Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic

Nat Commun. 2020 Aug 13;11(1):4049. doi: 10.1038/s41467-020-17922-x.


The ongoing novel coronavirus disease (COVID-19) pandemic has already infected millions worldwide and, with no vaccine available, interventions to mitigate transmission are urgently needed. While there is broad agreement that travel restrictions and social distancing are beneficial in limiting spread, recommendations around face mask use are inconsistent. Here, we use mathematical modeling to examine the epidemiological impact of face masks, considering resource limitations and a range of supply and demand dynamics. Even with a limited protective effect, face masks can reduce total infections and deaths, and can delay the peak time of the epidemic. However, random distribution of masks is generally suboptimal; prioritized coverage of the elderly improves outcomes, while retaining resources for detected cases provides further mitigation under a range of scenarios. Face mask use, particularly for a pathogen with relatively common asymptomatic carriage, is an effective intervention strategy, while optimized distribution is important when resources are limited.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Betacoronavirus / isolation & purification
  • COVID-19 / epidemiology*
  • COVID-19 / prevention & control*
  • COVID-19 / transmission
  • COVID-19 / virology
  • Coronavirus Infections / epidemiology*
  • Coronavirus Infections / prevention & control*
  • Coronavirus Infections / transmission
  • Coronavirus Infections / virology
  • Humans
  • Masks / statistics & numerical data
  • Masks / supply & distribution*
  • Models, Theoretical
  • Morbidity
  • Pandemics / prevention & control*
  • Physical Distancing
  • Pneumonia, Viral / epidemiology*
  • Pneumonia, Viral / prevention & control*
  • Pneumonia, Viral / transmission
  • Pneumonia, Viral / virology
  • Resource Allocation / methods*
  • Risk Factors
  • SARS-CoV-2