100+ datasets found
  1. d

    Données relatives à l’épidémie de COVID-19 en France : vue d’ensemble

    • data.gouv.fr
    csv, json
    Updated Sep 13, 2023
    + more versions
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    Ministère des Solidarités et de la Santé (2023). Données relatives à l’épidémie de COVID-19 en France : vue d’ensemble [Dataset]. https://www.data.gouv.fr/en/datasets/donnees-relatives-a-lepidemie-de-covid-19-en-france-vue-densemble/
    Explore at:
    json(501241), csv(47464)Available download formats
    Dataset updated
    Sep 13, 2023
    Dataset authored and provided by
    Ministère des Solidarités et de la Santé
    License

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

    Area covered
    France
    Description

    Point d'attention : les données sont désormais disponibles sur ce jeu de données. Tableau de bord de suivi de l'épidémie Les données sont exposées sur l'onglet vue d'ensemble du tableau de bord de suivi de l'épidémie disponible sur gouvernement.fr. Ce dernier présente depuis le 28 mars 2020 les données relatives à l’épidémie de COVID-19 en France. Cet outil dont le code source est libre, a été développé sous l’impulsion d’Etalab et avec la collaboration de la société civile. Il propose une vision consolidée des données officielles disponibles. Description du jeu de données Les données contenue dans le jeu de données sont publiées quotidiennement. Données sur le nombre de cas confirmés Cas confirmés : nombre cumulé de cas COVID-19 confirmé par un test positif. Données relatives à la situation hospitalière Hospitalisations : nombre de patients actuellement hospitalisés pour COVID-19. Nouveaux patients hospitalisés : nombre de nouveaux patients hospitalisés au cours des dernières 24 h. Retours à domicile : nombre cumulé de patients ayant été hospitalisés pour COVID-19 et de retour à domicile en raison de l'amélioration de leur état de santé. Réanimation : nombre de patients actuellement en réanimation ou soins intensifs. Nouveaux patients en réanimation : nombre de nouveaux patients admis en réanimation au cours des dernières 24 h. Données relatives au décès pour cause de COVID-19 Cumul des décès : cumul des décès constaté à l'hôpital et en EPHAD et EMS. Décès à l'hôpital : nombre cumulé de décès de patients hospitalisés pour COVID-19 depuis le 1er mars 2020. Cas confirmés en EHPAD et EMS : nombre de cas confirmés par test PCR en EHPAD et EMS. Ce chiffre est inclus dans le nombre total de cas confirmés. Décès en EHPAD : nombre cumulé de décès en EHPAD et EMS (Établissements médico-sociaux). Points d'attentions : Les méthodes de collecte des données ont évoluées dans le temps ; Au cours de l'été 2020, les données n'ont pas été publiées durant les week-end et jours fériés. Ressources Consulter le tableau de bord Consulter l'inventaire des données relatives au COVID-19 sur data.gouv.fr Consulter les données de Santé publique France Consulter les données du ministère des Solidarités et de la Santé

  2. Data from: COVID-19 Case Surveillance Public Use Data with Geography

    • healthdata.gov
    • data.virginia.gov
    • +5more
    application/rdfxml +5
    Updated Jun 9, 2021
    + more versions
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    data.cdc.gov (2021). COVID-19 Case Surveillance Public Use Data with Geography [Dataset]. https://healthdata.gov/w/x3vt-t6rt/default?cur=qTwZHXb3tvQ
    Explore at:
    xml, json, application/rdfxml, csv, application/rssxml, tsvAvailable download formats
    Dataset updated
    Jun 9, 2021
    Dataset provided by
    data.cdc.gov
    Description

    Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

    Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

    This case surveillance public use dataset has 19 elements for all COVID-19 cases shared with CDC and includes demographics, geography (county and state of residence), any exposure history, disease severity indicators and outcomes, and presence of any underlying medical conditions and risk behaviors.

    Currently, CDC provides the public with three versions of COVID-19 case surveillance line-listed data: this 19 data element dataset with geography, a 12 data element public use dataset, and a 33 data element restricted access dataset.

    The following apply to the public use datasets and the restricted access dataset:

    Overview

    The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (<a href="https://cdn.ymaws.com/www.cste.org/resource/resmgr/ps/positionstatement2020/Interim-20-ID-01_COVID

  3. d

    Cas confirmés d'infection au COVID-19 par région

    • data.gouv.fr
    csv, svg
    Updated Mar 26, 2020
    + more versions
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    Bastien Guerry (2020). Cas confirmés d'infection au COVID-19 par région [Dataset]. https://www.data.gouv.fr/en/datasets/cas-confirmes-dinfection-au-covid-19-par-region/
    Explore at:
    svg(133574), csv(1837)Available download formats
    Dataset updated
    Mar 26, 2020
    Authors
    Bastien Guerry
    License

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

    Description

    Santé Publique France a publié un point quotidien sur cette page indiquant le nombre de cas confirmés d'infection au virus COVID-19 ("Coronavirus"), région par région, jusqu'au 25 mars 2020 inclus. Ce jeu de données propose ces données en csv, accumulées au fil des jours. Avant d'utiliser ces données pour en proposer des représentations graphiques ou des calculs, assurez-vous de lire cet article. Le code source utilisé pour récupérer et compiler les données est sous licence libre ici.

  4. 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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    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.

  5. g

    Coronavirus (Covid-19) Data in the United States

    • github.com
    • openicpsr.org
    • +3more
    csv
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://github.com/nytimes/covid-19-data
    Explore at:
    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.

  6. d

    Johns Hopkins COVID-19 Case Tracker

    • data.world
    csv, zip
    Updated Mar 25, 2025
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    The Associated Press (2025). Johns Hopkins COVID-19 Case Tracker [Dataset]. https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker
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    zip, csvAvailable download formats
    Dataset updated
    Mar 25, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 22, 2020 - Mar 9, 2023
    Area covered
    Description

    Updates

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

    • April 9, 2020

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

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

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

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

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

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

      Overview

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

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

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

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

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

    Queries

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

    Interactive

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

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

    Interactive Embed Code

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

    Caveats

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

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

    Attribution

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

  7. COVID-19 Case Surveillance Public Use Data

    • catalog.data.gov
    • healthdata.gov
    • +6more
    Updated Mar 3, 2022
    + more versions
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    Centers for Disease Control and Prevention (2022). COVID-19 Case Surveillance Public Use Data [Dataset]. https://catalog.data.gov/dataset/covid-19-case-surveillance-public-use-data
    Explore at:
    Dataset updated
    Mar 3, 2022
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Beginning March 1, 2022, the "COVID-19 Case Surveillance Public Use Data" will be updated on a monthly basis. This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data. CDC has three COVID-19 case surveillance datasets: COVID-19 Case Surveillance Public Use Data with Geography: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements) COVID-19 Case Surveillance Public Use Data: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements) COVID-19 Case Surveillance Restricted Access Detailed Data: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (32 data elements) The following apply to all three datasets: Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf. Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers. Some data cells are suppressed to protect individual privacy. The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the previously updated datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured. Datasets are updated monthly. Datasets are created using CDC’s operational Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy. For more information about data collection and reporting, please see https://wwwn.cdc.gov/nndss/data-collection.html For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html Overview The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (Interim-20-ID-01). CSTE updated the position statement on August 5, 2020 to clarify the interpretation of antigen detection tests and serologic test results within the case classification. The statement also recommended that all states and territories enact laws to make COVID-19 reportable in their jurisdiction, and that jurisdictions conducting surveillance should submit case notifications to CDC. COVID-19 case surveillance data are collected by jurisdictions and reported volun

  8. Coronavirus (COVID-19) case numbers by age group and gender in Germany 2023

    • statista.com
    Updated Jan 20, 2025
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    Statista (2025). Coronavirus (COVID-19) case numbers by age group and gender in Germany 2023 [Dataset]. https://www.statista.com/statistics/1105465/coronavirus-covid-19-cases-age-group-germany/
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    Dataset updated
    Jan 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Germany
    Description

    In 2023, the coronavirus (COVID-19) is still present in Germany, affecting all of its federal states. Case numbers vary across age groups and genders. Based on current figures, among men, the most affected age group was 35-59 years. The same was true for women. These figures confirm that the virus can also affect younger age groups.

  9. D

    COVID-19 - Portrait quotidien des cas confirmés

    • donneesquebec.ca
    • ouvert.canada.ca
    csv, pdf
    Updated Mar 26, 2025
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    Ministère de la Santé et des services sociaux (2025). COVID-19 - Portrait quotidien des cas confirmés [Dataset]. https://www.donneesquebec.ca/recherche/dataset/covid-19-portrait-quotidien-des-cas-confirmes
    Explore at:
    csv, pdf(218358)Available download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    Ministère de la Santé et des services sociaux
    License

    https://www.donneesquebec.ca/licence/#cc-byhttps://www.donneesquebec.ca/licence/#cc-by

    Description

    Ce jeu présente le portrait quotidien du nombre de cas confirmés de COVID-19 au Québec. Note importante : Depuis le 12 avril 2023, la source de données des décès attribuables à la COVID-19 a été modifiée. Les données sont mises à jour hebdomadairement. Les cas et décès ayant eu lieu le dimanche, lundi et mardi précédent la mise en ligne du mercredi ne sont pas disponibles. Veuillez consulter les notes méthodologiques pour plus de détails.

  10. d

    COVID-19 case rate per 100,000 population and percent test positivity in the...

    • datasets.ai
    • data.ct.gov
    • +1more
    23, 40, 55, 8
    Updated Sep 8, 2024
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    State of Connecticut (2024). COVID-19 case rate per 100,000 population and percent test positivity in the last 7 days by town - ARCHIVE [Dataset]. https://datasets.ai/datasets/covid-19-case-rate-per-100000-population-and-percent-test-positivity-in-the-last-7-days-by
    Explore at:
    23, 55, 40, 8Available download formats
    Dataset updated
    Sep 8, 2024
    Dataset authored and provided by
    State of Connecticut
    Description

    DPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, these metrics will be calculated using a 14-day average rather than a 7-day average. The new dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2

    As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

    With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

    This dataset includes a weekly count and weekly rate per 100,000 population for COVID-19 cases, a weekly count of COVID-19 PCR diagnostic tests, and a weekly percent positivity rate for tests among people living in community settings. Dates are based on date of specimen collection (cases and positivity).

    A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.

    These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.

    These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020.

    Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.

  11. i

    COVID-19 Region-Wide Test, Case, and Death Trends

    • hub.mph.in.gov
    Updated May 14, 2020
    + more versions
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    (2020). COVID-19 Region-Wide Test, Case, and Death Trends [Dataset]. https://hub.mph.in.gov/dataset/covid-19-region-wide-test-case-and-death-trends
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    Dataset updated
    May 14, 2020
    License

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

    Description

    Archived as of 11/15/2023: With the end of the federal emergency and reporting requirements continuing to evolve, the Indiana Department of Health will no longer publish and refresh the COVID-19 datasets after November 15, 2023 - one final dataset publication will continue to be available as an archival copy. Number of COVID-19 cases, tests, and deaths by report date, by region. New positive cases, deaths and tests have occurred over a range of dates but were reported to ISDH in the last 24 hours. All data displayed is preliminary and subject to change as more information is reported to ISDH. Tests are displayed by the date the test was performed and deaths are displayed by the date the death occurred. Expect historical data to change as data is reported to ISDH

  12. d

    COVID-19 Case Investigation and Contact Tracing Dashboard

    • catalog.data.gov
    • data.kingcounty.gov
    • +1more
    Updated Feb 2, 2024
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    data.kingcounty.gov (2024). COVID-19 Case Investigation and Contact Tracing Dashboard [Dataset]. https://catalog.data.gov/dataset/covid-19-case-investigation-and-contact-tracing-dashboard
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    Dataset updated
    Feb 2, 2024
    Dataset provided by
    data.kingcounty.gov
    Description

    Case investigation and contact tracing are essential strategies for limiting the spread of COVID-19, along with face coverings, social distancing, handwashing and testing. Public Health's Case Investigation and Contact Tracing Team calls King County residents who have recently tested positive for COVID-19 ("cases"). And they call people who were exposed to COVID-19 ("contacts"). The phone calls include an explanation of isolation and quarantine guidelines, how to get testing and support services, and collecting information that helps Public Health's infection control programs.

  13. a

    Florida COVID19 06032021 Case Line Data

    • hub.arcgis.com
    Updated Jun 3, 2021
    + more versions
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    University of South Florida GIS (2021). Florida COVID19 06032021 Case Line Data [Dataset]. https://hub.arcgis.com/datasets/usflibrary::florida-covid19-06032021-case-line-data
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    Dataset updated
    Jun 3, 2021
    Dataset authored and provided by
    University of South Florida GIS
    Area covered
    Florida
    Description

    Florida COVID-19 Case Line data, exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu. Starting on 4/6/2021, the Florida Department of Health (FDOH) changed the way they provide COVID-19 caseline data. Beginning with this date the caseline data is being archived as two separate files, one for 2020 and one for 2021. The 2021 file will only include data from 1/1/2021 onward. In addition, FDOH has added two Object ID fields to their dataset. These caseline data are being preserved as they are provided by the FDOH, with a daily archive captured by the USF Libraries DHHC.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2021. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/. https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://www.arcgis.com/home/item.html?id=7a0c74a551904761812dc6b8bd620ee1 or Direct Download at: https://open-fdoh.hub.arcgis.com/datasets/7a0c74a551904761812dc6b8bd620ee1_0.

    Archives for this data layer begin on 5/11/2020. Archived data was exported directly from the live FDOH layer into the archive by the University of South Florida Libraries - Digital Heritage and Humanities Collection.For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from the Florida Department of Health. This data table represents all laboratory-confirmed cases of COVID-19 in Florida tabulated from the previous day's totals by the Florida Department of Health. Persons Under Investigation/Surveillance (PUI):Essentially, PUIs are any person who has been or is waiting to be tested. This includes: persons who are considered high-risk for COVID-19 due to recent travel, contact with a known case, exhibiting symptoms of COVID-19 as determined by a healthcare professional, or some combination thereof. PUI’s also include people who meet laboratory testing criteria based on symptoms and exposure, as well as confirmed cases with positive test results. PUIs include any person who is or was being tested, including those with negative and pending results.All PUIs fit into one of three residency types:1. Florida residents tested in Florida2. Non-Florida residents tested in Florida 3. Florida residents tested outside of Florida Florida Residents Tested Elsewhere: The total number of Florida residents with positive COVID-19 test results who were tested outsideof Florida, and were not exposed/infectious in Florida. Non-Florida Residents Tested in Florida: The total number of people with positive COVID-19 test results who were tested, exposed, and/or infectious while in Florida, but are legal residents of another state.Table Guide for Records of Confirmed Positive Cases of COVID-19"County": The Florida county where the individual with COVID-19's case has been processed. "Jurisdiction" of the case:"FL resident" -- a resident of Florida"Non-FL resident" -- someone who resides outside of Florida "Travel_Related": Whether or not the positive case of COVID-19 is designated as related to recent travel by the individual. "No" -- Case designated as not being a risk related to recent travel"Unknown" -- Case designated where a travel-related designation has not yet been made."Yes" -- Case is designated as travel-related for a person who recently traveled overseas or to an area with community"Origin": Where the person likely contracted the virus before arriving / returning to Florida."EDvisit": Whether or not an individual who tested positive for coronavirus visited and was admitted to an Emergency Department related to health conditions surrounding COVID-19."No" -- Individual was not admitted to an emergency department relating to health conditions surrounding the contraction of COVID-19"Unknown" -- It is unknown whether the individual was admitted to an emergency department relating to health conditions surrounding the contraction of COVID-19"Yes" -- Individual was admitted to an emergency department relating to health conditions surrounding the contraction of COVID-19“Hospitalized”: Whether or not a patient who receives a positive laboratory confirmed test for COVID-19 receives inpatient care at a hospital at any time during illness. These people may no longer be hospitalized. This information does not indicate that a COVID-19 positive person is currently hospitalized, only that they have been hospitalized for health conditions relating to COVID-19 at some point during their illness. "No" -- Individual was not admitted for inpatient care at a hospital at any time during illness "Unknown" -- It is unknown whether the individual was admitted for inpatient care at a hospital at any time during illness "Yes" -- Individual was admitted for inpatient care at a hospital at some point during the illness "Died": Whether or not the individual who tested positive for COVID-19 died as a result of health complications from the viral infection. "NA" -- Not applicable / resident has not died "Yes" -- Individual died of a health complication resulting from COVID-19 "Contact": Whether the person contracted COVID-19 from contact with current or previously confirmedcases."No" -- Case with no known contact with current or previously confirmed cases"Yes" -- Case with known contact with current or previously confirmed cases"Unknown" -- Case where contact with current or previous confirmedcases is not known or under investigation"Case_": The date the positive laboratory result was received in the Department of Health’s database system and became a “confirmed case.” This is not the date a person contracted the virus, became symptomatic, or was treated. Florida does not create a case or count suspected/probable cases in the case counts without a confirmed-positive lab result. "EventDate": When the individual reported likely first experiencing symptoms related to COVID-19. "ChartDate": Also the date the positive laboratory result for an individual was received in the Department ofHealth’s database system and became a recorded, “confirmed case” of COVID-19 in the state. Data definitions updated by the FDOH on 5/13/2020.

  14. d

    COVID 19 Case Data

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Feb 14, 2025
    + more versions
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    City of Sioux Falls GIS (2025). COVID 19 Case Data [Dataset]. https://catalog.data.gov/dataset/covid-19-case-data
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    Dataset updated
    Feb 14, 2025
    Dataset provided by
    City of Sioux Falls GIS
    Description

    A feature layer containing COVID-19 case data for Minnehaha County, South Dakota.Data was updated based on case information from the South Dakota Department of Health and ranges from March 8, 2020 to April 19 2023.Notes: - According to the State of SD Department of Health, on June 20 2020, in reviewing addresses a number of addresses were realigned from Minnehaha to Lincoln County, resulting in a negative daily case number for Minnehaha.- No records will exist on November 26, 2020 as the State of SD Department of Health did not post any new updates that day. Instead case data for November 27, 2020 includes records for the 26th and the 27th.- No records will exist on December 25, 2020 as the State of SD Department of Health did not post any new updates that day. Instead case data for December 26, 2020 includes records for the 25th and the 26th. - No records will exist on January 1, 2021 as the State of SD Department of Health did not post any new updates that day. Instead case data for January 2, 2021 includes records for the 1st and the 2nd.

  15. COVID-19 Trends in Each Country

    • coronavirus-response-israel-systematics.hub.arcgis.com
    • coronavirus-resources.esri.com
    • +2more
    Updated Mar 27, 2020
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    Urban Observatory by Esri (2020). COVID-19 Trends in Each Country [Dataset]. https://coronavirus-response-israel-systematics.hub.arcgis.com/maps/a16bb8b137ba4d8bbe645301b80e5740
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    Dataset updated
    Mar 27, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Earth
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur 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.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.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 sectionsRevisions 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 6/1/2020Discussion 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 SummaryCOVID-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: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.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.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. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

  16. COVID-19 Sewershed Restricted Case Data

    • data.ca.gov
    csv, xlsx, zip
    Updated Mar 20, 2025
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    COVID-19 Sewershed Restricted Case Data [Dataset]. https://data.ca.gov/dataset/covid-19-sewershed-restricted-case-data
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    xlsx, csv, zipAvailable download formats
    Dataset updated
    Mar 20, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

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

    Description

    The California Department of Public Health (CDPH) aggregates confirmed cases of COVID-19 by sewershed restricted locations. Confirmed cases are defined as individuals with a positive molecular test, which tests for viral genetic material, such as a polymerase chain reaction test.

    Since wastewater data available starts from January 1st, 2021, rather than the beginning of the COVID-19 pandemic in 2020, the cumulative counts of the confirmed cases variable are shown as “NA”.

    Please note that values less than 5 for confirmed cases are masked (shown as “Masked”) if the sewershed population size is 50,000 or fewer, in accordance with de-identification guidelines. Values less than 3 for cases are masked (shown as “Masked”) if the sewershed population size is between 50,001 and 250,000. For no confirmed cases reported, values are set as zero.

  17. b

    COVID-19 Pandemic : number of confirmed cases by date, age group and gender...

    • opendata.brussel.be
    • opendata.brussels.be
    csv, excel, geojson +1
    Updated Feb 20, 2025
    + more versions
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    (2025). COVID-19 Pandemic : number of confirmed cases by date, age group and gender (Belgium) [Dataset]. https://opendata.brussel.be/explore/dataset/pandemie-covid-19-nombre-de-cas-confirmes-par-date-age-et-genre-belgique/map/
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    csv, json, geojson, excelAvailable download formats
    Dataset updated
    Feb 20, 2025
    Area covered
    Belgium
    Description

    This dataset is based on the "Dataset of confirmed cases by date, age, sex and province" published by Sciensano beginning on March 31st, 2020.We added geographical points to display data on a map, based on the province names.

  18. COVID-19 case fatality rates in select countries worldwide February-August...

    • statista.com
    Updated Jun 15, 2021
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    COVID-19 case fatality rates in select countries worldwide February-August 2020 [Dataset]. https://www.statista.com/statistics/1076314/covid-19-case-fatality-rates-select-countries-worldwide/
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    Dataset updated
    Jun 15, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 25, 2020 - Aug 17, 2020
    Area covered
    Worldwide
    Description

    As of August 17, 2020, it was estimated that the case fatality rate for COVID-19 in Italy was around 14 percent. Case fatality rates are calculated by dividing the number of confirmed deaths by the number of confirmed cases. It is important to understand that the case fatality rate is not a good measure of the mortality risk of COVID-19. For a variety of reasons the case fatality rate varies over time and from country to country. Case fatality rates need to be interpreted with caution, especially when the total number of cases is not known, as is the current case with the COVID-19 pandemic. This statistic shows the development of the case fatality rates in select countries worldwide from February 25 to August 17, 2020.

  19. COVID-19 case fatality rate in Moscow 2020, by method

    • statista.com
    Updated Jun 23, 2020
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    Statista (2020). COVID-19 case fatality rate in Moscow 2020, by method [Dataset]. https://www.statista.com/statistics/1127809/covid-19-case-fatality-in-moscow-by-method/
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    Dataset updated
    Jun 23, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2020 - May 2020
    Area covered
    Russia
    Description

    The ratio of deaths directly from COVID-19 to the total number of the disease cases in Moscow was measured at two percent as of May 31, 2020. Taking into account lethal cases where COVID-19 was an accompanying cause of death, the case fatality rate reached 3.8 percent.

  20. Days since last reported case of COVID-19 worldwide as of March 21, 2020, by...

    • statista.com
    Updated Jun 12, 2020
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    Statista (2020). Days since last reported case of COVID-19 worldwide as of March 21, 2020, by country [Dataset]. https://www.statista.com/statistics/1100996/novel-coronavirus-covid19-days-since-last-case-worldwide-by-country/
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    Dataset updated
    Jun 12, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    As of March 23, 2020, the number of confirmed COVID-19 cases worldwide was approximately 339,712. Around 82 new cases were identified in China between March 20 and March 21, but it has been 58 days since the last reported case in Nepal.

    How can we prevent the spread? The novel coronavirus SARS-CoV-2 has not previously been identified in humans, and understanding how it is spreading is key to its containment. The SARS coronavirus, which caused a global epidemic between 2002 and 2004, is believed to have spread through cough and sneeze droplets. Basic protective measures against the new coronavirus include washing your hands frequently, ensuring social distancing is maintained, and practicing good hygiene etiquette, especially when coughing or sneezing.

    Who is at risk from the virus? The COVID-19 disease has been confirmed in around 210 countries and territories worldwide. The risk of infection is high if you are in a region where the virus is spreading or have recently traveled from an area where the virus is spreading. You should seek medical advice if you develop a fever, cough, and experience difficulty breathing. Older people and people with pre-existing medical conditions – such as asthma, diabetes, and heart disease – appear to be affected more than others.

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Ministère des Solidarités et de la Santé (2023). Données relatives à l’épidémie de COVID-19 en France : vue d’ensemble [Dataset]. https://www.data.gouv.fr/en/datasets/donnees-relatives-a-lepidemie-de-covid-19-en-france-vue-densemble/

Données relatives à l’épidémie de COVID-19 en France : vue d’ensemble

donnees-relatives-a-lepidemie-de-covid-19-en-france-vue-densemble

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8 scholarly articles cite this dataset (View in Google Scholar)
json(501241), csv(47464)Available download formats
Dataset updated
Sep 13, 2023
Dataset authored and provided by
Ministère des Solidarités et de la Santé
License

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

Area covered
France
Description

Point d'attention : les données sont désormais disponibles sur ce jeu de données. Tableau de bord de suivi de l'épidémie Les données sont exposées sur l'onglet vue d'ensemble du tableau de bord de suivi de l'épidémie disponible sur gouvernement.fr. Ce dernier présente depuis le 28 mars 2020 les données relatives à l’épidémie de COVID-19 en France. Cet outil dont le code source est libre, a été développé sous l’impulsion d’Etalab et avec la collaboration de la société civile. Il propose une vision consolidée des données officielles disponibles. Description du jeu de données Les données contenue dans le jeu de données sont publiées quotidiennement. Données sur le nombre de cas confirmés Cas confirmés : nombre cumulé de cas COVID-19 confirmé par un test positif. Données relatives à la situation hospitalière Hospitalisations : nombre de patients actuellement hospitalisés pour COVID-19. Nouveaux patients hospitalisés : nombre de nouveaux patients hospitalisés au cours des dernières 24 h. Retours à domicile : nombre cumulé de patients ayant été hospitalisés pour COVID-19 et de retour à domicile en raison de l'amélioration de leur état de santé. Réanimation : nombre de patients actuellement en réanimation ou soins intensifs. Nouveaux patients en réanimation : nombre de nouveaux patients admis en réanimation au cours des dernières 24 h. Données relatives au décès pour cause de COVID-19 Cumul des décès : cumul des décès constaté à l'hôpital et en EPHAD et EMS. Décès à l'hôpital : nombre cumulé de décès de patients hospitalisés pour COVID-19 depuis le 1er mars 2020. Cas confirmés en EHPAD et EMS : nombre de cas confirmés par test PCR en EHPAD et EMS. Ce chiffre est inclus dans le nombre total de cas confirmés. Décès en EHPAD : nombre cumulé de décès en EHPAD et EMS (Établissements médico-sociaux). Points d'attentions : Les méthodes de collecte des données ont évoluées dans le temps ; Au cours de l'été 2020, les données n'ont pas été publiées durant les week-end et jours fériés. Ressources Consulter le tableau de bord Consulter l'inventaire des données relatives au COVID-19 sur data.gouv.fr Consulter les données de Santé publique France Consulter les données du ministère des Solidarités et de la Santé

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