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Unified dataset for a better understanding of COVID-19

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COVID-19 Data Hub

DOI eRum2020::CovidR

The repository aims at developing a unified dataset by collecting worldwide fine-grained case data, merged with exogenous variables helpful for a better understanding of COVID-19. Available in:

R | Python | MATLAB | Scala | Julia | Node.js | Excel

The data are updated on an hourly basis. Read more

Exciting news!

Version 3.0 of the Data Hub will be released soon! This includes a new set of identifiers to enable geospatial analysis by linking to the GADM database. NUTS codes for Europe are also included. Data on the first and second doses of vaccines will be included as well. The data coverage for

has been significantly extended. What this means for you:
  • if you are not using the columns
    , and
    of the dataset (see here), nothing changes for you.
  • if you are using some of the columns above (e.g., FIPS codes for US), please use the new column
    . This contains the main identifier used by the local authorities (usually the national institute of statistics) regardless of its type (e.g., numeric, 2 character code, other). For a short period of time (starting 14 October 2021), both the previous keys and the new
    are made available to help the transition.
  • if you are accessing the columns by position (not recommended!) you may experience shifts in the column index.
  • for any question, please open an issue

Historical Data

The dataset includes the time series of vaccines, tests, cases, deaths, recovered, hospitalizations, intensive therapy, policy measures and more. See the full dataset documentation.

Administrative Areas

The data are available at different levels of granularity:

  • admin area level 1: administrative area of top level, usually countries.
  • admin area level 2: usually states, regions, cantons.
  • admin area level 3: usually cities, municipalities.

Direct Download

The latest and vintage CSV data files are available here.

Use Cases

See the projects and publications that use COVID-19 Data Hub.

Cite as

We have invested a lot of time and effort in creating COVID-19 Data Hub, please agree to the Terms of Use and cite the following reference when using it:

Guidotti, E., Ardia, D., (2020), "COVID-19 Data Hub", Journal of Open Source Software 5(51):2376, doi: 10.21105/joss.02376.

A BibTeX entry for LaTeX users is:

    title = {COVID-19 Data Hub},
    year = {2020},
    doi = {10.21105/joss.02376},
    author = {Emanuele Guidotti and David Ardia},
    journal = {Journal of Open Source Software},
    volume = {5},
    number = {51},
    pages = {2376}

Supported by

R Consortium IVADO HEC Montréal Hack Zurich Università degli Studi di Milano

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