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

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: Coronavirus disease-19; Elderly; Gibbs sampling Dirichlet multinomial mixture; Mobility Survey; Topic modeling.

Fig. 1

Geographic distribution of respondents.

Fig. 2

Work remotely/in-person, Period 1 (Before the pandemic) versus Period 3 (After reopening), Older Adults (only responses from older adults who worked before pandemic are included, n = 110).

Fig. 3

Work remotely/in-person, Period 1 (Before the pandemic) versus Period 3 (After reopening), Younger Adults (only responses from younger adults who work/attend class before the pandemic are included, n = 265).

Fig. 4

How often older adults use selected travel modes for commute trips, Period 1 (Before the pandemic) versus Period 3 (After reopening).

Fig. 5

How often older adults use selected travel modes for non-commute trips, Period 1 (Before the pandemic) versus Period 3 (After reopening).

Fig. 6

How often younger adults use selected travel modes for commute trips, Period 1 (Before the pandemic) versus Period 3 (After reopening).

Fig. 7

How often younger adults use selected travel modes for non-commute trips, Period 1 (Before the pandemic) versus Period 3 (After reopening).

Fig. 8

Attitude factors affecting the choice of travel mode, Period 1 (Before the pandemic) versus Period 3 (After reopening).

Fig. 9

Reasons for travel, Period 2 (During NY PAUSE).

Fig. 10

Topic and word distributions in each topic for open-ended question - biggest concerns about traveling during COVID-19, Period 2 (During NY PAUSE).

Fig. 11

Topic and word distributions in each topic for open-ended question – biggest inconvenience you faced while going for essential trips, Period 2 (During NY PAUSE).