Extreme Event Recovery: Optimizing Mental Health Resource Allocation

Abstract:

Extreme Events such as natural or human-caused disasters produce stress-induced outcomes. The severity of these outcomes varies based on socioeconomic standing, age group, and degree of exposure. Planners can mitigate potential stress-induced outcomes by assessing the capacity and scalability of their early, intermediate, and long-term interventions. However, local and state authorities are typically underfunded, understaffed, and have ongoing health and social service obligations, which constrain mitigation and response activities. In this research, we develop The Extreme Event Psychological Stress Recovery Framework (EEPSRF) to assist planners by producing a decision aid that optimally allocates constrained resources and satisfies mental health recovery priorities post-extreme event. The EEPSRF integrates a simulated impact of an extreme event on mental health, mental health provider capacities, and the Center for Disease Control and Prevention’s (CDC) Social Vulnerability Index (SVI) to identify vulnerable populations needing additional assistance post-disaster. Mental health providers are optimally distributed to treat the affected population based upon rulesets that simulate decision-maker priorities in extreme event response. These priorities include allocating resources to socially vulnerable populations defined by the SVI, identifying the greatest affected population using census tracts, and maximizing wage restoration for time spent away from work due to poor mental health days. Finally, EEPSRF maps the mental health recovery of the extreme event-affected populations over time, providing agencies a means to prepare for and respond to future extreme events given existing resource constraints. These capabilities will support decision makers in their ability to minimize long-term mental health impacts of extreme events on their communities through improved preparation and response activities.