The transmission risk of airborne diseases in public transportation systems is a concern. This paper proposes a modified Wells-Riley model for risk analysis in public transportation systems to capture the passenger flow characteristics, including spatial and temporal patterns, in the number of boarding and alighting passengers, and in number of infectors. The model is used to assess overall risk as a function of origin–destination flows, actual operations, and factors such as mask-wearing and ventilation. The model is integrated with a microscopic simulation model of subway operations (SimMETRO). Using actual data from a subway system, a case study explores the impact of different factors on transmission risk, including mask-wearing, ventilation rates, infectiousness levels of disease, and carrier rates. In general, mask-wearing and ventilation are effective under various demand levels, infectiousness levels, and carrier rates. Mask-wearing is more effective in mitigating risks. Impacts from operations and service frequency are also evaluated, emphasizing the importance of maintaining reliable, frequent operations in lowering transmission risks. Risk spatial patterns are also explored, highlighting locations of higher risk.

空气传播疾病在公共交通系统中的传播风险值得关注。本文提出了一种改进的Wells-Riley模型，用于公共交通系统中的风险分析，以捕获客流特征，包括时空格局，登机和下车乘客的数量以及感染者的数量。该模型用于评估总体风险，该风险是起点，目的地流量，实际操作以及戴口罩和通风等因素的函数。该模型与地铁运营的微观仿真模型（SimMETRO）集成在一起。案例研究使用地铁系统的实际数据，探索了各种因素对传播风险的影响，包括戴口罩，通风率，疾病的传染性水平和携带者的比率。一般来说，面罩的佩戴和通风在各种需求水平，传染水平和携带者比例下均有效。戴口罩在减轻风险方面更有效。还评估了运营和服务频率的影响，强调了保持可靠，频繁运行以降低传输风险的重要性。还探索了风险空间格局，突出了较高风险的位置。