Clinical features and prognostic factors of COVID-19 in people living with HIV hospitalized with suspected or confirmed SARS-CoV-2 infection, 15 July 2021

1Clinical features and prognostic factors of COVID-19 in people living with HIV hospitalized with suspected or confirmed SARS-CoV-2 infection 15 JULY 2021 © World Health Organization 2021. Some rights reserved. This work is available under the CC BY-NC-SA 3.0 IGO licence. WHO reference number: WHO/2019-nCoV/Clinical/HIV/2021.1 3Contents Acknowledgements..............................................................................................................................4 Abbreviations........................................................................................................................................5 Background...........................................................................................................................................6 Objectives of the analysis.......................................................................................................................6 Methods.................................................................................................................................................7 Data Collection Tools..............................................................................................................................7 Inclusion Criteria and Data Collection....................................................................................................7 Statistical Analysis..................................................................................................................................7 Results...................................................................................................................................................9 HIV infection and severe or critical illness at hospital admission...........................................................12 HIV infection and in-hospital mortality....................................................................................................13 Limitations.............................................................................................................................................15 Conclusions...........................................................................................................................................15 References.............................................................................................................................................16 Annex: Contributors to the WHO Global COVID-19 Clinical Data Platform....................................17 4Acknowledgements America); Lee Wallis (University of Cape Town, South Africa). Organization), Flaminia Sabbatucci (Consultant, World Health Organization) and Mr Firdavs Kurbonov (Consultant, World Health Organization), the WHO regional advisors on clinical management (Dr John (Appiah, Dr Dina Pfeifer, Dr Chiori Kodama, Dr Ludovic Reveiz, Dr Pushpa Wijesinghe and Dr Joao Toledo), Dr Jacobus Preller (World Health Organization, Department of Country Readiness Strengthening, Health Emergencies Programme), Dr Pryanka Relan (World Health Organization, Sincere thanks to all the facilities and collaborators contributing individualized anonymized data of hospitalized patients with suspected or confirmed COVID-19 to the WHO Clinical Platform. The list of facilities that contributed to this analysis is provided in Annex. Department of Integrated Health Services), Dr Marta Lado (World Health Organization, Department of Country Readiness Strengthening, Health Emergencies Programme) and the Clinical Advisory Group: John Amuasi (Kwame Nkrumah University of Science and Technology, Ghana); Yaseen Arabi (King Saud University, Saudi Arabia); Shabin Ariff (Department of Paediatrics and Child Health, Ministry of Health, Pakistan); Lindsey Baden (Harvard Medical School, United States of America); Lucille Blumberg (National Institute for Communicable Diseases, South Africa); Paolo Bonfanti (Hospital San Gerardo, Monza, Italy); Bin Cao (China-Japan Friendship Hospital, China); Gail Carson (Centre for Tropical America); Michael Jacobs (Royal Free London NHS Foundation Trust, United Kingdom); Richard Kojan (ALIMA and University of Kinshasa, Democratic Republic of the Congo); Yee Sin Leo (National Centre of Infectious Diseases, Ministry of Health, Singapore); Pisake Lumbiganon (Khon Kaen University, Thailand); Flavia Machado (Federal University of São Paulo, Brazil); Sabue Mulangu (Institut National de Recherche Biomedical, Democratic Republic of the Congo); Roger Paredes (Departament de Salut, Generalitat de Catalunya, Spain); Natalia Pshyenshya (Rostov State Medical University, Russian Federation); Yinzhong Shen (Fudan University, China); Tim Uyeki (Centers for Disease Control and Prevention, United States of The WHO Heath Emergencies Programme coordinated the development of this report in collaboration with the Department of Global HIV, Hepatitis and STI Programmes COVID-19 Task Team. This report was written by Dr Silvia Bertagnolio (World Health Organization, Department of Global HIV, STI, Hepatitis Programmes), in collaboration with Dr Soe Soe Thwin (World Health Organization, Department of Sexual and Reproductive Health and Research), Dr Ronaldo Silva (consultant, Department of Sexual and Reproductive Health and Research) and Dr Janet Diaz (World Health Organization, Department of Country Readiness Strengthening, Health Emergencies Programme). The report benefited from the contribution of Dr Sairaman Nagarajan (consultant, World Health Medicine and Global Health, University of Oxford, United Kingdom of Great Britain and Northern Island); Robert Fowler (Sunnybrook Health Sciences Centre, Canada); Rashan Haniffa (University College Hospital, United Kingdom); Michael Hughes (Harvard TH Chan School of Public Health, United States of 5aHR adjusted hazard ratio aOR adjusted odds ratio ART antiretroviral therapy BMI body mass index CI confidence interval HIV human immunodeficiency virus SAP statistical analysis plan WHO World Health Organization PLHIV people living with HIV Abbreviations 6Available published evidence on the impact of HIV infection on severity and mortality associated with COVID-19 is limited and conflicting, and analyses have been based primarily on small cohorts of individuals in specific settings (1-7). A retrospective cohort study in the United Kingdom found that people living with HIV (PLHIV) appear to be at increased risk for mortality (8). A retrospective cohort study in the United States of America found that while PLHIV do not appear to be at increased risk of infection, they are at increased risk for poor outcomes (mainly owing to higher rates of severe disease requiring hospitalization). In this sample of patients, the risk of hospitalization increased with the progression of HIV disease (9). Data from South Africa showed HIV to be an independent risk factor for in-hospital mortality (10). Data from meta-analyses are also inconsistent. One meta-analysis found that HIV infection was not associated with poor composite outcomes (11). However, two meta-analyses found that PLHIV had a moderately increased risk of mortality than compared with people without HIV (12, 13). Additional evidence from larger datasets with a broader geographical representation is required to expand the understanding of the interplay between HIV and SARS-CoV2 co-infection and guide global discussion on optimal clinical care for PLHIV who are infected with SARS-CoV-2. To expand the understanding of clinical characteristics and prognostic factors among patients hospitalized with suspected or confirmed COVID-19, and to inform optimal clinical management and interventions, the World Health Organization (WHO) has established the Global Clinical Platform, which is a secure web-based database including individual-level, anonymized clinical data of hospitalized patients with suspected or confirmed COVID-19 from health facilities across the globe. The WHO Global Clinical Platform is intended to provide Member States with a standardized clinical data collection system to characterize the natural history of COVID-19; identify risk factors for severe disease and poor outcomes; and describe treatment interventions and outcomes among adults, children, and subpopulations, including pregnant women and PLHIV. Objectives of the analysis This report describes the demographics, clinical presentation, clinical outcomes, and risk factors among PLHIV who have been hospitalized for suspected or confirmed COVID-19. The specific objectives of the analysis were to: • describe the clinical characteristics and outcomes of PLHIV hospitalized for COVID-19 • assess whether PLHIV hospitalized with COVID-19 were at increased risk of presenting with severe or critical illness at admission and were at increased risk of in-hospital death compared to individuals not infected with HIV • assess risk factors associated with severe or critical illness at hospital admission and of in-hospital death among PLHIV hospitalized for COVID-19. Background 7Methods We conducted a preliminary analysis of anonymized patient-level clinical data submitted to the WHO Global Clinical Platform for COVID-19 between 1 January 2020 and 29 April 2021 by a mix of national registries and sentinel health facilities from 37 countries. Data Collection Tools Two options exist to contribute data to the WHO Clinical Platform: i) use of the WHO Case Report Form (CRF), which exists in both paper-based or electronic formats, and ii) data entered into a local system or database. For locally entered data, relevant variables were mapped and aligned to the WHO CRF data dictionary and transferred to the WHO Clinical Platform hosted on OpenClinica. The WHO CRF contains a standardized set of variables, including demographics, severity, medications, comorbidities, and clinical outcomes (discharged alive to home, in-hospital mortality, transfer to another facility for further care, remaining in the hospital at the time of data entry and discharged to palliative care or hospice). The CRF is divided into three modules. Module1 is completed on the first day of inpatient admission to the healthcare facility, module 2 is completed daily during hospital stay for as many days as resources allow and module 3 is completed at the time of discharge or death. The CRF has been translated into Arabic, Chinese, English, French, Russian, Spanish and Portuguese. Inclusion Criteria All patients, regardless of age, with known HIV status and admitted to a hospital or health facility with laboratory-confirmed or suspected COVID-19 were included in the analysis. Statistical Analysis Descriptive and regression analyses were conducted to summarize demographic and clinical characteristics and to evaluate their association with HIV status, disease severity at hospital admission and in-hospital mortality. Records with missing data were excluded when determining distributions across outcome levels, and chi-square tests and student t-tests were used to assess the relationship between clinical characteristics and outcomes. The two clinical outcomes of interest were in-hospital mortality (yes vs no) and clinical severity, defined as follows. Cases were defined as severe or critical if they met one or more of the following conditions at hospital admission: 1) SpO2: <90%; 2) respiratory rate: >30 breaths/minute in adults and children over 5 years old; 3) received extracorporeal membrane oxygenation (ECMO); 4) admitted to an Intensive Care Unit (ICU); 5) received an inotrope or vasopressor; and 6) received oxygen therapy or ventilation. Cases not meeting all the conditions described above, and those meeting the conditions below were described as mild or moderate: 1) SpO2: ≥90% without supplemental oxygen; 2) respiratory rate: ≤30 breaths/minute in adults and children over 5 years old, and 3) did not receive oxygen therapy or ventilation. A logistic regression model using generalized estimating equations (GEE) was fitted to evaluate whether HIV infection was a risk for severe or critical illness at admission, and a proportional hazards model (that adjusted in variance estimation for clustering at the country level) was fitted to evaluate whether HIV infection was a risk factor for mortality. Age (≤65 years, >65 years), sex (male, female) with the binary indicator for HIV positive status (yes/no) were included in the model a priori. 8Covariates were considered for inclusion in the model when >80% reported data was not highly correlated with other variables using a correlation matrix threshold of >0.8, and they were associated with both the outcome (severity or mortality) and exposure (HIV status) at p<0.10 level. After covariate selection, they were then retained in the final model if further found to be significant at p<0.05 level. Based on the above criteria, the following underlying conditions were considered in the analysis: chronic cardiac disease, diabetes, hypertension, chronic pulmonary disease, tuberculosis, asthma and malignant neoplasms. A second model included categories of the number of underlying conditions or “comorbidity burden” (none, 1-2 underlying conditions, and ≥3 underlying conditions) to determine if the number of conditions, rather than the individual conditions themselves, had an impact on severe or critical illness and mortality. A subgroup analysis stratifying mortality risk by WHO geographical region to determine the impact of WHO Region of origin on mortality was also conducted. Regression analysis was repeated in the restricted sample of PLHIV to evaluate risk factors for disease severity at admission (logistic model) and risk factors for mortality (proportional hazards model). In a sensitivity analysis, the regression models were repeated, excluding individuals from South Africa, which represented the main data contributor and accounted for 94.6% of the data. All analyses were conducted in SAS version 9.4 (Copyright (c) 2016 by SAS Institute Inc., Cary, North Carolina, United States of America) or R version 3.6.3 (R: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria 2020, https://www.R- project.org) and maps were drawn using ARCGIS Pro Release 2.5.0 (Environmental Systems Research Institute (ESRI), 2020. Redlands, California, United States of America). 91 Argentina, Belarus, Brazil, Cameroon, Chile, China, Democratic Republic of the Congo, Dominican Republic, France, Germany, Guinea, India, Italy, Jordan, Nigeria, Panama, Romania, Russian Federation, South Africa, Spain, United Kingdom, United States of America, Zambia, Zimbabwe. Results As of 29 April 2021, 37 countries had contributed data to the WHO Global COVID-19 Clinical Data Platform with clinical information on 268 412 patients hospitalized with suspected or confirmed COVID-19 (Fig. 1a). 24 countries contributed clinical data on PLHIV (Fig. 1b).1 In this global sample, 9.2% (15 522/168 649) of cases hospitalized with suspected or confirmed COVID-19 were HIV positive; and 96.1% (14 914/15 522) of the PLHIV included in the analysis were from the WHO African Region, with 94.6% (14 682/15 522) of cases reported from South Africa alone. Among PLHIV, 37.1% (5737/15 442) were male, the mean age was 45.5 years, 91.8% (8842/9631) were on ART, and 36.2% (5613/15 522) had severe or critical illness on hospital admission. Among the severe cases, 89.8% (5039/5611) were ≤65 years of age and 39.1% (2187/5596) were male. Overall, the mean duration from hospital admission to death or discharge was 9.5 days (SD 13.4, n= 14,776). Fig. 1a. Countries contributing clinical data to the WHO Global Clinical Platform for COVID-19 as of 29 April 2021 10 Fig. 1b. Countries1 contributing clinical data on people living with HIV to the WHO Global Clinical Platform for COVID-19 as of 29 April 2021 Table 1. Demographic characteristics of people living with HIV hospitalized with suspected or confirmed COVID-19 Characteristics People living with HIV (n=15 522) n % Age ≤65 years 14 101 92.6 >65 years 1 132 7.4 Age group ≤18 years 229 1.5 18-45 years 7513 49.3 46-65 years 6359 41.7 66-75 years 920 6.0 >75 years 212 1.4 Sex Male 5737 37.2 Female 9705 62.9 Pregnant Yes 729 7.5 Health care worker Yes 328 2.2 No 14 636 97.8 11 Fig. 2. Distribution of people living with HIV hospitalized with COVID-19 by age and sex Reported underlying conditions2 in PLHIV are shown in Fig. 3. The most common underlying conditions were hypertension (33.2%), diabetes (22.7%) and obesity (16.9%). The presence of one or more underlying conditions was reported at the time of admission in 55.5% (7752/13 975) of PLHIV. Among those, 61% reported having one underlying condition, and 28.7% reported two underlying conditions. 10% had three or more underlying conditions. 13% (1548/11 873) were reported to be co-infected currently or previously with tuberculosis. 2 Asplenia, asthma, chronic cardiac disease, chronic kidney disease, chronic liver disease, chronic neurological disorder, chronic pulmonary disease, current smoker, diabetes, hypertension, malignant neoplasms, tuberculosis. Fig. 3. Frequency of underlying conditions among PLHIV hospitalized with COVID-19 3 Obesity is defined as Body Mass Index >30 Hypertension Diabetes Obesity3 Tuberculosis Chronic kidney disease Chronic liver disease Smoking Asthma Malnutrition Chronic pulmonary disease Chronic neurological disorder Chronic cardiac disease Malignant neoplasm Asplenia 33.2% 22.7% 16.9% 13.0% 12.1% 12.1% 8.9% 7.2% 7.0% 6.6% 6.2% 4.3% 1.7% 0.5% >75yrs - >65 to 75yrs - >45 to 65yrs - >18 to 45yrs - >=18yrs - Ag e gr ou p Male Female 2300 1150 0 1150 2300 3450 4600 Total number of hospitalized cases 12 23.1% (3578/15 463) of PLHIV with a known outcome died during the hospital stay. Mortality and other clinical outcomes in PLHIV presenting with severe/critical illness or mild/moderate illness are shown in Fig. 4. Fig. 4. Clinical outcomes among PLHIV hospitalized with COVID-19, stratified by severity of illness at hospital admission HIV infection and risk of severe or critical illness at hospital admission We assessed whether HIV infection was independently associated with a higher risk for severe or critical presentation of COVID-19 at hospital admission. In this hospitalized population, PLHIV were at increased risk of severe or critical disease at hospital admission (aOR 1.06, 95% CI 1.02–1.11) compared to HIV-negative individuals, after adjusting for age, sex and the presence of underlying conditions (diabetes, tuberculosis, malignant neoplasms and chronic cardiac and pulmonary diseases). By including in the model the number of underlying conditions (comorbidity burden) rather than individual conditions, we found a similar risk of severe or critical disease (aOR 1.13, 95% CI 1.09–1.17) (Fig. 5.) A sensitivity analysis was repeated to assess the impact of the country of origin on the severity outcome. After excluding data from South Africa, a total of 38 774 cases were available. Of those, 840 were people living with HIV, and 425 had information on severity status. In this analysis, HIV positive status remained an independent risk factor for severe/critical illness at hospital admission (aOR 2.27, 95% CI 1.73–2.97) after adjusting for age, sex and the presence of underlying conditions (diabetes, neoplasms and chronic cardiac disease). Risk factors associated with severe/critical illness among people living with HIV admitted to hospital with COVID-19. We assessed the associations between potential risk factors and severe/critical illness at hospital admission in this sample of PLHIV. After adjusting for age, sex, and underlying conditions (diabetes and hypertension), we found that PLHIV who were >65 years of age (aOR 1.62, 95% CI 1.41-18.7), male (aOR 1.21, 95% CI 1.23–1.31), with diabetes (aOR 1.10, 95% CI 1.03-1.22) or hypertension (aOR 1.54, 95%CI 1.41-1.68) had an increased risk of severe or critical illness at hospital admission after controlling for the other risk factors. All estimates were significant at p<0.0001 level (see Fig. 5., below). Clinical outcomes included: 1) discharged to home, 2) died in hospital, 3) transferred (to another facility for further care), 4) remaining hospitalized at the time of data entry, and 5) discharged to palliative care or hospice Severe/Critical illness at hospital admission Mild/Moderate illness at hospital admission Discharged alive Died Transferred Hospitalized1952 (34.9%) 3267 (58.4%) 269 (5.3%) 75 (1.34%) 7470 (78.8%) 1588 (16.8%) 271 (2.86%) 149 (1.57%) 1 (0.0105%) Discharged alive Died Transferred Hospitalized Palliative 13 Fig. 5. HIV infection and risk of severe or critical illness of COVID-19 at hospital admission HIV infection and risk of in-hospital mortality HIV infection was independently associated with a higher risk of death (aHR 1.29, 95% CI 1.23–1.35) compared to the HIV-negative population, after adjusting for age, sex, disease severity and underlying conditions (diabetes, chronic pulmonary disease and malignant neoplasms). A similar risk (aHR 1.30, 95% CI 1.24–1.36) was found after adjusting for age, sex, disease severity at admission and the number of underlying conditions (comorbidity burden). (Fig. 6). The presence of one or two underlying conditions (aHR 1.40, 95% CI 1.37–1.43) and the presence of three or more underlying conditions (aHR 1.50, 95% CI 1.44–1.56) were associated with increased risk of death. All estimates were significant at p<0.0001 level. We performed a subgroup analysis, stratifying mortality risk by WHO geographic region. After adjusting for age, sex, underlying conditions and clinical presentation at hospital admission (mild/moderate versus severe/critical illness), HIV infection was independently associated with an increased risk for in-hospital mortality in the WHO African Region (aHR 1.29, 95% CI 1.23-1.34) but not in the WHO European Region (aHR 0.59, 95% CI 0.29-1.2) or the WHO Region of the Americas (aHR 0.92, 95% CI 0.37-2.31). For other Regions, modelling for mortality outcomes was not possible due to the limited sample size. A sensitivity analysis was repeated to assess the impact of the country of origin on the mortality. When excluding data received from South Africa (resulting in a total of 311 HIV positive cases compared with 7474 HIV negative cases with a known outcome), the risk of death in people living with HIV hospitalized with COVID-19 remained elevated, but was no longer statistically significant (aHR 1.16, 95% CI 0.90– 1.51). Adjustment for covariates other than sex and age was not possible due to the limited sample size. The upper part of the figure shows HIV infection as a significant independent risk factor for severe or critical presentation of COVID-19, after adjusting for age, sex, burden of underlying conditions (adjusted odds ratio (aOR). The lower part of the figure shows the adjusted odds ratio for each risk factor for severe or critical presentation of COVID-19 among PLHIV, after controlling for the other risk factors. 14 Fig. 6. HIV infection and risk of in-hospital mortality for COVID-19 Risk factors associated with in-hospital mortality among people living with HIV admitted to hospital with suspected or confirmed COVID-19. We also assessed the relationship between potential risk factors predicting in-hospital mortality in this sample of PLHIV. Among PLHIV, being >65 years of age (aHR 1.82, 95% CI 1.62–2.04), male (aHR 1.21, 95% CI 1.15–1.28), having diabetes (aHR 1.50, 95% CI 1.39–1.62) and hypertension (aHR 1.26, 95% CI 1.19-1.34) increased the risk of in-hospital death after controlling for the other risk factors. All estimates were statistically significant with p<0.0001. (Fig. 6., lower section). The upper part of the figure shows HIV infection as a significant independent risk factor for in-hospital mortality of COVID-19, after adjusting for age, sex, disease severity and burden of underlying conditions (adjusted hazard ratios (aHR)). The lower part of the figure shows the adjusted hazard ratio for each risk factor for in-hospital mortality among PLHIV, after controlling for the other risk factors. 15 Limitations The WHO Global Clinical Platform for COVID-19 is an evolving project, and measures to improve the harmonization of data collection are in place. Not all facilities that submitted data to the WHO platform used the WHO case report form, which may have contributed to some heterogeneity and incompleteness of data. A major limitation of the data submitted to the WHO Platform was missing information on anti-retroviral therapy (ART) that was only available in 40% of the cases, which precluded meaningful analysis of clinical outcomes (disease severity on admission and in-hospital mortality) stratified by ART status. Some countries contributed data derived from national registries of hospitalized patients, while other countries contributed data from a convenience sample of clinics or sentinel clinics. Thus, lack of representativeness and potential selection bias may limit the generalizability of these findings. In this analysis, the data are predominantly from South Africa. Although this may limit the generalizability of the results, it is worth noting that this country is the epicenter of the HIV pandemic and has the largest AIDS epidemic globally, accounting for 20% of all people living with HIV worldwide and 20% of new HIV infections. Not all potentially relevant risk factors, such as body mass index (BMI), were considered in the regression model due to insufficient data reported; and this may have influenced our findings. In addition, findings only refer to in-hospital mortality and do not capture information on post-discharge outcomes, thus potentially underestimating the impact of HIV infection on overall mortality due to COVID-19. HIV appears to be a significant independent risk factor for severe or critical illness at hospital admission and in-hospital mortality. To improve our understanding of the clinical characterization and management impact of patients hospitalized with COVID-19, WHO will continue to expand the collection and analysis of clinical data of hospitalized patients with and without HIV through the WHO Global Clinical Platform for COVID-19 and encourage countries and stakeholders to contribute anonymized data. As the data contribution continues to expand, the generalizability of findings will increase and inform optimal clinical management in this co-infected vulnerable population. These analyses will be updated regularly to improve our understanding of the clinical characterization and management of people living with HIV that are hospitalized with COVID-19. Conclusions 16 References 1. Mirzaei H, McFarland W, Karamouzian M, Sharifi H. COVID-19 Among People Living with HIV: A Systematic Review. 2021;25:85-92. doi: 10.1007/s10461-020-02983-2. 2. Cooper TJ, Woodward BL, Alom S, Harky A. Coronavirus disease 2019 (COVID-19) outcomes in HIV/AIDS patients: a systematic review. 2020;21:567-77. doi: 10.1111/hiv.12911. 3. Costenaro P, Minotti C. SARS-CoV-2 infection in people living with HIV: a systematic review. 2021;31:1-12. doi: 10.1002/rmv.2155. 4. Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020;81:e16-e25. doi: 10.1016/j.jinf.2020.04.021. 5. Boulle A, Davies MA, Hussey H, Ismail M, Morden E, Vundle Z et al. Risk factors for COVID-19 death in a population cohort study from the Western Cape Province, South Africa. Clin Infect Dis. 2020. doi: 10.1093/cid/ciaa1198. 6. Hadi YB, Naqvi SFZ, Kupec JT, Sarwari AR. Characteristics and outcomes of COVID-19 in patients with HIV: a multicentre research network study. AIDS. 2020;34:F3-f8. doi: 10.1097/ qad.0000000000002666. 7. Geretti AM, Stockdale AJ, Kelly SH, Cevik M, Collins S, Waters L et al. Outcomes of COVID-19 related hospitalization among people with HIV in the ISARIC WHO Clinical Characterization Protocol (UK): a prospective observational study. Clin Infect Dis. 2020. doi: 10.1093/cid/ ciaa1605. 8. Bhaskaran K, Rentsch CT, MacKenna B, Schultze A, Mehrkar A, Bates CJ et al. HIV infection and COVID-19 death: a population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform. Lancet HIV. 2021;8:e24-e32. doi: 10.1016/s2352-3018(20)30305-2. 9. Tesoriero JM, Swain CE, Pierce JL, Zamboni L, Wu M, Holtgrave DR et al. COVID-19 Outcomes Among Persons Living With or Without Diagnosed HIV Infection in New York State. JAMA Netw Open. 2021;4:e2037069. doi: 10.1001/jamanetworkopen.2020.37069. 10. Jassat W, Cohen C, Masha M, Goldstein S, Kufa T, Savulescu D et al. COVID-19 in-hospital mortality in South Africa: the intersection of communicable and non-communicable chronic diseases in a high HIV prevalence setting. medRxiv. 2020:2020.12.21.20248409. doi: 10.1101/2020.12.21.20248409. 11. Hariyanto TI, Putri C, Frinka P, Louisa J, Lugito NPH, Kurniawan A. Human Immunodeficiency Virus (HIV) and outcomes from coronavirus disease 2019 (COVID-19) pneumonia: A Meta- Analysis and Meta-Regression. AIDS Res Hum Retroviruses. 2021. doi: 10.1089/aid.2020.0307. 12. Mellor MM, Bast AC, Jones NR, Roberts NW, Ordóñez-Mena JM, Reith AJM et al. Risk of adverse coronavirus disease 2019 outcomes for people living with HIV. AIDS. 2021;35:F1-f10. doi: 10.1097/qad.0000000000002836. 13. Hariyanto TI, Rosalind J. Human immunodeficiency virus and mortality from coronavirus disease 2019: A systematic review and meta-analysis. 2021;22:1220. doi: 10.4102/sajhivmed. v22i1.1220. 17 Annex 1. Contributors to the WHO Global COVID-19 Clinical Platform As of the 29th of April 2021, the following health care facilities/collaborators have contributed anonymized clinical data to the WHO Global Clinical Platform. Global WHO Collaborating Centre for TB and Lung Diseases, Maugeri Care and Research Institute, Italy Alma Mater Studiorum University of Bologna, Bologna, Italy Aristotle University of Thessaloniki, Thessaloniki, Greece ASST Spedali Civili, Brescia, Italy Catholic University Ruzomberok, Slovakia Centre Hospitalier Universitaire, Nantes, France Centro Hospitalar de Vila Nova de Gaia/Espinho, Vila Nova de Gaia, Portugal Centro Hospitalar São João, Porto, Portugal Centro Nacional de Programas Preventivos y Control de Enfermedades, Mexico City, Mexico CHI Créteil, Créteil, France Civico-Benfratelli Hospital, Palermo, Italy Clinical Hospital for Infectious Diseases and Pneumology “Dr. Victor Babes”, Timisoara, Romania Clinique Saint Luc, Bouge, Belgium Comisión Honoraria para la Lucha Antituberculosa y Enfermedades Prevalentes, Montevideo, Uruguay Damien Foundation, Conakry, Guinea Damien Foundation, Niamey, Niger Dr. Negri University Hospital of Gran Canaria, Las Palmas, Spain Groupe Hospitalier sud île de France, Melun, France Hôpital Européen de Paris La Roseraie, Aubervilliers, France Hôpital d’Instruction des Armées Percy, Clamary, France Hôpital National Ignace Deen, Conakry, Guinea Hospital Amador Guerrero, Ciudad de Colon, Panama Hospital de Cantoblanco, Madrid, Spain Hospital das Clinicas HCFMUSP, São Paulo, Brazil Hospital de Cruces, Bizkaia, Spain Hospital DIPRECA, Chile Hospital Especializado Octávio Mangabeira, Salvador, Brazil Hospital General Universitario La Paz, Madrid, Spain Hospital Nacional Dose de Mayo, Lima, Peru Hospital Valdecilla, Santander, Spain Hospital Virgen Macarena, Sevilla, Spain Huashan Hospital, Shanghai, China Indira Gandhi Government Medical College, Nagpur, India Instituto de Tisioneumonología Prof. Dr. R. Vaccarezza, Buenos Aires, Argentina Instituto Nacional de Enfermedades Repiratorisa Ismael Cosio Villegas, Mexico City, Mexico IRCCS Ospedale Sacro Cuore Don Calabria, Negrar, Italy Istituti Clinici Scientifici Maugeri, Tradate, Italy Karolinska Instituet, Stockholm, Sweden Karloniska University Hospital Solna, Stockholm, Sweden Laboratório Municipal de Alvorada, Alvorada, Brazil Lausanne University, Lausanne, Switzerland Lausanne University Hospital CHUV, Lausanne, Switzerland Lithuanian University of Health Sciences, Kaunas, Lithuania Luigi Sacco Hospital, Milan, Italy National Institute for Infectious Diseases ‘L. Spallanzani’, Rome, Italy McMaster University, Hamilton, Canada Ministerio de Salud, Chile Ministerio de Saluda, Panama City, Panama Ministerio de Salud Pública y Bienestar Social, Asunción, Paraguay Ministerio de Salud y Protección Social, Colombia Ministry of Health, Lima, Peru Moscow Research and Clinical Center for Tuberculosis Control, Moscow, Russian Federation National Centre for Infectious Diseases, Singapore National Institute of TB and Respiratory Diseases, New Delhi, India National University of Singapore, Singapore National University Health System, Singapore Nestor Goulart Reis Hospital, São Paulo, Brazil Niguarda Hospital, Milan, Italy Northern State Medical University, Arkhangelsk, Russian Federation Parramatta Chest Clinic, Parramatta, Australia P.D. Hinduja Hospital and Medical Research Centre, Mumbai, India Public Health Consulting Group, Lugano, Switzerland Public Health Institute of Serbia “Dr Milan Jovanovic Batut”, Belgrade, Serbia Republican Klaipėda Hospital, Klaipėda, Lithuania Republican Research and Practical Center for Pulmonology and Tuberculosis, Minsk, Belarus Republic Scientific and Practical Center of Pulmonology and Tuberculosis, Minsk, Belarus Riga East University Hospital, Riga, Latvia Royal London Hospital, London, United Kingdom Secretaria de Salud Departamental, Cuaca, Colombia Secreteria de Salud de Honduras, Tegucigalpa, Honduras Servicio de Salud Antofagasta, Chile 18 Servicio de Salud Arica, Chile Servicio de Salud Concepción, Chile Servicio de Salud Iquique, Chile Servicio de Salud Magallanes, Chile Servicio de Salud Metropolitano Central, Chile Servicio de Salud Metropolitano Occidente, Chile Servicio de Salud Metropolitano Oriente, Chile Servicio de Salud Metropolitano Sur, Chile Servicio de Salud Suroriente, Chile Servicio de Salud Talcahuano, Chile Servicio de Salud Vaplaraíso San Antonio, Valparaíso, Chile Sondalo Hospital, Sondrio, Italy Tuberculosis Research Programme SEPAR, Barcelona, Spain Unitat Clínica de Tractament Directament Observat de La Tuberculosi, Barcelona, Spain Université de Picardie Jules Verne, Amiens, France Universidad del Cauca, Popayán, Colombia Universidade Federal de Goiás, Goiânia, Brazil Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil University Hospital of Monterrey, Monterrey, Mexico University of Cape Town, Cape Town, South Africa University of Groningen, Groningen, Netherlands University of Insubria, Varese-Como, Italy University of Milan, Milan, Italy University of Sassari, Sassari, Italy University of Sydney, Sydney, Australia University of Torino, Italy University of Virginia, Charlottesville, Virginia, United States of America Université Paris Est Créteil, Créteil, France Vall d’Hebron University Hospital, Barcelona, Spain “Victor Babes” Clinical Hospital of Infectious Diseases and Pneumophtisiology, Cariova, Romania Vilnius University Hospital Santaros Klinikos, Vilinius, Lithuania Virginia Department of Health, Richmond, Virginia, United States of America VMMC and Safdarjung Hospital, New Delhi, India Volgograd State Medical University, Volgograd, Russian Federation Westmead Hospital, Westmead, Australia African Region Burkina Faso ALIMA (Alliance for International Medical Action), Burkina Faso CHU-T and CHU-B, Ouagadougou, Burkina Faso Clinique les Genets, Ouagadougou, Burkina Faso Cameroon Biyem-Assi District Hospital, Yaounde, Cameroon Djoungolo District Hospital, Yaounde, Cameroon Efoulan District Hospital, Yaounde, Cameroon Nkolbisson District Hospital, Yaounde, Cameroon Nkolndongo District Hospital, Yaounde, Cameroon Soa District Hospital, Yaounde, Cameroon Democratic Republic of the Congo ALIMA, Democratic Republic of the Congo Cliniques Universitaires de Kinshasa (CUK), Kinshasa, Democratic Republic of the Congo Ghana Komfo Anokye Teaching Hospital, Kumasi, Ghana Global Health and Infectious Diseases Research Group, Ghana Kumasi Centre for Collaborative Research in Tropical Medicine, Kumasi, Ghana Kwame Nkrumah University of Science and Technology, Kumasi Ghana Guinea ALIMA, Guinea CHU Donka, Conakry, Guinea Nigeria Abubakar Tafawa Balewa University Teaching Hospital, Bauchi, Nigeria Bingham University Teaching Hospital, Jos, Nigeria Federal Medical Centre, Asaba, Nigeria Federal Medical Centre, Yola, Nigeria General Hospital Abakaliki, Abakaliki, Nigeria General Hospital Riyom, Riyom, Nigeria Infectious Disease Centre, Specialist Hospital, Yola, Nigeria Infectious Disease Hospital, Akure, Nigeria Infectious Disease Hospital Amanawa, Amanawa, Nigeria Infectious Disease Hospital, Olodo, Nigeria Isolation Centre Amachara, Umuahia, Nigeria Jos University Teaching Hospital, Jos, Nigeria Kapital Klub Isolation and Treatment Centre, Abuja, Nigeria Lagos University Teaching Hospital, Lagos, Nigeria National Hospital of Abuja, Abuja, Nigeria Niger State Ministry of Health, Minna, Nigeria Obafemi Awolowo University Teaching Hospital, Ile- Ife, Nigeria Ogunstate Ministry of Health, Abeokuta, Nigeria Plateau State Specialist Hospital, Jos, Nigeria State Specialist Hospital, Damaturu, Nigeria State Specialist Hospital, Osogbo, Nigeria Taraba State Specialist Hospital, Jalingo, Nigeria This Day Dome Isolation and Treatment Centre, Abuja, Nigeria UN Sari Clinic, Abuja, Nigeria University of Abuja Teaching Hospital, Abuja, Nigeria South Africa Steve Biko Academic Hospital, Gauteng Provincial Department of Health, Pretoria, South Africa National Institute of Communicable Diseases, Johannesburg, South Africa Zambia Levy Mwanawasa University Teaching Hospital, Lusaka, Zambia 19 Zimbabwe Arundel Hospital, Harare, Zimbabwe Bindura Farm Health Centre, Bindura, Zimbabwe Gweru Infectious Diseases Hospital, Gweru City, Zimbabwe Hauna Hospital, Hauna, Zimbabwe HealthPoint, Harare, Zimbabwe Marondera Provincial Hospital, Marondera, Zimbabwe Mater Dei Hospital, Bulawayo, Zimbabwe Mutare Infectious Diseases Hospital, Mutare, Zimbabwe Parirenyatwa General Hospital, Harare, Zimbabwe St Annes Hospital, Harare, Zimbabwe Thorngrove Hospital, Bulawayo, Zimbabwe United Bulawayo Hospital, Bulawayo, Zimbabwe Victoria Chitepo Provincial Hospital, Mutare, Zimbabwe Region of the Americas Brazil Instituto de Infectologia Emilio Ribas, São Paulo, Brazil Grupo Hospitalar Conceição, Porto Alegre, Brazil Colombia Clínica Colsanitas, Bogota, Colombia Dominican Republic Hospital Regional Universitario Jose Maria Cabral y Baez, Santiago, Dominican Republic Hospital Regional Dr. Arturo Grullon, Santiago, Dominican Republic Hospital Metropolitano de Santiago (HOMS), Santiago, Dominican Republic Mexico Hospital Pediátrico de Sinaloa, Culiacán, Mexico United States of America Bronxcare Health System, New York City, USA Henry Ford Hospital, Detroit, USA New York City Health + Hospitals, New York City, USA South-East Asia Region India Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India European Region Belgium Infectious Diseases Clinic Brugmann Hospital, Brussels, Belgium Germany University Hospital Frankfurt, Frankfurt, Germany Hungary UD Kenezy Gyula University Hospital, Debrecen, Hungary Italy AOU Ospedali Riuniti, Ancona, Italy Infectious Diseases Unit, Bergamo, Italy San Giuliano Hospital – ASL Napoli 2 Nord, Naples, Italy Clinica Malattie Infettive, Università Politecnica delle Marche, Ancona, Italy SIMIT (Italian Society of Infectious Diseases and Tropical Medicine), Italy AOU Mater Domini, Catanzaro, Italy AOU Policlinico Giaccone, Palermo, Italy AOU Policlinico S. Orsola-Malpighi, Bologna, Italy ASUR Marche Area Vasta 4, Fermo, Italy AULS Toscana Centro, Pistoia, Italy Instituto Giannina Gaslini, Genova, Italy O.C. ‘Dell’Angelo’, Mestre-Venezia, Italy Ospedali Galliera, Genova, Italy Ospedale Policlinico Consorziale, Italy Ospedale San Bortolo, Vicenza, Italy Santa Maria della Misericordia, Italy Università Vanvitelli, Italy Spain Hospital Universitario Ramón y Cajal, Madrid, Spain Eastern Mediterranean Region Iran (Islamic Republic of) Shiraz University of Medical Sciences, Shiraz, Iran Jordan King Abdulla University Hospital, Ar-Ramtha, Jordan Prince Hamza Hospital, Amman, Jordan Pakistan Indus Hospital Research Center, Karachi, Pakistan Saudi Arabia King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia Western Pacific Region China Prince of Wales Hospital, Hong Kong Special Administrative Region, China School of Public Health, Capital Medical University, Beijing, China Republic of Korea National Medical Centre, Seoul, Republic of Korea Singapore National Centre for Infectious Diseases, Singapore National Institute of Communicable Diseases, Singapore