Spatio‐temporal patterns of the impact of COVID‐19 on public transit: An exploratory analysis from Lyon, France

Abstract

AbstractPublic transit has been highly impacted by coronavirus disease 2019 (COVID‐19), as well as transport demand in general. Using high‐resolution data from smart card systems, this research investigates spatial and temporal variability of the pandemic's impact on public transit in Lyon, France. The study was conducted with a sample of 95,779 daily records, distributed over years (2019, 2020, and 2021) and public transit stops (520 bus rapid transit stops, 88 tramway stops, and 40 subway stops). Clustering and statistical methods are used to assess changes observed in the data. Findings highlight variability between modes in terms of intensity of impacts, recovery patterns, and stability of the shock over time. Results show that central areas recover worse than peripheral areas and west stops recover worse than east stops. Globally, effects of COVID‐19 clear up over time, but not totally, with a faster recovery for subway. Local analysis on specific stops also suggests that public transit associated with medical facilities endures less COVID‐19 impacts than employment zones or universities.