Abstract
Due to the time-sensitive nature of heat-related illnesses, disparities in access to heat-related emergency medical services (EMS) services may contribute to urban health disparities. This paper is an empirical study utilizing Austin-Travis County EMS data to estimate the delays in response time due to traffic congestion through spatiotemporal analysis and to conduct the Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) models to examine the underlying factors affecting delays in peak traffic rush hours. Our results reveal that heat-related EMS is most delayed in the morning and the evening; there are higher clustering patterns of EMS travel time difference in Austin's metropolitan outskirts, notably in the east and west Austin. OLS and GWR analyses suggest that larger EMS counts, longer distances from an EMS station to the scene and from the scene to a hospital, and neighborhoods with a greater black and Hispanic population exacerbate heat-related EMS delays. Road density, average speed limit, and open space growth rate are statistically significant in the OLS model, although GWR findings suggest coefficient signs vary locally, requiring more investigation. Our findings provided additional insights through the spatial patterns of EMS delays to practitioners for their reference to reduce local response times.
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