100+ datasets found
  1. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +4more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

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

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

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

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

  2. COVID-19 Global Case and Death Data

    • kaggle.com
    zip
    Updated Dec 4, 2023
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    The Devastator (2023). COVID-19 Global Case and Death Data [Dataset]. https://www.kaggle.com/datasets/thedevastator/covid-19-global-case-and-death-data
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    zip(81724234 bytes)Available download formats
    Dataset updated
    Dec 4, 2023
    Authors
    The Devastator
    Description

    COVID-19 Global Case and Death Data

    Global COVID-19 Cases and Deaths Over Time

    By Coronavirus (COVID-19) Data Hub [source]

    About this dataset

    The COVID-19 Global Time Series Case and Death Data is a comprehensive collection of global COVID-19 case and death information recorded over time. This dataset includes data from various sources such as JHU CSSE COVID-19 Data and The New York Times.

    The dataset consists of several columns providing detailed information on different aspects of the COVID-19 situation. The COUNTRY_SHORT_NAME column represents the short name of the country where the data is recorded, while the Data_Source column indicates the source from which the data was obtained.

    Other important columns include Cases, which denotes the number of COVID-19 cases reported, and Difference, which indicates the difference in case numbers compared to the previous day. Additionally, there are columns such as CONTINENT_NAME, DATA_SOURCE_NAME, COUNTRY_ALPHA_3_CODE, COUNTRY_ALPHA_2_CODE that provide additional details about countries and continents.

    Furthermore, this dataset also includes information on deaths related to COVID-19. The column PEOPLE_DEATH_NEW_COUNT shows the number of new deaths reported on a specific date.

    To provide more context to the data, certain columns offer demographic details about locations. For instance, Population_Count provides population counts for different areas. Moreover,**FIPS** code is available for provincial/state regions for identification purposes.

    It is important to note that this dataset covers both confirmed cases (Case_Type: confirmed) as well as probable cases (Case_Type: probable). These classifications help differentiate between various types of COVID-19 infections.

    Overall, this dataset offers a comprehensive picture of global COVID-19 situations by providing accurate and up-to-date information on cases, deaths, demographic details like population count or FIPS code), source references (such as JHU CSSE or NY Times), geographical information (country names coded with ALPHA codes) , etcetera making it useful for researchers studying patterns and trends associated with this pandemic

    How to use the dataset

    • Understanding the Dataset Structure:

      • The dataset is available in two files: COVID-19 Activity.csv and COVID-19 Cases.csv.
      • Both files contain different columns that provide information about the COVID-19 cases and deaths.
      • Some important columns to look out for are: a. PEOPLE_POSITIVE_CASES_COUNT: The total number of confirmed positive COVID-19 cases. b. COUNTY_NAME: The name of the county where the data is recorded. c. PROVINCE_STATE_NAME: The name of the province or state where the data is recorded. d. REPORT_DATE: The date when the data was reported. e. CONTINENT_NAME: The name of the continent where the data is recorded. f. DATA_SOURCE_NAME: The name of the data source. g. PEOPLE_DEATH_NEW_COUNT: The number of new deaths reported on a specific date. h.COUNTRY_ALPHA_3_CODE :The three-letter alpha code represents country f.Lat,Long :latitude and longitude coordinates represent location i.Country_Region or COUNTRY_SHORT_NAME:The country or region where cases were reported.
    • Choosing Relevant Columns: It's important to determine which columns are relevant to your analysis or research question before proceeding with further analysis.

    • Exploring Data Patterns: Use various statistical techniques like summarizing statistics, creating visualizations (e.g., bar charts, line graphs), etc., to explore patterns in different variables over time or across regions/countries.

    • Filtering Data: You can filter your dataset based on specific criteria using column(s) such as COUNTRY_SHORT_NAME, CONTINENT_NAME, or PROVINCE_STATE_NAME to focus on specific countries, continents, or regions of interest.

    • Combining Data: You can combine data from different sources (e.g., COVID-19 cases and deaths) to perform advanced analysis or create insightful visualizations.

    • Analyzing Trends: Use the dataset to analyze and identify trends in COVID-19 cases and deaths over time. You can examine factors such as population count, testing count, hospitalization count, etc., to gain deeper insights into the impact of the virus.

    • Comparing Countries/Regions: Compare COVID-19

    Research Ideas

    • Trend Analysis: This dataset can be used to analyze and track the trends of COVID-19 cases and deaths over time. It provides comprehensive global data, allowing researchers and po...
  3. COVID-19 Deaths Over Time

    • healthdata.gov
    • data.sfgov.org
    • +2more
    csv, xlsx, xml
    Updated Apr 8, 2025
    + more versions
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    data.sfgov.org (2025). COVID-19 Deaths Over Time [Dataset]. https://healthdata.gov/dataset/COVID-19-Deaths-Over-Time/mjyp-v9dd
    Explore at:
    csv, xml, xlsxAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    data.sfgov.org
    Description

    A. SUMMARY This dataset represents San Francisco COVID-19 related deaths by day. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable.

    B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death data is provided by the California Department of Public Health.

    It takes time to process this data. Because of this, death totals may increase or decrease over time.

    Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

    C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

    Dataset will not update on the business day following any federal holiday.

    D. HOW TO USE THIS DATASET This dataset shows new deaths and cumulative deaths by date of death. New deaths are the count of deaths on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths up to the date listed.

    Use the Deaths by Population Characteristics Over Time dataset to see deaths by different subgroups including race/ethnicity, age, and gender.

    E. CHANGE LOG

    • 9/11/2023 – on this date, we began using an updated definition of a COVID-19 death to align with the California Department of Public Health. This change was applied to COVID-19 deaths retrospectively beginning on 1/1/2023. More information about the recommendation by the Council of State and Territorial Epidemiologists that motivated this change can be found https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">here.
    • 4/6/2023 - the State implemented system updates to improve the integrity of historical data.
    • 1/22/2022 - system updates to improve timeliness and accuracy of cases and deaths data were implemented.

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

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

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

    The difficulties of death figures

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

    Where are these numbers coming from?

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

  5. D

    COVID-19 Deaths by Population Characteristics

    • data.sfgov.org
    • healthdata.gov
    • +2more
    csv, xlsx, xml
    Updated Nov 20, 2025
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    (2025). COVID-19 Deaths by Population Characteristics [Dataset]. https://data.sfgov.org/w/kv9m-37qh/ikek-yizv?cur=Cz9wSjj1-K4&from=root
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Nov 20, 2025
    Description

    A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals may increase or decrease.

    Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

    B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

    Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

    Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

    To protect resident privacy, we summarize COVID-19 data by only one population characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

    Data notes on select population characteristic types are listed below.

    Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

    Gender * The City collects information on gender identity using these guidelines.

    C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

    Dataset will not update on the business day following any federal holiday.

    D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a dataset based on the San Francisco Population and Demographic Census dataset.These population estimates are from the 2018-2022 5-year American Community Survey (ACS).

    This dataset includes several characteristic types. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of cumulative deaths.

    Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

    To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

    E. CHANGE LOG

  6. COVID-19 Time-Series Metrics by County and State (ARCHIVED)

    • data.chhs.ca.gov
    • data.ca.gov
    • +3more
    csv, xlsx, zip
    Updated Nov 7, 2025
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    California Department of Public Health (2025). COVID-19 Time-Series Metrics by County and State (ARCHIVED) [Dataset]. https://data.chhs.ca.gov/dataset/covid-19-time-series-metrics-by-county-and-state
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    csv(7729431), csv(6223281), xlsx(11305), xlsx(7811), csv(3313), csv(4836928), xlsx(6471), zipAvailable download formats
    Dataset updated
    Nov 7, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    Note: This COVID-19 data set is no longer being updated as of December 1, 2023. Access current COVID-19 data on the CDPH respiratory virus dashboard (https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx) or in open data format (https://data.chhs.ca.gov/dataset/respiratory-virus-dashboard-metrics).

    As of August 17, 2023, data is being updated each Friday.

    For death data after December 31, 2022, California uses Provisional Deaths from the Center for Disease Control and Prevention’s National Center for Health Statistics (NCHS) National Vital Statistics System (NVSS). Prior to January 1, 2023, death data was sourced from the COVID-19 registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023.

    As of May 11, 2023, data on cases, deaths, and testing is being updated each Thursday. Metrics by report date have been removed, but previous versions of files with report date metrics are archived below.

    All metrics include people in state and federal prisons, US Immigration and Customs Enforcement facilities, US Marshal detention facilities, and Department of State Hospitals facilities. Members of California's tribal communities are also included.

    The "Total Tests" and "Positive Tests" columns show totals based on the collection date. There is a lag between when a specimen is collected and when it is reported in this dataset. As a result, the most recent dates on the table will temporarily show NONE in the "Total Tests" and "Positive Tests" columns. This should not be interpreted as no tests being conducted on these dates. Instead, these values will be updated with the number of tests conducted as data is received.

  7. US Covid Deaths By State Over Time

    • kaggle.com
    zip
    Updated Jul 4, 2021
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    David Roberts (2021). US Covid Deaths By State Over Time [Dataset]. https://www.kaggle.com/davidbroberts/us-covid-deaths-by-state-over-time
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    zip(783961 bytes)Available download formats
    Dataset updated
    Jul 4, 2021
    Authors
    David Roberts
    License

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

    Area covered
    United States
    Description

    Covid 19 Deaths by US state.

    CDC reports aggregate counts of COVID-19 cases and death numbers daily online. Data on the COVID-19 website and CDC’s COVID Data Tracker are based on these most recent numbers reported by states, territories, and other jurisdictions. This data set of “United States COVID-19 Cases and Deaths by State over Time” combines this information. However, data are dependent on jurisdictions’ timely and accurate reporting.

    This data was downloaded from the CDC website -> https://data.cdc.gov/Case-Surveillance/United-States-COVID-19-Cases-and-Deaths-by-State-o/9mfq-cb36

    It contains 31.7K rows and 15 columns of data with counts of suspected and confirmed deaths by Covid 19 in the US during the pandemic.

    Date ranges are from Jan 2020 to July 2021

    Thanks to https://unsplash.com/@fusion_medical_animation for the splash pic.

  8. [Archived] COVID-19 Deaths by Population Characteristics Over Time

    • healthdata.gov
    • data.sfgov.org
    • +1more
    csv, xlsx, xml
    Updated Apr 8, 2025
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    data.sfgov.org (2025). [Archived] COVID-19 Deaths by Population Characteristics Over Time [Dataset]. https://healthdata.gov/dataset/-Archived-COVID-19-Deaths-by-Population-Characteri/hs5f-amst
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    xml, csv, xlsxAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    data.sfgov.org
    Description

    As of July 2nd, 2024 the COVID-19 Deaths by Population Characteristics Over Time dataset has been retired. This dataset is archived and will no longer update. We will be publishing a cumulative deaths by population characteristics dataset that will update moving forward.

    A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable.

    Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

    B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

    Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

    Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

    To protect resident privacy, we summarize COVID-19 data by only one characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

    Data notes on each population characteristic type is listed below.

    Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

    Gender * The City collects information on gender identity using these guidelines.

    C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

    Dataset will not update on the business day following any federal holiday.

    D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).

    This dataset includes many different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of deaths on each date.

    New deaths are the count of deaths within that characteristic group on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

    This data may not be immediately available for more recent deaths. Data updates as more information becomes available.

    To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

    E. CHANGE LOG

    • 9/11/2023 - on this date, we began using an updated definition of a COVID-19 death to align with the California Department o

  9. COVID-19 deaths reported in the U.S. as of June 14, 2023, by age

    • statista.com
    + more versions
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    Statista, COVID-19 deaths reported in the U.S. as of June 14, 2023, by age [Dataset]. https://www.statista.com/statistics/1191568/reported-deaths-from-covid-by-age-us/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2020 - Jun 14, 2023
    Area covered
    United States
    Description

    Between the beginning of January 2020 and June 14, 2023, of the 1,134,641 deaths caused by COVID-19 in the United States, around 307,169 had occurred among those aged 85 years and older. This statistic shows the number of coronavirus disease 2019 (COVID-19) deaths in the U.S. from January 2020 to June 2023, by age.

  10. Number of COVID-19 deaths in the United States from 2020 to 2022, by year

    • statista.com
    + more versions
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    Statista, Number of COVID-19 deaths in the United States from 2020 to 2022, by year [Dataset]. https://www.statista.com/statistics/1382334/number-covid-deaths-us-by-year/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2020, there were around ******* deaths in the United States caused by COVID-19, compared to ******* COVID-19 deaths in 2021. This statistic shows the total number of deaths due to COVID-19 in the United States in 2020, 2021, and 2022.

  11. d

    COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical

    • catalog.data.gov
    • data.cityofchicago.org
    • +2more
    Updated May 24, 2024
    + more versions
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    data.cityofchicago.org (2024). COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical [Dataset]. https://catalog.data.gov/dataset/covid-19-cases-tests-and-deaths-by-zip-code
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    Dataset updated
    May 24, 2024
    Dataset provided by
    data.cityofchicago.org
    Description

    NOTE: This dataset has been retired and marked as historical-only. 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)

  12. T

    CORONAVIRUS DEATHS by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    TRADING ECONOMICS (2020). CORONAVIRUS DEATHS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/coronavirus-deaths
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    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Mar 4, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    2025
    Area covered
    World
    Description

    This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  13. T

    World Coronavirus COVID-19 Deaths

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

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

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

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

  14. New York Times Covid-19 Data (United States)

    • kaggle.com
    zip
    Updated Nov 22, 2025
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    Michael Peteuil (2025). New York Times Covid-19 Data (United States) [Dataset]. https://www.kaggle.com/datasets/mpeteuil/nytimes-covid-19-data
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    zip(162971226 bytes)Available download formats
    Dataset updated
    Nov 22, 2025
    Authors
    Michael Peteuil
    Area covered
    United States
    Description

    Source

    This data comes from the New York Times Coronavirus (Covid-19) Data in the United States GitHub repository. They use it to power their interactive page(s) on Covid-19, such as Coronavirus in the U.S.: Latest Map and Case Count.

    What's Included?

    The primary data published here are the daily cumulative number of cases and deaths reported in each county and state across the U.S. since the beginning of the pandemic. We have also published these additional data sets:

    • Prisons: Cases in prisons
    • Colleges: Cases on college and university campuses.
    • Excess deaths: The elevated overall number of deaths during the pandemic.
    • Mask use: A July 2020 survey of how regularly people in each county wore masks.
    • Averages and anomalies: A set of pre-computed rolling averages of cases and deaths for ease of analysis or use in making graphics, along with a set of days with anomalous data that have been excluded from the averages.

    The cumulative & rolling averages for cases and deaths are continually updated, but the more specific data mentioned above for prisons, etc. is no longer being updated.

    This includes data at the national, state, and county levels.

    License and Attribution

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

    Acknowledgements

    Header Image: https://www.pexels.com/photo/n95-face-mask-3993241/

    More Information

    See the original New York Times source README which is also included in this dataset.

  15. US COVID-19 Cases and Deaths by State Over Time

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). US COVID-19 Cases and Deaths by State Over Time [Dataset]. https://www.johnsnowlabs.com/marketplace/us-covid-19-cases-and-deaths-by-state-over-time/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Time period covered
    2020 - 2022
    Area covered
    United States
    Description

    This dataset shows the United States COVID-19 cases and deaths by state over time. This dataset is provided by the CDC Case Task Force.

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

    • statista.com
    Updated May 15, 2024
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    Statista (2024). COVID-19 death rates in the United States as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109011/coronavirus-covid19-death-rates-us-by-state/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

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

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

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Jan 13, 2025
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    Centers for Disease Control and Prevention (2025). Weekly United States COVID-19 Cases and Deaths by County - ARCHIVED [Dataset]. https://data.virginia.gov/dataset/weekly-united-states-covid-19-cases-and-deaths-by-county-archived
    Explore at:
    xsl, rdf, json, csvAvailable download formats
    Dataset updated
    Jan 13, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

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

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

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

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

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

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

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

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

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

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

    • statista.com
    Updated Nov 19, 2025
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    Statista (2025). COVID-19 deaths worldwide as of May 2, 2023, by country and territory [Dataset]. https://www.statista.com/statistics/1093256/novel-coronavirus-2019ncov-deaths-worldwide-by-country/
    Explore at:
    Dataset updated
    Nov 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2, 2023
    Area covered
    Worldwide
    Description

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

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

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

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

    • data.virginia.gov
    • healthdata.gov
    • +3more
    csv, json, rdf, xsl
    Updated Sep 25, 2025
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts and rates by month, jurisdiction of residence, and demographic characteristics [Dataset]. https://data.virginia.gov/dataset/provisional-covid-19-death-counts-and-rates-by-month-jurisdiction-of-residence-and-demographic-
    Explore at:
    rdf, csv, json, xslAvailable download formats
    Dataset updated
    Sep 25, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia.

    Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file.

    Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death.

    Death counts should not be compared across jurisdictions. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly.

    The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington.

    Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf).

    Rate are based on deaths occurring in the specified week and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly) rate prevailed for a full year.

    Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

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

    • catalog.data.gov
    • data.virginia.gov
    • +2more
    Updated Sep 26, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Provisional COVID-19 death counts, rates, and percent of total deaths, by jurisdiction of residence [Dataset]. https://catalog.data.gov/dataset/provisional-covid-19-death-counts-rates-and-percent-of-total-deaths-by-jurisdiction-of-res
    Explore at:
    Dataset updated
    Sep 26, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

Share
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New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html

Coronavirus (Covid-19) Data in the United States

Explore at:
Dataset provided by
New York Times
Description

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

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

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

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

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