Reduction of COVID-19 Incidence and Nonpharmacologic Interventions: Analysis Using a US County-Level Policy Data Set.
Reduction of COVID-19 Incidence and Nonpharmacologic Interventions: Analysis Using a US County-Level Policy Data Set.
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DOI：
10.2196/24614
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发表时间：
2020-12-21
影响因子：
7.4
通讯作者：
Chhatwal J
中科院分区：
文献类型：
--
作者：
Ebrahim S;Ashworth H;Noah C;Kadambi A;Toumi A;Chhatwal J
在世界范围内，非药物干预措施（npi）一直是缓解COVID-19大流行的主要工具。这包括社会隔离措施（关闭企业、关闭学校和隔离有症状的人）和接触者追踪（追踪和跟踪暴露者）。虽然全球范围内的初步研究表明这些政策是有效的，但目前缺乏关于美国国家志愿机构有效性的信息。本研究的目的是在县级层面建立一个细粒度的NPI数据集，然后分析NPI政策与新冠肺炎报告病例变化之间的关系。使用标准化的众包方法，我们收集了美国1320个县的7个关键npi的时间序列数据。该开源数据集是最大、最全面的县域NPI政策数据集，可满足对高分辨率COVID-19政策数据的需求。我们的分析揭示了州内和州间县级政策的巨大差异（P< 0.001）。我们确定了工作场所关闭与COVID-19病例增长率较低之间的相关性（P= 0.004）。我们发现就地避难的执行与民主党地方选民比例（R=0.21）和民选领导人（R=0.22）的措施之间存在弱相关性。这项研究是首次在县一级进行大规模的新产品导入分析，证明新产品导入与COVID-19发病率下降之间存在相关性。未来的工作将利用该数据集探索县级政策与COVID-19传播之间的关系，以优化实时政策制定。
Worldwide, nonpharmacologic interventions (NPIs) have been the main tool used to mitigate the COVID-19 pandemic. This includes social distancing measures (closing businesses, closing schools, and quarantining symptomatic persons) and contact tracing (tracking and following exposed individuals). While preliminary research across the globe has shown these policies to be effective, there is currently a lack of information on the effectiveness of NPIs in the United States. The purpose of this study was to create a granular NPI data set at the county level and then analyze the relationship between NPI policies and changes in reported COVID-19 cases. Using a standardized crowdsourcing methodology, we collected time-series data on 7 key NPIs for 1320 US counties. This open-source data set is the largest and most comprehensive collection of county NPI policy data and meets the need for higher-resolution COVID-19 policy data. Our analysis revealed a wide variation in county-level policies both within and among states (P<.001). We identified a correlation between workplace closures and lower growth rates of COVID-19 cases (P=.004). We found weak correlations between shelter-in-place enforcement and measures of Democratic local voter proportion (R=0.21) and elected leadership (R=0.22). This study is the first large-scale NPI analysis at the county level demonstrating a correlation between NPIs and decreased rates of COVID-19. Future work using this data set will explore the relationship between county-level policies and COVID-19 transmission to optimize real-time policy formulation.
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