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

基本信息

批准号：
2028675
负责人：
Bruce Desmarais
金额：
$ 1.64万
依托单位：
Pennsylvania State Univ University Park
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 2022-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028675&HistoricalAwards=false
关键词：
RAPID Collaborative Research Diffusion State

项目摘要

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减轻其传播的政策，了解这些政策选择的时间和顺序以及这些政策的最终后果至关重要。该项目收集有关州和地方政府应对 COVID-19 的数据，包括关闭学校、取消旅行、禁止公众聚会、关闭餐馆和酒吧、推迟支付租金等相关政策。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，哪些政策可以有效减缓病毒的传播和发病率。，以及各州如何以允许经济活动恢复的方式回滚政策，同时保持准备以避免和减轻病毒浪潮。该项目通过每天抓取政府网站（重点关注专门网站）来收集州政府应对 COVID-19 的数据。 COVID-19 及相关人员它还与行政部门、州立法机构和州公共卫生部门收集有关各州确诊病例、死亡人数、康复情况的数据，以及通过手机记录的地理移动数据。州政府页面上的信息包括与关闭学校、取消旅行、禁止公众集会（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以及各州何时修改这些相关的决定收集额外数据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，哪些政策可以有效减缓病毒的传播和发病率。，以及各州如何以允许经济活动恢复的方式回滚政策，同时保持准备以避免和减轻病毒浪潮。该项目由负责任的机构和行为计划以及刺激竞争性研究的既定计划共同资助。 (EPSCoR)。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（2）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Attention to the COVID‐19 Pandemic on Twitter: Partisan Differences Among U.S. State Legislators

Twitter 上对 COVID-19 大流行的关注：美国各州立法者之间的党派分歧

DOI：
10.1111/lsq.12367
发表时间：
2021-12
期刊：
Legislative Studies Quarterly
影响因子：
1.5
作者：
Kim, Taegyoon;Nakka, Nitheesha;Gopal, Ishita;Desmarais, Bruce A.;Mancinelli, Abigail;Harden, Jeffrey J.;Ko, Hyein;Boehmke, Frederick J.
通讯作者：
Boehmke, Frederick J.

Government websites as data: a methodological pipeline with application to the websites of municipalities in the United States

政府网站作为数据：适用于美国市政当局网站的方法管道