Summary
Background
The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020.
Methods
We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050.
Findings
In 2019, health spending globally reached $8·8 trillion (95% uncertainty interval [UI] 8·7–8·8) or $1132 (1119–1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40·4 billion (0·5%, 95% UI 0·5–0·5) was development assistance for health provided to low-income and middle-income countries, which made up 24·6% (UI 24·0–25·1) of total spending in low-income countries. We estimate that $54·8 billion in development assistance for health was disbursed in 2020. Of this, $13·7 billion was targeted toward the COVID-19 health response. $12·3 billion was newly committed and $1·4 billion was repurposed from existing health projects. $3·1 billion (22·4%) of the funds focused on country-level coordination and $2·4 billion (17·9%) was for supply chain and logistics. Only $714·4 million (7·7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34·3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448–1591) per person in 2050, although spending across countries is expected to remain varied.
Interpretation
Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all.
Funding
Bill & Melinda Gates Foundation.
Introduction
How much countries spend on health has long been of interest for relevance to a range of social and economic objectives, including the goal of providing essential health services and universal health coverage.1, 2, 3, 4, 5, 6 The COVID-19 pandemic has renewed interest in the past, present, and future of global health financing, in part because responding to the COVID-19 pandemic has been and continues to be tremendously costly. Governments around the world implemented restrictions on travel and mass gatherings; required masks and quarantines; and rolled out and ramped up access to COVID-19 testing, contact tracing, and, when possible, COVID-19 treatment.7, 8 Governments have fought to secure access to the first round of approved COVID-19 vaccines, with vaccination campaigns beginning in more than 30 countries in 2020, including China, Israel, Russia, Mexico, the USA, and the UK.9, 10, 11
Research in context.
Evidence before this study
The Global Burden of Disease Health Financing Collaborator Network and WHO have each published annual estimates of global health spending, with the former also publishing estimates of future health spending. So far, few research efforts have provided estimates of health spending associated with the COVID-19 pandemic, and these vary in their scope and completeness. The Economist Intelligence Unit's COVID-19 Health Funding Tracker provides visualisations of pledged and disbursed funding for pandemic response, although it does not include international commitments to individual countries or pledges less than US$2 million. The Kaiser Family Foundation Donor Funding for the Global Novel Coronavirus Response tracker is a tabulated database of funding pledged for the global response to COVID-19. This tracker has not been updated since April, 2020, and does not include resources for research and development or in-kind support. The Centre for Disaster Protection's database tracks funding from multilateral agencies and regional development banks for global humanitarian and development needs, but does not capture bilateral or private contributions. Devex's interactive website tracks funding committed toward addressing the health, social, economic, and environmental effects of the pandemic, but does not provide information on the disbursements of these funds. The COVID-19 Research Project tracker from the UK Collaborative on Development Research and the Global Research Collaboration for Infectious Disease Preparedness collates data on all research and development project commitments and maps these to WHO research priorities. Although these existing studies track various aspects of the funding targeted toward the pandemic response, none reports comprehensive tracking for the health sector.
Added value of this study
We track spending on health globally, providing estimates from 1990 to 2050. We focus mainly on novel estimates of development assistance for health for COVID-19 in 2020 and the ramifications that follow for funding other essential health areas. These estimates add value to trackers by focusing on 2020 disbursements, being as comprehensive as possible, and placing development assistance for health for COVID-19 in the context of past spending and projected future health spending.
Implications of all the available evidence
Since 1995, global health spending has increased constantly, but inequalities in spending remain. Our estimates suggest that although contributions have been forthcoming, there remains a gap in funding needed to fully address the effects of the pandemic in most low-income and middle-income countries, especially as vaccine roll-outs are initiated globally. Continued efforts are needed to raise the required resources to provide health care for the pandemic—prevention and treatment—for the most vulnerable. Beyond COVID-19, projected disparities in future health spending across income groups suggest an ongoing benefit of leveraging development assistance resources in promoting an equitable response to any future health emergencies.
Funding the pandemic response has been complicated by global economic recession, which has not spared low-income and middle-income countries.12 It was estimated that the global economy shrank by 3·3% in 2020, and the economies of low-income and middle-income countries (excluding China) shrank by 4·3%.13 Uncertainty is expected to linger as third and fourth waves sweep the globe and new COVID-19 variants spread with increasing speed.14, 15 Unemployment increased globally, and extreme poverty is estimated to have increased by between 88 and 115 million in 2020.16 Moreover, the economic consequences of the health crisis are leading to long-standing reductions in economic development in some countries, and further indirect adverse effects on health.4, 17, 18, 19, 20, 21
The response to the dual health and economic crises caused by COVID-19 generated substantial costs across countries. High-income countries and many middle-income countries have been able to finance their government programmes with financial reserves, reallocation of government resources, and by borrowing. The International Monetary Fund (IMF) estimates that globally, government debt increased by $20 trillion between Sept 1, 2019, and Sept 1, 2020.22 Although some low-income countries have also borrowed resources (obtaining loans at market rates) to fund their responses to the 2020 crises, development assistance plays a unique role in funding health systems during emergencies in many countries and can be a catalyst for rapidly scaling up novel health services.23
We estimated development assistance for health for COVID-19 in 2020, and assessed how that assistance compared with broader trends in health financing. We first present retrospective estimates of domestic spending on health and development assistance for health to provide context on the broader health financing landscape. Then we focus on development assistance for health and how it was used to target COVID-19 in 2020, and ramifications for development assistance for health funding in other essential health areas. We disaggregate estimates for development assistance for health for COVID in 2020 by funding sources, disbursing agencies, recipients, and programme areas to enable comparison with other key focus areas such as HIV/AIDS, health system strengthening, and pandemic preparedness. Finally, we generate estimates of future health spending to enable an assessment of the implications for future health financing.24, 25 Comprehensive health spending estimates are important for examining potential gaps in resource needs versus available funding.
Methods
Overview
Health spending can be disaggregated into four key financing sources: government, out-of-pocket, and prepaid private health spending, which collectively make up domestic health spending; and development assistance for health, which includes international disbursements for health to low-income and middle-income countries. Government health spending includes social health insurance and government public health programmes. Out-of-pocket health spending includes health-care spending by a patient or their household but excludes insurance premiums. Prepaid private health spending includes private insurance spending and spending by non-governmental agencies on health.
To estimate total health spending for 204 countries and territories, we estimated each of the four financing sources separately for the years that underlying data were available, and used past trends and relationships to forecast each financing source from the point where retrospective estimates end to the end of 2050. The primary data source for domestic spending financing streams was the WHO Global Health Expenditure Database (GHED), and retrospective estimates were made from 1995 to 2018. Development assistance for health was estimated by use of a diverse set of project and agency expenditure and revenue statements, and estimates extend from 1990 to 2020, with additional project-level databases used to generate special estimates of development assistance for health for COVID-19 in 2020 (appendix pp 26, 91). Forecasts for each financing source begin in 2019 or 2021. All estimates are inflation-adjusted and are mostly reported in 2020 US$, although some were adjusted for national prices and are thus reported in purchasing-power parity-adjusted US$ or relative to gross domestic product (GDP).
Estimating domestic health spending, 1995–2018
For government, out-of-pocket, and prepaid private health spending, we downloaded data from the GHED for all available countries in current national currency units.26 We adjusted these estimates for inflation, converted to 2020 US$, modelled estimates to ensure consistency over time and comprehensiveness across countries and territories, and estimated uncertainty (appendix p 21). We also converted these estimates into 2020 purchasing-power parity-adjusted US$. We used deflator series and exchange rate data based on data from the IMF World Economic Outlook.14
For each of the three domestic financing sources, we used the metadata provided by WHO to qualitatively assess the reliability of data extracted from the GHED. We assigned a weight to each downloaded datapoint according to the documented source information included in the metadata, completeness of metadata, and documented methods of estimation (appendix p 13). We then used a spatiotemporal Gaussian process model to generate a complete time series of data from 1995 until 2018 for each country, and calculated 95% uncertainty intervals (UIs).27, 28
Estimating development assistance for health, 1990–2020
Development assistance for health refers to the financial and non-financial resources that are disbursed through international development agencies to maintain or improve health in low-income and middle-income countries. We tracked these disbursements from their originating sources through their disbursing agencies to the health focus areas that these resources were designed to target in recipient countries. Originating sources were typically the national treasuries of donor governments or private philanthropies from which development assistance funds are transferred. The funds from originating sources are channelled through international development agencies, which are here referred to as the disbursing agency, before being disbursed to the recipient country. We relied on project-level disbursement data from major international development agencies' online databases, including the Organisation for Economic Cooperation and Development's Creditor Reporting System (OECD CRS), the Global Fund to Fight AIDS, Tuberculosis and Malaria (the Global Fund), and annual financial statements and reports for information on income sources. Data were not yet available for some more recent years, and we relied on budget data to generate these estimates. Detailed explanation of how the disbursements were estimated for each disbursing agency is provided in the appendix (pp 47–80) and published elsewhere.5, 29, 30, 31, 32, 33, 34, 35, 36 We disaggregated the estimates into ten health focus areas and 53 programme areas. This disaggregation captures the main programmatic areas to which development assistance for health contributions have historically been provided, and facilitates comparison with 2020 contributions and the international funding for the ongoing pandemic. We defined relevant health focus areas and programme areas for projects on the basis of a keyword search of the project descriptions downloaded from international agencies' online project databases. The specific keywords we used and their assigned health focus or programme area are detailed in the appendix (pp 35–46).
We leveraged information from available financial documents on revenue to remove double counting across disbursing agencies, so that each flow of funding is counted only once even if it was moved from one agency to another. Although OECD CRS completeness has improved over time, in earlier years (for this study, 1990 to 1996 especially) the data were less complete; thus, we used adjusted commitment data from the Development Assistance Committee tables to estimate disbursements. We also estimated the expenses associated with administering loans and grants.
Estimating development assistance for health for COVID-19
We developed a separate method for estimating development assistance for health for COVID-19 because much of the project-level data used as input for the historical development assistance for health estimates do not extend to 2020, and therefore do not include resources disbursed in response to COVID-19. Likewise, budget and commitment data made before 2020 do not include the response to the pandemic. To adjust our 2020 development assistance estimates and include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a diverse set of databases. Our primary focus was on the UN Office of Humanitarian Assistance financial tracking service (UNOCHA) and the International Aid Transparency Initiative (IATI). We relied on UNOCHA for data on non-governmental organisations; UNICEF; the UN Population Fund; and bilateral development agencies for the United Arab Emirates, Switzerland, Italy, and New Zealand. We relied on IATI for data on bilateral development agencies for Australia, Belgium, Canada, Denmark, Finland, France, Germany, Italy, the Netherlands, New Zealand, Norway, South Korea, Spain, Sweden, Switzerland, the UK, the USA, and the European Commission. We obtained data through correspondence for regional banks and other international agencies. For US foundations, we extracted commitment estimates from Candid. We extracted relevant data directly from organisations' online databases for the Bill & Melinda Gates Foundation; the Global Fund; Gavi, the Vaccine Alliance; WHO; the Pan American Health Organization; the World Bank; and regional development banks. For each agency, we extracted data on all 2020 project commitments and disbursements, as available. Data on commitments captured the resource allocation committed towards project activities that were generally available in project budget documents. Disbursements captured the value of project resources that had been transferred to implementing agencies to finance project activities.
We used the information available to determine whether projects were new grants or previous grants repurposed to COVID-19 projects. UNOCHA data designated whether resources were new or not. For IATI, we assumed that COVID-19 projects starting before 2020 were repurposed. For data received from correspondence or extracted from online databases, we contacted the respective agencies and searched their websites for more information. We included all research and development funding that went through international development agencies (appendix pp 91–92).
The approach used for each disbursing agency was specific to the data extracted and is detailed in the appendix (pp 92–106). Briefly, the general method was to use keywords to isolate COVID-19-relevant projects from each agency's database. We then examined these projects for completeness of information and adjusted the data to ensure that the estimate used was as precise as possible and could be compared between agencies. For instance, for projects with commitment estimates but without disbursement estimates, we calculated the average commitment-to-disbursement ratio for projects with complete data (for that development agency if possible) and multiplied the mean of those disbursement ratios by the commitment estimates for the projects without disbursement information. This commitment-to-disbursement ratio captures the proportion of committed funds that were estimated to have been disbursed in 2020. Next, we used a keyword search on project descriptions to disaggregate the estimated COVID-19 disbursements into eight COVID-19 programme areas: country-level coordination (planning, monitoring, and evaluation; risk communication; community engagement; and travel restrictions); surveillance, rapid-response teams, and case investigation; national laboratories and testing; infection prevention and personal protective equipment; treatment; supply chain and logistics; maintaining other essential health services and systems; and research and development for vaccines and other therapeutics (from a development agency). These programme areas were developed based on a review of the data and literature.
Finally, we reviewed the development agencies to identify any instances of double counting of the same resources across agencies. To do this, we reviewed income and recipient agency data for each of the disbursing channels that we tracked and excluded disbursements to recipient agencies that we tracked separately as disbursing agencies. We typically kept the disbursed resources with the development agency that was closest in the process to the final recipient country. This review ensured that we counted each disbursement from the source agency, to ultimate disbursing agency, to the final recipient only once.
Estimating future health spending, 2019–50
We estimated GDP; general government spending (across all sectors); government, out-of-pocket, and prepaid private health spending; and total development assistance for health provided and received until 2050. The methods used for these projections draw heavily from our previous research, with the key change being the updating of the retrospective estimates on which these projections are based.5, 32, 33 Because this research draws from a diverse set of underlying input data, updates to these data have cascading effects and affect all of the projections.
We generated these projections by use of ensemble modelling techniques, such that the estimates are the mean of 1000 estimated projections from a broad set of models. We defined model selection by out-of-sample validation. This selection was country-specific and year-specific. We completed projections sequentially so that previously projected values could be used as covariates and for bounding other models. We forecasted GDP per working-age adult aged 20–64 years from 2022 to 2050, with 2020 and 2021 estimates drawing on methods that focused on estimating economic growth sensitive to COVID-19 projects (appendix p 8). We forecasted general government spending from 2020 to 2050 (as the retrospective estimates extend to 2019). We modelled development assistance for health as a proportion of the donor country's general government spending, or, for private donors, on the basis of AutoRegressive Integrated Moving Average modelling techniques from 2021 to 2050 (as the retrospective estimates extend to 2020).
We aggregated total development assistance for health provided across sources and used a separate model to project the proportion of total development assistance for health that each recipient was expected to receive from 2019 to 2050 (as these retrospective data extend to 2018). We also modelled when countries are projected to transition to being high-income and are no longer eligible to receive development assistance for health. We projected government health spending as a share of general government spending, prepaid private health spending as a share of GDP, and out-of-pocket health spending as a share of GDP from 2019 to 2050 (as the retrospective data extend to 2018). To capture increased government spending in response to COVID-19, we checked whether our 2020 estimates of government health spending increased by at least the estimates made by the IMF October 2020 Fiscal Monitor of previously unanticipated government health spending. Countries that had year-over-year spending increases in 2020 that were less than estimated increase reported in the Fiscal Monitor were adjusted upward proportionally.
All projections incorporated several types of uncertainty. We used ensemble modelling techniques to propagate model uncertainty. We took draws of the variance-covariance matrix of each estimate's model to propagate parameter uncertainty. Finally, we added a random walk residual to each projection to propagate fundamental uncertainty. We generated 95% UIs by taking the 2·5th and 97·5th percentile of the 1000 estimated random draws.
Reporting
We report all the historical and future spending estimates in inflation-adjusted 2020 US$ and 2020 US$ per capita, and in purchasing-power parity-adjusted US$ per capita and as a proportion of GDP. For the development assistance for health estimates, we adjusted for inflation by taking disbursements in nominal US$ in the year of disbursements and using US GDP deflators from the IMF World Economic Outlook database to convert the series to constant 2020 US$. For the historical and future global health spending estimates, we used country-specific exchange rate data and deflator series from IMF to convert the series to constant 2020 US$. We report all spending estimates by 2019 Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) super-region and 2020 World Bank income groups.37 For these aggregates (and the global aggregate) the reported estimates provide information about a group as a whole, rather than the mean of the countries included in that group. For all tables and figures, the country income classifications were held constant at the 2020 reported level, irrespective of whether they changed groups. The time periods for each of the financing sources differs relative to the availability of the underlying data (development assistance for health, 1990–2020; domestic health spending, 1995–2018; and future health spending, 2019–50). These time periods provide a time series of health spending data that makes sure to leverage all available data. We completed all the analyses using Stata (versions 13 and 15), R (versions 3.6.0 and 3.6.1), and Python (version 3.7.0).
Role of the funding source
The funder of this study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
Results
In 2019, total global health spending reached $8·8 trillion (95% UI 8·7–8·8) and was $1132 per person (1119–1143; table 1), with a wide variation in spending across geographical regions and country income groups. In 2019, high-income countries spent an estimated $5702 (95% UI 5638–5769) per person, with country-specific spending ranging from $523 (443–610) per person in the Northern Mariana Islands to $11 345 (11 114–11 578) per person in the USA. Across this income group, the most spending was from governments, which made up 61·4% (95% UI 60·9–62·0) of health spending, although countries such as the USA and Switzerland also relied substantially on prepaid private spending. Upper-middle-income countries spent $500 (484–517) per person on health, ranging from $94 (84–104) in Venezuela to $1492 (1274–1751) in Tokelau, and relied mostly on governments to finance their health spending. Lower-middle-income countries spent $90 (86–95) per person on health, ranging from $29 (26–32) in Benin to $395 (368–425) in Palestine, and relied mostly on out-of-pocket spending to finance their health spending. In 2019, low-income countries spent $36 (35–37) per person on health, ranging from $7 (6–8) in Somalia to $73 (66–81) in Sierra Leone, and also relied mostly on out-of-pocket spending. In 2019, development assistance for health to low-income and middle-income countries was $40·4 billion, or 0·5% (95% UI 0·5–0·5) of total global health spending. In 2019, development assistance for health made up 24·6% (24·0–25·1) of health spending in low-income countries and 3·2% (3·1–3·4) of health spending in lower-middle-income countries.
Table 1.
Health spending and development assistance for health in 2019 and 2050 by region
| Health spending per person, 2019 (US$) | Projected health spending per person, 2050 (2020 US$) | Health spending per person, 2019 ($PPP) | Projected health spending per person, 2050 ($PPP) | Total health spending per GDP, 2019 | Total health spending per GDP, 2050 | Development assistance for health system strengthening per person, 2020 (US$) | ||
|---|---|---|---|---|---|---|---|---|
| Global | ||||||||
| Total | 1132 (1119 to 1143) | 1519 (1448 to 1591) | 1485 (1470 to 1501) | 2053 (1973 to 2135) | 10·0% (9·8 to 10·1) | 12·9% (11·5 to 14·2) | 0·7 | |
| World Bank income groups | ||||||||
| High income | 5702 (5638 to 5769) | 8539 (8074 to 9032) | 6288 (6226 to 6356) | 9322 (8871 to 9812) | 12·6% (12·5 to 12·8) | 17·6% (15·5 to 19·9) | 0·0 | |
| Upper-middle income | 500 (484 to 517) | 1001 (922 to 1083) | 984 (959 to 1011) | 1915 (1783 to 2051) | 5·7% (5·5 to 5·9) | 8·3% (6·4 to 10·3) | 0·0 | |
| Lower-middle income | 90 (86 to 95) | 150 (141 to 159) | 281 (267 to 297) | 461 (433 to 493) | 4·1% (3·9 to 4·3) | 4·6% (3·8 to 5·4) | 0·1 | |
| Low income | 36 (35 to 37) | 46 (44 to 47) | 124 (121 to 129) | 151 (145 to 158) | 5·0% (4·7 to 5·3) | 4·6% (4·1 to 5·2) | 0·1 | |
| GBD super-region | ||||||||
| Central Europe, eastern Europe, and central Asia | 571 (560 to 580) | 656 (628 to 684) | 1426 (1398 to 1453) | 1635 (1564 to 1708) | 6·0% (5·9 to 6·1) | 7·0% (6·0 to 7·9) | 0·2 | |
| High income | 6282 (6211 to 6356) | 9302 (8791 to 9852) | 6773 (6701 to 6848) | 9949 (9436 to 10 500) | 13·1% (12·9 to 13·3) | 18·1% (15·8 to 20·5) | 0·0 | |
| Latin America and Caribbean | 514 (497 to 530) | 762 (710 to 824) | 1163 (1125 to 1200) | 1734 (1615 to 1873) | 7·4% (7·2 to 7·6) | 10·3% (8·7 to 12·0) | 0·1 | |
| North Africa and Middle East | 378 (370 to 386) | 469 (444 to 498) | 945 (926 to 967) | 1225 (1154 to 1296) | 5·8% (5·6 to 6·0) | 8·6% (7·5 to 9·7) | 0·0 | |
| South Asia | 69 (62 to 77) | 134 (119 to 150) | 229 (207 to 255) | 447 (397 to 502) | 3·4% (3·1 to 3·8) | 4·1% (2·9 to 5·6) | 0·0 | |
| Southeast Asia, east Asia, and Oceania | 439 (419 to 459) | 1025 (915 to 1138) | 766 (735 to 800) | 1784 (1606 to 1966) | 5·1% (4·8 to 5·3) | 7·7% (5·6 to 10·3) | 0·0 | |
| Sub-Saharan Africa | 76 (74 to 79) | 99 (94 to 106) | 193 (187 to 199) | 253 (240 to 268) | 5·0% (4·8 to 5·2) | 5·0% (4·4 to 5·7) | 0·1 | |
| Central Europe, eastern Europe, and central Asia | ||||||||
| Central Asia | ||||||||
| Armenia | 436 (409 to 462) | 531 (495 to 568) | 1387 (1301 to 1472) | 1689 (1576 to 1807) | 9·6% (8·6 to 10·6) | 10·0% (6·7 to 13·9) | 3·3 | |
| Azerbaijan | 157 (140 to 174) | 185 (161 to 211) | 550 (492 to 612) | 648 (567 to 741) | 3·6% (3·2 to 4·0) | 4·1% (2·8 to 6·0) | 0·0 | |
| Georgia | 330 (311 to 350) | 516 (456 to 585) | 1133 (1067 to 1201) | 1773 (1568 to 2009) | 7·4% (6·8 to 8·1) | 10·5% (7·4 to 14·4) | 0·0 | |
| Kazakhstan | 282 (258 to 308) | 403 (331 to 484) | 855 (782 to 934) | 1219 (1002 to 1465) | 3·1% (2·8 to 3·4) | 3·8% (2·6 to 5·4) | 0·0 | |
| Kyrgyzstan | 83 (79 to 88) | 108 (98 to 121) | 350 (333 to 369) | 455 (412 to 510) | 6·3% (6·0 to 6·7) | 7·7% (5·7 to 10·2) | 0·0 | |
| Mongolia | 203 (187 to 222) | 293 (254 to 345) | 623 (575 to 683) | 900 (781 to 1059) | 4·8% (4·4 to 5·3) | 5·9% (4·0 to 8·3) | 9·4 | |
| Tajikistan | 59 (56 to 61) | 68 (62 to 77) | 251 (240 to 262) | 292 (264 to 329) | 7·0% (6·4 to 7·6) | 7·7% (5·4 to 10·8) | 0·0 | |
| Turkmenistan | 603 (559 to 648) | 745 (680 to 814) | 1247 (1157 to 1340) | 1543 (1406 to 1685) | 7·7% (7·1 to 8·4) | 8·6% (6·0 to 12·0) | 0·0 | |
| Uzbekistan | 93 (85 to 102) | 128 (112 to 145) | 391 (356 to 427) | 537 (469 to 606) | 5·3% (4·8 to 5·8) | 5·9% (4·1 to 8·4) | 0·7 | |
| Central Europe | ||||||||
| Albania | 293 (270 to 317) | 355 (319 to 396) | 816 (753 to 884) | 990 (888 to 1103) | 5·5% (5·1 to 6·0) | 6·0% (4·1 to 8·3) | 0·0 | |
| Bosnia and Herzegovina | 548 (517 to 582) | 951 (872 to 1038) | 1416 (1336 to 1503) | 2457 (2253 to 2682) | 9·0% (8·4 to 9·5) | 12·2% (8·3 to 17·4) | 0·0 | |
| Bulgaria | 785 (745 to 826) | 991 (847 to 1162) | 1896 (1799 to 1997) | 2396 (2047 to 2808) | 7·7% (7·3 to 8·2) | 8·9% (6·0 to 12·7) | 0·0 | |
| Croatia | 1024 (964 to 1082) | 1299 (1040 to 1619) | 2020 (1901 to 2134) | 2563 (2052 to 3193) | 6·7% (6·3 to 7·1) | 8·4% (5·5 to 12·3) | 0·0 | |
| Czech Republic | 1851 (1789 to 1911) | 2547 (2244 to 2869) | 3296 (3186 to 3402) | 4536 (3996 to 5109) | 7·6% (7·1 to 8·3) | 9·9% (6·8 to 13·6) | 0·0 | |
| Hungary | 1100 (1068 to 1133) | 1296 (1197 to 1405) | 2321 (2253 to 2390) | 2734 (2526 to 2964) | 6·7% (6·5 to 6·9) | 7·2% (5·3 to 9·5) | 0·0 | |
| Montenegro | 732 (689 to 780) | 814 (745 to 892) | 1840 (1733 to 1960) | 2047 (1873 to 2242) | 8·1% (7·7 to 8·7) | 9·0% (6·4 to 12·0) | 0·0 | |
| North Macedonia | 412 (396 to 429) | 412 (378 to 449) | 1137 (1092 to 1183) | 1136 (1042 to 1239) | 6·5% (6·0 to 7·0) | 6·7% (5·1 to 8·7) | 0·0 | |
| Poland | 1023 (999 to 1048) | 1461 (1338 to 1599) | 2256 (2202 to 2310) | 3221 (2949 to 3525) | 6·4% (6·3 to 6·6) | 8·7% (6·0 to 12·3) | 0·0 | |
| Romania | 773 (733 to 815) | 1038 (861 to 1228) | 1819 (1723 to 1917) | 2440 (2025 to 2888) | 5·8% (5·4 to 6·1) | 6·7% (4·4 to 9·6) | 0·0 | |
| Serbia | 518 (505 to 533) | 637 (598 to 677) | 1302 (1268 to 1339) | 1600 (1504 to 1700) | 6·8% (6·6 to 7·0) | 7·4% (5·4 to 9·7) | 0·0 | |
| Slovakia | 1375 (1317 to 1435) | 1813 (1637 to 2046) | 2373 (2272 to 2475) | 3128 (2824 to 3530) | 6·9% (6·6 to 7·2) | 8·6% (5·9 to 11·6) | 0·0 | |
| Slovenia | 2248 (2186 to 2314) | 2691 (2511 to 2883) | 3456 (3360 to 3558) | 4137 (3860 to 4432) | 8·4% (8·1 to 8·6) | 10·5% (7·4 to 14·5) | 0·0 | |
| Eastern Europe | ||||||||
| Belarus | 361 (334 to 387) | 459 (364 to 576) | 1163 (1075 to 1248) | 1480 (1174 to 1858) | 5·7% (5·3 to 6·1) | 6·6% (4·3 to 10·0) | 0·0 | |
| Estonia | 1628 (1586 to 1669) | 2211 (1973 to 2456) | 2623 (2555 to 2689) | 3561 (3179 to 3956) | 6·8% (6·6 to 7·0) | 8·2% (5·7 to 11·4) | 0·0 | |
| Latvia | 1132 (1094 to 1170) | 1384 (1259 to 1517) | 2008 (1941 to 2075) | 2456 (2233 to 2693) | 6·2% (6·0 to 6·4) | 7·1% (4·9 to 9·7) | 0·0 | |
| Lithuania | 1321 (1277 to 1364) | 1649 (1519 to 1786) | 2562 (2477 to 2646) | 3198 (2947 to 3465) | 6·6% (6·3 to 6·9) | 7·3% (4·9 to 10·3) | 0·0 | |
| Moldova | 215 (198 to 232) | 252 (225 to 285) | 667 (6168 to 720) | 783 (698 to 884) | 5·8% (4·3 to 8·3) | 7·1% (4·4 to 11·5) | 0·0 | |
| Russia | 563 (537 to 586) | 611 (554 to 676) | 1546 (1475 to 1610) | 1679 (1522 to 1858) | 5·4% (5·1 to 5·6) | 6·2% (4·4 to 8·5) | 0·0 | |
| Ukraine | 258 (242 to 274) | 259 (233 to 288) | 957 (899 to 1015) | 962 (865 to 1067) | 7·4% (6·7 to 8·1) | 8·4% (6·1 to 11·2) | 0·0 | |
| High income | ||||||||
| Australasia | ||||||||
| Australia | 5507 (5409 to 5608) | 7818 (7303 to 8402) | 5398 (5302 to 5498) | 7663 (7159 to 8236) | 10·3% (9·8 to 11·1) | 13·6% (9·4 to 18·6) | 0·0 | |
| New Zealand | 4175 (4081 to 4269) | 6012 (5553 to 6508) | 4434 (4334 to 4534) | 6386 (5898 to 6912) | 9·9% (9·4 to 10·2) | 13·2% (9·4 to 17·6) | 0·0 | |
| High-income Asia Pacific | ||||||||
| Brunei | 544 (501 to 592) | 490 (374 to 620) | 1454 (1339 to 1583) | 1310 (1001 to 1659) | 2·3% (2·1 to 2·5) | 2·5% (1·6 to 3·6) | 0·0 | |
| Japan | 4489 (4372 to 4622) | 6150 (5583 to 6734) | 4787 (4662 to 4929) | 6558 (5953 to 7180) | 10·9% (10·6 to 11·3) | 14·4% (10·0 to 20·0) | 0·0 | |
| Singapore | 2843 (2719 to 2966) | 5002 (4033 to 6083) | 4645 (4443 to 4847) | 8173 (6590 to 9940) | 4·5% (4·3 to 4·8) | 7·2% (4·6 to 10·6) | 0·0 | |
| South Korea | 2442 (2395 to 2487) | 4957 (4470 to 5478) | 3529 (3461 to 3594) | 7165 (6461 to 7917) | 7·8% (7·6 to 7·9) | 14·1% (9·7 to 20·2) | 0·0 | |
| High-income North America | ||||||||
| Canada | 5163 (5104 to 5218) | 7077 (6531 to 7661) | 5837 (5770 to 5899) | 8000 (7383 to 8661) | 11·2% (11·0 to 11·4) | 15·1% (10·8 to 20·4) | 0·0 | |
| Greenland | 6579 (5966 to 7194) | 7651 (6719 to 8606) | 5381 (4879 to 5884) | 6258 (5595 to 7038) | 11·5% (10·1 to 13·0) | 12·9% (8·8 to 18·2) | 0·0 | |
| USA | 11 345 (11 114 to 11 578) | 17 300 (15 680 to 18 976) | 11 345 (11 114 to 11 578) | 17 300 (15 680 to 18 976) | 17·2% (16·8 to 17·5) | 24·8% (19·0 to 32·5) | 0·0 | |
| Southern Latin America | ||||||||
| Argentina | 946 (905 to 988) | 1239 (1086 to 1428) | 2285 (2186 to 2387) | 2993 (2624 to 3449) | 9·7% (9·3 to 10·2) | 13·0% (8·8 to 18·1) | 0·0 | |
| Chile | 1329 (1304 to 1353) | 2025 (1885 to 2184) | 2472 (2426 to 2516) | 3765 (3505 to 4062) | 9·7% (9·5 to 9·9) | 14·0% (10·1 to 19·5) | 0·0 | |
| Uruguay | 1549 (1516 to 1585) | 2268 (2009 to 2572) | 2156 (2110 to 2205) | 3157 (2796 to 3580) | 9·5% (9·2 to 9·8) | 11·9% (8·2 to 16·8) | 0·0 | |
| Western Europe | ||||||||
| Andorra | 2948 (2827 to 3079) | 2957 (2538 to 3587) | 3141 (3012 to 3280) | 3150 (2704 to 3822) | 6·7% (5·9 to 7·8) | 9·7% (6·6 to 13·9) | 0·0 | |
| Austria | 5383 (5302 to 5463) | 6766 (6253 to 7294) | 6132 (6039 to 6222) | 7707 (7123 to 8308) | 10·3% (10·1 to 10·5) | 12·8% (8·8 to 17·3) | 0·0 | |
| Belgium | 4983 (4887 to 5083) | 6490 (6019 to 6960) | 5698 (5588 to 5813) | 7421 (6882 to 7958) | 10·4% (10·2 to 10·7) | 12·7% (9·5 to 16·6) | 0·0 | |
| Cyprus | 1262 (1212 to 1313) | 1582 (1443 to 1743) | 1881 (1806 to 1957) | 2358 (2150 to 2598) | 5·0% (4·0 to 6·6) | 6·2% (4·3 to 9·3) | 0·0 | |
| Denmark | 6182 (6035 to 6340) | 8095 (7433 to 8849) | 6112 (5967 to 6269) | 8004 (7350 to 8750) | 10·0% (9·7 to 10·3) | 12·2% (9·2 to 15·8) | 0·0 | |
| Finland | 4595 (4504 to 4690) | 5642 (5261 to 6023) | 4680 (4587 to 4776) | 5745 (5358 to 6134) | 9·1% (8·9 to 9·3) | 9·9% (7·3 to 13·1) | 0·0 | |
| France | 4844 (4792 to 4891) | 6245 (5714 to 6811) | 5605 (55475 to 5659) | 7226 (6612 to 7881) | 11·4% (11·0 to 11·7) | 14·1% (10·8 to 18·0) | 0·0 | |
| Germany | 5498 (5428 to 5570) | 7518 (6986 to 7987) | 6482 (6399 to 6567) | 8863 (8236 to 9416) | 11·4% (11·2 to 11·5) | 14·6% (10·4 to 19·5) | 0·0 | |
| Greece | 1595 (1515 to 1677) | 1620 (1470 to 1785) | 2551 (2422 to 2682) | 2591 (2351 to 2854) | 8·0% (7·6 to 8·4) | 9·2% (7·1 to 11·7) | 0·0 | |
| Iceland | 5486 (5256 to 5722) | 6931 (6189 to 7676) | 5227 (5007 to 5451) | 6603 (5896 to 7313) | 8·6% (8·0 to 9·2) | 10·3% (7·4 to 13·8) | 0·0 | |
| Ireland | 5673 (5413 to 5932) | 8456 (7758 to 9225) | 6362 (6071 to 6653) | 9484 (8700 to 10 345) | 6·8% (6·5 to 7·1) | 9·1% (6·6 to 11·8) | 0·0 | |
| Israel | 3246 (3184 to 3307) | 4174 (3854 to 4522) | 3056 (2997 to 3114) | 3930 (3629 to 4257) | 7·1% (6·6 to 7·4) | 8·1% (5·7 to 11·1) | 0·0 | |
| Italy | 2995 (2931 to 3061) | 3160 (2924 to 3424) | 3916 (3833 to 4003) | 4132 (3823 to 4478) | 8·7% (8·6 to 8·9) | 10·6% (8·1 to 13·6) | 0·0 | |
| Luxembourg | 6246 (5877 to 6655) | 6893 (6019 to 7849) | 6436 (6055 to 6856) | 7102 (6202 to 8087) | 5·3% (5·0 to 5·6) | 6·7% (4·9 to 8·9) | 0·0 | |
| Malta | 3174 (3081 to 3268) | 4837 (4486 to 5211) | 4803 (4663 to 4946) | 7320 (6788 to 7886) | 9·7% (8·6 to 10·6) | 10·9% (7·4 to 15·5) | 0·0 | |
| Monaco | 3560 (3346 to 3779) | 4719 (4118 to 5446) | 3479 (3270 to 3693) | 4612 (4025 to 5322) | 1·7% (1·5 to 2·1) | 2·0% (1·4 to 2·9) | 0·0 | |
| Netherlands | 5586 (5449 to 5735) | 7722 (6885 to 8669) | 6217 (6065 to 6382) | 8594 (7662 to 9648) | 10·3% (10·0 to 10·6) | 13·6% (9·5 to 18·7) | 0·0 | |
| Norway | 7352 (7176 to 7537) | 8329 (7576 to 9223) | 7013 (6845 to 7189) | 7945 (7227 to 8798) | 10·4% (10·2 to 10·7) | 12·6% (10·1 to 15·6) | 0·0 | |
| Portugal | 2187 (2117 to 2260) | 2389 (2141 to 2685) | 3350 (3243 to 3462) | 3659 (3281 to 4113) | 9·1% (8·8 to 9·4) | 10·6% (8·2 to 13·6) | 0·0 | |
| San Marino | 3393 (3249 to 3540) | 3944 (3644 to 4282) | 4612 (4417 to 4812) | 5361 (4953 to 5821) | 7·2% (6·9 to 7·5) | 8·5% (6·6 to 11·1) | 0·0 | |
| Spain | 2801 (2731 to 2868) | 3313 (3063 to 3708) | 3985 (3884 to 4079) | 4712 (4357 to 5274) | 9·1% (8·9 to 9·4) | 12·3% (9·5 to 15·8) | 0·0 | |
| Sweden | 5898 (5692 to 6117) | 8016 (7268 to 8874) | 6149 (5933 to 6376) | 8356 (7577 to 9250) | 10·8% (10·4 to 11·3) | 12·9% (9·1 to 17·6) | 0·0 | |
| Switzerland | 10 203 (10 057 to 10 351) | 14 239 (12 827 to 15 690) | 8521 (8398 to 8644) | 11 891 (10 712 to 13 103) | 11·6% (11·1 to 11·9) | 17·0% (11·9 to 23·5) | 0·0 | |
| UK | 4392 (4329 to 4457) | 5279 (4863 to 5702) | 4960 (4888 to 5033) | 5962 (5492 to 6439) | 10·1% (9·9 to 10·3) | 12·3% (9·9 to 14·9) | 0·0 | |
| Latin America and Caribbean | ||||||||
| Andean Latin America | ||||||||
| Bolivia | 233 (213 to 254) | 336 (299 to 378) | 585 (536 to 639) | 845 (752 to 949) | 6·4% (5·8 to 7·0) | 8·5% (5·9 to 12·1) | 0·0 | |
| Ecuador | 483 (455 to 512) | 684 (600 to 771) | 963 (907 to 1022) | 1366 (1198 to 1540) | 8·0% (7·5 to 8·5) | 11·0% (7·6 to 15·4) | 0·0 | |
| Peru | 346 (324 to 369) | 401 (352 to 455) | 683 (639 to 728) | 790 (694 to 897) | 5·0% (4·6 to 5·3) | 6·3% (4·5 to 8·6) | 0·0 | |
| Caribbean | ||||||||
| Antigua and Barbuda | 972 (925 to 1024) | 1381 (1160 to 1608) | 1281 (1219 to 1349) | 1820 (1528 to 2119) | 5·6% (5·3 to 5·9) | 7·9% (5·8 to 10·7) | 0·0 | |
| The Bahamas | 2191 (2111 to 2270) | 3238 (2932 to 3572) | 2468 (2377 to 2557) | 3646 (3302 to 4022) | 6·2% (6·0 to 6·5) | 10·1% (7·4 to 13·5) | 0·0 | |
| Barbados | 1126 (1074 to 1182) | 1104 (1023 to 1205) | 1020 (973 to 1071) | 1000 (927 to 1091) | 6·2% (5·9 to 6·5) | 6·4% (5·0 to 8·4) | 0·0 | |
| Belize | 283 (258 to 309) | 450 (346 to 551) | 431 (394 to 471) | 686 (527 to 841) | 6·0% (5·4 to 6·6) | 8·1% (5·6 to 11·7) | 0·0 | |
| Bermuda | 8049 (7007 to 9277) | 10 721 (8170 to 13 824) | 5686 (4950 to 6553) | 7574 (5771 to 9765) | 6·7% (5·0 to 9·2) | 12·1% (7·6 to 18·3) | 0·0 | |
| Cuba | 1170 (1090 to 1255) | 1745 (1549 to 1936) | 2863 (2667 to 3071) | 4268 (3790 to 4735) | 13·1% (11·7 to 14·7) | 20·3% (14·1 to 28·4) | 0·0 | |
| Dominica | 431 (403 to 460) | 466 (391 to 550) | 676 (632 to 722) | 731 (613 to 863) | 5·1% (4·8 to 5·5) | 5·1% (3·8 to 6·6) | 0·0 | |
| Dominican Republic | 446 (416 to 476) | 715 (600 to 847) | 1124 (1048 to 1200) | 1804 (1514 to 2137) | 5·7% (5·3 to 6·2) | 7·6% (5·1 to 10·9) | 0·0 | |
| Grenada | 515 (483 to 551) | 650 (560 to 766) | 863 (808 to 923) | 1088 (937 to 1283) | 4·7% (4·4 to 5·1) | 5·1% (3·6 to 6·9) | 0·0 | |
| Guyana | 323 (301 to 346) | 542 (422 to 692) | 648 (604 to 694) | 1087 (847 to 1390) | 4·4% (3·9 to 5·0) | 5·1% (3·6 to 7·5) | 0·0 | |
| Haiti | 47 (43 to 53) | 73 (64 to 84) | 111 (100 to 124) | 171 (151 to 199) | 5·3% (3·0 to 7·5) | 7·6% (3·8 to 12·6) | 0·0 | |
| Jamaica | 365 (337 to 393) | 598 (509 to 698) | 715 (660 to 769) | 1170 (996 to 1366) | 6·7% (6·0 to 7·3) | 12·0% (8·3 to 16·8) | 0·0 | |
| Puerto Rico | 1286 (1138 to 1459) | 1626 (1385 to 1890) | 1496 (1323 to 1697) | 1890 (1611 to 2198) | 3·9% (3·4 to 4·5) | 5·3% (3·8 to 7·2) | 0·0 | |
| Saint Kitts and Nevis | 1026 (967 to 1086) | 1457 (1293 to 1651) | 1415 (1332 to 1497) | 2008 (1782 to 2276) | 5·2% (4·8 to 5·7) | 5·7% (4·3 to 7·3) | 0·0 | |
| Saint Lucia | 531 (496 to 568) | 708 (610 to 809) | 744 (695 to 797) | 992 (855 to 1134) | 4·5% (4·2 to 4·9) | 6·2% (4·3 to 8·3) | 0·0 | |
| Saint Vincent and the Grenadines | 359 (334 to 387) | 510 (451 to 576) | 626 (583 to 675) | 890 (788 to 1005) | 4·7% (4·4 to 5·1) | 6·5% (4·7 to 8·7) | 0·0 | |
| Suriname | 408 (381 to 438) | 610 (501 to 746) | 1420 (1324 to 1524) | 2121 (1742 to 2595) | 8·2% (7·6 to 8·8) | 12·0% (8·1 to 17·1) | 0·0 | |
| Trinidad and Tobago | 1145 (1093 to 1203) | 1392 (1262 to 1530) | 1836 (1752 to 1929) | 2232 (2022 to 2452) | 6·6% (6·3 to 7·0) | 8·1% (6·1 to 10·6) | 0·0 | |
| Virgin Islands | 969 (825 to 1133) | 1132 (931 to 1375) | 969 (825 to 1133) | 1132 (931 to 1375) | 2·4% (2·0 to 2·9) | 2·7% (1·9 to 3·8) | 0·0 | |
| Central Latin America | ||||||||
| Colombia | 447 (429 to 468) | 810 (714 to 917) | 1214 (1165 to 1270) | 2198 (1939 to 2490) | 7·8% (7·5 to 8·2) | 12·7% (8·8 to 17·9) | 0·0 | |
| Costa Rica | 1083 (1061 to 1105) | 1682 (1530 to 1869) | 1798 (1762 to 1835) | 2792 (2541 to 3104) | 8·7% (8·6 to 8·9) | 13·0% (9·3 to 17·7) | 0·0 | |
| El Salvador | 322 (299 to 347) | 508 (452 to 572) | 707 (657 to 764) | 1116 (994 to 1258) | 7·7% (7·1 to 8·3) | 10·9% (8·2 to 14·1) | 0·0 | |
| Guatemala | 308 (291 to 326) | 461 (420 to 501) | 601 (567 to 636) | 899 (820 to 977) | 6·9% (6·3 to 7·4) | 8·4% (6·5 to 10·7) | 0·0 | |
| Honduras | 187 (173 to 203) | 283 (245 to 331) | 429 (396 to 465) | 650 (562 to 759) | 7·1% (6·5 to 7·7) | 8·3% (5·6 to 11·5) | 0·0 | |
| Mexico | 502 (482 to 525) | 619 (572 to 671) | 1171 (1124 to 1223) | 1441 (1332 to 1564) | 5·6% (5·4 to 5·8) | 6·6% (5·0 to 8·2) | 0·0 | |
| Nicaragua | 169 (153 to 186) | 262 (228 to 297) | 501 (454 to 551) | 777 (678 to 881) | 8·7% (7·9 to 9·6) | 12·5% (8·9 to 17·2) | 1·3 | |
| Panama | 1103 (1075 to 1128) | 1631 (1464 to 1813) | 2353 (2293 to 2406) | 3479 (3121 to 3866) | 7·1% (6·9 to 7·2) | 8·8% (6·1 to 12·3) | 0·0 | |
| Venezuela* | 94 (84 to 104) | 80 (68 to 93) | 230 (206 to 255) | 196 (166 to 228) | 3·7% (3·0 to 4·5) | 3·9% (2·5 to 5·6) | 0·0 | |
| Tropical Latin America | ||||||||
| Brazil | 639 (598 to 682) | 1099 (950 to 1266) | 1443 (1350 to 1540) | 2480 (2144 to 2858) | 9·3% (8·7 to 9·9) | 14·8% (10·1 to 21·0) | 0·2 | |
| Paraguay | 380 (357 to 404) | 750 (678 to 830) | 968 (908 to 1029) | 1909 (1727 to 2114) | 7·2% (6·8 to 7·7) | 11·1% (7·7 to 15·0) | 0·0 | |
| North Africa and Middle East | ||||||||
| Afghanistan | 54 (49 to 58) | 58 (53 to 64) | 223 (205 to 243) | 243 (221 to 265) | 10·5% (9·3 to 11·8) | 9·9% (6·6 to 14·2) | 0·0 | |
| Algeria | 231 (210 to 253) | 308 (260 to 363) | 765 (696 to 838) | 1021 (862 to 1202) | 6·4% (5·8 to 7·0) | 9·0% (6·4 to 12·3) | 0·0 | |
| Bahrain | 1052 (1001 to 1103) | 938 (793 to 1108) | 2260 (2151 to 2369) | 2015 (1705 to 2380) | 4·6% (4·1 to 4·9) | 6·2% (4·2 to 8·6) | 0·0 | |
| Egypt | 173 (162 to 183) | 276 (248 to 306) | 617 (580 to 655) | 984 (884 to 1093) | 5·2% (4·6 to 5·7) | 5·9% (4·0 to 8·2) | 0·0 | |
| Iran | 675 (642 to 706) | 890 (770 to 1014) | 1112 (1059 to 1164) | 1467 (1270 to 1671) | 8·4% (7·7 to 9·1) | 14·2% (10·2 to 19·1) | 0·0 | |
| Iraq | 185 (168 to 203) | 322 (246 to 409) | 415 (378 to 455) | 723 (552 to 917) | 3·6% (3·3 to 4·0) | 5·0% (3·1 to 7·9) | 0·0 | |
| Jordan | 306 (284 to 331) | 475 (403 to 560) | 734 (679 to 792) | 1137 (966 to 1341) | 6·9% (6·4 to 7·4) | 10·3% (7·3 to 14·2) | 0·0 | |
| Kuwait | 1453 (1317 to 1607) | 1098 (906 to 1332) | 2724 (2469 to 3013) | 2059 (1699 to 2497) | 5·4% (4·7 to 6·3) | 7·6% (5·0 to 11·3) | 0·0 | |
| Lebanon | 395 (367 to 425) | 436 (382 to 501) | 1663 (1547 to 1789) | 1837 (1608 to 2109) | 10·7% (10·0 to 11·5) | 12·7% (9·0 to 17·3) | 0·0 | |
| Libya | 798 (683 to 930) | 658 (448 to 924) | 1155 (988 to 1344) | 944 (648 to 1336) | 9·0% (3·5 to 18·1) | 10·3% (3·2 to 24·4) | 0·0 | |
| Morocco | 176 (165 to 187) | 295 (263 to 331) | 429 (401 to 455) | 719 (642 to 808) | 5·1% (4·7 to 5·6) | 7·1% (4·9 to 9·9) | 0·0 | |
| Oman | 612 (560 to 667) | 679 (528 to 860) | 1272 (1165 to 1387) | 1410 (1098 to 1788) | 4·1% (3·5 to 4·7) | 5·4% (3·4 to 7·9) | 0·0 | |
| Palestine | 395 (368 to 425) | 742 (638 to 859) | 190 (177 to 205) | 357 (307 to 414) | 10·6% (9·7 to 11·5) | 14·3% (9·8 to 19·7) | 0·0 | |
| Qatar | 1731 (1554 to 1923) | 2790 (1869 to 4115) | 3017 (2707 to 3351) | 4861 (3256 to 7169) | 3·2% (2·8 to 3·5) | 9·4% (5·5 to 15·6) | 0·0 | |
| Saudi Arabia | 1364 (1285 to 1444) | 2161 (1901 to 2437) | 3223 (3035 to 34117) | 5107 (4491 to 5758) | 6·5% (6·1 to 6·9) | 15·4% (10·4 to 22·1) | 0·0 | |
| Sudan | 49 (44 to 55) | 65 (57 to 75) | 252 (226 to 280) | 334 (289 to 382) | 5·1% (3·3 to 6·7) | 4·6% (2·6 to 6·7) | 0·0 | |
| Syria | 44 (39 to 50) | 57 (50 to 64) | 1046 (925 to 1204) | 1353 (1185 to 1542) | 3·6% (3·1 to 4·2) | 4·4% (3·0 to 6·5) | 0·0 | |
| Tunisia | 281 (260 to 303) | 434 (393 to 477) | 884 (820 to 953) | 1365 (1237 to 1504) | 7·8% (7·2 to 8·4) | 10·9% (7·6 to 15·2) | 0·0 | |
| Turkey | 359 (336 to 382) | 552 (448 to 665) | 1316 (1231 to 1400) | 2026 (1644 to 2438) | 4·4% (4·1 to 4·6) | 6·3% (4·1 to 9·0) | 0·0 | |
| United Arab Emirates | 1751 (1675 to 1824) | 1353 (839 to 2357) | 3203 (3065 to 3338) | 2476 (1535 to 4312) | 4·7% (4·3 to 5·2) | 9·4% (4·9 to 18·6) | 0·0 | |
| Yemen | 35 (30 to 40) | 46 (39 to 54) | 105 (91 to 121) | 137 (117 to 161) | 5·4% (4·0 to 7·4) | 5·5% (3·6 to 8·3) | 0·0 | |
| South Asia | ||||||||
| Bangladesh | 48 (43 to 54) | 76 (67 to 86) | 129 (115 to 145) | 204 (180 to 230) | 2·6% (2·3 to 3·0) | 2·7% (1·8 to 3·8) | 0·3 | |
| Bhutan | 90 (82 to 98) | 195 (155 to 241) | 315 (288 to 345) | 684 (545 to 846) | 2·6% (2·4 to 2·8) | 3·4% (2·2 to 5·1) | 12·2 | |
| India | 75 (67 to 85) | 150 (132 to 173) | 253 (223 to 286) | 504 (441 to 578) | 3·5% (3·1 to 4·0) | 4·3% (2·9 to 6·2) | 0·0 | |
| Nepal | 58 (54 to 64) | 105 (93 to 120) | 188 (173 to 205) | 336 (298 to 386) | 5·3% (4·8 to 5·8) | 5·9% (4·1 to 8·3) | 0·0 | |
| Pakistan | 43 (40 to 46) | 82 (70 to 94) | 158 (146 to 170) | 298 (256 to 343) | 3·0% (2·8 to 3·3) | 3·7% (2·5 to 5·2) | 0·0 | |
| Southeast Asia, east Asia, and Oceania | ||||||||
| East Asia | ||||||||
| China | 563 (531 to 594) | 1470 (1289 to 1657) | 893 (843 to 943) | 2334 (2046 to 2631) | 5·3% (5·0 to 5·6) | 8·3% (5·6 to 11·7) | 0·0 | |
| North Korea | 61 (52 to 70) | 72 (61 to 83) | 35 (30 to 41) | 41 (35 to 48) | 5·2% (4·5 to 6·1) | 7·2% (4·9 to 10·1) | 0·0 | |
| Taiwan (province of China) | 1377 (1307 to 1464) | 2368 (2218 to 2561) | 2765 (2624 to 2939) | 4754 (4453 to 5142) | 5·1% (4·8 to 5·5) | 7·7% (5·5 to 10·6) | 0·0 | |
| Oceania | ||||||||
| American Samoa | 577 (492 to 668) | 711 (603 to 828) | 577 (492 to 668) | 711 (603 to 828) | 4·9% (4·0 to 5·8) | 5·9% (3·9 to 8·4) | 0·0 | |
| Cook Islands | 756 (692 to 825) | 1287 (918 to 1773) | 1056 (967 to 1152) | 1797 (1282 to 2476) | 3·4% (3·1 to 3·8) | 4·1% (2·6 to 6·4) | 0·0 | |
| Federated States of Micronesia | 147 (131 to 164) | 249 (211 to 290) | 131 (117 to 147) | 222 (189 to 260) | 3·9% (3·3 to 4·6) | 5·4% (3·7 to 7·5) | 0·0 | |
| Fiji | 195 (182 to 208) | 304 (269 to 340) | 498 (466 to 531) | 777 (689 to 870) | 3·4% (2·9 to 4·0) | 4·5% (3·2 to 6·1) | 0·0 | |
| Guam | 953 (826 to 1099) | 1164 (1000 to 1352) | 953 (826 to 1099) | 1164 (1000 to 1352) | 2·6% (2·2 to 3·1) | 3·1% (2·3 to 4·2) | 0·0 | |
| Kiribati | 200 (182 to 219) | 255 (209 to 317) | 259 (236 to 284) | 331 (272 to 411) | 12·0% (10·9 to 13·1) | 14·0% (9·9 to 19·5) | 0·0 | |
| Marshall Islands | 536 (499 to 580) | 837 (683 to 1036) | 499 (464 to 539) | 778 (635 to 964) | 12·4% (10·4 to 14·2) | 15·4% (11·1 to 21·3) | 0·0 | |
| Nauru | 1237 (1134 to 1342) | 840 (653 to 1124) | 1387 (12571to 1504) | 941 (732 to 1260) | 11·9% (6·9 to 17·1) | 7·8% (3·7 to 14·1) | 0·0 | |
| Niue | 2273 (1858 to 27652 | 2897 (1734 to 4478) | 849 (694 to 1028) | 1082 (648 to 1673) | 11·9% (9·4 to 15·1) | 11·9% (6·6 to 20·3) | 0·0 | |
| Northern Mariana Islands | 523 (443 to 610) | 651 (509 to 841) | 523 (443 to 610) | 651 (509 to 841) | 2·2% (1·8 to 2·7) | 3·5% (2·3 to 5·2) | 0·0 | |
| Palau | 1827 (1742 to 1916) | 3046 (2651 to 3482) | 1817 (1733 to 1907) | 3031 (2638 to 3464) | 11·3% (10·7 to 11·8) | 16·2% (12·0 to 21·4) | 0·0 | |
| Papua New Guinea | 73 (66 to 82) | 104 (87 to 126) | 106 (95 to 119) | 151 (127 to 183) | 2·6% (2·4 to 3·0) | 3·0% (2·1 to 4·2) | 2·1 | |
| Samoa | 235 (217 to 253) | 331 (291 to 378) | 319 (294 to 344) | 450 (396 to 514) | 5·3% (4·7 to 5·8) | 7·3% (5·2 to 10·2) | 0·0 | |
| Solomon Islands | 112 (99 to 128) | 176 (102 to 300) | 116 (102 to 132) | 182 (105 to 310) | 4·8% (3·9 to 6·1) | 5·8% (2·9 to 11·1) | 0·0 | |
| Tokelau | 1492 (1274 to 1751) | 2679 (2229 to 3236) | 3074 (2625 to 3608) | 5520 (4592 to 6666) | 23·1% (19·6 to 27·2) | 26·3% (17·8 to 38·5) | 0·0 | |
| Tonga | 240 (224 to 256) | 330 (297 to 367) | 290 (272 to 310) | 399 (360 to 444) | 4·7% (4·3 to 5·1) | 4·8% (3·8 to 6·0) | 88·3 | |
| Tuvalu | 757 (693 to 833) | 1010 (799 to 1307) | 835 (763 to 918) | 1114 (881 to 1441) | 19·0% (16·9 to 21·3) | 19·8% (13·2 to 28·2) | 0·0 | |
| Vanuatu | 100 (88 to 114) | 148 (104 to 212) | 92 (81 to 105) | 136 (95 to 195) | 3·1% (2·7 to 3·5) | 3·3% (2·0 to 5·2) | 0·0 | |
| Southeast Asia | ||||||||
| Cambodia | 83 (75 to 91) | 108 (97 to 120) | 233 (212 to 257) | 305 (275 to 340) | 5·0% (4·6 to 5·6) | 4·5% (3·2 to 6·1) | 0·0 | |
| Indonesia | 122 (115 to 131) | 283 (237 to 336) | 373 (351 to 399) | 864 (724 to 1028) | 3·0% (2·8 to 3·2) | 4·8% (3·3 to 7·0) | 0·0 | |
| Laos | 63 (60 to 66) | 89 (81 to 98) | 202 (193 to 211) | 286 (260 to 314) | 2·5% (2·1 to 2·9) | 2·1% (1·4 to 3·0) | 0·2 | |
| Malaysia | 448 (422 to 477) | 947 (844 to 1070) | 1200 (1130 to 1277) | 2537 (2261 to 2866) | 4·1% (3·8 to 4·3) | 6·5% (4·5 to 9·2) | 0·0 | |
| Maldives | 1164 (1085 to 1245) | 1712 (1343 to 2146) | 2145 (2000 to 2293) | 3153 (2475 to 3953) | 9·1% (6·9 to 10·9) | 12·2% (7·2 to 18·9) | 0·0 | |
| Mauritius | 671 (632 to 714) | 1232 (1113 to 1362) | 1553 (1463 to 1652) | 2853 (2576 to 3152) | 6·4% (6·0 to 6·8) | 9·3% (6·5 to 12·7) | 0·0 | |
| Myanmar | 60 (56 to 63) | 109 (99 to 120) | 233 (220 to 246) | 424 (385 to 468) | 4·4% (4·0 to 4·8) | 4·8% (3·2 to 6·8) | 0·0 | |
| Philippines | 156 (142 to 172) | 259 (228 to 295) | 396 (362 to 437) | 659 (580 to 751) | 4·3% (3·8 to 4·8) | 5·6% (3·8 to 7·6) | 0·0 | |
| Seychelles | 673 (642 to 701) | 935 (791 to 1103) | 1440 (1376 to 1502) | 2003 (1694 to 2362) | 4·7% (4·4 to 4·9) | 6·1% (4·1 to 9·0) | 0·0 | |
| Sri Lanka | 156 (146 to 167) | 234 (211 to 261) | 555 (519 to 593) | 830 (749 to 926) | 4·0% (3·7 to 4·3) | 4·4% (3·1 to 6·0) | 1·8 | |
| Thailand | 307 (286 to 330) | 595 (517 to 680) | 759 (708 to 818) | 1475 (1282 to 1686) | 3·9% (3·6 to 4·2) | 6·8% (4·7 to 9·6) | 0·0 | |
| Timor-Leste | 82 (74 to 90) | 97 (73 to 132) | 226 (205 to 249) | 269 (202 to 365) | 6·5% (5·6 to 7·4) | 5·1% (3·2 to 7·7) | 0·0 | |
| Vietnam | 167 (157 to 177) | 288 (241 to 344) | 512 (483 to 545) | 884 (741 to 1056) | 5·7% (4·4 to 6·9) | 7·1% (4·3 to 10·7) | 0·1 | |
| Sub-Saharan Africa | ||||||||
| Central sub-Saharan Africa | ||||||||
| Angola | 57 (50 to 64) | 94 (75 to 117) | 195 (172 to 222) | 326 (260 to 405) | 2·7% (2·4 to 3·1) | 3·2% (2·1 to 4·7) | 0·0 | |
| Central African Republic | 30 (28 to 33) | 47 (41 to 56) | 61 (56 to 66) | 95 (83 to 113) | 6·1% (5·6 to 6·6) | 7·7% (5·6 to 10·4) | 0·0 | |
| Congo (Brazzaville) | 47 (43 to 51) | 70 (58 to 86) | 93 (86 to 102) | 139 (115 to 172) | 2·2% (1·9 to 2·6) | 2·5% (1·7 to 3·6) | 0·2 | |
| Democratic Republic of the Congo | 20 (19 to 22) | 25 (22 to 29) | 43 (41 to 46) | 54 (46 to 62) | 4·0% (3·5 to 4·5) | 4·3% (2·8 to 6·3) | 0·0 | |
| Equatorial Guinea | 222 (196 to 252) | 507 (431 to 603) | 554 (488 to 627) | 1265 (1074 to 1504) | 2·8% (2·5 to 3·2) | 3·5% (2·1 to 5·5) | 0·0 | |
| Gabon | 245 (228 to 261) | 452 (395 to 521) | 541 (504 to 576) | 997 (872 to 1151) | 3·4% (3·1 to 3·6) | 5·3% (3·8 to 7·3) | 0·0 | |
| Eastern sub-Saharan Africa | ||||||||
| Burundi | 29 (27 to 31) | 40 (35 to 47) | 86 (80 to 93) | 120 (103 to 141) | 10·0% (8·8 to 11·2) | 12·3% (8·7 to 16·8) | 0·0 | |
| Comoros | 83 (74 to 94) | 112 (96 to 133) | 187 (166 to 213) | 252 (216 to 299) | 5·6% (4·7 to 6·6) | 6·2% (4·2 to 8·7) | 0·0 | |
| Djibouti | 54 (47 to 61) | 72 (58 to 87) | 88 (77 to 100) | 119 (96 to 144) | 1·6% (1·4 to 1·9) | 1·9% (1·2 to 2·8) | 0·0 | |
| Eritrea | 15 (13 to 17) | 20 (17 to 23) | 46 (42 to 52) | 62 (54 to 72) | 2·5% (2·2 to 2·8) | 2·4% (1·7 to 3·3) | 0·0 | |
| Ethiopia | 26 (24 to 28) | 38 (33 to 43) | 75 (69 to 80) | 107 (94 to 122) | 3·0% (2·5 to 3·4) | 2·6% (1·7 to 3·7) | 0·2 | |
| Kenya | 103 (95 to 112) | 176 (152 to 204) | 248 (229 to 270) | 423 (367 to 492) | 5·2% (4·6 to 5·9) | 6·4% (4·4 to 8·8) | 0·1 | |
| Madagascar | 22 (19 to 25) | 31 (26 to 35) | 70 (61 to 79) | 98 (85 to 113) | 4·0% (3·6 to 4·5) | 5·4% (3·9 to 7·3) | 0·0 | |
| Malawi | 43 (40 to 45) | 51 (43 to 60) | 107 (101 to 113) | 126 (108 to 149) | 9·8% (8·9 to 11·0) | 7·9% (5·4 to 10·9) | 0·0 | |
| Mozambique | 36 (34 to 38) | 43 (35 to 54) | 100 (95 to 106) | 121 (97 to 151) | 7·4% (7·0 to 7·9) | 4·9% (3·3 to 7·3) | 0·0 | |
| Rwanda | 53 (47 to 59) | 96 (76 to 119) | 153 (137 to 172) | 278 (221 to 344) | 6·6% (5·8 to 7·5) | 8·6% (5·7 to 12·5) | 0·0 | |
| Somalia | 7 (6 to 8) | 9 (8 to 11) | 21 (19 to 23) | 28 (24 to 33) | 5·4% (4·7 to 6·2) | 6·4% (4·9 to 8·5) | 0·0 | |
| South Sudan | 29 (27 to 30) | 34 (30 to 41) | 83 (79 to 88) | 100 (88 to 119) | 9·3% (4·3 to 15·8) | 11·1% (4·3 to 20·5) | 0·0 | |
| Tanzania | 40 (37 to 43) | 54 (42 to 71) | 103 (95 to 111) | 140 (108 to 183) | 3·7% (3·1 to 4·3) | 3·6% (2·3 to 5·4) | 0·0 | |
| Uganda | 46 (43 to 50) | 55 (48 to 62) | 131 (121 to 142) | 154 (135 to 176) | 5·7% (4·5 to 7·6) | 4·3% (2·6 to 6·8) | 0·0 | |
| Zambia | 62 (58 to 67) | 76 (59 to 102) | 205 (191 to 222) | 252 (193 to 336) | 5·6% (5·1 to 6·1) | 5·1% (3·4 to 7·4) | 0·1 | |
| Southern sub-Saharan Africa | ||||||||
| Botswana | 464 (436 to 494) | 1257 (1124 to 1392) | 1144 (1073 to 1218) | 3097 (2768 to 3429) | 6·2% (5·7 to 6·6) | 11·7% (8·0 to 16·4) | 0·0 | |
| Eswatini | 226 (215 to 238) | 340 (296 to 389) | 593 (563 to 625) | 893 (775 to 1021) | 6·4% (6·0 to 6·8) | 6·6% (4·4 to 9·0) | 0·0 | |
| Lesotho | 125 (115 to 136) | 220 (188 to 255) | 390 (358 to 425) | 686 (586 to 795) | 13·0% (11·9 to 14·2) | 14·7% (10·1 to 20·9) | 0·0 | |
| Namibia | 410 (382 to 441) | 806 (702 to 930) | 964 (899 to 1039) | 1897 (1652 to 2190) | 9·4% (8·7 to 10·1) | 15·0% (10·6 to 20·4) | 0·0 | |
| South Africa | 478 (448 to 513) | 766 (666 to 890) | 1202 (1128 to 1290) | 1927 (1675 to 2238) | 9·1% (8·5 to 9·8) | 14·2% (10·8 to 18·2) | 0·0 | |
| Zimbabwe | 75 (69 to 83) | 108 (90 to 130) | 211 (194 to 231) | 303 (253 to 364) | 7·1% (6·5 to 7·8) | 8·3% (5·8 to 11·5) | 0·0 | |
| Western sub-Saharan Africa | ||||||||
| Benin | 29 (26 to 32) | 42 (37 to 49) | 79 (72 to 86) | 116 (101 to 133) | 2·2% (2·1 to 2·5) | 2·2% (1·6 to 3·0) | 0·2 | |
| Burkina Faso | 41 (39 to 44) | 70 (64 to 78) | 119 (113 to 125) | 202 (183 to 224) | 5·1% (4·9 to 5·4) | 5·8% (4·1 to 8·2) | 0·0 | |
| Cameroon | 49 (42 to 56) | 77 (65 to 90) | 121 (104 to 139) | 192 (161 to 223) | 3·1% (2·7 to 3·6) | 3·2% (2·4 to 4·2) | 0·0 | |
| Cape Verde | 183 (170 to 196) | 325 (261 to 386) | 380 (354 to 407) | 676 (542 to 802) | 5·0% (4·7 to 5·4) | 7·1% (5·0 to 9·6) | 0·0 | |
| Chad | 28 (25 to 33) | 33 (28 to 40) | 71 (62 to 83) | 85 (71 to 101) | 4·3% (3·7 to 4·9) | 3·8% (2·8 to 5·3) | 0·0 | |
| Côte d'Ivoire | 72 (66 to 79) | 110 (94 to 129) | 170 (155 to 186) | 259 (221 to 302) | 5·3% (2·6 to 10·6) | 6·8% (3·0 to 14·0) | 0·0 | |
| The Gambia | 39 (38 to 41) | 49 (44 to 55) | 118 (113 to 124) | 147 (132 to 166) | 5·0% (4·8 to 5·3) | 4·6% (3·4 to 6·2) | 0·0 | |
| Ghana | 72 (66 to 81) | 121 (104 to 142) | 189 (171 to 210) | 316 (271 to 371) | 3·7% (2·9 to 5·1) | 4·6% (3·0 to 7·3) | 0·0 | |
| Guinea | 50 (45 to 55) | 81 (71 to 93) | 124 (112 to 136) | 201 (174 to 230) | 4·3% (3·6 to 5·3) | 4·4% (3·1 to 6·2) | 0·0 | |
| Guinea-Bissau | 58 (55 to 62) | 78 (71 to 85) | 178 (167 to 190) | 238 (215 to 259) | 7·8% (6·9 to 8·6) | 7·4% (5·3 to 10·0) | 0·0 | |
| Liberia | 66 (62 to 70) | 94 (81 to 114) | 154 (145 to 164) | 222 (191 to 267) | 11·3% (8·5 to 15·7) | 13·7% (8·2 to 23·1) | 0·1 | |
| Mali | 30 (27 to 32) | 39 (34 to 44) | 80 (74 to 87) | 105 (92 to 118) | 3·0% (2·3 to 3·6) | 2·5% (1·6 to 3·8) | 0·0 | |
| Mauritania | 65 (59 to 71) | 93 (81 to 106) | 210 (192 to 231) | 301 (263 to 342) | 3·7% (3·2 to 4·2) | 3·7% (2·7 to 5·2) | 0·0 | |
| Niger | 30 (29 to 32) | 37 (34 to 42) | 71 (67 to 75) | 87 (78 to 97) | 5·5% (5·2 to 5·8) | 5·5% (3·9 to 7·4) | 0·0 | |
| Nigeria | 81 (73 to 90) | 106 (91 to 123) | 192 (173 to 213) | 249 (215 to 290) | 3·5% (3·2 to 3·9) | 3·4% (2·5 to 4·8) | 0·1 | |
| São Tomé and Príncipe | 117 (109 to 125) | 183 (134 to 258) | 234 (219 to 252) | 367 (268 to 518) | 5·6% (5·3 to 6·0) | 6·3% (4·0 to 9·9) | 0·0 | |
| Senegal | 66 (60 to 74) | 90 (80 to 102) | 158 (142 to 176) | 215 (191 to 243) | 4·4% (4·0 to 4·9) | 4·4% (3·2 to 5·9) | 0·1 | |
| Sierra Leone | 73 (66 to 81) | 110 (95 to 128) | 241 (217 to 269) | 363 (312 to 422) | 13·4% (12·0 to 14·9) | 14·9% (10·5 to 20·5) | 0·4 | |
| Togo | 40 (37 to 44) | 62 (54 to 71) | 96 (88 to 105) | 146 (128 to 169) | 5·2% (3·9 to 6·4) | 5·9% (3·7 to 8·4) | 0·0 | |
Estimates in parentheses are 95% uncertainty intervals. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. GDP=gross domestic product.
Estimates for Venezuela are presented as 2014 USD. $PPP=2020 purchasing-power parity-adjusted US$.
Between 1995 and 2019, inflation-adjusted health spending per person increased in 182 of the 204 countries and territories considered. For health spending for every country and year from 1995 to 2050, see the appendix (p 142). We estimate that global health spending will reach $14·3 trillion (95% UI 13·7–15·0) by 2050.
Between 2012 and 2019, development assistance for health contributions plateaued at an annualised rate of 1·2%. However, in 2020, total development assistance for health (including development assistance for health for COVID-19) amounted to $54·8 billion, a $14·0 billion (34·6%) increase from 2019. The increase is largely (96·5%) attributable to disbursements for the health response to COVID-19, which amassed $13·7 billion of health assistance (or 24·9% of total development assistance for health) in 2020 (figure 1). For year-on-year comparisons, we observed decreases in assistance targeted toward reproductive and maternal health (−6·8%), tuberculosis (−5·5%), and malaria (−2·2%). Meanwhile, development assistance for sector-wide approaches and health system strengthening increased (8·8%). Of note is the small proportion of health systems strengthening resources (14·9% in 2020) that have been targeted towards pandemic preparedness.
Figure 1.
Development assistance for health by health focus area, 1990–2020
HSS/SWAps=health system strengthening and sector-wide approaches. *Other captures development assistance for health for which we have health focus area information but is not identified as being allocated to any of the health focus areas listed. Health assistance for which we have no health focus area information is designated as unassigned. †2019 and 2020 disbursement estimates are preliminary.
Figure 2A shows the main sources of development assistance for health in 2020. Most of the funding came from the USA, the UK, and the Bill & Melinda Gates Foundation. The key disbursing agencies for these resources were USA bilateral organisations, non-governmental organisations, and the World Bank (figure 2B).
Figure 2.
Development assistance for health, 1990–2020
(A) Development assistance for health by source of funding. (B) Development assistance for health by channel of assistance. (C) Development assistance for other infectious disease programme areas. (D) Development assistance for health systems strengthening programmes. CEPI=Coalition for Epidemic Preparedness Innovations. GAVI=Gavi, the Vaccine Alliance. HSS/SWAps=health systems strengthening and sector-wide approaches. IBRD=International Bank for Reconstruction and Development. NGO=non-governmental organisation. PAHO=Pan American Health Organization. UNFPA=UN Population Fund. *Other captures development assistance for health for which we have source information but is not identified as being allocated to any of the health focus areas listed. Health assistance for which we have no health focus area information is designated as unassigned. †2019 and 2020 disbursement estimates are preliminary. ‡Regional development banks include the African Development Bank, the Asian Development Bank, and the Inter-American Development Bank. §Other bilateral development agencies include Austria, Belgium, Denmark, Finland, Greece, Ireland, Italy, Luxembourg, the Netherlands, New Zealand, Norway, South Korea, Spain, Sweden, Switzerland, the United Arab Emirates, the European Commission, and the European Economic Area.
Figure 3A shows the flow of development assistance for health contributions toward COVID-19 from the original source of funds, through the disbursing agency, and to the targeted programme area of focus as available for 2020. A total of $13·7 billion was disbursed in 2020 toward addressing the health-related effects of COVID-19 in low-income and middle-income countries. Of this total, the largest bilateral contributors were Japan ($2·3 billion), Germany ($1·3 billion), and the USA ($0·9 billion). Most of Japan's support ($1·4 billion) was disbursed through its own bilateral agencies, mostly the Japanese International Cooperation Agency, and was targeted to India ($360·6 million), Morocco ($204·7 million), and Indonesia ($194·4 million). Sub-Saharan Africa ($2·7 billion); south Asia ($2·2 billion); and southeast Asia, east Asia, and Oceania ($2·0 billion) were the main geographical super-regions that received COVID-19 funds. Both the UK and Germany primarily supported the Coalition for Epidemic Preparedness Innovations (CEPI; $64·3 million from the UK and $56·9 million from Germany). The Asian Development Bank, Gavi, and the Global Fund are the international development agencies that channelled most of the resources committed or disbursed for COVID-19.
Figure 3.
Distribution of development assistance for health for COVID-19 by programme area, recipient region, and income group, 2020
(A) Flow of development assistance for health disbursements from source to channel to programme area for COVID-19. Data are in million (m) or billion (b) 2020 US$. (B) Percentage of disbursed development assistance for health for COVID (excluding global initiatives) and percentage of total deaths from COVID-19 by GBD super-region. (C) Percentage of disbursed development assistance for health for COVID-19 (excluding global initiatives) and percentage of total deaths from COVID-19 by World Bank income group. The COVID-19 burden is represented by the percentage of total COVID-19 deaths in 2020 for lower-middle-income countries only, as high-income countries to not receive development assistance. CEPI=Coalition for Epidemic Preparedness Innovations. DAC=Development Assistance Committee. GAVI=Gavi, the Vaccine Alliance. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study HSS/SWAps=health systems strengthening and sector-wide approaches. IBRD=International Bank for Reconstruction and Development. NGO=non-governmental organisation. PAHO=Pan American Health Organization. UNFPA=UN Population Fund. *Other non-DAC governments include Afghanistan, Angola, Argentina, Azerbaijan, Bangladesh, Bhutan, Brazil, Brunei, Bulgaria, Côte d'Ivoire, Cameroon, Central African Republic, Chad, China, Colombia, Croatia, Democratic Republic of the Congo, Egypt, Estonia, Ethiopia, Gabon, Guinea, India, Indonesia, Iran, Iraq, Jamaica, Jordan, Kenya, Kuwait, Latvia, Lebanon, Libya, Lithuania, Madagascar, Malaysia, Malta, Monaco, Myanmar, Nigeria, Oman, Pakistan, Palestine, Peru, Qatar, Romania, Russia, São Tomé and Príncipe, Saudi Arabia, Serbia, Singapore, South Africa, South Sudan, Sudan, Syria, Taiwan (province of China), Thailand, Togo, Turkey, Uganda, Ukraine, United Arab Emirates, Yemen, and Zimbabwe. †Other DAC governments include Australia, Austria, Belgium, Czechia, Denmark, Finland, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, the Netherlands, New Zealand, Norway, Poland, Portugal, Slovakia, Slovenia, South Korea, Spain, Sweden, and Switzerland. ‡Development banks include the African Development Bank, the Asian Development Bank, and the Inter-American Development Bank. UN agencies include PAHO, UNAIDS, UNFPA, UNICEF, and Unitaid. §Country-level coordination includes planning, monitoring, and evaluations; risk communication and community engagement; and travel restrictions.
Figure 3B shows the allocation of development assistance for health for COVID-19 in the GBD super-regions. 23·5% of donors' COVID-19 resources were for global initiatives and did not directly target a single country or region. Examples of such investments include vaccine development and procurement, and partner organisations' coordination. The specific region to receive the most development assistance for health for COVID-19 was sub-Saharan Africa (28·8%). This figure also illustrates the poor alignment between COVID-19 assistance for health and COVID-19 burden. In 2020, 34·3% of recorded COVID-19 deaths in low-income and middle-income countries occurred in Latin America, but countries in Latin America received 7·7% of all development assistance for health for COVID-19 allocated to any specific country.
The proportion of COVID-19 funds that were new resources versus those that were previously budgeted and repurposed to COVID-19 is shown in figure 4. Of the total $13·7 billion in development assistance for health for COVID-19, $1·4 billion (9·9%) was money from already existing projects that was redirected toward COVID-19-related response activities. $12·3 billion (90·1%) of this funding was additional, previously unbudgeted resources. Across the disbursing entities, the Asian Development Bank ($1·8 billion) and Gavi ($1·8 billion) disbursed most of their resources as new money. Relative contributions for health and non-health response are shown in table 2. The health response accounted for 9·8% of the overall response, with the non-health response making up the dominant share ($125·4 billion) of the disbursed response. The types of contributions made and disbursed across the various disbursing agencies as part of the health-related COVID-19 response are shown in table 3. Grants made up most contributions, at $8·7 billion (63·6%), compared with loans at $4·8 billion (34·9%).
Figure 4.
Type of health assistance provided towards the COVID-19 pandemic, 2020
This figure shows the amount of global development assistance for health for the COVID-19 pandemic that was repurposed versus new spending. Overall, 90·1% of global development assistance for health was new money, and 9·9% was repurposed money. ADB=Asian Development Bank. AfDB=African Development Bank. CEPI=Coalition for Epidemic Preparedness Innovations. GAVI=Gavi, the Vaccine Alliance. Global Fund=The Global Fund to Fight AIDS, Tuberculosis and Malaria. IDB=Inter-American Development Bank. NGO=Non-governmental organisation. PAHO=Pan American Health Organization. UNFPA=UN Population Fund.
Table 2.
Estimates of global COVID-19-related disbursements and commitments of health and non-health funds, 2020
| Total | Health-related COVID-19 funds | Non-health-related COVID-19 funds | |
|---|---|---|---|
| Commitment | 243·804 | 61·5121 | 182·2919 |
| Disbursement | 139·1044 | 13·66932 | 125·4351 |
Units are billion US$. Using IHME's estimate of health-related disbursements, we estimated commitments and disbursements by health and non-health spending using data from the United Nations' Office for the Coordination of Humanitarian Affairs Financial Tracking Service, compiled by the Center for Disaster Protection.38 In the case where a grant was allocated to multiple sectors (health, as well as one or more non-health sectors), we calculated the funds attributed to health spending by multiplying the total grant amount by 1 divided by the number of sectors represented. Proportions of global commitments and disbursements by type of spending (health and non-health) were multiplied by IHME's estimate of health-related disbursements. IHME=Institute for Health Metrics and Evaluation.
Table 3.
Development assistance for health specific to COVID-19 in 2020, by channel and type of assistance (millions of 2020 US$)
| Total | New funds | Repurposed funds | Commitment | Disbursement | Grant | Loan | |
|---|---|---|---|---|---|---|---|
| African Development Bank | 566·3 | 566·3 | .. | 589·1 | 566·3 | 137·7 | 428·5 |
| Asian Development Bank | 1817·0 | 1817·0 | .. | 2103·1 | 1817·0 | 184·0 | 1633·0 |
| Bilateral development agencies | 2775·5 | 2493·4 | 282·0 | 3057·3 | 2775·5 | 1542·1 | 1032·7 |
| Bill & Melinda Gates Foundation | 313·3 | 313·3 | .. | 313·3 | 313·3 | 313·3 | .. |
| Coalition for Epidemic Preparedness Innovations | 278·7 | 278·7 | .. | 598·0 | 278·7 | 227·8 | 51·0 |
| European Commission | 605·6 | 565·9 | 39·6 | 718·9 | 605·6 | 605·6 | .. |
| Gavi, the Vaccine Alliance | 1903·3 | 1827·2 | 76·1 | 1903·3 | .. | 1903·3 | .. |
| The Global Fund | 977·9 | 257·3 | 720·7 | 977·9 | .. | 977·9 | .. |
| Inter-American Development Bank | 363·9 | 363·9 | .. | .. | 363·9 | .. | 363·9 |
| Non-governmental organisation | 280·6 | 267·5 | 13·1 | 153·1 | 280·6 | 280·6 | .. |
| Pan American Health Organization | 218·7 | 218·7 | .. | .. | 218·7 | 218·7 | .. |
| UNAIDS | 9·0 | 0·6 | 8·4 | 27·3 | 9·0 | 9·0 | .. |
| United Nations Population Fund | 96·9 | 56·5 | 40·4 | 30·3 | 74·2 | 96·9 | .. |
| UNICEF | 614·2 | 506·3 | 107·9 | 140·0 | 485·9 | 614·2 | .. |
| Unitaid | 17·7 | .. | 17·7 | .. | 17·7 | 17·7 | .. |
| USA foundations* | 93·7 | 93·7 | .. | 93·7 | .. | 93·7 | .. |
| World Bank International Bank for Reconstruction and Development | 913·1 | 873·1 | 40·0 | 694·5 | 913·1 | .. | 913·1 |
| World Bank International Development Association | 528·5 | 519 | 9·4 | 442·4 | 528·5 | 181·0 | 347·4 |
| WHO | 1295·5 | 1295·5 | .. | 7508·4 | 1295·5 | 1295·5 | .. |
| Total | 13 669·4 | 12 313·9 | 1355·3 | 19 350·6 | 10 543·5 | 8699 | 4769·6 |
Spending data are reported in millions of 2020 US$, where estimates were available. In-kind contributions such as personal protective equipment was assumed to be grants. $200·7 million in bilateral development agencies funds were not able to be identified as either grants or loans.
Commitments of at least $10 000 from USA foundations internationally and in the USA.
Relative to global spending, development assistance for health for COVID-19 remained small in 2020 (0·1%), and it is too early to know how much domestic spending has focused on COVID-19. Although there is a great deal of uncertainly, future spending on health is expected to continue to climb, albeit at a slower pace than anticipated before the pandemic. We estimated that global spending on health will reach $9·9 trillion (95% UI 9·7–10·1) in 2030 and $14·3 trillion (13·7–15·0) in 2050. Health spending over time for each income group is shown in figure 5, which highlights that health spending disparities are expected to persist and that there is a great deal of variation in total spending within income groups. We estimate that in 2050, low-income countries will spend $46 (95% UI 44–47) per person, lower-middle-income countries will spend $150 (141–159) per person, upper-middle-income countries will spend $1001 (922–1083) per person, and high-income countries will spend $8536 (8074–9032) per person.
Figure 5.
Distribution of total health spending per capita in 2019 and 2050 by income group
(A) 2019. (B) 2050. Estimates are reported in 2020 US$. The x-axes are presented in a natural logarithmic scale. Vertical lines represent the mean for each distribution. The World Bank income classification does not include Cook Islands, Niue, and Tokelau. The Cook Islands and Niue were assigned to the high-income group, and Tokelau was assigned to the upper-middle-income group.
Discussion
The context in which COVID-19 has spread globally is one of grave inequality in access to health services.39, 40 This research highlights how this inequality exists at the national level within the health sector. In 2019, national health spending ranged from $7 to $11 345 per person, with government health spending ranging from $2 to $6578 per person (table 1, appendix p 142). Development assistance for health reached $40·4 billion in 2019 and increased to $54·8 billion in 2020 because of the additional resources provided in response to COVID-19. Although development assistance for health makes up less than 1·0% of health spending in most middle-income countries, development assistance for health was 24·6% (95% UI 24·0–25·1) of total health spending in low-income countries. Health spending per person has grown almost universally between 1995 and 2019 and is expected to rise in 195 of 204 countries and territories to 2050, but expected spending remains highly unequal. The finding of rising global health spending before the onset of the pandemic is aligned with what is reported in the WHO 2020 Global Health Spending Report.4 In both our study and WHO spending report, the pandemic is expected to perpetuate already existing vulnerabilities in global health spending, such as inequalities in spending across and within income groups.
Our estimates of development assistance for health for COVID-19 show that in 2020, a total of $13·7 billion was disbursed to aid the health response in low-income and middle-income countries. This figure constituted over a quarter of all development assistance for health, and is evidence of how resources can be scaled quickly when needed. Resources focused on country-level coordination, supply chain and logistics, case management and treatment, surveillance, rapid-response teams, case investigation, maintaining essential health services and systems, and infection prevention and control have received modest contributions.
Previous estimates of development assistance for health for COVID-19 vary greatly, primarily because each set of estimates focused on tracking different aspects of the international response. Our total estimates of resources committed is similar to that reported by the Economist Intelligence Unit COVID-19 Health Funding Tracker, which estimated $13·8 billion pledged as of December, 2020, although it excluded support for individual countries. Our estimates of resources committed are much smaller in magnitude, however, than what is reported by the other trackers. As of its last update in April 2020, the Kaiser Family Foundation estimated $19 billion had been pledged toward the health sector response.24 As of Jan 20, 2021, the Centre for Disaster Protection online visualisation tool reported $100·7 billion had been committed in loans (concessional and non-concessional) and $14·24 billion had been committed in grants.25 A key difference between these estimates and our own is that most of the other research on this topic has not estimated disbursements, and instead focused on commitments or pledges. In practice, disbursements are generally less than commitments. Moreover, in the case of unexpected crisis, disbursing resources can take much longer than the time span that we have predicted. As of Dec 13, 2020, the Devex database reported 987 programme announcements worth $193·1 billion, 810 grants worth $2·9 billion, 2171 tenders worth $4·7 billion, and 1133 contracts worth $1·7 billion.26 Unlike our estimates, these have a much broader focus and include support for the humanitarian response (outside of the health sector).
Only a few studies have estimated the resources needed for an effective pandemic response.3, 12 Previously, the Commission on a Global Health Risk Framework for the Future, which was set up after the Ebola epidemic, estimated that annually $4·5 billion was needed globally for pandemic preparedness, by contrast with an expected annual loss of more than $60 billion from potential pandemics. One study12 on a sample of 73 low-income and middle-income countries estimated that the additional cost of responding to the COVID-19 pandemic was between $33 billion and $62 billion.
One consequence of the COVID-19 pandemic that is different from other recent epidemics, such as the Ebola outbreak in 2014 or MERS-CoV in 2012, is the significant economic toll on high-income countries. Precisely how the economic recession will affect governments' willingness to maintain record development assistance resources for low-income and middle-income countries is not known. Some countries have already restructured their aid budgets to prioritise addressing domestic challenges. For instance, the UK has passed a bill to reduce the foreign aid commitment from 0·7% of GDP to 0·5% of GDP to enable management of the national budget.41 In addition to this, Kobayashi and colleagues42 suggest that the global scale of the COVID-19 pandemic might have weakened public sentiment about contributing public resources abroad, given the immense challenges at home. In the next decade, development assistance for health disbursements might grow at a substantially slower pace and could rely more heavily on private philanthropy and multilateral institutions.
Nonetheless, as the pandemic has evolved, so have calls for support for low-income and middle-income countries. These calls for support are not only to address immediate health needs but also to provide additional social safety net support and economic relief. Multilateral institutions such as the IMF, the World Bank, and regional development banks including the Asian Development Bank, the Inter-American Development Bank, and the African Development Bank have all responded promptly to these requests with various packages. However, much of this support consists of loans that will add to national debt, with potential for long-term effects on growth and the ability to increase social spending.43 Additionally, there are calls for debt repayment suspension and a repurposing of such resources towards bolstering struggling economies.
The pandemic's effect on other essential service provisions has been notable, largely because addressing the urgent demands of the pandemic required a realignment of health resources, including personnel, hospital supplies, services, data, and funding, and has made accessing health services safely substantially more challenging.44 At the beginning of the pandemic, when some health-care systems were overwhelmed by the unfolding crisis, the complete refocus of resources seemed to be the most logical response. However, over time, this burden on the health system has made evident the importance of strong health systems worldwide in maintaining global health security, and made it even more obvious that targeting development assistance contributions to the strengthening of the broader health system is a crucial investment for global health security overall.45, 46 Although contributions toward health system strengthening have improved, the relative proportion of development assistance funds that are targeted toward such activities remains small, with an even smaller amount allocated toward pandemic preparedness.47 The pandemic has shown how quickly a local epidemic can develop into a global crisis, and the need for global activity and cooperation to be commensurate with this challenge.
The COVID-19 pandemic has also had ramifications for the Sustainable Development Goals (SDGs) more broadly. According to the SDGs Report 2020,48, 49 globally, progress has been insufficient and the pandemic has only worsened the precarious progress made on most of the goals. For instance, in several countries in sub-Saharan Africa it seemed the health toll of the pandemic was less than expected in 2020, but the economic fallout due to public health measures such as lockdowns might have had much more severe consequences and pushed an additional 23 million people into poverty.50, 51 The mitigation strategies used to reduce the impact of the pandemic have also led to a meaningful global response. So far, development assistance contribution that falls outside of the health sector has been much larger than health-related contributions ($125·4 billion vs $13·7 billion). This reflects how the effect of the COVID-19 pandemic has reverberated outside of the health sector, affecting the social, economic, and environmental sectors in most countries.
Another challenge associated with raising and disbursing record-setting amounts of development assistance is the crucial task of allocating these scarce resources. Despite the differences in the burden of the pandemic across geographical regions, the patterns in the allocation of development assistance for health for COVID-19 remain largely the same as development assistance for health in the past, with Latin America and the Caribbean receiving little support despite their high burden. In future, key contributions must be aligned with where they are needed the most.
The distribution of the COVID-19 vaccine has generated much public discourse.52 Although the initial discussion in popular media and among policy makers focused on national interests, the Access to COVID-19 Tools (ACT) Accelerator partnership was launched in April, 2020, by WHO, the European Commission, and the French Government to ensure pooled and equitable distribution of tools to fight COVID-19. ACT-Accelerator was estimated to need $33 billion for its work. Of ACT-Accelerator's four key pillars, the pillar that focuses on vaccines is the COVID-19 Vaccines Global Access Facility, which is led by Gavi, WHO, and CEPI. Leveraging its previous experience with managing advanced market commitment for immunisation, Gavi was tasked with facilitating the procurement of vaccines for 92 middle-income countries through the COVID advance market commitment. The objective was to raise $2 billion before the end of 2020 to enable it to support access to vaccines irrespective of income.53 As of August, 2021, $17·9 billion had been committed to the ACT Accelerator partnership.
COVID-19 has highlighted the nuanced role health systems play in providing health security. Although robust health systems—with capacity to test, track, and treat those with the virus and ability to access and provide vaccines quickly and efficiently—are necessary for keeping deaths from COVID-19 at bay, it has also been made clear that a robust health system alone is not sufficient.54 COVID-19 mortality rates have varied greatly across the globe, but there is little consensus on what is driving this variation, with key historical measures of pandemic preparedness highlighting capacity gaps, but not accurately predicting where the outcomes will be the best or worst.55 To be successful in fighting the virus and preventing substantial loss, a constellation of characteristics that fall both inside and outside of the traditional health system is necessary. These characteristics include leadership, public health system capacity, social safety nets, and trust in the systems providing information and care.56, 57 A painful lesson of this pandemic is that global health security is only as strong as its weakest link. It is crucial that those working in the health sector ensure that the entire health system is in fact robust, and that policy makers outside of the health sector also be prepared for many potential crises that can accompany a pandemic.
This research highlights the context in which COVID-19 spread quickly across the globe—one of enormous variation in health-care spending. Robust health systems require more resources, and those working in government and advocacy outside of the health sector are encouraged to see COVID-19 and the staggering loss of life and broader setbacks in global development as indicators of the importance of investing in health in and outside the health system, and building governments and social systems that can also contribute towards health security.
This study has several limitations. The data were extracted from multiple sources with different reporting structures and components included. We kept definitions and methods as consistent as possible across data sources to ensure a reliable estimate of resources. Furthermore, given that the pandemic is ongoing and development projects take some time to reach implementation, disbursement could still be low even where commitments have been made. Moreover, global health resource tracking does not allow comparable tracking of how domestic resources are spent on health and does not allow for comprehensive estimates of domestic health spending on COVID-19. More information is needed to assess how governments, households, and private organisations are spending health resources, and what resources are available for responding to health emergencies. Health financing reporting, especially in many low-income and middle-income countries, but also in high-income countries, is constrained by how timely domestic health spending data are available. Health financing data are not collated in a manner that is shareable or comparable across time and country. As countries deliberate on ways to rebuild systems after the pandemic, the health financing architecture and equity are important aspects to consider. Finally, our quantification of uncertainty captures some types of uncertainty, but not all types of uncertainty. It is included here as a relative quantification of where we have the most confidence in our estimates.
Health spending in 2019, before the COVID-19 pandemic, ranged widely, and marks tremendous variation in the access to essential health services and universal health coverage. Much more money is needed to fully address the effects of the pandemic in most low-income and middle-income countries, along with access to key tools such as vaccines. Moreover, long-term projections suggest that health inequalities are likely to persist and that international efforts to invest in global public goods related to global pandemic preparedness are essential. Resources are needed urgently to mitigate the loss associated with the COVID-19 pandemic and fund systems that can prevent and respond quicker to the next global health crisis.
Data sharing
Data used for this study were extracted from publicly available sources that are listed in the appendix (pp 7, 28–33, 65, 81–82, 92, 117). Further details are available on the Global Health Data Exchange website at http://ghdx.healthdata.org/series/financing-global-health-fgh
Declaration of interests
D McCracken's position was supported in part through the Wellcome Trust, and by the Department of Health and Social Care using UK aid funding managed by the Fleming Fund. R Ancuceanu reports consulting fees from AbbVie and AstraZeneca; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Sandoz, AbbVie, and Braun Medical; and support for attending meetings or travel from AbbVie and AstraZeneca, all outside the submitted work. M Ausloos and C Herteliu report grants or contracts from the Romanian National Authority for Scientific Research and Innovation (CNDS-UEFISCDI), project number PN-III-P4-ID-PCCF-2016-0084, outside the submitted work. C Herteliu reports grants or contracts from CNDS-UEFISCDI, project number PN-III-P2-2.1-SOL-2020-2-0351, outside the submitted work. S Bhaskar reports an unpaid leadership or fiduciary role in a board, society, committee or advocacy group, with the Rotary Club of Sydney Board of Directors, outside the submitted work. R Busse reports grants or contracts from Berlin University Alliance (COVID pre-exploration project), outside the submitted work. S M S Islam reports grants or contracts from National Health and Medical Research Council (NHMRC) and the National Heart Foundation of Australia, all outside the submitted work. K Krishan reports non-financial support from UGC Centre of Advanced Study phase II, Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. M J Postma reports grants or contacts from Merck Sharp & DDohme, GlaxoSmithKline, Pfizer, Boehringer Ingelheim, Novavax, Bayer, Bristol Myers Squibb, AstraZeneca, Sanofi, IQVIA, BioMerieux, WHO, EU, Seqirus, FIND, Antilope, DIKTI, LPDP, and Budi; consulting fees from Merk Sharp & Dohme, GlaxoSmithKline, Pfizer, Boehringer Ingelheim, Novavax, Quintiles, Bristol Myers Squibb, Astra Zeneca, Sanofi, Novartis, Pharmerit, IQVIA, and Seqirus; participation on a Data Safety Monitoring Board or Advisory Board to Asc Academics as Advisor; and stock or stock options in Health-Ecore and PAG, all outside the submitted work. M G Shrime reports grants or contracts from the Iris O'Brien Foundation; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Brightsight speakers; and leadership or fiduciary role in board, society, committee or advocacy group, paid or unpaid with Pharos Global Health Advisors as a board member. J A Singh reports consulting fees from Crealta/Horizon, Medisys, Fidia, Two labs, Adept Field Solutions, Clinical Care options, Clearview healthcare partners, Putnam associates, Focus forward, Navigant consulting, Spherix, MedIQ, UBM, Trio Health, Medscape, WebMD, and Practice Point communications, and the National Institutes of Health and the American College of Rheumatology; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Simply Speaking; support for attending meetings and travel from OMERACT; leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid, with OMERACT as a member of the steering committee, with the US Food and Drug Administration Arthritis Advisory Committee, with the Veterans Affairs Rheumatology Field Advisory Committee as a member, and with the UAB Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis as a Director and Editor; stock or stock options in TPT Global Tech, Vaxart pharmaceuticals, and Charlotte's Web Holdings; and previously owned stock options in Amarin, Viking, and Moderna pharmaceuticals, all outside the submitted work. All other authors declare no competing interests.
Acknowledgments
Acknowledgments
J L Dieleman reports support for the current manuscript from the Bill & Melinda Gates Foundation. This research was funded in part by the Wellcome Trust (grant number 220211). S Nomura acknowledges support from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT). S Afzal acknowledges support from King Edward Medical University by facilitating qualified human resource to work on this research and complete it in a timely manner. S M Aljunid would like to acknowledge the Department of Health Policy and Management, Faculty of Public Health, Kuwait University; and International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia for the approval and support to participate in this research project. S Bhaskar acknowledges funding support from the NSW Ministry of Health. T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. J-W De Neve was supported by the Alexander von Humboldt Foundation. M Golechha acknowledges being a project lead of NITI Aayog, Government of India funded project “Impact of the National Health Mission on Governance, Health System, and Human Resources for Health” and being a project lead of a Department of Science and Technology-funded project on the development and implementation of Heat Action Plan in Indian Cities under the National Mission on Strategic Knowledge for Climate Change. V K Gupta acknowledges funding support from NHMRC Australia. S M S Islam is supported by the NHMRC and the National Heart Foundation of Australia. M Jakovljevic was co-funded through Grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia (number XMUMRF/2020-C6/ITCM/0004). S L Koulmane Laxminarayana acknowledges institutional support provided by Manipal Academy of Higher Education. K Krishan is supported by the UGC Centre of Advanced Study (phase II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. L K D Le acknowledges support from the Alfred Deakin Postdoctoral Research Fellowship and funding from the NHMRC PREMISE. R J Maude is supported by a grant from the Research Council of Norway (285188). B R Nascimento was supported in part by CNPq (Bolsa de produtividade em pesquisa, 312382/2019-7), by the Edwards Lifesciences Foundation (Every Heartbeat Matters Program 2020) and by FAPEMIG (grant APQ-000627-20). M D Naimzada, N Otstavnov, and S S Otstavnov acknowledge the support by a grant from the Russian Science Foundation (project number 20-78-10157). J R Padubidri acknowledges the Manipal Academy of Higher Education, Manipal for their support in research publications. B Reshmi acknowledges Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India. A M Samy acknowledges the support from the Fellowship of the Egyptian Fulbright Mission program. A Sheikh is supported by the Health Data Research UK BREATHE Hub. A Shetty acknowledges support from Manipal Academy of Higher Education, Manipal.
Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations.
Contributors
Please see appendix (pp 1151–55) for more detailed information about individual author contributions to the research, divided into the following categories: managing the estimation or publication process; writing the first draft of the manuscript; primary responsibility for applying analytical methods to produce estimates; primary responsibility for seeking, cataloguing, extracting, or cleaning data; designing or coding figures and tables; providing data or critical feedback on data sources; development of methods or computational machinery; providing critical feedback on methods or results; drafting the manuscript or revising it critically for important intellectual content; extracting, cleaning, or cataloguing data; designing or coding figures and tables; and managing the overall research enterprise. All authors had full access to all the data in the study, and A E Micah and J L Dieleman had final responsibility for the decision to submit for publication.
Global Burden of Disease 2020 Health Financing Collaborator Network
Angela E Micah, Ian E Cogswell, Brandon Cunningham, Satoshi Ezoe, Anton C Harle, Emilie R Maddison, Darrah McCracken, Shuhei Nomura, Kyle E Simpson, Hayley N Stutzman, Golsum Tsakalos, Lindsey E Wallace, Yingxi Zhao, Rahul R Zende, Cristiana Abbafati, Michael Abdelmasseh, Aidin Abedi, Kedir Hussein Abegaz, E S Abhilash, Hassan Abolhassani, Michael R M Abrigo, Tara Ballav Adhikari, Saira Afzal, Bright Opoku Ahinkorah, Sepideh Ahmadi, Haroon Ahmed, Muktar Beshir Ahmed, Tarik Ahmed Rashid, Marjan Ajami, Budi Aji, Yonas Akalu, Chisom Joyqueenet Akunna, Hanadi Al Hamad, Khurshid Alam, Fahad Mashhour Alanezi, Turki M Alanzi, Yosef Alemayehu, Robert Kaba Alhassan, Cyrus Alinia, Syed Mohamed Aljunid, Sami Almustanyir Almustanyir, Nelson Alvis-Guzman, Nelson J Alvis-Zakzuk, Saeed Amini, Mostafa Amini-Rarani, Hubert Amu, Robert Ancuceanu, Catalina Liliana Andrei, Tudorel Andrei, Blake Angell, Mina Anjomshoa, Carl Abelardo T Antonio, Catherine M Antony, Muhammad Aqeel, Jalal Arabloo, Morteza Arab-Zozani, Timur Aripov, Alessandro Arrigo, Tahira Ashraf, Desta Debalkie Atnafu, Marcel Ausloos, Leticia Avila-Burgos, Asma Tahir Awan, Getinet Ayano, Martin Amogre Ayanore, Samad Azari, Gulrez Shah Azhar, Tesleem Kayode Babalola, Mohammad Amin Bahrami, Atif Amin Baig, Maciej Banach, Nastaran Barati, Till Winfried Bärnighausen, Amadou Barrow, Sanjay Basu, Bernhard T Baune, Mohsen Bayati, Habib Benzian, Adam E Berman, Akshaya Srikanth Bhagavathula, Nikha Bhardwaj, Pankaj Bhardwaj, Sonu Bhaskar, Sadia Bibi, Ali Bijani, Virginia Bodolica, Nicola Luigi Bragazzi, Dejana Braithwaite, Nicholas J K Breitborde, Alexey V Breusov, Nikolay Ivanovich Briko, Reinhard Busse, Lucero Cahuana-Hurtado, Emily Joy Callander, Luis Alberto Cámera, Carlos A Castañeda-Orjuela, Ferrán Catalá-López, Jaykaran Charan, Souranshu Chatterjee, Soosanna Kumary Chattu, Vijay Kumar Chattu, Simiao Chen, Arrigo Francesco Giuseppe Cicero, Omid Dadras, Saad M A Dahlawi, Xiaochen Dai, Koustuv Dalal, Lalit Dandona, Rakhi Dandona, Dragos Virgil Davitoiu, Jan-Walter De Neve, Antonio Reis de Sá-Junior, Edgar Denova-Gutiérrez, Deepak Dhamnetiya, Samath Dhamminda Dharmaratne, Leila Doshmangir, John Dube, Elham Ehsani-Chimeh, Maysaa El Sayed Zaki, Maha El Tantawi, Sharareh Eskandarieh, Farshad Farzadfar, Tomas Y Ferede, Florian Fischer, Nataliya A Foigt, Alberto Freitas, Sara D Friedman, Takeshi Fukumoto, Nancy Fullman, Peter Andras Gaal, Mohamed M Gad, MA Garcia-Gordillo, Tushar Garg, Mansour Ghafourifard, Ahmad Ghashghaee, Asadollah Gholamian, Ali Gholamrezanezhad, Ghozali Ghozali, Syed Amir Gilani, Ionela-Roxana Glăvan, Ekaterina Vladimirovna Glushkova, Salime Goharinezhad, Mahaveer Golechha, Srinivas Goli, Avirup Guha, Veer Bala Gupta, Vivek Kumar Gupta, Annie Haakenstad, Mohammad Rifat Haider, Alemayehu Hailu, Samer Hamidi, Asif Hanif, Harapan Harapan, Risky Kusuma Hartono, Ahmed I Hasaballah, Shoaib Hassan, Mohamed H Hassanein, Khezar Hayat, Mohamed I Hegazy, Golnaz Heidari, Delia Hendrie, Ileana Heredia-Pi, Claudiu Herteliu, Kamal Hezam, Ramesh Holla, Sheikh Jamal Hossain, Mehdi Hosseinzadeh, Sorin Hostiuc, Tanvir M Huda, Bing-Fang Hwang, Ivo Iavicoli, Bulat Idrisov, Olayinka Stephen Ilesanmi, Seyed Sina Naghibi Irvani, Sheikh Mohammed Shariful Islam, Nahlah Elkudssiah Ismail, Gaetano Isola, Mohammad Ali Jahani, Nader Jahanmehr, Mihajlo Jakovljevic, Manthan Dilipkumar Janodia, Tahereh Javaheri, Sathish Kumar Jayapal, Ranil Jayawardena, Seyed Behzad Jazayeri, Ravi Prakash Jha, Jost B Jonas, Tamas Joo, Farahnaz Joukar, Mikk Jürisson, Billingsley Kaambwa, Rohollah Kalhor, Tanuj Kanchan, Himal Kandel, Behzad Karami Matin, Salah Eddin Karimi, Getinet Kassahun, Gbenga A Kayode, Ali Kazemi Karyani, Leila Keikavoosi-Arani, Yousef Saleh Khader, Himanshu Khajuria, Rovshan Khalilov, Mohammad Khammarnia, Junaid Khan, Jagdish Khubchandani, Neda Kianipour, Gyu Ri Kim, Yun Jin Kim, Adnan Kisa, Sezer Kisa, Stefan Kohler, Soewarta Kosen, Rajasekaran Koteeswaran, Sindhura Lakshmi Koulmane Laxminarayana, Ai Koyanagi, Kewal Krishan, G Anil Kumar, Dian Kusuma, Demetris Lamnisos, Van Charles Lansingh, Anders O Larsson, Savita Lasrado, Long Khanh Dao Le, Shaun Wen Huey Lee, Yeong Yeh Lee, Stephen S Lim, Stany W Lobo, Rafael Lozano, Hassan Magdy Abd El Razek, Muhammed Magdy Abd El Razek, Mokhtar Mahdavi Mahdavi, Azeem Majeed, Alaa Makki, Afshin Maleki, Reza Malekzadeh, Ana Laura Manda, Fariborz Mansour-Ghanaei, Mohammad Ali Mansournia, Carlos Alberto Marrugo Arnedo, Adolfo Martinez-Valle, Seyedeh Zahra Masoumi, Richard James Maude, Martin McKee, Carlo Eduardo Medina-Solís, Ritesh G Menezes, Atte Meretoja, Tuomo J Meretoja, Mohamed Kamal Mesregah, Tomislav Mestrovic, Neda Milevska Kostova, Ted R Miller, G K Mini, Andreea Mirica, Erkin M Mirrakhimov, Bahram Mohajer, Teroj Abdulrahman Mohamed, Mokhtar Mohammadi, Abdollah Mohammadian-Hafshejani, Shafiu Mohammed, Modhurima Moitra, Ali H Mokdad, Mariam Molokhia, Mohammad Ali Moni, Yousef Moradi, Jakub Morze, Seyyed Meysam Mousavi, Christine Mpundu-Kaambwa, Moses K Muriithi, Saravanan Muthupandian, Ahamarshan Jayaraman Nagarajan, Mukhammad David Naimzada, Vinay Nangia, Atta Abbas Naqvi, Aparna Ichalangod Narayana, Bruno Ramos Nascimento, Muhammad Naveed, Biswa Prakash Nayak, Javad Nazari, Rawlance Ndejjo, Ionut Negoi, Sandhya Neupane Kandel, Trang Huyen Nguyen, Justice Nonvignon, Jean Jacques Noubiap, Vincent Ebuka Nwatah, Bogdan Oancea, Foluke Adetola Ogunyemi Ojelabi, Andrew T Olagunju, Babayemi Oluwaseun Olakunde, Stefano Olgiati, Jacob Olusegun Olusanya, Obinna E Onwujekwe, Adrian Otoiu, Nikita Otstavnov, Stanislav S Otstavnov, Mayowa O Owolabi, Jagadish Rao Padubidri, Raffaele Palladino, Songhomitra Panda-Jonas, Eun-Cheol Park, Fatemeh Pashazadeh Kan, Shrikant Pawar, Hamidreza Pazoki Toroudi, David M Pereira, Arokiasamy Perianayagam, Konrad Pesudovs, Cristiano Piccinelli, Maarten J Postma, Sergio I Prada, Mohammad Rabiee, Navid Rabiee, Fakher Rahim, Vafa Rahimi-Movaghar, Mohammad Hifz Ur Rahman, Mosiur Rahman, Amir Masoud Rahmani, Usha Ram, Chhabi Lal Ranabhat, Priyanga Ranasinghe, Chythra R Rao, Priya Rathi, David Laith Rawaf, Salman Rawaf, Lal Rawal, Reza Rawassizadeh, Robert C Reiner Jr, Andre M N Renzaho, Bhageerathy Reshmi, Mavra A Riaz, Rezaul Karim Ripon, Anas M Saad, Mohammad Ali Sahraian, Maitreyi Sahu, Joseph S Salama, Sana Salehi, Abdallah M Samy, Juan Sanabria, Francesco Sanmarchi, João Vasco Santos, Milena M Santric-Milicevic, Brijesh Sathian, Miloje Savic, Deepak Saxena, Mehdi Sayyah, Falk Schwendicke, Subramanian Senthilkumaran, Sadaf G Sepanlou, Allen Seylani, Saeed Shahabi, Masood Ali Shaikh, Aziz Sheikh, Adithi Shetty, Pavanchand H Shetty, Kenji Shibuya, Mark G Shrime, Kanwar Hamza Shuja, Jasvinder A Singh, Valentin Yurievich Skryabin, Anna Aleksandrovna Skryabina, Shahin Soltani, Moslem Soofi, Emma Elizabeth Spurlock, Simona Cătălina Ștefan, Viktória Szerencsés, Miklós Szócska, Rafael Tabarés-Seisdedos, Biruk Wogayehu Taddele, Yonas Getaye Tefera, Aravind Thavamani, Ruoyan Tobe-Gai, Roman Topor-Madry, Marcos Roberto Tovani-Palone, Bach Xuan Tran, Lorainne Tudor Car, Anayat Ullah, Saif Ullah, Nasir Umar, Eduardo A Undurraga, Pascual R Valdez, Tommi Juhani Vasankari, Jorge Hugo Villafañe, Francesco S Violante, Vasily Vlassov, Bay Vo, Sebastian Vollmer, Theo Vos, Giang Thu Vu, Linh Gia Vu, Richard G Wamai, Andrea Werdecker, Mesfin Agachew Woldekidan, Befikadu Legesse Wubishet, Gelin Xu, Sanni Yaya, Vahid Yazdi-Feyzabadi, Vahit Yiğit, Paul Yip, Birhanu Wubale Yirdaw, Naohiro Yonemoto, Mustafa Z Younis, Chuanhua Yu, Ismaeel Yunusa, Telma Zahirian Moghadam, Hamed Zandian, Mikhail Sergeevich Zastrozhin, Anasthasia Zastrozhina, Zhi-Jiang Zhang, Arash Ziapour, Yves Miel H Zuniga, Simon I Hay, Christopher J L Murray, Joseph L Dieleman.
Affiliations
Institute for Health Metrics and Evaluation (A E Micah PhD, I E Cogswell BS, B Cunningham MA, A C Harle BA, E R Maddison BS, D McCracken PhD, K E Simpson BS, H N Stutzman BA, G Tsakalos MS, L E Wallace MPA, R R Zende BTech, C M Antony MA, G S Azhar PhD, X Dai PhD, Prof L Dandona MD, Prof R Dandona PhD, Prof S D Dharmaratne MD, N Fullman MPH, A Haakenstad ScD, Prof S S Lim PhD, Prof R Lozano MD, M Moitra MPH, Prof A H Mokdad PhD, R C Reiner Jr PhD, M Sahu MS, E E Spurlock BA, Prof T Vos PhD, Prof S I Hay FMedSci, Prof C J L Murray DPhil, J L Dieleman PhD), Department of Health Metrics Sciences, School of Medicine (Prof R Dandona PhD, Prof S D Dharmaratne MD, Prof S S Lim PhD, Prof R Lozano MD, Prof A H Mokdad PhD, R C Reiner Jr PhD, Prof T Vos PhD, Prof S I Hay FMedSci, Prof C J L Murray DPhil, J L Dieleman PhD), University of Washington, Seattle, WA, USA; Department of Global Health Policy (S Ezoe MD, S Nomura PhD), University of Tokyo, Tokyo, Japan; Department of Health Policy and Management (S Nomura PhD), Keio University, Tokyo, Japan; Nuffield Department of Medicine (Y Zhao MPH), Centre for Tropical Medicine and Global Health (R J Maude PhD), The George Institute for Global Health (Prof S Yaya PhD), University of Oxford, Oxford, UK; Department of Juridical and Economic Studies (C Abbafati PhD), La Sapienza University, Rome, Italy; Department of Surgery (M Abdelmasseh MD, Prof J Sanabria MD), Marshall University, Huntington, WV, USA; Department of Orthopaedic Surgery (A Abedi MD, M K Mesregah MSc), Radiology (A Gholamrezanezhad MD), Department of Radiology (S Salehi MD), University of Southern California, Los Angeles, CA, USA; Department of Biostatistics (K H Abegaz MSc), Near East University, Nicosia, Cyprus; Department of Biostatistics and Health Informatics (K H Abegaz MSc), Madda Walabu University, Bale Robe, Ethiopia; Department of Botany (E S Abhilash PhD), Sree Narayana Guru College Chelannur, Kozhikode, India; Department of Laboratory Medicine (H Abolhassani PhD), Karolinska University Hospital, Huddinge, Sweden; Research Center for Immunodeficiencies (H Abolhassani PhD), Department of Health Management and Economics (M Anjomshoa PhD), National Institute of Health Research (E Ehsani-Chimeh PhD), Multiple Sclerosis Research Center (S Eskandarieh PhD, Prof M Sahraian MD), Non-communicable Diseases Research Center (Prof F Farzadfar DSc, B Mohajer MD), Department of Environmental Health Engineering (Prof A Maleki PhD), Digestive Diseases Research Institute (Prof R Malekzadeh MD, S G Sepanlou MD), Department of Epidemiology and Biostatistics (M Mansournia PhD), Metabolomics and Genomics Research Center (F Rahim PhD), Sina Trauma and Surgery Research Center (Prof V Rahimi-Movaghar MD), Tehran University of Medical Sciences, Tehran, Iran; Department of Research (M R M Abrigo PhD), Philippine Institute for Development Studies, Quezon City, Philippines; Department of Public Health (T Adhikari MPH), Aarhus University, Aarhus, Denmark; Nepal Health Frontiers, Kathmandu, Nepal (T Adhikari MPH), Kathmandu, Nepal; Department of Community Medicine (Prof S Afzal PhD), King Edward Memorial Hospital, Lahore, Pakistan; Department of Public Health (Prof S Afzal PhD), Public Health Institute, Lahore, Pakistan; The Australian Centre for Public and Population Health Research (B O Ahinkorah MPH), University of Technology Sydney, Sydney, NSW, Australia; School of Advanced Technologies in Medicine (S Ahmadi PhD), National Nutrition and Food Technology Research Institute (M Ajami PhD), Virtual School of Medical Education & Management (N Jahanmehr PhD), Prevention of Cardiovascular Disease Research Center (N Jahanmehr PhD), Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Biosciences (H Ahmed PhD), COMSATS Institute of Information Technology, Islamabad, Pakistan; Department of Epidemiology (M B Ahmed MPH), Jimma University, Jimma, Ethiopia; Australian Center for Precision Health (M B Ahmed MPH), University of South Australia, Adelaide, SA, Australia; Department of Computer Science and Engineering (T Ahmed Rashid PhD), University of Kurdistan Hewler, Erbil, Iraq; Department of Food and Nutrition Policy and Planning Research (M Ajami PhD), National Institute of Nutrition, Tehran, Iran; Faculty of Medicine and Public Health (B Aji DrPH), Jenderal Soedirman University, Purwokerto, Indonesia; Department of Medical Physiology (Y Akalu MSc), Department of Clinical Pharmacy (Y G Tefera MSc), Department of Midwifery (B W Yirdaw MSc), University of Gondar, Gondar, Ethiopia; Department of Public Health (C J Akunna DMD), The Intercountry Centre for Oral Health for Africa, Jos, Nigeria; Department of Public Health (C J Akunna DMD), Federal Ministry of Health, Garki, Nigeria; Geriatric and Long Term Care Department (H Al Hamad MD, B Sathian PhD), Rumailah Hospital (H Al Hamad MD), Hamad Medical Corporation, Doha, Qatar; Murdoch Business School (K Alam PhD), Murdoch University, Perth, WA, Australia; Health Information Management and Technology Department (T M Alanzi PhD), Environmental Health Department (S M A Dahlawi PhD), Forensic Medicine Division (Prof R G Menezes MD), Department of Pharmacy Practice (A Naqvi PhD), Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia (F M Alanezi PhD); Department of Midwifery (Y Alemayehu MSc), Arba Minch University, Arba Minch, Ethiopia; Institute of Health Research (R K Alhassan PhD), Department of Population and Behavioural Sciences (H Amu PhD), Department of Health Policy Planning and Management (M A Ayanore PhD), University of Health and Allied Sciences, Ho, Ghana; Department of Health Care Management and Economics (C Alinia PhD), Urmia University of Medical Science, Urmia, Iran; Department of Health Policy and Management (Prof S M Aljunid PhD), Kuwait University, Safat, Kuwait; International Centre for Casemix and Clinical Coding (Prof S M Aljunid PhD), National University of Malaysia, Bandar Tun Razak, Malaysia; College of Medicine (S A Almustanyir MD), Alfaisal University, Riyadh, Saudi Arabia; Ministry of Health, Riyadh, Saudi Arabia (S A Almustanyir MD); Research Group in Hospital Management and Health Policies (Prof N Alvis-Guzman PhD), Department of Economic Sciences (N J Alvis-Zakzuk MSc), Universidad de la Costa (University of the Coast), Barranquilla, Colombia; Research Group in Health Economics (Prof N Alvis-Guzman PhD, Prof C A Marrugo Arnedo MSc), University of Cartagena, Cartagena, Colombia; National Health Observatory (N J Alvis-Zakzuk MSc), Colombian National Health Observatory (C A Castañeda-Orjuela MD), National Institute of Health, Bogota, Colombia; Department of Health Services Management (S Amini PhD), Department of Pediatrics (J Nazari MD), Arak University of Medical Sciences, Arak, Iran; Health Management and Economics Reasearch Center (M Amini-Rarani PhD), Isfahan University of Medical Sciences, Isfahan, Iran; Pharmacy Department (Prof R Ancuceanu PhD), Cardiology Department (C Andrei PhD), Department of General Surgery (D V Davitoiu PhD, A Manda MD, I Negoi PhD), Department of Legal Medicine and Bioethics (S Hostiuc PhD), Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Department of Statistics and Econometrics (Prof T Andrei PhD, Prof M Ausloos PhD, I Glăvan PhD, Prof C Herteliu PhD, A Mirica PhD, Prof A Otoiu PhD), Management Department (S Ştefan PhD), Bucharest University of Economic Studies, Bucharest, Romania; Institute of Global Health (B Angell PhD), University College London, London, UK; Health System Science Program (B Angell PhD), The George Institute for Global Health, Newtown, NSW, Australia; Department of Health Policy and Administration (C T Antonio MD), University of the Philippines Manila, Manila, Philippines; Department of Applied Social Sciences (C T Antonio MD), Hong Kong Polytechnic University, Hong Kong, China; Department of Psychology (M Aqeel PhD, M Aqeel PhD), Foundation University Islamabad, Rawalpandi, Pakistan; Health Management and Economics Research Center (J Arabloo PhD, S Azari PhD, A Ghashghaee BSc, M Hosseinzadeh PhD), Student Research Committee (A Ghashghaee BSc), Preventive Medicine and Public Health Research Center (S Goharinezhad PhD), Department of Physiology (H Pazoki Toroudi PhD), Physiology Research Center (H Pazoki Toroudi PhD), Iran University of Medical Sciences, Tehran, Iran (F Pashazadeh Kan BSN); Social Determinants of Health Research Center (M Arab-Zozani PhD), Birjand University of Medical Sciences, Birjand, Iran; Public Health and Healthcare Management (T Aripov PhD), Tashkent Institute of Postgraduate Medical Education, Tashkent, Uzbekistan; Boston Children's Hospital, Boston, MA, USA (T Aripov PhD); Scientific Institute San Raffaele Hospital (A Arrigo MD), Vita-Salute University, Milan, Italy; University Institute of Radiological Sciences and Medical Imaging Technology (T Ashraf MS), Faculty of Allied Health Sciences (Prof S Gilani PhD), University Institute of Public Health (A Hanif PhD), The University of Lahore, Lahore, Pakistan; Department of Health System and Health Economics (D D Atnafu MPH), Bahir Dar University, Bahir Dar, Ethiopia; School of Business (Prof M Ausloos PhD), University of Leicester, Leicester, UK; Center for Health Systems Research (L Avila-Burgos ScD, Prof I Heredia-Pi DipSocSc), Center for Nutrition and Health Research (E Denova-Gutiérrez DSc), National Institute of Public Health, Cuernavaca, Mexico; School of Nursing and Health Sciences (A T Awan DrPH), Capella University, Minneapolis, MN, USA; Continuing Education-Grant Writing Academy (A T Awan DrPH), University of Nevada, Las Vegas, NV, USA; School of Public Health (G Ayano MSc, D Hendrie PhD, T R Miller PhD), Curtin University, Perth, WA, Australia; Badan Pusat Statistik (Central Bureau of Statistics) (G S Azhar PhD), The RAND Corporation, Santa Monica, CA, USA; Discipline of Public Health Medicine (T K Babalola MSc), University of KwaZulu-Natal, Durban, South Africa; Department of Community Health and Primary Care (T K Babalola MSc), Department of Psychiatry (A T Olagunju MD), University of Lagos, Lagos, Nigeria; Department of Healthcare Management and Education (M Bahrami PhD), Health Human Resources Research Center (M Bayati PhD), Non-communicable Disease Research Center (Prof R Malekzadeh MD, S G Sepanlou MD), Health Policy Research Center (S Shahabi PhD), Shiraz University of Medical Sciences, Shiraz, Iran; Unit of Biochemistry (A A Baig PhD), Faculty of Business and Management (M A Riaz Mcom), Universiti Sultan Zainal Abidin (Sultan Zainal Abidin University), Kuala Terengganu, Malaysia; Department of Hypertension (Prof M Banach PhD), Medical University of Lodz, Lodz, Poland; Polish Mothers' Memorial Hospital Research Institute, Lodz, Poland (Prof M Banach PhD); Deputy of Research and Technology (N Barati PhD), Hamedan University of Medical Sciences, Hamedan, Iran; Heidelberg Institute of Global Health (Prof T W Bärnighausen MD, S Chen DSc, J De Neve MD, S Kohler MD, S Mohammed PhD), Department of Ophthalmology (Prof J B Jonas MD, S Panda-Jonas MD), Heidelberg University, Heidelberg, Germany; T H Chan School of Public Health (Prof T W Bärnighausen MD, I Yunusa PhD), Center for Primary Care (S Basu PhD), Division of General Internal Medicine (Prof A Sheikh MD), Harvard University, Boston, MA, USA; Department of Public & Environmental Health (A Barrow MPH), University of The Gambia, Brikama, The Gambia; Epidemiology and Disease Control Unit (A Barrow MPH), Ministry of Health, Kotu, The Gambia; School of Public Health (S Basu PhD), Imperial College Business School (D Kusuma DSc), Department of Primary Care and Public Health (Prof A Majeed MD, R Palladino MD, Prof S Rawaf MD), WHO Collaborating Centre for Public Health Education and Training (D L Rawaf MD), Imperial College London, London, UK; Department of Psychiatry (Prof B T Baune PhD), University of Münster, Münster, Germany; Department of Psychiatry (Prof B T Baune PhD), Melbourne Medical School, Melbourne, VIC, Australia; Department of Epidemiology and Health Promotion (Prof H Benzian PhD), School of Global Public Health (S D Friedman BA), New York University, New York, NY, USA; Department of Medicine (A E Berman MD), Medical College of Georgia at Augusta University, Augusta, GA, USA; Department of Social and Clinical Pharmacy (A S Bhagavathula PharmD), Charles University, Hradec Kralova, Czech Republic; Institute of Public Health (A S Bhagavathula PharmD), United Arab Emirates University, Al Ain, United Arab Emirates; Department of Anatomy (Prof N Bhardwaj MD), Government Medical College Pali, Pali, India; Department of Community Medicine and Family Medicine (P Bhardwaj MD), School of Public Health (P Bhardwaj MD), Department of Pharmacology (J Charan MD), Department of Forensic Medicine and Toxicology (T Kanchan MD), All India Institute of Medical Sciences, Jodhpur, India; Neurovascular Imaging Laboratory (S Bhaskar PhD), NSW Brain Clot Bank, Sydney, NSW, Australia; Department of Neurology and Neurophysiology (S Bhaskar PhD), South West Sydney Local Heath District and Liverpool Hospital, Sydney, NSW, Australia; Institute of Soil and Environmental Sciences (S Bibi PhD, S Ullah PhD), University of Agriculture, Faisalabad, Faisalabad, Pakistan; Social Determinants of Health Research Center (A Bijani PhD, M A Jahani PhD), Babol University of Medical Sciences, Babol, Iran; School of Business Administration (Prof V Bodolica PhD), American University of Sharjah, Sharjah, United Arab Emirates; University of Genoa, Genoa, Italy (N L Bragazzi PhD); Department of Epidemiology (D Braithwaite PhD), University of Florida, Gainesville, FL, USA; Cancer Population Sciences Program (D Braithwaite PhD), University of Florida Health Cancer Center, Gainesville, FL, USA; Psychiatry and Behavioral Health Department (Prof N J K Breitborde PhD), Department of Psychology (Prof N J K Breitborde PhD), Division of Cardiovascular Medicine (A Guha MD), Ohio State University, Columbus, OH, USA; Institute of Medicine (Prof A V Breusov DSc), RUDN University, Moscow, Russia; Department of Epidemiology and Evidence-Based Medicine (Prof N I Briko DSc, E V Glushkova PhD), IM Sechenov First Moscow State Medical University, Moscow, Russia; Department of Health Care Management (Prof R Busse PhD), Technical University of Berlin, Berlin, Germany; School of Public Health and Administration (L Cahuana-Hurtado PhD), Peruvian University Cayetano Heredia, Lima, Peru; School of Public Health and Preventive Medicine (E J Callander PhD), Monash University, Melbourne, VIC, Australia; Internal Medicine Department (Prof L A Cámera MD), Hospital Italiano de Buenos Aires (Italian Hospital of Buenos Aires), Buenos Aires, Argentina; Board of Directors (Prof L A Cámera MD), Argentine Society of Medicine, Buenos Aires, Argentina (Prof P R Valdez MEd); Epidemiology and Public Health Evaluation Group (C A Castañeda-Orjuela MD), National University of Colombia, Bogota, Colombia; National School of Public Health (F Catalá-López PhD), Institute of Health Carlos III, Madrid, Spain; Clinical Epidemiology Program (F Catalá-López PhD), Ottawa Hospital Research Institute, Ottawa, ON, Canada; Department of Microbiology & Infection Control (S Chatterjee MD), Medanta Medicity, Gurugram, India; Department of Public Health (S Chattu PhD), Texila American University, Georgetown, Guyana; Department of Medicine (V Chattu MD), University of Toronto, Toronto, ON, Canada; Global Institute of Public Health, Thiruvananthapuram, India (V Chattu MD); Department of Medical and Surgical Sciences (Prof A F G Cicero PhD, Prof F S Violante MD), Department of Biomedical and Neuromotor Sciences (F Sanmarchi MD), University of Bologna, Bologna, Italy; Department of Health Informatics (O Dadras DrPH), Graduate School of Medicine (O Dadras DrPH), Kyoto University, Kyoto, Japan; Division of Public Health Science (Prof K Dalal PhD), Mid Sweden University, Sundsvall, Sweden; Higher School of Public Health (Prof K Dalal PhD), Al Farabi Kazakh National University, Almaty, Kazakhstan; Public Health Foundation of India, Gurugram, India (Prof L Dandona MD, Prof R Dandona PhD, G Kumar PhD); Indian Council of Medical Research, New Delhi, India (Prof L Dandona MD); Department of Surgery (D V Davitoiu PhD), Clinical Emergency Hospital Sf Pantelimon, Bucharest, Romania; Department of Medical Clinic (Prof A R de Sá-Junior PhD), Federal University of Santa Catarina, Florianópolis, Brazil; Department of Community Medicine (D Dhamnetiya MD), Dr Baba Sahib Ambedkar Medical College and Hospital, Delhi, India; Department of Community Medicine (Prof S D Dharmaratne MD), University of Peradeniya, Peradeniya, Sri Lanka; Department of Health Policy and Management (L Doshmangir PhD), Department of Medical Surgical Nursing (M Ghafourifard PhD), Social Determinants of Health Research Center (S Karimi PhD), Tabriz University of Medical Sciences, Tabriz, Iran; Office of Institutional Analysis (J Dube MA), University of Windsor, Windsor, ON, Canada; Reference Laboratory of Egyptian Universities-Cairo (Prof M El Sayed Zaki PhD), Ministry of Higher Education and Scientific Research, Cairo, Egypt; Pediatric Dentistry and Dental Public Health Department (Prof M El Tantawi PhD), Alexandria University, Alexandria, Egypt; School of Nursing (T Y Ferede MSc), School of Midwifery (G Kassahun MSc), Hawassa University, Hawassa, Ethiopia; Institute of Gerontological Health Services and Nursing Research (F Fischer PhD), Ravensburg-Weingarten University of Applied Sciences, Weingarten, Germany; Institute of Gerontology (N A Foigt PhD), National Academy of Medical Sciences of Ukraine, Kyiv, Ukraine; Department of Community Medicine, Information and Health Decision Sciences (A Freitas PhD), Associated Laboratory for Green Chemistry (Prof D M Pereira PhD), Center for Health Technology and Services Research (J V Santos MD), University of Porto, Porto, Portugal; Center for Health Technology and Services Research, Porto, Portugal (A Freitas PhD); Department of Dermatology (T Fukumoto PhD), Kobe University, Kobe, Japan; Health Services Management Training Centre (P A Gaal PhD, T Joo MSc, V Szerencsés MA), Faculty of Health and Public Administration (M Szócska PhD), Semmelweis University, Budapest, Hungary; Department of Applied Social Sciences (P A Gaal PhD), Sapientia Hungarian University of Transylvania, Târgu-Mureş, Romania; Department of Cardiovascular Medicine (M M Gad MD), Department of Nephrology and Hypertension (M H Hassanein MD), Heart and Vascular Institute (A M Saad MD), Cleveland Clinic, Cleveland, OH, USA; Gillings School of Global Public Health (M M Gad MD), University of North Carolina Chapel Hill, Chapel Hill, NC, USA; Faculty of Business and Management (M Garcia-Gordillo PhD), Universidad Autonóma de Chile (Autonomous University of Chile), Talca, Chile; Department of Radiology (T Garg MBBS), King Edward Memorial Hospital, Mumbai, India; Young Researchers and Elite Club (A Gholamian MSc), Islamic Azad University, Rasht, Iran; Department of Biology (A Gholamian MSc), Islamic Azad University, Tehran, Iran; Department of Public Health (G Ghozali PhD), University of Muhammadiyah Kalimantan Timur, Samarinda, Indonesia; Afro-Asian Institute, Lahore, Pakistan (Prof S Gilani PhD); Health Systems and Policy Research (M Golechha PhD), Department of Epidemiology (Prof D Saxena PhD), Indian Institute of Public Health, Gandhinagar, India; Australia India Institute New Generation Network (S Goli PhD), UWA Public Policy Institute (S Goli PhD), University of Western Australia, Perth, WA, Australia; Harrington Heart and Vascular Institute (A Guha MD), Department of Nutrition and Preventive Medicine (Prof J Sanabria MD), Division of Pediatric Gastroenterology (A Thavamani MD), Case Western Reserve University, Cleveland, OH, USA; School of Medicine (V Gupta PhD), Deakin University, Geelong, VIC, Australia; Department of Clinical Medicine (Prof V K Gupta PhD), Macquarie University, Sydney, NSW, Australia; Department of Global Health and Population (A Haakenstad ScD), TH Chan School of Public Health, Boston, MA, USA; Department of Social and Public Health (M Haider PhD), Ohio University, Athens, OH, USA; Department of Global Public Health and Primary Care (A Hailu PhD), Center for International Health (S Hassan MPhil), Bergen Center for Ethics and Priority Setting (S Hassan MPhil), University of Bergen, Bergen, Norway; School of Health and Environmental Studies (Prof S Hamidi DrPH), Hamdan Bin Mohammed Smart University, Dubai, United Arab Emirates; Medical Research Unit (H Harapan PhD), Universitas Syiah Kuala (Syiah Kuala University), Banda Aceh, Indonesia; Sekolah Tinggi Ilmu Kesehatan Indonesia Maju [Indonesian Advanced College of Health Sciences] (R K Hartono MPH), Institution of Public Health Sciences, Jakarta, Indonesia; Department of Zoology and Entomology (A I Hasaballah PhD), Al Azhar University, Cairo, Egypt; Institute of Pharmaceutical Sciences (K Hayat MS), University of Veterinary and Animal Sciences, Lahore, Pakistan; Department of Pharmacy Administration and Clinical Pharmacy (K Hayat MS), Xian Jiaotong University, Xian, China; Department of Neurology (M I Hegazy PhD), Cairo University, Cairo, Egypt; Independent Consultant, Santa Clara, CA, USA (G Heidari MD); School of Business (Prof C Herteliu PhD), London South Bank University, London, UK; Department of Applied Microbiology (K Hezam PhD), Taiz University, Taiz, Yemen; Department of Microbiology (K Hezam PhD), Nankai University, Tianjin, China; Kasturba Medical College, Mangalore (R Holla MD, J Padubidri MD, P Rathi MD), Manipal College of Pharmaceutical Sciences (Prof M D Janodia PhD), Manipal College of Dental Sciences, Manipal (Prof A I Narayana PhD), Department of Community Medicine (C R Rao MD), Department of Health Information Management (B Reshmi PhD), Manipal Academy of Higher Education, Manipal, India (B Reshmi PhD); Maternal and Child Health Division (S J Hossain MPH, T M Huda PhD), International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh; Clinical Legal Medicine Department (S Hostiuc PhD), National Institute of Legal Medicine Mina Minovici, Bucharest, Romania; School of Public Health (T M Huda PhD), Sydney Medical School (S Islam PhD), Save Sight Institute (H Kandel PhD), University of Sydney, Sydney, NSW, Australia; Department of Occupational Safety and Health (Prof B Hwang PhD), China Medical University, Taichung, Taiwan; Department of Public Health (Prof I Iavicoli PhD, R Palladino MD), University of Naples Federico II, Naples, Italy; Infectious Diseases Department (B Idrisov MD), Bashkir State Medical University, Ufa, Russia; Laboratory of Public Health Indicators Analysis and Health Digitalization (B Idrisov MD), Moscow Institute of Physics and Technology, Moscow, Russia; Department of Community Medicine (O S Ilesanmi PhD), Department of Medicine (Prof M O Owolabi DrM), University of Ibadan, Ibadan, Nigeria; Department of Community Medicine (O S Ilesanmi PhD), Department of Medicine (Prof M O Owolabi DrM), University College Hospital, Ibadan, Ibadan, Nigeria; Independent Consultant, Tabriz, Iran (S N Irvani MD); Institute for Physical Activity and Nutrition (S Islam PhD), Department of Economics (L K D Le PhD), Deakin University, Burwood, VIC, Australia; Department of Clinical Pharmacy (Prof N Ismail PhD), MAHSA University, Bandar Saujana Putra, Malaysia; Department of General Surgery and Surgical-Medical Specialties (Prof G Isola PhD), University of Catania, Catania, Italy; Institute of Comparative Economic Studies (Prof M Jakovljevic PhD), Hosei University, Tokyo, Japan; Department of Global Health, Economics and Policy (Prof M Jakovljevic PhD), University of Kragujevac, Kragujevac, Serbia; Health Informatic Lab (T Javaheri PhD), Department of Computer Science (R Rawassizadeh PhD), Boston University, Boston, MA, USA; Centre of Studies and Research (S Jayapal PhD), Ministry of Health, Muscat, Oman; Department of Physiology (R Jayawardena PhD), Department of Pharmacology (P Ranasinghe PhD), University of Colombo, Colombo, Sri Lanka; School of Exercise and Nutrition Sciences (R Jayawardena PhD), Queensland University of Technology, Brisbane, QLD, Australia; Urology Department (S Jazayeri MD), University of Florida, Jacksonville, FL, USA; Department of Community Medicine (R P Jha MSc), Dr Baba Saheb Ambedkar Medical College & Hospital, Delhi, India; Department of Community Medicine (R P Jha MSc), Banaras Hindu University, Varanasi, India; Beijing Institute of Ophthalmology (Prof J B Jonas MD), Beijing Tongren Hospital, Beijing, China; Gastrointestinal and Liver Diseases Research Center (F Joukar PhD, Prof F Mansour-Ghanaei MD), Caspian Digestive Disease Research Center (F Joukar PhD, Prof F Mansour-Ghanaei MD), Guilan University of Medical Sciences, Rasht, Iran; Institute of Family Medicine and Public Health (M Jürisson PhD), University of Tartu, Tartu, Estonia; Health Economics Unit (B Kaambwa PhD), College of Medicine and Public Health (B Kaambwa PhD), Health and Social Care Economics Group (C Mpundu-Kaambwa PhD), Flinders University, Adelaide, SA, Australia; Institute for Prevention of Non-communicable Diseases (R Kalhor PhD), Health Services Management Department (R Kalhor PhD), Qazvin University of Medical Sciences, Qazvin, Iran; Sydney Eye Hospital (H Kandel PhD), South Eastern Sydney Local Health District, Sydney, NSW, Australia; Research Center for Environmental Determinants of Health (Prof B Karami Matin PhD, A Kazemi Karyani PhD, S Soltani PhD), Department of Public Health (N Kianipour MA), Social Development and Health Promotion Research Center (M Soofi PhD), Department of Health Education and Health Promotion (A Ziapour PhD), Kermanshah University of Medical Sciences, Kermanshah, Iran; International Research Center of Excellence (G A Kayode PhD), Institute of Human Virology Nigeria, Abuja, Nigeria; Julius Centre for Health Sciences and Primary Care (G A Kayode PhD), Utrecht University, Utrecht, Netherlands; School of Health (L Keikavoosi-Arani PhD), Alborz University of Medical Sciences, Karaj, Iran; Department of Public Health (Prof Y S Khader PhD), Jordan University of Science and Technology, Irbid, Jordan; Amity Institute of Forensic Sciences (H Khajuria PhD, B P Nayak PhD), Amity University, Noida, India; Department of Biophysics and Biochemistry (Prof R Khalilov PhD), Baku State University, Baku, Azerbaijan; Russian Institute for Advanced Study (Prof R Khalilov PhD), Moscow State Pedagogical University, Moscow, Russia; Health Promotion Research Center (M Khammarnia PhD), Zahedan University of Medical Sciences, Zahedan, Iran; Department of Population Studies (J Khan MPhil), Department of Development Studies (Prof A Perianayagam PhD), Department of Public Health & Mortality Studies (Prof U Ram PhD), International Institute for Population Sciences, Mumbai, India; Department of Public Health (Prof J Khubchandani PhD), New Mexico State University, Las Cruces, NM, USA; Department of Preventive Medicine (G Kim PhD, Prof E Park PhD), Institute of Health Services Research (Prof E Park PhD), Yonsei University, Seoul, South Korea; School of Traditional Chinese Medicine (Y Kim PhD), Xiamen University Malaysia, Sepang, Malaysia; School of Health Sciences (Prof A Kisa PhD), Kristiania University College, Oslo, Norway; Department of Global Community Health and Behavioral Sciences (Prof A Kisa PhD), Tulane University, New Orleans, LA, USA; Department of Nursing and Health Promotion (S Kisa PhD), Oslo Metropolitan University, Oslo, Norway; Independent Consultant, Jakarta, Indonesia (S Kosen MD); Microbiology & Molecular Cell Biology Department (R Koteeswaran MD), Eastern Virginia Medical School, Norfolk, VA, USA; Kasturba Medical College, Udupi, India (S Koulmane Laxminarayana MD); CIBERSAM (A Koyanagi MD), San Juan de Dios Sanitary Park, Sant Boi de Llobregat, Spain; Catalan Institution for Research and Advanced Studies, Barcelona, Spain (A Koyanagi MD); Department of Anthropology (K Krishan PhD), Panjab University, Chandigarh, India; Faculty of Public Health (D Kusuma DSc), University of Indonesia, Depok, Indonesia; Department of Health Sciences (D Lamnisos PhD), European University Cyprus, Nicosia, Cyprus; HelpMeSee, New York, NY, USA (Prof V C Lansingh PhD); Mexican Institute of Ophthalmology, Queretaro, Mexico (Prof V C Lansingh PhD); Department of Medical Sciences (Prof A O Larsson PhD), Uppsala University, Uppsala, Sweden; Department of Clinical Chemistry and Pharmacology (Prof A O Larsson PhD), Uppsala University Hospital, Uppsala, Sweden; Department of Otorhinolaryngology (S Lasrado MS), Father Muller Medical College, Mangalore, India; School of Pharmacy (S W H Lee PhD), Monash University, Bandar Sunway, Malaysia; School of Pharmacy (S W H Lee PhD), Taylor's University Lakeside Campus, Subang Jaya, Malaysia; Department of Medicine (Prof Y Lee PhD), School of Medical Sciences (Prof Y Lee PhD), University of Science Malaysia, Kota Bharu, Malaysia; Department of Professional and Medical Education (S W Lobo PhD), Meharry Medical College, Nashville, TN, USA; Department of Biomedical Sciences (S W Lobo PhD), Mercer University, Macon, GA, USA; Radiology Department (H Magdy Abd El Razek MD), Egypt Ministry of Health and Population, Mansoura, Egypt; Ophthalmology Department (M Magdy Abd El Razek MSc), Ministry of Health & Population, Aswan, Egypt; Social Determinants of Health Research Center (M M Mahdavi PhD), Saveh University of Medical Sciences, Saveh, Iran; Mass Communication Department (A Makki PhD), University of Sharjah, Sharjah, United Arab Emirates; Environmental Health Research Center (Prof A Maleki PhD), Social Determinants of Health Research Center (Y Moradi PhD), Kurdistan University of Medical Sciences, Sanandaj, Iran; General Surgery Department I (A Manda MD), Emergency University Hospital Bucharest, Bucharest, Romania; Institución Tecnológica Colegio Mayor de Bolívar (Technological Institution College of Bolívar), Cartagena, Colombia (Prof C A Marrugo Arnedo MSc); Health Policy and Population Research Center (A Martinez-Valle PhD), National Autonomous University of Mexico, Mexico City, Mexico; Joint Learning Network for Universal Coverage, Arlington, VA, USA (A Martinez-Valle PhD); Department of Midwifery (S Masoumi PhD), Hamadan University of Medical Sciences, Hamadan, Iran; Mahidol Oxford Tropical Medicine Research Unit (R J Maude PhD), Mahidol University, Bangkok, Thailand; Department of Health Services Research and Policy (Prof M McKee DSc), Department of Disease Control (N Umar PhD), London School of Hygiene & Tropical Medicine, London, UK; Department of Dentistry (C E Medina-Solís MSc), Autonomous University of Hidalgo State, Pachuca, Mexico; Neurology Unit (A Meretoja MD), Breast Surgery Unit (T J Meretoja MD), Helsinki University Hospital, Helsinki, Finland; School of Health Sciences (A Meretoja MD), University of Melbourne, Melbourne, VIC, Australia; University of Helsinki, Helsinki, Finland (T J Meretoja MD); Department of Orthopaedic Surgery (M K Mesregah MSc), Menoufia University, Shebin El-Kom, Egypt; Clinical Microbiology and Parasitology Unit (T Mestrovic PhD), Dr Zora Profozic Polyclinic, Zagreb, Croatia; University Centre Varazdin (T Mestrovic PhD), University North, Varazdin, Croatia; Institute for Social Innovation, Skopje, Macedonia (N Milevska Kostova PhD); Health Policy and Management (N Milevska Kostova PhD), Centre for Regional Policy Research and Cooperation ‘Studiorum’, Skopje, Macedonia; Pacific Institute for Research & Evaluation, Calverton, MD, USA (T R Miller PhD); Global Institute of Public Health (Prof G Mini PhD), Ananthapuri Hospitals and Research Institute, Trivandrum, India; Women's Social and Health Studies Foundation, Trivandrum, India (Prof G Mini PhD); Internal Medicine Programme (Prof E M Mirrakhimov PhD), Kyrgyz State Medical Academy, Bishkek, Kyrgyzstan; Department of Atherosclerosis and Coronary Heart Disease (Prof E M Mirrakhimov PhD), National Center of Cardiology and Internal Disease, Bishkek, Kyrgyzstan; College of Dentistry (T A Mohamed MSc), University of Duhok, Duhok, Iraq; Department of Information Technology (M Mohammadi PhD), Lebanese French University, Erbil, Iraq; Department of Epidemiology and Biostatistics (A Mohammadian-Hafshejani PhD), Shahrekord University of Medical Sciences, Shahrekord, Iran; Health Systems and Policy Research Unit (S Mohammed PhD), Ahmadu Bello University, Zaria, Nigeria; Faculty of Life Sciences and Medicine (M Molokhia PhD), King's College London, London, UK; Department of Computer Science and Engineering (M A Moni PhD), Pabna University of Science and Technology, Pabna, Bangladesh; Department of Cardiology and Cardiac Surgery (J Morze PhDc), Univeristy of Warmia and Mazury, Olsztyn, Poland; Management and Leadership in Medical Education Research Center (S Mousavi PhD), Health Services Management Research Center (V Yazdi-Feyzabadi PhD), Department of Health Management, Policy, and Economics (V Yazdi-Feyzabadi PhD), Kerman University of Medical Sciences, Kerman, Iran; School of Economics (M K Muriithi PhD), School of Public Health (R G Wamai PhD), University of Nairobi, Nairobi, Kenya; Department of Medical Microbiology and Immunology (S Muthupandian PhD), School of Pharmacy (B Wubishet MPH), Mekelle University, Mekelle, Ethiopia; Saveetha Dental College (S Muthupandian PhD), Saveetha Institute of Medical and Technical Sciences, Chennai, India; Research and Analytics Department (A J Nagarajan MTech), Initiative for Financing Health and Human Development, Chennai, India; Department of Research and Analytics (A J Nagarajan MTech), Bioinsilico Technologies, Chennai, India; Graduate School of Business (M Naimzada MD, N Otstavnov BA, S S Otstavnov PhD), Department of Health Care Administration and Economics (Prof V Vlassov MD), National Research University Higher School of Economics, Moscow, Russia; Suraj Eye Institute, Nagpur, India (V Nangia MD); Discipline of Social & Administrative Pharmacy (A Naqvi PhD), University of Science, Malaysia, Penang, Malaysia; Department of Clinical Medicine (Prof B R Nascimento PhD), Clinical Hospital (Prof B R Nascimento PhD), Federal University of Minas Gerais, Belo Horizonte, Brazil; Department of Biotechnology (M Naveed PhD), University of Central Punjab, Lahore, Pakistan; Department of Disease Control and Environmental Health (R Ndejjo MSc), Makerere University, Kampala, Uganda; Department of General Surgery (I Negoi PhD), Emergency Hospital of Bucharest, Bucharest, Romania; Bupa Clemton Park (S Neupane Kandel BSN), Bupa, Sydney, NSW, Australia; Institute for Global Health Innovations (T H Nguyen MSc, L G Vu MSc), Faculty of Medicine (T H Nguyen MSc, L G Vu MSc), Institute of Research and Development (A Rahmani PhD), Duy Tan University, Da Nang, Vietnam; School of Public Health (J Nonvignon PhD), University of Ghana, Accra, Ghana; Centre for Heart Rhythm Disorders (J Noubiap MD), University of Adelaide, Adelaide, SA, Australia; Department of Pediatrics (V E Nwatah MD), National Hospital, Abuja, Nigeria; Department of International Public Health (V E Nwatah MD), University of Liverpool, Liverpool, UK; Administrative and Economic Sciences Department (Prof B Oancea PhD), University of Bucharest, Bucharest, Romania; Social Policy Program (F A O Ojelabi MPH), United Nations Childrens' Fund, Abuja, Nigeria; Department of Psychiatry and Behavioural Neurosciences (A T Olagunju MD), McMaster University, Hamilton, ON, Canada; Community Prevention and Care Services (B O Olakunde PhD), National AIDS Control Committee, Abuja, Nigeria; Department of Management, Economics, and Quantitative Methods (S Olgiati PhD), University of Bergamo, Bergame, Italy; Centre for Healthy Start Initiative, Lagos, Nigeria (J O Olusanya MBA); Department of Pharmacology and Therapeutics (Prof O E Onwujekwe PhD), University of Nigeria Nsukka, Enugu, Nigeria; Department of Genetics (S Pawar PhD), Yale University, New Haven, CT, USA; School of Optometry and Vision Science (Prof K Pesudovs PhD), University of New South Wales, Sydney, NSW, Australia; SSD Epidemiology Screening (C Piccinelli MS), City of Health and Science University Hospital of Turin, Turin, Italy; University Medical Center Groningen (Prof M J Postma PhD), School of Economics and Business (Prof M J Postma PhD), University of Groningen, Groningen, Netherlands; Centro de Investigaciones Clinicas (S I Prada PhD), Fundación Valle del Lili (Clinical Research Center, Valle del Lili Foundation), Cali, Colombia; Centro PROESA (S I Prada PhD), Universidad ICESI, Cali, Colombia; Biomedical Engineering Department (Prof M Rabiee PhD), Amirkabir University of Technology, Tehran, Iran; Department of Chemistry (N Rabiee MSc), Sharif University of Technology, Tehran, Iran; Thalassemia and Hemoglobinopathy Research Center (F Rahim PhD), Education Development Center (M Sayyah MD), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Department of Community Medicine (M Rahman PhD), Maharishi Markandeshwar Medical College & Hospital, Solan, India; Department of Population Science and Human Resource Development (M Rahman DrPH), University of Rajshahi, Rajshahi, Bangladesh; Future Technology Research Center (A Rahmani PhD), National Yunlin University of Science and Technology, Yunlin, Taiwan; Research Department (C L Ranabhat PhD), Policy Research Institute, Kathmandu, Nepal; Health and Public Policy Department (C L Ranabhat PhD), Global Center for Research and Development, Kathmandu, Nepal; University College London Hospitals, London, UK (D L Rawaf MD); Academic Public Health England (Prof S Rawaf MD), Public Health England, London, UK; School of Health, Medical and Applied Sciences (L Rawal PhD), CQ University, Sydney, NSW, Australia; School of Medicine (Prof A M N Renzaho PhD), Translational Health Research Institute (Prof A M N Renzaho PhD), Western Sydney University, Campbelltown, NSW, Australia; Department of Public Health and Informatics (R K Ripon MSPH), Jahangirnagar University, Dhaka, Bangladesh; Health Hub (J S Salama MSc), University of California San Francisco, San Francisco, CA, USA; Department of Entomology (A M Samy PhD), Ain Shams University, Cairo, Egypt; Public Health Unit (J V Santos MD), Northern Region Health Administration, Vila Nova de Gaia, Portugal; Faculty of Medicine (Prof M M Santric-Milicevic PhD), School of Public Health and Health Management (Prof M M Santric-Milicevic PhD), University of Belgrade, Belgrade, Serbia; Faculty of Health & Social Sciences (B Sathian PhD), Bournemouth University, Bournemouth, UK; GlaxoSmithKline Biologicals, Wavre, Belgium (M Savic PhD); Department of Community Medicine (Prof D Saxena PhD), Datta Meghe Institute of Medical Sciences, Wardha, India; Oral Diagnosis, Digital Health and Health Services Research (Prof F Schwendicke PhD), Charité University Medical Center Berlin, Berlin, Germany; Emergency Department (S Senthilkumaran MD), Manian Medical Centre, Erode, India; National Heart, Lung, and Blood Institute (A Seylani BS), National Institute of Health, Rockville, MD, USA; Independent Consultant, Karachi, Pakistan (M A Shaikh MD); Centre for Medical Informatics (Prof A Sheikh MD), University of Edinburgh, Edinburgh, UK; Department of Obstetrics and Gynaecology (A Shetty MS), Department of Forensic Medicine (P H Shetty MD), Manipal Academy of Higher Education, Mangalore, India; The University of Tokyo, Tokyo, Japan (Prof K Shibuya MD); Institute of Global Surgery (M G Shrime MD), Royal College of Surgeons in Ireland, Dublin, Ireland; National Institute of Psychology (K ShuMS), Quaid-i-Azam University, Islamabad, Pakistan; School of Medicine (Prof J A Singh MD), University of Alabama at Birmingham, Birmingham, AL, USA; Medicine Service (Prof J A Singh MD), US Department of Veterans Affairs (VA), Birmingham, AL, USA; Department No.16 (V Y Skryabin MD), Laboratory of Genetics and Genomics (Prof M S Zastrozhin PhD), Moscow Research and Practical Centre on Addictions, Moscow, Russia; Therapeutic Department (A A Skryabina MD), Balashiha Central Hospital, Balashikha, Russia; Department of Medicine (Prof R Tabarés-Seisdedos PhD), University of Valencia, Valencia, Spain; Carlos III Health Institute (Prof R Tabarés-Seisdedos PhD), Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Pharmacy (B W Taddele MPH), Arbaminch College of Health Sciences, Arba Minch, Ethiopia; Department of Pediatrics (A Thavamani MD), University Hospitals Rainbow Babies & Children's Hospital, Cleveland, OH, USA; Department of Social Security Empirical Research (Prof R Tobe-Gai PhD), National Institute of Population and Social Security Research, Tokyo, Japan; Institute of Public Health (R Topor-Madry PhD), Jagiellonian University Medical College, Kraków, Poland; Agency for Health Technology Assessment and Tariff System, Warsaw, Poland (R Topor-Madry PhD); Department of Pathology and Legal Medicine (M R Tovani-Palone PhD), University of São Paulo, Ribeirão Preto, Brazil; Modestum, London, UK (M R Tovani-Palone PhD); Department of Health Economics (B X Tran PhD), Hanoi Medical University, Hanoi, Vietnam; Lee Kong Chian School of Medicine (L Tudor Car PhD), Nanyang Technological University, Singapore, Singapore; Multidisciplinary Department (A Ullah MS), National University of Medical Sciences, Rawalpindi, Pakistan; School of Government (E A Undurraga PhD), Pontificia Universidad Catolica de Chile (Pontifical Catholic University of Chile), Santiago, Chile; Velez Sarsfield Hospital, Buenos Aires, Argentina (Prof P R Valdez MEd); UKK Institute, Tampere, Finland (Prof T J Vasankari MD); Clinical Research Department (J H Villafañe PhD), IRCCS Fondazione Don Carlo Gnocchi (Don Carlo Gnocchi Foundation), Milan, Italy; Occupational Health Unit (Prof F S Violante MD), Sant'Orsola Malpighi Hospital, Bologna, Italy; Faculty of Information Technology (B Vo PhD), Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam; Department of Economics (Prof S Vollmer PhD), University of Göttingen, Göttingen, Germany; Center of Excellence in Behavioral Medicine (G T Vu BA), Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam; Cultures, Societies and Global Studies, & Integrated Initiative for Global Health (R G Wamai PhD), Northeastern University, Boston, MA, USA; Demographic Change and Aging Research Area (A Werdecker PhD), Federal Institute for Population Research, Wiesbaden, Germany; National Data Management Center for Health (M A Woldekidan MPH), Ethiopian Public Health Institute, Addis Ababa, Ethiopia; Research Centre for Generational Health and Ageing (B Wubishet MPH), University of Newcastle, Newcastle, NSW, Australia; School of Medicine (Prof G Xu MD), Nanjing University, Nanjing, China; School of International Development and Global Studies (Prof S Yaya PhD), University of Ottawa, Ottawa, ON, Canada; Department of Health Management (V Yiğit PhD), Süleyman Demirel Üniversitesi (Süleyman Demirel University), Isparta, Turkey; Centre for Suicide Research and Prevention (Prof P Yip PhD), Department of Social Work and Social Administration (Prof P Yip PhD), University of Hong Kong, Hong Kong, China; Department of Neuropsychopharmacology (N Yonemoto MPH), National Center of Neurology and Psychiatry, Kodaira, Japan; Department of Public Health (N Yonemoto MPH), Juntendo University, Tokyo, Japan; Department of Health Policy and Management (Prof M Z Younis PhD), Jackson State University, Jackson, MS, USA; School of Medicine (Prof M Z Younis PhD), Tsinghua University, Beijing, China; Department of Epidemiology and Biostatistics (Prof C Yu PhD), School of Medicine (Z Zhang PhD), Wuhan University, Wuhan, China; Department of Clinical Pharmacy and Outcomes Sciences (I Yunusa PhD), University of South Carolina, Columbia, SC, USA; Social Determinants of Health Research Center (T Zahirian Moghadam PhD, H Zandian PhD), Department of Community Medicine (H Zandian PhD), Ardabil University of Medical Science, Ardabil, Iran; Addictology Department (Prof M S Zastrozhin PhD), Pediatrics Department (A Zastrozhina PhD), Russian Medical Academy of Continuous Professional Education, Moscow, Russia; Health Technology Assessment Unit (Y H Zuniga BS), Department of Health Philippines, Manila, Philippines; #MentalHealthPH, Quezon City, Philippines (Y H Zuniga BS).
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Global Burden of Disease 2020 Health Financing Collaborator Network:
Angela E Micah, Ian E Cogswell, Brandon Cunningham, Satoshi Ezoe, Anton C Harle, Emilie R Maddison, Darrah McCracken, Shuhei Nomura, Kyle E Simpson, Hayley N Stutzman, Golsum Tsakalos, Lindsey E Wallace, Yingxi Zhao, Rahul R Zende, Cristiana Abbafati, Michael Abdelmasseh, Aidin Abedi, Kedir Hussein Abegaz, E S Abhilash, Hassan Abolhassani, Michael R M Abrigo, Tara Ballav Adhikari, Saira Afzal, Bright Opoku Ahinkorah, Sepideh Ahmadi, Haroon Ahmed, Muktar Beshir Ahmed, Tarik Ahmed Rashid, Marjan Ajami, Budi Aji, Yonas Akalu, Chisom Joyqueenet Akunna, Hanadi Al Hamad, Khurshid Alam, Fahad Mashhour Alanezi, Turki M Alanzi, Yosef Alemayehu, Robert Kaba Alhassan, Cyrus Alinia, Syed Mohamed Aljunid, Sami Almustanyir Almustanyir, Nelson Alvis-Guzman, Nelson J Alvis-Zakzuk, Saeed Amini, Mostafa Amini-Rarani, Hubert Amu, Robert Ancuceanu, Catalina Liliana Andrei, Tudorel Andrei, Blake Angell, Mina Anjomshoa, Carl Abelardo T Antonio, Catherine M Antony, Muhammad Aqeel, Jalal Arabloo, Morteza Arab-Zozani, Timur Aripov, Alessandro Arrigo, Tahira Ashraf, Desta Debalkie Atnafu, Marcel Ausloos, Leticia Avila-Burgos, Asma Tahir Awan, Getinet Ayano, Martin Amogre Ayanore, Samad Azari, Gulrez Shah Azhar, Tesleem Kayode Babalola, Mohammad Amin Bahrami, Atif Amin Baig, Maciej Banach, Nastaran Barati, Till Winfried Bärnighausen, Amadou Barrow, Sanjay Basu, Bernhard T Baune, Mohsen Bayati, Habib Benzian, Adam E Berman, Akshaya Srikanth Bhagavathula, Nikha Bhardwaj, Pankaj Bhardwaj, Sonu Bhaskar, Sadia Bibi, Ali Bijani, Virginia Bodolica, Nicola Luigi Bragazzi, Dejana Braithwaite, Nicholas J K Breitborde, Alexey V Breusov, Nikolay Ivanovich Briko, Reinhard Busse, Lucero Cahuana-Hurtado, Emily Joy Callander, Luis Alberto Cámera, Carlos A Castañeda-Orjuela, Ferrán Catalá-López, Jaykaran Charan, Souranshu Chatterjee, Soosanna Kumary Chattu, Vijay Kumar Chattu, Simiao Chen, Arrigo Francesco Giuseppe Cicero, Omid Dadras, Saad M A Dahlawi, Xiaochen Dai, Koustuv Dalal, Lalit Dandona, Rakhi Dandona, Dragos Virgil Davitoiu, Jan-Walter De Neve, Antonio Reis de Sá-Junior, Edgar Denova-Gutiérrez, Deepak Dhamnetiya, Samath Dhamminda Dharmaratne, Leila Doshmangir, John Dube, Elham Ehsani-Chimeh, Maysaa El Sayed Zaki, Maha El Tantawi, Sharareh Eskandarieh, Farshad Farzadfar, Tomas Y Ferede, Florian Fischer, Nataliya A Foigt, Alberto Freitas, Sara D Friedman, Takeshi Fukumoto, Nancy Fullman, Peter Andras Gaal, Mohamed M Gad, MA Garcia-Gordillo, Tushar Garg, Mansour Ghafourifard, Ahmad Ghashghaee, Asadollah Gholamian, Ali Gholamrezanezhad, Ghozali Ghozali, Syed Amir Gilani, Ionela-Roxana Glăvan, Ekaterina Vladimirovna Glushkova, Salime Goharinezhad, Mahaveer Golechha, Srinivas Goli, Avirup Guha, Veer Bala Gupta, Vivek Kumar Gupta, Annie Haakenstad, Mohammad Rifat Haider, Alemayehu Hailu, Samer Hamidi, Asif Hanif, Harapan Harapan, Risky Kusuma Hartono, Ahmed I Hasaballah, Shoaib Hassan, Mohamed H Hassanein, Khezar Hayat, Mohamed I Hegazy, Golnaz Heidari, Delia Hendrie, Ileana Heredia-Pi, Claudiu Herteliu, Kamal Hezam, Ramesh Holla, Sheikh Jamal Hossain, Mehdi Hosseinzadeh, Sorin Hostiuc, Tanvir M Huda, Bing-Fang Hwang, Ivo Iavicoli, Bulat Idrisov, Olayinka Stephen Ilesanmi, Seyed Sina Naghibi Irvani, Sheikh Mohammed Shariful Islam, Nahlah Elkudssiah Ismail, Gaetano Isola, Mohammad Ali Jahani, Nader Jahanmehr, Mihajlo Jakovljevic, Manthan Dilipkumar Janodia, Tahereh Javaheri, Sathish Kumar Jayapal, Ranil Jayawardena, Seyed Behzad Jazayeri, Ravi Prakash Jha, Jost B Jonas, Tamas Joo, Farahnaz Joukar, Mikk Jürisson, Billingsley Kaambwa, Rohollah Kalhor, Tanuj Kanchan, Himal Kandel, Behzad Karami Matin, Salah Eddin Karimi, Getinet Kassahun, Gbenga A Kayode, Ali Kazemi Karyani, Leila Keikavoosi-Arani, Yousef Saleh Khader, Himanshu Khajuria, Rovshan Khalilov, Mohammad Khammarnia, Junaid Khan, Jagdish Khubchandani, Neda Kianipour, Gyu Ri Kim, Yun Jin Kim, Adnan Kisa, Sezer Kisa, Stefan Kohler, Soewarta Kosen, Rajasekaran Koteeswaran, Sindhura Lakshmi Koulmane Laxminarayana, Ai Koyanagi, Kewal Krishan, G Anil Kumar, Dian Kusuma, Demetris Lamnisos, Van Charles Lansingh, Anders O Larsson, Savita Lasrado, Long Khanh Dao Le, Shaun Wen Huey Lee, Yeong Yeh Lee, Stephen S Lim, Stany W Lobo, Rafael Lozano, Hassan Magdy Abd El Razek, Muhammed Magdy Abd El Razek, Mokhtar Mahdavi Mahdavi, Azeem Majeed, Alaa Makki, Afshin Maleki, Reza Malekzadeh, Ana Laura Manda, Fariborz Mansour-Ghanaei, Mohammad Ali Mansournia, Carlos Alberto Marrugo Arnedo, Adolfo Martinez-Valle, Seyedeh Zahra Masoumi, Richard James Maude, Martin McKee, Carlo Eduardo Medina-Solís, Ritesh G Menezes, Atte Meretoja, Tuomo J Meretoja, Mohamed Kamal Mesregah, Tomislav Mestrovic, Neda Milevska Kostova, Ted R Miller, GK Mini, Andreea Mirica, Erkin M Mirrakhimov, Bahram Mohajer, Teroj Abdulrahman Mohamed, Mokhtar Mohammadi, Abdollah Mohammadian-Hafshejani, Shafiu Mohammed, Modhurima Moitra, Ali H Mokdad, Mariam Molokhia, Mohammad Ali Moni, Yousef Moradi, Jakub Morze, Seyyed Meysam Mousavi, Christine Mpundu-Kaambwa, Moses K Muriithi, Saravanan Muthupandian, Ahamarshan Jayaraman Nagarajan, Mukhammad David Naimzada, Vinay Nangia, Atta Abbas Naqvi, Aparna Ichalangod Narayana, Bruno Ramos Nascimento, Muhammad Naveed, Biswa Prakash Nayak, Javad Nazari, Rawlance Ndejjo, Ionut Negoi, Sandhya Neupane Kandel, Trang Huyen Nguyen, Justice Nonvignon, Jean Jacques Noubiap, Vincent Ebuka Nwatah, Bogdan Oancea, Foluke Adetola Ogunyemi Ojelabi, Andrew T Olagunju, Babayemi Oluwaseun Olakunde, Stefano Olgiati, Jacob Olusegun Olusanya, Obinna E Onwujekwe, Adrian Otoiu, Nikita Otstavnov, Stanislav S Otstavnov, Mayowa O Owolabi, Jagadish Rao Padubidri, Raffaele Palladino, Songhomitra Panda-Jonas, Eun-Cheol Park, Fatemeh Pashazadeh Kan, Shrikant Pawar, Hamidreza Pazoki Toroudi, David M Pereira, Arokiasamy Perianayagam, Konrad Pesudovs, Cristiano Piccinelli, Maarten J Postma, Sergio I Prada, Mohammad Rabiee, Navid Rabiee, Fakher Rahim, Vafa Rahimi-Movaghar, Mohammad Hifz Ur Rahman, Mosiur Rahman, Amir Masoud Rahmani, Usha Ram, Chhabi Lal Ranabhat, Priyanga Ranasinghe, Chythra R Rao, Priya Rathi, David Laith Rawaf, Salman Rawaf, Lal Rawal, Reza Rawassizadeh, Robert C Reiner Jr, Andre M N Renzaho, Bhageerathy Reshmi, Mavra A Riaz, Rezaul Karim Ripon, Anas M Saad, Mohammad Ali Sahraian, Maitreyi Sahu, Joseph S Salama, Sana Salehi, Abdallah M Samy, Juan Sanabria, Francesco Sanmarchi, João Vasco Santos, Milena M Santric-Milicevic, Brijesh Sathian, Miloje Savic, Deepak Saxena, Mehdi Sayyah, Falk Schwendicke, Subramanian Senthilkumaran, Sadaf G Sepanlou, Allen Seylani, Saeed Shahabi, Masood Ali Shaikh, Aziz Sheikh, Adithi Shetty, Pavanchand H Shetty, Kenji Shibuya, Mark G Shrime, Kanwar Hamza Shuja, Jasvinder A Singh, Valentin Yurievich Skryabin, Anna Aleksandrovna Skryabina, Shahin Soltani, Moslem Soofi, Emma Elizabeth Spurlock, Simona Cătălina Stefan, Viktória Szerencsés, Miklós Szócska, Rafael Tabarés-Seisdedos, Biruk Wogayehu Taddele, Yonas Getaye Tefera, Aravind Thavamani, Ruoyan Tobe-Gai, Roman Topor-Madry, Marcos Roberto Tovani-Palone, Bach Xuan Tran, Lorainne Tudor Car, Anayat Ullah, Saif Ullah, Nasir Umar, Eduardo A Undurraga, Pascual R Valdez, Tommi Juhani Vasankari, Jorge Hugo Villafañe, Francesco S Violante, Vasily Vlassov, Bay Vo, Sebastian Vollmer, Theo Vos, Giang Thu Vu, Linh Gia Vu, Richard G Wamai, Andrea Werdecker, Mesfin Agachew Woldekidan, Befikadu Legesse Wubishet, Gelin Xu, Sanni Yaya, Vahid Yazdi-Feyzabadi, Vahit Yiğit, Paul Yip, Birhanu Wubale Yirdaw, Naohiro Yonemoto, Mustafa Z Younis, Chuanhua Yu, Ismaeel Yunusa, Telma Zahirian Moghadam, Hamed Zandian, Mikhail Sergeevich Zastrozhin, Anasthasia Zastrozhina, Zhi-Jiang Zhang, Arash Ziapour, Yves Miel H Zuniga, Simon I Hay, Christopher J L Murray, and Joseph L Dieleman
Supplementary Material
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data used for this study were extracted from publicly available sources that are listed in the appendix (pp 7, 28–33, 65, 81–82, 92, 117). Further details are available on the Global Health Data Exchange website at http://ghdx.healthdata.org/series/financing-global-health-fgh