A Factor Analysis Approach Toward Reconciling Community Vulnerability and Resilience Indices for Natural Hazards

The concepts of vulnerability and resilience help explain why natural hazards of similar type and magnitude can have disparate impacts on varying communities. Numerous frameworks have been developed to measure these concepts, but a clear and consistent method of comparing them is lacking. Here, we develop a data-driven approach for reconciling a popular class of frameworks known as vulnerability and resilience indices. In particular, we conduct an exploratory factor analysis on a comprehensive set of variables from established indices measuring community vulnerability and resilience at the U.S. county level. The resulting factor model suggests that 50 of the 130 analyzed variables effectively load onto five dimensions: wealth, poverty, agencies per capita, elderly populations, and non-English-speaking populations. Additionally, the factor structure establishes an objective and intuitive schema for relating the constituent elements of vulnerability and resilience indices, in turn affording researchers a flexible yet robust baseline for validating and expanding upon current approaches.