The American journal of the medical sciences · 2021
Policy Interventions, Social Distancing, and SARS-CoV-2 Transmission in the United States: A Retrospective State-level Analysis.
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Dreher Nickolas, Spiera Zachary, McAuley Fiona M, Kuohn Lindsey, Durbin John R, Marayati Naoum Fares, Ali Muhammad, Li Adam Y, Hannah Theodore C, Gometz Alex, Kostman J T, Choudhri Tanvir F
Аннотация
BACKGROUND: Various non-pharmaceutical interventions (NPIs) such as stay-at-home orders and school closures have been employed to limit the spread of Coronavirus disease (COVID-19). This study measures the impact of social distancing policies on COVID-19 transmission in US states during the early outbreak phase to assess which policies were most effective.
METHODS: To measure transmissibility, we analyze the average effective reproductive number (Rt) in each state the week following its 500th case and doubling time from 500 to 1000 cases. Linear and logistic regressions were performed to assess the impact of various NPIs while controlling for population density, GDP, and certain health metrics. This analysis was repeated for deaths with doubling time to 100 deaths with several healthcare infrastructure control variables.
RESULTS: States with stay-at-home orders in place at the time of their 500th case were associated with lower average Rt the following week compared to states without them (p<0.001) and significantly less likely to have an Rt>1 (OR 0.07, 95% CI 0.01-0.37, p = 0.004). These states also experienced longer doubling time from 500 to 1000 cases (HR 0.35, 95% CI 0.17-0.72, p = 0.004). States in the highest quartile of average time spent at home were also slower to reach 1000 cases than those in the lowest quartile (HR 0.18, 95% CI 0.06-0.53, p = 0.002).
CONCLUSIONS: Stay-at-home orders had the largest effect of any policy analyzed. Multivariate analyses with cellphone tracking data suggest social distancing adherence drives these effects. States that plan to scale back such measures should carefully monitor transmission metrics.
METHODS: To measure transmissibility, we analyze the average effective reproductive number (Rt) in each state the week following its 500th case and doubling time from 500 to 1000 cases. Linear and logistic regressions were performed to assess the impact of various NPIs while controlling for population density, GDP, and certain health metrics. This analysis was repeated for deaths with doubling time to 100 deaths with several healthcare infrastructure control variables.
RESULTS: States with stay-at-home orders in place at the time of their 500th case were associated with lower average Rt the following week compared to states without them (p<0.001) and significantly less likely to have an Rt>1 (OR 0.07, 95% CI 0.01-0.37, p = 0.004). These states also experienced longer doubling time from 500 to 1000 cases (HR 0.35, 95% CI 0.17-0.72, p = 0.004). States in the highest quartile of average time spent at home were also slower to reach 1000 cases than those in the lowest quartile (HR 0.18, 95% CI 0.06-0.53, p = 0.002).
CONCLUSIONS: Stay-at-home orders had the largest effect of any policy analyzed. Multivariate analyses with cellphone tracking data suggest social distancing adherence drives these effects. States that plan to scale back such measures should carefully monitor transmission metrics.