100+ datasets found
  1. Share of U.S. COVID-19 cases resulting in death from Feb. 12 to Mar. 16, by...

    • statista.com
    Updated Jul 27, 2022
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    Statista (2022). Share of U.S. COVID-19 cases resulting in death from Feb. 12 to Mar. 16, by age [Dataset]. https://www.statista.com/statistics/1105431/covid-case-fatality-rates-us-by-age-group/
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    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 12, 2020 - Mar 16, 2020
    Area covered
    United States
    Description

    Among COVID-19 patients in the United States from February 12 to March 16, 2020, estimated case-fatality rates were highest for adults aged 85 years and older. Younger people appeared to have milder symptoms, and there were no deaths reported among persons aged 19 years and under.

    Tracking the virus in the United States The outbreak of a previously unknown viral pneumonia was first reported in China toward the end of December 2019. The first U.S. case of COVID-19 was recorded in mid-January 2020, confirmed in a patient who had returned to the United States from China. The virus quickly started to spread, and the first community-acquired case was confirmed one month later in California. Overall, there had been approximately 4.5 million coronavirus cases in the country by the start of August 2020.

    U.S. health care system stretched California, Florida, and Texas are among the states with the most coronavirus cases. Even the best-resourced hospitals in the United States have struggled to cope with the crisis, and certain areas of the country were dealt further blows by new waves of infections in July 2020. Attention is rightly focused on fighting the pandemic, but as health workers are redirected to care for COVID-19 patients, the United States must not lose sight of other important health care issues.

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

    • statista.com
    Updated May 15, 2024
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    Statista (2024). 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
    May 15, 2024
    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.

  3. Monthly COVID-19 Death Rates per 100,000 Population by Age Group, Race and...

    • catalog.data.gov
    • healthdata.gov
    • +3more
    Updated Sep 17, 2025
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    Centers for Disease Control and Prevention (2025). Monthly COVID-19 Death Rates per 100,000 Population by Age Group, Race and Ethnicity, Sex, and Region with Double Stratification [Dataset]. https://catalog.data.gov/dataset/monthly-covid-19-death-rates-per-100000-population-by-age-group-race-and-ethnicity-sex-and-98960
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    Dataset updated
    Sep 17, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Monthly COVID-19 death rates per 100,000 population stratified by age group, race/ethnicity, sex, and region, with race/ethnicity by age group and age group by race/ethnicity double stratification

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

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Sep 26, 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
    Sep 26, 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.).

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

    • data.virginia.gov
    csv, json, rdf, xsl
    Updated Sep 25, 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-
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    json, csv, xsl, rdfAvailable download formats
    Dataset updated
    Sep 25, 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.).

  6. Age comparison of COVID-19 fatality rate South Korea 2023

    • statista.com
    Updated Jun 4, 2024
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    Statista (2024). Age comparison of COVID-19 fatality rate South Korea 2023 [Dataset]. https://www.statista.com/statistics/1105088/south-korea-coronavirus-mortality-rate-by-age/
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    Dataset updated
    Jun 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 28, 2023
    Area covered
    South Korea
    Description

    As of August 28, 2023, the fatality rate of novel coronavirus (COVID-19) in South Korea stood at around 1.7 percent among people aged 80 year and older. This made them the most vulnerable age group, followed by people in their seventies. After the first wave lasted till April and the second wave in August 2020, Korea faced a fourth wave fueled by the delta and omicron variants in 2022.

    For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  7. COVID-19 death rates in 2020 countries worldwide as of April 26, 2022

    • statista.com
    • thefarmdosupply.com
    • +1more
    Updated Mar 28, 2020
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    Statista (2020). COVID-19 death rates in 2020 countries worldwide as of April 26, 2022 [Dataset]. https://www.statista.com/statistics/1105914/coronavirus-death-rates-worldwide/
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    Dataset updated
    Mar 28, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. 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.

    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. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

    A word on the flaws of numbers like this

    People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

  8. Excess Deaths Associated with COVID-19

    • datalumos.org
    delimited
    Updated Apr 24, 2025
    + more versions
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    United States Department of Health and Human Services. Centers for Disease Control and Prevention. National Center for Health Statistics (2025). Excess Deaths Associated with COVID-19 [Dataset]. http://doi.org/10.3886/E227667V1
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    delimitedAvailable download formats
    Dataset updated
    Apr 24, 2025
    Authors
    United States Department of Health and Human Services. Centers for Disease Control and Prevention. National Center for Health Statistics
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017 - 2023
    Area covered
    United States
    Description

    Estimates of excess deaths can provide information about the burden of mortality potentially related to the COVID-19 pandemic, including deaths that are directly or indirectly attributed to COVID-19. Excess deaths are typically defined as the difference between the observed numbers of deaths in specific time periods and expected numbers of deaths in the same time periods. This visualization provides weekly estimates of excess deaths by the jurisdiction in which the death occurred. Weekly counts of deaths are compared with historical trends to determine whether the number of deaths is significantly higher than expected.Counts of deaths from all causes of death, including COVID-19, are presented. As some deaths due to COVID-19 may be assigned to other causes of deaths (for example, if COVID-19 was not diagnosed or not mentioned on the death certificate), tracking all-cause mortality can provide information about whether an excess number of deaths is observed, even when COVID-19 mortality may be undercounted. Additionally, deaths from all causes excluding COVID-19 were also estimated. Comparing these two sets of estimates — excess deaths with and without COVID-19 — can provide insight about how many excess deaths are identified as due to COVID-19, and how many excess deaths are reported as due to other causes of death. These deaths could represent misclassified COVID-19 deaths, or potentially could be indirectly related to the COVID-19 pandemic (e.g., deaths from other causes occurring in the context of health care shortages or overburdened health care systems).Estimates of excess deaths can be calculated in a variety of ways, and will vary depending on the methodology and assumptions about how many deaths are expected to occur. Estimates of excess deaths presented in this webpage were calculated using Farrington surveillance algorithms (1). A range of values for the number of excess deaths was calculated as the difference between the observed count and one of two thresholds (either the average expected count or the upper bound of the 95% prediction interval), by week and jurisdiction.Provisional death counts are weighted to account for incomplete data. However, data for the most recent week(s) are still likely to be incomplete. Weights are based on completeness of provisional data in prior years, but the timeliness of data may have changed in 2020 relative to prior years, so the resulting weighted estimates may be too high in some jurisdictions and too low in others. As more information about the accuracy of the weighted estimates is obtained, further refinements to the weights may be made, which will impact the estimates. Any changes to the methods or weighting algorithm will be noted in the Technical Notes when they occur. More detail about the methods, weighting, data, and limitations can be found in the Technical Notes.This visualization includes several different estimates:Number of excess deaths: A range of estimates for the number of excess deaths was calculated as the difference between the observed count and one of two thresholds (either the average expected count or the upper bound threshold), by week and jurisdiction. Negative values, where the observed count fell below the threshold, were set to zero.Percent excess: The percent excess was defined as the number of excess deaths divided by the threshold.Total number of excess deaths: The total number of excess deaths in each jurisdiction was calculated by summing the excess deaths in each week, from February 1, 2020 to present. Similarly, the total number of excess deaths for the US overall was computed as a sum of jurisdiction-specific numbers of excess deaths (with negative values set to zero), and not directly estimated using the Farrington surveillance algorithms.Select a dashboard from the menu, then click on “Update Dashboard” to navigate through the different graphics.The first dashboard shows the weekly predicted counts of deaths from all causes, and the threshold for the expected number of deaths. Select a jurisdiction from the drop-down menu to show data for that jurisdiction.The second dashboard shows the weekly predicted counts of deaths from all causes and the weekly count of deaths from all causes excluding COVID-19. Select a jurisdiction from the drop-down menu to show data for that jurisdiction.The th

  9. Provisional COVID-19 Death Counts in the United States by County

    • catalog.data.gov
    • data.virginia.gov
    • +4more
    Updated Apr 23, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 Death Counts in the United States by County [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-in-the-united-states-by-county
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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

    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) Provisional count of deaths involving COVID-19 by county of occurrence, in the United States, 2020-2023.

  10. g

    Coronavirus (Covid-19) Data in the United States

    • github.com
    • openicpsr.org
    • +2more
    csv
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://github.com/nytimes/covid-19-data
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    csvAvailable download formats
    Dataset provided by
    New York Times
    License

    https://github.com/nytimes/covid-19-data/blob/master/LICENSEhttps://github.com/nytimes/covid-19-data/blob/master/LICENSE

    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 the first reported coronavirus case in Washington State on Jan. 21, 2020, 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.

  11. Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent)...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    csv, xlsx, xml
    Updated May 30, 2023
    + more versions
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    CDC COVID-19 Response, Epidemiology Task Force (2023). Rates of COVID-19 Cases or Deaths by Age Group and Updated (Bivalent) Booster Status [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/54ys-qyzm
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    xlsx, csv, xmlAvailable download formats
    Dataset updated
    May 30, 2023
    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 Updated (Bivalent) Booster Status. Click 'More' for important dataset description and footnotes

    Webpage: https://covid.cdc.gov/covid-data-tracker/#rates-by-vaccine-status

    Dataset and data visualization details:

    These data were posted and archived on May 30, 2023 and reflect cases among persons with a positive specimen collection date through April 22, 2023, and deaths among persons with a positive specimen collection date through April 1, 2023. These data will no longer be updated after May 2023.

    Vaccination status: A person vaccinated with at least 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. A person vaccinated with a primary series and a monovalent booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and at least one additional dose of any monovalent FDA-authorized or approved COVID-19 vaccine on or after August 13, 2021. (Note: this definition does not distinguish between vaccine recipients who are immunocompromised and are receiving an additional dose versus those who are not immunocompromised and receiving a booster dose.) A person vaccinated with a primary series and an updated (bivalent) booster dose had SARS-CoV-2 RNA or antigen detected in a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and an additional dose of any bivalent FDA-authorized or approved vaccine COVID-19 vaccine on or after September 1, 2022. (Note: Doses with bivalent doses reported as first or second doses are classified as vaccinated with a bivalent booster dose.) People with primary series or a monovalent booster dose were combined in the “vaccinated without an updated booster” category.

    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. Per the interim guidance of the Council of State and Territorial Epidemiologists (CSTE), this should include persons whose death certificate lists COVID-19 disease or SARS-CoV-2 as the underlying cause of death or as a significant condition contributing to death. Rates of COVID-19 deaths by vaccination status are primarily reported based on when the patient was tested for COVID-19. In select jurisdictions, deaths are included that are not laboratory confirmed and are reported based on alternative dates (i.e., onset date for most; or date of death or report date, where onset date is unavailable). Deaths usually occur up to 30 days after COVID-19 diagnosis.

    Participating jurisdictions: Currently, these 24 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Colorado, District of Columbia, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (NY), North Carolina, Rhode Island, Tennessee, Texas, Utah, and West Virginia; 23 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 48% of the total U.S. population and all ten of the Health and Human Services Regions. 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 at least 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 6-12 months, half of the single-year population counts for ages <12 months were used. All rates are plotted by positive specimen collection date to reflect when incident infections occurred.

    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 without an updated (bivalent) booster dose) or vaccinated with an updated (bivalent) booster dose.

    Archive: An archive of historic data, including April 3, 2021-September 24, 2022 and posted on October 21, 2022 is available on data.cdc.gov. The analysis by vaccination status (unvaccinated and at least a primary series) for 31 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/3rge-nu2a. The analysis for one booster dose (unvaccinated, primary series only, and at least one booster dose) in 31 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/d6p8-wqjm. The analysis for two booster doses (unvaccinated, primary series only, one booster dose, and at least two booster doses) in 28 jurisdictions is posted here: https://data.cdc.gov/Public-Health-Surveillance/Rates-of-COVID-19-Cases-or-Deaths-by-Age-Group-and/ukww-au2k.

    References

    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

  12. f

    Age-specific case fatality rate and ICU admission rate.

    • plos.figshare.com
    zip
    Updated May 30, 2023
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    Taito Kitano; Mao Kitano; Carsten Krueger; Hassan Jamal; Hatem Al Rawahi; Rachelle Lee-Krueger; Rose Doulin Sun; Sandra Isabel; Marta Taida García-Ascaso; Hiromi Hibino; Bettina Camara; Marc Isabel; Leanna Cho; Helen E. Groves; Pierre-Philippe Piché-Renaud; Michael Kossov; Ikuho Kou; Ilsu Jon; Ana C. Blanchard; Nao Matsuda; Quenby Mahood; Anupma Wadhwa; Ari Bitnun; Shaun K. Morris (2023). Age-specific case fatality rate and ICU admission rate. [Dataset]. http://doi.org/10.1371/journal.pone.0246326.s005
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    zipAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Taito Kitano; Mao Kitano; Carsten Krueger; Hassan Jamal; Hatem Al Rawahi; Rachelle Lee-Krueger; Rose Doulin Sun; Sandra Isabel; Marta Taida García-Ascaso; Hiromi Hibino; Bettina Camara; Marc Isabel; Leanna Cho; Helen E. Groves; Pierre-Philippe Piché-Renaud; Michael Kossov; Ikuho Kou; Ilsu Jon; Ana C. Blanchard; Nao Matsuda; Quenby Mahood; Anupma Wadhwa; Ari Bitnun; Shaun K. Morris
    License

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

    Description

    A. Age-specific case fatality rate. B. Age-specific ICU admission rate. Age-specific national data with up to one year difference of age buckets were included. For example, age-specific national data reporting outcomes of 1–5 years and 10–15 years were included in our calculation of 1–4 years and 10–14 years. Abbreviations: y, years. (ZIP)

  13. T

    World Coronavirus COVID-19 Deaths

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 9, 2020
    + more versions
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    TRADING ECONOMICS (2020). World Coronavirus COVID-19 Deaths [Dataset]. https://tradingeconomics.com/world/coronavirus-deaths
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    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    Mar 9, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 4, 2020 - May 17, 2023
    Area covered
    World
    Description

    The World Health Organization reported 6932591 Coronavirus Deaths since the epidemic began. In addition, countries reported 766440796 Coronavirus Cases. This dataset provides - World Coronavirus Deaths- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  14. COVID-19 fatality rate as of February 28, 2020, by gender

    • statista.com
    Updated Mar 13, 2020
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    Statista (2020). COVID-19 fatality rate as of February 28, 2020, by gender [Dataset]. https://www.statista.com/statistics/1103644/covid-19-death-rate-confirmed-and-all-cases-by-gender/
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    Dataset updated
    Mar 13, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    As of the end of February 2020 and based on data available from China, the probability of dying as a result of a coronavirus infection was 4.7 percent among confirmed cases in males and 2.8 percent among confirmed cases in females. This statistic depicts the death rate of confirmed and all cases of COVID-19 worldwide as of February 28, 2020, by gender.

  15. d

    Replication Data for: Two years of Covid-19 pandemic : A higher prevalence...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Errasfa, Mourad (2023). Replication Data for: Two years of Covid-19 pandemic : A higher prevalence of the disease was associated with higher geographic latitudes, lower temperatures, and unfavorable epidemiologic and demographic conditions. [Dataset]. http://doi.org/10.7910/DVN/JYYZEI
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Errasfa, Mourad
    Description

    ABSTRACT Background : The Covid-19 pandemic associated with the SARS-CoV-2 has caused very high death tolls in many countries, while it has had less prevalence in other countries of Africa and Asia. Climate and geographic conditions, as well as other epidemiologic and demographic conditions, were a matter of debate on whether or not they could have an effect on the prevalence of Covid-19. Objective : In the present work, we sought a possible relevance of the geographic location of a given country on its Covid-19 prevalence. On the other hand, we sought a possible relation between the history of epidemiologic and demographic conditions of the populations and the prevalence of Covid-19 across four continents (America, Europe, Africa, and Asia). We also searched for a possible impact of pre-pandemic alcohol consumption in each country on the two year death tolls across the four continents. Methods : We have sought the death toll caused by Covid-19 in 39 countries and obtained the registered deaths from specialized web pages. For every country in the study, we have analysed the correlation of the Covid-19 death numbers with its geographic latitude, and its associated climate conditions, such as the mean annual temperature, the average annual sunshine hours, and the average annual UV index. We also analyzed the correlation of the Covid-19 death numbers with epidemiologic conditions such as cancer score and Alzheimer score, and with demographic parameters such as birth rate, mortality rate, fertility rate, and the percentage of people aged 65 and above. In regard to consumption habits, we searched for a possible relation between alcohol intake levels per capita and the Covid-19 death numbers in each country. Correlation factors and determination factors, as well as analyses by simple linear regression and polynomial regression, were calculated or obtained by Microsoft Exell software (2016). Results : In the present study, higher numbers of deaths related to Covid-19 pandemic were registered in many countries in Europe and America compared to other countries in Africa and Asia. The analysis by polynomial regression generated an inverted bell-shaped curve and a significant correlation between the Covid-19 death numbers and the geographic latitude of each country in our study. Higher death numbers were registered in the higher geographic latitudes of both hemispheres, while lower scores of deaths were registered in countries located around the equator line. In a bell shaped curve, the latitude levels were negatively correlated to the average annual levels (last 10 years) of temperatures, sunshine hours, and UV index of each country, with the highest scores of each climate parameter being registered around the equator line, while lower levels of temperature, sunshine hours, and UV index were registered in higher latitude countries. In addition, the linear regression analysis showed that the Covid-19 death numbers registered in the 39 countries of our study were negatively correlated with the three climate factors of our study, with the temperature as the main negatively correlated factor with Covid-19 deaths. On the other hand, cancer and Alzheimer's disease scores, as well as advanced age and alcohol intake, were positively correlated to Covid-19 deaths, and inverted bell-shaped curves were obtained when expressing the above parameters against a country’s latitude. Instead, the (birth rate/mortality rate) ratio and fertility rate were negatively correlated to Covid-19 deaths, and their values gave bell-shaped curves when expressed against a country’s latitude. Conclusion : The results of the present study prove that the climate parameters and history of epidemiologic and demographic conditions as well as nutrition habits are very correlated with Covid-19 prevalence. The results of the present study prove that low levels of temperature, sunshine hours, and UV index, as well as negative epidemiologic and demographic conditions and high scores of alcohol intake may worsen Covid-19 prevalence in many countries of the northern hemisphere, and this phenomenon could explain their high Covid-19 death tolls. Keywords : Covid-19, Coronavirus, SARS-CoV-2, climate, temperature, sunshine hours, UV index, cancer, Alzheimer disease, alcohol.

  16. f

    Multivariate beta regression modeling case fatality rate (n = 3,039...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    George Pro; Paul A. Gilbert; Julie A. Baldwin; Clare C. Brown; Sean Young; Nickolas Zaller (2023). Multivariate beta regression modeling case fatality rate (n = 3,039 counties). [Dataset]. http://doi.org/10.1371/journal.pone.0253466.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    George Pro; Paul A. Gilbert; Julie A. Baldwin; Clare C. Brown; Sean Young; Nickolas Zaller
    License

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

    Description

    Multivariate beta regression modeling case fatality rate (n = 3,039 counties).

  17. Fatality rate of major virus outbreaks in the last 50 years as of 2020

    • thefarmdosupply.com
    • tokrwards.com
    • +1more
    Updated Dec 20, 2023
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    John Elflein (2023). Fatality rate of major virus outbreaks in the last 50 years as of 2020 [Dataset]. https://www.thefarmdosupply.com/?_=%2Ftopics%2F5898%2Fnovel-coronavirus-covid-19-in-china%2F%23RslIny40YoL1bbEgyeyUHEfOSI5zbSLA
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    Dataset updated
    Dec 20, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    John Elflein
    Description

    Among the ten major virus outbreaks in the last 50 years, Marburg ranked first in terms of the fatality rate with 80 percent. In comparison, the recent novel coronavirus, originating from the Chinese city of Wuhan, had an estimated fatality rate of 2.2 percent as of January 31, 2020.

    Alarming COVID-19 fatality rate in Mexico More than 812,000 people worldwide had died from COVID-19 as of August 24, 2020. Three of the most populous countries in the world have reported particularly large numbers of coronavirus-related deaths: Mexico, Brazil, and the United States. Out of those three nations, Mexico has the highest COVID-19 death rate, with around one in ten confirmed cases resulting in death. The high fatality rate in Mexico indicates that cases may be much higher than reported because testing capacity has been severely stretched.

    Post-lockdown complacency a real danger In March 2020, each infected person was estimated to transmit the COVID-19 virus to between 1.5 and 3.5 other people, which was a higher infection rate than the seasonal flu. The coronavirus is primarily spread through respiratory droplets, and transmission commonly occurs when people are in close contact. As lockdowns ease around the world, people are being urged not to become complacent; continue to wear face coverings and practice social distancing, which can help to prevent further infections.

  18. Coronavirus (COVID-19) death rates in New York as of April 19, 2021, by...

    • thefarmdosupply.com
    • statista.com
    Updated May 4, 2021
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    Statista (2021). Coronavirus (COVID-19) death rates in New York as of April 19, 2021, by county [Dataset]. https://www.thefarmdosupply.com/?_=%2Fstatistics%2F1109417%2Fcoronavirus-covid19-death-rates-new-york-by-county%2F%23RslIny40YoL1bbEgyeyUHEfOSI5zbSLA
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    Dataset updated
    May 4, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    New York, United States
    Description

    As of April 19, 2021, there had been around 27 deaths due to COVID-19 in New York City per 10,000 population. New York has been one of the U.S. states most impacted by the COVID-19 pandemic, with New York accounting for the most deaths of any state in the U.S. This statistic shows the death rates for coronavirus (COVID-19) in New York State as of April 19, 2021, by county.

  19. H

    A negative history of epidemiologic and demographic factors was associated...

    • dataverse.harvard.edu
    Updated Apr 28, 2022
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    Mourad Errasfa (2022). A negative history of epidemiologic and demographic factors was associated with high numbers of Covid-19 [Dataset]. http://doi.org/10.7910/DVN/XWOREU
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 28, 2022
    Dataset provided by
    Harvard Dataverse
    Authors
    Mourad Errasfa
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Background : Substantial differences between countries were observed in terms of Covid-19 death tolls during the past two years. It was of interest to find out how the epidemiologic and/or demographic history of the population may have had a role in the high prevalence of the Covid-19 in some countries. Objective : This observational study aimed to investigate possible relations between Covid-19 death numbers in 39 countries and the prepandemic history of epidemiologic and demographic conditions. Methods : We sought the Covid-19 death toll in 39 countries in Europe, America, Africa, and Asia. Records (2019) of epidemiologic (Cancer, Alzheimer's disease) and demographic (natality, mortality, and fetility rates, percentage of people aged 65 and over) parameters as well as data on alcohol intake per capita were retrieved from official web pages. Data was analysed by simple linear or polynomial regression by the mean of Microsoft Excell software (2016). Results : When Covid-19 death numbers were plotted against the geographic latitude of each country, a bell-shaped curve was obtained for both the first and second years (coefficient of determination R2=0.38) of the pandemic. In a similar manner, bell-shaped curves were obtained when latitudes were plotted against the scores of (cancer plus Alzheimer's disease, R² = 0,65,), the percentage of advanced age (R² = 0,52,) and the alcohol intake level (R² = 0,64,). Covid-19 death numbers were positively correlated to the scores of (cancer plus Alzheimer's disease) (R2= 0.41, P= 1.61x10-5), advanced age (R2= 0.38, P= 4.09x10-5) and alcohol intake (R2= 0.48, P= 1.55x10-6). Instead, inverted bell-shaped curves were obtained when latitudes were plotted against the birth rate/mortality rate ratio (R² = 0,51) and the fetility rate (R² = 0,33). In addition, Covid-19 deaths were negatively correlated with the birth rate/mortality rate ratio (R2= 0.67) and fertility rate (R2= 0.50). Conclusion : The results show that the 39 countries in both hemisphers in this study have different patterns of epidemiologic and demographic factors, and that the negative history of epidemiologic and demographic factors of the northern hemisphere countries, as well as their high alcohol intake, were very correlated with their Covid-19 death tolls. Hence, also nutritional habits may have had a role in the general health status of people in regard to their immunity against the coronavirus.

  20. New York State Statewide COVID-19 Fatalities by Age Group (Archived)

    • health.data.ny.gov
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated Oct 6, 2023
    + more versions
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    New York State Department of Health (2023). New York State Statewide COVID-19 Fatalities by Age Group (Archived) [Dataset]. https://health.data.ny.gov/Health/New-York-State-Statewide-COVID-19-Fatalities-by-Ag/du97-svf7
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    application/rssxml, tsv, csv, json, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Oct 6, 2023
    Dataset authored and provided by
    New York State Department of Health
    Area covered
    New York
    Description

    Note: Data elements were retired from HERDS on 10/6/23 and this dataset was archived.

    This dataset includes the cumulative number and percent of healthcare facility-reported fatalities for patients with lab-confirmed COVID-19 disease by reporting date and age group. This dataset does not include fatalities related to COVID-19 disease that did not occur at a hospital, nursing home, or adult care facility. The primary goal of publishing this dataset is to provide users with information about healthcare facility fatalities among patients with lab-confirmed COVID-19 disease.

    The information in this dataset is also updated daily on the NYS COVID-19 Tracker at https://www.ny.gov/covid-19tracker.

    The data source for this dataset is the daily COVID-19 survey through the New York State Department of Health (NYSDOH) Health Electronic Response Data System (HERDS). Hospitals, nursing homes, and adult care facilities are required to complete this survey daily. The information from the survey is used for statewide surveillance, planning, resource allocation, and emergency response activities. Hospitals began reporting for the HERDS COVID-19 survey in March 2020, while Nursing Homes and Adult Care Facilities began reporting in April 2020. It is important to note that fatalities related to COVID-19 disease that occurred prior to the first publication dates are also included.

    The fatality numbers in this dataset are calculated by assigning age groups to each patient based on the patient age, then summing the patient fatalities within each age group, as of each reporting date. The statewide total fatality numbers are calculated by summing the number of fatalities across all age groups, by reporting date. The fatality percentages are calculated by dividing the number of fatalities in each age group by the statewide total number of fatalities, by reporting date. The fatality numbers represent the cumulative number of fatalities that have been reported as of each reporting date.

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Statista (2022). Share of U.S. COVID-19 cases resulting in death from Feb. 12 to Mar. 16, by age [Dataset]. https://www.statista.com/statistics/1105431/covid-case-fatality-rates-us-by-age-group/
Organization logo

Share of U.S. COVID-19 cases resulting in death from Feb. 12 to Mar. 16, by age

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3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 27, 2022
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Feb 12, 2020 - Mar 16, 2020
Area covered
United States
Description

Among COVID-19 patients in the United States from February 12 to March 16, 2020, estimated case-fatality rates were highest for adults aged 85 years and older. Younger people appeared to have milder symptoms, and there were no deaths reported among persons aged 19 years and under.

Tracking the virus in the United States The outbreak of a previously unknown viral pneumonia was first reported in China toward the end of December 2019. The first U.S. case of COVID-19 was recorded in mid-January 2020, confirmed in a patient who had returned to the United States from China. The virus quickly started to spread, and the first community-acquired case was confirmed one month later in California. Overall, there had been approximately 4.5 million coronavirus cases in the country by the start of August 2020.

U.S. health care system stretched California, Florida, and Texas are among the states with the most coronavirus cases. Even the best-resourced hospitals in the United States have struggled to cope with the crisis, and certain areas of the country were dealt further blows by new waves of infections in July 2020. Attention is rightly focused on fighting the pandemic, but as health workers are redirected to care for COVID-19 patients, the United States must not lose sight of other important health care issues.

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