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A structured open dataset of government interventions in response to COVID-19.
- 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.
- Subjects :
- Betacoronavirus
COVID-19
Communicable Disease Control
Coronavirus Infections diagnosis
Coronavirus Infections prevention & control
Coronavirus Infections therapy
Humans
Pandemics prevention & control
Pneumonia, Viral diagnosis
Pneumonia, Viral prevention & control
Pneumonia, Viral therapy
SARS-CoV-2
Coronavirus Infections epidemiology
Government
Pneumonia, Viral epidemiology
Subjects
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