Date of Award

January 2025

Document Type

Open Access Thesis

Degree Name

Master of Public Health (MPH)

Department

School of Public Health

First Advisor

Kai Chen

Abstract

Background: Extreme weather events pose risks to the power grid, threatening the wellbeing of individuals reliant on electricity to meet their health needs. The aim of this study is to identify geographical locations in the U.S. that have both high risk of power outage impact and high proportions of power-dependent durable medical equipment (DME) users.

Methods: To achieve this, I used the HHS emPOWER historical map dataset from years 2017 to 2022 and overlaid EAGLE-I data with county-level power outage data from the same study years. Using Local Moran’s I, I found spatially significant high-high clusters of each variable and then intersected cluster layers in ArcGIS Pro to find significant high-high clusters of both DME use and power outages.

Results: Through this analysis, I identified vulnerable areas for high levels of power outages and DME; the two risk factors co-occur to the greatest degree in northwest Texas, Appalachia, and Michigan. Significant differences in both DME use and power outage person-time were found across counties of low, medium, and high levels of social vulnerability, indicating disparities between social factors as measured by the Center for Disease Control and Prevention’s Social Vulnerability Index; socioeconomic status, race and ethnicity, language, and housing. Results can inform prioritization of public health interventions to safeguard the health of vulnerable populations during power outages.

Comments

This is an Open Access Thesis.

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