Citation

Abdullah M, Ali N, Javid MA, Dias C, Campisi T. Transp. Eng. (Amsterdam) 2021; 5: 100078.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.treng.2021.100078

PMID

unavailable

Abstract

A sharp decline in public transport use has been reported worldwide since the outbreak of the COVID-19 pandemic. As the virus spreads through close contacts, particularly in closed environments, public transport vehicles could be considered as hotspots for its transmission. However, public transport operations cannot be entirely stopped as many people in developing countries rely on them for their travel needs. This study aims to provide insights into people's travel mode choices during the COVID-19 pandemic. Data, i.e., 1,516 complete survey responses, were obtained through a questionnaire that was conducted in Lahore, Pakistan. A binary logistic model was developed using the collected data to model the likelihood of choosing solo or public transport modes during COVID-19. The results explained that the respondents preferred solo modes more than the public transport modes during the pandemic. Gender, income, education, profession, trip frequency, car ownership, motorbike ownership, and an underlying factor that was defined as "safety precautions" were found to be significant predictors of the public transport choice relative to solo modes. Females tend to choose public transport modes relative to solo modes as compared to males. Private vehicle (car or motorbike) owners were less likely to use public modes relative to solo modes when compared to those who do not own private vehicles. The outcomes of this study could be important for the government authorities, policymakers, and transport operators to understand the public transport use in developing countries during pandemics. Such information will be useful to devise regulations and preventive measures to control infectious diseases associated with public transport use, particularly in developing countries, where private transport options are limited.

Language: en

Keywords

Binary logistic regression; COVID-19; Mode choice; Pandemic; Public transport