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Tracking the Transit Divide: A Multilevel Modelling Approach of Urban Inequalities and Train Ridership Disparities in Chicago
Sustainability ; 15(11):8821, 2023.
Article Dans Anglais | ProQuest Central | ID: covidwho-20240899
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.
Mots clés

Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: ProQuest Central Type d'étude: Étude pronostique Les sujets: Vaccins langue: Anglais Revue: Sustainability Année: 2023 Type de document: Article

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Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: ProQuest Central Type d'étude: Étude pronostique Les sujets: Vaccins langue: Anglais Revue: Sustainability Année: 2023 Type de document: Article