Risk assessment of COVID-19 infection for subway commuters integrating dynamic changes in passenger numbers

Abstract

The COVID-19 global pandemic has had a significant impact on mass travel. We examined the risk of transmission of COVID-19 infection between subway commuters using the Susceptible Exposed Infected Recovered (SEIR) model. The model considered factors that may influence virus transmission, namely subway disinfection, ventilation capacity, average commuter spacing, single subway journey time, COVID-19 transmission capacity, and dynamic changes in passenger numbers. Based on these parameters, above a certain threshold (25 min), the risk of infection for susceptible people increased significantly as journey time increased. Average distance between commuters and levels of ventilation and disinfection were also important influencing factors. Meanwhile, the model also indicated that the risk of infection varied at different times of the day. Therefore, this paper recommends strengthening ventilation and disinfection in the carriages and limiting the time of single journeys, with an average distance of at least 1 m between passengers. In this light, subway commuters need to take proactive precautions to reduce their risk of COVID-19 infection. Also, the results show the importance of managing subway stations efficiently during epidemic and post-epidemic eras.

Changes on local travel behaviors under travel reduction-related interventions during COVID-19 pandemic: a case study in Hong Kong

“…The infection risk of susceptible population increased significantly with the passenger flow, and the infection risk varies with time (Li et al 2022). There was a negative correlation between COVID-19 spread and social distance, while short social distance would lead to (Seong et al 2021).…”

COVID-19 transmission and control in land public transport: A literature review

“…CDC recommended that 2 m should be kept from others [117] , Sun et al [118] proposed that 1.6–3.0 m was the safe social distance when considering the proximity of large drop spray transmission during mutual conversation activities, and the aerosol with the virus could spread 8.2 m under calm air environment. Li et al [58] recommended the average distance between passengers in a subway should be at least 1 m. However, most of the social distance between adjacent passengers in public vehicle cabins is usually less than 1 m. For example, the average interpersonal distance in the subway during rush hour is only 0.8 m [73] , which is smaller than most other social distances in the indoor environment. The proximity exposure typically means a higher infection probability.…”

Dynamic model of respiratory infectious disease transmission in urban public transportation systems

“…Particularly, some of these models focused on analyzing the role of transportation in disease transmission. For example, Cooley established a computer simulation of New York City's five boroughs that incorporated subway ridership into an SEIR model [ 22 ]; Zhang established a large-scale individual-based model for epidemic prediction in the context of the metropolitan area of Beijing China, where a microscopic public transport system (including metros and trams) is simulated [ 7 ]; Li examined the risk of transmission of COVID-19 between subway commuters using the SEIR model [ 23 ], etc. These models have played a positive role in discussing the epidemic transmitted by public transport.…”