A Geographic Framework for the Optimal Placement of Interventions for Opioid Treatment Deployment in Underserved Areas (OPIOID-UA)

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The scale and cadence of crises affecting large populations is on the rise. These crises or gradual onset disasters can be considered shocks or disruptions to social systems. The impacts of many of these shocks do not affect populations equally, but differentially based on social class, race, ethnicity, demographic category, and geographic location. This research seeks to investigate the spatial components of a complex system in response to a gradual onset crisis in an effort to develop a framework of spatial response. The context of the research will be the spatial system in which the health care system delivers care,; the crisis is the opioid overdose epidemic. The opioid overdose crisis in the United States (US) is well documented as overdose mortality has continued to climb year after year, is a leading cause of accidental death, and has contributed to a reduced life expectancy. Medication for opioid use disorder (MOUD) is the evidence-based treatment for opioid use disorder, however, substantial disparities and deficits in geographic access to MOUD exist. In an effort to improve the provision and allocation of MOUD, this research addresses a series of research questions to advance understanding regarding the spatial accessibility to MOUD, the landscape of risk for opioid overdose, and treatment expansion efforts via spatial optimization modelling. The four studies presented within this dissertation offer a roadmap for implementing a suite of geographic methods to improve the provision of MOUD. Moreover, the synthesis of these chapters provides a research framework for using the geographic advantage to address a modern, complex spatial problems; acknowledging the need to assess a problem from multiple angles for improved understanding of the problem context in order to promote more equitable and effective resource allocation. Emphasis is placed on the need for investigating social-spatial relationships with regard to the problem space as well as the response. These social-spatial insights are vital in informing optimization approaches for resource provision to modern, complex problems.

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