Understanding Transport Challenges to Help Advance Equitable Transportation for People with Disabilities and Low Income Households During Covid-19: A Survey-Based Approach in New York City

Abstract

COVID-19 and the ensuing restrictions in most cities around the world have resulted in unprecedented changes in the daily life of people. While everyone has been impacted by the COVID-19 pandemic in unique ways, the impact on certain disadvantaged groups is particularly severe. This paper aims to understand transport impacts and challenges for two disadvantaged groups: people with disabilities and low-income households. Through a survey targeted at respondents based in New York City, these impacts are quantified using questions about employment, travel mode, travel frequency, trip purpose, and so on. A descriptive analysis of the data shows that people with disabilities used fewer travel modes as compared to the overall population. Moreover, low-income households have less access to biking and bikeshare facilities than higher income households. A multivariate logit model containing demographic factors, mode preference, and mode choice was developed to analyze the interaction between various socio-demographic factors and understand the complex intersectionality between them. Combined with the descriptive analysis, the results reveal that transportation barriers were magnified for both people with disabilities and low-income households when options were already severely limited during a city shut down. This paper maps these results to actionable policy measures that can be undertaken by practitioners and public officials to devise an equitable roadmap that tackles the transportation challenges resulting from the COVID-19 pandemic. This will help in more efficient and inclusive planning practices in the future for the two underserved population groups studied in this paper.

Keywords: COVID-19, People with Disabilities, Low-income Households, Multinomial logit model, Topic modeling, Equitable Transportation