Analysing the impacts of individual-level factors on public transport usage during the COVID-19 pandemic: a comprehensive literature review and meta-analysis
Analysing the impacts of individual-level factors on public transport usage during the COVID-19 pandemic: a comprehensive literature review and meta-analysis
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DOI：
10.1080/01441647.2023.2295967
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发表时间：
2023-12
影响因子：
9.8
通讯作者：
Maximiliano Lizana;C. Choudhury;David Watling
中科院分区：
文献类型：
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作者：
Maximiliano Lizana;C. Choudhury;David Watling
摘要2019冠状病毒病疫情期间，公共交通工具的使用受到严重影响，导致许多城市于2020年减少多达90%。从那时起，人们进行了大量的研究，以确定个人层面的因素（如性别、态度等）之间的关系。以及流感大流行期间PT使用的减少。尽管提供了证据，但调查结果分散，并且在几个因素上相互矛盾，因此难以得出任何普遍的结论。此外，在此期间影响PT使用的旅行者因素之间的效应量的全面比较尚未汇编。本文旨在通过系统地回顾现有证据并通过荟萃分析综合旅行者因素的影响大小来解决这些差距。我们首先确定了36项研究，这些研究对COVID-19大流行期间15个个人层面因素对PT使用的贡献进行了统计评估。通过合并这些研究的经验证据，分析了这些因素与PT使用之间关联的方向。然后，在选择可比研究后，对每个因素进行荟萃分析，以估计相应的合并效应量。荟萃分析确定，汽车可用性、远程工作机会和高教育水平是大流行期间减少PT使用的最大因素。与大流行前相比，这些因素使PT使用减少的可能性增加了约三倍。COVID-19风险认知、性别、高收入和健康状况等因素对停止使用PT的决定有中度影响。PT习惯、出行距离和实际可达性也影响了大流行期间PT的使用。地理位置和大流行时期解释了部分异质性。本研究提供的结果可以帮助政策制定者了解旅行者因素对未来大流行/流行期间减少PT使用决策的影响，并据此指导公共政策。
ABSTRACT Public transport (PT) usage was severely impacted during the COVID-19 pandemic, resulting in up to a 90% reduction in many cities in 2020. Numerous studies have been conducted since then to determine the relationship between individual-level factors (such as gender, attitudes, etc.) and the decrease in PT usage during the pandemic. Despite the evidence provided, findings are dispersed, and for several factors contradictory, making it challenging to reach any generalised conclusion. Furthermore, a comprehensive comparison of the effect sizes among travellers’ factors affecting PT use during this period is yet to be compiled. This paper aims to address these gaps by systematically reviewing the existing evidence and synthesising the effect sizes of travellers’ factors through a meta-analysis. We first identified 36 studies that statistically assessed the contribution of 15 individual-level factors on PT usage during the COVID-19 pandemic. By merging the empirical evidence of those studies, the direction of the association between those factors and PT usage was analysed. Then, after selecting comparable studies, meta-analyses were conducted for each factor to estimate the corresponding pooled effect sizes. The meta-analysis established that car availability, teleworking opportunities and high educational level contributed the most to reducing PT use during the pandemic. These factors increased the odds of reducing PT usage compared with the pre-pandemic by about three times. Factors such as COVID-19 risk perception, gender, high income and health had a moderate effect on the decision to stop using PT. PT habits, travel distance and physical accessibility also influenced PT use during the pandemic. Geographical location and the pandemic period explained part of the heterogeneity found. The findings provided in this study can help policy-makers understand the impacts of travellers’ factors on the decision to reduce PT usage during future pandemics/epidemics and guide public policies accordingly.