Low-impact social distancing interventions to mitigate local epidemics of SARS-CoV-2

Microbes Infect. 2020 Nov-Dec;22(10):611-616. doi: 10.1016/j.micinf.2020.09.006. Epub 2020 Sep 22.

Abstract

Many jurisdictions implemented intensive social distancing to suppress SARS-CoV-2 transmission. The challenge now is to mitigate the ongoing COVID-19 epidemic without overburdening economic and social activities. An agent-based model simulated the population of King County, Washington. SARS-CoV-2 transmission probabilities were estimated by fitting simulated to observed hospital admissions. Interventions considered included encouraging telecommuting, reducing contacts to high-risk persons, and reductions to contacts outside of the home, among others. Removing all existing interventions would result in nearly 42,000 COVID-19 hospitalizations between June 2020 and January 2021, with peak hospital occupancy exceeding available beds 6-fold. Combining interventions is predicted to reduce total hospitalizations by 48% (95% CI, 47-49%), with peak COVID-19 hospital occupancy of 70% of total beds. Targeted school closures can further reduce the peak occupancy. Combining low-impact interventions may mitigate the course of the COVID-19 epidemic, keeping hospital burden within the capacity of the healthcare system.

Keywords: Biological; COVID-19; Herd; Immunity; Models; SARS-CoV-2.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19 / epidemiology*
  • COVID-19 / prevention & control
  • Communicable Disease Control / legislation & jurisprudence
  • Communicable Disease Control / methods*
  • Coronavirus Infections / prevention & control*
  • Early Medical Intervention / methods*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Masks / statistics & numerical data
  • Models, Statistical
  • Nursing Homes / standards
  • Pandemics / prevention & control*
  • Physical Distancing
  • Quarantine
  • SARS-CoV-2 / isolation & purification*
  • SARS-CoV-2 / pathogenicity
  • Virulence
  • Washington / epidemiology