Efficacy of face coverings in reducing transmission of COVID-19: calculations based on models of droplet capture

TL;DR

This paper evaluates how effective face coverings are in reducing COVID-19 transmission by analyzing physical filtration mechanisms, comparing model predictions with experiments, and exploring cloth mask designs as sustainable alternatives.

Contribution

It integrates physical filtration models with experimental data to predict mask efficacy and demonstrates that multi-layered cloth masks can match surgical mask performance under ideal conditions.

Findings

Three-layer cloth masks can achieve filtration comparable to surgical masks.

Good agreement between models and experimental results supports predictive capability.

Reusable cloth masks are a viable environmentally friendly alternative if properly sealed.

Abstract

In the COVID--19 pandemic, among the more controversial issues is the use of masks and face coverings. Much of the concern boils down to the question -- just how effective are face coverings? One means to address this question is to review our understanding of the physical mechanisms by which masks and coverings operate -- steric interception, inertial impaction, diffusion and electrostatic capture. We enquire as to what extent these can be used to predict the efficacy of coverings. We combine the predictions of the models of these mechanisms which exist in the filtration literature and compare the predictions with recent experiments and lattice Boltzmann simulations, and find reasonable agreement with the former and good agreement with the latter. Building on these results, we explore the parameter space for woven cotton fabrics to show that three-layered cloth masks can be constructed with comparable filtration performance to surgical masks under ideal conditions. Reusable cloth masks thus present an environmentally friendly alternative to surgical masks so long as the face seal is adequate enough to minimise leakage.