城市轨道交通病毒传播风险的微观时空特征分析
Virus Transmission Risk in Urban Rail Systems: A Microscopic Simulation-based Analysis of Spatio-temporal Characteristics
摘要：
空气传播疾病在公共交通系统中的传播风险是一个令人关切的问题。本文提出了一种改进的Wells-Riley模型，用于公共交通系统的风险分析，以捕捉乘客流的特性，包括空间和时间模式的乘客数量，下车乘客，和感染者的数量。该模型被用来评估整体风险作为OD流量，实际操作，以及口罩佩戴和通风等因素的函数。该模型集成了地铁运营的微观仿真模型（SimMETRO）。使用来自地铁系统的实际数据，案例研究探讨了不同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率。一般来说，戴口罩和通风是有效的各种需求水平，传染性水平，和载体率。戴口罩更能有效降低风险。从操作和服务频率的影响也进行了评估，强调保持可靠的，频繁的操作在降低传输风险的重要性。还探讨了风险的空间模式，突出了风险较高的地点。
英文摘要：
Transmission risk of air-borne diseases in public transportation systems is a concern. The 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 terms of number of boarding, alighting passengers, and number of infectors. The model is utilized to assess overall risk as a function of OD 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
