RAPID: Collaborative Research: The Diffusion of State Policy Responses to the 2019 Novel Coronavirus

RAPID：合作研究：国家对 2019 年新型冠状病毒的政策反应的扩散

• 批准号: 2028674
• 负责人: Jeffrey Harden
• 金额: $ 0.87万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-15 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028674&HistoricalAwards=false
• 关键词: RAPID; Collaborative; Research; Diffusion; State

When the 2019 novel coronavirus arrived in the United States in February and March of 2020, state governments quickly began enacting policies intended to contain and mitigate its spread. Understanding the timing and sequence of these policy choices, and those policies’ eventual consequences, is critical for assessing how governments can be most effective during pandemics. This project collects data on state and local governments’ responses to COVID-19, including policies related to closing schools, canceling travel, banning public gatherings, closing restaurants and bars, delaying rent payments, and rules on medical licenses. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigated waves of the virus. This project collects data on state government responses to COVID-19 by scraping government websites daily, focusing on sites dedicated to COVID-19 and those associated with the executive branch, state legislatures, and state departments of public health. It also collects data on the number of diagnosed cases, fatalities, recoveries in the states, and mobility data that tracks geographic movements from mobile phones. The policy recommendations or decisions recorded from state government pages include decisions related to closing schools, canceling travel, banning public gatherings (and their size), closing restaurants and bars, travel quarantines, postponing elections, safe shelter orders, limiting elective medical procedures, as well as when states modify these policies; additional data is collected from official state Twitter accounts. This data allows researchers to examine the factors that influence states’ policy choices, whether those factors differ from the ways in which states enact policies during normal times, which policies are effective in slowing the spread and morbidity of the virus, and how states roll back policies in a manner that allows economic activity to resume while maintaining preparedness to avoid and mitigated waves of the virus. This project is jointly funded by the Accountable Institutions and Behavior Program and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

当2019年新型冠状病毒于2020年2月和3月抵达美国时，各州政府迅速开始制定旨在遏制和缓解其传播的政策。了解这些政策选择的时机和顺序，以及这些政策的最终后果，对于评估政府如何在大流行期间最有效发挥作用至关重要。该项目收集了州和地方政府应对COVID-19的数据，包括与关闭学校、取消旅行、禁止公共集会、关闭餐馆和酒吧、延迟支付租金以及医疗执照规定有关的政策。这些数据使研究人员能够研究影响各州政策选择的因素，这些因素是否与各州在正常时期制定政策的方式不同，哪些政策有效地减缓了病毒的传播和发病率，以及各州如何以一种允许经济活动恢复的方式回退政策，同时保持防范和减轻病毒浪潮的准备。该项目通过每天抓取政府网站收集州政府应对COVID-19的数据，重点关注COVID-19专用网站以及与行政部门、州立法机构和州公共卫生部门相关的网站。它还收集有关各州确诊病例、死亡人数、康复人数的数据，以及追踪移动电话地理移动的移动数据。从州政府页面上记录的政策建议或决定包括与关闭学校、取消旅行、禁止公共集会（及其规模）、关闭餐馆和酒吧、旅行隔离、推迟选举、安全庇护令、限制选择性医疗程序有关的决定，以及各州何时修改这些政策；其他数据来自官方推特账户。这些数据使研究人员能够研究影响各州政策选择的因素，这些因素是否与各州在正常时期制定政策的方式不同，哪些政策有效地减缓了病毒的传播和发病率，以及各州如何以一种允许经济活动恢复的方式回退政策，同时保持防范和减轻病毒浪潮的准备。该项目由问责机构和行为计划以及促进竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。