100+ datasets found
  1. Coronavirus COVID-19 Global Cases

    • redivis.com
    application/jsonl +7
    Updated Jul 13, 2020
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    Stanford Center for Population Health Sciences (2020). Coronavirus COVID-19 Global Cases [Dataset]. http://doi.org/10.57761/pyf5-4e40
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    sas, csv, application/jsonl, spss, stata, parquet, arrow, avroAvailable download formats
    Dataset updated
    Jul 13, 2020
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 22, 2020 - Jul 12, 2020
    Description

    Abstract

    JHU Coronavirus COVID-19 Global Cases, by country

    Documentation

    PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

    This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

    Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

    Section 2

    Included Data Sources are:

    %3C!-- --%3E

    Section 3

    **Terms of Use: **

    This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

    Section 4

    **U.S. county-level characteristics relevant to COVID-19 **

    Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

    https://github.com/mkiang/county_preparedness/

  2. China CN: COVID-19: Confirmed Case: New Increase

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China CN: COVID-19: Confirmed Case: New Increase [Dataset]. https://www.ceicdata.com/en/china/covid19-no-of-patient/cn-covid19-confirmed-case-new-increase
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Apr 29, 2020 - May 10, 2020
    Area covered
    China
    Description

    China COVID-19: Confirmed Case: New Increase data was reported at 17.000 Person in 10 May 2020. This records an increase from the previous number of 14.000 Person for 09 May 2020. China COVID-19: Confirmed Case: New Increase data is updated daily, averaging 51.000 Person from Jan 2020 (Median) to 10 May 2020, with 112 observations. The data reached an all-time high of 15,152.000 Person in 12 Feb 2020 and a record low of 1.000 Person in 08 May 2020. China COVID-19: Confirmed Case: New Increase data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Patient.

  3. Duration change of TV news consumption in coronavirus outbreak in China...

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Duration change of TV news consumption in coronavirus outbreak in China 2019-2020 [Dataset]. https://www.statista.com/statistics/1108091/china-tv-news-viewing-duration-in-coronavirus-covid19-outbreak-period/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2019 - Mar 15, 2020
    Area covered
    China
    Description

    Over the first eleven weeks of 2020, Chinese consumers spent a total of ***** minutes on average watching TV news, indicating nearly a double amount of time compared to that in the equivalent period of the previous year. To curb the spread of coronavirus COVID-19, the Chinese government imposed a lockdown in the epicenter Wuhan city from late January, 2020, and later expanded the measure across the country. Most of the Chinese people relied on national TV channels to receive the most updated epidemic information.

  4. China CN: COVID-19: Confirmed Case

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China CN: COVID-19: Confirmed Case [Dataset]. https://www.ceicdata.com/en/china/covid19-no-of-patient/cn-covid19-confirmed-case
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 28, 2022 - Jan 8, 2023
    Area covered
    China
    Description

    China COVID-19: Confirmed Case data was reported at 118,147.000 Person in 08 Jan 2023. This records an increase from the previous number of 104,874.000 Person for 07 Jan 2023. China COVID-19: Confirmed Case data is updated daily, averaging 978.500 Person from Feb 2020 (Median) to 08 Jan 2023, with 1068 observations. The data reached an all-time high of 118,147.000 Person in 08 Jan 2023 and a record low of 55.000 Person in 09 Jun 2020. China COVID-19: Confirmed Case data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Patient.

  5. a

    Coronavirus COVID-19 Cases V2

    • hub.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +1more
    Updated Mar 26, 2020
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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.

  6. Shopping habit changes due to COVID-19 in China 2020

    • statista.com
    Updated Dec 20, 2024
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    Statista (2024). Shopping habit changes due to COVID-19 in China 2020 [Dataset]. https://www.statista.com/statistics/1235615/china-change-in-shopping-behavior-due-to-covid-19/
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    Dataset updated
    Dec 20, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 17, 2020 - Aug 21, 2020
    Area covered
    China
    Description

    According to a survey in China in August 2020, around 56 percent of respondents confirmed that they are more inclined to buy sustainably sourced products after the COVID-19 pandemic. Meanwhile, around 55 percent of respondent said they are also more likely to buy local products since the coronavirus outbreak.

  7. China CN: COVID-19: No of Death: Hubei: True Up

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China CN: COVID-19: No of Death: Hubei: True Up [Dataset]. https://www.ceicdata.com/en/china/covid19-no-of-death/cn-covid19-no-of-death-hubei-true-up
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Feb 13, 2020 - Apr 16, 2020
    Area covered
    China
    Description

    COVID-19: Number of Death: Hubei: True Up data was reported at 1,290.000 Person in 16 Apr 2020. This records an increase from the previous number of 1.000 Person for 05 Apr 2020. COVID-19: Number of Death: Hubei: True Up data is updated daily, averaging 1.000 Person from Feb 2020 (Median) to 16 Apr 2020, with 3 observations. The data reached an all-time high of 1,290.000 Person in 16 Apr 2020 and a record low of -108.000 Person in 13 Feb 2020. COVID-19: Number of Death: Hubei: True Up data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Death.

  8. H

    World COVID-19 Daily Cases with Basemap

    • dataverse.harvard.edu
    Updated Feb 20, 2024
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    Spatial Data Lab (2024). World COVID-19 Daily Cases with Basemap [Dataset]. http://doi.org/10.7910/DVN/L20LOT
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 20, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Spatial Data Lab
    License

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

    Area covered
    World
    Dataset funded by
    NSF
    Description

    Updated to May 13, 2021. World COVID-19 daily cases with basemap, starting from January 22, 2020.

  9. Bangladesh COVID-19 Daily Dataset

    • kaggle.com
    Updated Apr 16, 2020
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    Samrat Kumar Dey (2020). Bangladesh COVID-19 Daily Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/1085294
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 16, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Samrat Kumar Dey
    License

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

    Area covered
    Bangladesh
    Description

    Context

    COVID-19 is a novel coronavirus that emerged in China in 2019. However, Coronaviruses are zoonotic viruses that circulate amongst animals and spill ove9r to humans from time to time and have been causing illness ranging from mild symptoms to severe illness. On 7 January 2020, Chinese authorities confirmed COVID-19 and on 30 January 2020, the Director-General of WHO declared the COVID-19 outbreak a Public Health Emergency of International concern. On 8 March, Bangladesh has confirmed 3 laboratories tested coronavirus cases for the very first time. This Dataset file contains the data for analysing different cases of COVID-19 outbreak in Bangladesh. Date in a specific format, Daily new confirmed cases, Total confirmed cases, Daily new deaths, total deaths, Daily new recovered, Total recovered, Daily New Tests, Total Tests, and Active Cases are the vailable data format for this dataset.

    Content

    This dataset contains every single days data of COVID-19 outbreak in Bangladesh. From the first confirmed case of COVID-19, on 8 March 2020, it contains each confirmed, recovery, and death cases till date, This is a time-series dataset and this dataset will updated in a daily basis.

    Acknowledgements

    I would like to acknowldgwe the following organizations for their great efforts to make these data available for the greater community. Institute of Epidemiology, Disease Control and Research (IEDCR): https://www.iedcr.gov.bd/ DGHS:https://dghs.gov.bd/index.php/en/ Official Website of BD Government: http://www.corona.gov.bd/ WHO: https://www.who.int/countries/bgd/en/

    Inspiration

    As an academician and data science resercher, I feel this is an ample need for the greater data science community all over the world to understand and develop meaningful insights on the outbreak of COVID-19 in Bangladesh. Constructive suggestions and comments are highly appreciated.

  10. China CN: COVID-19: under Medical Observation

    • ceicdata.com
    Updated Dec 15, 2024
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    CEICdata.com (2024). China CN: COVID-19: under Medical Observation [Dataset]. https://www.ceicdata.com/en/china/covid19-no-of-patient/cn-covid19-under-medical-observation
    Explore at:
    Dataset updated
    Dec 15, 2024
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Apr 29, 2020 - May 10, 2020
    Area covered
    China
    Description

    China COVID-19: under Medical Observation data was reported at 5,501.000 Person in 10 May 2020. This records a decrease from the previous number of 5,840.000 Person for 09 May 2020. China COVID-19: under Medical Observation data is updated daily, averaging 15,359.500 Person from Jan 2020 (Median) to 10 May 2020, with 112 observations. The data reached an all-time high of 189,660.000 Person in 07 Feb 2020 and a record low of 922.000 Person in 20 Jan 2020. China COVID-19: under Medical Observation data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Patient.

  11. China CN: COVID-19: Confirmed Case: ytd

    • ceicdata.com
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    CEICdata.com, China CN: COVID-19: Confirmed Case: ytd [Dataset]. https://www.ceicdata.com/en/china/covid19-no-of-patient/cn-covid19-confirmed-case-ytd
    Explore at:
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Apr 29, 2020 - May 10, 2020
    Area covered
    China
    Description

    China COVID-19: Confirmed Case: Year to Date data was reported at 82,918.000 Person in 10 May 2020. This records an increase from the previous number of 82,901.000 Person for 09 May 2020. China COVID-19: Confirmed Case: Year to Date data is updated daily, averaging 80,860.000 Person from Jan 2020 (Median) to 10 May 2020, with 113 observations. The data reached an all-time high of 82,918.000 Person in 10 May 2020 and a record low of 201.000 Person in 19 Jan 2020. China COVID-19: Confirmed Case: Year to Date data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Patient.

  12. a

    Cases country

    • coronavirus-disasterresponse.hub.arcgis.com
    • coronavirus-resources.esri.com
    Updated Mar 26, 2020
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    CSSE_covid19 (2020). Cases country [Dataset]. https://coronavirus-disasterresponse.hub.arcgis.com/datasets/1cb306b5331945548745a5ccd290188e
    Explore at:
    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.

  13. f

    COVID-19 Case Reports in China

    • figshare.com
    txt
    Updated Jan 29, 2022
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    Xiao Fan Liu; Xiao-Ke Xu; Ye Wu (2022). COVID-19 Case Reports in China [Dataset]. http://doi.org/10.6084/m9.figshare.12656165.v35
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    txtAvailable download formats
    Dataset updated
    Jan 29, 2022
    Dataset provided by
    figshare
    Authors
    Xiao Fan Liu; Xiao-Ke Xu; Ye Wu
    License

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

    Area covered
    China
    Description

    Chinese prefectural level governments started to report daily confirmed COVID-19 cases online, starting from January 2020. The disclosures may contain the mobility, potential exposure scenario, epidemiological characteristics, and other useful information of individual cases. We organized a group of content coders since early March 2020, kept monitoring the information updates, manually extracted useful information from the public disclosures, and compiled these datasets.We welcome any form of collaborations with us and non-commercial reuse of our dataset. We highly encourage interested parties to examine the data, report errors in our coding, and help us to keep the data updated.The detailed data description can be found on SSRN preprint server https://dx.doi.org/10.2139/ssrn.3705815.

  14. T

    China Coronavirus COVID-19 Deaths

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    TRADING ECONOMICS (2020). China Coronavirus COVID-19 Deaths [Dataset]. https://tradingeconomics.com/china/coronavirus-deaths
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Mar 4, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 5, 2020 - Jul 14, 2022
    Area covered
    China
    Description

    China recorded 5226 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, China reported 99256991 Coronavirus Cases. This dataset includes a chart with historical data for China Coronavirus Deaths.

  15. A

    ‘COVID-19 Coronavirus Dataset’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 14, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘COVID-19 Coronavirus Dataset’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-covid-19-coronavirus-dataset-4bcc/6a53de38/?iid=022-083&v=presentation
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    Dataset updated
    Feb 14, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘COVID-19 Coronavirus Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/vignesh1694/covid19-coronavirus on 14 February 2022.

    --- Dataset description provided by original source is as follows ---

    Context

    A SARS-like virus outbreak originating in Wuhan, China, is spreading into neighboring Asian countries, and as far afield as Australia, the US a and Europe.

    On 31 December 2019, the Chinese authorities reported a case of pneumonia with an unknown cause in Wuhan, Hubei province, to the World Health Organisation (WHO)’s China Office. As more and more cases emerged, totaling 44 by 3 January, the country’s National Health Commission isolated the virus causing fever and flu-like symptoms and identified it as a novel coronavirus, now known to the WHO as 2019-nCoV.

    The following dataset shows the numbers of spreading coronavirus across the globe.

    Content

    Sno - Serial number Date - Date of the observation Province / State - Province or state of the observation Country - Country of observation Last Update - Recent update (not accurate in terms of time) Confirmed - Number of confirmed cases Deaths - Number of death cases Recovered - Number of recovered cases

    Acknowledgements

    Thanks to John Hopkins CSSE for the live updates on Coronavirus and data streaming. Source: https://github.com/CSSEGISandData/COVID-19 Dashboard: https://public.tableau.com/profile/vignesh.coumarane#!/vizhome/DashboardToupload/Dashboard12

    Inspiration

    Inspired by the following work: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

    --- Original source retains full ownership of the source dataset ---

  16. a

    Coronavirus COVID-19 Cases V2

    • covid19-southfield.hub.arcgis.com
    • data.amerigeoss.org
    Updated Mar 26, 2020
    + more versions
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    CSSE_covid19 (2020). Coronavirus COVID-19 Cases V2 [Dataset]. https://covid19-southfield.hub.arcgis.com/items/1cb306b5331945548745a5ccd290188e
    Explore at:
    Dataset updated
    Mar 26, 2020
    Dataset authored and provided by
    CSSE_covid19
    Area covered
    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.

  17. Confirmed, death and recovery cases of COVID-19 in Greater China 2022, by...

    • statista.com
    Updated Sep 2, 2024
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    Statista (2024). 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/
    Explore at:
    Dataset updated
    Sep 2, 2024
    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.

  18. C

    China CN: COVID-19: Vaccination: ytd

    • ceicdata.com
    Updated May 15, 2023
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    CEICdata.com (2023). China CN: COVID-19: Vaccination: ytd [Dataset]. https://www.ceicdata.com/en/china/covid19-vaccination/cn-covid19-vaccination-ytd
    Explore at:
    Dataset updated
    May 15, 2023
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Feb 16, 2023 - Apr 27, 2023
    Area covered
    China
    Variables measured
    Indicator
    Description

    China COVID-19: Vaccination: Year to Date data was reported at 3,494.740 Dose mn in 27 Apr 2023. This records an increase from the previous number of 3,494.432 Dose mn for 20 Apr 2023. China COVID-19: Vaccination: Year to Date data is updated daily, averaging 3,078.270 Dose mn from Dec 2020 (Median) to 27 Apr 2023, with 690 observations. The data reached an all-time high of 3,494.740 Dose mn in 27 Apr 2023 and a record low of 4.500 Dose mn in 31 Dec 2020. China COVID-19: Vaccination: Year to Date data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: Vaccination.

  19. o

    COVID-19 Pandemic - Worldwide

    • australiademo.opendatasoft.com
    • data.smartidf.services
    • +3more
    csv, excel, geojson +1
    Updated Mar 27, 2020
    + more versions
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    (2020). COVID-19 Pandemic - Worldwide [Dataset]. https://australiademo.opendatasoft.com/explore/dataset/coronavirus-covid-19-pandemic-worldwide-data/api/
    Explore at:
    geojson, json, csv, excelAvailable download formats
    Dataset updated
    Mar 27, 2020
    License

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

    Description

    This is the data for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Also, Supported by ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab (JHU APL).Data SourcesWorld 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.com/cdc.gov.tw/2019ncov/taiwan?authuser=0 US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-casesMinistry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus

  20. T

    China Coronavirus COVID-19 Recovered

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 11, 2020
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    TRADING ECONOMICS (2020). China Coronavirus COVID-19 Recovered [Dataset]. https://tradingeconomics.com/china/coronavirus-recovered
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    Mar 11, 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
    Dec 31, 2019 - Dec 15, 2021
    Area covered
    China
    Description

    China recorded 86689 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, China reported 4636 Coronavirus Deaths. This dataset includes a chart with historical data for China Coronavirus Recovered.

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Stanford Center for Population Health Sciences (2020). Coronavirus COVID-19 Global Cases [Dataset]. http://doi.org/10.57761/pyf5-4e40
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Coronavirus COVID-19 Global Cases

Explore at:
sas, csv, application/jsonl, spss, stata, parquet, arrow, avroAvailable download formats
Dataset updated
Jul 13, 2020
Dataset provided by
Redivis Inc.
Authors
Stanford Center for Population Health Sciences
Time period covered
Jan 22, 2020 - Jul 12, 2020
Description

Abstract

JHU Coronavirus COVID-19 Global Cases, by country

Documentation

PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

Section 2

Included Data Sources are:

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Section 3

**Terms of Use: **

This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

Section 4

**U.S. county-level characteristics relevant to COVID-19 **

Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

https://github.com/mkiang/county_preparedness/

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