As a first step to creating a resilient local public transportation system, the infection risk in the vehicle must be identified. Subsequently, measures to reduce the infection risk can be undertaken and communicated. This paper presents a model to identify the infection risk on local public transportation through both contact and infection probability. A simulation of the air movements inside two example vehicles under differing environmental conditions enabled the infection probability to be estimated. However, the contact probability links the infection probability to the current spread of a disease. The model includes trip parameters (the number of contacts and contact time), virus parameters (aerosol particle size, virus titer, minimal dose of infection), and epidemiologic parameters (incidence and estimated number of unreported cases), as well as environmental parameters (speaking behavior, mask wearing). The model enables the average infection risk for a certain time and area to be calculated, and also special cases of transmission in local public transportation vehicles to be investigated. It provides the present infection risk for a person using local public transportation and can be used as an objective tool for comparing the impact of measures meant to reduce infection risk (e.g. masks) by transit associations as well as policy makers. This in turn could benefit the health and wellbeing of all local public transport passengers.
Fouckhardt et al. (Tue,) studied this question.