ArticleTransportation research interdisciplinary perspectives2022
Integrating COVID-19 health risks into crowding costs for transit schedule planning.
Article in Transportation research interdisciplinary perspectives, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- The effect of quarantine policy on pollution emission and the usage of private transportation in urban areas.Scientific reports · 2024Article
- Skip-Stop Strategy Patterns optimization to enhance mass transit operation under physical distancing policy due to COVID-19 pandemic outbreak.Transport policy · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The public transport sector worldwide experienced the worst impact in recent history, in terms of ridership loss, due to the COVID-19 pandemic. The pandemic negatively affected passengers' perceptions of public transport and is likely to make a lasting impact on ridership, trip patterns, and modal share. Without any supportive changes to transit operations, ridership is likely to decline. This study explores the setting of frequencies in transit lines and proposes a two-part methodology that addresses the changing perceptions of users, especially in a health-related context. The first part develops a mathematical model that expresses the pre-COVID-19 cost of passenger crowding as an integral part of user costs to determine the optimal headway that considers the trade-offs between user and operator costs. A continuum approximation for the demand of the bus line has been used in the derivation. The second part extends the developed model to include both the costs of the health risks associated with the COVID-19 pandemic and crowding. The developed models will help transit planners and operators to plan and adapt operations to changing health risks during the pandemic and post-pandemic. Several numerical examples are provided to describe the uses and applications of the analytical models using information obtained from the literature.
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Registered trials
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