A rapid method for prediction of airborne disease infection risks in an intercity bus

Abstract

In an intercity bus, respiratory infectious diseases put passengers at high risk of getting infected by the droplets exhaled by an infected person, and the risk increases when exposed to more droplets. Here, to quickly determine the concentration distribution of droplets, to predict the infection risks in a closed space, and to enhance the reliability of the conventional steady-state particle tracking method for predicting the trajectory of droplets released by coughing or sneezing, an improved steady-state particle tracking method is proposed. In it, the momentum of released droplets previously ignored in the conventional steady-state particle tracking method was specifically incorporated using experimental data. Then, the improved method was combined with a random walk model and applied to investigate all possible trajectories of droplets released by different passengers inside a bus. Consequently, the concentration distribution of droplets was obtained from the trajectory information. Finally, the Wells–Riley equation was used to predict the infection risk of every passenger based on the evaluated number of droplets inhaled per passenger. The results show that the improved steady-state tracking method performs more accurately at predicting the concentration field of droplets and associated infection risk than the conventional steady-state particle tracking method. Furthermore, the relative cost of the improved steady-state tracking method is just 1% of the transient calculation method currently considered the most accurate.