Evaluating social vulnerability indicators: criteria and their application to the Social Vulnerability Index

Abstract

As a concept, social vulnerability describes combinations of social, cultural, economic, political, and institutional processes that shape socioeconomic differentials in the experience of and recovery from hazards. Quantitative measures of social vulnerability are widely used in research and practice. In this paper, we establish criteria for the evaluation of social vulnerability indicators and apply those criteria to the most widely used measure of social vulnerability, the Social Vulnerability Index (SoVI). SoVI is a single quantitative indicator that purports to measure a place's social vulnerability. We show that SoVI has some critical shortcomings regarding theoretical and internal consistency. Specifically, multiple SoVI-based measurements of the vulnerability of the same place, using the same data, can yield strikingly different results. We also show that the SoVI is often misaligned with theory; increases in variables that contribute to vulnerability, like the unemployment rate, often decrease vulnerability as measured by the SoVI. We caution against the use of the index in policy making or other risk-reduction efforts, and we suggest ways to more reliably assess social vulnerability in practice.

Methodological challenges to confirmatory latent variable models of social vulnerability

“…Only one of the five pillar models (Socioeconomic Status) achieved acceptable fit, while two others had marginal fit even after significant model respecification that may not generalize to new samples. Our results underscore challenges with the construct validity of SoVI (Spielman et al 2020), which remain an obstacle to achieving the goal of specifying a widely applicable vulnerability index. At the same time, we also face the reality that social vulnerability to hazards and disasters may be more context-specific than many other public health constructs, and that a generalizable indicator may be unnecessary for locally identifying vulnerable communities and facilitating effective disaster preparedness, response, and recovery efforts.…”

“…Although, the SoVI model has become one of the more notable targets for critical review. Most recently, Spielman and colleagues ( 2020 ) observed several problems with two measures used to determine a model’s utility, construct validity, and internal consistency. Spielman and colleagues ( 2020 ) further argue that SoVI’s construction is not consistently robust with respect to traditional psychometric theory.…”

Cluster Around Latent Variable for Vulnerability Towards Natural Hazards, Non-Natural Hazards, Social Hazards in West Papua

“…A proper assessment also needs to be sustainable habits by monitoring all phenomena covering infrastructure, socioeconomy and physics in disaster-prone areas and this information is also important for development planning. SoVI is also mismatched to theory and tends changes in variables that contribute to vulnerabilities, including unemployment, also minimize vulnerability [23]. Previous study, Nasution [24] addressing the new biophysical indicators, which are renters and housing quality to measure the social vulnerability index in Indonesia.…”

Using disaster outcomes to validate components of social vulnerability to floods: flood damage and property damage across the USA

“…This also means that the ability of policy makers to accurately target adaptation strategies that would reduce harm to populations most at risk may be limited precisely because the indicators and indices available may be inadequate for predicting the propensity for loss in a hazard. Validation of these widely used indices is particularly important to understand how factors of social vulnerability may remain constant or change over spatial, temporal, and socio-political scales as well as across different types of hazards [24]. Quantitative social vulnerability assessment requires more attention to internal validity through sensitivity and uncertainty analysis (e.g., Tate et al [20]) and external validity through the comparison of disaster outcomes to vulnerability metrics (e.g., [21].…”

“…Most quantitative assessments use social vulnerability indicators such as the SoVI that are generalized for all types of natural hazards [17], and which do not choose sociodemographic variables specific to flood hazards. In addition, minimal attention to the differential weighting of variables, analysis of uncertainty, and appropriate scales of analysis can lead to unstable results that predict different communities at risk when small changes in weights of specific variables are made [20,24,88]. Even more problematic, often social vulnerability indicators are not derived from empirical data on disaster loss specific to flood hazards [44].…”