Estimating infectious disease transmission risk: An analysis based on multi-scale modeling of respiratory droplet transport

In the present work, a multi-scale model is used to simulate the trajectory of exhaled droplets for different types of respiratory events. By estimating the saliva viral content, information on the exhaled droplet trajectory and size distribution are exploited to derive spatial maps of viral concentration. The maps are used to estimate the risk of infection by direct inhalation for a susceptible individual exposed to exhalations. Discriminating between the droplets falling to the ground and those remaining airborne, further estimates of the risks associated with fomite and airborne transmission routes are made possible. Simulations are based on an analytical model, recently developed by the authors, implementing the equations of droplet transport, evaporation, energy, and chemical composition. Turbulent dispersion is modeled with a random walk approach, whereas the droplets are released randomly within the exhalation time span and mouth/nose orifice cross section. Droplet transport within the respiratory cloud, a critical aspect in this kind of investigation, is evaluated by coupling the analytical model to the results of unsteady computational fluid dynamics simulations of the respiratory scenarios investigated, namely: mouth breathing, nose breathing, speaking, coughing, and sneezing. Results are compared to those obtained in a previous work where the respiratory cloud was simulated through a two-dimensional unsteady empirical model proposed by the authors based on momentum conservation. The multi-scale model provides better predictions of small droplet trajectories albeit at a higher computational cost. The risk maps provided constitute a useful tool for assessing prevention needs in controlling the spread of epidemics.