100+ datasets found
  1. 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.

  2. Leading causes of death in the U.S. Mar. 2020-Sep. 2022

    • statista.com
    Updated May 15, 2024
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    Statista (2024). Leading causes of death in the U.S. Mar. 2020-Sep. 2022 [Dataset]. https://www.statista.com/statistics/1254560/leading-causes-of-death-in-the-us-average-number-daily/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2020 - Sep 2022
    Area covered
    United States
    Description

    During the months December 2020, January 2021, and February 2021, COVID-19 was the leading cause of death in the United States based on the average number of daily deaths. Heart disease and cancer are usually the number one and number two leading causes of death, respectively. This statistic shows the average number of daily deaths in the United States among the leading causes of death from March 2020 to September 2022.

  3. d

    COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates -...

    • catalog.data.gov
    • data.cityofchicago.org
    Updated May 24, 2024
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    data.cityofchicago.org (2024). COVID-19 Daily Rolling Average Case, Death, and Hospitalization Rates - Historical [Dataset]. https://catalog.data.gov/dataset/covid-19-daily-rolling-average-case-and-death-rates
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    Dataset updated
    May 24, 2024
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset has been retired and marked as historical-only. This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data. All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns. Only Chicago residents are included based on the home address as provided by the medical provider. Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation. Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa). All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH. Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors. Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey

  4. Death rate by age and sex in the U.S. 2021

    • statista.com
    Updated Oct 25, 2024
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    Statista (2024). Death rate by age and sex in the U.S. 2021 [Dataset]. https://www.statista.com/statistics/241572/death-rate-by-age-and-sex-in-the-us/
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    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.

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

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Mar 22, 2025
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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
    Mar 22, 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.).

  6. D

    Monthly Provisional Counts of Deaths by Select Causes, 2020-2023

    • data.cdc.gov
    • data.virginia.gov
    • +3more
    application/rdfxml +5
    Updated Sep 27, 2023
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    NCHS/DVS (2023). Monthly Provisional Counts of Deaths by Select Causes, 2020-2023 [Dataset]. https://data.cdc.gov/NCHS/Monthly-Provisional-Counts-of-Deaths-by-Select-Cau/9dzk-mvmi
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    csv, tsv, json, application/rssxml, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Sep 27, 2023
    Dataset authored and provided by
    NCHS/DVS
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov.

    Provisional counts of deaths by the month the death occurred and by select causes of death for 2020-2023.

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

    • data.virginia.gov
    • healthdata.gov
    • +4more
    csv, json, rdf, xsl
    Updated Feb 20, 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:
    json, xsl, rdf, csvAvailable download formats
    Dataset updated
    Feb 20, 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.).

  8. Death rate in the USA 2022

    • statista.com
    Updated Nov 22, 2024
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    Statista (2024). Death rate in the USA 2022 [Dataset]. https://www.statista.com/statistics/269970/death-rate-in-the-usa/
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    Dataset updated
    Nov 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2022, the death rate in the United States decreased by 0.6 deaths per 1,000 inhabitants (-5.77 percent) compared to 2021. Nevertheless, the last two years recorded a significantly higher death rate than the preceding years.The crude death rate is the annual number of deaths in a given population, expressed per 1,000 people. When looked at in unison with the crude birth rate, the rate of natural increase can be determined.Find more statistics on other topics about the United States with key insights such as total fertility rate, life expectancy of men at birth, and infant mortality rate.

  9. d

    Johns Hopkins COVID-19 Case Tracker

    • data.world
    csv, zip
    Updated Mar 25, 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
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    zip, csvAvailable download formats
    Dataset updated
    Mar 25, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 22, 2020 - Mar 9, 2023
    Area covered
    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

  10. F

    Premature Death Rate for San Francisco County, CA

    • fred.stlouisfed.org
    json
    Updated Jun 2, 2022
    + more versions
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    (2022). Premature Death Rate for San Francisco County, CA [Dataset]. https://fred.stlouisfed.org/series/CDC20N2U006075
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    jsonAvailable download formats
    Dataset updated
    Jun 2, 2022
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    California, San Francisco
    Description

    Graph and download economic data for Premature Death Rate for San Francisco County, CA (CDC20N2U006075) from 1999 to 2020 about San Francisco County/City, CA; San Francisco; premature; death; CA; rate; and USA.

  11. F

    Premature Death Rate for El Paso County, TX

    • fred.stlouisfed.org
    json
    Updated Jun 2, 2022
    + more versions
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    (2022). Premature Death Rate for El Paso County, TX [Dataset]. https://fred.stlouisfed.org/series/CDC20N2U048141
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    jsonAvailable download formats
    Dataset updated
    Jun 2, 2022
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    El Paso County, Texas
    Description

    Graph and download economic data for Premature Death Rate for El Paso County, TX (CDC20N2U048141) from 1999 to 2020 about El Paso County, TX; El Paso; premature; death; TX; rate; and USA.

  12. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +3more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

    The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

    Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

    We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

    The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

  13. F

    Premature Death Rate for Richmond city, VA

    • fred.stlouisfed.org
    json
    Updated Jun 2, 2022
    + more versions
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    (2022). Premature Death Rate for Richmond city, VA [Dataset]. https://fred.stlouisfed.org/series/CDC20N2U051760
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 2, 2022
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Richmond, Virginia
    Description

    Graph and download economic data for Premature Death Rate for Richmond city, VA (CDC20N2U051760) from 1999 to 2020 about Richmond City, VA; Richmond; premature; death; VA; rate; and USA.

  14. 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

  15. N

    New York City Leading Causes of Death

    • data.cityofnewyork.us
    • catalog.data.gov
    application/rdfxml +5
    Updated Dec 9, 2024
    + more versions
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    Department of Health and Mental Hygiene (DOHMH) (2024). New York City Leading Causes of Death [Dataset]. https://data.cityofnewyork.us/Health/New-York-City-Leading-Causes-of-Death/jb7j-dtam
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    csv, json, tsv, xml, application/rssxml, application/rdfxmlAvailable download formats
    Dataset updated
    Dec 9, 2024
    Dataset authored and provided by
    Department of Health and Mental Hygiene (DOHMH)
    Area covered
    New York
    Description

    The leading causes of death by sex and ethnicity in New York City in since 2007. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City.

    Report last ran: 09/24/2019
    Rates based on small numbers (RSE > 30) as well as aggregate counts less than 5 have been suppressed in downloaded data

    Source: Bureau of Vital Statistics and New York City Department of Health and Mental Hygiene

  16. F

    Premature Death Rate for Dallas County, TX

    • fred.stlouisfed.org
    json
    Updated Jun 2, 2022
    + more versions
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    (2022). Premature Death Rate for Dallas County, TX [Dataset]. https://fred.stlouisfed.org/series/CDC20N2U048113
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    jsonAvailable download formats
    Dataset updated
    Jun 2, 2022
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Dallas County, Texas
    Description

    Graph and download economic data for Premature Death Rate for Dallas County, TX (CDC20N2U048113) from 1999 to 2020 about Dallas County, TX; Dallas; premature; death; TX; rate; and USA.

  17. F

    Age-Adjusted Premature Death Rate for Webb County, TX

    • fred.stlouisfed.org
    json
    Updated Jun 2, 2022
    + more versions
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    Age-Adjusted Premature Death Rate for Webb County, TX [Dataset]. https://fred.stlouisfed.org/series/CDC20N2UAA048479
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    jsonAvailable download formats
    Dataset updated
    Jun 2, 2022
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Webb County, Texas
    Description

    Graph and download economic data for Age-Adjusted Premature Death Rate for Webb County, TX (CDC20N2UAA048479) from 1999 to 2020 about Webb County, TX; Laredo; premature; death; TX; rate; and USA.

  18. COVID-19 death rates in the United States as of March 10, 2023, by state

    • statista.com
    Updated Mar 28, 2023
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    Statista (2023). COVID-19 death rates in the United States as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109011/coronavirus-covid19-death-rates-us-by-state/
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    Dataset updated
    Mar 28, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the death rate from COVID-19 in the state of New York was 397 per 100,000 people. New York is one of the states with the highest number of COVID-19 cases.

  19. F

    Premature Death Rate for Broward County, FL

    • fred.stlouisfed.org
    json
    Updated Jun 2, 2022
    + more versions
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    (2022). Premature Death Rate for Broward County, FL [Dataset]. https://fred.stlouisfed.org/series/CDC20N2U012011
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 2, 2022
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Broward County, Florida
    Description

    Graph and download economic data for Premature Death Rate for Broward County, FL (CDC20N2U012011) from 1999 to 2020 about Broward County, FL; Miami; premature; death; FL; rate; and USA.

  20. Deaths Involving COVID-19 by Vaccination Status

    • open.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://open.canada.ca/data/dataset/1375bb00-6454-4d3e-a723-4ae9e849d655
    Explore at:
    docx, csv, xlsxAvailable 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.

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

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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.

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