100+ datasets found
  1. Death Profiles by County

    • data.ca.gov
    • data.chhs.ca.gov
    • +3more
    csv, zip
    Updated Jun 26, 2025
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    California Department of Public Health (2025). Death Profiles by County [Dataset]. https://data.ca.gov/dataset/death-profiles-by-county
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    csv, zipAvailable download formats
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

    The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

    The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

  2. Death Profiles by Leading Causes of Death

    • data.ca.gov
    • data.chhs.ca.gov
    • +3more
    web link, zip
    Updated Apr 22, 2025
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    California Department of Public Health (2025). Death Profiles by Leading Causes of Death [Dataset]. https://data.ca.gov/dataset/death-profiles-by-leading-causes-of-death
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    web link, zipAvailable download formats
    Dataset updated
    Apr 22, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data for deaths by leading cause of death categories are now available in the death profiles dataset for each geographic granularity.

    The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

    Cause of death categories for years 1999 and later are based on tenth revision of International Classification of Diseases (ICD-10) codes. Comparable categories are provided for years 1979 through 1998 based on ninth revision (ICD-9) codes. For more information on the comparability of cause of death classification between ICD revisions see Comparability of Cause-of-death Between ICD Revisions.

  3. M

    World Death Rate (1950-2025)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). World Death Rate (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/wld/world/death-rate
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    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - Dec 31, 2025
    Area covered
    World, World
    Description

    Historical chart and dataset showing World death rate by year from 1950 to 2025.

  4. Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Oct 19, 2021
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    CDC COVID-19 Response, Epidemiology Task Force (2021). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/3rge-nu2a
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    tsv, application/rssxml, csv, application/rdfxml, xml, jsonAvailable download formats
    Dataset updated
    Oct 19, 2021
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response, Epidemiology Task Force
    Description

    Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

    Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

    Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases among people who received additional or booster doses were reported from 31 jurisdictions; 30 jurisdictions also reported data on deaths among people who received one or more additional or booster dose; 28 jurisdictions reported cases among people who received two or more additional or booster doses; and 26 jurisdictions reported deaths among people who received two or more additional or booster doses. This list will be updated as more jurisdictions participate. Incidence rate estimates: Weekly age-specific incidence rates by vaccination status were calculated as the number of cases or deaths divided by the number of people vaccinated with a primary series, overall or with/without a booster dose (cumulative) or unvaccinated (obtained by subtracting the cumulative number of people vaccinated with a primary series and partially vaccinated people from the 2019 U.S. intercensal population estimates) and multiplied by 100,000. Overall incidence rates were age-standardized using the 2000 U.S. Census standard population. To estimate population counts for ages 6 months through 1 year, half of the single-year population counts for ages 0 through 1 year were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred. For the primary series analysis, age-standardized rates include ages 12 years and older from April 4, 2021 through December 4, 2021, ages 5 years and older from December 5, 2021 through July 30, 2022 and ages 6 months and older from July 31, 2022 onwards. For the booster dose analysis, age-standardized rates include ages 18 years and older from September 19, 2021 through December 25, 2021, ages 12 years and older from December 26, 2021, and ages 5 years and older from June 5, 2022 onwards. Small numbers could contribute to less precision when calculating death rates among some groups. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent incidence and death rates from growing unrealistically large due to potential overestimates of vaccination coverage. Incidence rate ratios (IRRs): IRRs for the past one month were calculated by dividing the average weekly incidence rates among unvaccinated people by that among people vaccinated with a primary series either overall or with a booster dose. Publications: Scobie HM, Johnson AG, Suthar AB, et al. Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021. MMWR Morb Mortal Wkly Rep 2021;70:1284–1290. Johnson AG, Amin AB, Ali AR, et al. COVID-19 Incidence and Death Rates Among Unvaccinated and Fully Vaccinated Adults with and Without Booster Doses During Periods of Delta and Omicron Variant Emergence — 25 U.S. Jurisdictions, April 4–December 25, 2021. MMWR Morb Mortal Wkly Rep 2022;71:132–138. Johnson AG, Linde L, Ali AR, et al. COVID-19 Incidence and Mortality Among Unvaccinated and Vaccinated Persons Aged ≥12 Years by Receipt of Bivalent Booster Doses and Time Since Vaccination — 24 U.S. Jurisdictions, October 3, 2021–December 24, 2022. MMWR Morb Mortal Wkly Rep 2023;72:145–152. Johnson AG, Linde L, Payne AB, et al. Notes from the Field: Comparison of COVID-19 Mortality Rates Among Adults Aged ≥65 Years Who Were Unvaccinated and Those Who Received a Bivalent Booster Dose Within the Preceding 6 Months — 20 U.S. Jurisdictions, September 18, 2022–April 1, 2023. MMWR Morb Mortal Wkly Rep 2023;72:667–669.

  5. d

    COVID-19-Associated Deaths by Date of Death - ARCHIVE

    • datasets.ai
    • data.ct.gov
    • +1more
    23, 40, 55, 8
    Updated Aug 27, 2024
    + more versions
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    State of Connecticut (2024). COVID-19-Associated Deaths by Date of Death - ARCHIVE [Dataset]. https://datasets.ai/datasets/covid-19-associated-deaths-by-date-of-death
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    8, 55, 40, 23Available download formats
    Dataset updated
    Aug 27, 2024
    Dataset authored and provided by
    State of Connecticut
    Description

    Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

    The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

    The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

    The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

    The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

    Count of COVID-19-associated deaths by date of death. Deaths reported to either the OCME or DPH are included in the COVID-19 data. COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death and persons who were not tested for COVID-19 whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death.

    Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics

    Note the counts in this dataset may vary from the death counts in the other COVID-19-related datasets published on data.ct.gov, where deaths are counted on the date reported rather than the date of death

  6. Deaths registered by single year of age, UK

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Jan 18, 2022
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    Office for National Statistics (2022). Deaths registered by single year of age, UK [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathregistrationssummarytablesenglandandwalesdeathsbysingleyearofagetables
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    xlsxAvailable download formats
    Dataset updated
    Jan 18, 2022
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Annual data on death registrations by single year of age for the UK (1974 onwards) and England and Wales (1963 onwards).

  7. Provisional COVID-19 death counts, rates, and percent of total deaths, by...

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Jun 27, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts, rates, and percent of total deaths, by jurisdiction of residence [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-rates-and-percent-of-total-deaths-by-jurisdiction-of-res
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    Dataset updated
    Jun 27, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. 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. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

  8. NCHS - Leading Causes of Death: United States

    • catalog.data.gov
    • healthdata.gov
    • +5more
    Updated Apr 23, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). NCHS - Leading Causes of Death: United States [Dataset]. https://catalog.data.gov/dataset/nchs-leading-causes-of-death-united-states
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    This dataset presents the age-adjusted death rates for the 10 leading causes of death in the United States beginning in 1999. Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia using demographic and medical characteristics. Age-adjusted death rates (per 100,000 population) are based on the 2000 U.S. standard population. Populations used for computing death rates after 2010 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for non-census years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Causes of death classified by the International Classification of Diseases, Tenth Revision (ICD–10) are ranked according to the number of deaths assigned to rankable causes. Cause of death statistics are based on the underlying cause of death. SOURCES CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Murphy SL, Xu JQ, Kochanek KD, Curtin SC, and Arias E. Deaths: Final data for 2015. National vital statistics reports; vol 66. no. 6. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_06.pdf.

  9. Provisional COVID-19 Death Counts by Age in Years, 2020-2023

    • catalog.data.gov
    • healthdata.gov
    • +3more
    Updated Apr 23, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 Death Counts by Age in Years, 2020-2023 [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-deaths-counts-by-age-in-years
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Effective June 28, 2023, this dataset will no longer be updated. Similar data are accessible from CDC WONDER (https://wonder.cdc.gov/mcd-icd10-provisional.html). Cumulative deaths involving COVID-19 reported to NCHS by sex and age in years, in the United States.

  10. C

    Death Profiles by ZIP Code

    • data.chhs.ca.gov
    • data.ca.gov
    • +2more
    csv, zip
    Updated Apr 22, 2025
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    California Department of Public Health (2025). Death Profiles by ZIP Code [Dataset]. https://data.chhs.ca.gov/dataset/death-profiles-by-zip-code
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    csv(80055974), csv(80054609), csv(78958555), csv(4571), csv(40627562), zipAvailable download formats
    Dataset updated
    Apr 22, 2025
    Dataset authored and provided by
    California Department of Public Health
    Description

    This dataset contains counts of deaths for California residents by ZIP Code based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths of California residents. The data tables include deaths of residents of California by ZIP Code of residence (by residence). The data are reported as totals, as well as stratified by age and gender. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

    The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

  11. D

    ARCHIVED: COVID-19 Deaths by Population Characteristics Over Time

    • data.sfgov.org
    application/rdfxml +5
    Updated Dec 28, 2022
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    (2022). ARCHIVED: COVID-19 Deaths by Population Characteristics Over Time [Dataset]. https://data.sfgov.org/COVID-19/ARCHIVED-COVID-19-Deaths-by-Population-Characteris/w6fd-iq9e
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    csv, tsv, application/rssxml, xml, json, application/rdfxmlAvailable download formats
    Dataset updated
    Dec 28, 2022
    Description

    A. SUMMARY This archived dataset includes data for population characteristics that are no longer being reported publicly. The date on which each population characteristic type was archived can be found in the field “data_loaded_at”.

    To access the dataset that continues to refresh daily, navigate to this page: COVID-19 Deaths by Population Characteristics Over Time.   The dataset contains data on the following population characteristics that are no longer being reported publicly:

    • Skilled Nursing Facility Occupancy
    • Sexual orientation
    • Comorbidities
    • Homelessness
    • Single room occupancy (SRO) tenancy
    • Transmission Type

    B. HOW THE DATASET IS CREATED COVID-19 deaths are suspected to be associated with COVID-19. This means COVID-19 is listed as a cause of death or significant condition on the death certificate.    Data on the population characteristics of COVID-19 deaths are from:  * Case interviews  * Laboratories  * Medical providers    These multiple streams of data are merged, deduplicated, and undergo data verification processes.      Skilled Nursing Facility (SNF) occupancy * A Skilled Nursing Facility (SNF) is a type of long-term care facility that provides care to individuals, generally in their 60s and older, who need functional assistance in their daily lives.  * This dataset includes data for COVID-19 deaths reported in Skilled Nursing Facilities (SNFs) through 12/31/2022, archived on 1/5/2023. These data were identified where “Characteristic_Type” = ‘Skilled Nursing Facility Occupancy’.

    Sexual orientation    * The City began asking adults 18 years old or older for their sexual orientation identification during case interviews as of April 28, 2020. Sexual orientation data prior to this date is unavailable. * The City doesn’t collect or report information about sexual orientation for persons under 12 years of age. * Case investigation interviews transitioned to Virtual Assistant information gathering starting December 2021. The California Department of Public Health, Virtual Assistant is only sent to adults who are 18+ years old. Learn more about our data collection guidelines pertaining to sexual orientation.

    Comorbidities * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death.

    Homelessness Persons are identified as homeless based on several data sources: * self-reported living situation * the location at the time of testing * Department of Public Health homelessness and health databases * Residents in Single-Room Occupancy hotels are not included in these figures. These methods serve as an estimate of persons experiencing homelessness. They may not meet other homelessness definitions.

    Single Room Occupancy (SRO) tenancy * SRO buildings are defined by the San Francisco Housing Code as having six or more "residential guest rooms" which may be attached to shared bathrooms, kitchens, and living spaces. * The details of a person's living arrangements are verified during case interviews.

    Transmission type * Information on transmission of COVID-19 is based on case interviews with individuals who have a confirmed positive test. Individuals are asked if they have been in close contact with a known COVID-19 case. If they answer yes, transmission category is recorded as contact with a known case. If they report no contact with a known case, transmission category is recorded as community transmission. If the case is not interviewed or was not asked the question, they are counted as unknown.

    C. UPDATE PROCESS This dataset will only update when any population characteristics are archived. Data for existing characteristic types will not change but new characteristic types may be added.   D. HOW TO USE THIS DATASET This dataset may include different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of deaths on each date.

    New deaths are the count of deaths within that characteristic group on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

    E. CHANGE LOG

    • 6/6/2023 - data on deaths by transmission type are no longer being updated. This data is currently through 6/1/2023 (as of 6/6/2023) and will not include any new data after this date.
    • 5/16/2023 - data on deaths by sexual orientation, comorbidities, homelessness, and single room occupancy are no longer being updated. This data is currently through 5/11/2023 (as of 5/16/2023) and will not include any new data after this date.
    • 1/5/2023 - data on SNF deaths are no longer being updated. SNF data is currently through 12/31/2022 (as of 1/5/2023) and will not include any new data after this date.

  12. NCHS - Drug Poisoning Mortality by State: United States

    • healthdata.gov
    • data.virginia.gov
    • +4more
    application/rdfxml +5
    Updated Feb 25, 2021
    + more versions
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    data.cdc.gov (2021). NCHS - Drug Poisoning Mortality by State: United States [Dataset]. https://healthdata.gov/dataset/NCHS-Drug-Poisoning-Mortality-by-State-United-Stat/tmia-ur83
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    csv, tsv, application/rdfxml, xml, application/rssxml, jsonAvailable download formats
    Dataset updated
    Feb 25, 2021
    Dataset provided by
    data.cdc.gov
    Area covered
    United States
    Description

    This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning.

    Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).

    Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published.

    Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances.

    REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.

    1. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.
  13. Death in the United States

    • kaggle.com
    zip
    Updated Aug 3, 2017
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    The citation is currently not available for this dataset.
    Explore at:
    zip(766333584 bytes)Available download formats
    Dataset updated
    Aug 3, 2017
    Dataset authored and provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    Every year the CDC releases the country’s most detailed report on death in the United States under the National Vital Statistics Systems. This mortality dataset is a record of every death in the country for 2005 through 2015, including detailed information about causes of death and the demographic background of the deceased.

    It's been said that "statistics are human beings with the tears wiped off." This is especially true with this dataset. Each death record represents somebody's loved one, often connected with a lifetime of memories and sometimes tragically too short.

    Putting the sensitive nature of the topic aside, analyzing mortality data is essential to understanding the complex circumstances of death across the country. The US Government uses this data to determine life expectancy and understand how death in the U.S. differs from the rest of the world. Whether you’re looking for macro trends or analyzing unique circumstances, we challenge you to use this dataset to find your own answers to one of life’s great mysteries.

    Overview

    This dataset is a collection of CSV files each containing one year's worth of data and paired JSON files containing the code mappings, plus an ICD 10 code set. The CSVs were reformatted from their original fixed-width file formats using information extracted from the CDC's PDF manuals using this script. Please note that this process may have introduced errors as the text extracted from the pdf is not a perfect match. If you have any questions or find errors in the preparation process, please leave a note in the forums. We hope to publish additional years of data using this method soon.

    A more detailed overview of the data can be found here. You'll find that the fields are consistent within this time window, but some of data codes change every few years. For example, the 113_cause_recode entry 069 only covers ICD codes (I10,I12) in 2005, but by 2015 it covers (I10,I12,I15). When I post data from years prior to 2005, expect some of the fields themselves to change as well.

    All data comes from the CDC’s National Vital Statistics Systems, with the exception of the Icd10Code, which are sourced from the World Health Organization.

    Project ideas

    • The CDC's mortality data was the basis of a widely publicized paper, by Anne Case and Nobel prize winner Angus Deaton, arguing that middle-aged whites are dying at elevated rates. One of the criticisms against the paper is that it failed to properly account for the exact ages within the broad bins available through the CDC's WONDER tool. What do these results look like with exact/not-binned age data?
    • Similarly, how sensitive are the mortality trends being discussed in the news to the choice of bin-widths?
    • As noted above, the data preparation process could have introduced errors. Can you find any discrepancies compared to the aggregate metrics on WONDER? If so, please let me know in the forums!
    • WONDER is cited in numerous economics, sociology, and public health research papers. Can you find any papers whose conclusions would be altered if they used the exact data available here rather than binned data from Wonder?

    Differences from the first version of the dataset

    • This version of the dataset was prepared in a completely different many. This has allowed us to provide a much larger volume of data and ensure that codes are available for every field.
    • We've replaced the batch of sql files with a single JSON per year. Kaggle's platform currently offer's better support for JSON files, and this keeps the number of files manageable.
    • A tutorial kernel providing a quick introduction to the new format is available here.
    • Lastly, I apologize if the transition has interrupted anyone's work! If need be, you can still download v1.
  14. Z

    Effect of suicide rates on life expectancy dataset

    • data.niaid.nih.gov
    • zenodo.org
    Updated Apr 16, 2021
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    Filip Zoubek (2021). Effect of suicide rates on life expectancy dataset [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4694269
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    Dataset updated
    Apr 16, 2021
    Dataset authored and provided by
    Filip Zoubek
    License

    Attribution-NonCommercial-ShareAlike 3.0 (CC BY-NC-SA 3.0)https://creativecommons.org/licenses/by-nc-sa/3.0/
    License information was derived automatically

    Description

    Effect of suicide rates on life expectancy dataset

    Abstract In 2015, approximately 55 million people died worldwide, of which 8 million committed suicide. In the USA, one of the main causes of death is the aforementioned suicide, therefore, this experiment is dealing with the question of how much suicide rates affects the statistics of average life expectancy. The experiment takes two datasets, one with the number of suicides and life expectancy in the second one and combine data into one dataset. Subsequently, I try to find any patterns and correlations among the variables and perform statistical test using simple regression to confirm my assumptions.

    Data

    The experiment uses two datasets - WHO Suicide Statistics[1] and WHO Life Expectancy[2], which were firstly appropriately preprocessed. The final merged dataset to the experiment has 13 variables, where country and year are used as index: Country, Year, Suicides number, Life expectancy, Adult Mortality, which is probability of dying between 15 and 60 years per 1000 population, Infant deaths, which is number of Infant Deaths per 1000 population, Alcohol, which is alcohol, recorded per capita (15+) consumption, Under-five deaths, which is number of under-five deaths per 1000 population, HIV/AIDS, which is deaths per 1 000 live births HIV/AIDS, GDP, which is Gross Domestic Product per capita, Population, Income composition of resources, which is Human Development Index in terms of income composition of resources, and Schooling, which is number of years of schooling.

    LICENSE

    THE EXPERIMENT USES TWO DATASET - WHO SUICIDE STATISTICS AND WHO LIFE EXPECTANCY, WHICH WERE COLLEECTED FROM WHO AND UNITED NATIONS WEBSITE. THEREFORE, ALL DATASETS ARE UNDER THE LICENSE ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 3.0 IGO (https://creativecommons.org/licenses/by-nc-sa/3.0/igo/).

    [1] https://www.kaggle.com/szamil/who-suicide-statistics

    [2] https://www.kaggle.com/kumarajarshi/life-expectancy-who

  15. NCHS - Death rates and life expectancy at birth

    • data.virginia.gov
    • healthdata.gov
    • +5more
    csv, json, rdf, xsl
    Updated Apr 21, 2025
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    Centers for Disease Control and Prevention (2025). NCHS - Death rates and life expectancy at birth [Dataset]. https://data.virginia.gov/dataset/nchs-death-rates-and-life-expectancy-at-birth
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    rdf, json, xsl, csvAvailable download formats
    Dataset updated
    Apr 21, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex.

    Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below).

    Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm.

    SOURCES

    CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov).

    REFERENCES

    1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm.

    2. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

    3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf.

    4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf.

    5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

  16. Deaths from All Causes - Datasets - Lincolnshire Open Data

    • lincolnshire.ckan.io
    Updated May 8, 2017
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    lincolnshire.ckan.io (2017). Deaths from All Causes - Datasets - Lincolnshire Open Data [Dataset]. https://lincolnshire.ckan.io/dataset/deaths-from-all-causes
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    Dataset updated
    May 8, 2017
    Dataset provided by
    CKANhttps://ckan.org/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    This data shows premature deaths (Age under 75), numbers and rates by gender, as 3-year moving-averages. All-Cause Mortality rates are a summary indicator of population health status. All-cause mortality is related to Life Expectancy, and both may be influenced by health inequalities. Directly Age-Standardised Rates (DASR) are shown in the data (where numbers are sufficient) so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates. A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death. Data source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator ID 108. This data is updated annually.

  17. Provisional COVID-19 death counts and rates by month, jurisdiction of...

    • data.virginia.gov
    • healthdata.gov
    • +3more
    csv, json, rdf, xsl
    Updated Jun 18, 2025
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts and rates by month, jurisdiction of residence, and demographic characteristics [Dataset]. https://data.virginia.gov/dataset/provisional-covid-19-death-counts-and-rates-by-month-jurisdiction-of-residence-and-demographic-
    Explore at:
    csv, rdf, json, xslAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia.

    Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file.

    Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death.

    Death counts should not be compared across jurisdictions. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly.

    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; 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.

    Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf).

    Rate are based on deaths occurring in the specified week and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly) rate prevailed for a full year.

    Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

  18. d

    Mass Killings in America, 2006 - present

    • data.world
    csv, zip
    Updated Jun 30, 2025
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    The Associated Press (2025). Mass Killings in America, 2006 - present [Dataset]. https://data.world/associatedpress/mass-killings-public
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    zip, csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 1, 2006 - Jun 26, 2025
    Area covered
    Description

    THIS DATASET WAS LAST UPDATED AT 2:11 AM EASTERN ON JUNE 30

    OVERVIEW

    2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

    In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

    A total of 229 people died in mass killings in 2019.

    The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

    One-third of the offenders died at the scene of the killing or soon after, half from suicides.

    About this Dataset

    The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

    The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

    This data will be updated periodically and can be used as an ongoing resource to help cover these events.

    Using this Dataset

    To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

    Mass killings by year

    Mass shootings by year

    To get these counts just for your state:

    Filter killings by state

    Definition of "mass murder"

    Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

    This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

    Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

    Methodology

    Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

    Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

    In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

    Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

    Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

    This project started at USA TODAY in 2012.

    Contacts

    Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

  19. 🌱Life Expectation

    • kaggle.com
    Updated Sep 7, 2023
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    meer atif magsi (2023). 🌱Life Expectation [Dataset]. https://www.kaggle.com/datasets/meeratif/life-expection/data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 7, 2023
    Dataset provided by
    Kaggle
    Authors
    meer atif magsi
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    The dataset contains information on various demographic and health indicators for different countries. It is organized into several columns, each providing essential information about these countries. Here's a description of each column:

    1. Country: This column represents the names of different countries or regions included in the dataset. Each row corresponds to a specific country or region, and this column serves as the identifier for each entry.

    2. Life Expectancy Males: This column contains data on the average life expectancy of males in each of the listed countries. Life expectancy is a crucial health indicator and provides an estimate of the average number of years a male can expect to live, given current mortality rates and health conditions.

    3. Life Expectancy Females: Similar to the "Life Expectancy Males" column, this column provides data on the average life expectancy of females in the same countries. It reflects the average number of years a female can expect to live, considering the prevailing health and mortality conditions.

    4. Birth Rate: The "Birth Rate" column contains information about the birth rate in each country. Birth rate is a demographic indicator that represents the number of live births per 1,000 people in a given population over a specific period, usually a year. It can provide insights into a country's population growth or decline.

    5. Death Rate: This column presents data on the death rate in each of the listed countries. The death rate is another crucial demographic indicator and represents the number of deaths per 1,000 people in a population over a specific period, often a year. It helps gauge the overall health and mortality conditions within a country.

  20. d

    Johns Hopkins COVID-19 Case Tracker

    • data.world
    csv, zip
    Updated Jul 2, 2025
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    The Associated Press (2025). Johns Hopkins COVID-19 Case Tracker [Dataset]. https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Jul 2, 2025
    Authors
    The Associated Press
    Description

    Updates

    • Notice of data discontinuation: Since the start of the pandemic, AP has reported case and death counts from data provided by Johns Hopkins University. Johns Hopkins University has announced that they will stop their daily data collection efforts after March 10. As Johns Hopkins stops providing data, the AP will also stop collecting daily numbers for COVID cases and deaths. The HHS and CDC now collect and visualize key metrics for the pandemic. AP advises using those resources when reporting on the pandemic going forward.

    • April 9, 2020

      • The population estimate data for New York County, NY has been updated to include all five New York City counties (Kings County, Queens County, Bronx County, Richmond County and New York County). This has been done to match the Johns Hopkins COVID-19 data, which aggregates counts for the five New York City counties to New York County.
    • April 20, 2020

      • Johns Hopkins death totals in the US now include confirmed and probable deaths in accordance with CDC guidelines as of April 14. One significant result of this change was an increase of more than 3,700 deaths in the New York City count. This change will likely result in increases for death counts elsewhere as well. The AP does not alter the Johns Hopkins source data, so probable deaths are included in this dataset as well.
    • April 29, 2020

      • The AP is now providing timeseries data for counts of COVID-19 cases and deaths. The raw counts are provided here unaltered, along with a population column with Census ACS-5 estimates and calculated daily case and death rates per 100,000 people. Please read the updated caveats section for more information.
    • September 1st, 2020

      • Johns Hopkins is now providing counts for the five New York City counties individually.
    • February 12, 2021

      • The Ohio Department of Health recently announced that as many as 4,000 COVID-19 deaths may have been underreported through the state’s reporting system, and that the "daily reported death counts will be high for a two to three-day period."
      • Because deaths data will be anomalous for consecutive days, we have chosen to freeze Ohio's rolling average for daily deaths at the last valid measure until Johns Hopkins is able to back-distribute the data. The raw daily death counts, as reported by Johns Hopkins and including the backlogged death data, will still be present in the new_deaths column.
    • February 16, 2021

      - Johns Hopkins has reconciled Ohio's historical deaths data with the state.

      Overview

    The AP is using data collected by the Johns Hopkins University Center for Systems Science and Engineering as our source for outbreak caseloads and death counts for the United States and globally.

    The Hopkins data is available at the county level in the United States. The AP has paired this data with population figures and county rural/urban designations, and has calculated caseload and death rates per 100,000 people. Be aware that caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.

    This data is from the Hopkins dashboard that is updated regularly throughout the day. Like all organizations dealing with data, Hopkins is constantly refining and cleaning up their feed, so there may be brief moments where data does not appear correctly. At this link, you’ll find the Hopkins daily data reports, and a clean version of their feed.

    The AP is updating this dataset hourly at 45 minutes past the hour.

    To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

    Queries

    Use AP's queries to filter the data or to join to other datasets we've made available to help cover the coronavirus pandemic

    Interactive

    The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.

    @(https://datawrapper.dwcdn.net/nRyaf/15/)

    Interactive Embed Code

    <iframe title="USA counties (2018) choropleth map Mapping COVID-19 cases by county" aria-describedby="" id="datawrapper-chart-nRyaf" src="https://datawrapper.dwcdn.net/nRyaf/10/" scrolling="no" frameborder="0" style="width: 0; min-width: 100% !important;" height="400"></iframe><script type="text/javascript">(function() {'use strict';window.addEventListener('message', function(event) {if (typeof event.data['datawrapper-height'] !== 'undefined') {for (var chartId in event.data['datawrapper-height']) {var iframe = document.getElementById('datawrapper-chart-' + chartId) || document.querySelector("iframe[src*='" + chartId + "']");if (!iframe) {continue;}iframe.style.height = event.data['datawrapper-height'][chartId] + 'px';}}});})();</script>
    

    Caveats

    • This data represents the number of cases and deaths reported by each state and has been collected by Johns Hopkins from a number of sources cited on their website.
    • In some cases, deaths or cases of people who've crossed state lines -- either to receive treatment or because they became sick and couldn't return home while traveling -- are reported in a state they aren't currently in, because of state reporting rules.
    • In some states, there are a number of cases not assigned to a specific county -- for those cases, the county name is "unassigned to a single county"
    • This data should be credited to Johns Hopkins University's COVID-19 tracking project. The AP is simply making it available here for ease of use for reporters and members.
    • Caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.
    • Population estimates at the county level are drawn from 2014-18 5-year estimates from the American Community Survey.
    • The Urban/Rural classification scheme is from the Center for Disease Control and Preventions's National Center for Health Statistics. It puts each county into one of six categories -- from Large Central Metro to Non-Core -- according to population and other characteristics. More details about the classifications can be found here.

    Johns Hopkins timeseries data - Johns Hopkins pulls data regularly to update their dashboard. Once a day, around 8pm EDT, Johns Hopkins adds the counts for all areas they cover to the timeseries file. These counts are snapshots of the latest cumulative counts provided by the source on that day. This can lead to inconsistencies if a source updates their historical data for accuracy, either increasing or decreasing the latest cumulative count. - Johns Hopkins periodically edits their historical timeseries data for accuracy. They provide a file documenting all errors in their timeseries files that they have identified and fixed here

    Attribution

    This data should be credited to Johns Hopkins University COVID-19 tracking project

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California Department of Public Health (2025). Death Profiles by County [Dataset]. https://data.ca.gov/dataset/death-profiles-by-county
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Death Profiles by County

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2 scholarly articles cite this dataset (View in Google Scholar)
csv, zipAvailable download formats
Dataset updated
Jun 26, 2025
Dataset authored and provided by
California Department of Public Healthhttps://www.cdph.ca.gov/
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

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