Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
License information was derived automatically
https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F128750%2F66baee67b3e35bf9656ff816e692527e%2Fsnapshot_worldometer_july4.png?generation=1593988535797227&alt=media" alt="">
The dataset contains data about the numbers of tests, cases, deaths, serious/critical cases, active cases and recovered cases in each country for every day since April 18, and also contains the population of each country to calculate per-capita penetration of the virus
I've removed data from the "Diamond Princess" and "MS Zaandam" since they are not countries
Additionally, an auxiliray table with information about the fraction of the general population at different age groups for every country is added (taken from Wikipedia). This is specifically relevant since COVID-19 death rate is very much age dependent.
The people at "www.worldometers.info" collecting and maintaining this site really are doing very important work "https://www.worldometers.info/coronavirus/#countries">https://www.worldometers.info/coronavirus/#countries
Data about age structure for every country comes from wikipedia
It's possible to use this dataset for various purposes and analyses My goal will be to use the additional data about the number of tests performed in each country to estimate the true death and infection rates of COVID-19
JHU Coronavirus COVID-19 Global Cases, by country
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
Included Data Sources are:
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**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.
**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://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This is the data repository 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).
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.
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Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
License information was derived automatically
https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F128750%2F66baee67b3e35bf9656ff816e692527e%2Fsnapshot_worldometer_july4.png?generation=1593988535797227&alt=media" alt="">
The dataset contains data about the numbers of tests, cases, deaths, serious/critical cases, active cases and recovered cases in each country for every day since April 18, and also contains the population of each country to calculate per-capita penetration of the virus
I've removed data from the "Diamond Princess" and "MS Zaandam" since they are not countries
Additionally, an auxiliray table with information about the fraction of the general population at different age groups for every country is added (taken from Wikipedia). This is specifically relevant since COVID-19 death rate is very much age dependent.
The people at "www.worldometers.info" collecting and maintaining this site really are doing very important work "https://www.worldometers.info/coronavirus/#countries">https://www.worldometers.info/coronavirus/#countries
Data about age structure for every country comes from wikipedia
It's possible to use this dataset for various purposes and analyses My goal will be to use the additional data about the number of tests performed in each country to estimate the true death and infection rates of COVID-19