Excellence in Research: Bending the Curve for Vulnerable Populations: A Data-Analytical and Socio-Technical Decision-Making Framework forSheltering in Hurricane-Pandemics

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Co-occurrence of geophysical hazards with the COVID-19 pandemic has challenged the resilience of the most vulnerable populations in unique ways. In the midst of a pandemic, a natural disaster such as a hurricane puts additional strain on mass care resources in addition to the compounding effects of the two hazards on the mechanisms of physical and social vulnerability. As a result of social distancing requirements, the capacities of regular shelter spaces will be reduced drastically and alternate non-congregate shelters— such as hotel/motels or renovated facilities— may need to be considered. This Excellence in Research (EiR) project takes a community-engaged, multidisciplinary approach to address the pressing research problems for concurrently occurring hurricanes and pandemics, with a focus on the challenges facing vulnerable populations. The overall objective of the project is to formulate a new data-analytical framework that integrates epidemiological models with hurricane management approaches with a strong understanding of social vulnerabilities. This framework can help public health and emergency managers make sheltering and resource allocation decisions while simultaneously minimizing the disease spread. The research team brings together investigators from engineering and social science with expertise in statistical learning, infrastructure resilience, disaster risk analysis, and social vulnerability in order to systematically study the research problems. By improving the resilience of vulnerable communities in hurricane-pandemics, the project aims to address a critical national need in disaster preparedness as well as advance national health, prosperity, and welfare.The research activities will include investigation of statistical disease spread and outbreak detection methods, integration of epidemic models with hurricane evacuation scenario analyses to better predict disease spread and allocate resources in the aftermath of hurricane-pandemics, and engagement of emergency managers and social workers in vulnerability analysis through surveys and focus groups. Specifically, the project team will utilize the following methods: (1) risk-adjusted public health surveillance methods to devise targeted pandemic containment and sheltering plans of vulnerable populations, (2) network-based epidemic models to understand how mixing of populations during sheltering operations affect disease transmissions and to make forecasts of the size and timing of new infections, (3) network interdiction models to explore the impacts of pandemic-induced disruptions on geographically dispersed shelters and to determine the optimal assignments of shelters and resource allocations in response to emerging disease outbreaks, and (4) integrated qualitative and quantitative methods with active stakeholder participation to gather key information on the needs of vulnerable groups and enable definition of vulnerability indicators specific to hurricane-pandemics. Furthermore, the research will contribute to the multi-disciplinary education and technical training of under-represented minority students and producing advanced-degree HBCU graduates better prepared to enter the workforce.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.