A Mathematical Framework for Estimating Risk of Airborne Transmission of COVID-19 with Application to Face Mask Use and Social Distancing

TL;DR

This paper introduces a simple mathematical model to estimate airborne COVID-19 transmission risk, considering factors like face masks, social distancing, and activity level, aiming for broad accessibility and interdisciplinary use.

Contribution

It presents a straightforward, fluid dynamics-based model for assessing airborne transmission risk, incorporating mask efficacy, distancing, and activity level effects, with detailed discussion of limitations.

Findings

Face masks significantly reduce transmission risk.

Increased physical distance lowers risk substantially.

Higher activity levels increase transmission risk.

Abstract

A mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19, is presented. The model employs basic concepts from fluid dynamics and incorporates the known scope of factors involved in the airborne transmission of such diseases. Simplicity in the mathematical form of the model is by design, so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries, but also be understandable by a broad audience outside science and academia. The caveats and limitations of the model are discussed in detail. The model is used to assess the protection from transmission afforded by face coverings made from a variety of fabrics. The reduction in transmission risk associated with increased physical distance between the host and susceptible is also quantified by coupling the model with available data on scalar dispersion in canonical flows. Finally, the effect of the level of physical activity (or exercise intensity) of the host and the susceptible in enhancing transmission risk, is also assessed.