Authors: Matthew Wilson*, Appalachian State University, Maggie M Sugg, Appalachian State University, Sandi J Lane, Appalachian State University
Topics: Hazards and Vulnerability, Hazards, Risks, and Disasters, Geographic Information Science and Systems
Keywords: Vulnerability, Validation, Hazards, Elderly
Session Type: Paper
Start / End Time: 9:55 AM / 11:35 AM
Room: Marshall South, Marriott, Mezzanine Level
Presentation File: No File Uploaded
The increase in disaster frequency has prompted a shift in preparation strategies for emergency management personnel, especially in relationship to disproportionately impacted demographics. To address these new needs, an interdisciplinary approach is used to assess the vulnerability of nursing home facilities throughout the southeastern United States. Using an inductive-hierarchical index structure; underlying community characteristics, natural hazards frequency, and nursing facility demographics are combined to create the Multivariate Nursing Home Vulnerability Index (MNHVI). This index determines the relative vulnerability of nursing homes at both county and census tract levels. Before the index can be confidently implemented, the MNHVI must be internally and externally validated. To internally validate the multivariate index, both the brute force method and Monte Carlo simulations are used to create multiple unique versions of the MNHVI. Each iteration of the MNHVI considers alternative choices throughout the index construction process which allows for insight into sources of uncertainty and sensitivity within the model. To externally validate the MNHVI, a case-crossover study is used to compare age-adjusted death rates following specific hazard events to a baseline death rate with the fewest possible confounding variables. To properly conduct this analysis, a distributed lag non-linear model is used to examine the relative risk of death for older adults (aged 65+) and nursing home residents over time. The goal of this research is to determine where the MNHVI is identifying vulnerability most accurately to bolster confidence in emergency preparedness strategies and hazard mitigation for this disproportionately impacted demographic.