COVID-19 dataset clearinghouse: Difference between revisions

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* [https://github.com/kgjenkins/covid-19-ny Covid-19 coronovirus cases in New York State]
* [https://github.com/kgjenkins/covid-19-ny Covid-19 coronovirus cases in New York State]
* [https://www.nytimes.com/article/coronavirus-county-data-us.html Coronavirus Case Data for Every U.S. County], New York Times
* [https://www.nytimes.com/article/coronavirus-county-data-us.html Coronavirus Case Data for Every U.S. County], New York Times
==== Europe ====
* [https://leoss.net/ Studying SARS-CoV-2 in European patients], Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)
* [https://github.com/pcm-dpc/COVID-19 COVID-19 Italia - Monitoraggio situazione]
* [https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0/data RKI COVID19] (Germany), NPGEO Corona
* [https://www.bag.admin.ch/bag/en/home/krankheiten/ausbrueche-epidemien-pandemien/aktuelle-ausbrueche-epidemien/novel-cov/situation-schweiz-und-international.html New coronavirus: Current situation – Switzerland and international], Bundesamt für Gesundheit.
** [https://www.bag.admin.ch/dam/bag/de/dokumente/mt/k-und-i/aktuelle-ausbrueche-pandemien/2019-nCoV/covid-19-datengrundlage-lagebericht.xlsx.download.xlsx/200325_Datengrundlage_Grafiken_COVID-19-Bericht.xlsx data set]


==== Other regional data ====
==== Other regional data ====
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* [https://github.com/jihoo-kim/Data-Science-for-COVID-19-old Data Science for COVID-19 in South Korea]
* [https://github.com/jihoo-kim/Data-Science-for-COVID-19-old Data Science for COVID-19 in South Korea]
** [https://www.kaggle.com/kimjihoo/coronavirusdataset The data set on Kaggle]
** [https://www.kaggle.com/kimjihoo/coronavirusdataset The data set on Kaggle]
* [https://github.com/pcm-dpc/COVID-19 COVID-19 Italia - Monitoraggio situazione]
* [https://www.health.nsw.gov.au/Infectious/diseases/Pages/covid-19-latest.aspx Latest updates on COVID-19], New South Wales
* [https://leoss.net/ Studying SARS-CoV-2 in European patients], Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)


=== Genomics and homology ===
=== Genomics and homology ===

Revision as of 10:09, 27 March 2020

This is a repository for public data sets relating to the COVID-19 pandemic. It was also initially envisioned as a clearinghouse for matching requests for data cleaning of such datasets with volunteers willing to perform this clearing, but the existing clearinghouse at Data against COVID is already up and running for this purpose, so we are redirecting such requests to that site in order not to fragment the pools of requests and volunteers.

For discussion of this project, see this blog post.

Data sets

Epidemiology

North America

Europe

Other regional data

Genomics and homology

Literature

Medical imagery

Other data

Data scrapers and aggregators

Visualizations and summaries

Other lists

Data or Data cleaning requests

As mentioned at the top of this page, future requests for data or data cleaning should be directed to Data against COVID. Below are the legacy requests of this project prior to this redirect.

From Chris Strohmeier (UCLA), Mar 25

The biorxiv_medrxiv file at https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge contains another folder titled biorxiv_medrxiv, which in turn contains hundreds of json files. Each file corresponds to a research article, at least tangentially related to COVID-19.

We are requesting:

  • A tf-idf matrix associated to the subset of the above collection which contain full-text articles (some appear to only have abstracts).
  • The rows should correspond to the (e.g. 5000) most commonly used words.
  • The columns should correspond to each individual json file.
  • The clean data should be stored as a npy or mat file (or both).
  • Finally, there should be a csv or text document (or both) explaining the meaning of the individual rows and columns of the matrix (what words do the rows correspond to? What file does each column correspond to).

Contact: c.strohmeier@math.ucla.edu

From Juan José Piñero de Armas (U. Católica de Murcia), Mar 27

We request information (on a person basis) to perform survival analyses, regressions with random effects, etc. Some data exists for instance at

https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset/data https://www.kaggle.com/kimjihoo/coronavirusdataset https://www.kaggle.com/imdevskp/covid-19-analysis-visualization-comparisons/data https://www.sirm.org/category/senza-categoria/covid-19/

but we need much more detail (date when each person was diagnosed, date of infection for the same person, discharge date, date of death, gender, age, treatments, temperatures...) not just summaries or country-aggregated data.

Contact: jjpinero@ucam.edu