基于选座行为的定制公交车内新冠病毒传播风险建模与分析

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

摘要:

为精细度量公共交通车厢内不同乘客位置分布下的传染病传播风险，以新冠病毒早期传播特征为例，首先，分析了我国2019—2020年新冠病毒感染爆发前后的定制公交乘客选座行为变化规律。其次，基于加权接触网络，构建了传染病扩散模型（susceptible-exposed-infectious-recovered，SEIR），并探究了不同乘客位置分布下的新冠病毒传播风险。最后，量化对比分析了优化座位分配、控制上车人数、引导个人防护等管理策略下的防控效果。结果表明，新冠病毒爆发初期，乘客自发将座间距离增大15%，降低了超30%的感染风险；在防控策略方面，除个人防护可取得显著效果外，通过控制上车人数与优化乘客座位分布，也可大幅降低公交系统内的新冠病毒扩散风险。在最优选座策略下，以现有平均班次客流为参照，乘客感染风险可下降约40%。

关键词:公共交通;选座行为;加权接触网络;新冠病毒传播规律;定制公交

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%.

Key words:public transport;seat choice behaviors;weighted encounter network;patterns of covid-19 spreading;customized bus