100+ datasets found
  1. COVID-19 Dataset

    • kaggle.com
    zip
    Updated Nov 13, 2022
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    Meir Nizri (2022). COVID-19 Dataset [Dataset]. https://www.kaggle.com/datasets/meirnizri/covid19-dataset
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    zip(4890659 bytes)Available download formats
    Dataset updated
    Nov 13, 2022
    Authors
    Meir Nizri
    License

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

    Description

    Context

    Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people, and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illness. During the entire course of the pandemic, one of the main problems that healthcare providers have faced is the shortage of medical resources and a proper plan to efficiently distribute them. In these tough times, being able to predict what kind of resource an individual might require at the time of being tested positive or even before that will be of immense help to the authorities as they would be able to procure and arrange for the resources necessary to save the life of that patient.

    The main goal of this project is to build a machine learning model that, given a Covid-19 patient's current symptom, status, and medical history, will predict whether the patient is in high risk or not.

    content

    The dataset was provided by the Mexican government (link). This dataset contains an enormous number of anonymized patient-related information including pre-conditions. The raw dataset consists of 21 unique features and 1,048,576 unique patients. In the Boolean features, 1 means "yes" and 2 means "no". values as 97 and 99 are missing data.

    • sex: 1 for female and 2 for male.
    • age: of the patient.
    • classification: covid test findings. Values 1-3 mean that the patient was diagnosed with covid in different degrees. 4 or higher means that the patient is not a carrier of covid or that the test is inconclusive.
    • patient type: type of care the patient received in the unit. 1 for returned home and 2 for hospitalization.
    • pneumonia: whether the patient already have air sacs inflammation or not.
    • pregnancy: whether the patient is pregnant or not.
    • diabetes: whether the patient has diabetes or not.
    • copd: Indicates whether the patient has Chronic obstructive pulmonary disease or not.
    • asthma: whether the patient has asthma or not.
    • inmsupr: whether the patient is immunosuppressed or not.
    • hypertension: whether the patient has hypertension or not.
    • cardiovascular: whether the patient has heart or blood vessels related disease.
    • renal chronic: whether the patient has chronic renal disease or not.
    • other disease: whether the patient has other disease or not.
    • obesity: whether the patient is obese or not.
    • tobacco: whether the patient is a tobacco user.
    • usmr: Indicates whether the patient treated medical units of the first, second or third level.
    • medical unit: type of institution of the National Health System that provided the care.
    • intubed: whether the patient was connected to the ventilator.
    • icu: Indicates whether the patient had been admitted to an Intensive Care Unit.
    • date died: If the patient died indicate the date of death, and 9999-99-99 otherwise.
  2. g

    Coronavirus (Covid-19) Data in the United States

    • github.com
    • openicpsr.org
    • +4more
    csv
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://github.com/nytimes/covid-19-data
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    csvAvailable download formats
    Dataset provided by
    New York Times
    License

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

    Description

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

    Since the first reported coronavirus case in Washington State on Jan. 21, 2020, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

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

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

  3. Chicago COVID-19 Dataset

    • kaggle.com
    zip
    Updated Jul 20, 2022
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    Ryan Park (2022). Chicago COVID-19 Dataset [Dataset]. https://www.kaggle.com/datasets/ryandpark/chicago-covid19-dataset
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    zip(12812 bytes)Available download formats
    Dataset updated
    Jul 20, 2022
    Authors
    Ryan Park
    License

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

    Area covered
    Chicago
    Description

    Description Source data: https://www.chicago.gov/city/en/sites/covid-19/home/latest-data.html.

    Only Chicago residents are included based on the home ZIP Code as provided by the medical provider. If a ZIP was missing or was not valid, it is displayed as "Unknown".

    Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the week the test specimen was collected. For privacy reasons, until a ZIP Code reaches five cumulative cases, both the weekly and cumulative case counts will be blank. Therefore, summing the “Cases - Weekly” column is not a reliable way to determine case totals. Deaths are those that have occurred among cases based on the week of death.

    For tests, each test is counted once, based on the week the test specimen was collected. Tests performed prior to 3/1/2020 are not included. Test counts include multiple tests for the same person (a change made on 10/29/2020). PCR and antigen tests reported to Chicago Department of Public Health (CDPH) through electronic lab reporting are included. Electronic lab reporting has taken time to onboard and testing availability has shifted over time, so these counts are likely an underestimate of community infection.

    The “Percent Tested Positive” columns are calculated by dividing the number of positive tests by the number of total tests . Because of the data limitations for the Tests columns, such as persons being tested multiple times as a requirement for employment, these percentages may vary in either direction from the actual disease prevalence in the ZIP Code.

    All data are provisional and subject to change. Information is updated as additional details are received.

    To compare ZIP Codes to Chicago Community Areas, please see http://data.cmap.illinois.gov/opendata/uploads/CKAN/NONCENSUS/ADMINISTRATIVE_POLITICAL_BOUNDARIES/CCAzip.pdf. Both ZIP Codes and Community Areas are also geographic datasets on this data portal.

    Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, Illinois Vital Records, American Community Survey (2018)

  4. COVID 19 Dataset

    • kaggle.com
    zip
    Updated Oct 23, 2024
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    Rhona Rose Cortez (2024). COVID 19 Dataset [Dataset]. https://www.kaggle.com/datasets/rhonarosecortez/covid-19-dataset
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    zip(10774892 bytes)Available download formats
    Dataset updated
    Oct 23, 2024
    Authors
    Rhona Rose Cortez
    License

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

    Description

    Description:

    This comprehensive dataset provides global information on both COVID-19 related deaths and vaccinations from January 5, 2020, to August 4, 2024. It consists of two parts: one tracking COVID-19 cases, deaths, and population statistics, and another monitoring vaccination progress worldwide. This dataset allows for an in-depth analysis of the pandemic’s spread, fatality rates, and the effectiveness of vaccination campaigns across various countries and regions.

    Researchers and data analysts can use this dataset to study trends, compare countries, and evaluate public health responses throughout the COVID-19 pandemic.

    Includes:

    CovidDeaths Dataset: Records of total cases, deaths, and population.

    CovidVaccinations Dataset: Records of daily vaccination counts and cumulative totals.

    Use Cases:

    Analyzing death rates relative to confirmed cases. Examining the percentage of population affected by COVID-19. Evaluating vaccination rates and coverage across different regions. This dataset is ideal for data exploration, statistical analysis, and visualizations related to the COVID-19 pandemic.

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

    • catalog.data.gov
    • data.virginia.gov
    • +5more
    Updated May 8, 2021
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    Centers for Disease Control and Prevention (2021). COVID-19 Case Surveillance Public Use Data with Geography [Dataset]. https://catalog.data.gov/dataset/covid-19-case-surveillance-public-use-data-with-geography-0605b
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    Dataset updated
    May 8, 2021
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    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 32 data element restricted access dataset. The following apply to the public use datasets and the restricted access dataset: - 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 are suppressed to protect individual privacy. - 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 ensure that time-dependent outcome data are accurately captured. - Datasets are updated monthly. - Datasets are created using CDC’s 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 wwwn.cdc.gov/nndss/data-collection.html. - For more information about the COVID-19 case surveillance data, please see www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html. Overview The COVID-19 case surveillance database includes patient-level data reported by 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 (Interim-20-ID-02). 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 collected by jurisdictions are shared voluntarily with CDC. For more information, visit: wwwn.cdc.gov/nndss/conditions/coronavirus-disease-2019-covid-19/case-definition/2020/08/05/. COVID-19 Case Reports COVID-19 case reports are routinely submitted to CDC by pu

  6. d

    Johns Hopkins COVID-19 Case Tracker

    • data.world
    • kaggle.com
    csv, zip
    Updated Dec 3, 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
    Dec 3, 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. Public Health Infobase - Data on COVID-19 in Canada

    • open.canada.ca
    • datasets.ai
    csv
    Updated Nov 21, 2024
    + more versions
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    Public Health Agency of Canada (2024). Public Health Infobase - Data on COVID-19 in Canada [Dataset]. https://open.canada.ca/data/en/dataset/261c32ab-4cfd-4f81-9dea-7b64065690dc
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 21, 2024
    Dataset provided by
    Public Health Agency Of Canadahttp://www.phac-aspc.gc.ca/
    License

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

    Area covered
    Canada
    Description

    The data contained in the table describes COVID-19 in Canada in terms of number of cases and deaths at the provincial and national levels from January 31, 2020 to present time. It also describes the number of tests performed and the number of people recovered. The values displayed in the table are provided by the Public Health Infobase, managed by the Health Promotion and Chronic Disease Prevention Branch (HPCDPB) of the Public Health Agency of Canada (PHAC). The values are updated daily.

  8. B

    COVID-19 Twitter Dataset

    • borealisdata.ca
    • figshare.com
    Updated Nov 10, 2020
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    Anatoliy Gruzd; Philip Mai (2020). COVID-19 Twitter Dataset [Dataset]. http://doi.org/10.5683/SP2/PXF2CU
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 10, 2020
    Dataset provided by
    Borealis
    Authors
    Anatoliy Gruzd; Philip Mai
    License

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

    Description

    The current dataset contains 237M Tweet IDs for Twitter posts that mentioned "COVID" as a keyword or as part of a hashtag (e.g., COVID-19, COVID19) between March and July of 2020. Sampling Method: hourly requests sent to Twitter Search API using Social Feed Manager, an open source software that harvests social media data and related content from Twitter and other platforms. NOTE: 1) In accordance with Twitter API Terms, only Tweet IDs are provided as part of this dataset. 2) To recollect tweets based on the list of Tweet IDs contained in these datasets, you will need to use tweet 'rehydration' programs like Hydrator (https://github.com/DocNow/hydrator) or Python library Twarc (https://github.com/DocNow/twarc). 3) This dataset, like most datasets collected via the Twitter Search API, is a sample of the available tweets on this topic and is not meant to be comprehensive. Some COVID-related tweets might not be included in the dataset either because the tweets were collected using a standardized but intermittent (hourly) sampling protocol or because tweets used hashtags/keywords other than COVID (e.g., Coronavirus or #nCoV). 4) To broaden this sample, consider comparing/merging this dataset with other COVID-19 related public datasets such as: https://github.com/thepanacealab/covid19_twitter https://ieee-dataport.org/open-access/corona-virus-covid-19-tweets-dataset https://github.com/echen102/COVID-19-TweetIDs

  9. n

    COVID-19 Open Research Dataset

    • neuinfo.org
    • scicrunch.org
    • +2more
    Updated Aug 11, 2024
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    (2024). COVID-19 Open Research Dataset [Dataset]. http://identifiers.org/RRID:SCR_018336
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    Dataset updated
    Aug 11, 2024
    Description

    Collection of scholarly articles about COVID-19 and coronavirus family of viruses for use by global research community. Dataset is updated on weekly basis.

  10. COVID-19 Outbreak Data (ARCHIVED)

    • data.chhs.ca.gov
    • data.ca.gov
    • +2more
    csv, zip
    Updated Nov 7, 2025
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    California Department of Public Health (2025). COVID-19 Outbreak Data (ARCHIVED) [Dataset]. https://data.chhs.ca.gov/dataset/covid-19-outbreak-data
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    zip, csv(62919), csv(326192)Available download formats
    Dataset updated
    Nov 7, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    Note: This dataset is no longer being updated as of June 2, 2025.

    This dataset contains numbers of COVID-19 outbreaks and associated cases, categorized by setting, reported to CDPH since January 1, 2021.

    AB 685 (Chapter 84, Statutes of 2020) and the Cal/OSHA COVID-19 Emergency Temporary Standards (Title 8, Subchapter 7, Sections 3205-3205.4) required non-healthcare employers in California to report workplace COVID-19 outbreaks to their local health department (LHD) between January 1, 2021 – December 31, 2022. Beginning January 1, 2023, non-healthcare employer reporting of COVID-19 outbreaks to local health departments is voluntary, unless a local order is in place. More recent data collected without mandated reporting may therefore be less representative of all outbreaks that have occurred, compared to earlier data collected during mandated reporting. Licensed health facilities continue to be mandated to report outbreaks to LHDs.

    LHDs report confirmed outbreaks to the California Department of Public Health (CDPH) via the California Reportable Disease Information Exchange (CalREDIE), the California Connected (CalCONNECT) system, or other established processes. Data are compiled and categorized by setting by CDPH. Settings are categorized by U.S. Census industry codes. Total outbreaks and cases are included for individual industries as well as for broader industrial sectors.

    The first dataset includes numbers of outbreaks in each setting by month of onset, for outbreaks reported to CDPH since January 1, 2021. This dataset includes some outbreaks with onset prior to January 1 that were reported to CDPH after January 1; these outbreaks are denoted with month of onset “Before Jan 2021.” The second dataset includes cumulative numbers of COVID-19 outbreaks with onset after January 1, 2021, categorized by setting. Due to reporting delays, the reported numbers may not reflect all outbreaks that have occurred as of the reporting date; additional outbreaks may have occurred that have not yet been reported to CDPH.

    While many of these settings are workplaces, cases may have occurred among workers, other community members who visited the setting, or both. Accordingly, these data do not distinguish between outbreaks involving only workers, outbreaks involving only residents or patrons, or outbreaks involving both.

    Several additional data limitations should be kept in mind:

    • Outbreaks are classified as “Insufficient information” for outbreaks where not enough information was available for CDPH to assign an industry code.

    • Some sectors, particularly congregate residential settings, may have increased testing and therefore increased likelihood of outbreak recognition and reporting. As a result, in congregate residential settings, the number of outbreak-associated cases may be more accurate.

    • However, in most settings, outbreak and case counts are likely underestimates. For most cases, it is not possible to identify the source of exposure, as many cases have multiple possible exposures.

    • Because some settings have been at times been closed or open with capacity restrictions, numbers of outbreak reports in those settings do not reflect COVID-19 transmission risk.

    • The number of outbreaks in different settings will depend on the number of different workplaces in each setting. More outbreaks would be expected in settings with many workplaces compared to settings with few workplaces.

  11. d

    COVID-19 County Level Data - Archive

    • catalog.data.gov
    • data.ct.gov
    • +1more
    Updated Jun 21, 2025
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    data.ct.gov (2025). COVID-19 County Level Data - Archive [Dataset]. https://catalog.data.gov/dataset/covid-19-county-level-data
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    Dataset updated
    Jun 21, 2025
    Dataset provided by
    data.ct.gov
    Description

    Covid-19 Daily metrics at the county level As of 6/1/2023, this data set is no longer being updated. The COVID-19 Data Report is posted on the Open Data Portal every day at 3pm. The report uses data from multiple sources, including external partners; if data from external partners are not received by 3pm, they are not available for inclusion in the report and will not be displayed. Data that are received after 3pm will still be incorporated and published in the next report update. The cumulative number of COVID-19 cases (cumulative_cases) includes all cases of COVID-19 that have ever been reported to DPH. The cumulative number of COVID_19 cases in the last 7 days (cases_7days) only includes cases where the specimen collection date is within the past 7 days. While most cases are reported to DPH within 48 hours of specimen collection, there are a small number of cases that routinely are delayed, and will have specimen collection dates that fall outside of the rolling 7 day reporting window. Additionally, reporting entities may submit correction files to contribute historic data during initial onboarding or to address data quality issues; while this is rare, these correction files may cause a large amount of data from outside of the current reporting window to be uploaded in a single day; this would result in the change in cumulative_cases being much larger than the value of cases_7days. On June 4, 2020, the US Department of Health and Human Services issued guidance requiring the reporting of positive and negative test results for SARS-CoV-2; this guidance expired with the end of the federal PHE on 5/11/2023, and negative SARS-CoV-2 results were removed from the List of Reportable Laboratory Findings. DPH will no longer be reporting metrics that were dependent on the collection of negative test results, specifically total tests performed or percent positivity. Positive antigen and PCR/NAAT results will continue to be reportable.

  12. i

    COVID-19 dataset 3 classes

    • ieee-dataport.org
    Updated Jul 1, 2020
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    Vaishnavi Jamdade (2020). COVID-19 dataset 3 classes [Dataset]. https://ieee-dataport.org/documents/covid-19-dataset-3-classes
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    Dataset updated
    Jul 1, 2020
    Authors
    Vaishnavi Jamdade
    License

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

    Description

    The rapid outbreak of COVID-19 due to the novel coronavirus SARS-COV-2 is the biggest issue faced by mankind today. It is important to detect the positive cases as early as possible to prevent the further spread of this pandemic.

  13. d

    CMS COVID-19 Nursing Home Dataset

    • catalog.data.gov
    • data.ct.gov
    • +2more
    Updated Sep 27, 2025
    + more versions
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    data.ct.gov (2025). CMS COVID-19 Nursing Home Dataset [Dataset]. https://catalog.data.gov/dataset/cms-covid-19-nursing-home-dataset
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    Dataset updated
    Sep 27, 2025
    Dataset provided by
    data.ct.gov
    Description

    The Nursing Home COVID-19 Public File from the Centers for Medicare & Medicaid Services, filtered for Connecticut. View the full dataset and detailed metadata here. The Nursing Home COVID-19 Public File includes data reported by nursing homes to the CDC’s National Healthcare Safety Network (NHSN) system COVID-19 Long Term Care Facility Module, including Resident Impact, Facility Capacity, Staff & Personnel, and Supplies & Personal Protective Equipment, and Ventilator Capacity and Supplies Data Elements.

  14. COVID-19 in Italy

    • kaggle.com
    zip
    Updated Dec 7, 2020
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    SRK (2020). COVID-19 in Italy [Dataset]. https://www.kaggle.com/datasets/sudalairajkumar/covid19-in-italy
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    zip(451901 bytes)Available download formats
    Dataset updated
    Dec 7, 2020
    Authors
    SRK
    License

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

    Area covered
    Italy
    Description

    Context

    Coronaviruses are a large family of viruses which may cause illness in animals or humans. In humans, several coronaviruses are known to cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). The most recently discovered coronavirus causes coronavirus disease COVID-19 - WHO

    People can catch COVID-19 from others who have the virus. This has been spreading rapidly around the world and Italy is one of the most affected country.

    On March 8, 2020 - Italy’s prime minister announced a sweeping coronavirus quarantine early Sunday, restricting the movements of about a quarter of the country’s population in a bid to limit contagions at the epicenter of Europe’s outbreak. - TIME

    Content

    This dataset is from https://github.com/pcm-dpc/COVID-19 collected by Sito del Dipartimento della Protezione Civile - Emergenza Coronavirus: la risposta nazionale

    This dataset has two files

    • covid19_italy_province.csv - Province level data of COVID-19 cases
    • covid_italy_region.csv - Region level data of COVID-19 cases

    Acknowledgements

    Data is collected by Sito del Dipartimento della Protezione Civile - Emergenza Coronavirus: la risposta nazionale and is uploaded into this github repo.

    Dashboard on the data can be seen here. Picture courtesy is from the dashboard.

    Inspiration

    Insights on * Spread to various regions over time * Try to predict the spread of COVID-19 ahead of time to take preventive measures

  15. COVID-19 Global Dataset

    • kaggle.com
    zip
    Updated Jun 2, 2024
    + more versions
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    Saikat Sinha Ray (2024). COVID-19 Global Dataset [Dataset]. https://www.kaggle.com/datasets/saikatsray/covid-19-global-dataset
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    zip(542392 bytes)Available download formats
    Dataset updated
    Jun 2, 2024
    Authors
    Saikat Sinha Ray
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Saikat Sinha Ray

    Released under Apache 2.0

    Contents

  16. COVID-19 State Profile Report - Nevada

    • healthdata.gov
    • data.virginia.gov
    • +2more
    csv, xlsx, xml
    Updated Jan 27, 2021
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    White House COVID-19 Team, Joint Coordination Cell, Data Strategy and Execution Workgroup (2021). COVID-19 State Profile Report - Nevada [Dataset]. https://healthdata.gov/Community/COVID-19-State-Profile-Report-Nevada/ym2i-z2sf
    Explore at:
    csv, xlsx, xmlAvailable download formats
    Dataset updated
    Jan 27, 2021
    Dataset authored and provided by
    White House COVID-19 Team, Joint Coordination Cell, Data Strategy and Execution Workgroup
    License

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

    Area covered
    Nevada
    Description

    After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.

    The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level.

    It is a weekly snapshot in time that:

    • Focuses on recent outcomes in the last seven days and changes relative to the month prior
    • Provides additional contextual information at the county level for each state, and includes national level information
    • Supports rapid visual interpretation of results with color thresholds

  17. United States COVID-19 Community Levels by County

    • datalumos.org
    • healthdata.gov
    • +2more
    delimited
    Updated Oct 16, 2025
    + more versions
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    United States Department of Health and Human Services. Centers for Disease Control and Prevention (2025). United States COVID-19 Community Levels by County [Dataset]. http://doi.org/10.3886/E238954V1
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    delimitedAvailable download formats
    Dataset updated
    Oct 16, 2025
    Authors
    United States Department of Health and Human Services. Centers for Disease Control and Prevention
    License

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

    Area covered
    United States
    Description

    Reporting of Aggregate Case and Death Count data was discontinued 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.This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.Using these data, the COVID-19 community level was classified as low, medium, or high.COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.Archived Data Notes:This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflect

  18. d

    COVID-19 Time Series Data

    • data.world
    • kaggle.com
    csv, zip
    Updated Mar 18, 2025
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    Shad Reynolds (2025). COVID-19 Time Series Data [Dataset]. https://data.world/shad/covid-19-time-series-data
    Explore at:
    csv, zipAvailable download formats
    Dataset updated
    Mar 18, 2025
    Authors
    Shad Reynolds
    Time period covered
    Jan 22, 2020 - Mar 9, 2023
    Area covered
    Description

    This data is synced hourly from https://github.com/CSSEGISandData/COVID-19. All credit is to them.

    Latest Confirmed Cases

    @(https://data.world/shad/covid-analysis/workspace/query?datasetid=covid-19-time-series-data&queryid=e066701e-fa8d-4c9f-97f8-aab3a6f219a8)

    I have also added confirmed_pivot.csv which gives a slightly more workable view of the data. Extra columns/day makes things difficult.

    @(https://data.world/shad/covid-analysis/workspace/file?datasetid=covid-19-time-series-data&filename=confirmed_pivot)

    #

  19. d

    COVID-19 Daily Counts of Cases, Hospitalizations, and Deaths

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Nov 29, 2025
    + more versions
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    data.cityofnewyork.us (2025). COVID-19 Daily Counts of Cases, Hospitalizations, and Deaths [Dataset]. https://catalog.data.gov/dataset/covid-19-daily-counts-of-cases-hospitalizations-and-deaths
    Explore at:
    Dataset updated
    Nov 29, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    Daily count of NYC residents who tested positive for SARS-CoV-2, who were hospitalized with COVID-19, and deaths among COVID-19 patients. Note that this dataset currently pulls from https://raw.githubusercontent.com/nychealth/coronavirus-data/master/trends/data-by-day.csv on a daily basis.

  20. D

    Archive: COVID-19 Vaccination and Case Trends by Age Group, United States

    • data.cdc.gov
    • healthdata.gov
    • +2more
    csv, xlsx, xml
    Updated Oct 14, 2022
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    IISInfo (2022). Archive: COVID-19 Vaccination and Case Trends by Age Group, United States [Dataset]. https://data.cdc.gov/Vaccinations/Archive-COVID-19-Vaccination-and-Case-Trends-by-Ag/gxj9-t96f
    Explore at:
    xlsx, xml, csvAvailable download formats
    Dataset updated
    Oct 14, 2022
    Dataset authored and provided by
    IISInfo
    License

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

    Description

    After October 13, 2022, this dataset will no longer be updated as the related CDC COVID Data Tracker site was retired on October 13, 2022.

    This dataset contains historical trends in vaccinations and cases by age group, at the US national level. Data is stratified by at least one dose and fully vaccinated. Data also represents all vaccine partners including jurisdictional partner clinics, retail pharmacies, long-term care facilities, dialysis centers, Federal Emergency Management Agency and Health Resources and Services Administration partner sites, and federal entity facilities.

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Meir Nizri (2022). COVID-19 Dataset [Dataset]. https://www.kaggle.com/datasets/meirnizri/covid19-dataset
Organization logo

COVID-19 Dataset

COVID-19 patient's symptoms, status, and medical history.

Explore at:
28 scholarly articles cite this dataset (View in Google Scholar)
zip(4890659 bytes)Available download formats
Dataset updated
Nov 13, 2022
Authors
Meir Nizri
License

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

Description

Context

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people, and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illness. During the entire course of the pandemic, one of the main problems that healthcare providers have faced is the shortage of medical resources and a proper plan to efficiently distribute them. In these tough times, being able to predict what kind of resource an individual might require at the time of being tested positive or even before that will be of immense help to the authorities as they would be able to procure and arrange for the resources necessary to save the life of that patient.

The main goal of this project is to build a machine learning model that, given a Covid-19 patient's current symptom, status, and medical history, will predict whether the patient is in high risk or not.

content

The dataset was provided by the Mexican government (link). This dataset contains an enormous number of anonymized patient-related information including pre-conditions. The raw dataset consists of 21 unique features and 1,048,576 unique patients. In the Boolean features, 1 means "yes" and 2 means "no". values as 97 and 99 are missing data.

  • sex: 1 for female and 2 for male.
  • age: of the patient.
  • classification: covid test findings. Values 1-3 mean that the patient was diagnosed with covid in different degrees. 4 or higher means that the patient is not a carrier of covid or that the test is inconclusive.
  • patient type: type of care the patient received in the unit. 1 for returned home and 2 for hospitalization.
  • pneumonia: whether the patient already have air sacs inflammation or not.
  • pregnancy: whether the patient is pregnant or not.
  • diabetes: whether the patient has diabetes or not.
  • copd: Indicates whether the patient has Chronic obstructive pulmonary disease or not.
  • asthma: whether the patient has asthma or not.
  • inmsupr: whether the patient is immunosuppressed or not.
  • hypertension: whether the patient has hypertension or not.
  • cardiovascular: whether the patient has heart or blood vessels related disease.
  • renal chronic: whether the patient has chronic renal disease or not.
  • other disease: whether the patient has other disease or not.
  • obesity: whether the patient is obese or not.
  • tobacco: whether the patient is a tobacco user.
  • usmr: Indicates whether the patient treated medical units of the first, second or third level.
  • medical unit: type of institution of the National Health System that provided the care.
  • intubed: whether the patient was connected to the ventilator.
  • icu: Indicates whether the patient had been admitted to an Intensive Care Unit.
  • date died: If the patient died indicate the date of death, and 9999-99-99 otherwise.
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