Spatial and Temporal Variation of Subway Ridership before and during the COVID-19 Period in Beijing

Abstract

The outbreak of COVID-19 in 2019 caused a huge impact on people’s lives. Uncovering the variation of public traffic daily patterns during the pre-pandemic and pandemic periods would help interpret the impact of the pandemic on people’s routine activity and promote the sustainable development of public transport systems. By collecting subway traffic data during the pre-pandemic and pandemic periods in Beijing, China, this paper analyzes the spatial and temporal variation of subway ridership and seeks to find out what sort of environment variables related to the variation of subway ridership during the two periods. The results show that the ridership of Beijing subway during the pandemic period decreased by 91.69% compared with the pre-pandemic period. On working days and non-working days during the pandemic period, the subway stations experiencing huge ridership reductions were mainly distributed within the core urban areas, while in the morning peak hours, the stations experiencing huge ridership reduction were located within suburban areas. The origin-destination stations with a large decrease in ridership were mainly distributed along the central to northern directions of Beijing but, on non-working days, they were mainly distributed along the central to northwestern directions of Beijing. The results of the regression analysis indicated that, during the pandemic period, the industrial parks were significantly positively correlated with subway ridership, while the pedestrian road network density was significantly negatively correlated with subway ridership.