100+ datasets found
  1. Deaths by vaccination status, England

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Aug 25, 2023
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    Office for National Statistics (2023). Deaths by vaccination status, England [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsbyvaccinationstatusengland
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    xlsxAvailable download formats
    Dataset updated
    Aug 25, 2023
    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

    Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

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

    • healthdata.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Jun 16, 2023
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    data.cdc.gov (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status and Second Booster Dose [Dataset]. https://healthdata.gov/dataset/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/4tut-jeki
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    xml, json, csv, tsv, application/rdfxml, application/rssxmlAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    data.cdc.gov
    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

  3. Statewide Death Profiles

    • data.chhs.ca.gov
    • data.ca.gov
    • +1more
    csv, zip
    Updated Mar 25, 2025
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    California Department of Public Health (2025). Statewide Death Profiles [Dataset]. https://data.chhs.ca.gov/dataset/statewide-death-profiles
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    csv(463460), csv(164006), csv(4689434), zip, csv(16301), csv(200270), csv(5034), csv(2026589), csv(5401561), csv(419332), csv(300479)Available download formats
    Dataset updated
    Mar 25, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    This dataset contains counts of deaths for California as a whole 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 California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California 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.

  4. U

    United States Excess Deaths excl COVID: Predicted: Above Expected: Florida

    • ceicdata.com
    Updated Nov 27, 2021
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    CEICdata.com (2021). United States Excess Deaths excl COVID: Predicted: Above Expected: Florida [Dataset]. https://www.ceicdata.com/en/united-states/number-of-excess-deaths-by-states-all-causes-excluding-covid19-predicted/excess-deaths-excl-covid-predicted-above-expected-florida
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    Dataset updated
    Nov 27, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Aug 14, 2021 - Oct 30, 2021
    Area covered
    United States
    Variables measured
    Vital Statistics
    Description

    United States Excess Deaths excl COVID: Predicted: Above Expected: Florida data was reported at 0.000 Number in 30 Oct 2021. This stayed constant from the previous number of 0.000 Number for 23 Oct 2021. United States Excess Deaths excl COVID: Predicted: Above Expected: Florida data is updated weekly, averaging 0.000 Number from Jan 2017 (Median) to 30 Oct 2021, with 251 observations. The data reached an all-time high of 729.000 Number in 21 Aug 2021 and a record low of 0.000 Number in 30 Oct 2021. United States Excess Deaths excl COVID: Predicted: Above Expected: Florida data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G012: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted (Discontinued).

  5. Deaths, by marital status

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +1more
    Updated Feb 19, 2025
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    Government of Canada, Statistics Canada (2025). Deaths, by marital status [Dataset]. http://doi.org/10.25318/1310071101-eng
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    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number of deaths, by marital status, age group, sex, and place of residence, 1991 to most recent year.

  6. Coronavirus (COVID-19) deaths per day compared to all causes U.S. 2022

    • statista.com
    Updated Jul 27, 2022
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    Statista (2022). Coronavirus (COVID-19) deaths per day compared to all causes U.S. 2022 [Dataset]. https://www.statista.com/statistics/1109281/covid-19-daily-deaths-compared-to-all-causes/
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    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of January 6, 2022, an average of 1,192 people per day have died from COVID-19 in the U.S. since the first case was confirmed in the country on January 20th the year before. On an average day, nearly 8,000 people die from all causes in the United States, based on data from 2019. Based on the latest information, roughly one in seven deaths each day were related to COVID-19 between January 2020 and January 2022. However, there were even days when more than every second death in the U.S. was connected to COVID-19. The daily death toll from the seasonal flu, using preliminary maximum estimates from the 2019-2020 influenza season, stood at an average of around 332 people. We have to keep in mind that a comparison of influenza and COVID-19 is somewhat difficult. COVID-19 cases and deaths are counted continuously since the begin of the pandemic, whereas flue counts are seasonal and often less accurate. Furthermore, during the last two years, COVID-19 more or less 'replaced' the flu, with COVID-19 absorbing potential flu cases. Many countries reported a very weak seasonal flu activity during the COVID-19 pandemic. But it has yet to be seen how the two infectious diseases will develop side by side during the winter season 2021/2022 and in the years to come.

    Symptoms and self-isolation COVID-19 and influenza share similar symptoms – a cough, runny nose, and tiredness – and telling the difference between the two can be difficult. If you have minor symptoms, there is no need to seek urgent medical care, but it is recommended that you self-isolate, whereas rules vary from country to country. Additionally, rules depend on someone's vaccination status and infection history. However, if you think you have the disease, a diagnostic test can show if you have an active infection.

    Scientists alert to coronavirus mutations The genetic material of the novel coronavirus is RNA, not DNA. Other notable human diseases caused by RNA viruses include SARS, Ebola, and influenza. A continual problem that vaccine developers encounter is that viruses can mutate, and a treatment developed against a certain virus type may not work on a mutated form. The seasonal flu vaccine, for example, is different each year because influenza viruses are frequently mutating, and it is critical that those genetic changes continue to be tracked.

  7. Death rates for all causes among U.S. adults in 2010 and 2019, by marital...

    • statista.com
    Updated Oct 13, 2021
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    Statista (2021). Death rates for all causes among U.S. adults in 2010 and 2019, by marital status [Dataset]. https://www.statista.com/statistics/1269128/death-rates-us-by-marital-status/
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    Dataset updated
    Oct 13, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2019, the death rate for all causes among married individuals in the U.S. was around 747 deaths per 100,000 population. In comparison, the death rate among those who were never married was around 1,423 per 100,000 population. This statistic depicts death rates for all causes among adults aged 25 years and older in the United States in 2010 and 2019, by marital status.

  8. Deaths Involving COVID-19 by Vaccination Status

    • ouvert.canada.ca
    • datasets.ai
    • +4more
    csv, docx, xlsx
    Updated Jan 22, 2025
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    Government of Ontario (2025). Deaths Involving COVID-19 by Vaccination Status [Dataset]. https://ouvert.canada.ca/data/dataset/1375bb00-6454-4d3e-a723-4ae9e849d655
    Explore at:
    xlsx, docx, csvAvailable download formats
    Dataset updated
    Jan 22, 2025
    Dataset provided by
    Government of Ontariohttps://www.ontario.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Mar 1, 2021 - Nov 12, 2024
    Description

    This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

  9. D

    Deaths by medical end-of-life decision; age, cause of death

    • staging.dexes.eu
    • ckan.mobidatalab.eu
    • +3more
    atom, json
    Updated Mar 26, 2025
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    Centraal Bureau voor de Statistiek (2025). Deaths by medical end-of-life decision; age, cause of death [Dataset]. https://staging.dexes.eu/en/dataset/deaths-by-medical-end-of-life-decision-age-cause-of-death
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    atom, jsonAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset authored and provided by
    Centraal Bureau voor de Statistiek
    License

    https://opendata.cbs.nl/ODataApi/OData/81655ENGhttps://opendata.cbs.nl/ODataApi/OData/81655ENG

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

    Description

    The survey of medical end-of-life decisions presents information on medical end-of-life decisions by attending physicians. For this survey, a random sample is taken from death certificates at Statistics Netherlands on persons listed in the Dutch population register who died in the months August to November inclusive of the survey year. The sample is raised to an annual figure. This table concerns deaths by medical end-of-life decisions, cause of death and age. Data available from: 2010, 2015 and 2021 Status of the figures: All data are definite. Changes as of 26 May 2023: - Figures for 2021 have been added. - In 2021, there were 96 deceased persons with unknown 'medical end-of-life'. These were only added to the total. The underlying numbers therefore do not add up to the total. When will new figures be published? The survey takes place every five years. In 2020, the survey was postponed by one year due to the high workload in the healthcare sector on account of COVID-19. As a result, there is a one-off six-year interval between 2015 and 2021.

  10. d

    Registered Deaths (15 Years Old and Over) By Marital Status, Age Group and...

    • data.gov.qa
    • data.qa
    csv, excel, json
    Updated Jun 21, 2020
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    (2020). Registered Deaths (15 Years Old and Over) By Marital Status, Age Group and Gender (Total) [Dataset]. https://www.data.gov.qa/explore/dataset/registered-deaths-15-years-old-and-over-by-marital-status-age-group-and-gender-1/
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    excel, csv, jsonAvailable download formats
    Dataset updated
    Jun 21, 2020
    License

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

    Description

    Mortality and morbidity rate and its distribution, as reflected by age and gender structures and geographical distribution, are essential data for the setting up of economic and social development plans.This statistic contains an estimate of the total registered death rates (15 years old and over) by marital status, age group and gender in 2016.

  11. d

    Registered Deaths (15 Years Old and Over) by Marital Status, Age Group and...

    • data.gov.qa
    • data.qa
    csv, excel, json
    Updated Jun 20, 2020
    + more versions
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    Registered Deaths (15 Years Old and Over) by Marital Status, Age Group and Gender (Qataris) [Dataset]. https://www.data.gov.qa/explore/dataset/registered-deaths-15-years-old-and-over-by-marital-status-age-group-and-gender-0/
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    json, excel, csvAvailable download formats
    Dataset updated
    Jun 20, 2020
    License

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

    Area covered
    Qatar
    Description

    Mortality and morbidity rate and its distribution, as reflected by age and gender structures and geographical distribution, are essential data for the setting up of economic and social development plans.This statistic contains an estimate of registered death rates of Qataris (15 years old and over) by marital status, age group and gender 2016.

  12. n

    National Longitudinal Mortality Study

    • neuinfo.org
    • rrid.site
    • +2more
    Updated Mar 7, 2025
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    (2025). National Longitudinal Mortality Study [Dataset]. http://identifiers.org/RRID:SCR_008946
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    Dataset updated
    Mar 7, 2025
    Description

    A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

  13. d

    The number of deaths by marital status

    • data.gov.tw
    csv
    Updated Jan 23, 2025
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    Dept. of Statistics (2025). The number of deaths by marital status [Dataset]. https://data.gov.tw/en/datasets/14237
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    csvAvailable download formats
    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Dept. of Statistics
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    The number of deaths by marital status (data starting time: 85 years)

  14. C

    Death Profiles by County

    • data.chhs.ca.gov
    • data.ca.gov
    • +2more
    csv, zip
    Updated Feb 27, 2025
    + more versions
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    California Department of Public Health (2025). Death Profiles by County [Dataset]. https://data.chhs.ca.gov/dataset/death-profiles-by-county
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    csv(11738570), csv(15127221), csv(1128641), csv(60023260), csv(60201673), csv(17520989), zip, csv(74497014), csv(60676655), csv(60517511), csv(73906266), csv(74689382), csv(52019564), csv(51592721), csv(28125832), csv(24235858), csv(75015194), csv(74043128), csv(5095), csv(74351424)Available download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    California Department of Public Health
    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.

  15. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    Updated Nov 25, 2024
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    Statista (2024). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
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    Dataset updated
    Nov 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    The difficulties of death figures

    This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

  16. e

    Deaths per day reported to the Civil State

    • data.europa.eu
    csv, pdf
    + more versions
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    Commune de Saint-Paul-lès-Dax, Deaths per day reported to the Civil State [Dataset]. https://data.europa.eu/data/datasets/5c9a516c8b4c4175a7996257
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    csv(30761), pdf(50177)Available download formats
    Dataset authored and provided by
    Commune de Saint-Paul-lès-Dax
    License

    https://www.etalab.gouv.fr/licence-ouverte-open-licencehttps://www.etalab.gouv.fr/licence-ouverte-open-licence

    Description

    This dataset draws up an annual list of the days on which deaths were reported to the civil status of the city of Saint-Paul-lès-Dax. It consists of a list of days with the number of deaths for each given day. These data are derived from the register of civil status.

    “'” Themes: Administration and public action Key words: Death, Civil Status, Day, Statistics Updated data: Annual “'”

  17. U

    United States Excess Deaths: Above Expected: Alabama

    • ceicdata.com
    Updated Mar 15, 2023
    + more versions
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    CEICdata.com (2023). United States Excess Deaths: Above Expected: Alabama [Dataset]. https://www.ceicdata.com/en/united-states/number-of-excess-deaths-by-states-all-causes/excess-deaths-above-expected-alabama
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    Dataset updated
    Mar 15, 2023
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Aug 14, 2021 - Oct 30, 2021
    Area covered
    United States
    Variables measured
    Vital Statistics
    Description

    United States Excess Deaths: Above Expected: Alabama data was reported at 0.000 Number in 30 Oct 2021. This stayed constant from the previous number of 0.000 Number for 23 Oct 2021. United States Excess Deaths: Above Expected: Alabama data is updated weekly, averaging 0.000 Number from Jan 2017 (Median) to 30 Oct 2021, with 251 observations. The data reached an all-time high of 679.000 Number in 11 Sep 2021 and a record low of 0.000 Number in 30 Oct 2021. United States Excess Deaths: Above Expected: Alabama data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G010: Number of Excess Deaths: by States: All Causes (Discontinued).

  18. U

    United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine

    • ceicdata.com
    Updated Mar 9, 2021
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    CEICdata.com (2021). United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine [Dataset]. https://www.ceicdata.com/en/united-states/number-of-excess-deaths-by-states-all-causes-excluding-covid19-predicted/excess-deaths-excl-covid-predicted-avg-no-of-deaths-maine
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    Dataset updated
    Mar 9, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Oct 23, 2021 - Jan 8, 2022
    Area covered
    United States
    Variables measured
    Vital Statistics
    Description

    United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine data was reported at 313.000 Number in 08 Jan 2022. This stayed constant from the previous number of 313.000 Number for 01 Jan 2022. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine data is updated weekly, averaging 291.500 Number from Jan 2017 to 08 Jan 2022, with 262 observations. The data reached an all-time high of 317.000 Number in 16 Mar 2019 and a record low of 266.000 Number in 18 Aug 2018. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Maine data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G014: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted.

  19. Updated estimates of coronavirus (COVID-19) related deaths by disability...

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated May 9, 2022
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    Office for National Statistics (2022). Updated estimates of coronavirus (COVID-19) related deaths by disability status, England [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/updatedestimatesofcoronaviruscovid19relateddeathsbydisabilitystatusengland
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    xlsxAvailable download formats
    Dataset updated
    May 9, 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

    Estimates of differences in coronavirus (COVID-19) mortality risk by self-reported disability status for deaths occurring up to 9 March 2022, using linked data from the Office for National Statistics’ Public Health Data Asset.

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

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Jul 20, 2023
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    Centers for Disease Control and Prevention (2023). Rates of COVID-19 Cases or Deaths by Age Group and Vaccination Status [Dataset]. https://data.virginia.gov/dataset/rates-of-covid-19-cases-or-deaths-by-age-group-and-vaccination-status
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    xsl, csv, rdf, jsonAvailable download formats
    Dataset updated
    Jul 20, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    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

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Office for National Statistics (2023). Deaths by vaccination status, England [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsbyvaccinationstatusengland
Organization logo

Deaths by vaccination status, England

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26 scholarly articles cite this dataset (View in Google Scholar)
xlsxAvailable download formats
Dataset updated
Aug 25, 2023
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

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

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