Social Vulnerability and Access of Local Medical Care During Hurricane Harvey: A Spatial Analysis

• Authors: David S Rickless, Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, Atlanta; Grete E Wilt, Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, Atlanta; Danielle J Sharpe, Emory University; Noelle Molinari, Centers for Disease Control and Prevention; William Stephens, Texas Informatics, Dallas-Fort Worth; Tanya Telfair LeBlanc, Centers for Disease Control and Prevention
• Journal Title: Disaster Medicine and Public Health Preparedness
• Volume: Volume 17
• Publisher: Cambridge University Press (CUP) | 2021-03-15
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1017/dmp.2020.421
• Subjects: Health Sciences, Public Health; Environmental Sciences
• Keywords: emergency medical services; geographic mapping; natural disasters; social vulnerability; spatial statistics

Abstract

Objectives: When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW). This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere. Methods: We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent. Results: Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding. Conclusions: These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status.