data science for covid-19

1. Cite a dataset produced by the COVID-NMA initiative by using this format:
   Thu Van Nguyen, Gabriel Ferrand, Sarah Cohen-Boulakia, Ruben Martinez, Philipp Kapp, Emmanuel Coquery, … for the COVID-NMA consortium. (2020). RCT studies on preventive measures and treatments for COVID-19 [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4266528
2. Cite a visualization developed by the COVID-NMA initiative by using this format:
   Data: Thu Van Nguyen, Gabriel Ferrand, Sarah Cohen-Boulakia, Ruben Martinez, Philipp Kapp, Emmanuel Coquery, … for the COVID-NMA consortium. (2020). RCT studies on preventive measures and treatments for COVID-19 [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4266528
   Visualizations: Romain Vuillemot - LIRIS, École Centrale de Lyon; Philippe Rivière - LIRIS, VisionsCarto; Pierre Ripoll - LIRIS, INSA Lyon; Julien Barnier - Centre Max Weber, CNRS.
   Retrieved from: ‘https://covid-nma.com/dataviz/’ [Online Resource]

https://covid-nma.com/dataviz/

https://covid-nma.com/vaccines/mapping/

https://covid-nma.com/treatments_tested/

https://ncov.dxy.cn/ncovh5/view/pneumonia?from=timeline

https://ncov.deepeye.tech/

https://www.healthmap.org/covid-19/

https://who.maps.arcgis.com/apps/opsdashboard/index.html#/c88e37cfc43b4ed3baf977d77e4a0667

https://datastudio.google.com/reporting/c84945c0-21a5-42ee-bd79-e6e02dfa43c6/page/eHUDB?s=i-m2_mCOmYM

1.Johns Hopkins University

Johns Hopkins University

The Center for Systems Science and Engineering (CSSE) at Johns Hopkins University(JHU)

https://systems.jhu.edu/

 Visualization:JHU CSSE.

Automation Support:Esri Living Atlas team.

Read more in thisblog.

Data sources:WHO,CDC,ECDC, NHC andDXY.

Downloadable Google Sheet (new link):Here. Time series table:Here. Feature service:Here.

Point level: City level - US, Canada and Australia; Province level - China; Country level - other countries.

 maps

https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

http://www.arcgis.com/apps/opsdashboard/index.html#/85320e2ea5424dfaaa75ae62e5c06e61

https://systems.jhu.edu/research/public-health/ncov-model-2/

2.Git hub

https://github.com/

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

https://github.com/search?q=ncov+2019(715)

https://github.com/shfshanyue/2019-ncov

https://github.com/BlankerL/DXY-COVID-19-Crawler

3.kaggle

https://www.kaggle.com/

The goal of this page is to bring together the most useful contributions from the Kaggle community's COVID-19 work into a single place. It is organized into literature review, tools and datasets.

https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge

https://www.kaggle.com/covid-19-contributions

https://www.kaggle.com/search?q=2019+ncov（257）

https://www.kaggle.com/paultimothymooney/coronavirus-genome-sequence/discussion/132982#latest-759834

https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset

https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset/discussion/129594#latest-764827

4.tableau

https://public.tableau.com/

https://public.tableau.com/zh-cn/search/all/ncov（161）

https://public.tableau.com/profile/dennis199441#!/vizhome/2019-nCoVMap/2019-nCoVMap

5.mathematica

https://community.wolfram.com/groups/-/m/t/1872608?source=frontpage-latest-news