A structured open dataset of government interventions in response to COVID-19

  1. Amélie Desvars-Larrive
  2. Elma Dervic
  3. Nina Haug
  4. Thomas Niederkrotenthaler
  5. Jiaying Chen
  6. Anna Di Natale
  7. Jana Lasser
  8. Diana S. Gliga
  9. Alexandra Roux
  10. Johannes Sorger
  11. Abhijit Chakraborty
  12. Alexandr Ten
  13. Alija Dervic
  14. Andrea Pacheco
  15. Ania Jurczak
  16. David Cserjan
  17. Diana Lederhilger
  18. Dominika Bulska
  19. Dorontinë Berishaj
  20. Erwin Flores Tames
  21. Francisco S. Álvarez
  22. Huda Takriti
  23. Jan Korbel
  24. Jenny Reddish
  25. Joanna Grzymała-Moszczyńska
  26. Johannes Stangl
  27. Lamija Hadziavdic
  28. Laura Stoeger
  29. Leana Gooriah
  30. Lukas Geyrhofer
  31. Marcia R. Ferreira
  32. Marta Bartoszek
  33. Rainer Vierlinger
  34. Samantha Holder
  35. Simon Haberfellner
  36. Verena Ahne
  37. Viktoria Reisch
  38. Vito D. P. Servedio
  39. Xiao Chen
  40. Xochilt María Pocasangre-Orellana
  41. Zuzanna Garncarek
  42. David Garcia
  43. Stefan Thurner

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Abstract

In response to the COVID-19 pandemic, governments have implemented a wide range of non-pharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020.

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  1. Version published to 10.1038/s41597-020-00609-9
  2. ScreenIT

    SciScore for 10.1101/2020.05.04.20090498: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  3. Version published to 10.1101/2020.05.04.20090498v1 on medRxiv