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

Abstract

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.

Hospital Disaster Resilience: a Conceptual Framework

“…Vulnerability is also referred to as the amount of exposure to hazard systems and structures experience, while resilience is the capability systems and structures have to manage, withstand, and/or overcome disaster. It is also argued that vulnerability is the opposite of resilience, but that a distinction between passive versus active, and pre-disaster versus post-disaster, is recognised in relation to the terms 'vulnerability' and 'resilience' (Johnson et al, 2020). Thus, an analysis of research literature leads to the conclusion that the definition of the term 'resilience' as the ability to manage external hindrances essentially encompasses the concept of 'vulnerability'.…”

Geospatial indicators of exposure, sensitivity, and adaptive capacity to assess neighbourhood variation in vulnerability to climate change-related health hazards

“…The idea of measuring vulnerability has also been contested [21,24] due to the difficulty of operationalising a complex process of adaptation -'a change in processes, practices, and structures to moderate potential damages or to benefit from opportunities associated with climate change'. That is, adaptive capacity is a theoretical measure of the future ability to reduce future risks through individual-and societal-level interventions, and other frameworks have adopted more risk-management framing.…”

“…A review of vulnerability indicators revealed that indicators in the past have been constructed with a variety of approaches including expert judgment [17], multi-criteria decision analysis [18], equal weighting, ordered weighted averaging [19], unweighted standardisation [17], analytic hierarchy process [18], and multivariate statistical techniques, such as principal components [17] or cluster analysis [20]. Johnson and colleagues argue that the community vulnerability and resilience literature is lacking data-driven methodologies that are more conducive to empirical validation compared to theory-driven philosophies [21]. Future data-driven vulnerability indices may benefit from the selection of indicators and weights-based references, local contextual information, and relevant hazard-related health outcomes [20].…”

Degree and direction of overlap between social vulnerability and community resilience measurements

“…There have been relatively few empirical studies explicitly assessing relationships between community resilience and social vulnerability measures and how these manifest themselves spatially and temporally [ 3 ]. Whether resilience and vulnerability are complementary or conflicting concepts, an idea initially posed by Miller et al [ 4 ], remains ambiguous, despite recent studies on reconciling measurements of these two concepts [ 5 ]. Are earlier claims of statistical independence and negative correlations true?…”

“…Sherrieb et al only found a 14% overlap between their community resilience measure and SoVI, yet a significantly strong negative correlation between the two (r = -0.68). Two other studies [ 34 , 35 ] also found negative correlations between community resilience and social vulnerability with varying strengths of the correlations, but none as high as Sherrieb et al As they concluded, “…data support the premise that the three attributes share some common characteristics yet are distinct concepts (2010, p. 241).” Johnson et al [ 5 ] compared six empirically based indices at the variable level to identify redundancies between them and using a factor analytic approach found five factors accounted for 34% of the variation in county measurements of vulnerability and resilience. However, and most significantly, they did not distinguish between vulnerability and resilience variables and thus did not delineate the overlap in variable level measurements and interactions.…”