  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.
