Impact of COVID-19 on Public Transit Accessibility and Ridership

Abstract

COVID-19 has radically transformed urban travel behavior throughout the world. Agencies have had to provide adequate service while navigating a rapidly changing environment with reduced revenue. As COVID-19-related restrictions are lifted, transit agencies are concerned about their ability to adapt to changes in ridership behavior and public transit usage. To aid their becoming more adaptive to sudden or persistent shifts in ridership, we addressed three questions: To what degree has COVID-19 affected fixed-line public transit ridership and what is the relationship between reduced demand and -vehicle trips? How has COVID-19 changed ridership patterns and are they expected to persist after restrictions are lifted? Are there disparities in ridership changes across socioeconomic groups and mobility-impaired riders? Focusing on Nashville and Chattanooga, TN, ridership demand and vehicle trips were compared with anonymized mobile location data to study the relationship between mobility patterns and transit usage. Correlation analysis and multiple linear regression were used to investigate the relationship between socioeconomic indicators and changes in transit ridership, and an analysis of changes in paratransit demand before and during COVID-19. Ridership initially dropped by 66% and 65% over the first month of the pandemic for Nashville and Chattanooga, respectively. Cellular mobility patterns in Chattanooga indicated that foot traffic recovered to a greater degree than transit ridership between mid-April and the last week in June, 2020. Education-level had a statistically significant impact on changes in fixed-line bus transit, and the distribution of changes in demand for paratransit services were similar to those of fixed-line bus transit.

Estimation of trip purposes in public transport during the COVID-19 pandemic: The case of Santiago, Chile

“…In particular, the communes of the western sector had to continue making work trips, while the communes of the eastern sector decreased their participation, which is explained mainly by teleworking. This fact is related to income, which is in line with what other authors have mentioned ( Wilbur et al, 2020 ; Astroza et al, 2020 ). Then, when analyzing the period of relaxed restriction measures, our results show that the number of trips for all purposes increased strongly with respect to the period of confinement.…”

“…On the other hand, in North America, Wilbur et al (2020) analyze the impact of COVID-19 on transportation accessibility and its demand, differentiating by socioeconomic groups in the cities of Nashville and Chattanooga, USA. For the above, the authors use data from the boarding of passengers and socioeconomic information, which is obtained through surveys.…”

Durations of Dockless E-Scooter Trips Before and During the COVID-19 Pandemic in Austin, TX: An Analysis Using Hazard-Based Duration Models

“…Over the last year, many studies have explored the impact of COVID-19 on transportation on the basis of different changes, such as those occurring for modal shares ( 13 – 19 ), transit ridership ( 14 , 20 , 21 ), airline operation ( 22 , 23 ), railway systems operation ( 24 ), daily outdoor activities ( 14 , 19 , 22 , 25–30 ), telework status ( 22 , 31 ), travel distances ( 18 , 32 ), homestay dwell time, and attitudes and risk perceptions ( 33 ). These explorations highlighted a large decline in mobility as a result of state-level lockdowns and the fear of COVID-19 infection.…”

Effects of Individual and Built Environmental Features on Commuting Mode Shifts before and after the COVID-19 Outbreak in Guangzhou, China

“…Compared with people without cars, car (car or motorcycle) owners were less likely to use public transport. Research conducted in the United States using the data of transportation agencies found that in Nashville, TN, the trafc passenger fow in higher-income census tracts decreased by 77%, while that in low-income census tracts decreased by 58% [50]. A study from the Philippines showed that for economic reasons, a large proportion of low-income or blue-collar workers had a high demand for travel [51].…”