Department of Health Law, Policy, and Management, Boston University School of Public Health, Boston, MA, United States of America.
Department of Global Health and Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States of America.
PLoS One. 2020 Dec 31;15(12):e0245008. doi: 10.1371/journal.pone.0245008. eCollection 2020.
State "shelter-in-place" (SIP) orders limited the spread of COVID-19 in the U.S. However, impacts may have varied by state, creating opportunities to learn from states where SIPs have been effective. Using a novel dataset of state-level SIP order enactment and county-level mobility data form Google, we use a stratified regression discontinuity study design to examine the effect of SIPs in all states that implemented them. We find that SIP orders reduced mobility nationally by 12 percentage points (95% CI: -13.1 to -10.9), however the effects varied substantially across states, from -35 percentage points to +11 percentage points. Larger reductions were observed in states with higher incomes, higher population density, lower Black resident share, and lower 2016 vote shares for Donald J. Trump. This suggests that optimal public policies during a pandemic will vary by state and there is unlikely to be a "one-size fits all" approach that works best.
“就地庇护”（SIP）令限制了 COVID-19 在美传播。然而，其影响可能因州而异，因此有机会从 SIP 有效的州学习经验。我们利用谷歌提供的州级 SIP 令颁布和县级流动数据的新颖数据集，采用分层回归不连续性研究设计，考察了所有实施 SIP 令的州的 SIP 令效果。我们发现， SIP 令使全国流动性减少了 12 个百分点（95%CI：-13.1 至-10.9），但各州的效果差异很大，从减少 35 个百分点到增加 11 个百分点不等。在收入较高、人口密度较高、黑人居民比例较低以及 2016 年唐纳德·J·特朗普（Donald J. Trump）选票份额较低的州，降幅更大。这表明，大流行期间的最佳公共政策将因州而异，不太可能有一种“一刀切”的最佳方法。
