100+ datasets found
  1. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

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

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

    The difficulties of death figures

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

    Where are these numbers coming from?

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

  2. d

    MD COVID-19 - Total Confirmed Deaths Statewide

    • catalog.data.gov
    • opendata.maryland.gov
    Updated Mar 22, 2025
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    opendata.maryland.gov (2025). MD COVID-19 - Total Confirmed Deaths Statewide [Dataset]. https://catalog.data.gov/dataset/md-covid-19-total-confirmed-deaths-statewide
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents. Description The MD COVID-19 - Total Confirmed Deaths Statewide data layer is a collection of the statewide confirmed COVID-19 related deaths that have been reported each day by the Vital Statistics Administration. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Total Probable Deaths Statewide data layer. Update 5/27/21: The Maryland Department of Health (MDH) Vital Statistics Administration (VSA) revised the state’s COVID-19 data to include deaths that were not properly classified by medical certifiers over the past year. VSA identified these deaths as COVID-19 deaths through an information reconciliation process utilizing other sources of data. Learn more: https://health.maryland.gov/newsroom/Pages/Maryland-Department-of-Health-Vital-Statistics-Administration-issues-revision-of-COVID-19-death-data.aspx Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  3. COVID-19 deaths worldwide as of May 2, 2023, by country and territory

    • statista.com
    • flwrdeptvarieties.store
    Updated May 22, 2024
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    Statista (2024). COVID-19 deaths worldwide as of May 2, 2023, by country and territory [Dataset]. https://www.statista.com/statistics/1093256/novel-coronavirus-2019ncov-deaths-worldwide-by-country/
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    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2, 2023
    Area covered
    Worldwide
    Description

    As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

    Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

    What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

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

    • statista.com
    Updated Mar 20, 2023
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    Statista (2023). 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 20, 2023
    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.

  5. d

    MD COVID-19 - Confirmed Deaths by Gender Distribution

    • catalog.data.gov
    • opendata.maryland.gov
    • +1more
    Updated Mar 22, 2025
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    opendata.maryland.gov (2025). MD COVID-19 - Confirmed Deaths by Gender Distribution [Dataset]. https://catalog.data.gov/dataset/md-covid-19-confirmed-deaths-by-gender-distribution
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents by gender: Female; Male; Unknown. Description The MD COVID-19 - Confirmed Deaths by Gender Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by gender. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Probable Deaths by Gender Distribution data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  6. Total number of COVID-19 deaths APAC April 2024, by country or territory

    • statista.com
    Updated Sep 18, 2024
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    Statista (2024). Total number of COVID-19 deaths APAC April 2024, by country or territory [Dataset]. https://www.statista.com/statistics/1104268/apac-covid-19-deaths-by-country/
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    Dataset updated
    Sep 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Asia–Pacific
    Description

    As of April 13, 2024, India had the highest number of confirmed deaths due to the outbreak of the novel coronavirus in the Asia-Pacific region, with over 533 thousand deaths. Comparatively, Indonesia, which had the second highest number of coronavirus deaths in the Asia-Pacific region, recorded approximately 162 thousand COVID-19 related deaths as of April 13, 2024. Contrastingly, Bhutan had reported 21 deaths due to COVID-19 as of April 13, 2024.

  7. A

    ‘MD COVID-19 - Confirmed Deaths by Gender Distribution’ analyzed by...

    • analyst-2.ai
    Updated May 9, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘MD COVID-19 - Confirmed Deaths by Gender Distribution’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-md-covid-19-confirmed-deaths-by-gender-distribution-0191/latest
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    Dataset updated
    May 9, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘MD COVID-19 - Confirmed Deaths by Gender Distribution’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/f9f2d97c-bad8-43fc-be33-c9e09d9f2f27 on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents by gender: Female; Male; Unknown.

    Description The MD COVID-19 - Confirmed Deaths by Gender Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by gender. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Probable Deaths by Gender Distribution data layer.

    Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

    --- Original source retains full ownership of the source dataset ---

  8. d

    COVID-19 Cases, Hospitalizations, and Deaths (By County) - ARCHIVE

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Aug 12, 2023
    + more versions
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    data.ct.gov (2023). COVID-19 Cases, Hospitalizations, and Deaths (By County) - ARCHIVE [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-hospitalizations-and-deaths-by-county
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    Dataset updated
    Aug 12, 2023
    Dataset provided by
    data.ct.gov
    Description

    Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases, hospitalizations, and associated deaths that have been reported among Connecticut residents. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Hospitalization data were collected by the Connecticut Hospital Association and reflect the number of patients currently hospitalized with laboratory-confirmed COVID-19. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported d

  9. d

    MD COVID-19 - Total Probable Deaths by Date of Death

    • catalog.data.gov
    • opendata.maryland.gov
    • +2more
    Updated Mar 22, 2025
    + more versions
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    opendata.maryland.gov (2025). MD COVID-19 - Total Probable Deaths by Date of Death [Dataset]. https://catalog.data.gov/dataset/md-covid-19-total-probable-deaths-by-date-of-death
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    Dataset updated
    Mar 22, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of probable COVID-19 deaths among Maryland residents, by date of death. Description The MD COVID-19 - Total Probable Deaths by Date of Death data layer is a collection of the statewide probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by date of death. A death is classified as probable if the person's death certificate notes COVID-19 to be a probable, suspect or presumed cause or condition. Probable deaths are not yet been confirmed by a laboratory test. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Confirmed deaths are available from the MD COVID-19 - Total Confirmed Deaths by Date of Death data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  10. Number of coronavirus (COVID-19) deaths in the United Kingdom (UK) 2023

    • flwrdeptvarieties.store
    • statista.com
    Updated Dec 20, 2023
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    Juliette Gagliardi (2023). Number of coronavirus (COVID-19) deaths in the United Kingdom (UK) 2023 [Dataset]. https://flwrdeptvarieties.store/?_=%2Ftopics%2F6112%2Fcoronavirus-covid-19-in-the-uk%2F%23zUpilBfjadnZ6q5i9BcSHcxNYoVKuimb
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    Dataset updated
    Dec 20, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Juliette Gagliardi
    Area covered
    United Kingdom
    Description

    On March 4, 2020, the first death as a result of coronavirus (COVID-19) was recorded in the United Kingdom (UK). The number of deaths in the UK has increased significantly since then. As of January 13, 2023, the number of confirmed deaths due to coronavirus in the UK amounted to 202,157. On January 21, 2021, 1,370 deaths were recorded, which was the highest total in single day in the UK since the outbreak began.

    Number of deaths among highest in Europe
    The UK has had the highest number of deaths from coronavirus in western Europe. In terms of rate of coronavirus deaths, the UK has recorded 297.8 deaths per 100,000 population.

    Cases in the UK The number of confirmed cases of coronavirus in the UK was 24,243,393 as of January 13, 2023. The South East has the highest number of first-episode confirmed cases of the virus in the UK with 3,123,050 cases, while London and the North West have 2,912,859 and 2,580,090 confirmed cases respectively. As of January 16, the UK has had 50 new cases per 100,000 in the last seven days.

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

  11. 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-
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    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.).

  12. Coronavirus (Covid-19) Data of United States (USA)

    • kaggle.com
    zip
    Updated Nov 5, 2020
    + more versions
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    Joel Hanson (2020). Coronavirus (Covid-19) Data of United States (USA) [Dataset]. https://www.kaggle.com/joelhanson/coronavirus-covid19-data-in-the-united-states
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    zip(7506633 bytes)Available download formats
    Dataset updated
    Nov 5, 2020
    Authors
    Joel Hanson
    License

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

    Area covered
    United States
    Description

    Coronavirus (COVID-19) Data in the United States

    [ U.S. State-Level Data (Raw CSV) | U.S. County-Level Data (Raw CSV) ]

    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.

    United States Data

    Data on cumulative coronavirus cases and deaths can be found in two files for states and counties.

    Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information.

    Both files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.

    Download all the data or clone this repository by clicking the green "Clone or download" button above.

    State-Level Data

    State-level data can be found in the states.csv file. (Raw CSV file here.)

    date,state,fips,cases,deaths
    2020-01-21,Washington,53,1,0
    ...
    

    County-Level Data

    County-level data can be found in the counties.csv file. (Raw CSV file here.)

    date,county,state,fips,cases,deaths
    2020-01-21,Snohomish,Washington,53061,1,0
    ...
    

    In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these.

    Methodology and Definitions

    The data is the product of dozens of journalists working across several time zones to monitor news conferences, analyze data releases and seek clarification from public officials on how they categorize cases.

    It is also a response to a fragmented American public health system in which overwhelmed public servants at the state, county and territorial levels have sometimes struggled to report information accurately, consistently and speedily. On several occasions, officials have corrected information hours or days after first reporting it. At times, cases have disappeared from a local government database, or officials have moved a patient first identified in one state or county to another, often with no explanation. In those instances, which have become more common as the number of cases has grown, our team has made every effort to update the data to reflect the most current, accurate information while ensuring that every known case is counted.

    When the information is available, we count patients where they are being treated, not necessarily where they live.

    In most instances, the process of recording cases has been straightforward. But because of the patchwork of reporting methods for this data across more than 50 state and territorial governments and hundreds of local health departments, our journalists sometimes had to make difficult interpretations about how to count and record cases.

    For those reasons, our data will in some cases not exactly match the information reported by states and counties. Those differences include these cases: When the federal government arranged flights to the United States for Americans exposed to the coronavirus in China and Japan, our team recorded those cases in the states where the patients subsequently were treated, even though local health departments generally did not. When a resident of Florida died in Los Angeles, we recorded her death as having occurred in California rather than Florida, though officials in Florida counted her case in their records. And when officials in some states reported new cases without immediately identifying where the patients were being treated, we attempted to add information about their locations later, once it became available.

    • Confirmed Cases

    Confirmed cases are patients who test positive for the coronavirus. We consider a case confirmed when it is reported by a federal, state, territorial or local government agency.

    • Dates

    For each date, we show the cumulative number of confirmed cases and deaths as reported that day in that county or state. All cases and deaths are counted on the date they are first announced.

    • Counties

    In some instances, we report data from multiple counties or other non-county geographies as a single county. For instance, we report a single value for New York City, comprising the cases for New York, Kings, Queens, Bronx and Richmond Counties. In these instances, the FIPS code field will be empty. (We may assign FIPS codes to these geographies in the future.) See the list of geographic exceptions.

    Cities like St. Louis and Baltimore that are administered separately from an adjacent county of the same name are counted separately.

    • “Unknown” Counties

    Many state health departments choose to report cases separately when the patient’s county of residence is unknown or pending determination. In these instances, we record the county name as “Unknown.” As more information about these cases becomes available, the cumulative number of cases in “Unknown” counties may fluctuate.

    Sometimes, cases are first reported in one county and then moved to another county. As a result, the cumulative number of cases may change for a given county.

    Geographic Exceptions

    • New York City

    All cases for the five boroughs of New York City (New York, Kings, Queens, Bronx and Richmond counties) are assigned to a single area called New York City.

    • Kansas City, Mo.

    Four counties (Cass, Clay, Jackson, and Platte) overlap the municipality of Kansas City, Mo. The cases and deaths that we show for these four counties are only for the portions exclusive of Kansas City. Cases and deaths for Kansas City are reported as their line.

    • Alameda, Calif.

    Counts for Alameda County include cases and deaths from Berkeley and the Grand Princess cruise ship.

    • Chicago

    All cases and deaths for Chicago are reported as part of Cook County.

    License and Attribution

    In general, we are making this data publicly available for broad, noncommercial public use including by medical and public health researchers, policymakers, analysts and local news media.

    If you use this data, you must attribute it to “The New York Times” in any publication. If you would like a more expanded description of the data, you could say “Data from The New York Times, based on reports from state and local health agencies.”

    If you use it in an online presentation, we would appreciate it if you would link to our U.S. tracking page at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.

    If you use this data, please let us know at covid-data@nytimes.com and indicate if you would be willing to talk to a reporter about your research.

    See our LICENSE for the full terms of use for this data.

    This license is co-extensive with the Creative Commons Attribution-NonCommercial 4.0 International license, and licensees should refer to that license (CC BY-NC) if they have questions about the scope of the license.

    Contact Us

    If you have questions about the data or licensing conditions, please contact us at:

    covid-data@nytimes.com

    Contributors

    Mitch Smith, Karen Yourish, Sarah Almukhtar, Keith Collins, Danielle Ivory, and Amy Harmon have been leading our U.S. data collection efforts.

    Data has also been compiled by Jordan Allen, Jeff Arnold, Aliza Aufrichtig, Mike Baker, Robin Berjon, Matthew Bloch, Nicholas Bogel-Burroughs, Maddie Burakoff, Christopher Calabrese, Andrew Chavez, Robert Chiarito, Carmen Cincotti, Alastair Coote, Matt Craig, John Eligon, Tiff Fehr, Andrew Fischer, Matt Furber, Rich Harris, Lauryn Higgins, Jake Holland, Will Houp, Jon Huang, Danya Issawi, Jacob LaGesse, Hugh Mandeville, Patricia Mazzei, Allison McCann, Jesse McKinley, Miles McKinley, Sarah Mervosh, Andrea Michelson, Blacki Migliozzi, Steven Moity, Richard A. Oppel Jr., Jugal K. Patel, Nina Pavlich, Azi Paybarah, Sean Plambeck, Carrie Price, Scott Reinhard, Thomas Rivas, Michael Robles, Alison Saldanha, Alex Schwartz, Libby Seline, Shelly Seroussi, Rachel Shorey, Anjali Singhvi, Charlie Smart, Ben Smithgall, Steven Speicher, Michael Strickland, Albert Sun, Thu Trinh, Tracey Tully, Maura Turcotte, Miles Watkins, Jeremy White, Josh Williams, and Jin Wu.

    Context

    There's a story behind every dataset and here's your opportunity to share yours.# Coronavirus (Covid-19) Data in the United States

    [ U.S. State-Level Data ([Raw

  13. Total number of U.S. COVID-19 cases and deaths April 26, 2023

    • statista.com
    Updated May 15, 2024
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    Statista (2024). Total number of U.S. COVID-19 cases and deaths April 26, 2023 [Dataset]. https://www.statista.com/statistics/1101932/coronavirus-covid19-cases-and-deaths-number-us-americans/
    Explore at:
    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of April 26, 2023, the number of both confirmed and presumptive positive cases of the COVID-19 disease reported in the United States had reached over 104 million with over 1.1 million deaths reported among these cases.

    Coronavirus deaths by age in the U.S. Daily new cases of COVID-19 hit record highs in the United States at the beginning of 2022. Underlying health conditions can worsen cases of coronavirus, and case fatality rates among confirmed COVID-19 patients increase with age. The highest number of deaths from COVID-19 have been among those aged 85 years and older, with this age group accounting for over 300 thousand deaths.

    Where has this coronavirus come from? Coronaviruses are a large group of viruses transmitted between animals and people that cause illnesses ranging from the common cold to more severe diseases. The novel coronavirus that is currently infecting humans was already circulating among certain animal species. The first human case of this new coronavirus strain was reported in China at the end of December 2019. The coronavirus was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and its associated disease is known as COVID-19.

  14. Weekly United States COVID-19 Cases and Deaths by County - ARCHIVED

    • healthdata.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Jun 9, 2023
    + more versions
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    data.cdc.gov (2023). Weekly United States COVID-19 Cases and Deaths by County - ARCHIVED [Dataset]. https://healthdata.gov/dataset/Weekly-United-States-COVID-19-Cases-and-Deaths-by-/fjew-c6u8
    Explore at:
    application/rdfxml, csv, json, tsv, application/rssxml, xmlAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    data.cdc.gov
    Area covered
    United States
    Description

    Note: The cumulative case count for some counties (with small population) is higher than expected due to the inclusion of non-permanent residents in COVID-19 case counts.

    Reporting of Aggregate Case and Death Count data was discontinued on May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

    Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported through a robust process with the following steps:

    • Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
    • If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
    • A CDC data team reviewed counts for congruency prior to integration. CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
    • Cases and deaths are based on date of report and not on the date of symptom onset. CDC calculates rates in this data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
    • COVID-19 aggregate case and death data were organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts were calculated as the week-to-week change in reported cumulative cases and deaths (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the week before.

    This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues. CDC also worked with jurisdictions after the end of the public health emergency declaration to finalize county data.

    • Source: The weekly archived dataset is based on county-level aggregate count data
    • Confirmed/Probable Cases/Death breakdown: Cumulative cases and deaths for each county are included. Total reported cases include probable and confirmed cases.
    • Time Series Frequency: The weekly archived dataset contains weekly time series data (i.e., one record per week per county)

    Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the daily archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

    The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implement these case classifications. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

    Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, counts of confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report

  15. Weekly United States COVID-19 Cases and Deaths by State - ARCHIVED

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Feb 23, 2025
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    Centers for Disease Control and Prevention (2025). Weekly United States COVID-19 Cases and Deaths by State - ARCHIVED [Dataset]. https://data.virginia.gov/dataset/weekly-united-states-covid-19-cases-and-deaths-by-state-archived
    Explore at:
    json, csv, xsl, rdfAvailable download formats
    Dataset updated
    Feb 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    Reporting of new Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

    Aggregate Data Collection Process Since the start of the COVID-19 pandemic, data have been gathered through a robust process with the following steps:

    • A CDC data team reviews and validates the information obtained from jurisdictions’ state and local websites via an overnight data review process.
    • If more than one official county data source exists, CDC uses a comprehensive data selection process comparing each official county data source, and takes the highest case and death counts respectively, unless otherwise specified by the state.
    • CDC compiles these data and posts the finalized information on COVID Data Tracker.
    • County level data is aggregated to obtain state and territory specific totals.
    This process is collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provide the most up-to-date numbers on cases and deaths by report date. CDC may retrospectively update counts to correct data quality issues.

    Methodology Changes Several differences exist between the current, weekly-updated dataset and the archived version:

    • Source: The current Weekly-Updated Version is based on county-level aggregate count data, while the Archived Version is based on State-level aggregate count data.
    • Confirmed/Probable Cases/Death breakdown:  While the probable cases and deaths are included in the total case and total death counts in both versions (if applicable), they were reported separately from the confirmed cases and deaths by jurisdiction in the Archived Version.  In the current Weekly-Updated Version, the counts by jurisdiction are not reported by confirmed or probable status (See Confirmed and Probable Counts section for more detail).
    • Time Series Frequency: The current Weekly-Updated Version contains weekly time series data (i.e., one record per week per jurisdiction), while the Archived Version contains daily time series data (i.e., one record per day per jurisdiction).
    • Update Frequency: The current Weekly-Updated Version is updated weekly, while the Archived Version was updated twice daily up to October 20, 2022.
    Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

    Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report probable cases and deaths to CDC.* Confirmed and probable case definition criteria are described here:

    Council of State and Territorial Epidemiologists (ymaws.com).

    Deaths CDC reports death data on other sections of the website: CDC COVID Data Tracker: Home, CDC COVID Data Tracker: Cases, Deaths, and Testing, and NCHS Provisional Death Counts. Information presented on the COVID Data Tracker pages is based on the same source (to

  16. COVID-19 Trends in Each Country

    • data.amerigeoss.org
    esri rest, html
    Updated Jul 29, 2020
    + more versions
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    ESRI (2020). COVID-19 Trends in Each Country [Dataset]. https://data.amerigeoss.org/dataset/covid-19-trends-in-each-country
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    esri rest, htmlAvailable download formats
    Dataset updated
    Jul 29, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Description

    COVID-19 Trends Methodology
    Our goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.


    6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.
    6/22/2020 - Added Executive Summary and Subsequent Outbreaks sections
    Revisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.
    Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.
    Correction on 6/1/2020
    Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020.
    Revisions added on 4/30/2020 are highlighted.
    Revisions added on 4/23/2020 are highlighted.

    Executive Summary
    COVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties.
    The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.

    We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.

    Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.

    Reasons for undertaking this work in March of 2020:
    1. The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.
    2. The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.
    3. The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:
    • U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online.
    • Initial older guidance was also obtained online.
    Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws.
    Thus, the formula used to compute an estimate of active cases is:

    Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths.
    <br

  17. H

    Coronavirus - Time Series of Confirmed Cases, Deaths and Vaccination in Rio...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Apr 9, 2023
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    Eduardo de Medeiros da Silveira (2023). Coronavirus - Time Series of Confirmed Cases, Deaths and Vaccination in Rio Grande do Sul [Dataset]. http://doi.org/10.7910/DVN/BFOJRU
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 9, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Eduardo de Medeiros da Silveira
    License

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

    Area covered
    South Region, State of Rio Grande do Sul
    Description

    This dataset contains three time series related to each other (number of confirmed cases, deaths and percentage of people with completed primary series vaccination in the Brazilian State of Rio Grande do Sul.

  18. d

    MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution

    • catalog.data.gov
    Updated Mar 22, 2025
    + more versions
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    opendata.maryland.gov (2025). MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution [Dataset]. https://catalog.data.gov/dataset/md-covid-19-probable-deaths-by-race-and-ethnicity-distribution
    Explore at:
    Dataset updated
    Mar 22, 2025
    Dataset provided by
    opendata.maryland.gov
    Area covered
    Maryland
    Description

    Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of probable COVID-19 deaths among Maryland residents by race and ethnicity: African American; White; Hispanic; Asian; Other; Unknown. Description The MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by categories of race and ethnicity. A death is classified as probable if the person's death certificate notes COVID-19 to be a probable, suspect or presumed cause or condition. Probable deaths are not yet been confirmed by a laboratory test. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Confirmed deaths are available from the MD COVID-19 - Confirmed Deaths by Race and Ethnicity Distribution data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  19. COVID-19 confirmed and death case development in China 2020-2022

    • statista.com
    Updated Mar 20, 2023
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    COVID-19 confirmed and death case development in China 2020-2022 [Dataset]. https://www.statista.com/statistics/1092918/china-wuhan-coronavirus-2019ncov-confirmed-and-deceased-number/
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    Dataset updated
    Mar 20, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 20, 2020 - Jun 6, 2022
    Area covered
    China
    Description

    As of June 6, 2022, the novel coronavirus SARS-CoV-2 that originated in Wuhan, the capital of Hubei province in China, had infected over 2.1 million people and killed 14,612 in the country. Hong Kong is currently the region with the highest active cases in China.

    From Wuhan to the rest of China

    In late December 2019, health authorities in Wuhan detected several pneumonia cases of unknown cause. Most of these patients had links to the Huanan Seafood Market. With Chinese New Year approaching, millions of Chinese migrant workers travelled back to their hometowns for the celebration. Before the start of the travel ban on January 23, around five million people had left Wuhan. By the end of January, the number of infections had surged to over ten thousand. The death toll from the virus exceeded that of the SARS outbreak a few days later. On February 12, thousands more cases were confirmed in Wuhan after an improvement to the diagnosis method, resulting in another sudden surge of confirmed cases. On March 31, 2020, the National Health Commission (NHC) in China announced that it would begin reporting the infection number of symptom-free individuals who tested positive for coronavirus. On April 17, 2020, health authorities in Wuhan revised its death toll, adding 50 percent more fatalities. After quarantine measures were implemented, the country reported no new local coronavirus COVID-19 transmissions for the first time on March 18, 2020.

    The overloaded healthcare system

    In Wuhan, 28 hospitals were designated to treat coronavirus patients, but the outbreak continued to test China’s disease control system and most of the hospitals were soon fully occupied. To combat the virus, the government announced plans to build a new hospital swiftly. On February 3, 2020, Huoshenshan Hospital was opened to provide an additional 1,300 beds. Due to an extreme shortage of health-care professionals in Wuhan, thousands of medical staff from all over China came voluntarily to the epicenter to offer their support. After no new deaths reported for first time, China lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country.

  20. Colombia COVID-19 - Complete Dataset

    • kaggle.com
    zip
    Updated Apr 1, 2020
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    Camilo Ruiz (2020). Colombia COVID-19 - Complete Dataset [Dataset]. https://www.kaggle.com/camesruiz/colombia-covid19-complete-dataset
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    zip(13219 bytes)Available download formats
    Dataset updated
    Apr 1, 2020
    Authors
    Camilo Ruiz
    License

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

    Area covered
    Colombia
    Description

    Context

    Coronavirus (COVID-19) made its outbreak in Colombia with the first confirmed in the country on march 6th, since then, number of confirmed cases has been increasing and deaths related to the virus are starting to have the first confirmed cases.

    Content

    This data set contains complete information about confirmed cases, deaths and number of recovered patients according to the daily reports by the colombian health department (Ministerio de Salud)

    I'll try to keep this dataset fully updated daily as soon as the official reports are published.

    Versions

    Version 5: Data encoding problem solved by omitting accents and 'ñ' in the states' names Version 6: Departments (states) file added with name and coordinates Version 9: File with each detailed case including sex, age and type of case

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Statista (2024). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
Organization logo

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

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166 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Nov 25, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

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

The difficulties of death figures

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

Where are these numbers coming from?

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

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