Impacts of COVID-19 on urban rail transit ridership using the Synthetic Control Method

• Published in: Transport policy Vol. 111; pp. 1 - 16
• Main Authors: Xin, Mengwei, Shalaby, Amer, Feng, Shumin, Zhao, Hu
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.09.2021
• Subjects: COVID-19 effects; Relative change in daily ridership; Ridership recovery; Synthetic control method; System closure effects; System closure effects; Relative change in daily ridership; COVID-19 effects; Synthetic control method; Ridership recovery
• DOI: 10.1016/j.tranpol.2021.07.006
• ISSN: 0967-070X

The outbreak of COVID-19 in 2020 has had drastic impacts on urban economies and activities, with transit systems around the world witnessing an unprecedented decline in ridership. This paper attempts to estimate the effect of COVID-19 on the daily ridership of urban rail transit (URT) using the Synthetic Control Method (SCM). Six variables are selected as the predictors, among which four variables unaffected by the pandemic are employed. A total of 22 cities from Asia, Europe, and the US with varying timelines of the pandemic outbreak are selected in this study. The effect of COVID-19 on the URT ridership in 11 cities in Asia is investigated using the difference between their observed ridership reduction and the potential ridership generated by the other 11 cities. Additionally, the effect of the system closure in Wuhan on ridership recovery is analyzed. A series of placebo tests are rolled out to confirm the significance of these analyses. Two traditional methods (causal impact analysis and straightforward analysis) are employed to illustrate the usefulness of the SCM. Most Chinese cities experienced about a 90% reduction in ridership with some variation among different cities. Seoul and Singapore experienced a minor decrease compared to Chinese cities. The results suggest that URT ridership reductions are associated with the severity and duration of restrictions and lockdowns. Full system closure can have severe impacts on the speed of ridership recovery following resumption of service, as demonstrated in the case of Wuhan with about 22% slower recovery. The results of this study can provide support for policymakers to monitor the URT ridership during the recovery period and understand the likely effects of system closure if considered in future emergency events. •The Synthetic Control Method helps evaluate COVID-19's impact on public transit.•A reduction effect of COVID-19 on ridership is indicated in most Chinese cities.•Ridership reduction varies between cities and is not guided by the infection rate.•Ridership reduction is influenced by the severity and duration of lockdowns.•Full system closure delayed the ridership recovery following service resumption.