协调政府对COVID-19大流行病的反应
Cindy Cheng1, Luca Messerschmidt2, Isaac Bravo2
1Hochschule für Politik, Technical University of Munich, Richard-Wagner Str. 1, Munich, 80333, Bavaria, Germany. ccheng623@gmail.com.
Scientific data
|February 14, 2024
概括
这项研究协调了来自八个主要数据集的COVID-19公共卫生和安全措施 (PHSM) 数据. 它解决了现有数据的局限性,以便对PHSM影响进行全面分析.
科学领域:
- 流行病学 流行病学
- 公共卫生政策 公共卫生政策
- 数据科学数据科学数据科学
背景情况:
- 由于COVID-19的流行,需要采取前所未有的公共卫生和安全措施 (PHSM).
- 现有的COVID-19 PHSM数据集在地理范围,政策范围和时间覆盖方面存在局限性.
- 了解PHSM的全部影响需要全面和高质量的数据.
研究的目的:
- 协调来自八个主要的COVID-19 PHSM数据集的数据.
- 为分析PHSM创建一个全面的,高质量的数据集.
- 提供现有的PHSM数据集的比较分析,并引入一种新的协调方法.
主要方法:
- 来自八个大规模COVID-19 PHSM数据集的数据协调.
- 利用了由CoronaNet研究项目开发的分类学.
- 对现有数据集的比较分析和对协调方法的评估.
主要成果:
- 一个协调的COVID-19 PHSM数据数据集,截至2021年9月21日.
- 确定了各种PHSM数据收集工作的优缺点.
- 展示了一种用于整合多样化的PHSM数据的新方法.
结论:
- 统一的数据集为COVID-19 PHSM提供了更全面的视图.
- 新的协调方法提高了数据质量和可比性.
- 这项工作有助于对公共卫生政策多方面的影响进行更深入的研究.
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