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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 retrospective national health spending estimates for 1995-2015 for 188 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. National health spending by source, including development assistance for health, was estimated based on a diverse set of data, including program reports, budget data, national estimates, and National Health Accounts. The resulting estimates were used to help produce prospective health spending estimates for 2016-2040. Results of the analysis were published in The Lancet in April 2018 in "Spending on health and HIV/AIDS: domestic health spending and development assistance in 188 countries, 1995-2015."

This version of the Development Assistance for Health (DAH) Database includes estimates for 1990-2017, 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 2017 are a program area disaggregation within the tuberculosis health focus area, and identification of DAH targeting pandemic preparedness, within the HSS/SWAps health focus area. Also new this year are the tracking of the United Arab Emirates as a source of funding and tracking Unitaid channel funding.

To understand the framework used to track DAH, users of the database should review IHME's Financing Global Health 2017 report and methods annex.

This survey was conducted as part of the Gavi Full Country Evaluation (FCE) project in Zambia. Gavi FCEs are prospective studies covering the period 2013-2016 that aim to assess the barriers to and drivers of immunization program performance. The Zambia FCE Health Facility Survey was conducted in 22 districts purposely selected to overlap with those where a baseline facility survey for the Access, Bottlenecks, Costs, and Equity (ABCE) Project in Zambia was performed. The districts provide a geographically and demographically representative sample of Zambia’s health system. For this survey, data on financing, staffing, facility procedures and guidelines, vaccine stocks, and supply delivery (including cold chain temperature measurements) were collected from a representative sample of 171 health facilities. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of immunization sessions.

IHME research produced estimates for age-standardized mortality rates by county from lower respiratory infections (LRIs), diarrheal diseases, HIV/AIDS, meningitis, hepatitis, and tuberculosis. The estimates were generated using de-identified death records from the National Center for Health Statistics (NCHS); population counts from the U.S. Census Bureau, NCHS, and the Human Mortality Database; the cause list from the Global Burden of Disease Study (GBD); and the application of small area estimation models. This dataset provides estimates for age-standardized mortality rates by cause and sex at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014. Also included are changes in rates during this period and counties with the highest and lowest mortality rates for each cause in 2014. Study results were published in JAMA in March 2018 in "Trends and patterns of differences in infectious disease mortality among US counties, 1980–2014."

The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Tamil Nadu are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, and other variables related to facility operations. In total, a nationally representative sample of 168 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.

The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Odisha are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, HIV/AIDS care, and other variables related to facility operations. In total, a nationally representative sample of 108 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.

The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Madhya Pradesh are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, vaccines, and other variables related to facility operations. In total, a nationally representative sample of 203 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.

The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Gujarat are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, vaccines, and other variables related to facility operations. In total, a nationally representative sample of 103 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.

The Access, Bottlenecks, Costs, and Equity (ABCE) project is a multipronged and multicountry research collaboration focused on understanding what drives and hinders health service provision. Two datasets resulting from the ABCE project in the Indian state of Andhra Pradesh (now Andhra Pradesh and Telangana) are available for download. This first contains results of a health facility survey which gathered information on services offered, expenditure, revenue, personnel by category, equipment, capacity, HIV/AIDS care, and other variables related to facility operations. In total, a nationally representative sample of 98 facilities were surveyed. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of facility resources. The second dataset includes information collected in patient exit interviews conducted after patients visited facilities in the ABCE sample.

IHME research produced estimates for age-standardized mortality rates by county from alcohol use disorders, drug use disorders, self-harm, and interpersonal violence. The estimates were generated using de-identified death records from the National Center for Health Statistics (NCHS); population counts from the U.S. Census Bureau, NCHS, and the Human Mortality Database; the cause list from the Global Burden of Disease Study (GBD); and the application of small area estimation models. This dataset provides estimates for age-standardized mortality rates by cause and sex at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014. Also included are changes in rates during this period and counties with the highest and lowest mortality rates for each cause in 2014. Study results were published in JAMA in March 2018 in "Trends and patterns of geographic variation in mortality from substance use disorders and intentional injuries among US counties, 1980–2014."

HealthRise is a collaborative multicountry initiative to implement and evaluate innovative community-based programs intended to improve heart disease and diabetes care in underserved communities. Conducted as part of HealthRise South Africa, this health facility survey was carried out at 86 facilities in Umgungundlovu district in KwaZulu-Natal province and Pixley ka Seme district in Northern Cape province. The survey was based on based on the WHO package of essential NCD interventions and South Africa’s Essential Medicine List and Standard Treatment Guidelines for Primary Health Care 2014. It was adapted from a questionnaire created for the Access, Bottlenecks, Costs, and Equity (ABCE) study. Data were collected about facility capacity, equipment availability, pharmaceutical and supply stocks, staffing, and services provided. The data were collected through computer-assisted personal interviews (CAPI).

Estimates were produced for under-5 stunting, wasting, and underweight prevalence at the 5x5 km-level in 51 countries in Africa between 2000-2015. These estimates were produced using individual-level height, weight, and age data for children under 5 and geographical locations from household survey series including the Demographic and Health Survey (DHS), Mulitple Indicator Cluster Survey (MICS), Living Standards Measurement Study (LSMS), and Core Welfare Indicators Questionnaire Survey (CWIQ). This dataset includes both GeoTIFF raster files for pixel-level estimates of under-5 stunting, wasting, and underweight prevalence, along with relative annualized rates of change for each, and CSV files of aggregated estimates for each country at the first and second administrative divisions.

Code files used to generate the estimates are available online.

Estimates were produced for average years of educational attainment for women of reproductive age (15-49), women ages 20-24, and equivalent male age groups at the 5x5 km-level in 51 countries in Africa between 2000-2015. Estimates were also generated for the disparity in years of attainment between males and females for the same ages and period. These estimates were produced using data on educational attainment and geographical locations from censuses, several household survey series, including the Demographic and Health Survey (DHS) and Multiple Indicator Cluster Survey (MICS), and other country‐specific surveys. This dataset includes both GeoTIFF raster files for pixel-level estimates of educational attainment and attainment disparity and CSV files of aggregated estimates for each country at the first and second administrative divisions.

Code files used to generate the estimates are available online.

The Child Growth Failure Visualization is an interactive data tool that shows levels and trends in growth failure at birth and in children under 5, both past and projected from 1990 to 2030. The tool also demonstrates how cases of child growth failure (stunting, wasting, and underweight) have changed due to contributing factors including population growth, Socio-demographic Index, and unsafe sanitation from 1990 to 2016 and 2000 to 2016.

This dataset contains the input data used to produce the estimates visualized by the tool. Each file includes information about how the input sources were used and relevant metadata about the sources as suggested in the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).

Estimates were produced for three stages underlying the potential of widespread epidemics for four viral hemorrhagic fevers (VHFs) in Africa: Ebola virus disease, Marburg virus disease, Lassa fever, and Crimean-Congo hemorrhagic fever. Stage 1, index case potential, assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, measures potential for secondary spread amongst humans within specific communities. Stage 3, epidemic potential, evaluates possible spread of local outbreaks nationally, regionally, and internationally. Estimates were generated at the second national administrative division (admin 2) level and as indices on a 0-10 scale, with 10 representing the worst outcome. This dataset includes these estimates in shapefiles and CSV files for admin 2 locations across Africa for each pathogen in each stage.

Estimates were produced for under‐5 mortality (the probability of death before reaching age 5) and neonatal mortality (probability of death within first month of life) for each pixel cell (approximately 5x5 kilometer (km)) in 46 countries in Africa for 1998-2002, 2003-2007, 2008-2012, and 2013-2017. These estimates were produced using data on child mortality and geographical locations from censuses and several household survey series, including the Demographic and Health Survey (DHS), Unicef Mulitple Indicator Cluster Survey (MICS), and other country‐specific surveys. This dataset includes both GeoTIFF raster files for pixel-level estimates of probability of death and CSV files of aggregated estimates for each country at the first and second administrative divisions.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Estimates for deaths, YLLs, YLDs, and DALYs attributable to 84 risk factors by age and sex as well as estimates for summary exposure values (SEVs) by risk are available from the GBD Results Tool for 1990-2016 (5-year intervals). This record contains select tables published in The Lancet in September 2017 in "Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016.".

For additional GBD results and resources, visit the GBD 2016 Data Resources page.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Estimates for disability-adjusted life years (DALYs) by cause, age, and sex and healthy life expectancy (HALE) by age and sex are available from the GBD Results Tool for 1990-2016. Select tables published in The Lancet in September 2017 in "Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available in this record.

For additional GBD results and resources, visit the GBD 2016 Data Resources page.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Estimates for incidence, prevalence, and years lived with disability (YLDs) are available from the GBD Results Tool. Estimates are available by age and sex for 328 causes for 1990-2016 (quinquennial). Select tables published in The Lancet in September 2017 in "Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available for download via the “Files” tab above.

For additional GBD results and resources, visit the GBD 2016 Data Resources page.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Cause-specific mortality estimates for deaths and years of life lost (YLLs) are available from the GBD Results Tool. Estimates are available by age and sex for 264 causes for 1990-2016. Select tables published in The Lancet in September 2017 in "Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available for download via the “Files” tab above.

For additional GBD results and resources, visit the GBD 2016 Data Resources page.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Estimates of life expectancy and all-cause mortality, including under-5 mortality, are available from the GBD Results Tool. Estimates are available by age, sex, and location for 1990-2016. Select tables published in The Lancet in September 2017 in "Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016” are also available for download via the “Files” tab above.

For additional GBD results and resources, visit the GBD 2016 Data Resources page.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors from 1990 to 2016.

The United Nations established, in September 2015, the Sustainable Development Goals (SDGs), which specify 17 universal goals, 169 targets, and 232 indicators leading up to 2030. Drawing from GBD 2016, this dataset provides estimates for 37 health-related SDG indicators for 188 countries from 1990 to 2016, as well as projections, based on past trends, from 2017 to 2030. These 37 SDG indicators were used to construct the health-related SDG index, a summary measure of overall performance across the health-related SDGs.

The results were published in The Lancet in September 2017 in "Measuring progress and projecting attainment based on past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016."

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Disability weights, which represent the magnitude of health loss associated with specific health outcomes, are used to calculate years lived with disability (YLD) for these outcomes in a given population. The weights are measured on a scale from 0 to 1, where 0 equals a state of full health and 1 equals death. This dataset provides disability weights for the 235 unique health states used to estimate nonfatal health outcomes for the GBD 2016 study. The data were published in The Lancet in September 2017 in "Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016."

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

This set of location hierarchy files contains the GBD 2016 reporting hierarchy for the full set of locations estimated for the study, including all subnational locations. It also includes the hierarchy for the set of locations for which results are available in the GBD Results Tool, and data visualizations such as GBD Compare, as of September 2017. (Please note that this latter hierarchy will change as results for additional subnational results are released.) These files files can help users aggregate GBD 2016 results by GBD super region and region, Socio-demographic Index (SDI) grouping, and other location levels.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. These tables contain International Classification of Diseases (ICD) codes, for both ICD-9 and ICD-10, mapped to GBD 2016 causes of death and nonfatal causes.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

This dataset provides population estimates by location, age, and sex for 1950-2016. Data sources used to produce these estimates include World Population Prospects: 2015 Revision, from the United Nations Population Division, and the WHO Human Mortality Database.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Developed by GBD researchers and used to help produce these estimates, the Socio-demographic Index (SDI) is a summary measure of a geography's socio-demographic development. It is based on average income per person, educational attainment, and total fertility rate (TFR). SDI contains an interpretable scale: zero represents the lowest income per capita, lowest educational attainment, and highest TFR observed across all GBD geographies from 1970 to 2016, and one represents the highest income per capita, highest educational attainment, and lowest TFR. This dataset provides tables with SDI values for all estimated GBD 2016 geographies for 1970–2016 and groupings by geography based on 2016 values.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

In GBD, an essential stage in the process for producing estimates for adult mortality rates (or 45q15, the probability of death between exact ages 15 and 60) involves assessing the completeness of adult death reporting from vital registration and censuses. In this evaluation, raw data points from vital registration and sample registration are adjusted using formal demographic techniques called death distribution methods (DDM) and then smoothed to generate full time-series estimates of adult death reporting completeness. This dataset contains a list of data input sources used in the generation of DDM estimates for adult mortality.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

This reference life table is used in GBD to calculate years of life lost (YLLs). It was constructed based on the lowest estimated age-specific mortality rates from all locations with populations over 5 million in the 2015 iteration of GBD. YLLs are computed by multiplying the number of estimated deaths by the reference life table’s life expectancy at age of death. The table includes estimates for the probability of death within an age range, the proportion of the hypothetical cohort still alive at age x, and life expectancy at age x for ages 0 to 110+ at five-year intervals.

The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.

Covariates, which are independent variables with a positive or negative relationship to GBD diseases and conditions, are used to inform the estimation process in all models of the GBD study. Types of covariates used include socioeconomic, demographic, health system access, climate, and food consumption. This dataset contains data for 565 covariates for 1980-2016 used in the GBD 2016 study. Please note that data for England is not included for some covariates.

Data files are available to download at this location.

Research by the Global Burden of Disease Health Financing Collaborator Network produced forecasted health spending estimates for 2015-2040 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. GDP and all-sector government spending were extracted for 1980–2015 and used with retrospective health spending estimates for 1995-2014 to forecast GDP, all-sector government spending, and health spending through 2040. Results of the study were published in The Lancet in April 2017 in "Future and potential spending on health 2015–40: government, prepaid private, out-of-pocket, and donor financing in 184 countries."

Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective national health spending estimates for 1995-2014 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. National health spending by source, including development assistance for health, was estimated based on a diverse set of data, including program reports, budget data, national estimates, and 964 National Health Accounts. The resulting estimates were used to help produce forecasted health spending estimates for 2015-2040. Results of the study were published in The Lancet in April 2017 in "Evolution and patterns of global health financing 1995–2014: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries."

This update of the Development Assistance for Health (DAH) Database includes estimates for 1990-2016, 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 funding agency, country and geographic region, and health focus area. New in 2016 is a program area disaggregation within malaria health focus areas.

To understand the framework used to track DAH, users of the DAH Database 1990-2016 should review IHME's Financing Global Health 2016 technical report and methods annex.

IHME research produced estimates on US health care spending by age, sex, condition, and type of care, from 1996 through 2013, for children and adolescents ages 19 years and younger. Government budgets, insurance claims, facility surveys, household surveys, and official US records for the period were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions. For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Study results were published in JAMA Pediatrics in December 2016 in “Spending on Children’s Personal Health Care in the United States, 1996-2013.”

IHME research produced estimates for US health care spending by age, sex, condition, and type of care from 1996 to 2013. Government budgets, insurance claims, facility surveys, household surveys, and official US records for the period were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions), and 38 age and sex groups. For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Study results were published in JAMA in December 2016 in “US Spending on Personal Health Care and Public Health, 1996-2013.”

This update of the Development Assistance for Health (DAH) Database includes estimates for 1990-2015, 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 developing countries from key agencies. The data are disaggregated by funding agency, country and geographic region, and health focus area. New in 2015 is a program area disaggregation within HIV/AIDS health focus areas.

To understand the framework used to track DAH, users of the DAH Database 1990-2015 should review IHME's Financing Global Health 2015 policy report and methods annex.

This 2014 update of the Development Assistance for Health (DAH) Database includes estimates for 1990-2014, 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 developing countries from key agencies. The data are disaggregated by funding agency, country and geographic region, and health focus area.

To understand the framework used to track DAH, users of the DAH Database 1990-2014 should review IHME's Financing Global Health 2014 policy report and methods annex.

An updated version of the database with DAH estimates through 2015 is now available.

These data capture the development assistance for health (DAH) provided to faith-based organizations (FBOs), as divided among FBO and non-FBO funding. The data available for download also show FBO DAH divided by health focus area as well as by funder, providing the FBO DAH furnished by the Global Fund and the Gates Foundation. These results were published in PLOS One in May 2015 in "Estimating the development assistance for health provided to faith-based organizations, 1990-2013."

IHME research produced alcohol use prevalence estimates (including estimates for any drinking, heavy drinking, and binge drinking) by county, year, and sex for 2002-2012. The data also include changes by percent for the period. The estimates were produced by applying small area models to data from the Behavioral Risk Factor Surveillance System (BRFSS). This dataset contains estimates for all states and counties, the District of Columbia, and the US as a whole, along with data on the 10 counties with the highest and lowest rates of any, heavy, and binge drinking by sex. Study results were published in the American Journal of Public Health in April 2015 in "Drinking patterns in US counties from 2002 to 2012."

This 2013 update of the Development Assistance for Health (DAH) database includes estimates for 1990-2011, 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 for health from sources of funding and channels of funding and for recipient countries/geographic regions in health focus areas. The data associated with previous versions of IHME's Financing Global Health report were presented as two databases, the DAH country and regional recipient level database, and the DAH database. This year, in an effort to make the data more accessible to researchers, these databases have been combined.

To understand the framework used to track DAH, we recommend that users of the DAH database 1990-2011 review IHME's Financing Global Health 2013 policy report and methods appendix.

The 2012 update of the Development Assistance for Health (DAH) database enables analysis of trends in disbursements on grants/loans from key agencies by funding agency, country/geographic region, and health focus area.

These DAH totals do not match those in the IHME DAH 1990-2010 database. This database only contains DAH allocable by country and/or region and does not contain DAH that could not be traced to a specific region or country.

The 1990-2008 database is available here, and the 1990-2009 database is available here.

This is the 2012 update of the Development Assistance for Health (DAH) database, which includes estimates based on project databases, financial statements, annual reports, IRS 990s, and correspondences with agencies.

It enables estimation of DAH envelope (disbursements and expenditures), trends in DAH (disbursements and expenditures) by global health institutions, and trends in DAH (disbursements and expenditures) by source of income. Also provided is a code file to generate figures based on the database.

The 1990-2008 database is available here, and the 1990-2009 database is available here.

This December 2011 updated database includes US-based non-governmental organizations' (NGOs) financial data from USAID VolAg report years 1992-2010 (covers fiscal years 1990-2008) with unique ID codes added. The VolAg reports can be found on the USAID website.

The 1990-2007 database is available here.

This is the December 2011 update of the Development Assistance for Health (DAH) database which includes estimates based on data project databases, financial statements, annual reports, IRS 990s, and correspondences with agencies.

It enables estimation of DAH envelope (disbursements and expenditures), trends in DAH (disbursements and expenditures) by global health institutions, and trends in DAH (disbursements and expenditures) by source of income.

The 1990-2008 database is available here.

The December 2011 update of the Development Assistance for Health (DAH) database enables analysis of trends in disbursements on grants/loans from key agencies by funding agency, country/geographic region, and health focus area.

These DAH totals do not match those in the IHME DAH 1990-2009 database. This database only contains DAH allocable by country/region.

The 1990-2008 database is available here.

This database includes US-based non-governmental organizations' (NGOs) financial data from USAID VolAg report years 1992-2009 (covers fiscal years 1990-2007) with unique ID codes added. The VolAg reports can be found on the USAID website.

2011 update available here.

This database includes Development Assistance for Health (DAH) project databases that enable analysis of trends in disbursements on grants and loans from key agencies by funding agency, country/geographic region, and health focus area.

Note: The DAH totals in this database do not match up with those in the IHME Development Assistance for Health Database 1990-2008 because this database only contains DAH allocable by country and/or region and does not contain DAH that could not be traced to a specific region or country.

2011 update available here.

These IHME results are from the paper, "Public financing of health in developing countries: a cross-national systematic analysis," published in The Lancet in April 2010. This dataset provides estimates on domestically financed government health expenditures in developing countries and development assistance for health (DAH) to governmental and non-governmental recipients from 1995 to 2006.

This database includes development assistance for health (DAH) estimates based on data project databases, financial statements, annual reports, IRS 990s, and correspondences with agencies.

It enables estimation of the DAH envelope (disbursements and expenditures), trends in by global health institutions, and trends in DAH by source of income.

Graphing and additional use information are available in the "IHME_DAH_DATABASE_1990_2008_CODE.txt" file.

2011 update available here.

IHME results, published in November 2010, provide a global assessment of trends in development assistance for health (DAH) from 1990 to 2008 and preliminary estimates for 2009 and 2010. The report, Financing Global Health 2010: Development Assistance and Country Spending in Economic Uncertainty, compiles contributions by all significant public and private channels of development assistance for improving health outcomes and strengthening health systems in low- and middle-income countries.

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