Ozbilen Basar, Slagle Kristina M, Akar Gulsah
City and Regional Planning, Knowlton School, The Ohio State University, United States.
School of Environment and Natural Resources, The Ohio State University, United States.
Transp Res Interdiscip Perspect. 2021 Jun;10:100326. doi: 10.1016/j.trip.2021.100326. Epub 2021 Mar 10.
The COVID-19 outbreak caused major disruptions on individuals' out-of-home activities. Worldwide mandates to slow down the spread of the disease resulted in significant reductions in travel. This study analyzes the changes in individuals' travel outcomes and their risk perceptions related to exposure and specific travel modes during the COVID-19 pandemic. We use data collected through an online survey with residents of Columbus, OH from April 30 to May 7, 2020. Employing multiple generalized estimating equations (GEEs) with a logit link function, we analyze the perceived risk of infection while traveling with different modes controlling for socio-demographics. The findings show that on average individuals are more likely to find shared modes (i.e., transit, ride-hailing, carsharing) riskier as compared to individual ones (i.e., walking, autos) when it comes to COVID-19 exposure. This study also suggests that the associations between perceptions related to exposure and various travel modes vary across groups with (1) different primary mode preferences (auto users vs non-auto users (e.g., transit users, bicyclists, etc.)), and (2) different socio-demographics. For example, auto users are more likely to find shared modes such as ride-hailing or transit riskier as compared to personal car. The conclusions present recommendations for future transportation policies in the post-COVID era. These include building upon the emerging positive perceptions towards non-motorized modes as an opportunity to promote sustainable transportation as well as formulating viable solutions to address the high-risk perceptions associated with transit.
新冠疫情的爆发对个人的户外出行活动造成了重大干扰。全球范围内为减缓疾病传播而发布的强制令导致出行大幅减少。本研究分析了新冠疫情期间个人出行结果的变化以及他们对与接触和特定出行方式相关的风险认知。我们使用了2020年4月30日至5月7日通过对俄亥俄州哥伦布市居民进行在线调查收集的数据。采用具有logit链接函数的多个广义估计方程（GEEs），我们在控制社会人口统计学因素的情况下，分析了不同出行方式下的感染风险认知。研究结果表明，在新冠病毒暴露方面，与个人出行方式（如步行、自驾）相比，平均而言，个人更有可能认为共享出行方式（如公共交通、网约车、汽车共享）风险更高。本研究还表明，与暴露相关的认知和各种出行方式之间的关联在不同群体中存在差异，这些群体包括：（1）不同的主要出行方式偏好（自驾使用者与非自驾使用者（如公共交通使用者、骑自行车者等）），以及（2）不同的社会人口统计学特征。例如，与私家车相比，自驾使用者更有可能认为网约车或公共交通等共享出行方式风险更高。研究结论为新冠疫情后时代的未来交通政策提出了建议。这些建议包括利用对非机动出行方式新出现的积极认知，将其作为促进可持续交通的契机，以及制定可行的解决方案来应对与公共交通相关的高风险认知。
