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.
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.
This dataset provides estimates of vaccination coverage for meningococcal serogroup A conjugate vaccine (MenAfriVac®) for 24 countries in the meningitis belt of sub-Saharan Africa between 2010 and 2021. Indicators include mean and 95% uncertainty intervals for the estimated coverage for children aged 1 to 5 and children and young adults aged 1 to 29. These estimates include coverage from both mass vaccination campaigns and routine immunization delivery. The estimation process primarily utilized survey report data and country-reported administrative vaccine coverage data.
This dataset includes estimates for COVID-19 spending on vaccine delivery for seven regions in 2020-2021. These estimates are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The estimates are disaggregated by source of funds, channels or disbursing entities, focus or program area for the spending, and spending type. Estimates are reported in 2021 US dollars.
Estimates from the Global Burden of Disease Study 2019 (GBD 2019) were used to create the Healthcare Access and Quality (HAQ) Index overall and for select age groups in 204 countries and territories from 1990 to 2019. For GBD 2019, HAQ Index construction methods were updated to use the arithmetic mean of scaled mortality-to-incidence ratios (MIRs) and risk-standardised death rates (RSDRs) for 32 causes of death that should not occur in the presence of timely, quality health care.
This dataset contains estimates for the overall and age-group specific indices along with each unscaled HAQ Index indicator by location in 1990 and 2019. Code used to produce the estimates is also available for download.
Results were published in The Lancet Global Health in December 2022 in “Assessing performance of the Healthcare Access and Quality Index, overall and by select age groups, for 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019.”
Annual estimates were produced for HIV prevalence and the number of people living with HIV (PLHIV) at the 5x5 km-level for 43 countries in sub-Saharan Africa from 2000-2018. The estimates are by sex and for 5-year age groups in the 15-59 year range, and the age groups 15-49 years and 15-59 years. These estimates were produced using a geo-positioned dataset created from 95 household surveys as well as 10,351 site-years of sentinel surveillance reporting of Antenatal Care clinic attendees. Data for covariates associated with HIV prevalence were also incorporated from 294 surveys.
This dataset includes:
- GeoTIFF raster files for pixel-level estimates of HIV prevalence and PLHIV
- CSV files of aggregated HIV prevalence estimates for each country at zero, first, and second administrative divisions
- Code files used to generate the estimates
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 and 2021; age-standardized mortality in 2021 by Socio-Demographic Index (SDI), a composite indicator of fertility, income, and education; all ages and age-standardized prevalence for 2021; and age-standardized disability-adjusted life years (DALYs) for 2021. The dataset also includes burden attributable to selected risk factors for each GBD region in 2021, 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 2021 Results Tool.
Researchers at IHME and the University of Oxford produced estimates of deaths and years of life lost (YLLs) associated with bacterial infections caused by 33 pathogens across 204 locations in 2019. This study extends the results of the 2019 Global Burden of AMR study and uses its overall methodological approach to provide more granular estimates. 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 6 modelling components which were then combined with results from GBD 2019 to estimate the burden of AMR.
This dataset includes custom generated risk-attributable, non-risk attributable and total cancer burden estimates by location, age group, sex, cause, risk, and measure for the year 2019 that are not part of the 2019 GBD Results tool. This dataset also contains metrics that are custom calculated such as male to female ratios, proportions, and change between two years of estimates. Some examples of results: age-standardized mortality rates attributable to risks assessed and age-standardized mortality rates not attributable to risks assessed for cancers attributable to risk factors, for non-high Socio-Demographic Index (SDI) and high SDI in 2019 by sex. Non-high SDI include low, low-middle, middle, and high-middle SDI locations.
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 53 countries within the WHO European 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 471 million individual records or isolates and 7,585 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.
The Burden of Proof analysis is designed to assess the strength of evidence for epidemiological relationships, considering all pairs of risk factors and health outcomes in the GBD study. For a given risk-outcome pair, the approach generates a score that is based on size of the risk factor effect, agreement of results across studies, and availability of data. The score is obtained using the burden of proof risk function, which is the most conservative effect size consistent with the data. For a harmful risk factor, the burden of proof risk function is the lower bound of uncertainty interval of the log-relative risk, and for a protective risk factor, it is the upper bound. The final risk-outcome score is summarized using stars, with a 5-star rating indicating the strongest evidence, and 1-star score indicating the weakest evidence.
Global estimates were produced on the impacts of malnutrition in children younger than 5 years with orofacial clefts. Patient data collected by Smile Train clinical partners were merged with the estimates and insights on the direct health consequences of malnutrition from the Global Burden of Diseases, Injuries, and Risk Factors Study. The resulting estimates encompass relative rates of underweight in those with clefts, total children with underweight status and cleft occurrence, excess malnutrition cases in those with clefts, and the associated malnutrition-related consequences including deaths and disease burden. These results are detailed by country, age, sex, and year.
Estimates were produced for onchocerciasis all-age microfiladermia (positive skin snip) prevalence at the 5x5 km-level in 34 endemic countries across Africa, plus Yemen, annually between 2000 and 2018. These estimates were produced using reported data on onchocerciasis prevalence from endemicity mapping surveys, surveillance during elimination programs, and other sources.
This dataset includes the following:
- GeoTIFF raster files for pixel-level estimates of onchocerciasis prevalence
- CSV files of aggregated estimates of onchocerciasis prevalence for each country at the national level, and for first and second administrative divisions
- Code files used to generate the estimates
This dataset contains relative risks, excess mortality, and death count estimates computed from probabilistically linked hospital and mortality records for 72,021,918 patients in the Brazilian Public Health System (SUS) between January 1, 2000, and April 21, 2015. Follow-up duration was measured from the date of the patients’ first hospitalization until their death, or until April 21, 2015. Severe mental illness was defined as schizophrenia, bipolar disorder, or depressive disorder by ICD-10 codes used for the admission. Relative risks were calculated with 95% CIs, comparing mortality among patients with severe mental illness with those with other diagnoses for patients aged 15 years and older. Ill-defined causes of death were redistributed according the Global Burden of Disease study (GBD) methodology when present as the underlying cause.
Annual estimates of contraceptive use and need for family planning were produced for 204 countries and territories from 1970–2019. Data used came from cross-sectional surveys that sampled women ages 15-49 in which respondents self-reported contraceptive use. This dataset includes annual estimates by location, age group, and marital status for any and modern contraceptive prevalence, unmet need for any contraception, and demand satisfied with modern methods. Additionally, prevalence was estimated for 15 contraceptive methods. If a women reported using more than one method, only the most effective method was counted. Due to small sample sizes of partnered and unpartnered women in some locations, only all age and age-standardized estimates (ages 15-49) are provided with marital breakdowns.
This dataset contains health expenditure by state and the District of Columbia for the United States for the years 2003-2019, reported in spending per person in 2020 United States Dollars (USD). These data include total health expenditure, health spending by payer, and health spending by type of service, sourced from the Centers for Medicare and Medicaid Services (CMS) State Health Expenditure Accounts from 1991-2014 and estimated by IHME for 2015-2019. In addition to true spending estimates, these data contain standardized estimates of total health spending and spending by payer, where estimates were controlled for state variation in age, regional prices, income, population density, and health risk factors. Standardized estimates were produced by IHME for the years 2003-2019.
Health care spending effectiveness is the ratio of an increase in spending per case of illness or injury to an increase in disability-adjusted life-years (DALYs) averted per case. This dataset contains health care spending effectiveness ratios in the United States from 1996 to 2016. The ratios were created using comprehensive estimates of health care spending from the Disease Expenditure Study (DEX) and DALYs from the 2017 Global Burden of Disease study (GBD). Changes were decomposed over time to estimate spending per case and DALYs averted per case, while controlling for changes in population size, age-sex structure, and incidence or prevalence of cases.
Estimates were produced for mortality rates, life expectancy, and population at the state level in the United States, and by racial/ethnic group, for each year between 1990-2019. These estimates were produced using population and deaths data from the National Center for Health Statistics.
This dataset includes the following:
- CSV files of state-, and national-level estimates of mortality rates and life expectancy for each age group, sex, year, and racial-ethnic group (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic, Other). Blank cells are for masked estimates
- Code used to generate the estimates
The dataset contains predictions of the incremental cost-effectiveness ratios (ICERs) for the rotavirus vaccine in 195 countries. Predictions are based on meta-regression estimates of ICERs on three sets of independent variables (true variation measured by country characteristics, intervention characteristics, and bias variables). Data used in the meta-regression analysis are 515 ICERs from 68 studies in the Tufts University’s cost-effectiveness analysis registries, and additional extractions of ICERs for sensitivity analyses.
Estimates were produced for mortality rates and life expectancy at the county level in the United States, and by racial/ethnic group, for each year between 2000-2019. These estimates were produced 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 (all of which are non-Latino, except for the Latino group): White, Black, American Indian and Alaska Native (AIAN), Asian and Pacific Islander (API), and Latino. Blank cells are for masked estimates
- Code used to generate the estimates
This dataset contains retrospective estimates for healthcare spending attributable to dementia for 195 countries from 2000 to 2019 and prospective spending estimates from 2020 to 2050 under multiple scenarios. Intermediate and final estimates are provided. Intermediate estimates include community based care rate (CBC), nursing home based care rate (NHBC), community based care unit cost, and nursing home based care unit cost. Final estimates are attributable dementia spending. All spending is reported in 2019 United States dollars. Future estimates report the same model outputs as those reported in the retrospective model but include both reference and alternative scenarios based on accelerated care setting rates and units costs.
These development assistance for human resources for health (DAHRH) estimates are generated using data from IHME’s Development Assistance for health Database DAH, COVID development assistance database and the Organization for Economic Cooperation and Development’s Creditor Reporting System (CRS) online database. The IHME databases enables comprehensive analysis of donor funding aimed towards activities that support the health workforce in low- and middle-income countries from key agencies. The DAHRH estimates are disaggregated by source of funds, channel (disbursing agency) of funding, geographic region (Global Burden of Disease Study (GBD) super region), and the type of human resources for health activities supported (program areas).
The Global Burden of Disease Study 2019 (GBD 2019), 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.
A GBD 2019 analysis also produced estimates for health workforce densities for 204 countries and territories from 1990–2019. Data used come from WHO’s Global Health Observatory and cross-sectional surveys and censuses that sampled general working-age populations (defined as ages 15–69) in which respondents self-reported employment status and current occupation. Employment and occupation data were mapped to the International Standard Classification of Occupations (ISCO) 88. This dataset includes annual estimates by location for health workforce densities per 10,000 employed individuals for 23 health worker cadres.
For additional GBD results and resources, visit the GBD 2019 Data Resources page.
This dataset contains estimates of daily and cumulative infections with SARS-CoV-2 from the beginning of the pandemic through November 14, 2021, as well as estimates of cumulative COVID-19 deaths (adjusted for under-reporting) and estimates of the infection-detection ratio, infection-hospitalization ratio, and infection-fatality ratio. These are made available by day for 190 countries and territories – and subnational locations in 10 of those countries – aggregated into 21 regions and 7 super-regions and globally. Methods and limitations for the underlying models can be found in detail in the publication.
This dataset contains estimates of excess mortality from the COVID-19 pandemic for global populations during the period of January 1, 2020 – December 31, 2021. Excess mortality is defined as the net difference between the number of deaths during the pandemic (measured by observed or estimated all-cause mortality) and the number of deaths that would be expected based on past trends in all-cause mortality. The dataset also includes reported COVID-19 deaths (or deaths attributable to the virus), the reported COVID-19 mortality rate and the ratio between excess mortality rate and reported COVID-19 mortality rate for the same time period. The ratio of excess mortality rate to reported COVID-19 mortality is a measurement of undercounting of the true mortality impact of the pandemic. Methods and limitations for the model for estimating excess mortality can be found in detail in the publication.
Estimates were produced for target-age routine immunization (RI) coverage of 11 vaccines in 107 low- and middle-income countries (LMICs) between 2000–2020. 5x5 km level-coverage was estimated for six vaccines, and second administrative level-coverage was estimated for five vaccines. Coverage estimates were also produced for age-specific RI measles-containing vaccine first dose (MCV1) at the 5x5 km level and combined RI and supplemental immunization (RI plus SIA) MCV1 and second-dose measles (MCV2) at the second administrative level. Estimates were produced using data from household-based surveys.
This dataset includes the following:
- GeoTIFF raster files for pixel-level coverage estimates for vaccines estimated at the 5x5km level
- CSV files of aggregated coverage estimates at the first and second administrative levels for all vaccines
As part of an analysis on the effects of the COVID-19 pandemic on gender equality, researchers at IHME reviewed publicly available datasets with information related to: vaccine hesitancy and uptake; healthcare services; economic and work-related concerns; education; and safety at home and in the community. Estimates of the prevalence of impacts of the COVID-19 pandemic on the domains listed above were produced by gender and world region using data from 13 sources with sex- or gender- disaggregated data. One additional gender-invariant source was used in estimating vaccine uptake. This dataset provides the generated estimates by gender and seven world regions (North Africa and Middle East; Sub-Saharan Africa; Central Europe, Eastern Europe, and Central Asia; High-income; South Asia; Latin America and Caribbean; and Southeast Asia, East Asia, and Oceania). This dataset also provides estimates by month (March 2020 – September 2021), when available.
This dataset contains estimates of the COVID-19 infection-fatality ratio (IFR) for global populations during the period April 15, 2020 to January 1, 2021. IFR is defined as the probability of an individual dying from COVID-19 once infected with the SARS-CoV-2 virus. In these files, IFR is expressed as a percent: deaths divided by infections multiplied by 100. Location-specific estimates include 190 countries and territories, as well as subnational locations in 11 countries and territories. Specific time points for each location include April 15, 2020; July 15, 2020; October 15, 2020; and January 1, 2021. The age-specific IFR estimates are time-invariant and pool data from all locations with age-stratified data; only data from prior to vaccine introduction in each location was used for the age-specific estimates. The analytic process that produced these estimates accounted for several known biases, such as under-reporting of COVID-19 deaths and the waning sensitivity of SARS-CoV-2 antibody tests.
Researchers at IHME produced estimates for age-specific Healthcare Access and Quality (HAQ) indices for ten year intervals from 1990-2016. The US national age-specific HAQ scores were compared with high-income peers (Canada, Western Europe, High-Income Asia Pacific countries, and Australasia) in 1990, 2000, 2010, and 2016. Scores among US states were also analyzed for 2010 and 2016. The public use microdata sample of the American Community Survey was used to estimate insurance coverage and the median income per person by age and state.
This dataset contains national-level estimates of unadjusted and adjusted COVID-19 infections per capita and infection fatality ratio (IFR) between January 1, 2020 and September 30, 2021 for 177 countries. Cumulative COVID-19 infections per 1,000 population include both unadjusted estimates and estimates standardized for environmental seasonality (measured as the relative risk of pneumonia), population density, gross domestic product (GDP) per capita, proportion of the population living below 100 m, and a proxy for previous exposure to other betacoronaviruses. IFR per 1,000 infections include both unadjusted estimated and estimates standardized for the age distribution of the population, mean body-mass index (BMI), exposure to air pollution, smoking rates, the proxy for previous exposure to other betacoronaviruses, population density, age-standardized prevalence of chronic obstructive pulmonary disease and cancer, and GDP per capita.
(For U.S. Resiliency Data.)
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 21 Global Burden of Disease Study (GBD) regions and 7 super-regions 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 471 million individual records or isolates and 7,585 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.
The dataset contains predictions of the incremental cost-effectiveness ratios (ICERs) for the HPV vaccine in 195 countries. Predictions are based on meta-regression estimates of ICERs on three sets of independent variables (true variation measured by country characteristics, intervention characteristics, and bias variables). Data used in the meta-regression analysis are 613 ICERs from 75 studies in the Tufts University’s cost-effectiveness analysis registries, and additional extractions of ICERs for sensitivity analyses.
This dataset contains estimates for the number of persons with exposure to household incident pulmonary tuberculosis (TB) for 20 high-incidence TB countries in 2019 (as determined by Global Burden of Disease (GBD) Study 2019 estimates). Estimates were produced using pulmonary TB incidence from the GBD 2019 and location-specific household structure data from Demographic Health Surveys (DHS) and Integrated Public Use Microdata Series (IPUMs). Estimates include mean and 95% uncertainty intervals for both sexes disaggregated by age groups.
These estimates inform a paper published in EclinicalMedicine in November 2021 titled “Estimating the population at high risk for tuberculosis through household exposure in high-incidence countries: a model-based analysis.”
The COVID-19 Health Services Disruption Survey 2020 is a series of surveys developed to assess the level of disruption to a range of health services resulting from the COVID-19 pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease.
The IPSOS General Population COVID-19 Health Services Disruption Survey 2020 was conducted by IPSOS via telephone and online surveys in 14 countries. Respondents were individual members of the general population. Data were collected from 15,258 respondents. The survey focused on the level of disruption to the provision of general health services, including visits to medical providers and access to medication.
This survey was developed specifically to assess the change in levels of service delivery prior to, and immediately following, the onset of the COVID-19 global pandemic. Data generated from this survey are not intended to be used as an overall estimate of the level of health service delivery.
This dataset contains annual spending estimates on immunizations for 135 low- and middle-income countries (as determined by the World Bank) from 2000 through 2017. The estimates are disaggregated by spending source — government, out-of-pocket, prepaid private, and development assistance for immunization — and immunization component or activity: e.g., vaccine costs, delivery costs, and routine and supplementary immunizations. Data used to produce the estimates came from National Health Accounts, Joint Reporting Forms, comprehensive multi-year plans, databases from Gavi, the Vaccine Alliance, and the Institute for Health Metrics and Evaluation’s 2019 Development Assistance for Health Database. Estimates are reported in 2019 United States Dollars (USD).
These Emergency Department (ED) health spending estimates are part of the Disease Expenditure Project (DEX) at IHME, which produced estimates for US spending on health care according to 3 types of payers: public insurance (including Medicare, Medicaid, and other government programs), private insurance, and out-of-pocket payments. This dataset contains ED spending estimates by aggregate health category, age group, sex, and payer for 2006 through 2016. The underlying data set used to generate estimates was the National Emergency Department Sample (NEDS); the DEX data pipeline was also leveraged to include government budgets, insurance claims, facility records, household surveys, and official US records from 2006 through 2016 to produce the results.
Annual estimates were produced for anemia prevalence in women of reproductive age (15-49 years) at the 5x5 km-level for 82 low- and middle-income countries (LMICs) between 2000 and 2019. These estimates were produced using a geo-positioned dataset created from 218 household surveys. Countries and subnational units outside of these 82 LMICs were supplemented with GBD results.
This dataset includes the following:
- GeoTIFF raster files for pixel-level estimates of anemia prevalence in women of reproductive age (15-49 years) for 82 LMICs
- CSV files of aggregated for 195 countries at the national level, 82 LMICs plus GBD subnational locations at the first-level administrative divisions, and 82 LMICs at the second-level administrative divisions
- Code files used to generate the estimates
The Global Burden of Disease Study 2019 (GBD 2019), 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 contains air pollution exposure estimates for ozone pollution, ambient particulate matter pollution, and household air pollution by year for 1990 to 2019. Population-weighted exposure summary files are provided for all air pollution risk factors, and gridded exposure files are provided for ozone and ambient particulate matter pollution. Files with GBD 2019 location hierarchies and ISO3 codes are also included. Estimates of disease burden attributable to air pollution risks are available through the GBD Results Tool.
For additional GBD results and resources, visit the GBD 2019 Data Resources page.
Estimates of deaths due to police violence were produced for all ages by sex, state, and race/ethnicity for the United States between 1980 and 2019. Data from the USA National Vital Statistics System (NVSS) was compared to three non-governmental, open-source databases on police violence: Fatal Encounters, Mapping Police Violence, and The Counted. Data from all sources were extracted and standardized, and a network meta-regression used to quantify the rate of under-reporting within the USA NVSS. These rates were used to inform correction factors and provide adjusted mortality estimates.
The Global Burden of Disease Study 2019 (GBD 2019), 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.
Estimates of 15 dietary risks and the burden attributable to these were produced for 1990-2019. Files available in this record include estimates of the daily intake of the 15 GBD food groups (either in grams or percent energy) by year, sex, and 5-year age groups for age 25 and up, with an aggregated 25+ age group. Estimates of disease burden attributable to dietary risks are available through the GBD Results Tool.
For additional GBD results and resources, visit the GBD 2019 Data Resources page.
This dataset contains estimates for deaths and years of life lost (YLLs) attributable to non-optimal temperature exposure (including high temperature, low temperature, and the aggregate non-optimal temperature risk) for 204 countries, Global Burden of Disease Study (GBD) regions and super regions, and globally for the years 1990, 2010, and 2010. These estimates inform a paper published in The Lancet in August 2021 titled “Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study.”
This version of the Development Assistance for Health (DAH) Database includes estimates for 1990-2020, 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. New in 2021: this release of the DAH Database incorporated estimates for COVID-19.
To better understand the data and how to use it, please refer to the IHME DAH Database 2019 User Guide.
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 2020 purchasing-power parity-adjusted (PPP) dollars.
Development Assistance for Health (DAH) on COVID-19 produced estimates for 2020, 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, health focus areas, and program areas.
Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective health spending estimates for 1995-2018 for 204 countries and territories. They cover total health spending, health spending disaggregated by source into three domestic financing source categories, and development assistance for health (DAH). Domestic source data came primarily from the WHO’s Global Health Expenditure Database (GHED). DAH data came from diverse 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 2018-2050. Estimates are reported in constant 2020 United States dollars, constant 2020 purchasing 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 projected health spending estimates for 2019-2050 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 1995-2018 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 2020 US dollars, constant 2020 purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.
The Premise Child Health COVID-19 Health Services Disruption Survey 2021 is a follow-up series to the COVID-19 Health Services Disruption Survey 2020 series conducted in July 2020. These surveys were developed to assess the level of disruption to a range of health services resulting from the COVID-19 pandemic and subsequent government mandates and changes in behavior to mitigate the spread of the disease. Data generated from this survey is not intended to be used as an overall estimate of the level of health service delivery.
This survey was conducted in 51 countries using the smartphone-based Premise data collection platform. Respondents were 4,319 individual members of the general population ages 16-49 years who identified as women. The survey focused on the level of disruption to family planning and reproductive health services and changes in risk of gender-based violence
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