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Social Distancing Interventions in the United States: An Exploratory Investigation of Determinants and Impacts
Shenyang Guo; Ruopeng An; Timothy D McBride; Danlin Yu; Linyun Fu; Yuanyuan Yang.
Affiliation
  • Shenyang Guo; Washington University in St. Louis
  • Ruopeng An; Washington University in St. Louis
  • Timothy D McBride; Washington University in St. Louis
  • Danlin Yu; Montclair State University
  • Linyun Fu; Washington University in St. Louis
  • Yuanyuan Yang; Washington University in St. Louis
Preprint in English | medRxiv | ID: ppmedrxiv-20117259
ABSTRACT
BackgroundTo combat the Covid-19 pandemic in the United States, many states and Washington DC enacted Stay-at-Home order and nonpharmaceutical mitigation interventions. This study examined the determinants of the timing to implement an intervention. Through an impact analysis, the study explored the effects of the interventions and the potential risks of removing them under the context of reopening the economy. MethodA content analysis identified nine types of mitigation interventions and the timing at which states enacted these strategies. A proportional hazard model, a multiple-event survival model, and a random-effect spatial error panel model in conjunction with a robust method analyzing zero-inflated and skewed outcomes were employed in the data analysis. FindingsTo our knowledge, we provided in this article the first explicit analysis of the timing, determinants, and impacts of mitigation interventions for all states and Washington DC in the United States during the first five weeks of the pandemic. Unlike other studies that evaluate the Stay-at-Home order by using simulated data, the current study employed the real data of various case counts of Covid-19. The study obtained two meritorious

findings:

(1) states with a higher prevalence of Covid-19 cases per 10,000 population reacted more slowly to the outbreak, suggesting that some states may have missed the optimal timing to prevent the wide spread of the Covid-19 disease; and (2) of nine mitigation measures, three (non-essential business closure, large-gathering bans, and restaurant/bar limitations) showed positive impacts on reducing cumulative cases, new cases, and death rates across states. InterpretationThe opposite direction of the prevalence rate on the timing of issuing the mitigation interventions partially explains why the Covid-19 caseload in the U.S. remains high. A swift implementation of social distancing is crucial-- the key is not whether such measures should be taken but when. Because there is no preventive vaccine and because there are few potentially effective treatments, recent reductions in new cases and deaths must be due, in large part, to the social interventions delivered by states. The study suggests that the policy of reopening economy needs to be implemented carefully.
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study / Prognostic study / Qualitative research / Rct Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study / Prognostic study / Qualitative research / Rct Language: English Year: 2020 Document type: Preprint
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