During the COVID-19 pandemic, interventions were decided under rapidly changing, conjectural conditions, with limited (if any) prior experience. Worldwide, governments have implemented country-specific control strategies to prevent the introduction and mitigate the spread of the virus. However, were those measures effective?
Researchers at the Complexity Science Hub Vienna are building a comprehensive database of non-pharmaceutical interventions (NPIs) taken by the governments worldwide in order to assess the impact of these actions on the spread of the COVID-19 in the respective countries.
Data
Students, researchers, and volunteers are collecting data from public sources on the implemented NPIs, including the time schedules for the implementation.
The dataset describes the implemented NPIs for 57 countries, including the Diamond Princess cruise ship. Measures implemented at the subnational level (state, region, city) are also included.
The CCCSL provides the date of implementation of the NPI. Date of announcement was used when the date of implementation of the NPI could not be found (this is then specified in the field Comment).
NPIs are listed in a standardized manner, i.e. classified using a four-level hierarchical coding scheme (theme/category/subcategory/code). Eight major themes (level 1, L1 of the classification scheme) were identified and each NPI is assigned to one of them:
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- Case identification, contact tracing and related measures
- Environmental measures
- Healthcare and public health capacity
- Resource allocation
- Returning to normal life
- Risk communication
- Social distancing
- Travel restriction
Then the specific description of each NPI is coded into category (L2), subcategory (L3) and code (L4) that describe the intervention onto subsequent levels of details.
The Master List of Codes provided on the Github shows all combinations of theme/category/subcategory/code used in the CCCSL dataset.
R Codes for exploring the CCCSL dataset are available at: https://doi.org/10.5281/zenodo.3949808 and https://github.com/amel-github/CCCSL-Codes
Data access
The Data can be found at https://github.com/amel-github/covid19-interventionmeasures
The CCCSL dataset is continuously updated.
Cite as:
Desvars-Larrive A., Ahne V., Álvarez S., Bartoszek M., Berishaj D., Bulska D., Chakraborty A., Chen E., Chen X., Cserjan D., Dervic A., Dervic E., Di Natale A., Ferreira M.R., Flores Tames E., Garcia D., Garncarek Z., Gliga D.S., Gooriah L., Grzymała-Moszczyńska J., Jurczak A., Haberfellner S., Hadziavdic L., Haug N., Holder S., Korbel J., Lasser J., Lederhilger D., Niederkrotenthaler T., Pacheco A., Pocasangre-Orellana X.M., Reddish J., Reisch V., Roux A., Sorger J., Stangl J., Stoeger L., Takriti H., Ten A., Vierlinger R., Thurner S. CCCSL: Complexity Science Hub Covid-19 Control Strategies List (2020). Version 2.0. https://github.com/amel-github/covid19-interventionmeasures
Data use license
Creative Commons Share-Alike with Attribution: CC BY-SA 4.0.
Publication
Our paper has been published in Scientific Data: Desvars-Larrive, A., Dervic, E., Haug, N. et al.
A structured open dataset of government interventions in response to COVID-19. Sci Data 7, 285 (2020). https://doi.org/10.1038/s41597-020-00609-9
We are waiting for your feedback…
If you see any inaccuracies in the underlying data or if some NPIs are missing, please contact us via the form here.
The CCCSL is part of a worldwide initiative
Joining a global effort to fight the pandemic, our dataset has been integrated into the Global Dataset of Public Health and Social Measures (PHSM) aggregated by the World Health Organization (WHO): https://www.who.int/emergencies/diseases/novel-coronavirus-2019/phsm
Descriptive visualizations of the dataset
Countries
Other initiatives on the topic
https://lukaslehner.github.io/covid19policytrackers/
Contact information
Grant
Acknowledgments
Country visualizations by Michael Gruber and Jana Lasser. Website by David Garcia and Michael Gruber.