A Computational Methodology for Addressing Differentiated Access of Vulnerable Populations During Biological Emergencies

TitleA Computational Methodology for Addressing Differentiated Access of Vulnerable Populations During Biological Emergencies
Publication TypeThesis
Year of Publication2014
AuthorsO'Neill II M
AdvisorMikler AR
Academic DepartmentComputer Science and Engineering
DegreeDoctor of Philosophy
Number of Pages115
Date Published08/2014
UniversityUniversity of North Texas
CityDenton
Thesis TypeDoctoral Dissertation
Abstract

Mitigation response plans must be created to protect affected populations during biological emergencies resulting from the release of harmful biochemical substances. Medical countermeasures have been stockpiled by the federal government for such emergencies. However, it is the responsibility of local governments to maintain solid, functional plans to apply these countermeasures to the entire target population within short, mandated time frames. Further, vulnerabilities in the population may serve as barriers preventing certain individuals from participating in mitigation activities. Therefore, functional response plans must be capable of reaching vulnerable populations.Transportation vulnerability results from lack of access to transportation. Transportation vulnerable populations located too far from mitigation resources are at-risk of not being able to participate in mitigation activities. Quantification of these populations requires the development of computational methods to integrate spatial demographic data and transportation resource data from disparate sources into the context of planned mitigation efforts. Research described in this dissertation focuses on quantifying transportation vulnerable populations and maximizing participation in response efforts. Algorithms developed as part of this research are integrated into a computational framework to promote a transition from research and development to deployment and use by biological emergency planners.

URLhttps://digital.library.unt.edu/ark:/67531/metadc699851/