Understanding the travel challenges and gaps for older adults during the COVID-19 outbreak: Insights from the New York City area.

Jingqin Gao, Change Dae Lee, Kaan Ozbay, Fan Zuo, Tracy L Chippendale
Author Information
  1. Jingqin Gao: C2SMART Center, Department of Civil and Urban Engineering, Tandon School of Engineering, New York University, 6 MetroTech Center, 4th Floor, RM456, Brooklyn, NY 11201, USA.
  2. Change Dae Lee: Department of Rehabilitation Science and Technology, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6425 Penn Avenue, Suite 400, Pittsburgh, PA 15206, USA.
  3. Kaan Ozbay: C2SMART Center, Department of Civil and Urban Engineering, Tandon School of Engineering, New York University, 6 MetroTech Center, 4th Floor, RM456, Brooklyn, NY 11201, USA.
  4. Fan Zuo: C2SMART Center, Department of Civil and Urban Engineering, Tandon School of Engineering, New York University, 6 MetroTech Center, 4th Floor, RM456, Brooklyn, NY 11201, USA.
  5. Tracy L Chippendale: Department of Occupational Therapy, Steinhardt School of Culture, Education, and Human Development, 82 Washington Square E, 6th Floor, New York, NY 10003, USA.

Abstract

The COVID-19 pandemic has greatly impacted lifestyles and travel patterns, revealing existing societal and transportation gaps and introducing new challenges. In the context of an aging population, this study investigated how the travel behaviors of older adults (aged 60+) in New York City were affected by COVID-19, using an online survey and analyzing younger adult (aged 18-59) data for comparative analysis. The purpose of the study is to understand the pandemic's effects on older adults' travel purpose and frequency, challenges faced during essential trips, and to identify potential policies to enhance their mobility during future crises. Descriptive analysis and Wilcoxon signed-rank tests were used to summarize the changes in employment status, trip purposes, transportation mode usage, and attitude regarding transportation systems before and during the outbreak and after the travel restrictions were lifted. A Natural Language Processing model, Gibbs Sampling Dirichlet Multinomial Mixture, was adopted to open-ended questions due to its advantage in extracting information from short text. The findings show differences between older and younger adults in telework and increased essential-purpose trips (e.g., medical visits) for older adults. The pandemic increased older adults' concern about health, safety, comfort, prices when choosing travel mode, leading to reduced transit use and walking, increased driving, and limited bike use. To reduce travel burdens and maintain older adults' employment, targeted programs improving digital skills (telework, telehealth, telemedicine) are recommended. Additionally, safe, affordable, and accessible transportation alternatives are necessary to ensure mobility and essential trips for older adults, along with facilitation of walkable communities.

Keywords

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