Tracking the Transit Divide: A Multilevel Modelling Approach of Urban Inequalities and Train Ridership Disparities in Chicago

Danial Owen (), Daniel Arribas-Bel and Francisco Rowe
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Danial Owen: Geographic Data Science Lab, Department of Geography and Planning, Roxby Building, University of Liverpool, Liverpool L69 7ZT, UK
Daniel Arribas-Bel: Geographic Data Science Lab, Department of Geography and Planning, Roxby Building, University of Liverpool, Liverpool L69 7ZT, UK
Francisco Rowe: Geographic Data Science Lab, Department of Geography and Planning, Roxby Building, University of Liverpool, Liverpool L69 7ZT, UK

Sustainability, 2023, vol. 15, issue 11, 1-18

Abstract: Using a multilevel modelling approach, this study investigates the impact of urban inequalities on changes to rail ridership across Chicago’s “L” stations during the pandemic, the mass vaccination rollout, and the full reopening of the city. Initially believed to have an equal impact, COVID-19 disproportionally impacted the ability of lower socioeconomic status (SES) neighbourhoods’ to adhere to non-pharmaceutical interventions: working-from-home and social distancing. We find that “L” stations in predominately Black or African American and Hispanic or Latino neighbourhoods with high industrial land-use recorded the smallest behavioural change. The maintenance of higher public transport use at these stations is likely to have exacerbated existing health inequalities, worsening disparities in users’ risk of exposure, infection rates, and mortality rates. This study also finds that the vaccination rollout and city reopening did not significantly increase the number of users at stations in higher vaccinated, higher private vehicle ownership neighbourhoods, even after a year into the pandemic. A better understanding of the spatial and socioeconomic determinants of changes in ridership behaviour is crucial for policymakers in adjusting service routes and frequencies that will sustain reliant neighbourhoods’ access to essential services, and to encourage trips at stations which are the most impacted to revert the trend of declining public transport use.

Keywords: urban inequalities; multilevel modelling; spatial patterns; COVID-19; mobility; health inequalities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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