Transit ridership has been seriously affected around the world by the COVID-19 pandemic. This study investigates the impacts of the COVID-19 pandemic on bus service ridership patterns in King County, Washington, using clustering and multinomial logit (MNL) models. Ridership patterns of King County Metro buses during different study periods are detected using clustering. The characteristics of ridership patterns and cluster assignment spatial distributions are further examined. The MNL models were developed using explanatory factors, including socio-demographic, transit service, and land use characteristics at each stop, that are correlated with the ridership pattern cluster assignments. Results of the developed models demonstrate disparities across socio-economic groups and unevenness throughout different neighborhoods in ridership reduction and peaking patterns during COVID-19.
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