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The COVID-19 pandemic has profoundly reshaped urban mobility. During the lockdown, workers teleworked if possible and left home only for essential activities. Our study investigates the spatial patterns of essential travel and their socioeconomic differences during the COVID-19 lockdown phase in comparison with the same period in 2019. Using data from Columbus, Ohio, we categorized travelers into high, moderate, and low socioeconomic status (SES) clusters and modeled travel demand of SES clusters for both phases using spatially weighted interaction models. Then, we characterized the SES variability in essential travel based on frequently visited business activities from each cluster. Results suggest that disparities in travel across SES clusters that existed prior to COVID-19 were exacerbated during the pandemic lockdown. The diffused travel pattern of high and moderate SES clusters became localized and the preexisting localized travel pattern of low SES clusters became diffused. During the lockdown, the low and moderate SES clusters traveled mostly for work with long-and medium-distance trips, respectively, whereas the high SES cluster traveled mostly for recreational and other nonwork purposes with short-distance trips. This study draws some conclusions and implications to help researchers and practitioners plan for resilient and economically vibrant transportation systems in response to future shocks.

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Stay-at-home policies in response to COVID-19 transformed high-volume arterials and highways into lower-volume roads, and reduced congestion during peak travel times. To learn from the effects of this transformation on traffic safety, an analysis of crash data in Ohio’s Franklin County, U.S., from February to May 2020 is presented, augmented by speed and network data. Crash characteristics such as type and time of day are analyzed during a period of stay-at-home guidelines, and two models are estimated: (i) a multinomial logistic regression that relates daily volume to crash severity; and (ii) a Bayesian hierarchical logistic regression model that relates increases in average road speeds to increased severity and the likelihood of a crash being fatal. The findings confirm that lower volumes are associated with higher severity. The opportunity of the pandemic response is taken to explore the mechanisms of this effect. It is shown that higher speeds were associated with more severe crashes, a lower proportion of crashes were observed during morning peaks, and there was a reduction in types of crashes that occur in congestion. It is also noted that there was an increase in the proportion of crashes related to intoxication and speeding. The importance of the findings lay in the risk to essential workers who were required to use the road system while others could telework from home. Possibilities of similar shocks to travel demand in the future, and that traffic volumes may not recover to previous levels, are discussed, and policies are recommended that could reduce the risk of incapacitating and fatal crashes for continuing road users.

Hurricanes can have a significant impact on the functioning and capacity of healthcare systems. However, little work has been done to understand the extent to which hurricanes influence local residents' spatial access to healthcare. Our study evaluates the change in spatial access to primary care physicians (PCPs) between 2016 and 2018 (i.e., before and after Hurricane Harvey) in Harris County, Texas. We used an enhanced 2-step floating catchment area (E2SFCA) method to measure spatial access to PCPs at the census tract level. The results show that, despite an increased supply of PCPs across the county, most census tracts, especially those in the northern and eastern fringe areas, experienced decreased access during this period as measured by the spatial access ratio (SPAR). We explain this decline in SPAR by the shift in the spatial distribution of PCPs to the central areas of Harris County from the fringe areas after Harvey. We also examined the socio-demographic impact in the SPAR change and found little variation in change among different socio-demographic groups. Therefore, public health professionals and disaster managers may use our spatial access measure to highlight the geographic disparities in healthcare systems. In addition, we recommend considering other social and institutional dimensions of access, such as users' needs, preferences, resource capacity, mobility options, and quality of healthcare services, in building a resilient and inclusive post-hurricane healthcare system.