Evaluating Descriptive and Predictive Spatial Models of Emergency Medical Services Demand During Extreme Heat Events in Austin, TX

dc.contributor.advisorJiao, Junfeng
dc.creatorMandalapu, Akhil
dc.date.accessioned2023-04-24T14:08:15Z
dc.date.available2023-04-24T14:08:15Z
dc.date.issued2023
dc.description.abstractExtreme heat events are becoming increasingly common. With extreme heat exposure often necessitating prompt emergency medical service (EMS) response, the situation is critical as a rapid response is necessary to prevent severe disability or death. However, limited EMS capacity requires reallocation of resources to meet the increased demand for EMS. Although prior literature suggests a slight positive association between heat and EMS demand, studies have not investigated the spatial patterns of EMS demand during extreme heat. This study compares predictive models of EMS demand during extreme heat events across space. First, an unsupervised clustering approach was utilized to characterize EMS demand spatially to identify clusters with similar EMS demand and heat vulnerability characteristics. Finally, linear regression and geographically weighted regression (GWR) models were evaluated in predicting the spatial demand of EMS.en_US
dc.description.departmentPublic Healthen_US
dc.identifier.urihttps://hdl.handle.net/2152/118386
dc.identifier.urihttp://dx.doi.org/10.26153/tsw/45265
dc.language.isoengen_US
dc.relation.ispartofHonors Thesesen_US
dc.rights.restrictionOpenen_US
dc.subjectExtreme heaten_US
dc.subjectemergency medical servicesen_US
dc.subjectepidemiologyen_US
dc.subjectclimate changeen_US
dc.subjecturban informaticsen_US
dc.subjecturban planningen_US
dc.subjectenvironmental justiceen_US
dc.titleEvaluating Descriptive and Predictive Spatial Models of Emergency Medical Services Demand During Extreme Heat Events in Austin, TXen_US
dc.typeThesisen_US

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