Global status report on the public health response to dementia Web Annex Methodology for producing global dementia cost estimates Global status report on the public health response to dementia. Web Annex. Methodology for producing global dementia cost estimates ISBN 978-92-4-003326-9 (electronic version) © World Health Organization 2021 Some rights reserved. This work is available under the Creative Commons Attribution- NonCommercial-ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this work, there should be no suggestion that WHO endorses any specific organization, products or services. The use of the WHO logo is not permitted. If you adapt the work, then you must license your work under the same or equivalent Creative Commons licence. 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It is being made publicly available for transparency purposes and information. iii Acknowledgements The development of this technical document overseen by Tarun Dua and Katrin Seeher (Brain Health Unit). The document was developed by Anders Wimo (Karolinska Institute, Sweden) and Rodrigo Cataldi (Brain Health Unit), with inputs from Joe Dielemann (Institute for Health Metrics and Evaluation, United States of America); Oskar Frisell (Linköping University, Sweden); Maëlenn Guerchet (French National Research Institute for Sustainable Development, France); Linus Jönsson (Karolinska Institute, Sweden); Martin Knapp (London School of Economics, United Kingdom of Great Britain and Northern Ireland); Angeladine Kenne Malaha (University of Limoges, France); Emma Nichols (Institute for Health Metrics and Evaluation, United States of America); and Martin Prince (Kings College London, United Kingdom). For further information about the estimates and methods, please contact whodementia@who.int. iv Abbreviations ADI Alzheimer’s Disease International ADLs (basic) Activities of daily living bUS$ Billion US dollars DMC Direct medical costs DSC Direct social costs DWCD Dementia Worldwide Cost Database GBD Global Burden of Disease GDO Global Dementia Observatory GDP Gross Domestic Product GLM General linear model GNI Gross National Income HICs High-income countries HICPs Harmonized Indices of Consumer Prices IADLs Instrumental activities of daily living IHME Institute for Health Metrics and Evaluation LMICs Low- and middle-income countries LTIC Long-term institutional care MeSH Medical subject headings OECD Organisation for Economic Co-operation and Development PPP Purchase Power Parities PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses SHA System of Health Accounts STRiDE Strengthening responses to dementia in developing countries () UN United Nations WAR World Alzheimer Report WB World Bank WHO World Health Organization v Contents Acknowledgements iii Abbreviations iv 1. Introduction 1 2. Approaches to data gathering 1 2.1 Systematic review of published literature 1 2.2 Global Dementia Observatory (GDO) indicators 2 2.3 Work by others 2 2.4 Aggregate and person-level data 2 2.5 Prevalence sources 3 2.6 The viewpoint 3 2.7 Costs 3 2.7.1 Direct medical costs 4 2.7.2 Direct social costs 4 2.7.3 Indirect costs and informal care 4 2.7.4 Severity of dementia 5 2.8 Representativity of studies 6 2.9 Cost inflation 6 2.10 Currency transformation 7 2.11 Missing data and imputations 7 2.12 Regional and income classifications & included countries 9 2.12.1 WHO regions (194 countries) 10 2.12.2 World Bank classification 11 2.12.3 Global Burden of Disease regions (GBD) 11 Appendices 12 Appendix 1. PRISMA diagram: Search results for cost studies 12 Appendix 2. PRISMA diagram: Search results for informal care studies 13 Appendix 3. Check-lists for judgement of papers on costs and informal care cost studies 14 Appendix 4. Other types of studies used in this report 15 Appendix 5. References and how they are used in the report. 16 Appendix 6. Imputation status 24 References 31 1 1. Introduction People with dementia use resources and get support in several sectors in society. Thus, data inputs from several sources are necessary for the estimate of the costs of dementia on a societal level, including all relevant costs in different sectors of society (both in terms of formal and informal care). Since many people with dementia are not identified or known in registries, in most countries it is necessary to use multiple sources to make an estimate of the societal costs of dementia. Furthermore, since care for people with dementia is organized and financed in different ways in different countries (and sometimes also in different ways within countries), the potential list of resources and support that is used and sources through which this information is available is extensive. 2. Approaches to data gathering Data gathered here pertains to indicator 27 of the Global Dementia Observatory, the following approaches were used to obtain data on resource use and costs for the calculation of cost estimates. 2.1 Systematic review of published literature A systematic review of published papers and reports, as in World Alzheimer Report (WAR) 2010 (1). In WAR 2010 the search was done in PubMed/Medline, Ingenta, Cochrane Library, NHSEED/HTA, HEED, EMBASE, Current contents, PsycINFO, ERIC, Societal services abstracts and Sociological abstracts. The search terms (MESH/subheadings when appropriate) were dementia/Alzheimer’s disease/Alzheimer disease combined with cost and/or economic and informal care. The cost estimates that are presented in this report are now based on an update of the Dementia Worldwide Cost Database (DWCD), which have been used in previous global cost estimates (1-9). There were separate search rounds for costs and informal care in the databases PubMed, EMBASE, PsychINFO, HEED, Societal services abstracts and Sociological abstracts. For cost studies, the following terms were used: ("Dementia"[Mesh] OR "Alzheimer Disease"[Mesh]) AND ("Costs and Cost Analysis"[Mesh] OR "Economics"[Mesh] OR "Cost of Illness"[Mesh]). For informal care, the search terms were "patient care"[MeSH Terms] OR “Informal care”[Text Word]) in combinations with ("Economics"[Mesh]), “Hours” [Text Word], “caregiving time”[Text Word] The search period was 2009 to January 2019 (it was assumed that the search results for the 2010 estimates were appropriate). The process is reported in terms of PRISMA. A stepwise process for identifying relevant papers was applied: Title screening-abstract screening and full- text screening (10). The stepwise process applied to the search results is described in Appendix 1 (cost studies) and Appendix 2 (informal care). Check-lists for the judgement of papers are seen in Appendix 3. Besides these two main approaches, peer-reviewed publications were also used such as population-based 2 top-down studies of high quality, literature describing dementia severity and describing costs attributed to dementia. Available literature was also used for characterization of caregivers, as well as of long-term institutional care (LTIC). See Appendix 4 for detailed information on the publications. These peer-reviewed publications were used for both estimates of direct costs and informal care. Publications that did not fit the modelling approach were not included even though they were of good quality. To make relevant estimates for the report, recalculations and extractions have been made, based on results in many studies. For some studies, authors have been contacted and have provided additional data. Since many countries and some regions lack of data, some additional papers have also been included after the search period. Besides the prevalence inputs (see that section), 163 studies were used in this report (Appendix 5). 2.2 Global Dementia Observatory (GDO) indicators Relevant GDO indicators were leveraged to provide further information about care system resources and volumes of resource use to be included in the overall economic cost algorithm (such as GDO indicators 8, 9.2.2, 9.6 and 16). 2.3 Work by others Work by other institutions such as the OECD and results from international research projects such as the 10/66 group (11) and the United Kingdom initiative Strengthening responses to dementia in developing countries (STRiDE) (12), which aims to perform field studies in seven middle-income countries are also important sources for data on resource use and costs. Furthermore, personal communications with a range of different researchers regarding their ongoing research, as well as information from another systematic review (in progress)(13) focusing on LMICs have been added to supplement the analysis. 2.4 Aggregate and person-level data There are two ways to obtain data on resource use and costs of dementia: on a person-level or on an aggregated (national) level. These two approaches are interrelated: to obtain national-level costs from person-level costs, the costs per person are multiplied by the number of people with dementia; to obtain person-level cost from aggregated costs, such costs are divided by the number of people with dementia. Both ways assume that used samples of people with dementia are representative for the dementia population in a specific country. Aggregated data are often generated (and recalculated) from national registries. The person-level corresponds roughly to the “bottom-up” concept in health economics, while the aggregated level reflects the “top-down” concept. For the purpose of this report, both person-level and aggregated national-level data were used. 3 2.5 Prevalence sources The methodology used takes advantage of a prevalence-based approach. As previously described, estimates on the number of people that live with dementia in different countries and regions are essential for cost estimates. To obtain data on the number of people with dementia in each World Health Organization (WHO) Member State, country specific and age-specific prevalence in 5-year groups was multiplied by corresponding population data in each country. Dementia prevalence figures are based on Chapter 3 of the Global status report on the public health response to dementia. In brief, these estimates were derived using age-specific prevalence data from the Global Burden of Disease (GBD) study 2019 by the Institute for Health Metrics and Evaluation (IHME) (14). World population prospects from the United Nations (UN) were used as source for the country-, and age- specific population data (15). 2.6 The viewpoint Any health economic analysis needs to have a clearly defined viewpoint. In early cost-of-illness studies, the focus was given to the health sector and indirect costs related to lost productivity of those affected by the disease of interest. This approach has its limitations as highlighted in a previously published WHO guide (16), especially in the context of dementia where the biggest drivers of direct costs are located outside the health sector (i.e. social care sector, informal care) and indirect costs are attributable to the family (informal carers) and not the person with dementia. With a societal viewpoint, all relevant costs and outcomes are included and costs for contributing sectors/ payers/ stakeholders described accordingly. Therefore, the viewpoint used for this report takes into account the societal costs, thereby including direct and indirect costs not only for persons with dementia, but also for families. Further descriptions of the type of costs and measures are described below. 2.7 Costs The opportunity cost is the value of a resource in its best alternative use. This is the value that should theoretically be assigned to a resource in a decision-making situation. Although basic in economics, it is not always easy to estimate the opportunity costs in all aspects of dementia care (17). Costs are also often divided into direct costs (referring to costs of resources used) and indirect costs (referring to costs of resources lost). To obtain a cost, a basic calculation is used: cost = resource use (units such as days, visits etc) multiplied with the unit cost for the specific resource. Throughout, the following cost definitions were used and aligned as much as possible with WHO’s System of Health Accounts (SHA): 4 2.7.1 Direct medical costs Direct medical costs (DMC) refer to the health care/medical care system, such as costs of hospital care, drugs, diagnostic tests, and visits to clinics (specialist care, primary care). 2.7.2 Direct social costs Direct social costs (DSC), sometimes labelled as “direct non-medical costs”, arise from formal services provided outside of the medical care system, commonly to assist with activities of daily living; for example, community services such as home care, food supply (‘meals on wheels’) and transport, and residential or nursing home care/long-term care. Depending on how care is organized, the boundaries between social and medical care may be blurry, and some ‘social care’ costs may still relate in part to medical care services, for example home nursing or nursing and medical care provided to care home residents. Whether long- term institutional care (LTIC) should be regarded as a part of the health care or social care sector is controversial since care in such facilities includes components of both. It has been suggested that support in personal (basic) activities of daily living (ADLs) should be regarded as a health sector activity and support in instrumental activities of daily living (IADLs) should be a part of the social care sector (18). This separation is problematic in dementia care since people with dementia have needs in both these domains (and also supervision needs), but at different proportions during the course of dementia. Thus, in this report, we considered LTIC costs as part of the DSC. 2.7.3 Indirect costs and informal care Indirect costs usually refer to productivity losses linked to the person with a given illness (arising from impaired productivity while working, sick leave, premature early retirement, or death). This type of indirect cost is generally less regarded as relevant in the context of dementia since most people with dementia are older and/or retired. However, as outlined above, an important driver in the societal costs of dementia is unpaid informal care provided by family members, friends, neighbours etc. It may also be related to productivity losses of informal carers of working age, making the costing issue crucial. The way of quantification and costing of informal care is methodologically challenging, and transparency is crucial to make comparisons possible. It is also not easy to classify informal care in terms of direct or indirect costs, since in some countries a proportion (usually a very small proportion of the total contribution) of care by family members may be paid (which then can partly be classified as a direct cost). However, to ensure the closest representation and due to lack of data on this matter, this report considers all informal care as an indirect cost. The basic cost model for informal care presented in Chapter 3 of the Global status report on the public health response to dementia is based on studies with data on hours of informal care and not cost studies on informal care (although several studies include both). Given that costing estimates of informal care are very heterogenous, basing these estimates on hours was considered to be more robust. 5 The hourly care contribution by informal carers can be described in three domains: support in personal/basic ADLs (such as eating hygiene, toilet visits, dressing), support in IADLs (more complex activities such as shopping, preparing food, economic transactions etc) and supervision (to prevent, for example, dangerous events). In the base option in this report, the focus is on the aggregated ADL- support (basic and instrumental). In a next step, hourly costs at country level were used. Finally, costing analyses have also considered the proportions of informal carers (partners) that are retired or no longer in working age, as well as children (and children-in-law), assumed to be of working age. Due to the heterogeneity of available input sources, various ways of costing informal care and challenges such as valuing productivity losses, leisure time and caregiving time by retired persons (19), were taken into consideration. The base option is to use separate female and male inputs for hours and their related costs as previously reported (1, 4). The earning inputs were derived from International Labour Organization (ILO) statistics (20). In the base option average monthly earnings are used, to ensure comparability with previous reports (1, 4). Figures in the database that were clearly invalid were excluded. To highlight the burden on families by other metrics and not only costs, the aggregated hours of informal caring time, the average time per day spent caring and the female proportion in caring time are also presented and disaggregated by WHO regions. Furthermore, these amounts of hours are also transformed to corresponding fulltime workers. Working time is a complex concept with a great variability across the world (21). Here we use an assumption that an annual full-time working time is 2,000 hours. This way of presenting informal care has been used in a previous report from ADI (22). 2.7.4 Severity of dementia There is a close relationship between dementia severity and resource use and costs. IHME has provided estimates of how dementia severity is distributed in all countries (percentages), which were applied on the country specific prevalence figures. In total, there were 67 studies in the database describing aspects of dementia severity, of which 32 studies described costs from 20 individual countries and 3 multinational studies, and 55 studies describing amounts of informal care (all ADLs) from 21 countries (and 2 multinational). 26 studies presented data on both direct costs and informal care. In the final severity cost model, 56 studies were used: 18 with both data on costs and informal care, 32 with data on informal care only and 6 with cost data only. The studies that describe economic aspects of dementia severity are not identical to the studies that were used for the cost estimates without severity aspects, therefore the cost estimates are different. The distribution of dementia severity differs according to living situation; at home versus in LTIC. At home the distribution is towards milder cases and in LTIC towards more severe cases. Particularly for informal care, there is a risk of overestimation of costs if the general severity distribution is applied since most people with dementia live at home. Thus, when possible, and this is of particular importance for HIC, the 6 distribution vs severity for the home staying population in the community is used. For this purpose, and based on a scoping review, population-based studies or selected top-down studies with community data on severity have been derived for the following countries: Australia (23, 24) , Canada (25, 26), the United States of America (27-30), Japan (31, 32), Germany (33, 34), France (35), Sweden (36, 37) and the United Kingdom (38). Extracted data have also been used for imputation in other HICs. For Latin America there is similar information available (39) that was used for imputation in for those countries. This approach was applied to 61 countries. For other countries, mainly LMICs, it is assumed that only people with severe dementia live in LTIC, resulting in slight adjustments (since the assumed LTIC is so sparse) from the IHME severity figures to get estimates of severity distribution in the community. For those LMICs where no LTIC is assumed to exist, the IHME severity distribution is applied. 2.8 Representativity of studies In many of the sources for the global cost estimates there are problems in terms of generalization. Many bottom-up studies are based on convenience or clinical samples, making the representativity questionable or difficult to predict. Register-based studies are often large, but per definition assume that individuals are known to the systems that register them. In some studies, it might be difficult to identify sample types. In general terms, cost estimates based on samples that are not population-based have a risk of overestimating costs since people that are not known to the care system (and therefore assumed to have a lower use of resources) are not represented in such studies. These risks are lower in population-based studies or some top-down studies (or combined top-down and bottom-up studies) where the prevalence is known, and costs are distributed over that population. The criteria used in this report to define the population representation was that the individuals participating in a given study represented a general population of dementia in a target area (most often a country) and not only a segment of it. The biggest drawback here is that such studies are not common: only 30 (see Appendix 5), of which 28 are from high-income countries (HICs), which consequently makes the generalizability problematic. 2.9 Cost inflation The year for which data on resource use and costs are collected varies considerably. Thus, a method to inflate costs to a basic cost year is needed. The cost year considered in the report is 2019. In order to standardize health and/or social care costs across countries over time, a price index must be used. The Statistical Office of the European Communities, Eurostat, presents Harmonized Indices of Consumer Prices (HICPs) for different sectors in society, including health care. However, as they are not available at a global level, such an approach cannot be utilized for the purpose of this report and instead, a globally available consumer price index was used. Costs are inflated to 2019 by the use of Inflation, average consumer prices, derived from International Monetary Fund, World Economic Outlook Database (40). 7 2.10 Currency transformation Data on costs from different parts of the world are often presented in terms of the local currency and/or as US$ and/or €. Thus, it is necessary to use a method to express costs in a uniform way. Usual currency exchange rates reflect trade between countries rather than purchasing power, which Purchase Power Parities (PPPs) do (41). With the PPP approach, an international dollar is used as a standard metric, equalizing the purchasing power of different currencies for a given basket of goods. For the global aggregated cost estimates of diseases there is no simple solution. Using PPPs is more useful than exchange rates when comparing differences in living standards between countries as PPP takes into account the relative cost of living and the inflation rates of countries, while exchange rates may skew differences in income. However, the use of PPP may be more questionable from a global viewpoint with aggregated costs. Previous global cost estimates for dementia (3,4) used currency exchange rates and costs expressed as US$. To allow for comparability, the same approach was used for Chapter 3 of the Global dementia status report: exchange rates are used in the base option, while PPPs are used for country comparisons. However, no aggregated results based on PPPs are presented. 2.11 Missing data and imputations Although the updated systematic review resulted in more and better data on resource use and costs than in previous studies, there are still incomplete and missing data from many countries, particularly LMICs. There are several challenges in imputation resource use data with various statistical approaches (42). In Tables 1 and 2, the imputation status vs the World Bank (WB) classification is summarized. Proportions of imputed costs are strongly related to World Bank income level (Table 1). The low imputation proportion of costs in high-income countries is due to the fact that the countries with the largest dementia populations in high-income countries (such as the United States of America, Japan and Germany) also monitor and publish cost data. Table 1. Amounts and proportions of costs that are imputed. Base option Imputed direct costs Imputed informal care cost All data imputed WB 2019 Direct costs Informal care Total costs bUS$ % bUS$ Per cent bUS$ % Low- income 0.6 2.6 3.2 0.6 100.0 2.6 100.0 3.2 100.0 Lower- middle- income 14.0 28.1 42.1 8.8 62.9 25.6 91.2 26.9 64.0 8 Upper- middle- income 100.8 179.8 280.5 23.9 23.7 40.3 22.4 58.9 21.0 Low- and middle- income 115.4 210.5 325.9 33.3 28.9 68.6 32.6 89.1 27.3 High- income 544.8 416.6 961.5 10.8 2.0 22.9 5.5 26.0 2.7 Total 660.2 627.1 1287.3 44.1 6.7 91.5 14.6 115.1 8.9 In lower-middle-income countries most data are imputed and in low-income countries all data are imputed (Table 2). Table 2. Imputation level of countries in the different WB-classes. Direct costs Informal care (all ADL) Any imputation All imputation All countries WB 2019 n (countries) % n (countries) % n (countries) % n (countries) % n (countries) Low- income 29 100.0 29 100.0 29 100.0 29 100.0 29 Lower middle- income 47 95.9 45 91.8 48 98.0 44 89.8 49 Upper- middle- income 46 82.1 52 92.9 53 94.6 45 80.4 56 Low- and middle income 122 91.0 126 94.0 130 97.0 118 88.1 134 High- income 30 50.0 35 58.3 36 60.0 30 50.0 60 Total 152 78.4 161 83.0 166 85.6 148 76.3 194 For previous global dementia cost estimates (1,3), several imputation approaches were used. For missing direct costs, a regression model was used (r2=.43; p<0.001), assuming a relationship between GDP per capita and direct costs of dementia care per capita, as a basis for imputation (similar to the relationship between GDP per capita and health expenditures per capita). For informal care, amounts of informal care were imputed from nearby countries with similar care structure from which data on informal care was available. In Appendix 6, the imputation status at country level is summarized. Many countries completely lack data, and most are LMICs. 9 For the updated dementia cost estimates in Chapter 3 of the Global dementia status report, two mixed model approaches for imputation have been used for countries without data. For direct costs, it was assumed that the GBD classification to some extent reflects both income level and cultural and organizational aspects in a better way than only utilizing data from the World Bank classification or GDP/capita would. The GBD-method is used in the base model while a mixed GLM model with a gamma distribution and a log link was tested in the sensitivity analysis since it was deemed difficult to obtain data on relevant covariates across all countries worldwide. Highly relevant information from a dementia care perspective such as countries’ LTIC, health care organization, workforce capacity (both in terms of number and competence) as well as dementia diagnostic rates is very sparse. Data such as GDP/capita, sociodemographic and socioeconomic indices also highly intercorrelate with each other. However, since there are differences also within the GBD-groups, cost estimates were adjusted (GDP per capita in a country in a particular GBD was regionally adjusted for the population weighted GDP/capita in that GBD-region). Data on direct costs were available from 14 out of 21 GBD regions. Asia South was used for imputation for Asia Central (and adjusted for GDP/capita as above). There are particularly few studies from Africa; none at all on cost and only some studies on informal care. To mitigate this lack of data, the following approach was used: the work by ADI and the 10/66 has produced valuable inputs of data about dementia care in LMICs (43). A thesis based on 10/66 countries included data on dementia costs. These data were adjusted for GDP/person and have been used for the imputation of direct costs for Sub-Saharan African countries (44) (although none of these six countries were in Africa). Data from 10/66 was used also for Oceania. In this regard, pending results from the ongoing STRiDE-project will be of great value to close existing data gaps. All input cost data were also weighted for dementia severity distribution in each country. Hourly figures of informal care were available from countries representing ten of the 21 GBD regions. Available data from GBD-regions adjusted for the severity distribution of people with dementia living at home but not for GDP per capita, were used to impute data for countries in similar GBD regions. In the Sub-Saharan African regions where data was not available (Central, East and Southern), hourly figures from West Africa were used. Hourly figures from East Asia were used for the Central, South, Southeast Asia and Oceania. For the Andean, Central and Caribbean regions in Latin-America hourly figures from Tropical Latin-America were used. 2.12 Regional and income classifications & included countries In previous global dementia cost estimates (3,4), two ways to classify countries were used: the World Bank (WB) classification (based on Gross Domestic Income, GDI) and Global Burden of Disease (GBD) world regions. 10 Throughout the report, the six WHO regions, the World Bank classification and the GBD regions are used. All analyses are based on the 194 WHO member states. 2.12.1 WHO regions (194 countries) African Region: 47 countries Algeria, Angola, Benin, Botswana, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros (the), Congo, Côte d'Ivoire, Democratic Republic of the Congo, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, Gabon, 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, South Sudan, the Gambia, Togo, Uganda, United Republic of Tanzania, Zambia, and Zimbabwe. Region of the Americas: 35 countries Antigua and Barbuda, Argentina, Bahamas (the), Barbados, Belize, Bolivia (Plurinational State of), Brazil, Canada, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic (the), Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, United States of America, Uruguay, and Venezuela (Bolivarian Republic of). South-East Asia Region: 11 countries Bangladesh, Bhutan, Democratic People's Republic of Korea, India, Indonesia, Maldives, Myanmar, Nepal, Sri Lanka, Thailand, and Timor-Leste. European Region: 53 countries Albania, Andorra, Armenia, Austria, Azerbaijan, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Luxembourg, Malta, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Republic of Moldova, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Tajikistan, Turkey, Turkmenistan, Ukraine, United Kingdom of Great Britain and Northern Ireland (the), and Uzbekistan. Eastern Mediterranean Region: 21 countries Afghanistan, Bahrain, Djibouti, Egypt, Iran (Islamic Republic of), Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Qatar, Saudi Arabia, Somalia, Sudan, Syrian Arab Republic, Tunisia, United Arab Emirates, and Yemen. Western Pacific Region: 27 countries Australia, Brunei Darussalam, Cambodia, China, Cook Islands, Fiji, Japan, Kiribati, Lao People's Democratic Republic, Malaysia, Marshall Islands, Micronesia (Federated States of), Mongolia, Nauru, New Zealand, Niue, Palau, Papua New Guinea, Philippines, Republic of Korea, Samoa, Singapore, Solomon Islands, Tonga, Tuvalu, Vanuatu, and Viet Nam. 11 2.12.2 World Bank classification The WB classification is based on Gross National Income (GNI) per capita (Atlas method) (45),and subdivided in four levels: low-income, lower-middle-income, upper-middle-income and high-income countries. Low- income, lower-middle-income and upper-middle-income are in some analyses aggregated as low-and- middle income countries. Since GNI per capita change, this classification system is dynamic and changes over time; and thus continuous updates are needed. Comparisons over time are then more complicated since the countries may be “upgraded” or “downgraded”. 2.12.3 Global Burden of Disease regions (GBD) Table 3 lists the 21 GBD regions used in the analyses Table 3. GBD regions Australasia Caribbean Asia Pacific High Income Latin America Andean Oceania Latin America Central Asia Central Latin America Southern Asia East Latin America Tropical Asia South North Africa / Middle East Asia Southeast Sub-Saharan Africa Central Europe Western Sub-Saharan Africa East Europe Central Sub-Saharan Africa Southern Europe Eastern Sub-Saharan Africa West North America High Income Country-level cost estimates will be produced for WHO Member States, associate members, areas and territories, to the extent possible. 12 Appendices Appendix 1. PRISMA diagram: Search results for cost studies Included from 2010 and 2015: n=28 Final data set: n=64 Removed duplicates: Excluded after 1st round n=1,768 n=37 Search total all databases: n=5,451 Screened for title: n=3,683 Excluded after title screening: n=3,353 Screened abstract: n=330 Screened full text: n=172 Excluded after abstract screening: n=158 Excluded after full text screening: n=99 Included 1st round n=73 Included: n=36 13 Appendix 2. PRISMA diagram: Search results for informal care studies New papers from Included from 2010 secondary sources: n=27 and 2015: n=49 Included 1st round Included 2nd round New dataset: n=66 Final dataset: n=115 n=50 n=39 Any informal care study Excluded after 1st round n=11 Search PubMed: n=825 Removed duplicates: n=205 Screened for title: 620 Non-english: n=59 obviously not relevant: n=377 Screened for abstract: n=184 Removed after abstract screening: n=92 Screened full text: n=92 Excluded full text: n=42 14 Appendix 3. Check-lists for judgement of papers on costs and informal care cost studies Author(s) Title Year Journal Country Costing year Currency Sampling 1 = Population based, 2=Clinical 3=convenience, Viewpoint 1= societal, 2= nonsocietal, 3 = both Top down or bottom up 1= top down, 2= bottom up, 3= Mix 4= not reported Gross/Net 1 = Net cost , 2= gross cost, 3= both or not reported Prevalence/Incidence 1= prevalence, 2= incidence, 3 = not reported Direct medical costs 1= yes, 2= no Direct social sector costs 1= yes, 2= no Direct costs 1= yes, 2= no Patient production losses patients 1= yes, 2= no Informal care Basic ADLs 1= yes, 2= no Instrumental ADLs 1= yes, 2= no Supervision 1= yes, 2= no Unspecified 1= yes, 2= no Severity 1= mild, 2= moderate, 3= Severe, 4 = all, 5= not specified Notes Informal care Author Title Year Journal Country Costing year Currency Sampling 1=Population based 2=Clinical 3=Convenience 4=other Informal care Basic ADLs 1=Yes 2=No Instrumental ADLs 1=Yes 2=No Supervision 1=Yes 2=No Unspecified 1=Yes 2=No Dementia severity 1=Mild 2=Moderate 3=Severe 4=All 5=Unspecified Hours 1=Yes 2=No Cost 1=Yes 2=No Notes 15 Appendix 4. Other types of studies used in this report Item of interest Used in 2010 and 2015 estimates New for 2019 estimates Total Caregiver status 29 54 83 LTIC 15 19 34 Population based /Top down 20 12 32 Severity of dementia 29 38 67 Costs attributed to dementia 5 5 10 16 Appendix 5. References and how they are used in the report. Carer characteristics Used in WAR Added in WAR World Bank Direct medical Direct social Direct costs ADLs IADLs All ADLs Super- vision Total Sex Spou se Child Workin g LTIC Population based or Reference 2010 2015 Country 2019 costs costs all hours hours hours hours hours % % % % % Top down Severity Net costs (46) x Argentina 2 x x x . . x . . . . . . . . x (47) Argentina 2 x x x . . . . . . . . . . . . (48) x Australia 1 x x x . . x . . . . . . . x x (49) Australia 1 . . . . . . . . . . . . x . . (50) x Australia 1 . . . . . . . . x x x . x . . (23) Australia 1 x x x . . . . . x x x x x x x (24) Australia 1 . x . . . . . x . . . . . x x (51) Australia 1 x (52) x Australia 1 . . . . . x . . . . . . . . . (53) x Belgium 1 x x x . . . . . . . . . . . . (54) x Brazil 2 . . . . . x . . x x x . . . . (55) Brazil 2 x x x x x x x x x x x x . . x (25) Canada 1 x (26) Canada 1 x (56) x Canada 1 x x x . . . . . . . . . x x . (57) x Canada 1 x x x . . x x x . . . . . x x (58) x Canada 1 x x x x x x . . . . . . . x x x (59) Canada 1 x x x . . . . . . . . . . x . (60) Chile 1 x x x . . . . x x . . x . . . (61) China 2 x x x . . . . . . . . . . . . (62) x China 2 . . . . . . . x x . . . . . . (63) China 2 x x x . . x . x . . . . x . . (64) x China 2 x x x . . x . . . . . . . . x (65) x China 2 . . . x x x x x x x . . . . x (66) China 2 x x x . . . . . . . . . . . . (67) Colombia 2 x . . . . . . . . . . . . . x 17 (68) Congo 3 . . . . . . . x x x x . x . . (69) x Cyprus 1 . . . . . . . . x x x . . . . (70) Czechia 1 . . . . . . . x . . . . . . . (71) Czechia 1 x x x x x x x x x . . . x . x (72) Denmark 1 . . . x x x x x x x x x . . . (73) x Denmark 1 x x x . . . . . . . . . x . x x (74) Denmark 1 . . . x x x x x . x x . . . x (75) Finland 1 . . . . . . . x . . . . . . x (76) Finland 1 x . . . . . . . . . . . . x . x (35) France 1 x (77) x France 1 x x x . . . . x . . . . . . x (78) x France 1 . . . . . . . . x x x . . . . (79) x France 1 x x x . . . . x . . . . . . x (80) France 1 . . . x x x x x . x x . . . . (81) x France 1 x x x . . x . . . . . . . x x (82) France 1 . . . x x x x x x x . x . . . (83) France 1 x x x . . . . . x x . . . . x (84) France 1 . . . . . . . x x x x x . . . (85) France 1 . . . . . x x x . . . . . . x (86) France 1 x x x x x x . (33) x Germany 1 x x x . . . . x . . . . . x x x (87) Germany 1 . . . x x x x x x x x . . . x (88) Germany 1 . . . . . . . . x x x . . . . (34) Germany 1 x x x x x x x x x x x . . . x x (89) x Germany 1 . . . x x x x x x x x . . . . (90) Ghana 3 . . . x x x x x x x x . x . . (91) x Hungary 1 x x x x x x . . x x . x x . x (92) India 3 x x x . . . . . . . . . . . . (93) x India 3 . . . . . x . . . . . . . . . (94) Iran (Islamic Republic of) 2 x x x . . . . . . . . . x x (95) Ireland 1 . . . x x x x x . . . . . . . (96) x Ireland 1 x x x . . . . x . . . . x x . 18 (97) Ireland 1 . . . x x x x x . . . x . . x (98) Ireland 1 . . . x x x x x . . . x . . . (99) Ireland 1 x . . . . . . x . . . x . . . (100) x Israel 1 x x x . . x x x . x x . x . . x (101) Italy 1 . . . . . . . x x x x . . . x (102) x Italy 1 . . . . . x x x . x x . . . . (103) Italy 1 x x x x x x x x x x x . . . x (104) x Japan 1 . . . . . x . . x x x . . . . (32) Japan 1 . . . x x x x x x x x . . . x (31) Japan 1 x x X x x x x x x x x . . x x (105) Lebanon 2 . . . . . . . . x . . x . . . (106) Netherlands 1 . . . x x x x x x x . x . . . (107) Netherlands 1 x x x . . . . . x . x . x . . (108) Netherlands 1 x x x . . . . x x x . x . . . (109) New Zealand 1 x x x . . x . . . . . . x x . x (110) x New Zealand 1 . . . . . x . . . . . . . . . (111) x Nigeria 3 . . . . x x x x x . . . . . . (112) x Nigeria 3 . . . . . . . . x . . . . . . (113) x Norway 1 x x x . . . . . . . . . x x . (114) Philippines 3 x x x . . . . . . . . . . x . (115) Poland 1 . . . . . . . . x x x . . . . (116) Poland 1 . . . . . . . . x x x . . . . (117) Portugal 1 . . . . . . . . . . . . x . . (118) x Republic of Korea 1 x x x . . . . . x x . . x . x (119) Republic of Korea 1 . . . . . . . x x x x . . . . (120) x Republic of Korea 1 x x x . . x . . . . . . x . . (121) Romania 1 x x x x x x x x x x x (122) Russian Federation 2 . . . . . . . x . . . . . . . (123) x Russian Federation 2 . . . . . . . . x . . . . . . 19 (124) x Russian Federation 2 . . . . . . . . x . . . . . . (125) Singapore 1 x x x . . . . . . . . . x x . (126) Singapore 1 . . . x x x x x x x . x . . x (127) Singapore 1 . . . x x x x x x x x . x . . (128) Singapore 1 . . . . . . . . x x x . . . . (129) Spain 1 x x x . . . . . . . . . . . . (130) x Spain 1 x x x . . x x x . x x . x . . (131) Spain 1 x x x x x x x x x x . . . . x (132) x Spain 1 x x x x x x . . x x x . . . x (133) Spain 1 x x x x x x x x x x x . . . x (134) Spain 1 . . . . . . . x x . . x . . x (135) x Spain 1 . . . . . . . . x . . . . . . (136) Spain 1 . . . . . x . . x x x . . . x (137) Sweden 1 . . . . . . . x . . . . . . x (37) Sweden 1 x x x . . x x x . x x x x x . x (138) x Sweden 1 . . . . . x . . . . . . . . x (139) x Sweden 1 x x x x x x x x . . . . . . x (36) x Sweden 1 . . . . . x x x . . . . . x x (140) x Sweden 1 . . . x x x x x . . . . . . x (141) x Sweden 1 . . . x x x x x x x x . . . x (142) Switzerland 1 x x x . . . . . . . . . x x . (143) x Taiwan, China 1 . . . . . . . . . x x . . . . (144) Taiwan, China 1 . . . x x x x x x x x x . . . (145) x Thailand 2 . . . . . . . . x x x . . . . (146) Thailand 2 x x x x x x x x x x x x x (147) Tunisia 3 . . . . . x . . . . . . . . . (148) x Turkey 2 . . . x x x . . x x x . . . x (149) United Kingdom 1 . . . . . . . x . . . . . . x (150) x United Kingdom 1 . . . . . . . x . x x . . . x (38) x United Kingdom 1 x x x x x x x . . . . . . x x 20 (151) United Kingdom 1 . . . x x x x x x x x . . . . (152) x United Kingdom 1 . . . . . x . . . . . . . . . (153) x United Kingdom 1 . . . . . x . . . . . . . . . (154) x United Kingdom 1 x x x . . x . . . . . . . . . (155) United Kingdom 1 . . . . . . . . x . x . . . . (156) United Kingdom 1 x x x . . . . x x x x x x . . x (157) the USA 1 . . . . . . . x . . . . . . x (158) x the USA 1 . . . . . . . x . . . . . . x (159) the USA 1 . . . . . . . x . . . . . . . (160) the USA 1 . . . . . . . x . x x . . . . (161) the USA 1 . . . . . . . x . . x . . . . (162) the USA 1 x x x . . . . x . . . . . . . (163) x the USA 1 . . . . . . . . x x x . . . . (28) the USA 1 . . . . . . . x . . . . . x x (164) the USA 1 . . . . . . . x . . . . . . . (165) x the USA 1 x x x . . . . . . . . . . x . (166) x the USA 1 . . . . . x . . . . . . . . x (167) x the USA 1 . . . . . x . . . . . . . . . (168) the USA 1 . . . . . . . x . . . . . . x (169) x the USA 1 x x x . . . . x . . . . . x . x (27) x the USA 1 . . . . . x . . . . . . . x x (170) x the USA 1 . . . . . x . . . . . . . . x (29) the USA 1 X (30) the USA 1 X (171) x the USA 1 . . . . . x . . . . . . . . X (172) x the USA 1 . . . . . x . . . x x . . . x (173) x the USA 1 . . . . . x . . . . . . . . . (174) x the USA 1 . . . x x x x x x x x x . . . (175) x the USA 1 . . . . . x . . . x x . . . . 21 (176) x the USA 1 . . . . . x . . . . . . . x . (177) x the USA 1 . . . . . x . . . . . . x x . (178) x the USA 1 . . . . . x . . . . . . . x . (179) the USA 1 x (39) x Latin America x (180) Argentina, Czechia, Finland, France, Israel, Italy, Russian Federation, Spain, Sweden, Turkey, United Kingdom, the USA x x (181) Australia, Austria, Belgium, Czechia, Denmark, Estonia, France, Germany, Greece, Israel, Italy, Luxembourg, Netherlands, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, United Kingdom, the USA . . . . . . . . x . . . . . . (88) x Australia, Canada, Japan, Sweden, the USA, Germany . . . . . . . . x x x . . . . 22 (182) Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom x x x . . . . x . . . x x x . (183) x Belgium, Denmark, Finland, France, Germany, Ireland, Norway, Sweden x x x x (184) x Belgium, Denmark, France, Germany, Greece, Italy, Netherlands, Romania, Spain, Sweden, Switzerland, United Kingdom . . . x x x x x . . . . . . . (43) x China, Cuba, Dominican Republic, India, Mexico, Peru, Puerto Rico, Venezuela (Bolivarian Rep. of) . . . x . . x . x x x . . x . (44) X China, Cuba, Dominican x x x x x 23 Republic, India, Mexico, Peru, Puerto Rico, Venezuela (Bolivarian Rep. of) (185) Estonia, Finland, France, Germany, Netherlands, Spain, Sweden United Kingdom x x x . . . . x x . . . x . x (186) x Finland, Norway x x x . . . . . . . . . x . . (187) France, Germany, United Kingdom x x x x x x x x x x x . . . x (188) Germany, Ireland, Italy, Netherlands, Norway, Portugal, Sweden x x x x x x x x x x x . . . . (189) Spain, Sweden, United Kingdom, the USA x x x . . x . . . . . . x . x (190) Spain, Sweden,United Kingdom, the USA . . . . . . . x x x x x . . . (1) Global x x x x x x x x x x x x 162 studies 62 61 59 41 40 76 44 77 66 63 57 23 32 29 65 10 24 Appendix 6. Imputation status 1=data imputed. 0=data not imputed. For single countries. several sources may have been used. Direct Female Spouse Child Working medical social costs ADL IADL All ADL Supervision Total caregiver caregiver caregiver caregiver LTIC Severity Country costs costs all hours hours hours hours hours % % % % % costs Afghanistan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Albania 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Algeria 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Andorra 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Angola 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Antigua and Barbuda 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Argentina 0 0 0 1 1 1 1 0 1 1 1 1 1 0 Armenia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Australia 0 0 0 1 1 0 0 0 0 0 0 0 0 0 Austria 0 0 0 1 1 1 1 1 0 1 1 1 1 1 Azerbaijan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Bahamas, The 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Bahrain 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Bangladesh 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Barbados 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Belarus 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Belgium 0 0 0 0 0 0 0 0 0 1 1 1 1 1 Belize 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Benin 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Bhutan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Bolivia (Plurinational State of) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Bosnia and Herzegovina 1 1 1 1 1 1 1 1 1 1 1 1 1 1 25 Botswana 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Brazil 0 0 0 0 0 0 0 0 0 0 0 0 1 0 Brunei Darussalam 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Bulgaria 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Burkina Faso 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Burundi 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Cambodia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Cameroon 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Canada 0 0 0 0 0 0 0 0 0 0 0 0 1 0 Cabo Verde 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Central African Republic 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Chad 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Chile 0 0 0 1 1 1 1 0 0 1 1 0 1 1 China 0 0 0 0 0 0 0 0 0 0 1 1 0 0 Colombia 0 1 1 1 1 1 1 1 1 1 1 1 1 0 Comoros 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Congo, Democratic Republic of (the) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Congo, Republic of (The) 1 1 1 1 1 1 1 0 0 0 0 1 1 1 Cook Islands 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Costa Rica 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Côte d'Ivoire 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Croatia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Cuba 0 0 0 0 1 1 0 1 1 1 1 1 1 1 Cyprus 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Czechia 0 0 0 0 0 0 0 0 0 1 1 1 0 0 Democratic People's Republic of Korea (The) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Denmark 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Djibouti 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Dominica 1 1 1 1 1 1 1 1 1 1 1 1 1 1 26 Dominican Republic 0 0 0 0 1 1 0 1 1 1 1 1 1 1 Ecuador 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Egypt 1 1 1 1 1 1 1 1 1 1 1 1 1 1 El Salvador 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Equatorial Guinea 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Eritrea 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Estonia 0 0 0 1 1 1 1 0 0 1 1 1 0 0 Eswatini 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Ethiopia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Fiji 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Finland 0 0 0 1 1 1 1 0 0 1 1 1 0 0 France 0 0 0 0 0 0 0 0 0 0 0 0 1 0 Gabon 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Gambia, The 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Georgia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Germany 0 0 0 0 0 0 0 0 0 0 0 1 1 0 Ghana 1 1 1 0 0 0 0 0 0 0 0 1 1 0 Greece 0 0 0 0 0 0 0 0 0 1 1 1 1 1 Grenada 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Guatemala 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Guinea 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Guinea-Bissau 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Guyana 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Haiti 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Honduras 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Hungary 0 0 0 0 0 0 1 1 0 0 1 0 0 0 Iceland 1 1 1 1 1 1 1 1 1 1 1 1 1 1 India 0 0 0 0 1 0 0 1 1 1 1 1 1 1 Indonesia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Iran, Islamic Republic of 0 0 0 1 1 1 1 1 1 1 1 1 1 1 27 Iraq 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Ireland 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Israel 0 0 0 1 1 0 0 0 0 0 0 1 0 1 Italy 0 0 0 0 0 0 0 0 0 0 0 1 1 0 Jamaica 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Japan 0 0 0 0 0 0 0 0 0 0 0 1 1 0 Jordan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Kazakhstan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Kenya 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Kiribati 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Kuwait 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Kyrgyzstan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Lao People's Democratic Republic 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Latvia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Lebanon 1 1 1 1 1 1 1 1 0 1 1 0 1 1 Lesotho 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Liberia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Libya 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Lithuania 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Luxembourg 0 0 0 1 1 1 1 1 0 1 1 1 1 1 Madagascar 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Malawi 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Malaysia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Maldives 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Mali 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Malta 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Marschall Islands 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Mauritania 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Mauritius 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Mexico 0 0 0 0 1 1 0 1 1 1 1 1 1 1 28 Micronesia (Federated States of) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Republic of Moldova 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Monaco 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Mongolia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Montenegro 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Morocco 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Mozambique 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Myanmar 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Namibia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Nauru 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Nepal 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Netherlands 0 0 0 0 0 0 0 0 0 0 0 0 0 0 New Zealand 0 0 0 1 1 0 1 1 1 1 1 1 0 1 Nicaragua 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Niger 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Nigeria 1 1 1 1 0 0 0 0 0 1 1 1 1 1 Niue 1 1 1 1 1 1 1 1 1 1 1 1 1 1 North Macedonia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Norway 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Oman 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Pakistan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Palau 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Panama 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Papua New Guinea 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Paraguay 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Peru 0 0 0 0 1 1 0 1 1 1 1 1 1 1 Philippines 0 0 0 1 1 1 1 1 1 1 1 1 1 1 Poland 1 1 1 1 1 1 1 1 0 0 0 1 1 1 Portugal 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Qatar 1 1 1 1 1 1 1 1 1 1 1 1 1 1 29 Republic of Korea 0 0 0 1 1 0 1 1 0 0 0 1 0 0 Romania 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Russian Federation 1 1 1 1 1 1 1 0 0 1 1 1 1 1 Rwanda 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Samoa 1 1 1 1 1 1 1 1 1 1 1 1 1 1 San Marino 1 1 1 1 1 1 1 1 1 1 1 1 1 1 São Tomé and Príncipe 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Saudi Arabia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Senegal 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Serbia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Seychelles 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Sierra Leone 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Singapore 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Slovak Republic 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Slovenia 1 1 1 1 1 1 1 1 0 1 1 1 1 1 Solomon Islands 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Somalia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 South Africa 1 1 1 1 1 1 1 1 1 1 1 1 1 1 South Sudan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Spain 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Sri Lanka 1 1 1 1 1 1 1 1 1 1 1 1 1 1 St. Kitts and Nevis 1 1 1 1 1 1 1 1 1 1 1 1 1 1 St. Lucia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 St. Vincent and the Grenadines 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Sudan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Suriname 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Sweden 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Switzerland 0 0 0 0 0 0 0 0 0 1 1 1 0 1 Syrian Arab Republic 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Tajikistan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 30 Thailand 0 0 0 0 0 0 0 0 0 0 0 1 0 0 Timor-Leste 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Togo 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Tonga 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Trinidad and Tobago 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Tunisia 1 1 1 1 1 0 1 1 1 1 1 1 1 1 Turkey 1 1 1 0 0 0 1 0 0 0 0 1 1 0 Turkmenistan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Tuvalu 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Uganda 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Ukraine 1 1 1 1 1 1 1 1 1 1 1 1 1 1 United Arab Emirates 1 1 1 1 1 1 1 1 1 1 1 1 1 1 United Kingdom (The) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 United Republic of Tanzania (The) 1 1 1 1 1 1 1 1 1 1 1 1 1 1 United States of America (The) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Uruguay 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Uzbekistan 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Vanuatu 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Venezuela (Bolivarian Rep. of) 1 1 1 0 1 1 0 1 1 1 1 1 1 1 Viet Nam 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Yemen, Republic of 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Zambia 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Zimbabwe 1 1 1 1 1 1 1 1 1 1 1 1 1 1 All 152 153 153 162 167 161 161 160 154 167 169 178 172 168 Imputation in countries as proportion of world dementia population 23% 24% 24% 27% 36% 27% 28% 30% 28% 34% 59% 77% 55% 35% 31 References 1. 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Global status report on the public health response to dementia: web annex: methodology for producing global dementia cost estimates
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