Estimating the Effect of Social Distancing Interventions on COVID-19 in the United States

Andrew M. Olney; Jesse Smith; Saunak Sen; Fridtjof Thomas; H. Juliette T. Unwin

Disclosures

Am J Epidemiol. 2021;190(8):1504-1509. 

In This Article

Abstract and Introduction

Abstract

Since its global emergence in 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused multiple epidemics in the United States. When medical treatments for the virus were still emerging and a vaccine was not yet available, state and local governments sought to limit its spread by enacting various social-distancing interventions, such as school closures and lockdowns; however, the effectiveness of these interventions was unknown. We applied an established, semimechanistic Bayesian hierarchical model of these interventions to the spread of SARS-CoV-2 from Europe to the United States, using case fatalities from February 29, 2020, up to April 25, 2020, when some states began reversing their interventions. We estimated the effects of interventions across all states, contrasted the estimated reproduction numbers before and after lockdown for each state, and contrasted the predicted number of future fatalities with the actual number of fatalities as a check of the model's validity. Overall, school closures and lockdowns were the only interventions modeled that had a reliable impact on the time-varying reproduction number, and lockdown appears to have played a key role in reducing that number to below 1.0. We conclude that reversal of lockdown without implementation of additional, equally effective interventions will enable continued, sustained transmission of SARS-CoV-2 in the United States.

Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). SARS-CoV-2 was discovered in Wuhan, China, in December 2019 and rapidly spread to the rest of the world. Transmission was initially through travelers from Wuhan, but COVID-19 later spread via transmission through Asia, Europe, Australia, and North America until it was declared a pandemic by the World Health Organization on March 11, 2020. The rapid spread of SARS-CoV-2 is attributable to its transmissibility via aerosol and fomites[1,2] by presymptomatic and asymptomatic carriers[3,4] and to the relatively mild clinical characteristics of symptomatic carriers, which often include fever, cough, and fatigue.[5] However, approximately 20% of confirmed cases develop into severe or critical forms of COVID-19, which include the complications of respiratory failure, myocardial dysfunction, and acute kidney injury, with approximately a 50% mortality rate for critically ill patients.[6]

As of July 2020, outbreaks or epidemics of SARS-CoV-2 had emerged in all 50 states, with more than 2.5 million confirmed cases reported. When medical treatments and vaccines were still emerging, state and local governments sought to limit the spread of the virus by enacting various social-distancing interventions. Social-distancing interventions varied widely within states and across states. Within states, interventions typically began with public health directives like washing hands and staying home if sick; next came restrictions on or closures of places that housed vulnerable populations (such as nursing homes or schools), followed by successive, increasingly restrictive bans on gathering in groups, which culminated in stay-at-home orders or so-called lockdown. Across states, interventions have been adopted with different speeds, such that some states moved rapidly to lockdown and others never entered lockdown at all. Likewise, states lifted lockdown and reversed social-distancing interventions at different rates.

To explore the association between social-distancing interventions and the number of deaths from COVID-19, we applied an established, semimechanistic Bayesian hierarchical model of these interventions to the spread of SARS-CoV-2 from Europe[7,8] to the United States. We estimated the effects of interventions and the time-varying reproduction number (Rt) for each state using state-level daily case fatality counts.

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