Spatio-Temporal Patterns of Heat Index and Heat-Related Emergency Medical Services (Ems)

Abstract

Despite growing concerns about heat waves due to climate change and their health impacts, there has been limited research on patterns of extreme heat during summertime and their association with heat-related Emergency Medical Services (EMS) incidents. This study examines spatiotemporal patterns of the heat index (HI) and its relationship to heat-related EMS incidents in Austin-Travis County, Texas, focusing on the summers of 2020 and 2021. Collecting 47,838 heat-related EMS incidence cases and aggregating them at the tract level (N = 290), the research employs spatiotemporal analysis, spatial autocorrelation, K-means clustering, and geographically weighted Poisson regression to identify disparities in heat-related health outcomes. Key findings indicate a significant correlation between high HI frequency and intensity and increased EMS incidents, particularly in East Austin, underscoring the area's heightened vulnerability to heat. the study also reveals that heat vulnerability and urban growth patterns are closely linked to the incidence of heat-related illnesses, and its impact varies by region. These results emphasize the critical need for targeted heat resilience strategies in urban planning and emergency response. This research merges socio-economic and environmental data to offer insights into heat-related health risks, informing targeted public health policies and urban planning for more equitable and effective interventions.

Department(s)

Biological Sciences

Comments

University of Texas at Austin, Grant 2133302

Keywords and Phrases

Climate resilience; Emergency Medical Services (EMS); Extreme heat; Geographically weighted poisson regression; Heat index; k-Mean clustering

International Standard Serial Number (ISSN)

2210-6707

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Elsevier, All rights reserved.

Publication Date

15 Sep 2024

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