Developing a Dynamic Social Vulnerability Index for Public Health (DSVI-PH) Using Location-based Data

This study developed a Dynamic Social Vulnerability Index for Public Health (DSVI-PH) by integrating the CDC’s social vulnerability index with Meta population movement data and hospital location datasets. We chose Hurricane Beryl (2024) as a target disaster and captured daily changes in vulnerability through Meta Data for Good Movement data, which is unlike static annual social vulnerability index data.

Summary of Findings
DSVI-PH captured daily fluctuations in social vulnerability by evacuation, return migration, and hospital accessibility compared to the current static social vulnerability index.
Hot and cold spot analysis revealed that spatial disparities within major cities (Houston, San Antonio, and Corpus Christi) influenced the distribution of vulnerability.

Policy and Practice Implications
Policymakers can use DSVI-PH to guide real-time allocation of resources, prioritizing highly vulnerable populations.
DSVI-PH provides a quantitative change of latent construct (social vulnerability), so we can set up the quantified adaptive recovery policies.