five

Institutional Origins of COVID-19 Public Health Protective Policy Response (PPI)

收藏
ICPSR2022-01-01 更新2026-04-16 收录
下载链接:
https://www.openicpsr.org/openicpsr/project/123401/version/V6/view?path=/openicpsr/123401/fcr:versions/V6/data/PPI_regions_m1/PPI_regions_DE_m1.csv&type=file
下载链接
链接失效反馈
官方服务:
资源简介:
The PPI measures public health government responses to COVID-19 at all levels of government throughout the world. The PPI measure considers the extent of COVID-19 policy responses in the following categories: state of emergencies, border closures, school closures, social gathering, and social distancing limitations, home-bound policies, medical isolation policies, closure/restriction of businesses and services, and the mandates to wear face masks. The coding for public health policies is based on government websites and reputable news sources reporting the adoption of these policies.<br><br>Total, National, and Subnational Indices are calculated based on the standing public health policies adopted at various levels of government for each unit (state, province, etc.) for each day, by adding together the highest values across levels of government in each category on that day and normalizing it to range between 0 and 1.<br><br>National and subnational PPIs were constructed with the values in each category from just national- or just subnational-level policies. The current version of the data set contains public health protective policies on the national and sub-national levels, while we plan to expand to the municipal level in the future. The unit of analysis is unit-day.<br><br>Regular updates of this dataset are posted in the dedicated GitHub repository (https://github.com/COVID-policy-response-lab/PPI-data). <br><br>An ArcGIS dashboard with the project data can be found here: https://elcamaleon.binghamton.edu/portal/apps/opsdashboard/index.html#/cc61a3652eb74b8ea8864928e8026...<br><br><br><br>
提供机构:
Binghamton University; Boise State University; Pennsylvania State University; Rutgers, the State University of New Jersey; National Research University-Higher School of Economics; University of Exeter
创建时间:
2022-01-01
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作