация о которых поступает в ВОЗ за определенный год, и этот показатель рассчитывается на 100 000 населения. Зарегистрированная заболеваемость впервые выявленным и повторным ТБ имеет важное значение для оценки истинной заболеваемости ТБ. В некоторых странах информация об истории лечения некоторых пациентов может отсутствовать, и тогда повторные эпизоды заболевания невозможно отличить от других случаев повторного лечения, так как все эти случаи регистрируются как случаи TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper, no. 2; WHO/HTM/TB/2009.416): www.who.int/tb/advisory_bodies/ impact_measurement_taskforce 2 Более подробную информацию можно получить на сай те Целевой группы: www.who.int/tb/advisory_bodies/impact_ measurement_taskforce 3 Например, некоторые параметры в настоящее время рассчитываются только на глобальном уровне или на уровне регионов, а не отдельно по каждой стране. 4 Straetemans M et al. Assessing tuberculosis case fatality ratio: a metaanalysis. PLoS One. 2011, 6(6):e20755. 1

1.

Общие положения

Ежегодно ВОЗ проводит оценку бремени туберкулеза (выраженного в показателях заболеваемости, распространенности и смертности) на основе данных эпиднадзора (регистрируемая заболеваемость и смертность), специальных исследований (включая исследования по изучению распространенности болезни, исследования по изучению причин смерти и углубленный анализ данных эпиднадзора), мнений экспертов и консультаций с представителями стран. Недавно опубликованы два современных руководства по методике оценки заболеваемости, распространенности и смертности от ТБ 1, основанные на работе Глобальной целевой рабочей группы ВОЗ по оценке воздействия ТБ 2. Методы, используемые для оценки бремени болезни, были обновлены в 2009 году после 18 месяцев работы группы экспертов, созванной Целевой группой. Эти изменения были одобрены на заседании Целевой группы, собранной в полном составе, в марте 2010 года. Усовершенствованная методика включает систематическое документирование экспертных оценок и изложение того, как эта информация используется для оценки бремени болезни, упрощения моделей 3, обновления значений

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повторного лечения «retreatment cases». Пациенты, ранее учитываемые как «история заболевания неизвестна», теперь должны регистрироваться как новый эпизод заболевания (новый случай или рецидив ТБ). Этот способ учета отличается от ранее используемой методики, в рамках которой трудно было определить долю истинно новых случаев ТБ и рецидивов в данной категории больных (ранее пациенты с неизвестной историей болезни не учитывались, ни как новые случаи, ни как рецидивы). Это изменение влияет на относительно небольшое число стран, главным образом, на страны Западной Европы. 2.2 Регионы Региональный анализ, как правило, проводился для шести регионов ВОЗ (Африка, Америка, Восточное Средиземноморье, Европейский регион, Юго-Восточная Азия и регион Западной части Тихого океана). Для проведения исследований, связанных с МЛУТБ, а также для расчетов по экологической модели, использовавшейся для оценки смертности от ТБ в некоторых странах, были выделены девять эпидемиологических регионов. Это африканские страны с высокой распространенностью ВИЧ-инфекции, африканские страны с низкой распространенностью ВИЧ-инфекции, страны Центральной Европы, страны Восточной Европы, страны с высоким уровнем доходов 1, Латинская Америка, регион Восточного Средиземноморья (за исключением стран с высоким уровнем доходов), Юго-Восточная Азия (за исключением стран с высоким уровнем доходов) и регион Западной части Тихого Океана (за исключением стран с высоким уровнем доходов). Страны в этих девяти регионах перечислены в Дополнении 1. 2.3 Оценочная численность населения

3.1 Оценочные показатели смертности от туберкулеза среди ВИЧ-отрицательных лиц, основанные на данных систем ЗАГС и специальных исследований по смертности Ежегодно данные из систем ЗАГС сообщаются государствами-членами и территориями в ВОЗ. В странах с функционирующими системами ЗАГС, в которых причины смерти кодируются в соответствии с двумя последними редакциями Международной классификации болезней (первоначальная причина смерти по МКБ-10: A15-A19, что соответствует в МКБ-9: 010–018), данные ЗАГС являются лучшим источником информации о смертности от туберкулеза среди ВИЧ-неинфицированных лиц. В случаях смерти от ТБ больных ВИЧ-инфекцией на стадии вторичных заболеваний (СПИД), ВИЧ-инфекция указывается как первопричина смерти, а туберкулез регистрируется в качестве дополнительной причины. Поскольку треть всех стран, имеющих системы ЗАГС, информирует ВОЗ только о первоначальных причинах смерти, а не о дополнительных, данные ЗАГС обычно нельзя использовать для оценки числа случаев смерти от ТБ среди ВИЧ-инфицированных больных. Данные о  смертности от ТБ, полученные через системы ЗАГС, важны для понимания тенденций в бремени ТБ в странах с неполной регистрацией случаев заболевания или в странах, где ситуация с достоверностью регистрируемой заболеваемости не изучена с помощью специальных исследований полноты регистрации случаев заболевания туберкулезом. С обновленным описанием глобального охвата и качества данных систем ЗАГС можно ознакомиться в сборнике Мировая статистика здравоохранения за 2013 год 3. По состоянию на май 2013 года, из 217 стран и территорий, которые получили запрос на предоставление информации, 125 стран представили в ВОЗ данные о смертности (включая данные систем ЗАГС по выборке территорий и данные специальных исследований по изучению причин смерти). В число этих 125 стран входят 9 из 22 стран с высоким бременем ТБ (СВБ): Бразилия, Вьетнам, Зимбабве, Индия, Китай, Российская Федерация, Таиланд, Филиппины и Южно-Африканская Республика. Тем не менее, данные систем ЗАГС о смертности от ТБ из Зимбабве и Южно-Африканской Республики не использовались для настоящего доклада потому, что значительное число случаев смерти от ВИЧ-инфекции было неправильно закодировано как случаи смерти от ТБ. Недавно была опубликована улучшенная процедура эмпирической корректировки причин смерти 4, и Глобальная целевая группа ВОЗ по измерению воздействия ТБ в 2014 году более детально пересмотрит опции для специфической ретроспективной корректировки ошибок классификации при измерении смертности от ТБ. В показателях по странам, по которым были данные систем ЗАГС (см. Рисунок 2.11 в  Главе 2), имелось 2087 точек данных «страна-год» за период 1990–2012 годы. Из этих точек данных для проведения анализа были исключены 24 точки, являющиеся выбросами, или полученными из систем ЗАГС с очень низким уровнем охвата. Выбросы были обнаружены визуально путем построения графиков динамики показателей зарегистрированной смертности от ТБ в каждой стране. По состоянию на июнь 2013 года, 62 точки данных были доступны за 2010 год, 35 — за 2011 год, и ни одной за 2012 год. В среднем, из отобранных для анализа точек данных, на одну страну пришлось 16 (стандартное отклонение (SD) равно 6,7). 1

Источником оценочных данных по численности населения, необходимых для расчета показателей ТБ, стал Доклад Отдела народонаселения ООН за 2012 год World Population Prospects (Прогнозы народонаселения мира) 2. Оценки Отдела народонаселения ООН иногда расходятся с оценками, проводимыми самими странами.

3.  Оценочные показатели смертности от туберкулеза, 1990–2012 годы Лучшими источниками данных о  числе случаев смерти от туберкулеза (за исключением случаев смертей среди больных ВИЧ-инфекцией) являются системы записей актов гражданского состояния (ЗАГС), в которых причины смерти кодируются в соответствии с МКБ-10 (хотя в нескольких странах до сих пор используются предыдущие версии — МКБ-9 и МКБ-8). Случаи смерти от туберкулеза у больных ВИЧ-инфекцией кодируются в соответствии с кодами, предусмотренными для ВИЧ-инфекции. Для оценки смертности от ТБ среди ВИЧ-отрицательных лиц были использованы три метода: •• прямые методы измерения на основе данных о причинах смерти из системы ЗАГС или специальных исследований по смертности; •• косвенные оценки, рассчитанные на основе экологической модели, с использованием данных из систем ЗАГС; •• косвенные оценки, полученные как произведение оценочного показателя заболеваемости ТБ и оценочного показателя летальности. Каждый метод описан более подробно ниже. Подробнее о методах, используемых для каждой страны, можно узнать на сайте: www.who.int/tb/publications/global_report/gtbr13_ mortality_source.csv.

Страны с высоким уровнем доходов приводятся по классификации Всемирного Банка как страны с уровнем доходов на душу населения (GNI) ≥US$ 12 616 в 2012 году. 2 http://esa.un.org/unpd/wpp/ (доступно с июня 2013 года). 3 http://www.who.int/gho/publications/world_health_statistics/2013/ru/ (доступно с июля 2013 года) (обратите особое внимание на стр.15–16). 4 Birnbaum JK, Murray CJL, Lozano R. Exposing misclassified HIV/AIDS deaths in South Africa. Bulletin of the World Health Organization, 2011, 89:278–285.

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Отчеты о смертности от ТБ были скорректированы в сторону повышения для учета неполного охвата регистрацией случаев смерти (оценочное число случаев смерти без документального указания причины) и неточно обозначенных причин смерти (МКБ-9 код B46, МКБ-10 коды R00–R99) 1. Было сделано допущение, что доля случаев смерти от ТБ среди всех случаев смерти, не зарегистрированных системой ЗАГС, была такой же, как доля случаев смерти от ТБ среди всех случаев смерти, зарегистрированных системой ЗАГС. Было также сделано допущение, что доля случаев смерти от ТБ среди случаев смерти с неточно обозначенными причинами была такой же, как среди всех правильно зарегистрированных системой ЗАГС случаев смерти. Скорректированное число смертей от ТБ da было получено из числа зарегистрированных системой ЗАГС случаев смерти d следующим образом: d da = c(1 – g) где c обозначает охват регистрацией случаев смерти (т. е. отношение числа смертей с документально зарегистрированной причиной к оценочному показателю общего числа смертей) и g обозначает долю неточно обозначенных причин смерти. Неопределенность, связанная с данной корректировкой, оценивалась со стандартным отклонением SD = d/4[1/c(1 – g) – 1]. При таком расчете неопределенности не учитывается неправильная кодировка причин смерти, такая, например, как случай смерти от ВИЧ-инфекции, закодированная как смерть от туберкулеза. Отсутствующие значения показателей между имеющимися скорректированными точками данных были интерполированы. Конечные отсутствующие значения были спрогнозированы с помощью модели экспоненциального сглаживания для временных ́ рядов 2. При выборе модели для каждой отдельной страны применялся метод правдоподобия с использованием штрафных функций, основанный на настройке моделей на имеющуюся выборку данных. Начальные недостающие значения аналогичным образом оценивались ретроспективно до 1990 года. Таким образом были сформированы в общей сложности 799 точек данных «страна-год». Для оценки смертности от туберкулеза во Вьетнаме и Индии были использованы результаты специальных исследований по изучению причин смерти. В 2012 году 45% от общего числа случаев смерти от туберкулеза в мире (за исключением случаев в сочетании с ВИЧ-инфекцией) были определены непосредственно по данным систем ЗАГС, или по данным специальных исследований (или сформированы на основе таких данных за предыдущие годы). Остальные 55% случаев оценивались с использованием косвенных методов, описанных в Разделе 3.2 и Разделе 3.3. 3.2 Оценочные показатели смертности от туберкулеза ВИЧ-отрицательных лиц по экологической модели С целью подбора экологической модели, позволяющей прогнозировать смертность от ТБ в странах, не имеющих системы ЗАГС, в 2012 году был применен метод пошагового отбора на основе качества настройки моделей с разделением обучающей и контрольной выборок; при этом использовались данные за 1990–2011 годы. Модель была основана на временных ́ рядах данных ЗАГС, представленных в ВОЗ как описано выше, выраженных как число случаев смерти от ТБ, скорректированное на долю неточно обозначенных причин и охват системой ЗАГС. Для описания продольной структуры данных, а также высокой вариативности количества случаев смерти от ТБ использовалась усредненная по популяции отрицательная биномиальная модель со смещением на размер популяции, в результате чего модель выдавала удельные значения. Были проанализированы десять переменных с целью их включения в модель: показатель младенческой смертности

на 1 000 живорождений; валовой внутренний продукт на душу населения; показатель распространенности ВИЧ-инфекции среди населения в целом; доля населения в возрасте до 15 лет и с 65 лет и старше; доля успешного лечения туберкулеза; общее число впервые зарегистрированных случаев ТБ в год; высокое или низкое бремя МЛУ-ТБ в стране; принадлежность к числу 22 стран с высоким бременем ТБ (СВБ); а также принадлежность страны к одной из девяти категорий стран со сходным типом эпидемической ситуации по туберкулезу (см. Дополнение 1). При одномерном анализе все факторы риска были связаны с показателем смертности от ТБ в качестве исхода. В окончательную многомерную модель были включены показатель младенческой смертности на 1000 живорождений, показатель распространенности ВИЧ-инфекции среди населения в целом, валовой внутренний продукт на душу населения, доля населения в возрасте до 15 и с 65 лет и старше, принадлежность к числу 22 стран с высоким бременем ТБ, а также принадлежность страны к одной из девяти категорий стран со сходным типом эпидемической ситуации по туберкулезу. Из общего количества в  4 686 точек данных по странам и годам за период с 1990 по 2011 годы, 802 точки невозможно было предсказать из-за того, что данные были недоступны ни для одной из десяти включенных в модель переменных. Оценочные показатели смертности от ТБ, предсказанные с помощью модели, были использованы для 26 стран 3, в которых не было данных ЗАГС или данных специальных исследований по изучению причин смерти достаточного качества и охвата, или для которых оценочные показатели заболеваемости туберкулезом были признаны слишком неопределенными. 3.3 Оценочные показатели смертности от туберкулеза среди ВИЧ-отрицательных лиц, полученные на основе оценочных показателей летальности и заболеваемости туберкулезом В 68 странах, где отсутствуют данные ЗАГС с надлежащим охватом и качеством (в целом по 94 странам имеется недостаток данных ЗАГС надлежащего охвата и качества, но в 26 из них была использована описанная выше экологическая модель), смертность от ТБ была рассчитана как произведение показателя заболеваемости ТБ (см. Раздел 4) и показателя летальности с использованием модели, разработанной в 2012 году. Показатель летальности оценивался отдельно для зарегистрированных и незарегистрированных системой эпиднадзора НПТ случаев, и в каждой из этих двух групп отдельные оценки были сделаны для стран с высоким уровнем доходов и для остальных стран (Таблица A1.1). Таблица A1.1 Оценки уровня летальности от туберкулеза (для ВИЧотрицательных больных) по типам случаев и группам стран Тип случая и группа стран Среднее значение (Стандартное отклонение)

Не зарегистрированные: страны с высоким уровнем доходов Не зарегистрированные: остальные страны Зарегистрированные: страны с высоким уровнем доходов Зарегистрированные: остальные страны

0,12 (0,042) 0,32 (0,13) 0,039 (0,042) 0,074 (0,03)

1

Mathers CD et al. Counting the dead and what they died from: an assessment of the global status of cause of death data. Bulletin of the World Health Organization, 2005, 83:171–177. 2 Hyndman R et al. Forecasting with exponential smoothing: the state space approach. Springer Series in Statistics, 2008. 3 Список 26 стран см. по адресу: www.who.int/tb/publications/global_ report/gtbr13_ mortality_source.csv.

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Для обеспечения согласованности с данными ЗАГС и специальных исследований по изучению причин смерти, показатели летальности оценивались так, чтобы обеспечить максимальное соответствие показателям смертности от ТБ, полученным с использованием прямых методов на основе данных ЗАГС или данных специальных исследований по изучению причин смерти (в пределах их диапазона неопределенности) в 123 странах, а также оценочным значениям показателей заболеваемости ТБ по оценке ВОЗ. Эта статистическая настройка использовала байесовские линейные модели и проводилась отдельно по двум группам стран (страны с высоким уровнем доходов и все остальные страны) для учета различий в соотношении показателя зарегистрированной смертности от ТБ к показателю зарегистрированной заболеваемости ТБ среди этих двух групп стран (данные не показаны). Для построения модели применялись нормальные ошибки и формирование выборки по Гиббсу: y = ( I – N ) β1 + N β2 + e, e ~ N (0, σ2) где y — показатель смертности от ТБ по данным систем ЗАГС, I обозначает заболеваемость ТБ, исключая больных ВИЧ-инфекцией, N обозначает зарегистрированную заболеваемость ТБ, за исключением случаев у больных ВИЧ-инфекцией, а параметры β1 и β2 обозначают показатель летальности в группах не зарегистрированных и зарегистрированных случаев туберкулеза соответственно. Псевдо-сопряженные априорные распределения величин были заданы неинформативным обратным гамма-распределением в качестве априорного условного распределения вариации ошибки: b ~ N ( b i , B i -2), σ2 ~ IG (5.10 -4 ,5.10 -4) Для стран с низким и средним уровнем доходов априорные величины b и их точность B были определены на основе обзоров литературы 1 и показателей летальности по странам и годам, используемых ВОЗ для периода с 1999 по 2008 годы. Для стран с высоким уровнем доходов были использованы неинформативные априорные распределения величин. Сходимость марковских цепей была оценена графически и с использованием диагностических тестов сходимости. В каждой категории оценочные показатели смертности за 1990–2011 годы были вычислены как произведение апостериорных распределений показателя летальности (с допущением, что они со временем не меняются (Таблица A1.1)) и распределения оценочного показателя заболеваемости для соответствующей страны и года. 3.4 Оценочные показатели смертности от туберкулеза, сочетанного с ВИЧ-инфекцией На момент написания данного доклада не было доступно общенациональных репрезентативных данных по смертности от ТБ, сочетанного с ВИЧ-инфекцией, из систем ЗАГС ни для одной из стран. В связи с отсутствием данных прямых измерений смертность от ТБ, сочетанного с ВИЧ-инфекцией, была оценена косвенно с использованием нижеописанных методов (см. также Раздел 4.5), реализованных в программном обеспечении Spectrum softwarе 2. Показатель смертности от ТБ рассчитывается как произведение заболеваемости туберкулезом, сочетанным с ВИЧ-инфекцией (см. Раздел 4.5) и показателей летальности: M = (I-N)Fu + NFn где I — число случаев заболевания ТБ, сочетанным с ВИЧ-инфекцией, N — число зарегистрированных больных ТБ, сочетанным с ВИЧ-инфекцией, (I-N) — число не зарегистрированных больных ТБ, сочетанным с ВИЧ-инфекцией и  M — смертность от ТБ, сочетанного с ВИЧ-инфекцией; Fn и  Fu — коэффициенты летальности для зарегистрированных и не зарегистрированных случаев заболевания соответственно. 104

Таблица A1.2 Оценочные коэффициенты летальности среди больных туберкулезом, сочетанным с ВИЧ-инфекцией Не зарегистрированные Зарегистрированные

ВИЧ-отрицательные Мода треугольного распределения ВИЧ-положительные, не получающие АРТ Мода треугольного распределения Больные, получающие АРТ менее одного года Мода треугольного распределения Больные, получающие АРТ более одного года Мода треугольного распределения

0,43 0,78 0,62 0,49

0,03 0,09 0,06 0,04

Коэффициенты летальности были получены в сотрудничестве с Консорциумом моделирования и анализа эпидемиологии туберкулеза (TB-MAC) 3,4,5, и показаны в Таблице A1.2. Разбивка данных по заболеваемости ТБ на зарегистрированные и не зарегистрированные случаи основана на соотношении точечной оценки истинного числа случаев заболевания и числа зарегистрированных случаев. Один и тот же показатель летальности использовался для расчета всех оценочных показателей смертности методом бутстрэп (bootstrap). Необходимо срочно получить оценочные показатели смертности от ТБ, сочетанного с ВИЧ-инфекцией, с использованием прямых методов измерения. Это в особенности касается таких стран, как Зимбабве и Южно-Африканская Республика, где уже созданы национальные системы ЗАГС. В других странах необходимо приложить дополнительные усилия, чтобы обеспечить выборочный сбор данных ЗАГС в качестве временной меры. 3.5 Показатель смертности от туберкулеза с разбивкой по возрасту и полу Для стран, где существуют данные ЗАГС, есть возможность рассчитать число случаев смерти от ТБ (за исключением случаев среди больных ВИЧ-инфекцией отдельно в группе детей (до 15 лет) и взрослых (15 лет и старше), а также дезагрегировать случаи смерти от ТБ по полу. Для этих стран были рассчитаны половозрастные коэффициенты смертности от ТБ мужчины: женщины и дети:взрослые (выраженные как показатели на 100 000 населения) с поправкой на неправильно определенные причины смерти и охват населения системой ЗАГС. Экологическая модель, описанная в  Разделе 3.2, была использована для прогнозирования коэффициентов для стран без данных системы ЗАГС. Коэффициенты, полученные на основании данных, измеренных напрямую (т. е. на основе данных ЗАГС за последний доступный год), и спрогнозированные коэффициенты для отдельных стран были затем использованы для расчета коэффициентов для регионов ВОЗ. Далее они использовались для оценки глобального коэффициента, который, в свою очередь, был применен для расчета глобального числа случаев смерти от ТБ среди ВИЧ-отрицательных больных ТБ, что дало возможность

1 2 3

4

5

Straetemans M et al. Assessing tuberculosis case fatality ratio: a metaanalysis. PLoS One. 2011, 6(6):e20755. http://www.futuresinstitute.org/spectrum.aspx Tiemersma EW, van der Werf MJ, Borgdorff MW, Williams BG, Nagelkerke NJ (2011) Natural history of tuberculosis: duration and fatality of untreated pulmonary tuberculosis in HIV negative patients: a systematic review. PLoS One 6: e17601. Corbett EL, Watt CJ, Walker N, Maher D, Williams BG, et al. (2003) The growing burden of tuberculosis: global trends and interactions with the HIV epidemic. Archives of Internal Medicine; 163: 1009–1021. Mukadi YD, Maher D, Harries A (2001) Tuberculosis case fatality rates in high HIV prevalence populations in sub-Saharan Africa. AIDS; 15: 143–152.

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провести стратификацию полученных оценочных значений по полу и возрасту. Случаи смерти от ТБ, сочетанного с ВИЧ-инфекцией были стратифицированы по полу, основываясь на допущении того, что соотношение мужчины: женщины такое же, как среди умерших от СПИДа по оценкам ЮНЭЙДС. Дополнительная информация представлена во Вставке 2.2, Глава 2 . Одним из следующих шагов в разработке компонента ТБ в программном обеспечении Spectrum software будет обеспечение возможности стратифицировать случаи смерти от ТБ, сочетанного с ВИЧ-инфекцией по возрасту и полу (см. также Раздел 3.4).

4. Оценочные показатели заболеваемости туберкулезом, 1990–2012 годы Ни в одной стране мира не предпринимались попытки провести общенациональное исследование по изучению заболеваемости ТБ из-за необходимости охвата обследованием больших контингентов населения и связанных с этим значительных материально-технических и финансовых проблем. В результате не существует информации об истинной заболеваемости туберкулезом, полученной с помощью прямых методов измерения. Теоретически, данные из системы эпиднадзора за ТБ тех стран, где обеспечен высокий охват и качество медицинской помощи, могут охватывать регистрацию всех (или почти всех) случаев заболевания ТБ. Глобальная целевая группа ВОЗ по измерению воздействия ТБ разработала ряд стандартов эпиднадзора за ТБ и критериев, внедрение которых позволяет осуществлять прямое измерение случаев заболевания и смерти от ТБ на основе данных эпиднадзора (Глава 2). В отсутствие возможности использования прямых методов оценки заболеваемости ТБ, этот показатель почти для всех стран мира рассчитывается с помощью методов, описанных в Разделах 4.1–4.3. Следует подчеркнуть, что более не применяется оценка заболеваемости ТБ на основе данных специальных исследований по изучению распространенности инфицирования возбудителем туберкулеза с применением туберкулино-диагностики. Глобальная целевая группа ВОЗ по измерению воздействия ТБ пришла к соглашению, что методы расчета заболеваемости, основанные на распространенности инфекции, являются ненадежными. Целевая группа также констатировала, что, за несколькими исключениями, повторные обследования с помощью туберкулиновых проб не позволили достоверно оценить тенденции в заболеваемости туберкулезом 1. 4.1 Оценка заболеваемости туберкулезом на основе показателей доли выявленных случаев В ходе шести региональных семинаров и визитов в страны за период с 2009 по 2013 годы был проведен анализ данных о регистрации новых случаев и повторных эпизодов заболевания в соответствии с методикой, разработанной Глобальной целевой группой по оценке воздействия ТБ, а также с учетом информации об охвате системой эпиднадзора за ТБ, и мнений специалистов. К маю 2013 года подобные семинары и визиты прошли в 96 странах (Рисунок 2.1, Глава 2), причем в некоторых странах оценки проводились неоднократно. Для 96 стран, изученных в ходе этих региональных семинаров и страновых визитов, заболеваемость была оценена по следующей формуле: зарегистрированные случаи заболеваемость = 1 – незарегистрированные случаи

годам (1997, 2003 и, в зависимости от того, когда был проведен семинар, 2008–2012). Это было сделано после углубленного анализа данных по зарегистрированной заболеваемости (включая данные на субнациональном административном уровне), данных о национальных туберкулезных программах, касающихся организации противотуберкулезных мероприятий (например, данные об инфраструктуре, кадровом обеспечении, эффективности работы и финансировании) и (при наличии) данных исследований по изучению полноты регистрации 3. Кроме того, данные о доступе к медико-санитарной помощи, полученные из демографических исследований и исследований по организации здравоохранения, а также общие данные по эффективности работы систем здравоохранения (используя такие показатели, как коэффициент младенческой смертности) были использованы для обоснования оценки доли населения, не имеющего доступа или имеющего очень ограниченный доступ к медицинской помощи (Таблица А1.3). Результаты специальных исследований по изучению полноты регистрации больных ТБ в сочетании с моделированием на основе первичного и повторного обследования определенной выборки (сapture-recapture modeling) использовались для оценки разницы между истинной и регистрируемой заболеваемостью в трех странах, представители которых участвовали в региональных семинарах: Египет, Ирак и Йемен. Полное описание методов, использованных на этих семинарах, изложено в отчете о работе семинара, проведенного для стран региона Африки (в  г. Хараре, Зимбабве, декабрь 2010 года) 4. Таблица A1.3 Источники информации и данные о заболеваемости, использованные на региональных семинарах и в ходе визитов в страны Возможные категории случаев заболевания Источники данных

Отсутствие физического и финансового доступа к медицинской помощи Обращался за помощью, но ТБ не был диагностирован Случай ТБ диагностирован, но не зарегистрирован Зарегистрированные случаи a

Демографические исследования, исследования по оценке систем здравоохранения, исследования KABP a Специальные исследования

Моделирование на основе первичной и повторной выборки

Специальные исследования по изучению полноты регистрации случаев Эпиднадзор за ТБ

KABP (knowledge, attitudes, behaviour and practices) = знание, отношение, поведение и привычки.

Предполагалось, что распределение доли случаев, которые не были зарегистрированы в трех опорных годах является бета-распределением ( Таблица А1.4). Существуют следующие причины использования бета-распределений:

Экспертная оценка доли случаев туберкулеза 2, которые не были зарегистрированы, была установлена по трем опорным

TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper, no. 2; WHO/HTM/TB/2009.416). 2 Определяются как случаи всех форм туберкулеза, включая случаи туберкулеза легких с положительным мазком мокроты, случаи туберкулеза легких с отрицательным мазком мокроты и случаи внелегочного туберкулеза. 3 Данные, полученные в результате специальных исследований по изучению числа случаев, которые были диагностированы, но не были зарегистрированы в национальной системе эпиднадзора. 4 См.  www.who.int/tb/advisory_bodies/impact_measurement_taskforce 1

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•• Они являются непрерывными и определены на интервале (0, 1). Поскольку дисперсия доли незарегистрированных случаев, как правило, бывает значительной в результате высокой неопределенности, значения случайной величины при нормальном распределении будут давать значения вне интервала (0, 1). Использование усеченного нормального распределения может привести к избыточной плотности ближе к одной из границ. •• Они необязательно симметричны. •• Они определяются двумя параметрами, которые могут быть оценены из имеющихся данных, с помощью метода моментов 1. Параметры формы и масштаба, необходимые для определения бета-распределения, были рассчитаны с использованием метода моментов следующим образом: Во-первых, дисперсия распределения была рассчитана следующим образом: V = ((u – l )/4)2 где l и u есть нижняя и верхняя границы правдоподобного диапазона для доли зарегистрированных случаев (который назван долей выявленных случаев в Главе 3). Формы 1 (обозначенная как α) и 2 (обозначенная как β) рассчитываются из: E(l – E ) V α = sE s= β = s(l – E ) где E — математическое ожидание распределения. Временные ́ ряды за период 1990–2012 годы были построены в соответствии с данными о неполной регистрации и гиподиагностики, которые были оценены для трех опорных лет. Экстраполяция V и  E с помощью кубического сплайна с узлами в опорных годах была использована для стран с низким уровнем распространения или концентрированной эпидемией ВИЧ-инфекции. В странах с генерализованной эпидемией ВИЧ-инфекции траектория заболеваемости с 1990 года и до первого рассматриваемого года (как правило, 1997 год) основывалась на данных о ежегодных темпах роста распространенности ВИЧ-инфекции. Траектории заболеваемости были получены с использованием рядов данных о зарегистрированной заболеваемости с помощью имитационного моделирования методом Монте-Карло, в результате были получены данные по ожидаемым значениям и 2,5%-е и 97,5%-е квантили. Все вычисления проводились в статистической среде R 2. Для двух стран показатели заболеваемости были оценены на уровне соседних стран, потому что информации, полученной из систем эпиднадзора, было недостаточно: для Западного берега реки Иордан и сектора Газа оценки были экстраполированы из оценок для Иордании, а для Южного Судана — из оценок для Судана. Поэтому оценки для Западного берега реки Иордан и сектора Газа, а также Южного Судана должны рассматриваться как предварительные. Тенденции в заболеваемости были рассчитаны на основе данных повторных туберкулиновых исследований в Бутане, Индии и Йемене, а для 40 стран (включая страны Восточной Европы) — на основе тенденций показателей смертности. Если было недостаточно данных для определения факторов, ведущих к изменению во времени зарегистрированной заболеваемости, предполагалось, что в последней со времени последней оценки поддерживается горизонтальный тренд. –l

4.2 Оценочный показатель заболеваемости туберкулезом для стран с высоким уровнем доходов на основании данных о зарегистрированной заболеваемости и экспертных заключений По мнению экспертов, для стран с высоким уровнем доходов показатель заболеваемости распределялся между показателем зарегистрированной заболеваемости (новые и повторные эпизоды заболевания, а также случаи заболевания с неизвестной историей болезни, как описано в  Разделе 2.1) (нижний предел неопределенности обозначается как l ) и зарегистрированной заболеваемостью, умноженной на 1,3 (верхний предел неопределенности обозначается как u). Предполагается, что заболеваемость имеет бета-распределение; параметры формы и масштаб которого, вычисляются с помощью метода моментов, как описано выше. В отсутствие данных по конкретным странам о качестве и охвате системой эпиднадзора за ТБ предполагалось, что системы эпиднадзора за ТБ стран с высоким уровнем доходов функционируют одинаково хорошо, хотя модель допускает возможность стохастических колебаний. Исключение составили Великобритания и Нидерланды, где доля незарегистрированных случаев ТБ была определена путем проведения специального исследования по изучению полноты регистрации случаев ТБ и моделирования на основе данных первичного и повторного обследования определенной выборки 3,4. Результаты данных исследований в этих двух странах были использованы для прямого измерения заболеваемости. 4.3 Оценка заболеваемости туберкулезом на основании эмпирического измерения распространенности болезни Заболеваемость может быть оценена с помощью данных специальных общенациональных исследований по изучению распространенности ТБ в сочетании с оценкой продолжительности болезни. Уровень заболеваемости оценивается как частное от деления показателя распространенности туберкулеза на среднюю продолжительность болезни. На практике продолжительность болезни невозможно измерить с помощью прямых методов. Например, измерение продолжительности симптомов у больных активным туберкулезом, выявленных в ходе специальных исследований по изучению распространенности заболевания, смещены в сторону более низких значений за счет систематической ошибки в результате того, что активное выявление случаев заболевания усекает естественное течение недиагностированного заболевания. Измерение продолжительности заболевания только у зарегистрированных больных не позволяет учесть продолжительность заболевания среди не зарегистрированных и не получивших лечения больных. Обзоры литературы, сделанные по заказу Глобальной целевой группы ВОЗ по измерению воздействия ТБ, дали оценки продолжительности заболевания нелеченых больных ТБ

1

Rényi A. Probability theory. New York, Dover Publications Inc., 2007. R Development Core Team. R: a language and environment for statistical computing. Vienna, R Foundation for Statistical Computing, 2009 (www.R-project.org). 3 Tuberculosis in the UK: annual report on tuberculosis surveillance in the UK 2010. London, Health Protection Agency Centre for Infections, 2010 (доступно на: www.hpa.org.uk/web/HPAweb&HPAwebStandard/ HPAweb_C/1287143581697; доступно с июля 2011 года). 4 van Hest NA et al. Completeness of notification of tuberculosis in The Netherlands: how reliable is record-linkage and capture–recapture analysis? Epidemiology and Infection, 2007, 135(6):1021–1029. 2

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Таблица A1.4 Оценки параметров, которые используются для расчетов оценочных показателей заболеваемости, распространенности и смертности от ТБ Параметр модели Распределение Параметры распределения b

Заболеваемость, страны с высоким уровнем доходов

бета a

α=Ī.

Ī (1– Ī ) –1 V

Ī (1– Ī ) –1 β = (1– Ī ) . V где Ī была установлена в 1,3 раза выше зарегистрированной заболеваемости, обозначенной как N, и где V рассчитывается по формуле: 2 0,3 V= 4 N Распространенность ВИЧ-инфекции среди новых случаев ТБ α=– x. – (1– x –) x –1 V

бета a

– – – ) . x (1– x ) – 1 β = (1– x V – представляет собой математическое ожидание, а V Где x рассчитывается по формуле: u–l 2 V= 4 l = 1, u = 4 (года)

Длительность заболевания, незарегистрированные ВИЧ-отрицательные случаи ТБ Длительность заболевания, незарегистрированные ВИЧ-положительные случаи ТБ Длительность заболевания, зарегистрированные ВИЧ-отрицательные случаи ТБ Длительность заболевания, зарегистрированные ВИЧ-положительные случаи ТБ a b

Равномерное

Равномерное

l = 0,01, u = 0,2 (года)

Равномерное

l = 0,2, u = 2 (года)

Равномерное

l = 0,01, u = 1 (год)

Функция плотности вероятности бета-распределения: u и l определяют верхнюю и нижнюю границы.

ƒ ( x; a, β) =

x a –1 (1– x) β –1 1 a –1 t 0

(1– t) β –1 dt

в доантибактериальную эру (до 1950-х годов). Наилучшая оценка средней продолжительности заболевания (суммарно для больных с положительным и отрицательным мазком) среди ВИЧ-отрицательных лиц составляет около трех лет. Однако доля новых случаев ТБ, которые остаются без лечения, неизвестна. Существует мало данных о продолжительности болезни у больных ВИЧ-инфекцией. При наличии данных двух исследований по изучению распространенности болезни, тенденции распространенности ТБ определялись путем настройки лог-линейной модели на имеющиеся данные. При наличии трех или более измерений распространенности, траектория распространенности строилась с использованием кубической сплайн-интерполяции. Если было доступно только одно измерение распространенности, временные ́ тенденции были оценены с помощью углубленного анализа данных эпиднадзора, как описано выше. В настоящем докладе метод оценки заболеваемости по распространенности был использован для двух стран: Лаосской Народно-Демократической Республики и Эфиопии. 4.4 Дезагрегация данных о заболеваемости ТБ В настоящем докладе данные о заболеваемости туберкулезом дезагрегированы по статусу ВИЧ-инфекции (см. Раздел 4.5) на национальном уровне. Оценка заболеваемости туберкулезом

с положительным мазком была прекращена в 2010 году по причинам, подробно изложенным в Глобальном докладе, опубликованном в 2010 году. Глобальные и региональные (в соответствии с делением на регионы ВОЗ) оценочные показатели истинной заболеваемости с дезагрегацией по полу были также рассчитаны в разрезе отдельных стран на основании соотношения женщины: мужчины среди всех новых зарегистрированных больных ТБ (все типы случаев), допуская, что последнее является приближением этого соотношения среди первой группы. Рассчитанные по модели соотношения по регионам ВОЗ коэффициенты были применены к показателю глобальной распространенности для окончательного разделения по полу (Глава 2). Данные о заболеваемости ТБ также были дезагрегированы по возрасту, что позволило рассчитать глобальные оценочные значения показателя заболеваемости среди детей (до 15 лет) и взрослых (от 15 лет и старше). Подробности метода расчетов приведены в Главе 2, Вставка 2.2. 4.5 Оценки распространенности ВИЧ-инфекции среди новых случаев заболевания туберкулезом, 1990–2012 годы Для дезагрегирования заболеваемости ТБ по ВИЧ-статусу и уровню CD4-лимфоцитов использовалось программное 107

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обеспечение Spectrum 1. В качестве исходных данных для модели ВИЧ-инфекции системы Spectrum использовались данные ВОЗ по истинной заболеваемости ТБ. Эта модель была настроена на данные ВОЗ по заболеваемости ТБ и затем использована для оценки заболеваемости ТБ среди больных ВИЧ-инфекцией с дезагрегацией по уровню CD4 2. При помощи регрессионного метода был оценен относительный риск заболеваемости ТБ при различном уровне CD4-лимфоцитов, который используется Spectrum для прогнозирования развития эпидемического процесса по ВИЧ-инфекции в общенациональном масштабе. Данные системы Spectrum были основаны на национальных прогнозах, подготовленных для Доклада ЮНЭЙДС о глобальной эпидемии СПИД, 2012. Модель также может использоваться для оценки смертности от ТБ, сочетанного с ВИЧ-инфекцией, потребности в ресурсах, необходимых для проведения лечения в соответствии с недавно обновленным руководством по АРТ 3, и результатов распространения АРТ. Гибкий и относительно простой способ моделирования заболеваемости ТБ (или любой функции, зависящей от времени) состоит в представлении ее как k зависящих от времени кубических сплайнов m-той степени: I(x) = Σi=1 to k βi Bmi(x) где βi - есть i-ый коэффициент сплайна, и  Bmi (x) представляет оценку i-ой базисной функции в момент времени (год) x. Порядок каждой базисной функции есть m и используются кубические сплайны, т. е. m = 3. Уравнение просто показывает, что любая зависимая от времени функция, такая как заболеваемость, может быть представлена в виде линейной комбинации базисных кубических сплайн-функций. Значения коэффициентов кубических сплайнов β были определены посредством оптимизационной процедуры, которая минимизирует наименьшие квадратические ошибки между данными по заболеваемости (Iobs) и кривой оценки распространенности I (x): Σx=1990:2012 |I(x) - Iobs(x)|2 + λ β T S β Здесь |I — Iobs|2 — это сумма квадратических ошибок оценки истинной заболеваемости и S — это матрица разностных штрафов, применяемая непосредственно к параметрам β для контроля за уровнем различия между соседними коэффициентами кубических сплайнов, чтобы таким образом контролировать (через выбор λ) гладкость кривой уровня заболеваемости по времени. Еще одной важной целью использования матрицы штрафов S является стремление регуляризировать (путем создания гладкости в зависимости между смежными параметрами) плохо обусловленную обратную задачу (наличие большего количества неизвестных параметров, чем могут определить имеющиеся данные), которая имеет тенденцию к сверхнастройке, если оставить ее плохо обусловленной. Кубические сплайны и доверительные интервалы Метод кубических сплайнов был использован для того, чтобы настроить показатели (заболеваемость, регистрируемая заболеваемость, и т. д .) на набор данных, полученных по методу бутстрэп из «точечных оценок» с нормальным распределением ошибок. Данный бутстрэп-метод дает набор кубических сплайн-кривых, который практически эквивалентен набору, который был бы получен при настройке модели на то же число повторных измерений (или оценок) данного индикатора. Доверительные интервалы, основанные на бутстрэп-данных, как правило, узки в тех годах, где имеются данные и «расходятся» после этого в соответствии с гауссовским процессом с растущей дисперсией.

Прогнозирование показателя истинной заболеваемости туберкулезом среди больных ВИЧинфекцией, в зависимости от уровня CD4-лимфоцитов Дезагрегирование показателя заболеваемости ТБ по уровню СD4 у больных ВИЧ-инфекцией было основано на предположении, что увеличение относительного риска заболевания ТБ является функцией снижения количества CD4. Williams с соавт. воплотили это предположение в модели взаимосвязи между относительным риском развития ТБ и снижением количества CD4 4. Они предложили следующее соотношение: снижение на каждые 100 CD4-лимфоцитов в мкл увеличивает относительный риск ТБ на 42% (+/-17%). Метод дезагрегации модели Spectrum-ТB основан на модели, разработанной Williams с соавт. Эта модель сначала оценивает заболеваемость среди больных ВИЧ-инфекцией, а затем вычисляет «риск развития ТБ» F=I- / P-, где I- — это заболеваемость ТБ среди больных ВИЧ-инфекцией, а  P- — это число больных ВИЧ-инфекцией, чувствительных к ТБ. Предполагается, что риск инфицирования ТБ среди больных ВИЧ-инфекцией, при количестве клеток CD4 > более 500 в 1 мкл пропорционален F (ранее предполагалось, что он был выше в 2,5 раза 5). Для каждого снижения CD4 на 100 клеток/мкл в остальных диапазонах (350–499, 250–349, 200–249, 100–199, 50–99 CD4 клеток/мкл и CD4 менее 50 клеток/мкл) риск инфицирования представлен следующим образом: F(c<500) = F(c>500)∙p(1)∙p(2)dc, где p(1) — это коэффициент, описывающий более высокий риск инфицирования возбудителем туберкулеза больных ВИЧ-инфекцией, с высоким уровнем CD4 по сравнению с ВИЧ-отрицательными людьми, а  p (2)  — параметр, контролирующий экспоненциальный рост ОР, который наблюдается при снижении количества CD4. dc — это число снижений уровня CD4 на 100 в 1 мкл, связанное с серединной точкой каждого диапазона CD4 относительно 500: dc= (3,0, 4,4, 8,6, 12,9, 19,2, 28,6, 37,3) для шести рассматриваемых категорий CD4. Снижение ОР применяется в отношении тех, кто получал АРТ более одного года. Определение значений параметров Для приведения в соответствие показателя общей заболеваемости ТБ с оценочным числом больных ТБ, сочетанным с ВИЧ-инфекцией, полученным на основании данных тестирования на ВИЧ-инфекцию, где они были доступны, было сделано предположение, что p(1) = 2,5, а  p(2) подбиралось соответствующим образом. В подходе, основанном на расчете относительного риска, следует уравновешивать «биологический смысл», присваиваемый параметрам, и более простую интерпретацию этих параметров как коэффициентов регрессии. Оба параметра могут быть подобраны или могут быть фиксированными. Изменение,

1

http://www.futuresinstitute.org/spectrum.aspx Stover J, McKinnon R, Winfrey B. Spectrum: a model platform for linking maternal and child survival interventions with AIDS, family planning and demographic projections. International Journal of Epidemiology 2010; 39 Suppl 1:i7–10. 3 http://www.who.int/hiv/pub/guidelines/arv2013/en/index.html 4 Williams B. The impact of ART for HIV on TB. http://www.who.int/hiv/ topics/artforprevention/williams.pdf (доступно с июля 2013 года). 5 Sonnenberg P, et al. How Soon after Infection with HIV Does the Risk of Tuberculosis Start to Increase? A Retrospective Cohort Study in South African Gold Miners. Journal of Infectious Diseases. 2005 Jan 15;191(2):150–8. 2

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по крайней мере, параметра p(2) описывает различия между странами, которые ожидаются в связи с различиями базового (среди ВИЧ-отрицательных пациентов) уровня CD4; такой подход обеспечивает баланс между биологическими механизмами и механизмами регрессии. Подход, основанный на использовании модели ОР для оценки показателя заболеваемости ТБ, был применен к группе больных, получающих АРТ. Несмотря на то, что оценка заболеваемости ТБ среди больных, получающих АРТ, может быть получена на основании данных статистического наблюдения, предоставляемых в ВОЗ (что ставит под вопрос необходимость использования модели ОР), недостатки данных по АРТ (в частности, некоторые страны, по-видимому, сообщают совокупное число больных, получающих АРТ) свидетельствуют в пользу необходимости применения ОР подхода. Было предположено, что отношение рисков (ОР) (hazard ratios) — составляет 0,35 для всех диапазонов CD4 на момент начала АРТ. Suthar AB с соавт. оценили ОР в 0,16, 0,35 и 0,43 для тех, кто получает АРТ и имеет значения CD4 в диапазонах: <200, 1, и эти значения в принципе могли бы быть 200–350 и >350  использованы. Тем не менее, Spectrum учитывает уровень CD4 только на момент начала АРТ, что затрудняет применение ОР, зависящих от CD4-статуса для больных, получающих АРТ. Кроме того, было предположено, что ОР в значении 0,35 применим только в отношении больных, получающих АРТ более шести месяцев. Оценки смертности на АРТ, полученные с помощью программы Spectrum и основанные по большей части на АРТ-данных из стран Африки южнее Сахары, показывают, что смертность остается очень высокой в течение первых шести месяцев лечения АРТ. Поскольку туберкулез является ведущей причиной смерти среди больных ВИЧ-инфекцией, был сделан вывод, что ОР больных, получающих АРТ в течение от 0 до 6 месяцев, вероятно, останется высоким, а поэтому коэффициент снижения в связи с АРТ не применялся для этой подгруппы больных. Функция правдоподобия Простой метод наименьших квадратов был использован для того, чтобы настроить модель на общую заболеваемость ТБ, а также на все доступные оценки заболеваемости ТБ среди больных ВИЧ-инфекцией. Эти оценочные показатели заболеваемости ТБ среди больных ВИЧ-инфекцией были получены путем трех методов измерений: специальные популяционные исследования по изучению распространенности ВИЧ-инфекции среди больных ТБ (наименее смещенные данные, но малочисленные из-за логистических сложностей), выборочные исследования по ВИЧ-инфекции (систематическая ошибка связана с бол ́ ьшим охватом обследованием больных с поздними стадиями ВИЧ-инфекции) и рутинное тестирование на ВИЧ-инфекцию зарегистрированных больных ТБ (различный охват). Для максимального использования данных специальных исследований, копии этих данных были включены в функцию правдоподобия. Другими словами, в те годы, для которых были доступны данные тестирования на ВИЧ, идентичные копии этих данных ВИЧ-тестирования были добавлены в функцию правдоподобия. Оценка общей заболеваемости ТБ была основана на гораздо большем числе данных, равномерно распределенных по оценочному периоду 1990–2015 годов. Тестирование модели показало, что использование двух копий данных специальных исследований по ВИЧ (т. е. удвоение данных специальных исследований) и двух копий данных рутинного тестирования с охватом более 90% было наилучшим подходом к стратификации заболеваемости ТБ: кривые оценок проходили близко к точкам данных специальных исследований или рутинного тестирования с высоким покрытием там, где такие данные имелись. Не использовались данные ни

Таблица A1.5 Источники данных о распространенности ВИЧ-инфекции среди больных с новым эпизодом заболевания туберкулезом Прямое измерение распространенности ВИЧ-инфекции среди больных туберкулезом Количество стран-лет

Специальные национальные исследования a Выборочные исследования на ВИЧ-инфекцию Тестирование и консультирование по инициативе медработников при минимальном охвате в 50% Общее число, по крайней мере, один источник данных доступен a

124 24 1297 1322

Представленные данные о количестве стран, выполнивших специальные исследования, завышены, так как в ряде национальных отчетов не различают данные специальных исследований от данных рутинного тестирования с охватом около 100%

по а) выборочным исследованиям на ВИЧ-инфекцию, ни по б) рутинному тестированию с охватом между 50% и 90%. Прототип алгоритма байесовской выборки по значимости (IMIS) был разработан, чтобы иметь возможности для применения к данным сложных весовых функций, но он был основан на субъективных априорных распределениях и функциях правдоподобия и был более вычислительно-сложным, чем метод наименьших квадратов. Для получения оценок по всем странам автоматическим путем был использован метод наименьших квадратов. В будущем метод наименьших квадратов и IMIS-настройка могут быть доступными для конечного пользователя. Для стран, данные по которым отсутствуют, диапазон для p(2) был оценен на основе данных из стран, в которых имеются данные специальных исследований или рутинного обследования, что дало значение p(2) = 1,96 [1,8–2,1]. Затем ОР-модель была настроена только на общую заболеваемость ТБ. Следует отметить, что не существует надежного метода верификации оценочных показателей заболеваемости ТБ, сочетанным с ВИЧ-инфекцией, если нет данных об охвате тестированием на ВИЧ-инфекцию. Тем не менее, сравнение глобальной оценки заболеваемости ТБ, сочетанным с ВИЧ-инфекцией, полученной с помощью программы Spectrum, и оценки, ранее опубликованной ВОЗ (опирающейся на другой метод, использующий распространенность ВИЧ-инфекции вместо распределений по CD4, и использующий данные тестирования на ВИЧ по-другому) позволяет предположить, что ОР-модель работает достаточно хорошо. Тестирование и консультирование по инициативе медработников при минимальном охвате тестированием на ВИЧ в 50% является наиболее широкодоступным источником информации о распространенности ВИЧ-инфекции среди больных ТБ. Однако данные, полученные из этого источника, подвержены систематическим ошибкам, особенно при охвате ближе к 50%, чем к 100%. Для всех стран, которые представили повторные данные о тестировании, взаимосвязь между распространенностью ВИЧ-инфекции среди больных ТБ и охватом тестированием на ВИЧ-инфекцию была изучена графически. С повышением охвата тестированием на ВИЧ-инфекцию в ряде стран распространенность ВИЧ-инфекции среди больных ТБ уменьшалась, а в ряде стран она увеличивалась; в большинстве стран по мере увеличения охвата тестированием на

1

Suthar AB, Lawn SD, del Amo J, Getahun H, Dye C, et al. (2012) Antiretroviral Therapy for Prevention of Tuberculosis in Adults with HIV: A Systematic Review and Meta-Analysis. PLoS Med 9(7): e1001270. doi:10.1371/journal.pmed.1001270

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ВИЧ-инфекцию, распространенность ВИЧ менялась непоследовательно, неоднократно меняя направление. Поэтому было невозможно просчитать эффект, который неполный охват тестированием на ВИЧ-инфекцию оказывает на оценки распространенности ВИЧ-инфекции среди больных ТБ. Таким образом, было сделано предположение, что больные ТБ с результатами теста на ВИЧ-инфекцию являются статистически репрезентативной группой для всех случаев ТБ. Поскольку охват населения тестированием на ВИЧ-инфекцию продолжает расти во всем мире, влияние систематической ошибки будет уменьшаться. Для 1003 точек данных «страна-год», соответствующих странам, по которым нет данных эпиднадзора, распространенность ВИЧ-инфекции была рассчитана с применением косвенных методов по следующей формуле: hρ t= l + h(ρ – l) где t — распространенность ВИЧ-инфекции среди новых случаев ТБ (истинная заболеваемость), h — распространенность ВИЧ-инфекции среди населения в целом (из последних временных ́ рядов, предоставленных ЮНЭЙДС) и  ρ — отношение относительных инцидентностей (IRR) (определенное как отношение показателя истинной заболеваемости ТБ среди больных ВИЧ-инфекцией к показателю истинной заболеваемости ТБ у ВИЧ-отрицательных лиц). Далее, определяем logit(t) как log(t/(1-t)) и  logit(h) — как log(h/(1- h)). Используя данные из стран, где распространенность ВИЧ-инфекции была определена ЮНЭЙДС, в качестве независимой переменной, линейная модель логит-трансформированных t была настроена с использованием логит-трансформированных h в соответствии со следующим уравнением, записанным в матричной форме: ˆ = Xβ T ˆ представляет собой вектор предсказаний logit(t), X являетгдеT ся n×2 матрицей, в которой первый столбец состоит из единиц, а второй столбец состоит из logit(h). Вектор β содержит в себе оцениваемые параметры модели. Модели были протестированы с лагом (временной ́ задержкой), установленной для logit(h) в диапазоне от отсутствия лага и до лага в восемь лет. Наилучшее соответствие было получено для лага в один год. Прогоны моделей осуществлялись по методу Монте-Карло, в котором h выбиралось случайным образом из бета-распределения с параметрами формы рассчитанными, как описано в  Разделе 4.1, (нижние и верхние границы неопределенности предоставляются ЮНЭЙДС — также см. Таблицу A1.5). Модель была запущена 50 000 раз с использованием своих распределений H и  T для каждой страны (заглавные буквы используются для обозначения векторов или матриц) на основе их интервалов неопределенности. Границы неопределенности для β были установлены как 2,5%-ный и 97,5%-ный квантили.

неопределенным из трех показателей ТБ, используемых для оценки бремени болезни, так как показатель распространенности представляет собой произведение двух случайных величин: (i) показателя заболеваемости и (ii) длительности заболевания. Длительность заболевания очень трудно поддается количественной оценке, так как данная величина не может быть измерена в ходе исследований распространенности ТБ (в рамках которых продолжительность естественного течения болезни усекается). Продолжительность заболевания может быть оценена в группе пациентов, обратившихся за медицинской помощью, но ее практически невозможно измерить у пациентов, которые не были зарегистрированы в национальной программе по борьбе с ТБ (НПТ). Косвенные оценки распространенности рассчитывались по следующей формуле: P = ∑ I i,j d i,j , i∈{1,2} , j∈{1,2} где индекс-переменная i обозначает ВИЧ+ и ВИЧ-, индекс-переменная j –зарегистрированные и незарегистрированные случаи, d — продолжительность болезни у зарегистрированных больных и I — общая заболеваемость. При отсутствии измерений мы не изменяли продолжительности заболевания среди зарегистрированных случаев от страны к стране. Учитывая большую степень неопределенности, оценки распространенности ТБ следует использовать с большой осторожностью при отсутствии прямых измерений в рамках специальных исследований по изучению распространенности. При отсутствии измерений, полученных из НПТ (как, например, в Турции), использовались предположения о  длительности заболевания, показанные в последних четырех строках Таблицы A1.3.

6.  Оценка числа случаев заболевания МЛУ-ТБ и случаев смерти от МЛУ-ТБ 6.1 Доля зарегистрированных случаев туберкулеза с множественной лекарственной устойчивостью возбудителя, 2012 год Глобальные и региональные оценки доли новых и зарегистрированных для повторного лечения случаев ТБ, имеющих МЛУ возбудителя в 2012 году были рассчитаны с использованием информации, полученной на национальном уровне. В случае, если страны представили данные о доле МЛУ-ТБ среди новых и зарегистрированных для повторного лечения случаев ТБ, полученных из систем эпиднадзора или специальных исследований по изучению распространенности лекарственной устойчивости, были использованы самые последние данные. Для стран, которые не представили таких данных, оценки доли МЛУ-ТБ среди новых и зарегистрированных для повторного лечения случаев ТБ были получены с помощью моделирования (в том числе при помощи метода множественной интерполяции), основанного на имеющихся данных других стран. Оценки для стран, данные по которым отсутствовали, были смоделированы на основе данных стран, считавшихся схожими с точки зрения эпидемиологии ТБ (см. группы стран в Дополнении 1). Доли МЛУТБ среди новых и зарегистрированных для повторного лечения случаев ТБ, полученные на основе фактических и интерполированных данных, затем были объединены, что дало глобальную оценку; при этом (удельный) вес каждой страны соответствовал ее доле зарегистрированных новых и зарегистрированных для повторного лечения случаев в их глобальном числе. 1

5. Оценка распространенности туберкулеза, 1990–2012 годы Лучшим способом измерения распространенности ТБ является проведение специальных исследований по изучению распространенности ТБ при помощи сплошного обследования населения 1,2. Данные таких исследований становятся доступными для все большего числа стран (Глава 2). Однако следует отметить, что измерения распространенности обычно ограничены взрослым населением. Кроме того, специальные исследования распространенности не охватывают внелегочных больных и больных туберкулезом легких с отсутствием бактериовыделения, определяемого методом посева. В связи с  отсутствием общенациональных специальных исследований распространенности ТБ с применением прямых методов измерения, распространенность является наиболее 110

Glaziou P et al. Tuberculosis prevalence surveys: rationale and cost. International Journal of Tuberculosis and Lung Disease , 2008, 12(9):1003–1008. 2 TB prevalence surveys: a handbook. Geneva, World Health Organization, 2011 (WHO/HTM/TB/2010.17).

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6.2

Смертность от МЛУ-ТБ, 2012 год

Данные по смертности, поступающие в  ВОЗ из ЗАГС государств-членов организации, не позволяют разграничить МЛУ-ТБ и не МЛУ-ТБ в качестве причины смерти (не существует специфических кодов в МКБ-9 или МКБ-10 для МЛУ-ТБ, хотя такие страны как ЮАР присвоили два специфических кода U51 и U52 для 1. классификации смертей от МЛУ-ТБ и ШЛУ-ТБ соответственно)  Поэтому был проведен систематический обзор и мета-анализ опубликованной литературы, имевший целью оценить относительный риск смерти от МЛУ-ТБ по сравнению с не МЛУ-ТБ. Глобальная оценка смертности от МЛУ-ТБ (Вставка 2.3) была затем представлена следующей формулой: m = M.p.r Где: m = глобальная смертность от МЛУ-ТБ, M = глобальная смертность от ТБ, p = общая доля случаев МЛУ-ТБ в контингенте больных ТБ, приблизительно заданная взвешенным средним доли новых и зарегистрированных для повторного лечения случаев, имеющих МЛУ-ТБ, r = относительный риск смерти от МЛУ-ТБ по сравнению с не МЛУ-ТБ. 6.3 Численность случаев заболевания МЛУ-ТБ, 2012 год Глобальная оценка заболеваемости МЛУ-ТБ была рассчитана как сумма трех групп случаев заболевания МЛУ-ТБ: 1. Заболеваемость МЛУ-ТБ среди новых случаев легочной и внелегочной формы ТБ с учетом доли МЛУ-ТБ среди новых случаев заболевания ТБ на основе данных обследований на лекарственную устойчивость (ОЛУ); 2. Заболеваемость МЛУ-ТБ среди рецидивов, с учетом доли МЛУ-ТБ среди новых случаев на основе ОЛУ и оценочного относительного риска МЛУ среди рецидивов по сравнению с новыми случаями, 3. Заболеваемость МЛУ-ТБ среди взятых на повторное лечение случаев, не являющихся рецидивами, которая, как предполагалось, имеет равномерное распределение в пределах мин = 0, макс = верхний предел глобальной доли МЛУТБ среди пролеченных случаев по оценкам, полученным в результате исследований по изучению распространенности лекарственной устойчивости. Был также рассмотрен второй способ оценки глобальной заболеваемости МЛУ-ТБ, в котором глобальная оценка смертности от МЛУ-ТБ была разделена на предполагаемый коэффициент летальности среди случаев МЛУ-ТБ. Коэффициент летальности был рассчитан как средневзвешенное значение летальности среди пациентов, получающих лечение и тех, кто его не получает, в соответствии со следующей формулой: ƒ = pt * ƒt + (1-pt)*ƒun Где: pt = доля больных, получающих лечение, приблизительно заданная отношением числа взятых на лечение больных МЛУ-ТБ к оценочному числу таковых, среди зарегистрированных пациентов с легочным ТБ; ƒt = коэффициент летальности среди пациентов, получающих лечение в связи с МЛУ-ТБ, на основе данных результатов лечения групп пациентов с МЛУ-ТБ; ƒun= коэффициент летальности среди людей с МЛУ-ТБ, не получающих терапию, который, как предполагалось, имел равномерное распределение с мин=0,4, макс=0,6.

Результаты применения обоих методов дали сходные наилучшие оценки заболеваемости МЛУ-ТБ с по большей части перекрывающимися доверительными интервалами. 6.4 Устойчивость к препаратам второго ряда среди пациентов с МЛУ-ТБ Данные из 75 стран были использованы для получения глобальных оценок в следующих пропорциях: (i) больные с МЛУ-ТБ, имеющие ШЛУ-ТБ; (ii) пациенты с МЛУ-ТБ, имеющие устойчивость к фторхинолону; (iii) больные с МЛУ-ТБ (не с ШЛУ-ТБ) с устойчивостью к инъекционным препаратам второго ряда и фторхинолонам. Самые последние имеющиеся национальные и субнациональные данные от каждой страны были проанализированы с помощью модели логистической регрессии с робастными стандартными ошибками, что позволило объяснить эффект кластеризации на уровне стран или территорий. Анализ был ограничен странами, в которых более 66% пациентов с МЛУ-ТБ прошли тестирование на лекарственную устойчивость к противотуберкулезным препаратам второго ряда.

7. Прогнозы заболеваемости, распространенности и смертности до 2015 года Прогнозы заболеваемости, распространенности и смертности от ТБ до 2015 года позволяют оценить, возможно ли достижение глобальных целей, запланированных на 2015 год, на глобальном, региональном и национальном уровнях. Прогнозы на 2013– 2015 годы были сделаны с использованием моделей экспоненциального сглаживания, настроенных на данные 2006–2012 годов.

8.

Оценка неопределенности

Существует множество потенциальных источников неопределенности, связанных с оценками заболеваемости ТБ, распространенности ТБ и смертности от ТБ, а также оценок бремени ТБ, сочетанного с ВИЧ-инфекцией и МЛУ-ТБ. К ним относятся погрешности в исходных данных, в значениях параметров, в экстраполяции, используемой для расчета недостающих данных и в используемых моделях. Мы использовали фиксированную численность населения, представленную Отделом народонаселения ООН. Мы не учитывали погрешности в этих значениях. Данные по зарегистрированной заболеваемости имеют нестабильное качество. Число случаев может быть занижено (например, отсутствие квартальных отчетов из удаленных административных районов не является редкостью), пациенты часто получают неверную характеристику (в частности, часто встречается отнесение повторных случаев ТБ к категории новых случаев, а повторное занесение пациента в информационную систему ТБ приводит к завышению показателей). Две последние проблемы могут быть эффективно решены только в странах с общенациональными персонифицированными базами данных по ТБ, которые включают идентификаторы пациента. Внезапные изменения числа выявленных случаев во времени часто являются результатом ошибок или непоследовательности в отчетности, но иногда могут отражать резкие изменения в эпидемиологии ТБ (например, в результате быстрого притока мигрантов из стран с высоким бременем ТБ, или в результате быстрых улучшений в выявлении больных). Отсутствующие сводные национальные показатели новых и повторных случаев ТБ были заполнены путем интерполяции.

1

Mortality and causes of death in Южно-Африканская Республика, 2010: Findings from death notification. http://www.statssa.gov.za/ publications/p03093/p030932010.pdf

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Кривые зарегистрированной заболеваемости сглаживались с использованием кубических сплайнов со штрафами с параметрами, основанными на данных. Ежегодно предпринимаются попытки получить корректировки для исторических данных, но только изредка страны предоставляют соответствующие корректировки данных. Оценки смертности включали следующие источники неопределенности: выборочные погрешности измерения смертности от ТБ по данным; погрешности в оценках заболеваемости и распространенности ВИЧ-инфекции среди новых и зарегистрированных случаев ТБ; и погрешности параметров в байесовской модели. Временные ́ ряды смертности от ТБ были получены для каждой страны посредством моделирования Монте-Карло. Если не указано иное, диапазоны неопределенности и их границы были определены как 2,5%-ный и 97,5%-ный квантили распределения результатов. В данном отчете для всех оценок, полученных с использованием моделирования Монте-Карло, приводятся диапазоны неопределенности, заданные этими квантилями. В случаях, где погрешность была установлена с использованием наблюдаемых или других эмпирических данных, приведены 95%-ые доверительные интервалы. В модели использовалась следующая последовательность: (1) общая оценка заболеваемости ТБ после проверки и фильтрования данных о зарегистрированной заболеваемости; (2) фильтрование и корректировка необработанных данных о смертности из систем ЗАГС и специальных исследований смертности, с последующим заполнением отсутствующих значений для стран с данными ЗАГС или специального исследования. В некоторых странах шаг 1 был обновлен с учетом данных о смертности; (3) фильтрование данных о распространенности ВИЧ-инфекции среди больных ТБ с последующим проведением оценки заболеваемости ТБ, сочетанным с ВИЧ-инфекцией, при помощи программы Spectrum и данных о смертности от ТБ, сочетанного с ВИЧ-инфекцией; (4) оценка распространенности ВИЧ-инфекции среди новых случаев ТБ с помощью моделирования для стран, не имеющих данных; (5) оценка смертности от ТБ среди ВИЧ-отрицательных больных в странах с отсутствием данных из системы ЗАГС с последующей корректировкой стадии 1 в некоторых странах; (6) проверка оценок распространенности, поправка на ТБ у детей и бактериологически неподтвержденный ТБ, оценка распространенности с последующей корректировкой стадии 1 в некоторых странах; (7) оценка заболеваемости и смертности с дезагрегацией по возрасту, полу и статусу лекарственной устойчивости. Общий подход к анализу неопределенности состоял в получении значений для каждого параметра (за исключением данных по зарегистрированной заболеваемости и данных о численности населения) из определенных распределений в рамках моделирования методом Монте-Карло, причем количество прогонов модели должно обеспечивать стабильность результирующих распределений. Для каждой страны использовалось одно и то же затравочное значение генератора случайных чисел для каждого года, и предполагалось, что ошибки зависят от времени внутри стран (создавая, таким образом, автокорреляцию во временных ́ рядах). Региональные параметры использовались в некоторых случаях (например, для коэффициента летальности). Результаты по параметрам, представляющим интерес, были получены путем извлечения среднего, 2,5%-ного и 97,5%-ного квантилей апостериорных распределений. Везде, где это возможно, погрешность результатов оценивалась аналитическим путем за счет аппроксимации моментов функций случайных величин с помощью разложения в ряд Тейлора (например, при рассмотрении произведения или частного двух случайных значений переменных), а не методом моделирования Монте-Карло, что позволило сократить длительность вычислений.

Дополнение 1. Эпидемиологические регионы, использованные в исследованиях Африка  — страны с  высоким уровнем распространенности ВИЧ: Ботсвана, Бурунди, Габон, Демократическая Республика Конго, Замбия, Зимбабве, Камерун, Кения, Конго, Кот-д’Ивуар, Лесото, Малави, Мозамбик, Намибия, Нигерия, Объединенная Республика Танзания, Руанда, Свазиленд, Уганда, Центральноафриканская Республика, Эфиопия, Южно-Африканская Республика, Южный Судан. Африка — страны с низким уровнем распространенности ВИЧ: Алжир, Ангола, Бенин, Буркина-Фасо, Гамбия, Гана, Гвинея, Гвинея-Бисау, Джибути, Кабо-Верде, Коморские острова, Либерия, Маврикий, Мавритания, Мадагаскар, Мали, Нигер, Сан-Томе и Принсипи, Сейшельские острова, Сенегал, Сомали, Судан, Сьерра-Леоне, Того, Чад, Эритрея. Центральная Европа: Албания, Босния и  Герцеговина, Бывшая Югославская Республика Македония, Сербия, Турция, Черногория. Восточная Европа: Азербайджан, Армения, Беларусь, Болгария, Грузия, Казахстан, Кыргызстан, Латвия, Литва, Республика Молдова, Российская Федерация, Румыния, Таджикистан, Туркменистан, Узбекистан, Украина. Страны с высоким уровнем доходов: Австралия, Австрия, Андорра, Аруба, Багамские острова, Барбадос, Бахрейн, Бельгия, Бермуды, Бруней-Даруссалам, Венгрия, Виргинские острова США, Германия, Гонконг, Гренландия, Греция, Гуам, Дания, Израиль, Ирландия, Исландия, Испания, Италия, Каймановы острова, Канада, Катар, Кипр, Китай, Китай Макао, Кувейт, Люксембург, Мальта, Монако, Нидерландские Антильские острова, Нидерланды, Новая Зеландия, Новая Каледония, Норвегия, Объединенные Арабские Эмираты, Оман, Польша, Португалия, Пуэрто-Рико, Республика Корея, Сан-Марино, Саудовская Аравия, Северные Марианские острова, Сент-Китс и Невис, Сингапур, Словакия, Словения, Соединенное Королевство, Соединенные Штаты, Теркс и Кайкос острова, Тринидад и Тобаго, Финляндия, Франция, Французская Полинезия, Хорватия, Чешская Республика, Швейцария, Швеция, Экваториальная Гвинея, Эстония, Япония. Восточное Средиземноморье: Афганистан, Египет, Западный берег реки Иордан и сектор Газа, Иордания, Ирак, Иран (Исламская Республика), Йемен, Ливан, Ливия, Марокко, Пакистан, Сирийская Арабская Республика, Тунис. Латинская Америка: Ангилья, Антигуа и Барбуда, Аргентина, Белиз, Боливия (Многонациональное Государство), Бонайре, Бразилия, Британские Виргинские острова, Венесуэла (Боливарианская Республика)., Гаити, Гайана, Гватемала, Гондурас, Гренада, Доминика, Доминиканская Республика, Колумбия, Коста-Рика, Куба, Кюрасао, Мексика, Монтсеррат, Никарагуа, Панама, Парагвай, Перу, Сальвадор, Сент- Винсент и Гренадины, СентКитс и Невис, Сент- Люсия, Сент-Эстатиус и Саба, Синт-Мартен (Голландская часть), Суринам, Уругвай, Чили, Эквадор, Ямайка. Юго-Восточная Азия: Бангладеш, Бутан, Восточный Тимор, Индия, Индонезия, Корейская Народно-Демократическая Республика, Корея, Мальдивы, Мьянма, Непал, Таиланд, Шри-Ланка. Западная часть Тихого океана: Американское Самоа, Вануату, Вьетнам, Камбоджа, Кирибати, Китай, Лаосская Народно-Демократическая Республика, Малайзия, Маршалловы Острова, Микронезия (Федеративные Штаты), Монголия, Науру, Ниуэ, Острова Кука, Острова Уоллис и Футуна, Палау, Папуа-Новая Гвинея, Самоа, Соломоновы Острова, Токелау, Тонга, Тувалу, Фиджи, Филиппины.

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Всемирная организация здравоохранения осуществляет контроль за глобальной эпидемией туберкулеза в поддержку национальных программ по борьбе с ТБ.

Для получения дальнейшей информации о туберкулезе обращайтесь в Информационный ресурсный центр HTM/GTB Всемирная организация здравоохранения 20 Avenue Appia, 1211–Geneva–27, Switzerland Эл. почта: tbdocs@who.int Веб-сайт: www.who.int/tb ISBN 978 92 4 4564653