Modeling of Indoor Airborne COVID-19 Transmission Via Human Expiratory Activities

It is well established that COVID-19 transmits from asymptomatic individuals, but the underlying mechanism remains controversial. One distinct but terrifying possibility involves “aerosol transmission,” in which breathing and normal speech yield significant quantities of particles that are too small to see by eye, but are large enough to carry a variety of communicable respiratory pathogens including SARS-CoV-2. Here we use a non-steady state eddy diffusion model with an isotropic turbulent diffusivity to predict the probability of COVID-19 transmission in an indoor environment. We focus on the idealized case of a single infector (a point source) releasing virus-laden aerosol particles into the air while breathing, speaking, or coughing. We also investigate how the size distribution of released particles and the presence of “speech superemitters”, individuals who release an order of magnitude more aerosol particles than others, affect the probability of transmission. Our results indicate that in some certain circumstances speaking can lead to higher probabilities of transmission than coughing.