Your browser doesn't support javascript.
Who is returning to public transport for non-work trips after COVID-19? Evidence from older citizens' smart cards in the UK's second largest city region.
Long, Alfie; Carney, Ffion; Kandt, Jens.
  • Long A; The Bartlett Centre for Advanced Spatial Analysis, University College London, UK.
  • Carney F; The Bartlett Centre for Advanced Spatial Analysis, University College London, UK.
  • Kandt J; The Bartlett Centre for Advanced Spatial Analysis, University College London, UK.
J Transp Geogr ; 107: 103529, 2023 Feb.
Article in English | MEDLINE | ID: covidwho-2181082
ABSTRACT
Harnessing a unique data source - longitudinal travel smartcard data linked to passenger demographics from 2019 to 2022 - we use methods of survival analysis to model the recovery of public transport patronage among 183,891 senior citizens resident in the West Midlands metropolitan region in the United Kingdom. Comparing pre and peri-pandemic patronage, we identify pronounced social and spatial inequalities in the speed of return to public transport. We find that male, younger and non-White passengers are more likely to return to public transport as soon as movement restrictions were lifted, whereas passengers from White ethnic background and affluent areas do not return to public transport within the first year after the outbreak. Pronounced social inequalities persist into the middle of 2021, and only thence they began to attenuate as part of a wider return to public transport among passengers post retirement age. In 2022, 80% of these passengers have returned to public transport but the frequency of use has remained lower than prior to the pandemic. We discuss implications for transport policy and planning.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: J Transp Geogr Year: 2023 Document Type: Article Affiliation country: J.jtrangeo.2023.103529

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: J Transp Geogr Year: 2023 Document Type: Article Affiliation country: J.jtrangeo.2023.103529