Citation

Adepoju OE, Kiaghadi A. Disaster Med. Public Health Prep. 2023; ePub(ePub): ePub.

Copyright

(Copyright © 2023, Society for Disaster Medicine and Public Health, Publisher Cambridge University Press)

DOI

10.1017/dmp.2023.29

PMID

36805737

Abstract

Researchers have developed numerous indices to identify vulnerable sub-populations. The Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) is the most common and highly functional, but it has some temporal limitations; constant transformations in societal composition change social vulnerability. The 15 variables categorized into four themes temporally limits the use of SVI to recent years because some variables used in calculating SVI were not available prior to 1980. We defined an alternative index that could serve as a surrogate for the CDC-SVI without the temporal limitations. An inventory analysis of the historical census data (1960-2018) was used to develop a Modified SVI that allows for historic analyses. This modified SVI can be used to generate historical maps, find temporal patterns, and inform a longitudinal SVI measure. Furthermore, to consider the chronical effect of social vulnerabilities, a longitudinal SVI was introduced to elucidate how a community's multidimensional experiences exacerbate social vulnerability to disaster events. We use Harris County, Texas to examine how the modified SVI performs against the original CDC-SVI. The results showed a good agreement among the developed indices and the CDC-SVI and satisfactory performance in identifying the areas that are most vulnerable to COVID-19 pandemic.

Language: en

Keywords

Public Health; COVID-19; Harris County; Temporal Analysis