4.7 Article

Characterising public transport shifting to active and private modes in South American capitals during the COVID-19 pandemic

期刊

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tra.2022.08.010

关键词

Coronavirus; COVID-19; Public transport; Modal shift; Perception; Active modes

资金

  1. BRT +Centre of Excellence - VREF
  2. Fondecyt [117104]

向作者/读者索取更多资源

This paper examines the impact of the COVID-19 pandemic on public transportation in five South American capitals. It finds that the decline in public transport usage may have negative long-term consequences for these cities unless users switch to more sustainable modes. Surveys and a SEM-MIMIC model were used to identify factors influencing the shift from public transport to other modes, with COVID-19 cases and deaths increasing the probability of moving to alternative modes.
During the year 2020, the COVID-19 pandemic affected mobility around the world, significantly reducing the number of trips by public transport. In this paper, we study its impact in five South American capitals (i.e., Bogota, Buenos Aires, Lima, Quito and Santiago). A decline in public transport patronage could be very bad news for these cities in the long term, particularly if users change to less sustainable modes, such as cars or motorbikes. Notwithstanding, it could be even beneficial if users selected more sustainable modes, such as active transport (e.g., bicycles and walking). To better understand this phenomenon in the short term, we conducted surveys in these five cities looking for the main explanation for changes from public transport to active and private modes in terms of user perceptions, activity patterns and sociodemographic information. To forecast people's mode shifts in each city, we integrated both objective and subjective information collected in this study using a SEM-MIMIC model. We found five latent variables (i.e., COVID-19 impact, Entities response, Health risk, Life related activities comfort and Subjective well-being), two COVID-19 related attributes (i.e., new cases and deaths), two trip attributes (i.e., cost savings and time), and six socio-demographic attributes (i.e., age, civil status, household characteristics, income level, occupation and gender) influencing the shift from public transport to other modes. Furthermore, both the number of cases and the number of deaths caused by COVID-19 increased the probability of moving from public transport to other modes but, in general, we found a smaller probability of moving to active modes than to private modes. The paper proposes a novel way for understanding geographical and contextual similarities in the pandemic scenario for these metropolises from a transportation perspective.

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