In brief

A 150 percent increase in bike-share ridership during the pandemic lockdowns points to bike-sharing as a potentially safe and reliable mode of transport during infectious disease outbreaks.

© A*STAR Research

The rise of pandemic pedal-pushers

5 Oct 2023

A surge in Singapore's bike-sharing usage during the COVID-19 pandemic highlights the importance of shared mobility modes during periods of restricted public transit.

With the worst of the pandemic behind us, a bustling public transport system is a reassuring symbol of increased mobility and return to normalcy. The close proximity of transit passengers in the enclosed spaces of buses and trains made maintaining a safe physical distance during COVID-19 lockdowns particularly challenging, spurring public health policies that restricted the use of public transportation.

These measures forced people to seek alternative modes of transport to get around, with many turning to bike-sharing networks as an easy and low-cost solution. Jie Song, a Senior Research Scientist at A*STAR’s Institute of High Performance Computing (IHPC), and corresponding author Liye Zhang from the Shandong University of Science and Technology, China, led a three-year project in collaboration with the Land Transport Authority (LTA), to study how the pandemic influenced bike-share ridership in Singapore.

Bike-sharing systems consist of strategically placed docking stations in urban areas, where individuals can rent bicycles for short periods. As a part of their investigation, the researchers studied bike-share usage in commercial and residential areas during different stages of lockdown measures in Singapore.

Song and team saw a 150 percent uptick in ridership during Singapore’s ‘circuit breaker’ phase compared to pre-pandemic levels. During this period of heightened restrictions, bike-sharing activities in the downtown and waterfront areas rose dramatically; the concentration of riders occupying bike paths around residential and mixed-use urban areas also increased. From these findings, the researchers suggest that bike-sharing could be an important mode of transportation when public transit services are limited.

Bike usage on weekdays before, during and after the COVID-19 circuit breaker in Singapore.

©️ A*STAR Research

“Bike-sharing networks may be able to absorb additional travel demands due to the reduced capacities of public transit services while complying with social distancing requirements,” commented Song. Bike-sharing services are reliable and accessible first- and last-mile options which help support a resilient urban transportation system even during difficult times, Song elaborated.

While envisioning a future where Singapore’s bike-sharing systems can be easily adapted to cope with increased usage during infectious disease outbreaks, Song recommended that additional bikes can be deployed with stricter hygiene protocols during periods of higher frequency bike use.

Moreover, policymakers can use the lessons learned during the pandemic as an opportunity to promote a stronger year-round cycling culture. “Building a bike-share-friendly environment is key to sustaining the casual cyclists’ dependence upon this micro-mobility mode,” emphasised Song.

Moving forward, Song and colleagues plan to validate their findings using additional methods and bigger datasets. Gathering more data on mass transit usage during the pandemic will enable them to confirm the study’s hypotheses on bike-sharing as a primary mode of public transport during the pandemic.

The A*STAR-affiliated researchers contributing to this research are from the Institute of High Performance Computing (IHPC).

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Song, J., Zhang, L., Qin, Z. and Ramli, M.A. Spatiotemporal evolving patterns of bike-share mobility networks and their associations with land-use conditions before and after the COVID-19 outbreak. Physica A: Statistical Mechanics and its Applications 592, 126819 (2022). | article

About the Researcher

Jie Song is a Senior Scientist at A*STAR’s Institute of High Performance Computing (IHPC) where he studies transportation demand modelling, active mobility, and complex urban systems dynamics. In response to the burgeoning data landscape driven by novel urban components like bike-sharing and autonomous vehicles, Song—as both a planning researcher and data scientist—addresses the gap between data-driven insights and urban planning. Through cutting-edge methodologies, he contributes to advancing urban social science and empirical urban planning practices.

This article was made for A*STAR Research by Wildtype Media Group