100+ datasets found
  1. g

    Coronavirus (Covid-19) Data in the United States

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

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

    Description

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

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

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

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

  2. Cumulative cases of COVID-19 in the U.S. from Jan. 20, 2020 - Nov. 11, 2022,...

    • statista.com
    Updated Nov 17, 2022
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    Cumulative cases of COVID-19 in the U.S. from Jan. 20, 2020 - Nov. 11, 2022, by week [Dataset]. https://www.statista.com/statistics/1103185/cumulative-coronavirus-covid19-cases-number-us-by-day/
    Explore at:
    Dataset updated
    Nov 17, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 20, 2020 - Nov 11, 2022
    Area covered
    United States
    Description

    As of November 11, 2022, almost 96.8 million confirmed cases of COVID-19 had been reported by the World Health Organization (WHO) for the United States. The pandemic has impacted all 50 states, with vast numbers of cases recorded in California, Texas, and Florida.

    The coronavirus in the U.S. The coronavirus hit the United States in mid-March 2020, and cases started to soar at an alarming rate. The country has performed a high number of COVID-19 tests, which is a necessary step to manage the outbreak, but new coronavirus cases in the U.S. have spiked several times since the pandemic began, most notably at the end of 2022. However, restrictions in many states have been eased as new cases have declined.

    The origin of the coronavirus In December 2019, officials in Wuhan, China, were the first to report cases of pneumonia with an unknown cause. A new human coronavirus – SARS-CoV-2 – has since been discovered, and COVID-19 is the infectious disease it causes. All available evidence to date suggests that COVID-19 is a zoonotic disease, which means it can spread from animals to humans. The WHO says transmission is likely to have happened through an animal that is handled by humans. Researchers do not support the theory that the virus was developed in a laboratory.

  3. d

    Johns Hopkins COVID-19 Case Tracker

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

    Updates

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

    • April 9, 2020

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

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

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

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

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

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

      Overview

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

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

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

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

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

    Queries

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

    Interactive

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

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

    Interactive Embed Code

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

    Caveats

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

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

    Attribution

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

  4. Number of COVID-19 deaths in the United States 2020-2022, by age

    • statista.com
    Updated May 9, 2023
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    Statista (2023). Number of COVID-19 deaths in the United States 2020-2022, by age [Dataset]. https://www.statista.com/statistics/1382342/number-covid-deaths-us-by-age/
    Explore at:
    Dataset updated
    May 9, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2020, there were a total of 384,536 deaths in the United States caused by COVID-19. Those aged 85 years and older accounted for 122,707 COVID deaths that year. This statistic shows the total number of deaths due to COVID-19 in the United States in 2020, 2021, and 2022, by age.

  5. Number of U.S. COVID-19 cases from Jan. 20, 2020 - Nov. 11, 2022, by week

    • statista.com
    Updated Nov 17, 2022
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    Statista (2022). Number of U.S. COVID-19 cases from Jan. 20, 2020 - Nov. 11, 2022, by week [Dataset]. https://www.statista.com/statistics/1102816/coronavirus-covid19-cases-number-us-americans-by-day/
    Explore at:
    Dataset updated
    Nov 17, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 20, 2020 - Nov 11, 2022
    Area covered
    United States
    Description

    Around 282 thousand new cases of COVID-19 were reported in the United States during the week ending November 11, 2022. Between January 20, 2020 and November 11, 2022 there had been around 96.8 million confirmed cases of COVID-19 with over one million deaths in the U.S. as reported by the World Health Organization.

    How did the coronavirus outbreak start? Pneumonia cases with an unknown cause were first reported in the Hubei province of China at the end of December 2019. Patients described symptoms including a fever and difficulty breathing, and early reports suggested no evidence of human-to-human transmission. We now know that a novel coronavirus named SARS-CoV-2 is causing the disease COVID-19. The virus has been characterized as a pandemic and continues to spread from person to person – there have been around 642 million cases worldwide as of November 17, 2022.

    The importance of isolation and quarantine In an effort to contain the early spread of the virus, China tightened travel restrictions and enforced isolation measures in the hardest-hit areas. The World Health Organization endorsed this strategy, and countries around the world implemented similar quarantine measures. Staying at home can limit the spread of the virus, and this applies to individuals who are only showing mild symptoms or none at all. Asymptomatic carriers of the virus – those that are experiencing no symptoms – may transmit the virus to people who are at a higher risk of getting very sick.

  6. B

    Brazil New Covid tests per month, September, 2021 - data, chart |...

    • theglobaleconomy.com
    csv, excel, xml
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    Globalen LLC, Brazil New Covid tests per month, September, 2021 - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Brazil/covid_new_tests/
    Explore at:
    excel, xml, csvAvailable download formats
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Apr 30, 2020 - Sep 30, 2021
    Area covered
    Brazil
    Description

    New Covid tests per month in Brazil, September, 2021 The most recent value is 3787260 new Covid tests as of September 2021, an increase compared to the previous value of 2239698 new Covid tests. Historically, the average for Brazil from April 2020 to September 2021 is 4641320 new Covid tests. The minimum of 436538 new Covid tests was recorded in April 2020, while the maximum of 20400000 new Covid tests was reached in October 2020. | TheGlobalEconomy.com

  7. COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries...

    • healthdata.gov
    • datahub.hhs.gov
    • +1more
    Updated May 3, 2024
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    U.S. Department of Health & Human Services (2024). COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries (RAW) [Dataset]. https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh
    Explore at:
    csv, application/rssxml, application/rdfxml, tsv, xml, kmz, application/geo+json, kmlAvailable download formats
    Dataset updated
    May 3, 2024
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Authors
    U.S. Department of Health & Human Services
    License

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

    Description

    After May 3, 2024, this dataset and webpage will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, and hospital capacity and occupancy data, to HHS through CDC’s National Healthcare Safety Network. Data voluntarily reported to NHSN after May 1, 2024, will be available starting May 10, 2024, at COVID Data Tracker Hospitalizations.

    The following dataset provides state-aggregated data for hospital utilization in a timeseries format dating back to January 1, 2020. These are derived from reports with facility-level granularity across three main sources: (1) HHS TeleTracking, (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities and (3) National Healthcare Safety Network (before July 15).

    The file will be updated regularly and provides the latest values reported by each facility within the last four days for all time. This allows for a more comprehensive picture of the hospital utilization within a state by ensuring a hospital is represented, even if they miss a single day of reporting.

    No statistical analysis is applied to account for non-response and/or to account for missing data.

    The below table displays one value for each field (i.e., column). Sometimes, reports for a given facility will be provided to more than one reporting source: HHS TeleTracking, NHSN, and HHS Protect. When this occurs, to ensure that there are not duplicate reports, prioritization is applied to the numbers for each facility.

    On April 27, 2022 the following pediatric fields were added:

  8. all_pediatric_inpatient_bed_occupied
  9. all_pediatric_inpatient_bed_occupied_coverage
  10. all_pediatric_inpatient_beds
  11. all_pediatric_inpatient_beds_coverage
  12. previous_day_admission_pediatric_covid_confirmed_0_4
  13. previous_day_admission_pediatric_covid_confirmed_0_4_coverage
  14. previous_day_admission_pediatric_covid_confirmed_12_17
  15. previous_day_admission_pediatric_covid_confirmed_12_17_coverage
  16. previous_day_admission_pediatric_covid_confirmed_5_11
  17. previous_day_admission_pediatric_covid_confirmed_5_11_coverage
  18. previous_day_admission_pediatric_covid_confirmed_unknown
  19. previous_day_admission_pediatric_covid_confirmed_unknown_coverage
  20. staffed_icu_pediatric_patients_confirmed_covid
  21. staffed_icu_pediatric_patients_confirmed_covid_coverage
  22. staffed_pediatric_icu_bed_occupancy
  23. staffed_pediatric_icu_bed_occupancy_coverage
  24. total_staffed_pediatric_icu_beds
  25. total_staffed_pediatric_icu_beds_coverage

    On January 19, 2022, the following fields have been added to this dataset:
  26. inpatient_beds_used_covid
  27. inpatient_beds_used_covid_coverage

    On September 17, 2021, this data set has had the following fields added:
  28. icu_patients_confirmed_influenza,
  29. icu_patients_confirmed_influenza_coverage,
  30. previous_day_admission_influenza_confirmed,
  31. previous_day_admission_influenza_confirmed_coverage,
  32. previous_day_deaths_covid_and_influenza,
  33. previous_day_deaths_covid_and_influenza_coverage,
  34. previous_day_deaths_influenza,
  35. previous_day_deaths_influenza_coverage,
  36. total_patients_hospitalized_confirmed_influenza,
  37. total_patients_hospitalized_confirmed_influenza_and_covid,
  38. total_patients_hospitalized_confirmed_influenza_and_covid_coverage,
  39. total_patients_hospitalized_confirmed_influenza_coverage

    On September 13, 2021, this data set has had the following fields added:
  40. on_hand_supply_therapeutic_a_casirivimab_imdevimab_courses,
  41. on_hand_supply_therapeutic_b_bamlanivimab_courses,
  42. on_hand_supply_therapeutic_c_bamlanivimab_etesevimab_courses,
  43. previous_week_therapeutic_a_casirivimab_imdevimab_courses_used,
  44. previous_week_therapeutic_b_bamlanivimab_courses_used,
  45. previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_used

    On June 30, 2021, this data set has had the following fields added:
  46. deaths_covid
  47. deaths_covid_coverage

    On April 30, 2021, this data set has had the following fields added:
  48. previous_day_admission_adult_covid_confirmed_18-19
  49. previous_day_admission_adult_covid_confirmed_18-19_coverage
  50. previous_day_admission_adult_covid_confirmed_20-29_coverage
  51. previous_day_admission_adult_covid_confirmed_30-39
  52. previous_day_admission_adult_covid_confirmed_30-39_coverage
  53. previous_day_admission_adult_covid_confirmed_40-49
  54. previous_day_admission_adult_covid_confirmed_40-49_coverage
  55. previous_day_admission_adult_covid_confirmed_40-49_coverage
  56. previous_day_admission_adult_covid_confirmed_50-59
  57. previous_day_admission_adult_covid_confirmed_50-59_coverage
  58. previous_day_admission_adult_covid_confirmed_60-69
  59. previous_day_admission_adult_covid_confirmed_60-69_coverage
  60. previous_day_admission_adult_covid_confirmed_70-79
  61. previous_day_admission_adult_covid_confirmed_70-79_coverage
  62. previous_day_admission_adult_covid_confirmed_80+
  63. previous_day_admission_adult_covid_confirmed_80+_coverage
  64. previous_day_admission_adult_covid_confirmed_unknown
  65. previous_day_admission_adult_covid_confirmed_unknown_coverage
  66. previous_day_admission_adult_covid_suspected_18-19
  67. previous_day_admission_adult_covid_suspected_18-19_coverage
  68. previous_day_admission_adult_covid_suspected_20-29
  69. previous_day_admission_adult_covid_suspected_20-29_coverage
  70. previous_day_admission_adult_covid_suspected_30-39
  71. previous_day_admission_adult_covid_suspected_30-39_coverage
  72. previous_day_admission_adult_covid_suspected_40-49
  73. previous_day_admission_adult_covid_suspected_40-49_coverage
  74. previous_day_admission_adult_covid_suspected_50-59
  75. previous_day_admission_adult_covid_suspected_50-59_coverage
  76. previous_day_admission_adult_covid_suspected_60-69
  77. previous_day_admission_adult_covid_suspected_60-69_coverage
  78. previous_day_admission_adult_covid_suspected_70-79
  79. previous_day_admission_adult_covid_suspected_70-79_coverage
  80. previous_day_admission_adult_covid_suspected_80+
  81. previous_day_admission_adult_covid_suspected_80+_coverage
  82. previous_day_admission_adult_covid_suspected_unknown
  83. previous_day_admission_adult_covid_suspected_unknown_coverage

  • Weekly Summary of U.S. COVID-19 Trends

    • beta-search-prod-pre-a-hub.hub.arcgis.com
    Updated Jul 3, 2020
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    Urban Observatory by Esri (2020). Weekly Summary of U.S. COVID-19 Trends [Dataset]. https://beta-search-prod-pre-a-hub.hub.arcgis.com/datasets/UrbanObservatory::weekly-summary-of-u-s-covid-19-trends-1
    Explore at:
    Dataset updated
    Jul 3, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    United States
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This map is updated weekly and currently shows data through Mar 5, 2023. Notes: as of 5/25/2021, Nebraska stopped sharing COVID-19 testing and on 9/26/21 began, but with a lump sum for the previous four months. Nebraska's reporting became unconsumable by JHU on July 1, 2022. Maryland stopped reporting results for several weeks on 12/4/2021 due to a website hack.It shows COVID-19 Trend for the most recent Monday with a colored dot for each county. The larger the dot, the longer the county has had this trend.Includes Puerto Rico, Guam, Northern Marianas, U.S. Virgin Islands.The intent of this map is to give more context than just the current day of new data because daily data for COVID-19 cases is volatile and can be unreliable on the day it is first reported. Weekly summaries in the counts of new cases smooth out this volatility.Click or tap on a county to see a history of trend changes and a weekly graph of new cases going back to February 1, 2020.For more information about COVID-19 trends, see the full methodology.Data Source: Johns Hopkins University CSSE US Cases by County dashboard and USAFacts for Utah County level Data.

  • T

    Morocco Coronavirus COVID-19 Vaccination Rate

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Apr 20, 2021
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    TRADING ECONOMICS (2021). Morocco Coronavirus COVID-19 Vaccination Rate [Dataset]. https://tradingeconomics.com/morocco/coronavirus-vaccination-rate
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Apr 20, 2021
    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 1, 2021 - May 15, 2023
    Area covered
    Morocco
    Description

    The number of COVID-19 vaccination doses administered per 100 people in Morocco rose to 148 as of Oct 27 2023. This dataset includes a chart with historical data for Morocco Coronavirus Vaccination Rate.

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

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

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

    The difficulties of death figures

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

    Where are these numbers coming from?

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

  • A

    Aruba New Covid tests per thousand people, June, 2021 - data, chart |...

    • theglobaleconomy.com
    csv, excel, xml
    + more versions
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    Globalen LLC, Aruba New Covid tests per thousand people, June, 2021 - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Aruba/covid_new_tests_per_thousand/
    Explore at:
    excel, xml, csvAvailable download formats
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Jun 30, 2021
    Area covered
    Aruba
    Description

    New Covid tests per thousand people in Aruba, June, 2021 The most recent value is 112 new Covid tests per thousand people as of June 2021, an increase compared to the previous value of new Covid tests per thousand people. Historically, the average for Aruba from June 2021 to June 2021 is 112 new Covid tests per thousand people. The minimum of 112 new Covid tests per thousand people was recorded in June 2021, while the maximum of 112 new Covid tests per thousand people was reached in June 2021. | TheGlobalEconomy.com

  • Coronavirus cases in England: 5 January 2021

    • gov.uk
    • s3.amazonaws.com
    Updated Jan 5, 2021
    + more versions
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    Department of Health and Social Care (2021). Coronavirus cases in England: 5 January 2021 [Dataset]. https://www.gov.uk/government/publications/coronavirus-cases-in-england-5-january-2021
    Explore at:
    Dataset updated
    Jan 5, 2021
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department of Health and Social Care
    Area covered
    England
    Description

    The data includes:

    • case rate per 100,000 population
    • case rate per 100,000 population aged 60 years and over
    • percentage change in case rate per 100,000 from previous week
    • number of people tested and weekly positivity
    • NHS pressures by Sustainability and Transformation Partnership (STP)

    More detailed epidemiological charts and graphs are presented for areas in very high and high local COVID alert level areas.

    See the https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-hospital-activity/" class="govuk-link">detailed data on hospital activity.

    See the https://coronavirus.data.gov.uk/?_ga=2.43448994.685856970.1607933075-1070872729.1597161719" class="govuk-link">detailed data on the progress of the coronavirus pandemic.

  • T

    Honduras Coronavirus COVID-19 Vaccination Total

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 10, 2021
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    TRADING ECONOMICS (2021). Honduras Coronavirus COVID-19 Vaccination Total [Dataset]. https://tradingeconomics.com/honduras/coronavirus-vaccination-total
    Explore at:
    xml, csv, json, excelAvailable download formats
    Dataset updated
    Jul 10, 2021
    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
    Aug 16, 2021 - May 5, 2023
    Area covered
    Honduras
    Description

    The number of COVID-19 vaccination doses administered in Honduras rose to 16963148 as of Jul 15 2023. This dataset includes a chart with historical data for Honduras Coronavirus COVID-19 Vaccination Total.

  • T

    Brazil Coronavirus COVID-19 Vaccination Total

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Apr 21, 2021
    + more versions
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    TRADING ECONOMICS (2021). Brazil Coronavirus COVID-19 Vaccination Total [Dataset]. https://tradingeconomics.com/brazil/coronavirus-vaccination-total
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    Apr 21, 2021
    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 18, 2021 - Mar 22, 2023
    Area covered
    Brazil
    Description

    The number of COVID-19 vaccination doses administered in Brazil rose to 486436436 as of Oct 27 2023. This dataset includes a chart with historical data for Brazil Coronavirus Vaccination Total.

  • D

    Provisional COVID-19 Death Counts by Age in Years, 2020-2023

    • data.cdc.gov
    • data.virginia.gov
    • +3more
    application/rdfxml +5
    Updated Jun 28, 2023
    + more versions
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    NCHS/DVS (2023). Provisional COVID-19 Death Counts by Age in Years, 2020-2023 [Dataset]. https://data.cdc.gov/NCHS/Provisional-COVID-19-Death-Counts-by-Age-in-Years-/3apk-4u4f
    Explore at:
    xml, csv, json, application/rdfxml, tsv, application/rssxmlAvailable download formats
    Dataset updated
    Jun 28, 2023
    Dataset authored and provided by
    NCHS/DVS
    License

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

    Description

    Effective June 28, 2023, this dataset will no longer be updated. Similar data are accessible from CDC WONDER (https://wonder.cdc.gov/mcd-icd10-provisional.html).

    Cumulative deaths involving COVID-19 reported to NCHS by sex and age in years, in the United States.

  • a

    Baseline COVID Data for New Mexico, December 2021

    • chi-phi-nmcdc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 28, 2022
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    New Mexico Community Data Collaborative (2022). Baseline COVID Data for New Mexico, December 2021 [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/datasets/baseline-covid-data-for-new-mexico-december-2021-
    Explore at:
    Dataset updated
    Feb 28, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    NM Health Councils participating in the Vaccine Equity Project can use this map to determine what their baseline data is from Dec 2021.Need help navigating this map? View the Step-by-step guide to identifying your Health Councils Dec Baseline data here: https://nmcdc.maps.arcgis.com/sharing/rest/content/items/208ebb2d96f448858ec7a38dbded3ad6/dataAlso see the data table showing percent vaccinated by age categories as of Dec 31st 2021 to make finding your baseline data easy: https://nmcdc.maps.arcgis.com/sharing/rest/content/items/30848fdb69ea4d2c89324f9830d2cd40/data

  • COVID-19 Blueprint for a Safer Economy Data Chart (ARCHIVED)

    • data.chhs.ca.gov
    • data.ca.gov
    • +2more
    csv, zip
    Updated Aug 28, 2024
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    California Department of Public Health (2024). COVID-19 Blueprint for a Safer Economy Data Chart (ARCHIVED) [Dataset]. https://data.chhs.ca.gov/dataset/covid-19-blueprint-for-a-safer-economy
    Explore at:
    csv(6568), csv(6800), csv(5697), csv(7462), csv(7698), csv(6662), csv(7587), csv(8418), csv(5704), csv(5732), csv(9008), csv(3905), csv(7434), csv(5166), csv(4712), csv(8458), csv(7905), csv(3960), csv(7639), csv(7720), csv(7745), csv(6740), csv(4591), csv(4603), csv(5752), csv(6660), csv(4694), csv(7873), csv(7714), csv(7815), csv(8991), csv(7348), csv(7757), csv(3821), csv(8059), csv(8222), csv(8419), csv(7435), csv(6661), csv(7444), csv(4539), csv(7707), zipAvailable download formats
    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    Description

    Note: Blueprint has been retired as of June 15, 2021. This dataset will be kept up for historical purposes, but will no longer be updated.

    California has a new blueprint for reducing COVID-19 in the state with revised criteria for loosening and tightening restrictions on activities. Every county in California is assigned to a tier based on its test positivity and adjusted case rate for tier assignment. Additionally, a new health equity metric took effect on October 6, 2020. In order to advance to the next less restrictive tier, each county will need to meet an equity metric or demonstrate targeted investments to eliminate disparities in levels of COVID-19 transmission, depending on its size. The California Health Equity Metric is designed to help guide counties in their continuing efforts to reduce COVID-19 cases in all communities and requires more intensive efforts to prevent and mitigate the spread of COVID-19 among Californians who have been disproportionately impacted by this pandemic.

    Please see https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/COVID19CountyMonitoringOverview.aspx for more information.

    Also, in lieu of a Data Dictionary, please refer to the detailed explanation of the data columns in Appendix 1 of the above webpage.

    Because this data is in machine-readable format, the merged headers at the top of the source spreadsheet have not been included:

    • The first 8 columns are under the header "County Status as of Tier Assignment"

    • The next 3 columns are under the header "Current Data Week Tier and Metric Tiers for Data Week"

    • The next 4 columns are under the header "Case Rate Adjustment Factors"

    • The next column is under the header "Small County Considerations"

    • The last 5 columns are under the header "Health Equity Framework Parameters"

  • Data for Figures and Tables in "Bounce backs amid continued losses: Life...

    • zenodo.org
    bin, csv, pdf
    Updated Jul 16, 2024
    + more versions
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    Jonas Schöley; Jonas Schöley; José Manuel Aburto; José Manuel Aburto; Ilya Kashnitsky; Ilya Kashnitsky; Maxi S. Kniffka; Maxi S. Kniffka; Luyin Zhang; Luyin Zhang; Hannaliis Jaadla; Hannaliis Jaadla; Jennifer B. Dowd; Jennifer B. Dowd; Ridhi Kashyap; Ridhi Kashyap (2024). Data for Figures and Tables in "Bounce backs amid continued losses: Life expectancy changes since COVID-19" [Dataset]. http://doi.org/10.5281/zenodo.6653120
    Explore at:
    bin, csv, pdfAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Jonas Schöley; Jonas Schöley; José Manuel Aburto; José Manuel Aburto; Ilya Kashnitsky; Ilya Kashnitsky; Maxi S. Kniffka; Maxi S. Kniffka; Luyin Zhang; Luyin Zhang; Hannaliis Jaadla; Hannaliis Jaadla; Jennifer B. Dowd; Jennifer B. Dowd; Ridhi Kashyap; Ridhi Kashyap
    License

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

    Description

    Data for Figures and Tables in "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

    cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

    These are CSV files of data in the figures and tables published in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

    50-e0diffT.csv

    Figure 1: Life expectancy changes 2019/20 and 2020/21 across countries. The countries are ordered by increasing cumulative life expectancy losses since 2019. Grey dots indicate the average annual LE changes over the years 2015 through 2019.

    51-arriagaT.csv

    Figure 2: Age contributions to life expectancy changes since 2019 separated for 2020 and 2021. The position of the arrowhead indicates the total contribution of mortality changes in a given age group to the change in life expectancy at birth since 2019. The discontinuity in the arrow indicates those contributions separately for the years 2020 and 2021. Annual contributions can compound or reverse. The total life expectancy change from 2019 to 2021 in a given country is the sum of the arrowhead positions across age.

    52-sexdiff.csv

    Figure 3: Change in the female life expectancy advantage from 2019 through 2021. Blue colors indicate an increase and red colors a decrease in the female life expectancy advantage. Muted colors indicate non-significant changes.

    53-e0diffcodT.csv

    Figure 4: Life expectancy deficit in 2021 decomposed into contributions by age and cause of death. LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.

    55-vaxe0.csv

    Figure 5: Years of life expectancy deficit during October through December 2021 contributed by ages <60 and 60+ against % of population twice vaccinated by October 1st in the respective age groups. LE deficit is defined as the counterfactual LE from a Lee-Carter mortality forecast based on death rates for the fourth quarter of the years 2015 to 2019 minus observed LE.

    54-tab_arriaga.csv

    Table 1: Months of life expectancy (LE) changes and deficits (labelled ES) since the start of the pandemic attributed to age-specific mortality changes (labelled AT). LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.

  • c

    A Year of COVID-19: Finnish Experiences of Everyday Life during the Pandemic...

    • datacatalogue.cessda.eu
    • services.fsd.tuni.fi
    Updated May 30, 2024
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    Finnish Literature Society. Archive (2024). A Year of COVID-19: Finnish Experiences of Everyday Life during the Pandemic 2021 [Dataset]. http://doi.org/10.60686/t-fsd3778
    Explore at:
    Dataset updated
    May 30, 2024
    Authors
    Finnish Literature Society. Archive
    Time period covered
    Mar 12, 2021 - Oct 15, 2021
    Area covered
    Finland
    Variables measured
    Individual
    Measurement technique
    Self-administered writings and/or diaries: Web-based, Self-administered writings and/or diaries: Paper
    Description

    The dataset consists of self-administered written texts on experiences related to the coronavirus epidemic. The data chart people's everyday lives as the pandemic continued in 2021. The dataset is a continuation of the Finnish Literary Society's previous COVID-19 related data collection, Koronakevät ('COVID-19 Spring”), which was carried out in 2020. The Koronakevät dataset is available from the archive of the Finnish Literature Society. The writing guidelines directed participants to write about their experiences during the continuing COVID-19 pandemic in the spring of 2021. Participants were asked to reflect on how they personally perceived the time period affected by the coronavirus epidemic and how their attitudes towards the coronavirus had changed as the pandemic had continued. The study investigated participants' attitudes towards restrictions and security measures and their efforts to avoid contracting COVID-19. Participants were also prompted to write about their possible personal experiences of contracting COVID-19, the experiences of individuals in their immediate circle who had contracted COVID-19, and their attitudes towards contracting the virus. In relation to the coronavirus, participants were asked about their attitudes towards COVID-19 vaccines and their general attitudes towards COVID-19. Additionally, participants could write about the impact COVID-19 had had on their everyday lives, interpersonal relationships, and life in general. Any possible positive effects of COVID-19 and factors affecting participants' well-being and resilience were also charted. Background information included the participant's gender, year of birth, occupation, and area of residence. The data were organised into an easy to use HTML version at FSD. The dataset is only available in Finnish.

  • M

    Madagascar New Covid tests per month, September, 2021 - data, chart |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Sep 15, 2021
    + more versions
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    Globalen LLC (2021). Madagascar New Covid tests per month, September, 2021 - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Madagascar/covid_new_tests/
    Explore at:
    excel, xml, csvAvailable download formats
    Dataset updated
    Sep 15, 2021
    Dataset authored and provided by
    Globalen LLC
    License

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

    Time period covered
    Apr 30, 2020 - Sep 30, 2021
    Area covered
    Madagascar
    Description

    New Covid tests per month in Madagascar, September, 2021 The most recent value is 20790 new Covid tests as of September 2021, an increase compared to the previous value of 13847 new Covid tests. Historically, the average for Madagascar from April 2020 to September 2021 is 16919 new Covid tests. The minimum of 2445 new Covid tests was recorded in April 2020, while the maximum of 40410 new Covid tests was reached in April 2021. | TheGlobalEconomy.com

  • Share
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://github.com/nytimes/covid-19-data

    Coronavirus (Covid-19) Data in the United States

    Explore at:
    csvAvailable download formats
    Dataset provided by
    New York Times
    License

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

    Description

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

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

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

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

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