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Caspar J. van Lissa 4/1/2020

COVID-19 Metadata

A collection of relevant country/city level metadata about the COVID-19 pandemic, made interoperable for secondary analysis. Curated by Data scientists Against Corona, collaborators: Caspar van Lissa, Tim Draws, Andrii Grygoryshyn, Konstantin Tomić, and Malte Lüken.

Available data sets

The following data sets have been processed:

Category Information Source URL Progress Folder License Reference
Mobility Google mobility data Google Done google_mobility
Risk level Hospital data per country WHO Health workforce/facilities database Done WHO_OECD
Risk level Health infrastructure per country data OECD Health care resources database Done WHO_OECD
Policies Government effectiveness Worldwide Governance Indicators Done WB_GOV CC-BY 3.0
Policies COVID-19 specific regulation policies Oxford Tracker for Regulation Policies Done Ox_CGRT CC-BY 4.0 Hale, Thomas and Samuel Webster (2020)
Preparedness Global Health Security Index Nuclear Threat Initiative Done GHS CC BY-NC-ND�4.0
COVID19 Number of cases and fatalities CSSE Global Cases Done CSSE Copyright (academic use permitted) Dong, Du, & Gardner, 2020
Economic World Development Indicators World Bank Done WB_WDI CC-BY 4.0
Response Number of tests Our world in data OWID_Tests
Economic Doing Business World Bank WB_BUSINESS CC-BY 4.0
Mobility Logistics Performance Index World Bank WB_LOGISTICS CC-BY 4.0
Failed States Index World Bank WB_FAILED CC-BY 4.0
Freedom House World Bank WB_FREEDOM CC-BY 4.0
Global Indicators of Regulatory Governance World Bank WB_GOVERNANCE CC-BY 4.0
Institutional Profiles Database World Bank WB_INSTITUTIONAL CC-BY 4.0
Worldwide Buresucracy Indicators World Bank WB_BUREAUCRACY CC-BY 4.0
United Nations Conference on Trade and Development World Bank WB_TRADE_DEV CC-BY 4.0
Press Freedom Index by Reporters without Borders World Bank WB_PRESS_FREE CC-BY 4.0
Education Statistics World Bank WB_EDUCATION CC-BY 4.0
Gender Statistics World Bank WB_GENDER CC-BY 4.0
Travel & Tourism Competitiveness World Bank WB_TOURISM CC-BY 4.0
World Travel & Tourism Counsil World Bank WB_WTTC CC-BY 4.0
Poverty ans Equity Data World Bank WB_POV_EQUITY CC-BY 4.0

Folder structure:

Folder Description Permissions
data Metadata sources in .csv format (intermediate formats are acceptable until they can be made tidy). Do not edit
scripts (R)-scripts Human editable
doc Documentation for your contribution, ideally in Rmarkdown format. Rmarkdown can contain code chunks. Elaborate functions should be relegated to the ‘scripts’ folder. Human editable

How to use

Fork or clone this repository (for GitHub beginners: You can also click the green button that says “Clone or download”, and download a .zip). All data are in the /data folder. Some data are rarely updated (e.g., annual data), and some are updated daily. To ensure that you have access to the latest data for frequently updated sources, run the R-script in the run_me.R file, in the main folder.

Standards for data

Every source is condensed into one data file in .csv format, according to these specifications:

  • Data should be available on the country- or community-and-country level.
  • Recent data are the focus; if multi-year data is available, older years can be dropped
  • All variable names should be lower case
  • Mandatory variables are country (plain text country), and countryiso3 (ISO3 country code)
  • Optionally, a region variable can be added
  • Data should be in wide format: One row per country, one column per variable

Standards for data dictionary

A data_dictionary.csv is available for each data set, unless the file contents are immediately clear from the file. This data dictionary includes:

  • variable: The name of the variable in the data file
  • description: The description of this variable

Any other important information per variable can be included in this dictionary, such as sources, weights, etc.


The following issues are ongoing:

  • Adding more databases; feel free to make a suggest or request a database here
  • Added time-since first occurrence for Oxford policy / incidence trackers
  • Added last observation carried forward for WHO data


This project is under a GNU GPL v3 open source license (see the LICENSE file). Individual data sources have different licenses; always check the license before publishing based on these data.

Contributing and Contact Information

This project is open for collaborators with valuable expertise. Contribute by:

  • Filing a GitHub issue here
  • Making a pull request here

By participating in this project, you agree to abide by the Contributor Code of Conduct v2.0.

A WORCS Project

This project is based on the Workflow for Open Reproducible Code in Science (WORCS). For more details, please read the preprint at

WORCS - steps to follow for each project

Study design phase

  1. Create a new Private repository on github, copy the https:// link to clipboard
    The link should look something like
  2. In Rstudio, click File > New Project > New directory > WORCS Project Template
    1. Paste the GitHub Repository address in the textbox
    2. Keep the checkbox for renv checked if you want to document all dependencies (recommended)
    3. Select a preregistration template
  3. Write the preregistration .Rmd
  4. In the top-right corner of Rstudio, select the Git tab, select the checkboxes next to all files, and click the Commit button. Write an informative message for the commit, e.g., “Preregistration”, again click Commit, and then click the green Push arrow to send your commit to GitHub
  5. Go to the GitHub repository for this project, and tag the Commit as a preregistration
  6. Optional: Render the preregistration to PDF, and upload it to or as an attachment
  7. Optional: Add study Materials (to which you own the rights) to the repository. It is possible to solicit feedback (by opening a GitHub Issue) and acknowledge outside contributions (by accepting Pull requests)

Data analysis phase

  1. Read the data into R, and document this procedure in prepare_data.R
  2. Use open_data() or closed_data() to store the data
  3. Write the manuscript in Manuscript.Rmd, using code chunks to perform the analyses.
  4. Regularly commit your progress to the Git repository; ideally, after completing each small and clearly defined task. Use informative commit messages. Push the commits to GitHub.
  5. Cite essential references with one at-symbol ([@essentialref2020]), and non-essential references with a double at-symbol ([@@nonessential2020]).

Submission phase

  1. To save the state of the project library (all packages used), call renv::snapshot(). This updates the lockfile, renv.lock.
  2. To render the paper with essential citations only for submission, change the line knit: worcs::cite_all to knit: worcs::cite_essential. Then, press the Knit button to generate a PDF

Publication phase

  1. Make the GitHub repository public
  2. Create an OSF project; although you may have already done this in Step 6.
  3. Connect your GitHub repository to the OSF project
  4. Add an Open Science statement to the manuscript, with a link to the OSF project
  5. Optional: Publish preprint in a not-for-profit preprint repository such as PsyArchiv, and connect it to your existing OSF project
    • Check Sherpa Romeo to be sure that your intended outlet allows the publication of preprints; many journals do, nowadays - and if they do not, it is worth considering other outlets.