Modeling and Analysis of Risks of COVID-19 Spreading in Customized Buses Based on Seat Choice Behaviors

Abstract:

This paper aims to quantify the spreading risks of infectious disease in public transport vehicles under various distributions of the passengers. Using the spreading characteristics of COVID-19 in 2020 as an example， first， the patterns of customized bus seat choice behaviors before and after the outbreak of the disease ranging from 2019 to 2020 were analyzed. Then， based on weighted encounter network， a susceptible-exposed-infectious-recovered（SEIR） model for epidemic dynamics was constructed， while the risks of spreading of disease with various distributions of passengers were studied. Finally， a comparative analysis was conducted to quantify the impacts of different infectious disease control policies such as seat assignment optimization， ridership control， and personal protection guidance. The results demonstrate that at the beginning of the outbreak of the diseases， customized passengers spontaneously increase their distances by 15% which effectively reduced the risks of infection by over 30%. In terms of the epidemic control policies， in addition to personal protection with significant impacts on reducing the risks， the implementation of ridership control with seat assignment can also largely decrease the risks of spreading of infectious disease in public transport systems. With the optimized allocation of seats， using the current average ridership as the reference， the risk of infection may decline by about 40%.