100+ datasets found
  1. Confirmed, death and recovery cases of COVID-19 in Greater China 2022, by...

    • statista.com
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    Statista, Confirmed, death and recovery cases of COVID-19 in Greater China 2022, by region [Dataset]. https://www.statista.com/statistics/1090007/china-confirmed-and-suspected-wuhan-coronavirus-cases-region/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    The new SARS-like coronavirus has spread around China since its outbreak in Wuhan - the capital of central China’s Hubei province. As of June 7, 2022, there were 2,785,848 active cases with symptoms in Greater China. The pandemic has caused a significant impact in the country's economy.

    Fast-moving epidemic

    In Wuhan, over 3.8 thousand deaths were registered in the heart of the outbreak. The total infection number surged on February 12, 2020 in Hubei province. After a change in official methodology for diagnosing and counting cases, thousands of new cases were added to the total figure. There is little knowledge about how the virus that originated from animals transferred to humans. While human-to-human transmission has been confirmed, other transmission routes through aerosol and fecal-oral are also possible. The deaths from the current virus COVID-19 (formally known as 2019-nCoV) has surpassed the toll from the SARS epidemic of 2002 and 2003.

    Key moments in the Chinese coronavirus timeline

    The doctor in Wuhan, Dr. Li Wenliang, who first warned about the new strain of coronavirus was silenced by the police. It was announced on February 7, 2020 that he died from the effects of the coronavirus infection. His death triggered a national backlash over freedom of speech on Chinese social media. On March 18, 2020, the Chinese government reported no new domestically transmissions for the first time after a series of quarantine and social distancing measures had been implemented. On March 31, 2020, the National Health Commission (NHC) in China started reporting the infection number of symptom-free individuals who tested positive for coronavirus. Before that, asymptomatic cases had not been included in the Chinese official count. China lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country. On April 17, 2020, health authorities in Wuhan revised its death toll, adding some 1,290 fatalities in its total count.

  2. COVID-19 confirmed and death case development in China 2020-2022

    • statista.com
    • avatarcrewapp.com
    Updated Mar 11, 2020
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    Statista (2020). COVID-19 confirmed and death case development in China 2020-2022 [Dataset]. https://www.statista.com/statistics/1092918/china-wuhan-coronavirus-2019ncov-confirmed-and-deceased-number/
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    Dataset updated
    Mar 11, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 20, 2020 - Jun 6, 2022
    Area covered
    China
    Description

    As of June 6, 2022, the novel coronavirus SARS-CoV-2 that originated in Wuhan, the capital of Hubei province in China, had infected over 2.1 million people and killed 14,612 in the country. Hong Kong is currently the region with the highest active cases in China.

    From Wuhan to the rest of China

    In late December 2019, health authorities in Wuhan detected several pneumonia cases of unknown cause. Most of these patients had links to the Huanan Seafood Market. With Chinese New Year approaching, millions of Chinese migrant workers travelled back to their hometowns for the celebration. Before the start of the travel ban on January 23, around five million people had left Wuhan. By the end of January, the number of infections had surged to over ten thousand. The death toll from the virus exceeded that of the SARS outbreak a few days later. On February 12, thousands more cases were confirmed in Wuhan after an improvement to the diagnosis method, resulting in another sudden surge of confirmed cases. On March 31, 2020, the National Health Commission (NHC) in China announced that it would begin reporting the infection number of symptom-free individuals who tested positive for coronavirus. On April 17, 2020, health authorities in Wuhan revised its death toll, adding 50 percent more fatalities. After quarantine measures were implemented, the country reported no new local coronavirus COVID-19 transmissions for the first time on March 18, 2020.

    The overloaded healthcare system

    In Wuhan, 28 hospitals were designated to treat coronavirus patients, but the outbreak continued to test China’s disease control system and most of the hospitals were soon fully occupied. To combat the virus, the government announced plans to build a new hospital swiftly. On February 3, 2020, Huoshenshan Hospital was opened to provide an additional 1,300 beds. Due to an extreme shortage of health-care professionals in Wuhan, thousands of medical staff from all over China came voluntarily to the epicenter to offer their support. After no new deaths reported for first time, China lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country.

  3. Novel Covid-19 Dataset

    • kaggle.com
    Updated Sep 18, 2025
    + more versions
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    GHOST5612 (2025). Novel Covid-19 Dataset [Dataset]. https://www.kaggle.com/datasets/ghost5612/novel-covid-19-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 18, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    GHOST5612
    License

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

    Description

    Context:

    From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, we do not know how it affects people.

    So daily level information on the affected people can give some interesting insights when it is made available to the broader data science community.

    Johns Hopkins University has made an excellent dashboard using the affected cases data. Data is extracted from the google sheets associated and made available here.

    Edited:

    Now data is available as csv files in the Johns Hopkins Github repository. Please refer to the github repository for the Terms of Use details. Uploading it here for using it in Kaggle kernels and getting insights from the broader DS community.

    Content

    2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

    This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.

    The data is available from 22 Jan, 2020.

    Here’s a polished version suitable for a professional Kaggle dataset description:

    Dataset Description

    This dataset contains time-series and case-level records of the COVID-19 pandemic. The primary file is covid_19_data.csv, with supporting files for earlier records and individual-level line list data.

    Files and Columns

    1. covid_19_data.csv (Main File)

    This is the primary dataset and contains aggregated COVID-19 statistics by location and date.

    • Sno – Serial number of the record
    • ObservationDate – Date of the observation (MM/DD/YYYY)
    • Province/State – Province or state of the observation (may be missing for some entries)
    • Country/Region – Country of the observation
    • Last Update – Timestamp (UTC) when the record was last updated (not standardized, requires cleaning before use)
    • Confirmed – Cumulative number of confirmed cases on that date
    • Deaths – Cumulative number of deaths on that date
    • Recovered – Cumulative number of recoveries on that date

    2. 2019_ncov_data.csv (Legacy File)

    This file contains earlier COVID-19 records. It is no longer updated and is provided only for historical reference. For current analysis, please use covid_19_data.csv.

    3. COVID_open_line_list_data.csv

    This file provides individual-level case information, obtained from an open data source. It includes patient demographics, travel history, and case outcomes.

    4. COVID19_line_list_data.csv

    Another individual-level case dataset, also obtained from public sources, with detailed patient-level information useful for micro-level epidemiological analysis.

    ✅ Use covid_19_data.csv for up-to-date aggregated global trends.

    ✅ Use the line list datasets for detailed, individual-level case analysis.

    Country level datasets:

    If you are interested in knowing country level data, please refer to the following Kaggle datasets:

    India - https://www.kaggle.com/sudalairajkumar/covid19-in-india

    South Korea - https://www.kaggle.com/kimjihoo/coronavirusdataset

    Italy - https://www.kaggle.com/sudalairajkumar/covid19-in-italy

    Brazil - https://www.kaggle.com/unanimad/corona-virus-brazil

    USA - https://www.kaggle.com/sudalairajkumar/covid19-in-usa

    Switzerland - https://www.kaggle.com/daenuprobst/covid19-cases-switzerland

    Indonesia - https://www.kaggle.com/ardisragen/indonesia-coronavirus-cases

    Acknowledgements :

    Johns Hopkins University for making the data available for educational and academic research purposes

    MoBS lab - https://www.mobs-lab.org/2019ncov.html

    World Health Organization (WHO): https://www.who.int/

    DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia.

    BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/

    National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml

    China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm

    Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html

    Macau Government: https://www.ssm.gov.mo/portal/

    Taiwan CDC: https://sites.google....

  4. a

    Coronavirus COVID-19 Cases V2

    • hub.arcgis.com
    • coronavirus-resources.esri.com
    • +2more
    Updated Mar 26, 2020
    + more versions
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    CSSE_covid19 (2020). Coronavirus COVID-19 Cases V2 [Dataset]. https://hub.arcgis.com/maps/1cb306b5331945548745a5ccd290188e
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    Dataset updated
    Mar 26, 2020
    Dataset authored and provided by
    CSSE_covid19
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals)and the US at county-level. Data sources: WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, state and national government health departments, and local media reports. . The China data is automatically updating at least once per hour, and non-China data is updating hourly. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.

  5. Key figures of coronavirus COVID-19 in Greater China 2022

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). Key figures of coronavirus COVID-19 in Greater China 2022 [Dataset]. https://www.statista.com/statistics/1092967/china-wuhan-coronavirus-key-figures/
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    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    The novel coronavirus that originated in the Chinese city Wuhan - the capital of Hubei province - had killed 17,826 people in Greater China. As of June 7, 2022, there were 2,785,848 active cases with symptoms in the region.

    How did it spread?

    In late December 2019, the health authorities in Wuhan detected several pneumonia cases of unknown cause. Most of these patients had links to the Huanan seafood market. The virus then spread spread rapidly to other provinces when millions of Chinese migrant workers headed home for Chinese New Year celebrations. About five billion people left Wuhan before the start of the travel ban on January 23. Right before Chinese New Year, the central government decided to put Wuhan and other cities in Hubei province on lockdown. With further travel restrictions and cancellations of public celebration events, the number of infections surpassed 80 thousand by the end of February. On March 18, 2020, China reported no new local coronavirus COVID-19 transmissions for the first time after quarantine measures had been implemented. On March 31, 2020, the National Health Commission (NHC) in China announced that it would begin reporting the infection number of symptom-free individuals who tested positive for coronavirus. After no new deaths reported for first time, the Chinese government lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country.

    What is COVID-19?

    Coronaviruses originate in animals like camels, civets and bats and are usually not transmissible to humans. But when a coronavirus mutates, it can be passed from animals to humans. The new strain of coronavirus COVID-19 is one of the seven known coronaviruses that can infect humans causing fever and respiratory infections. China's National Health Commission has confirmed the virus can be transmitted between humans through direct contact, airborne droplets. Faecal-oral transmission could also be possible. Although the death toll of COVID-19 has surpassed that of SARS, its fatality rate is relatively low compared to other deadly coronavirus, such as SARS and MERS.

  6. a

    Coronavirus cases - total active

    • udel.hub.arcgis.com
    Updated May 15, 2020
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    University of Delaware (2020). Coronavirus cases - total active [Dataset]. https://udel.hub.arcgis.com/maps/fd2fb9f316b04e5fada4501627c8dbcd
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    Dataset updated
    May 15, 2020
    Dataset authored and provided by
    University of Delaware
    Area covered
    Description

    This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China (in province level), the US, Canada, Australia (in city level), and the rest of the world (in country level).Data sources are WHO, US CDC, China NHC, ECDC, and DXY. The China data is automatically updating at least once per hour, and non China data is updating manually. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. The source feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.

  7. Table_1_Estimation of Local Novel Coronavirus (COVID-19) Cases in Wuhan,...

    • frontiersin.figshare.com
    docx
    Updated Jun 1, 2023
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    Zian Zhuang; Peihua Cao; Shi Zhao; Yijun Lou; Shu Yang; Weiming Wang; Lin Yang; Daihai He (2023). Table_1_Estimation of Local Novel Coronavirus (COVID-19) Cases in Wuhan, China from Off-Site Reported Cases and Population Flow Data from Different Sources.docx [Dataset]. http://doi.org/10.3389/fphy.2020.00336.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Zian Zhuang; Peihua Cao; Shi Zhao; Yijun Lou; Shu Yang; Weiming Wang; Lin Yang; Daihai He
    License

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

    Area covered
    Wuhan, China
    Description

    In December 2019, novel coronavirus disease (COVID-19) hit Wuhan, Hubei Province, China and spread to the rest of China and overseas. The emergence of this virus coincided with the Spring Festival Travel Rush in China. It is possible to estimate the total number of COVID-19 cases in Wuhan, by 23 January 2020, given the cases reported in other cities/regions and population flow data between Wuhan and these cities/regions. We built a model to estimate the total number of COVID-19 cases in Wuhan by 23 January 2020, based on the number of cases detected outside Wuhan city in China, with the assumption that cases exported from Wuhan were less likely underreported in other cities/regions. We employed population flow data from different sources between Wuhan and other cities/regions by 23 January 2020. The number of total cases in Wuhan was determined by the maximum log likelihood estimation and Akaike Information Criterion (AIC) weight. We estimated 8 679 (95% CI: 7 701, 9 732) as total COVID-19 cases in Wuhan by 23 January 2020, based on combined source of data from Tencent and Baidu. Sources of population flow data impact the estimates of the total number of COVID-19 cases in Wuhan before city lockdown. We should make a comprehensive analysis based on different sources of data to overcome the bias from different sources.

  8. A

    Coronavirus COVID-19 Cases V2

    • data.amerigeoss.org
    • covid19-southfield.hub.arcgis.com
    esri rest, html
    Updated Aug 11, 2020
    + more versions
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    ESRI (2020). Coronavirus COVID-19 Cases V2 [Dataset]. https://data.amerigeoss.org/sr/dataset/coronavirus-covid-19-cases-v2
    Explore at:
    esri rest, htmlAvailable download formats
    Dataset updated
    Aug 11, 2020
    Dataset provided by
    ESRI
    Description
    This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals)and the US at county-level. Data sources: WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, state and national government health departments, and local media reports. . The China data is automatically updating at least once per hour, and non-China data is updating hourly. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.
  9. COVID-19 (CSEA)

    • kaggle.com
    zip
    Updated Mar 26, 2020
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    Pratik (2020). COVID-19 (CSEA) [Dataset]. https://www.kaggle.com/pratik1235/covid19-csea
    Explore at:
    zip(406465 bytes)Available download formats
    Dataset updated
    Mar 26, 2020
    Authors
    Pratik
    Description

    Context

    From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, we do not know how it affects people.

    So daily level information on the affected people can give some interesting insights when it is made available to the broader data science community.

    Johns Hopkins University has made an excellent dashboard using the affected cases data. Data is extracted from the google sheets associated and made available here.

    Edited: Now data is available as csv files in the Johns Hopkins Github repository. Please refer to the github repository for the Terms of Use details. Uploading it here for using it in Kaggle kernels and getting insights from the broader DS community.

    Content

    2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

    This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.

    The data is available from 22 Jan, 2020.

    Column Description

    Main file in this dataset is covid_19_data.csv and the detailed descriptions are below.

    covid_19_data.csv

    • Sno - Serial number
    • ObservationDate - Date of the observation in MM/DD/YYYY
    • Province/State - Province or state of the observation (Could be empty when missing)
    • Country/Region - Country of observation
    • Last Update - Time in UTC at which the row is updated for the given province or country. (Not standardised and so please clean before using it)
    • Confirmed - Cumulative number of confirmed cases till that date
    • Deaths - Cumulative number of of deaths till that date
    • Recovered - Cumulative number of recovered cases till that date

    Apart from that these two files have individual level information

    COVID_open_line_list_data.csv This file is originally obtained from this link

    COVID19_line_list_data.csv This files is originally obtained from this link

    Country level datasets If you are interested in knowing country level data, please refer to the following Kaggle datasets: South Korea - https://www.kaggle.com/kimjihoo/coronavirusdataset Italy -
    https://www.kaggle.com/sudalairajkumar/covid19-in-italy

    Acknowledgements

    Inspiration

    Some useful insi...

  10. Total number of COVID-19 cases APAC April 2024, by country

    • statista.com
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    Statista, Total number of COVID-19 cases APAC April 2024, by country [Dataset]. https://www.statista.com/statistics/1104263/apac-covid-19-cases-by-country/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Asia, APAC
    Description

    The outbreak of the novel coronavirus in Wuhan, China, saw infection cases spread throughout the Asia-Pacific region. By April 13, 2024, India had faced over 45 million coronavirus cases. South Korea followed behind India as having had the second highest number of coronavirus cases in the Asia-Pacific region, with about 34.6 million cases. At the same time, Japan had almost 34 million cases. At the beginning of the outbreak, people in South Korea had been optimistic and predicted that the number of cases would start to stabilize. What is SARS CoV 2?Novel coronavirus, officially known as SARS CoV 2, is a disease which causes respiratory problems which can lead to difficulty breathing and pneumonia. The illness is similar to that of SARS which spread throughout China in 2003. After the outbreak of the coronavirus, various businesses and shops closed to prevent further spread of the disease. Impacts from flight cancellations and travel plans were felt across the Asia-Pacific region. Many people expressed feelings of anxiety as to how the virus would progress. Impact throughout Asia-PacificThe Coronavirus and its variants have affected the Asia-Pacific region in various ways. Out of all Asia-Pacific countries, India was highly affected by the pandemic and experienced more than 50 thousand deaths. However, the country also saw the highest number of recoveries within the APAC region, followed by South Korea and Japan.

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

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

  12. COVID-19. Novel coronavirus dataset Jan-Feb 2020

    • kaggle.com
    zip
    Updated Feb 10, 2020
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    Mukharbek Organokov (2020). COVID-19. Novel coronavirus dataset Jan-Feb 2020 [Dataset]. https://www.kaggle.com/muhakabartay/novel-coronavirus-2019ncov
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    zip(8283 bytes)Available download formats
    Dataset updated
    Feb 10, 2020
    Authors
    Mukharbek Organokov
    License

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

    Description

    Context

    Coronaviruses are a large family of viruses found in both animals and humans. Some infect people and are known to cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS).

    A novel coronavirus (CoV) is a new strain of coronavirus that has not been previously identified in humans. The new, or “novel” coronavirus, now called 2019-nCoV, had not previously detected before the outbreak was reported in Wuhan, China in December 2019.

    Short story: On December 31, 2019, the WHO was informed of an outbreak of “pneumonia of unknown cause” detected in Wuhan City, Hubei Province, China – the seventh-largest city in China with 11 million residents. As of January 23, there are over 800 cases of 2019-nCoV confirmed globally, including cases in at least 20 regions in China and nine countries/territories. The first reported infected individuals, some of whom showed symptoms as early as December 8, were discovered to be among stallholders from the Wuhan South China Seafood Market. Subsequently, the wet market was closed on Jan 1. The virus causing the outbreak was quickly determined to be a novel coronavirus. On January 10, gene sequencing further determined it to be the new Wuhan coronavirus, namely 2019-nCoV, a betacoronavirus, related to the Middle Eastern Respiratory Syndrome virus (MERS-CoV) and the Severe Acute Respiratory Syndrome virus (SARS-CoV). However, the mortality and transmissibility of 2019-nCoV are still unknown, and likely to vary from those of the prior referenced coronaviruses.

    See more information on the webpage of World Health Organization

    Content

    John Hopkins University Google Sheet of time series confirmed|recovered|death case numbers converted to CSV format.

    The data operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE).

    See also GitHub.

    Track virus here.

    Acknowledgements

    Thanks to
    - JHU CCSE
    - WHO
    - Centers for Disease Control and Prevention (CDC)
    - European Centre for Disease Prevention and Control (ECDC)
    - DXY
    - National Health Commission of the People's Republic of China (NHC)

  13. Data_Sheet_1_Strongly Heterogeneous Transmission of COVID-19 in Mainland...

    • frontiersin.figshare.com
    zip
    Updated Jun 6, 2023
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    Yuke Wang; Peter Teunis (2023). Data_Sheet_1_Strongly Heterogeneous Transmission of COVID-19 in Mainland China: Local and Regional Variation.ZIP [Dataset]. http://doi.org/10.3389/fmed.2020.00329.s001
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    zipAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Yuke Wang; Peter Teunis
    License

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

    Area covered
    China
    Description

    Background: The outbreak of novel coronavirus disease 2019 (COVID-19) started in the city of Wuhan, China, with a period of rapid initial spread. Transmission on a regional and then national scale was promoted by intense travel during the holiday period of the Chinese New Year. We studied the variation in transmission of COVID-19, locally in Wuhan, as well as on a larger spatial scale, among different cities and even among provinces in mainland China.Methods: In addition to reported numbers of new cases, we have been able to assemble detailed contact data for some of the initial clusters of COVID-19. This enabled estimation of the serial interval for clinical cases, as well as reproduction numbers for small and large regions.Findings: We estimated the average serial interval was 4.8 days. For early transmission in Wuhan, any infectious case produced as many as four new cases, transmission outside Wuhan was less intense, with reproduction numbers below two. During the rapid growth phase of the outbreak the region of Wuhan city acted as a hot spot, generating new cases upon contact, while locally, in other provinces, transmission was low.Interpretation: COVID-19 is capable of spreading very rapidly. The sizes of outbreak in provinces of mainland China mainly depended on the numbers of cases imported from Wuhan as the local reproduction numbers were low. The COVID-19 epidemic should be controllable with appropriate interventions (suspension of public transportation, cancellation of mass gatherings, implementation of surveillance and testing, and promotion of personal hygiene and face mask use).

  14. Age comparison of COVID-19 fatality rate in China 2020

    • statista.com
    Updated Aug 28, 2024
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    Statista (2024). Age comparison of COVID-19 fatality rate in China 2020 [Dataset]. https://www.statista.com/statistics/1099662/china-wuhan-coronavirus-covid-19-fatality-rate-by-age-group/
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    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    According to a medical analysis of 44,672 confirmed COVID-19 cases in China, the overall fatality rate of the novel coronavirus was 2.3 percent. As of February 11, 2020, the fatality rate of patients aged 80 years and older was 14.8 percent.

  15. a

    Where are Coronavirus COVID-19 active cases, total cases, and deaths, per...

    • uagis.hub.arcgis.com
    Updated Jun 29, 2021
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    University of Arizona GIS (2021). Where are Coronavirus COVID-19 active cases, total cases, and deaths, per Johns Hopkins University?-CpoyAB [Dataset]. https://uagis.hub.arcgis.com/maps/5d1f8549b7de4e57a48bc7bbeb8f7ce9
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    Dataset updated
    Jun 29, 2021
    Dataset authored and provided by
    University of Arizona GIS
    Area covered
    Description

    This feature layer contains the most up-to-date COVID-19 cases and latest trend plot. It covers China (in province level), the US, Canada, Australia (in city level), and the rest of the world (in country level).Data sources are WHO, US CDC, China NHC, ECDC, and DXY. The China data is automatically updating at least once per hour, and non China data is updating manually. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. The source feature layer is supported by Esri Living Atlas team and JHU Data Services. This layer is opened to the public and free to share. Contact us.

  16. Data_Sheet_1_Epidemiological Trends of Coronavirus Disease 2019 in...

    • frontiersin.figshare.com
    • figshare.com
    docx
    Updated Jun 1, 2023
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    Bilin Chen; Huanhuan Zhong; Yueyan Ni; Lulu Liu; Jinjin Zhong; Xin Su (2023). Data_Sheet_1_Epidemiological Trends of Coronavirus Disease 2019 in China.DOCX [Dataset]. http://doi.org/10.3389/fmed.2020.00259.s001
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Bilin Chen; Huanhuan Zhong; Yueyan Ni; Lulu Liu; Jinjin Zhong; Xin Su
    License

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

    Area covered
    China
    Description

    Background: The Coronavirus Disease 2019 (COVID-19) epidemic broke out in Wuhan, China, and it spread rapidly. Since January 23, 2020, China has launched a series of unusual and strict measures, including the lockdown of Wuhan city to contain this highly contagious disease. We collected the epidemiological data to analyze the trend of this epidemic in China.Methods: We closely tracked the Chinese and global official websites to collect the epidemiological information about COVID-19. The number of total and daily new confirmed cases of COVID-19 in China was presented to illustrate the trend of this epidemic.Results: On January 23, 2020, 835 confirmed COVID-19 cases were reported in China. On February 6, 2020, there were 31,211 cases. By February 20, 2020, the number reached as high as 75,993. Most cases were distributed in and around Wuhan, Hubei province. Since January 23, 2020, the number of daily new cases in China except Hubei province reached a peak of 890 on the eleventh day and then it declined to a low level of 34 within two full-length incubation periods (28 days), and the number of daily new cases in Hubei also started to decrease on the twelfth day, from 3,156 on February 4, 2020 to 955 on February 15, 2020.Conclusion: The COVID-19 epidemic has been primarily contained in China. The battle against this epidemic in China has provided valuable experiences for the rest of the world. Strict measures need to be taken as earlier as possible to prevent its spread.

  17. f

    Case data with referenced sources for cities within China from Novel...

    • datasetcatalog.nlm.nih.gov
    • rs.figshare.com
    Updated Apr 26, 2021
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    Cummings, Derek A. T.; Bridgen, Jessica R. E.; Read, Jonathan M.; Jewell, Chris P.; Ho, Antonia (2021). Case data with referenced sources for cities within China from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000815239
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    Dataset updated
    Apr 26, 2021
    Authors
    Cummings, Derek A. T.; Bridgen, Jessica R. E.; Read, Jonathan M.; Jewell, Chris P.; Ho, Antonia
    Area covered
    China
    Description

    Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39–4.13), indicating that 58–76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6–7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090–33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.

  18. COVID -19 Coronavirus Pandemic Dataset

    • kaggle.com
    zip
    Updated Sep 30, 2022
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    Aman Chauhan (2022). COVID -19 Coronavirus Pandemic Dataset [Dataset]. https://www.kaggle.com/datasets/whenamancodes/covid-19-coronavirus-pandemic-dataset/code
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    zip(10926 bytes)Available download formats
    Dataset updated
    Sep 30, 2022
    Authors
    Aman Chauhan
    Description

    Context

    The 2019–20 coronavirus pandemic is an ongoing global pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus first emerged in Wuhan, Hubei, China, in December 2019. On 11 March 2020, the World Health Organization declared the outbreak a pandemic. As of 11 March 2020, over 126,000 cases have been confirmed in more than 110 countries and territories, with major outbreaks in mainland China, Italy, South Korea, and Iran. More than 4,600 have died from the disease and 67,000 have recovered.

    Content

    2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

    This dataset has information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this data was scrapped from https://www.worldometers.info/coronavirus/.This data is solely for education purposes only.

    More - Find More Exciting🙀 Datasets Here - An Upvote👍 A Dayᕙ(`▿´)ᕗ , Keeps Aman Hurray Hurray..... ٩(˘◡˘)۶Hehe

    Acknowledgements

    This data is solely belongs to https://www.worldometers.info/coronavirus/. for licensing visit https://www.worldometers.info/licensing/

  19. Coronavirus (COVID-19) dataset

    • kaggle.com
    Updated Apr 29, 2020
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    Balaaje (2020). Coronavirus (COVID-19) dataset [Dataset]. https://www.kaggle.com/balaaje/coronavirus-covid19-dataset/metadata
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 29, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Balaaje
    Description

    Context

    The 2019–20 coronavirus pandemic is an ongoing global pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus first emerged in Wuhan, Hubei, China, in December 2019. On 11 March 2020, the World Health Organization declared the outbreak a pandemic. As of 11 March 2020, over 126,000 cases have been confirmed in more than 110 countries and territories, with major outbreaks in mainland China, Italy, South Korea, and Iran. More than 4,600 have died from the disease and 67,000 have recovered.

    Content

    2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

    This dataset has information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this data was scrapped from https://www.worldometers.info/coronavirus/.This data is solely for education purposes only.

    Acknowledgements

    This data is solely belongs to https://www.worldometers.info/coronavirus/. for licensing visit https://www.worldometers.info/licensing/

  20. f

    Data associated with the article: Epidemiological and clinical...

    • datasetcatalog.nlm.nih.gov
    • springernature.figshare.com
    Updated Apr 22, 2021
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    Xu, Yi; Niu, Shengmei; Yang, Shixiong; Cai, Pingjun; Zhou, Yueqin; Dong, Li; Liu, Jialiang; Liao, Kai; Chen, Yuguo; Guo, Jinjun; Zhang, Ying; Tian, Sijia; Li, Dou; Lou, Jing; Kang, Xuqin; Ma, Yu; Wang, Shaoping; Zhang, Jinjun (2021). Data associated with the article: Epidemiological and clinical characteristics of imported cases with COVID-19 infection: a multicentre study [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000835529
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    Dataset updated
    Apr 22, 2021
    Authors
    Xu, Yi; Niu, Shengmei; Yang, Shixiong; Cai, Pingjun; Zhou, Yueqin; Dong, Li; Liu, Jialiang; Liao, Kai; Chen, Yuguo; Guo, Jinjun; Zhang, Ying; Tian, Sijia; Li, Dou; Lou, Jing; Kang, Xuqin; Ma, Yu; Wang, Shaoping; Zhang, Jinjun
    Description

    This dataset consists of a single .xlsx spreadsheet with two tabs. The first tab contains the epidemiological and clinical features of 478 confirmed cases of COVID-19 from a multicentre study outside of Wuhan, China. It contains 21 measured variables. The second tab gives the variable list for the headings of the columns in the first tab.The included patients were those with the COVID-19 infection who were transferred from the general hospitals to the designated hospitals for special treatment of infectious diseases by Emergency Medical Service (EMS) in Beijing, Chongqing, Jinan and Nanning outside of Wuhan, China, from Jan 20 to Feb 20, 2020. The related manuscript describes the collection and analysis of this data.

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Statista, Confirmed, death and recovery cases of COVID-19 in Greater China 2022, by region [Dataset]. https://www.statista.com/statistics/1090007/china-confirmed-and-suspected-wuhan-coronavirus-cases-region/
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Confirmed, death and recovery cases of COVID-19 in Greater China 2022, by region

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6 scholarly articles cite this dataset (View in Google Scholar)
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
China
Description

The new SARS-like coronavirus has spread around China since its outbreak in Wuhan - the capital of central China’s Hubei province. As of June 7, 2022, there were 2,785,848 active cases with symptoms in Greater China. The pandemic has caused a significant impact in the country's economy.

Fast-moving epidemic

In Wuhan, over 3.8 thousand deaths were registered in the heart of the outbreak. The total infection number surged on February 12, 2020 in Hubei province. After a change in official methodology for diagnosing and counting cases, thousands of new cases were added to the total figure. There is little knowledge about how the virus that originated from animals transferred to humans. While human-to-human transmission has been confirmed, other transmission routes through aerosol and fecal-oral are also possible. The deaths from the current virus COVID-19 (formally known as 2019-nCoV) has surpassed the toll from the SARS epidemic of 2002 and 2003.

Key moments in the Chinese coronavirus timeline

The doctor in Wuhan, Dr. Li Wenliang, who first warned about the new strain of coronavirus was silenced by the police. It was announced on February 7, 2020 that he died from the effects of the coronavirus infection. His death triggered a national backlash over freedom of speech on Chinese social media. On March 18, 2020, the Chinese government reported no new domestically transmissions for the first time after a series of quarantine and social distancing measures had been implemented. On March 31, 2020, the National Health Commission (NHC) in China started reporting the infection number of symptom-free individuals who tested positive for coronavirus. Before that, asymptomatic cases had not been included in the Chinese official count. China lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country. On April 17, 2020, health authorities in Wuhan revised its death toll, adding some 1,290 fatalities in its total count.

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