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

Author:

Desvars-Larrive AmélieORCID,Dervic ElmaORCID,Haug NilsORCID,Niederkrotenthaler Thomas,Chen JiayingORCID,Di Natale Anna,Lasser Jana,Gliga Diana S.,Roux Alexandra,Sorger Johannes,Chakraborty Abhijit,Ten Alexandr,Dervic AlijaORCID,Pacheco Andrea,Jurczak Ania,Cserjan David,Lederhilger Diana,Bulska Dominika,Berishaj Dorontinë,Tames Erwin FloresORCID,Álvarez Francisco S.ORCID,Takriti Huda,Korbel JanORCID,Reddish Jenny,Grzymała-Moszczyńska Joanna,Stangl Johannes,Hadziavdic Lamija,Stoeger Laura,Gooriah LeanaORCID,Geyrhofer LukasORCID,Ferreira Marcia R.,Bartoszek Marta,Vierlinger Rainer,Holder Samantha,Haberfellner Simon,Ahne Verena,Reisch Viktoria,Servedio Vito D. P.,Chen Xiao,Pocasangre-Orellana Xochilt MaríaORCID,Garncarek Zuzanna,Garcia DavidORCID,Thurner Stefan

Abstract

AbstractIn 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.

Funder

Vienna Science and Technology Fund

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3