Date of Award

3-2021

Document Type

Thesis

Degree Name

Master of Science in Engineering Management

Department

Department of Systems Engineering and Management

First Advisor

Justin D. Delorit, PhD

Abstract

Extreme events, such as natural or human-caused disasters, cause mental health stress in affected communities. While the severity of these outcomes varies based on socioeconomic standing, age group, and degree of exposure, disaster planners can mitigate potential stress-induced mental health outcomes by assessing early, intermediate, and long-term treatment interventions by social workers and psychologists. However, local and state authorities are typically underfunded, understaffed, and have ongoing health and social service obligations that constrain mitigation and response activities. A resource assignment framework is developed as a coupled-state transition and linear optimization model that assists planners in optimally allocating constrained resources and satisfying mental health recovery priorities post-disaster. The resource assignment framework integrates the impact of a simulated disaster on mental health, mental health provider capacities, and the Center for Disease Control and Preventions (CDC) Social Vulnerability Index (SVI) to identify vulnerable populations needing additional assistance post-disaster. Mental health clinicians are optimally distributed to treat the affected population based upon rulesets simulating decision-maker priorities, such as economic and social vulnerability criteria. Finally, the resource assignment framework maps the mental health recovery of disaster-affected populations over time, providing agencies a means to prepare for and respond to future disasters given existing resource constraints.

AFIT Designator

AFIT-ENV-MS-21-M-214

DTIC Accession Number

AD1134090

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