Modeling the Airborne Transmission of SARS-CoV-2 in Public Transport

Abstract

This study presents the transmission of SARS-CoV-2 in the main types of public transport vehicles and stations to comparatively assess the relative theoretical risk of infection of travelers. The presented approach benchmarks different measures to reduce potential exposure in public transport and compares the relative risk between different means of transport and situations encountered. Hence, a profound base for the selection of measures by operators, travelers and staff is provided. Zonal modeling is used as the simulation method to estimate the exposure to passengers in the immediate vicinity as well as farther away from the infected person. The level of exposure to passengers depends on parameters such as the duration of stay and travel profile, as well as the ventilation situation and the wearing of different types of masks. The effectiveness of technical and behavioral measures to minimize the infection risk is comparatively evaluated. Putting on FFP2 (N95) masks and refraining from loud speech decreases the inhaled viral load by over 99%. The results show that technical measures, such as filtering the recirculated air, primarily benefit passengers who are a few rows away from the infected person by reducing exposure 84–91%, whereas near-field exposure is only reduced by 30–69%. An exception is exposure in streetcars, which in the near-field is 17% higher due to the reduced air volume caused by the filter. Thus, it can be confirmed that the prevailing measures in public transport protect passengers from a high theoretical infection risk. At stations, the high airflows and the large air volume result in very low exposures (negligible compared to the remaining means of transport) provided that distance between travelers is kept. The comparison of typical means of transport indicates that the inhaled quanta dose depends primarily on the duration of stay in the vehicles and only secondarily on the ventilation of the vehicles. Due to the zonal modeling approach, it can also be shown that the position of infected person relative to the other passengers is decisive in assessing the risk of infection.

An evaluation of the risk of airborne transmission of COVID ‐19 on an inter‐city train carriage

“…An epidemiological study of infections on high‐speed trains in China by Hu et al 10 concluded that there was a significant risk of infection and recommended that measures such as the use of personal protective equipment and maximising distance between passengers should be used. A modelling study of the infection risk on various train types in Germany came to similar conclusions, 11 demonstrating that the risk of infection can be reduced by as much as two orders of magnitude by enforcing the wearing of FFP2 masks. Shinohara et al 12 used CO 2 sensors to evaluate the risk of infection on naturally ventilated trains and found that by opening all windows the risk could be reduced by over 90%.…”

“…It therefore seems that a well‐mixed assumption throughout the saloon can lead to some inaccuracy in the estimates of risk of infection and the number of secondary infections. A zonal approach such as that used in Noakes & Sleigh 32 and Matheis et al 11 for a hospital may provide improved estimates. Alternatively, the one‐dimensional advection–diffusion model described in de Kreij et al 20 and applied to the same inter‐city carriage is able to fully resolve the longitudinal variation in risk within the carriage for different occupancies and passenger locations.…”

Impact of pre-pandemic travel mobility patterns on the spatial diffusion of COVID-19 in South Korea

“…They also argued that the routes and main factors of public transit in diffusing COVID-19 were still unclear during the early experiences of the pandemic. Some studies have found that such measures such as mask wearing, physical distancing, air conditioning, and filtering on public transit have a significant impact on reducing exposure to COVID-19 transmission ( Kriegel et al, 2021 ; Matheis et al, 2022 ; Miller et al, 2022 ; Yang et al, 2022 ). Musselwhite et al (2020) argues that restrictions on the operation of overcrowded public transit due to the higher possibility of individual transmission of COVID-19 needs to be well thought because the exposure in households can be higher.…”

Predicting aerosol transmission in airplanes: Benefits of a joint approach using experiments and simulation

“…This same assumption has also been made to speed up simulation based approaches to model aerosol transmission in airplanes. 29 However, both measurements 30,31 and computational models 32,33 clearly show a spatial variation with increased concentrations closer to the emitter and lower concentrations farther away. Experimental work has even shown that the actual risk of infection can be higher than that predicted by the perfect mixing assumption.…”