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

Authors :
Desvars-Larrive A
Dervic E
Haug N
Niederkrotenthaler T
Chen J
Di Natale A
Lasser J
Gliga DS
Roux A
Sorger J
Chakraborty A
Ten A
Dervic A
Pacheco A
Jurczak A
Cserjan D
Lederhilger D
Bulska D
Berishaj D
Tames EF
Álvarez FS
Takriti H
Korbel J
Reddish J
Grzymała-Moszczyńska J
Stangl J
Hadziavdic L
Stoeger L
Gooriah L
Geyrhofer L
Ferreira MR
Bartoszek M
Vierlinger R
Holder S
Haberfellner S
Ahne V
Reisch V
Servedio VDP
Chen X
Pocasangre-Orellana XM
Garncarek Z
Garcia D
Thurner S
Source :
Scientific data [Sci Data] 2020 Aug 27; Vol. 7 (1), pp. 285. Date of Electronic Publication: 2020 Aug 27.
Publication Year :
2020

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.

Details

Language :
English
ISSN :
2052-4463
Volume :
7
Issue :
1
Database :
MEDLINE
Journal :
Scientific data
Publication Type :
Academic Journal
Accession number :
32855430
Full Text :
https://doi.org/10.1038/s41597-020-00609-9