LAUSR

As the frequency of natural disasters increases, there has been an emphasis on vulnerability index creation studies. In this study, we test the validity of vulnerability indices by examining a vulnerability index created for nursing homes throughout the Southeastern United States. In this index, underlying community characteristics, natural hazards frequency, and nursing home facility data were combined to create the Multivariate Nursing Home Vulnerability Index (MNHVI) using an inductive-hierarchical index structure. To internally validate these indices, a manual construction method and Monte Carlo simulations are used to create multiple unique versions of the MNHVI. Each iteration of the MNHVI considers alternative model structures for insight into regions of precision within the model and the average amount of variation for each census unit. External validation is used to determine if the indices are accurately predicting harm or mortality caused by storm events. External validation was assessed using death and injury statistics from NOAA’s storm event database and North Carolina death certificate data. Results demonstrated that indices were not precise despite changes in spatial scale and that hazard level indices were the most accurate predictor of injury and death from natural hazards. Identifying accuracy and precision for vulnerability indices provides additional assurance on the appropriate identification of at-risk regions.