Comparative Analysis of Social Vulnerability Indices: CDC’s SVI and SoVI®

Sammanfattning: As interest in social vulnerability to hazards grows, more indices are formulated for identifying and mapping population groups that may experience differential consequences from natural hazards. However, less attention has been given to the underlying choices researchers make when creating these indices. With the aim to contribute to understanding the issues surrounding social vulnerability indices, this research will analyze and compare two popular methods for social vulnerability mapping: CDC SVI and SoVI®, using San Francisco, California, U.S.A. as a case study. To do so, this research focuses on the impact of each model’s unique components: the type of social vulnerability each model exhibits and the overall usability of each model. Using Pearson correlation analysis to assess the association of age dependency variables, the two models, different geographic scales and statistical choices, it is clear that index variable selection has the biggest impact on index results. Geographic units within San Francisco that have the largest difference between the two models, when classified, are analyzed to understand what underlying variables the models use to represent social vulnerability to create different results. Results show that CDC SVI better represents a socioeconomic related social vulnerability, while SoVI® focuses on old age related social vulnerability. Furthermore, a SWOC analysis is employed to understand which model works best for an organization internally vis a vis ease of use and time and cost and externally, regarding the type of social vulnerability they intend to reduce. Findings suggest that for internal use, CDC SVI is easier to use, but for external use, the organization should consider the variables that compose each index to understand what kind of social vulnerability they aim to reduce.