Understanding Social Impacts of Major Disruptions from the Perspective of Destination Access

Document Type

Article

Publication Date

8-1-2025

Abstract

Major disruptions significantly impact human mobility and travel patterns. This study investigates social impacts of major disruptions on human mobility from the perspective of accessing destinations within the impacted regions. This study used a large-scale data set from SafeGraph and focused on analyzing the impacts of COVID-19 and Hurricane Ida on destination access in Louisiana, U.S. The temporal plots show that the impact magnitude of Hurricane Ida was much smaller than that of the COVID-19 pandemic but still resulted in hardship on destination access. Two modeling approaches were used (i.e., linear regression and random forest) subsequently to explore both linear and non-linear associations between community characteristics and mobility variations at the census tract level. A spatial random forest model was also estimated to address spatial autocorrelation issues. The modeling results show that there are common variables that are significantly associated with mobility variations in the two disruptions. However, mobility variations in COVID-19 are more likely to be linearly/non-linearly associated with built environment and socio-demographic factors that are related to transportation infrastructure. In contrast, mobility variations during Hurricane Ida are more likely to be non-linearly associated with socio-demographic factors featuring community vulnerabilities. Overall, this study quantified the different impact magnitude of two disruptions on human mobility (in terms of destination access) and statistically identified communities that are more likely to be influenced. Communities with the above-mentioned characteristics should be targeted, respectively, for destination access improvement during future disruptions.

Publication Source (Journal or Book title)

Data Science for Transportation

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