Developing a data-driven system for identifying socially vulnerable populations and neighborhoods across the United States.

Abstract

Due to increased efforts to bolster both equity and resilience to natural hazards, there is considerable interest in developing precise methods for identifying socially vulnerable populations. The objective of this paper is to explain issues with how common social vulnerability indices use United States (US) Census Bureau data for emergency management and how the Census' new Community Resilience Estimates (CRE) program overcomes these concerns. Using the 2019 CRE as a case study, we demonstrate how small area estimates of the most socially vulnerable populations in the US can be used to make statistical comparisons. We find that the high social vulnerability population rate is greater in the South, small rural and isolated areas, and environmentally toxic communities. In developing a response to bolster community resilience to natural hazards, decision-makers should rely on the CRE program to quantify socially vulnerable -populations.