Neighborhood, built environment and resilience in transportation during the COVID-19 pandemic

Weiye Xiao; Yehua Dennis Wei; Yangyi Wu

doi:10.1016/j.trd.2022.103428

Neighborhood, built environment and resilience in transportation during the COVID-19 pandemic

Transp Res D Transp Environ. 2022 Sep:110:103428. doi: 10.1016/j.trd.2022.103428. Epub 2022 Aug 12.

Authors

Weiye Xiao¹, Yehua Dennis Wei², Yangyi Wu³

Affiliations

¹ Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, Jiangsu 214000, China.
² Department of Geography, University of Utah, Salt Lake City, UT 84112-9155, USA.
³ School of Urban Design, Wuhan University, Wuhan, Hubei 430072, China.

Abstract

COVID-19 has swept the world, and the unprecedented decline in transit ridership has been noticed. However, little attention has been paid to the resilience of the transportation system, particularly in medium-sized cities. Drawing upon a light rail ridership dataset in Salt Lake County from 2017 to 2021, we develop a novel method to measure the vulnerability and resilience of transit ridership using a Bayesian structure time series model. The results show that government policies have a more significant impact than the number of COVID-19 cases on transit ridership. Regarding the built environment, a highly compact urban design might reduce the building coverage ratio and makes transit stations more vulnerable and less resilient. Furthermore, the high rate of minorities is the primary reason for the drops in transit ridership. The findings are valuable for understanding the vulnerability and resilience of transit ridership to pandemics for better coping strategies in the future.

Keywords: Bayesian structure time series; Build environment; COVID-19; Regression tree; Transit ridership.