A structured open dataset of government interventions in response to COVID-19
| Autor: | Erwin Flores Tames, Alija Dervic, Amélie Desvars-Larrive, Dorontinë Berishaj, Jiaying Chen, Dominika Bulska, Vito D. P. Servedio, Diana Lederhilger, Xochilt Pocasangre-Orellana, Alexandra Roux, Huda Takriti, Thomas Niederkrotenthaler, Jana Lasser, Leana Gooriah, Márcia R. Ferreira, Samantha Holder, Andrea Pacheco, Lamija Hadziavdic, Anna Di Natale, Zuzanna Garncarek, Joanna Grzymała-Moszczyńska, Abhijit Chakraborty, Lukas Geyrhofer, Viktoria Reisch, Marta Bartoszek, David Cserjan, Nils Haug, Diana S. Gliga, Elma Dervic, Johannes Stangl, Francisco S. Álvarez, Jenny Reddish, Rainer Vierlinger, Ania Jurczak, Stefan Thurner, Alexandr Ten, Simon Haberfellner, Laura Stoeger, Xiao Chen, David Garcia, Verena Ahne, Johannes Sorger, Jan Korbel |
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| Přispěvatelé: | Complexity Science Hub Vienna (CSHV), sans affiliation, Sexualité et soins (Genre, Sexualité, Santé) (CESP - INSERM U1018 - Equipe 7), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Flowing Epigenetic Robots and Systems (Flowers), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Unité d'Informatique et d'Ingénierie des Systèmes (U2IS), École Nationale Supérieure de Techniques Avancées (ENSTA Paris)-École Nationale Supérieure de Techniques Avancées (ENSTA Paris), University of Vienna [Vienna], German Centre for Integrative Biodiversity Research (iDiv), Uniwersytet Jagielloński w Krakowie = Jagiellonian University (UJ), University of Warsaw (UW), Fundación Naturaleza El Salvador, D.G. and A.D.N. acknowledge funding from the Vienna Science and Technology Fund - WWTF (VRG16-005). S.T. acknowledges funding from the Austrian Research Promotion Agency FFG (project number 882184) and the Vienna Science and Technology Fund - WWTF (COV20-017)., Sans affiliation, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Data Descriptor Knowledge management 010504 meteorology & atmospheric sciences Standardization Computer science public policy Pneumonia Viral Psychological intervention Population health Library and Information Sciences 01 natural sciences Education 03 medical and health sciences Betacoronavirus Databases dataset Humans lcsh:Science Pandemics 030304 developmental biology 0105 earth and related environmental sciences 0303 health sciences Government business.industry SARS-CoV-2 governmental intervention COVID-19 Timeline Covid 19 Transparency (behavior) 3. Good health Computer Science Applications covid-19 Content analysis Viral infection Preparedness ddc:320 Communicable Disease Control lcsh:Q Statistics Probability and Uncertainty business Coronavirus Infections [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology Information Systems |
| Zdroj: | Scientific Data Scientific Data, Nature Publishing Group, 2020, 7 (1), ⟨10.1038/s41597-020-00609-9⟩ Scientific Data, 2020, 7 (1), ⟨10.1038/s41597-020-00609-9⟩ Scientific Data, Vol 7, Iss 1, Pp 1-9 (2020) |
| ISSN: | 2052-4463 |
| DOI: | 10.1038/s41597-020-00609-9 |
| Popis: | 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. Measurement(s) time at medical intervention • medical intervention Technology Type(s) digital curation • content analysis strategy of existing information sources Factor Type(s) non-pharmaceutical intervention • date Sample Characteristic - Location global Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12668792 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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