Global Health Data Exchange - Discover the World's Health Data

IHME Data

Download datasets created by IHME for our research projects and publications. You can learn more about our research and publications on our website


Data made available for download on IHME Websites can be used, shared, modified or built upon by non-commercial users in accordance with the IHME FREE-OF-CHARGE NON-COMMERCIAL USER AGREEMENT. For more information (and inquiries about commercial use), visit IHME Terms and Conditions.


The Global Burden of Disease Study 2021 (GBD 2021), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

This dataset includes annual estimates for number and rates of stillbirth at ≥ 20 and ≥ 28 weeks gestation from 1990-2021. For additional GBD results and resources, visit the GBD 2021 Data Resources page.

The Global Burden of Disease Study 2021 (GBD 2021), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 204 countries and territories and selected subnational locations.

Annual estimates for fertility, population, migration, and all-cause mortality are available by age and sex for 1950-2021 from the GBD Results Tool. Select tables published in The Lancet in March 2024 in "Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2021" are also available for download via the “Files” tab above.

For additional GBD results and resources, visit the GBD 2021 Data Resources page.

Liver cancer mortality rate estimates were produced at the county level in the United States, and by racial and ethnic population, for each year between 2000-2019. These estimates were generated using population and deaths data from the National Center for Health Statistics.

This dataset includes the following:

  • CSV files of county-, state-, and national-level estimates of liver cancer mortality rates for each age group, sex, year, and racial and ethnic population (non-Latino and non-Hispanic American Indian or Alaska Native [AIAN], non-Latino and non-Hispanic Asian or Pacific Islander [Asian], non-Latino and non-Hispanic Black [Black], Latino or Hispanic [Latino], and non-Latino and non-Hispanic White [White]). Blank cells are for masked estimates
  • Code used to generate the estimates

Researchers systematically reviewed, identified, and extracted data from cohort, case-control, and Mendelian randomization studies published between 1970 and 2021 that estimated the association between alcohol consumption and risk of ischemic heart disease. In total, 124 unique studies were included. Relative risk curves for the association between alcohol consumption and ischemic heart disease were estimated using data from cohort and case-control studies separately and in combination, and from Mendelian randomization studies using the Burden of Proof meta-analytic framework.

Estimates were produced for family planning for women ages 15-49 years at the 5x5 km-level in Burkina Faso, Kenya, and Nigeria from 2000-2020. They were produced using data from 65 population-based household surveys conducted in Africa between 2000 and 2020 that included information on contraception use and fertility, and subnational geographical location for women 15-49 years.

This dataset includes:

  • GeoTIFF raster files for pixel-level estimates of CPR (contraceptive prevalence), mCPR (modern contraceptive prevalence), tCPR (traditional contraceptive prevalence), unmet need (unmet need for contraception), met need (met need for contraception with modern methods), and intent (intent to use contraception in the future)
  • CSV files of aggregated estimates at the country level and the first and second administrative divisions
  • Code files used to generate the estimates

Get Data Files

Researchers at IHME and the Centre for Global Health Inequalities Research (CHAIN) at the Norwegian University of Science and Technology (NTNU), conducted a systematic review and meta-analysis to assess the effect of education on all-cause adult mortality. Mixed-effects meta-regression models were implemented to address heterogeneity in referent and exposure measures among studies and to adjust for study-level covariates. 17 094 unique records were identified, 603 of which were eligible for analysis and included data from 70 locations in 59 countries, producing a final dataset of 10 355 observations. Education showed a dose–response relationship with all-cause adult mortality, with an average reduction in mortality risk of 1·9% per additional year of education. The effect was greater in younger age groups than in older age groups, and researchers found no differential effect of education on all-cause mortality by sex or sociodemographic index level.

Development Assistance for Health (DAH) on COVID-19 produced estimates for 2020-2022, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for COVID-19-related health projects in low- and middle-income countries from key agencies. The data are disaggregated by source of funds, channel of funding, country and geographic region, and program areas.

Researchers at IHME and the University of Oxford estimated deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) associated with and attributable to bacterial antimicrobial resistance (AMR) in 88 pathogen-drug combinations for the WHO Region of Africa and for 35 countries in 2019. Data gathered to inform these estimates included multiple cause of death data, hospital discharges, minimally invasive tissue sampling, systematic literature reviews, and microbiology lab results from hospitals and national and multi-national surveillance systems, totaling 343 million individual records or isolates and 11,361 study-location-years collected. These data informed 8 modelling components which were combined with results from GBD 2019 to estimate AMR burden. Estimates were produced for two counterfactual scenarios: no infection and drug-susceptible infection.

This dataset includes total cardiovascular disease burden estimates globally for multiple cardiovascular diseases for 7 Global Burden of Disease Study (GBD) super regions, 21 GBD regions, 204 countries and territories, and select subnational locations. The following are reported: mortality by age and sex for the years 1990-2022; age-standardized mortality in 2022 by Socio-Demographic Index (SDI), a composite indicator of fertility, income, and education; all ages and age-standardized prevalence for 2022; and age-standardized disability-adjusted life years (DALYs) for 2022. The dataset also includes burden attributable to selected risk factors for each GBD region in 2022, as measured by DALYs. These data are custom calculated for publication in the Journal of the American College of Cardiology and will not be available in the GBD 2022 Results Tool.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI community survey carried out in Belize covers eligible women’s background characteristics, access to health care, fertility preferences, and knowledge and use of contraceptive methods (including barriers to use). Women who have been pregnant in the last two years answer questions about birth history; antenatal, delivery, and postpartum care; breastfeeding; and infant feeding practices. Caretakers of children aged 0-5 years are asked detailed questions for each child under age 5 on topics such as child’s current health status, recent history of illness, immunization, and supplementation history.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI health facility survey is designed to assess facility conditions, evaluate service provision and utilization, and measure quality of care. Patient medical records are examined to evaluate facilities’ treatment practices retrospectively over the course of the evaluation period. Health facility data collection aims to capture changes produced by interventions at the level of the health services access point, which may foretell changes in population health outcomes.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. Funding focuses on supply- and demand-side interventions, including evidence-based interventions, the expansion of proven and cost-effective healthcare packages, and the delivery of incentives for effective health services. One of its defining features is the application of a results-based financing (RBF) model that relies on performance measurement and enhanced transparency and accountability. The initiative focuses its resources on integrating key interventions aimed at reducing health inequalities that stem from the lack of access to quality reproductive, maternal, neonatal, and child health services (including immunization and nutrition services) for the poorest quintile of the population.

The Salud Mesoamérica Initiative (SMI) is a regional public-private partnership that brings together Mesoamerican governments, private foundations and bilateral and multilateral donors with the purpose of reducing health inequalities affecting the poorest 20 percent of the population in the  region. The SMI household survey captures household characteristics, reported maternal and child health data for women 15-49 years of age and for children 0-59 months of age, and anthropometric measurements including height, weight, and hemoglobin concentration for children. Community data collection via household surveys permits the measurement of changes in health status, access to health care, and satisfaction with health care, as well as an array of data points which give context to these factors.

This dataset contains aggregated indicators calculated using self-report survey data from more than 621,000 people in 21 countries aged 18 years and up collected from March-May 2023. Data were collected through a stratified random sampling approach of Facebook users via a Qualtrics platform. Questionnaires were translated into 15 languages and survey weights were calculated to help correct for sampling bias. Indicator topics include access to health care, trust in governmental organizations, vaccine confidence, financial security, food security, education, COVID-19 vaccination status, childhood routine immunizations, and demographic and behavioral variables.

Completed as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, this dataset provides estimates of anemia prevalence and years lived with disability by 37 underlying causes, three severity levels, age, and sex for 204 countries and territories and selected subnational geographies in five year increments from 1990 to 2021. Please refer to the related publication for information on modeling methods and analysis.

Get Data Files

Researchers at IHME and the University of Oxford produced estimates of deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) associated with and attributable to bacterial antimicrobial resistance (AMR) in 88 pathogen-drug combinations for the WHO Region of the Americas and for 35 countries within this geographical region in 2019. A variety of data were gathered to inform these estimates, including multiple cause of death data, hospital discharges, minimally invasive tissue sampling, systematic literature reviews, and microbiology lab results from hospitals and national and multi-national surveillance systems, with a total of 343 million individual records or isolates and 11,361 study-location-years collected. These data informed 8 modelling components which were then combined with results from GBD 2019 to estimate the burden of AMR. Estimates were produced for two counterfactual scenarios: no infection and drug-susceptible infection.

Stomach cancer mortality rate estimates were produced at the county level in the United States, by racial/ethnic group, for each year between 2000-2019. These estimates were generated using population and deaths data from the National Center for Health Statistics.

This dataset includes the following:

  • CSV files of county-, state-, and national-level estimates of stomach cancer mortality rates for each age group, sex, year, and racial-ethnic group (non-Hispanic White [White], non-Hispanic Black [Black], non-Hispanic Asian or Pacific Islander [Asian], non-Hispanic American Indian Alaska Native [AIAN], and Hispanic or Latino [Latino]). Blank cells are for masked estimates
  • Code used to generate the estimates

Mortality rate estimates were produced at the county level in the United States, for 19 causes of death and by racial/ethnic group, for each year between 2000-2019. These estimates were generated using population and deaths data from the National Center for Health Statistics.

This dataset includes the following:

  • CSV files of county-, state-, and national-level estimates of mortality rates and life expectancy for each age group, sex, year, and racial-ethnic group (non-Hispanic White [White], non-Hispanic Black [Black], non-Hispanic Asian or Pacific Islander [Asian], non-Hispanic American Indian Alaska Native [AIAN], and Hispanic or Latino [Latino]). Blank cells are for masked estimates
  • Code used to generate the estimates

Established in 2015 by the United Nations, the Sustainable Development Goals (SDGs) specify 17 universal goals for achieving "peace and prosperity" by reducing inequality, improving health and education, and more. Each goal contains a number of specific targets and indicators for measurement and is intended to be achieved by 2030. This dataset provides estimates on progress for indicator 5.2.1, the proportion of age-standardized prevalence of ever-partnered women ages 15 years and older who experienced physical or sexual violence by a current or former intimate partner in the last 12 months. Progress on this indicator is reported as index values (scaled 0 to 100) which cover 204 countries and territories from 1990 to 2021. The indicator is a component of SDG 5 (Achieve gender equality and empower all women and girls), target 5.2 (Eliminate all forms of violence against all women and girls in the public and private spheres, including trafficking and sexual and other types of exploitation).

This dataset provides estimates of first- and third-dose coverage of diphtheria-tetanus-pertussis (DTP) vaccine at the first- and second-administrative unit levels in Nigeria from 2000-2018. These estimates were produced using data on vaccination coverage and geographical locations from household-based surveys.

This dataset includes the following:

  • CSV files of aggregated DTP1 and DTP3 coverage estimates at the first, and second administrative unit divisions
  • Code files used to generate the estimates

This dataset includes estimates generated by IHME to assess trends in maternal mortality across five racial and ethnic groups in the U.S. The dataset includes MMR (maternal mortality ratio) estimates for Hispanic and any race; non-Hispanic American Indian and Alaska Native; non-Hispanic Asian, Native Hawaiian, or Other Pacific Islander; non-Hispanic Black; and non-Hispanic White females ages 10-54 for each year from 1999 through 2019. The dataset includes national estimates, estimates for each Census region, estimates for each racial and ethnic group and Census region, and estimates for each racial and ethnic group and state. 

Completed as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, this dataset provides a global assessment of sickle cell disease (SCD) birth incidence, prevalence and mortality burden by age and sex for 204 countries and territories from 2000 to 2021. It includes estimates for three distinct genotype-specific SCD models: homozygous SCD and severe sickle cell/beta thalassaemia (SS and Sβ°), sickle cell-hemoglobin C disease (SC), and “mild” sickle cell/beta thalassaemia (Sβ+). The three model estimates were summed into estimates for “total SCD mortality.” The latter can be compared against the estimates provided for the GBD cause "Sickle cell disorders," both of which are also included in the dataset. Refer to the related publication for information on modeling methods and analysis.

Subnational estimates were produced of the overlap of prevalence of target-age children who have never received a dose of diphtheria-tetanus-pertussis-containing vaccine (No-DTP) with that of five related health indicators: 1) children with stunting, 2) mortality among children under 5, 3) children who had diarrhea who did not receive oral rehydration therapy, 4) prevalence of lymphatic filariasis (LF), and 5) individuals who did not sleep under insecticide-treated bednets. Data are presented at the second administrative level for five countries: Angola, Democratic Republic of the Congo, Ethiopia, Indonesia, and Nigeria. Data are presented for the years 2000 and the most recent year of data available for the respective health indicators. Data include designations into population-weighted quartiles according to both prevalence and counts, and at both country-specific and multinational levels. Values for percent overlap and area under the curve (AUC) are also included at the national level.

This dataset includes estimates generated by IHME to assess the impact of COVID-19 in the USA and evaluate possible trade-offs between COVID-19 outcomes and the economy, employment, and education. The estimates include standardized cumulative infection and death rates, relative reductions in cumulative GDP and employment, and changes in student test scores. State-level estimates of cumulative death rates due to COVID-19 between January 1, 2020 and July 31, 2022 were extracted from IHME’s COVID-19 database and standardized for age and the prevalence of key comorbidities. Estimates of cumulative SARS-Cov-2 infection rates between January 1, 2020 and December 15, 2021 were adjusted for population density. Monthly data on GDP and employment rates were sector-standardized and estimated relative to the expected non-pandemic value. Student standardized test scores were expressed as the change in mean 4th grade math and reading scores between 2019 and 2022.

Researchers at IHME systematically reviewed, identified, and extracted data from scientific literature studies that estimated the reduction in risk of COVID-19 among individuals with a past SARS-CoV-2 infection in comparison to those without a previous infection. The outcomes assessed were reinfection, symptomatic reinfection, and severe reinfection (hospitalization or death). Extracted SARS-CoV-2 lineages were ancestral, mixed (two different specified variants – e.g., ancestral and Alpha), Alpha (B.1.1.7), Beta (B.1.351), Delta (B.1.617.2), and Omicron (BA.1) and its sub-lineages (BA.2, BA.4/BA.5). A total of 65 studies from 19 different countries were identified. The researchers also produced a meta-analysis of the effectiveness of past infection by outcome (infection, symptomatic disease, and severe disease), variant, and time since infection.

Research by the Global Burden of Disease Health Financing Collaborator Network produced estimates for Gross Domestic Product (GDP) from 1960-2050. Estimates are reported as GDP per person in constant 2021 purchasing-power parity-adjusted (PPP) dollars. 

Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2020-2050 for 204 countries and territories. The estimates cover total health spending, health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private), and development assistance for health (DAH). Retrospective health spending estimates for 1995-2019 and key covariates (including GDP per capita, total government spending, total fertility rate, and fraction of the population older than 65 years) were used to forecast GDP and health spending through 2050. Estimates are reported in constant 2021 US dollars, constant 20201purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.

Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective health spending estimates for 1995-2019 for 204 countries and territories. The estimates cover total health spending, health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private), and development assistance for health (DAH). Domestic health spending source data came primarily from the WHO’s Global Health Expenditure Database (GHED). DAH data came from a diverse set of sources, including program reports, budget data, national estimates, and National Health Accounts (NHAs). The resulting estimates were used to forecast GDP and prospective health spending estimates for 2020-2050. Estimates are reported in constant 2021 United States Dollars, constant 2021 purchasing power parity adjusted (PPP) dollars, and as a percent of gross domestic product.

This version of the Development Assistance for Health (DAH) Database includes estimates for 1990-2021, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for health projects in low- and middle-income countries from key agencies. The data are disaggregated by source of funds, channel of funding, country and geographic region, health focus areas, and program areas.
To better understand the data and how to use it, please refer to the IHME DAH Database 2021 User Guide.

Development Assistance for Health (DAH) on COVID-19 produced estimates for 2020-2021, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for COVID-19-related health projects in low- and middle-income countries from key agencies. The data are disaggregated by source of funds, channel of funding, country and geographic region, and program areas.

This version of the Development Assistance for Health (DAH) Database includes estimates for 1990-2022, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for health projects in low- and middle-income countries from key agencies. The data are disaggregated by source of funds, channel of funding, country and geographic region, health focus areas, and program areas.
To better understand the data and how to use it, please refer to the IHME DAH Database 2022 User Guide.

Pages

GHDx: IHME Data Subscribe