Estimating the value of face coverings during the COVID-19 epidemic: a dynamic causal modelling study.

Introduction: The value of face coverings in the pandemic has been disputed. Dynamic causal modelling (DCM) allows one to test hypotheses about the nature of viral spread and effectiveness of interventions. Our aim was to quantify the impact of face coverings on viral transmission and deaths associated with COVID-19 between 2020 and 2023 in the UK. Methods: A DCM of the COVID-19 outbreak in the UK was used. It combines conventional (ie, Susceptible Exposed Infectious Recovered (SEIR)) epidemiological and sociobehavioural models to simultaneously fit measures of prevalence, clinical data, vaccine use and fluctuations in mobility. The model was augmented to include an effect of reported use of face coverings within the past week by adults in reducing community transmission, which was then suppressed to see what might have happened in their absence. Results: We found face coverings by adults reduced COVID-19 transmission by 5% in adults (90% CI 4.6% to 5.6%) and the elderly (90% CI 4.8% to 5.6%), but only by 2.3% in children (90% CI 1.5% to 3.4%) and had negligible effects in younger adults (0.4%, 90% CI 0.2% to 0.8%). This effect on transmission had a large impact on mortality, with an estimated saving of 102 000 (90% CI range 40 000 to 164 000) lives over the 30-month study period, suggesting a 50% reduction in mortality. Conclusions: Modelling the impact of widely used face coverings during the pandemic revealed a quantitatively small (age-dependent) impact on community transmission that translates into a marked public health impact, as estimated by the prevention of deaths.