100+ datasets found
  1. Covid-19 Global Dataset

    • kaggle.com
    zip
    Updated Apr 12, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Khushi Yadav (2025). Covid-19 Global Dataset [Dataset]. https://www.kaggle.com/datasets/khushikyad001/covid-19-global-dataset
    Explore at:
    zip(482555 bytes)Available download formats
    Dataset updated
    Apr 12, 2025
    Authors
    Khushi Yadav
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    This dataset contains 3,000 rows and 26 columns of synthetically generated COVID-19 records. It replicates realistic global pandemic data, simulating values for cases, deaths, tests, vaccinations, demographics, and policy measures. The data mimics actual records from sources like Our World in Data, designed specifically for data science experimentation, visualization, and machine learning projects.

    It is ideal for:

    Practicing exploratory data analysis (EDA)

    Creating dashboards

    Building predictive models

    Teaching or student projects

    Kaggle Notebooks without API dependencies

  2. COVID-19 Global Dataset

    • kaggle.com
    zip
    Updated Jun 2, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Saikat Sinha Ray (2024). COVID-19 Global Dataset [Dataset]. https://www.kaggle.com/datasets/saikatsray/covid-19-global-dataset
    Explore at:
    zip(542392 bytes)Available download formats
    Dataset updated
    Jun 2, 2024
    Authors
    Saikat Sinha Ray
    License

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

    Description

    Dataset

    This dataset was created by Saikat Sinha Ray

    Released under Apache 2.0

    Contents

  3. g

    Coronavirus COVID-19 Global Cases by the Center for Systems Science and...

    • github.com
    • systems.jhu.edu
    • +1more
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE), Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) [Dataset]. https://github.com/CSSEGISandData/COVID-19
    Explore at:
    Dataset provided by
    Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE)
    Area covered
    Global
    Description

    2019 Novel Coronavirus COVID-19 (2019-nCoV) Visual Dashboard and Map:
    https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

    • Confirmed Cases by Country/Region/Sovereignty
    • Confirmed Cases by Province/State/Dependency
    • Deaths
    • Recovered

    Downloadable data:
    https://github.com/CSSEGISandData/COVID-19

    Additional Information about the Visual Dashboard:
    https://systems.jhu.edu/research/public-health/ncov

  4. WHO COVID-19 Global Data Insights

    • kaggle.com
    zip
    Updated Sep 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Mohammad Reza Ghazi Manas (2023). WHO COVID-19 Global Data Insights [Dataset]. https://www.kaggle.com/datasets/mohammadrezagim/who-covid-19-global-data
    Explore at:
    zip(2309669 bytes)Available download formats
    Dataset updated
    Sep 30, 2023
    Authors
    Mohammad Reza Ghazi Manas
    License

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

    Description

    About Dataset: WHO COVID-19 Global Data

    This dataset provides comprehensive information on the global COVID-19 pandemic as reported to the World Health Organization (WHO). The dataset is available in comma-separated values (CSV) format and includes the following fields:

    Daily cases and deaths by date reported to WHO: WHO-COVID-19-global-data.csv

    • Date_reported (Date): The date of reporting to WHO.
    • Country_code (String): The ISO Alpha-2 country code.
    • Country (String): The name of the country, territory, or area.
    • WHO_region (String): The WHO regional office to which the country belongs. WHO Member States are grouped into six WHO regions, including AFRO (Regional Office for Africa), AMRO (Regional Office for the Americas), SEARO (Regional Office for South-East Asia), EURO (Regional Office for Europe), EMRO (Regional Office for the Eastern Mediterranean), and WPRO (Regional Office for the Western Pacific).
    • New_cases (Integer): The number of new confirmed cases reported on a given day. This is calculated by subtracting the previous cumulative case count from the current cumulative case count.
    • Cumulative_cases (Integer): The total cumulative confirmed cases reported to WHO up to the specified date.
    • New_deaths (Integer): The number of new confirmed deaths reported on a given day. Similar to new cases, this is calculated by subtracting the previous cumulative death count from the current cumulative death count.- Cumulative_deaths (Integer): The total cumulative confirmed deaths reported to WHO up to the specified date.

    In addition to the COVID-19 case and death data, this dataset also includes valuable information related to COVID-19 vaccinations. The vaccination data consists of the following fields:

    Vaccination Data Fields: vaccination-data.csv

    • COUNTRY (String): Country, territory, or area.
    • ISO3 (String): ISO Alpha-3 country code.
    • WHO_REGION (String): The WHO regional office to which the country belongs.
    • DATA_SOURCE (String): Indicates the data source, which can be either "REPORTING" (Data reported by Member States or sourced from official reports) or "OWID" (Data sourced from Our World in Data COVID-19 Vaccinations).
    • DATE_UPDATED (Date): Date of the last update.
    • TOTAL_VACCINATIONS (Integer): Cumulative total vaccine doses administered.
    • PERSONS_VACCINATED_1PLUS_DOSE (Decimal): Cumulative number of persons vaccinated with at least one dose.
    • TOTAL_VACCINATIONS_PER100 (Integer): Cumulative total vaccine doses administered per 100 population.
    • PERSONS_VACCINATED_1PLUS_DOSE_PER100 (Decimal): Cumulative persons vaccinated with at least one dose per 100 population.
    • PERSONS_LAST_DOSE (Integer): Cumulative number of persons vaccinated with a complete primary series.
    • PERSONS_LAST_DOSE_PER100 (Decimal): Cumulative number of persons vaccinated with a complete primary series per 100 population.
    • VACCINES_USED (String): Combined short name of the vaccine in the format "Company - Product name."
    • FIRST_VACCINE_DATE (Date): Date of the first vaccinations, equivalent to the start/launch date of the first vaccine administered in a country.
    • NUMBER_VACCINES_TYPES_USED (Integer): Number of vaccine types used per country, territory, or area.
    • PERSONS_BOOSTER_ADD_DOSE (Integer): Cumulative number of persons vaccinated with at least one booster or additional dose.
    • PERSONS_BOOSTER_ADD_DOSE_PER100 (Decimal): Cumulative number of persons vaccinated with at least one booster or additional dose per 100 population.

    In addition to the vaccination data, a separate dataset containing vaccination metadata is available, including information about vaccine names, product names, company names, authorization dates, start and end dates of vaccine rollout, and more.

    Vaccination metadata Fields: vaccination-metadata.csv

    • ISO3 (String): ISO Alpha-3 country code
    • VACCINE_NAME (String): Combined short name of vaccine: "Company - Product name" (see below)
    • PRODUCT_NAME (String): Name or label of vaccine product, or type of vaccine (if unnamed).
    • COMPANY_NAME (String): Marketing authorization holder of vaccine product.
    • FIRST_VACCINE_DATE (Date): Date of first vaccinations. Equivalent to start/launch date of the first vaccine administered in a country.
    • AUTHORIZATION_DATE (Date): Date vaccine product was authorized for use in the country, territory, area.
    • START_DATE (Date): Start/launch date of vaccination with vaccine type (excludes vaccinations during clinical trials).
    • END_DATE (Date): End date of vaccine rollout
    • COMMENT (String): Comments related to vaccine rollout
    • DATA_SOURCE (String): Indicates data source - REPORTING: Data reported by Member States, or sourced from official re...
  5. Cumulative cases of COVID-19 worldwide from Jan. 22, 2020 to Jun. 13, 2023,...

    • statista.com
    Updated May 22, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Cumulative cases of COVID-19 worldwide from Jan. 22, 2020 to Jun. 13, 2023, by day [Dataset]. https://www.statista.com/statistics/1103040/cumulative-coronavirus-covid19-cases-number-worldwide-by-day/
    Explore at:
    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 22, 2020 - Jun 13, 2023
    Area covered
    World
    Description

    As of June 13, 2023, there have been almost 768 million cases of coronavirus (COVID-19) worldwide. The disease has impacted almost every country and territory in the world, with the United States confirming around 16 percent of all global cases.

    COVID-19: An unprecedented crisis Health systems around the world were initially overwhelmed by the number of coronavirus cases, and even the richest and most prepared countries struggled. In the most vulnerable countries, millions of people lacked access to critical life-saving supplies, such as test kits, face masks, and respirators. However, several vaccines have been approved for use, and more than 13 billion vaccine doses had already been administered worldwide as of March 2023.

    The coronavirus in the United Kingdom Over 202 thousand people have died from COVID-19 in the UK, which is the highest number in Europe. The tireless work of the National Health Service (NHS) has been applauded, but the country’s response to the crisis has drawn criticism. The UK was slow to start widespread testing, and the launch of a COVID-19 contact tracing app was delayed by months. However, the UK’s rapid vaccine rollout has been a success story, and around 53.7 million people had received at least one vaccine dose as of July 13, 2022.

  6. Global Covid Trend

    • kaggle.com
    zip
    Updated Jan 26, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nidula Elgiriyewithana ⚡ (2024). Global Covid Trend [Dataset]. https://www.kaggle.com/datasets/nelgiriyewithana/global-covid-trend
    Explore at:
    zip(562001 bytes)Available download formats
    Dataset updated
    Jan 26, 2024
    Authors
    Nidula Elgiriyewithana ⚡
    Description

    Description

    Dive into the dynamic narrative of the 'Global Covid Trend' dataset, capturing the ebb and flow of COVID-19 cases worldwide. Uncover trends, patterns, and vital statistics meticulously compiled to paint a comprehensive picture of the pandemic's journey across the globe.

    Key Features

    • Province/State: Province or state of the location
    • Country/Region: Country or region of the location
    • Lat: Latitude coordinate
    • Long: Longitude coordinate
    • 1/22/2020 - 1/2/2022: Daily COVID-19 cases from January 22, 2020, to February 2, 2022

    Sample Data

    Province/StateCountry/RegionLatLong1/22/20201/23/2020...2/1/20222/2/2022
    SampleCountry0.00000.000001...10001005
    AnotherRegion12.3456-45.6789510...500505
    ...........................

    Dataset Information

    • Data Format: CSV (Comma-Separated Values)

    It's important to note that the data does not contain any personally identifiable information (PII) to ensure privacy and comply with ethical guidelines.

    If this was helpful, a vote is appreciated 🙂❤️

  7. r

    covid19_jhu_csse_summary

    • redivis.com
    Updated Oct 8, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Stanford Center for Population Health Sciences (2025). covid19_jhu_csse_summary [Dataset]. https://redivis.com/datasets/rxta-4v35cgyzf
    Explore at:
    Dataset updated
    Oct 8, 2025
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 22, 2020 - Jul 12, 2020
    Description

    The table covid19_jhu_csse_summary is part of the dataset Coronavirus COVID-19 Global Cases, available at https://stanford.redivis.com/datasets/rxta-4v35cgyzf. It contains 390476 rows across 13 variables.

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

    • statista.com
    Updated Jul 13, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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/
    Explore at:
    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.

  9. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +4more
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
    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.

  10. Coronavirus (COVID-19) cases, recoveries, and deaths worldwide as of May 2,...

    • statista.com
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista, Coronavirus (COVID-19) cases, recoveries, and deaths worldwide as of May 2, 2023 [Dataset]. https://www.statista.com/statistics/1087466/covid19-cases-recoveries-deaths-worldwide/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2, 2023
    Area covered
    Worldwide
    Description

    As of May 2, 2023, there were roughly 687 million global cases of COVID-19. Around 660 million people had recovered from the disease, while there had been almost 6.87 million deaths. The United States, India, and Brazil have been among the countries hardest hit by the pandemic.

    The various types of human coronavirus The SARS-CoV-2 virus is the seventh known coronavirus to infect humans. Its emergence makes it the third in recent years to cause widespread infectious disease following the viruses responsible for SARS and MERS. A continual problem is that viruses naturally mutate as they attempt to survive. Notable new variants of SARS-CoV-2 were first identified in the UK, South Africa, and Brazil. Variants are of particular interest because they are associated with increased transmission.

    Vaccination campaigns Common human coronaviruses typically cause mild symptoms such as a cough or a cold, but the novel coronavirus SARS-CoV-2 has led to more severe respiratory illnesses and deaths worldwide. Several COVID-19 vaccines have now been approved and are being used around the world.

  11. Average number of COVID-19 deaths in last 7 days in select countries, Mar....

    • statista.com
    Updated Aug 29, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). Average number of COVID-19 deaths in last 7 days in select countries, Mar. 1-Oct. 27 [Dataset]. https://www.statista.com/statistics/1111867/trailing-seven-day-average-number-of-covid-19-deaths-select-countries-worldwide/
    Explore at:
    Dataset updated
    Aug 29, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 1, 2020 - Oct 27, 2020
    Area covered
    Worldwide
    Description

    The seven-day average number of COVID-19 deaths in the U.S. decreased significantly from April to July 2020, but it remained higher than in other countries. Seven-day rolling averages are used to adjust for administrative delays in the reporting of deaths by authorities, commonly over weekends.

    The challenges of tracking and reporting the disease The U.S. confirmed its first coronavirus case in mid-January 2020 – the virus was detected in a passenger who arrived in Seattle from China. Since that first case, around 945 people have died every day from COVID-19 in the United States as of August 23, 2020. In total, the U.S. has recorded more coronavirus deaths than any other country worldwide. Accurately tracking the number of COVID-19 deaths has proved complicated, with countries having different rules for what deaths to include in their official figures. Some nations have even changed which deaths they can attribute to the disease during the pandemic.

    Young people urged to act responsibly Between January and May 2020, case fatality rates among COVID-19 patients in the United States increased with age, highlighting the particular risks faced by the elderly. However, COVID-19 is not only a disease that affects older adults. Surges in the number of new cases throughout July 2020 were blamed on young people. The World Health Organization has urged young people not to become complacent, reminding them to maintain social distancing guidelines and take precautions to protect themselves and others.

  12. COVID-19 Community Mobility Reports

    • google.com
    • google.com.tr
    • +4more
    csv, pdf
    Updated Oct 17, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Google (2022). COVID-19 Community Mobility Reports [Dataset]. https://www.google.com/covid19/mobility/
    Explore at:
    csv, pdfAvailable download formats
    Dataset updated
    Oct 17, 2022
    Dataset authored and provided by
    Googlehttp://google.com/
    Description

    As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

  13. COVID-19 cases and deaths among hardest hit countries worldwide as of Nov....

    • statista.com
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista, COVID-19 cases and deaths among hardest hit countries worldwide as of Nov. 14, 2022 [Dataset]. https://www.statista.com/statistics/1105264/coronavirus-covid-19-cases-most-affected-countries-worldwide/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    As of November 14, 2022, the United States had recorded almost 98 million cases of COVID-19. The country had also reported a total number of over one million deaths from the disease.

    COVID-19 testing remains important The cumulative number of coronavirus cases worldwide reached almost 633 million towards the beginning of November 2022. Demand for test kits has at times exceeded production levels, but many countries continue to test citizens to more effectively control rises in cases. The U.S. has performed the most tests worldwide, followed by India and the United Kingdom.

    The silent spread of the coronavirus Widespread testing will also help to detect people who might be asymptomatic – showing few or no symptoms of the illness. These carriers are unwittingly transmitting the virus to others, and the threat of silent transmission is one reason why mass lockdowns have been imposed around the world. However, as asymptomatic carriers produce no symptoms, they may have developed some natural immunity to the illness. Viruses are not as easily spread in communities with high rates of immunity, which helps to protect more vulnerable groups of people. When an infection rate is less than one, a community has achieved herd immunity.

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

    • statista.com
    Updated Nov 19, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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.

  15. a

    COVID-19 Trends in Each Country-Copy

    • hub.arcgis.com
    Updated Jun 4, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    United Nations Population Fund (2020). COVID-19 Trends in Each Country-Copy [Dataset]. https://hub.arcgis.com/maps/1c4a4134d2de4e8cb3b4e4814ba6cb81
    Explore at:
    Dataset updated
    Jun 4, 2020
    Dataset authored and provided by
    United Nations Population Fund
    Area covered
    Description

    COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.Revisions added on 4/23/2020 are highlighted.Revisions added on 4/30/2020 are highlighted.Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Correction on 6/1/2020Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Reasons for undertaking this work:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-30 days + 5% from past 31-56 days - total deaths.We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source used as basis:Stephen A. Lauer, MS, PhD *; Kyra H. Grantz, BA *; Qifang Bi, MHS; Forrest K. Jones, MPH; Qulu Zheng, MHS; Hannah R. Meredith, PhD; Andrew S. Azman, PhD; Nicholas G. Reich, PhD; Justin Lessler, PhD. 2020. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine DOI: 10.7326/M20-0504.New Cases per Day (NCD) = Measures the daily spread of COVID-19. This is the basis for all rates. Back-casting revisions: In the Johns Hopkins’ data, the structure is to provide the cumulative number of cases per day, which presumes an ever-increasing sequence of numbers, e.g., 0,0,1,1,2,5,7,7,7, etc. However, revisions do occur and would look like, 0,0,1,1,2,5,7,7,6. To accommodate this, we revised the lists to eliminate decreases, which make this list look like, 0,0,1,1,2,5,6,6,6.Reporting Interval: In the early weeks, Johns Hopkins' data provided reporting every day regardless of change. In late April, this changed allowing for days to be skipped if no new data was available. The day was still included, but the value of total cases was set to Null. The processing therefore was updated to include tracking of the spacing between intervals with valid values.100 News Cases in a day as a spike threshold: Empirically, this is based on COVID-19’s rate of spread, or r0 of ~2.5, which indicates each case will infect between two and three other people. There is a point at which each administrative area’s capacity will not have the resources to trace and account for all contacts of each patient. Thus, this is an indicator of uncontrolled or epidemic trend. Spiking activity in combination with the rate of new cases is the basis for determining whether an area has a spreading or epidemic trend (see below). Source used as basis:World Health Organization (WHO). 16-24 Feb 2020. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Obtained online.Mean of Recent Tail of NCD = Empirical, and a COVID-19-specific basis for establishing a recent trend. The recent mean of NCD is taken from the most recent fourteen days. A minimum of 21 days of cases is required for analysis but cannot be considered reliable. Thus, a preference of 42 days of cases ensures much higher reliability. This analysis is not explanatory and thus, merely represents a likely trend. The tail is analyzed for the following:Most recent 2 days: In terms of likelihood, this does not mean much, but can indicate a reason for hope and a basis to share positive change that is not yet a trend. There are two worthwhile indicators:Last 2 days count of new cases is less than any in either the past five or 14 days. Past 2 days has only one or fewer new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 5 days or 14 days. Most recent 5 days: In terms of likelihood, this is more meaningful, as it does represent at short-term trend. There are five worthwhile indicators:Past five days is greater than past 2 days and past 14 days indicates the potential of the past 2 days being an aberration. Past five days is greater than past 14 days and less than past 2 days indicates slight positive trend, but likely still within peak trend time frame.Past five days is less than the past 14 days. This means a downward trend. This would be an

  16. Days it took for COVID-19 deaths to double select countries worldwide as of...

    • statista.com
    Updated Dec 15, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). Days it took for COVID-19 deaths to double select countries worldwide as of Dec. 13 [Dataset]. https://www.statista.com/statistics/1104836/days-for-covid19-deaths-to-double-select-countries-worldwide/
    Explore at:
    Dataset updated
    Dec 15, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The time it takes for the number of COVID-19 deaths to double varies by country. The doubling rate in the United States was 139 days as of December 13, 2020. In comparison, the number of confirmed deaths in Australia doubled from 450 to 908 in the space of 117 days between August 18 and December 13, 2020.

    COVID-19: We are all in this together The commitment of civilians to follow basic hygiene measures and maintain social distancing must continue. The wellbeing of populations cannot be jeopardized, and young people must also engage in the response. In Australia, the 20- to 29-year-old age group accounts for the highest number of COVID-19 cases. With lockdown restrictions lifted, many people have returned to their regular routines and jumped back into socializing. However, there are concerns about complacency and suggestions that young adults could be driving spikes in coronavirus cases.

    Receive coronavirus warnings on your smartphone It is of paramount importance that countries keep a vigilant eye on the spread of the coronavirus. One way of doing so is to invest in track and trace surveillance systems. Electronic tools are not essential, but many countries are using contact-tracing smartphone apps to make the tracking of cases more efficient. In June 2020, a contact-tracing app was rolled out across Japan, and it received nearly eight million downloads in the first month. A COVID-19 alert app was also launched in Canada at the end of July 2020. The smartphone software is initially being piloted in Ontario, but it will soon be possible for people in other provinces to use the app and report a diagnosis.

  17. COVID-19 Trends in Each Country

    • coronavirus-response-israel-systematics.hub.arcgis.com
    • coronavirus-disasterresponse.hub.arcgis.com
    • +2more
    Updated Mar 28, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Urban Observatory by Esri (2020). COVID-19 Trends in Each Country [Dataset]. https://coronavirus-response-israel-systematics.hub.arcgis.com/maps/a16bb8b137ba4d8bbe645301b80e5740
    Explore at:
    Dataset updated
    Mar 28, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Earth
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

  18. T

    World Coronavirus COVID-19 Deaths

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 9, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2020). World Coronavirus COVID-19 Deaths [Dataset]. https://tradingeconomics.com/world/coronavirus-deaths
    Explore at:
    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.

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

    • statista.com
    Updated Mar 28, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). COVID-19 death rates countries worldwide as of April 26, 2022 [Dataset]. https://www.statista.com/statistics/1105914/coronavirus-death-rates-worldwide/
    Explore at:
    Dataset updated
    Mar 28, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

    A word on the flaws of numbers like this

    People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

  20. Days it took for COVID-19 cases in select countries worldwide to double as...

    • statista.com
    Updated Dec 14, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2020). Days it took for COVID-19 cases in select countries worldwide to double as of Dec. 13 [Dataset]. https://www.statista.com/statistics/1104809/days-for-covid19-cases-to-double-select-countries-worldwide/
    Explore at:
    Dataset updated
    Dec 14, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    This statistic shows the number of days it has taken for the number of coronavirus (COVID-19) cases in select countries worldwide to double as of December 13, 2020, 10:00 am CET. For example, the number of COVID-19 cases in the United States as of October 17 was 8.09 million. On December 13, the U.S. had a total of 16.25 million COVID-19 cases. So it took 57 days for the number of cases in the U.S. to double as of December 13.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Khushi Yadav (2025). Covid-19 Global Dataset [Dataset]. https://www.kaggle.com/datasets/khushikyad001/covid-19-global-dataset
Organization logo

Covid-19 Global Dataset

A realistic, artificially generated COVID-19 dataset for EDA,& visualization .

Explore at:
zip(482555 bytes)Available download formats
Dataset updated
Apr 12, 2025
Authors
Khushi Yadav
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Description

This dataset contains 3,000 rows and 26 columns of synthetically generated COVID-19 records. It replicates realistic global pandemic data, simulating values for cases, deaths, tests, vaccinations, demographics, and policy measures. The data mimics actual records from sources like Our World in Data, designed specifically for data science experimentation, visualization, and machine learning projects.

It is ideal for:

Practicing exploratory data analysis (EDA)

Creating dashboards

Building predictive models

Teaching or student projects

Kaggle Notebooks without API dependencies

Search
Clear search
Close search
Google apps
Main menu