AndreaBozzo/ceres-open-data-index huggingface dataset:
500 Cities: Local Data for Better Health, 2016 release

This is the complete dataset for the 500 Cities project 2016 release. This dataset includes 2013, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2013, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2009-2013, 2010-2014 estimates. More information about the methodology can be found at www.cdc.gov/500cities. Note: During the process of uploading the 2015 estimates, CDC found a data discrepancy in the published 500 Cities data for the 2014 city-level obesity crude prevalence estimates caused when reformatting the SAS data file to the open data format. . The small area estimation model and code were correct. This data discrepancy only affected the 2014 city-level obesity crude prevalence estimates on the Socrata open data file, the GIS-friendly data file, and the 500 Cities online application. The other obesity estimates (city-level age-adjusted and tract-level) and the Mapbooks were not affected. No other measures were affected. The correct estimates are update in this dataset on October 25, 2017.
500 Cities: Local Data for Better Health, 2017 release

This is the complete dataset for the 500 Cities project 2017 release. This dataset includes 2015, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2015, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2011-2015, 2010-2014 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures from the 2014 BRFSS that are the same in the 2017 release as the previous 2016 release. More information about the methodology can be found at www.cdc.gov/500cities.
500 Cities: Local Data for Better Health, 2018 release

This is the complete dataset for the 500 Cities project 2018 release. This dataset includes 2016, 2015 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2016, 2015), Census Bureau 2010 census population data, and American Community Survey (ACS) 2012-2016, 2011-2015 estimates. Because some questions are only asked every other year in the BRFSS, there are 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, cholesterol screening) from the 2015 BRFSS that are the same in the 2018 release as the previous 2017 release. More information about the methodology can be found at www.cdc.gov/500cities.
500 Cities: Local Data for Better Health, 2019 release

This is the complete dataset for the 500 Cities project 2019 release. This dataset includes 2017, 2016 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2017, 2016), Census Bureau 2010 census population data, and American Community Survey (ACS) 2013-2017, 2012-2016 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures (all teeth lost, dental visits, mammograms, pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) from the 2016 BRFSS that are the same in the 2019 release as the previous 2018 release. More information about the methodology can be found at www.cdc.gov/500cities.
Active Bacterial Core surveillance (ABCs) Group A Streptococcus

ABCs is an ongoing surveillance program that began in 1997. [ABCs reports] describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year. The methods, [surveillance areas], and [laboratory isolate collection areas] have changed over time. Additionally, the way missing data are taken into account changed in 2010. It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method. Given these changes over time, trends should be interpreted with caution. * [Methodology] Find details about surveillance population, case determination, surveillance evaluation, and more. * [Reports and Findings] Get official interpretations from reports and publications created from ABCs data.
Active Bacterial Core surveillance (ABCs) Group B Streptococcus

ABCs is an ongoing surveillance program that began in 1997. [ABCs reports] describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year. The methods, [surveillance areas], and [laboratory isolate collection areas] have changed over time. Additionally, the way missing data are taken into account changed in 2010. It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method. Given these changes over time, trends should be interpreted with caution. * [Methodology] Find details about surveillance population, case determination, surveillance evaluation, and more. * [Reports and Findings] Get official interpretations from reports and publications created from ABCs data.
Active Bacterial Core surveillance (ABCs) Haemophilus influenzae

ABCs is an ongoing surveillance program that began in 1997. [ABCs reports] describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year. The methods, [surveillance areas], and [laboratory isolate collection areas] have changed over time. Additionally, the way missing data are taken into account changed in 2010. It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method. Given these changes over time, trends should be interpreted with caution. * [Methodology] Find details about surveillance population, case determination, surveillance evaluation, and more. * [Reports and Findings] Get official interpretations from reports and publications created from ABCs data.
Active Bacterial Core surveillance (ABCs) Neisseria meningitidis

ABCs is an ongoing surveillance program that began in 1997. [ABCs reports] describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year. The methods, [surveillance areas], and [laboratory isolate collection areas] have changed over time. Additionally, the way missing data are taken into account changed in 2010. It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method. Given these changes over time, trends should be interpreted with caution. * [Methodology] Find details about surveillance population, case determination, surveillance evaluation, and more. * [Reports and Findings] Get official interpretations from reports and publications created from ABCs data.
Active Bacterial Core surveillance (ABCs) Streptococcus pneumoniae

ABCs is an ongoing surveillance program that began in 1997. [ABCs reports] describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year. The methods, [surveillance areas], and [laboratory isolate collection areas] have changed over time. Additionally, the way missing data are taken into account changed in 2010. It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method. Given these changes over time, trends should be interpreted with caution. * [Methodology] Find details about surveillance population, case determination, surveillance evaluation, and more. * [Reports and Findings] Get official interpretations from reports and publications created from ABCs data.
AH Cumulative Provisional COVID-19 Deaths by Sex, Race, and Age from 1/1/2020 to 7/28/2020

Cumulative provisional counts of deaths sex, race/Hispanic origin, age group, and by select underlying causes of death. The dataset also includes provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death. Includes deaths that occurred between January 1, 2020 to July 28, 2020.
AH Cumulative Provisional Death Counts by Sex, Race, and Age from 1/1/2020 to 7/4/2020

Cumulative provisional counts of deaths sex, race/Hispanic origin, age group, and by select underlying causes of death. The dataset also includes provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death. Includes deaths that occurred between January 1, 2020 to July 4, 2020.
AH Monthly Provisional Counts of Deaths for Select Causes of Death by Age, and Race and Hispanic Origin

Provisional counts of deaths by the month the deaths occurred, by age group and race/ethnicity, for select underlying causes of death for 2020-2021. Final data is provided for 2019. The dataset also includes monthly provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death.
AH Monthly Provisional Counts of Deaths for Select Causes of Death by Sex, Age, and Race and Hispanic Origin

Provisional counts of deaths by the month the deaths occurred, by age group, sex, and race/ethnicity, for select underlying causes of death for 2020-2021. Final data are provided for 2019. The dataset also includes monthly provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death.
AH Provisional COVID-19 Death Counts by Week, Race, and Age, United States 2020-2023

Provisional deaths involving COVID-19 reported to NCHS by MMWR week, race and Hispanic origin, and age group. Deaths occurred in the United States. Age groups: 0-4, 5-11, 12-17, 18-29, 30-39, 40-49, 50-64, 65-74, and 75+ years
AH Provisional COVID-19 Deaths by Age, United States, Week 40 2020 through Week 39 2021

Provisional deaths involving coronavirus disease 2019 (COVID-19) reported to NCHS by age group among United States residents, from MMWR Week 40 2020 through MMWR Week 39 2021. Age groups: 0-4, 5-11, 12-15, 16-17, 18-24, 25-39, 40-49, 50-64, 65-74, and 75+ years
AH Provisional COVID-19 Deaths by HHS Region, Race, Age 65plus

Deaths involving coronavirus disease 2019 (COVID-19) reported to NCHS by time-period, HHS region, race and Hispanic origin, and age groups (<65, 65-74. 75-84, 85+, and 65+). United States death counts include the 50 states, plus the District of Columbia and New York City. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington.
AH Provisional COVID-19 Deaths by HHS Region, Race, and Age, 2015-2021

Provisional deaths involving coronavirus disease 2019 (COVID-19) and deaths from all causes reported to NCHS by week the death occurred, HHS region of occurrence, race and Hispanic origin, and age group (0-24, 25-64, 65+ years), from 2015-2021. United States death counts include the 50 states, plus the District of Columbia and New York City. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington.
AH Provisional COVID-19 Deaths by HHS Region, Race, and Age, 2015 to date

Deaths from all causes and deaths involving coronavirus disease 2019 (COVID-19) reported to NCHS by time-period, HHS region, race and Hispanic origin, and age group. United States death counts include the 50 states, plus the District of Columbia and New York City. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington.
AH Provisional COVID-19 Deaths by HHS Region, Race, and Age Group, 2020-2021

Provisional deaths involving coronavirus disease 2019 (COVID-19) reported to NCHS by time-period (week, month, year), HHS region, race and Hispanic origin, and age group (0-24, 25-64, 65+ years) for 2020-2021. United States death counts include the 50 states, plus the District of Columbia and New York City. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington.
AH Provisional COVID-19 Deaths by Hospital Referral Region

Provisional count of deaths involving coronavirus disease 2019 (COVID-19) in the United States by week of death and by hospital referral region (HRR). HRR is determined by county of occurrence. Weekly weighted counts of deaths from all causes and due to COVID-19 are provided by HRR overall and for decedents 65 years and older. The weighted counts by HRRs are based on published methods for aggregating county-level data to HRRs. More detail about aggregating to HRRs from counties can be found in the following: https://github.com/Dartmouth-DAC/covid-19-hrr-mapping https://dartmouthatlas.org/covid-19/hrr-mapping/
AH Quarterly Excess Deaths by State, Sex, Age, and Race

Quarterly data on the number of deaths from all causes by state (of occurrence), sex, age group, and race/Hispanic origin group for the United States. Counts of deaths in more recent time periods can be compared with counts from earlier years (2015-2019) to determine if the number is higher than expected. Annual and cumulative counts (from Quarter 2, 2020 through the most recent quarter) are also shown.
American Community Survey (ACS) – Vision and Eye Health Surveillance

2014 - 2022 (excluding 2020). This dataset is a de-identified summary table of vision and eye health data indicators from ACS, stratified by all available combinations of age group, race/ethnicity, sex, and state. ACS is an annual nationwide survey conducted by the U.S. Census Bureau that collects information on demographic, social, economic, and housing characteristics of the U.S. population. Approximate sample size is 3 million annually. ACS data for VEHSS includes one question related to Visual Function. Data were suppressed for cell sizes less than 30 persons, or where the relative standard error more than 30% of the mean. Data will be updated as it becomes available. Detailed information on VEHSS ACS analyses can be found on the VEHSS ACS webpage (link). Additional information about ACS can be found on the U.S. Census Bureau website (https://www.census.gov/content/dam/Census/programs-surveys/acs/about/ACS_Information_Guide.pdf). The VEHSS ACS dataset was last updated April 2024
American Rescue Plan (ARP) Rural Payments

The U.S. Department of Health and Human Services (HHS) via the Health Resources and Services Administration (HRSA) is releasing American Rescue Plan payments to providers and suppliers who have served rural Medicaid, Children's Health Insurance Program (CHIP), and Medicare beneficiaries from January 1, 2019 through September 30, 2020. The dataset will be updated as additional payments are released. Data does not reflect recipients’ attestation status, returned payments, or unclaimed funds.
Archive: COVID-19 LTC Program Vaccinations and Trends in the United States, Jurisdiction

The Federal Pharmacy Partnership for Long-Term Care (LTC) Program was a partnership between CDC and CVS, Walgreens, and Managed Health Care Associates, Inc. The program offered on-site COVID-19 vaccination services for residents of nursing homes and assisted living facilities. The Federal Pharmacy Partnership for LTC Program was in effect after vaccines became available to April 23, 2021. This is the historical archived data related to the LTC Program and represents data that was shown on COVID Data Tracker through September 30, 2021. Twelve variables that provided data on residents and staff vaccinated through the program were removed from the COVID-19 Vaccinations in the United States,Jurisdiction dataset. LTC was removed as an option from the location variable in the following datasets: COVID-19 Vaccinations in the United States,Jurisdiction and COVID-19 Vaccination Trends in the United States,National and Jurisdictional.
Archive: COVID-19 Vaccination and Case Trends by Age Group, United States

After October 13, 2022, this dataset will no longer be updated as the related CDC COVID Data Tracker site was retired on October 13, 2022. This dataset contains historical trends in vaccinations and cases by age group, at the US national level. Data is stratified by at least one dose and fully vaccinated. Data also represents all vaccine partners including jurisdictional partner clinics, retail pharmacies, long-term care facilities, dialysis centers, Federal Emergency Management Agency and Health Resources and Services Administration partner sites, and federal entity facilities.
Archive: COVID-19 Vaccination Demographic Trends by Report Date, National

This data dictionary provides information about archived demographic trend data for people receiving COVID-19 vaccinations in the United States at the national level. Data represents all vaccine partners including jurisdictional partner clinics, retail pharmacies, long-term care facilities, dialysis centers, Federal Emergency Management Agency and Health Resources and Services Administration partner sites, and federal entity facilities. These data have been archived to provide historical demographic trend data for COVID-19 vaccine recipients prior to CDC converting the Vaccination Demographic Trends site to using data based on the date of vaccine administration. Previously, the Vaccination Demographic Trends site presented trend data by the date the vaccination was reported to CDC.