This paper aims to investigate the following research questions: (1) what are the hourly patterns of heat index and heat-related emergency medical service (EMS) incidents during summertime?; and (2) how do the lagged effects of heat intensity and hourly excess heat (HEH) vary by heat-related symptoms? Using the hourly weather and heat-related EMS call data in Austin-Travis County, Texas, this paper reveals the relationship between heat index patterns on an hourly basis and heat-related health issues and evaluates the immediate health effects of extreme heat events by utilizing a distributed lag non-linear model (DLNM). Delving into the heat index intensity and HEH, our findings suggest that higher heat intensity has immediate, short-term lagged effects on all causes of heat-related EMS incidents, including in cardiovascular, respiratory, neurological, and non-severe cases, while its relative risk (RR) varies by time. HEH also shows a short-term cumulative lagged effect within 5 h in all-cause, cardiovascular, and non-severe symptoms, while there are no statistically significant RRs found for respiratory and neurological cases in the short term. Our findings could be a reference for policymakers when devoting resources, developing extreme heat warning standards, and optimizing local EMS services, providing data-driven evidence for the effective deployment of ambulances.
Keywords: distributed lag non-linear model; emergency medical service (EMS) incident; extreme heat; heat index; hourly excess heat; intensity.