Geographic Heat Vulnerability Among Individuals with Sickle Cell Disease: A Spatial Linkage Analysis
Siobhan M Lawler, Li Yang, Stephaine Wildridge, Ashley Buscetta, Rebecca Metellus, Samuel M Degenhard, Djaina-Shae Dervil, Samuel Zamora, Danetta Hooks, Allison Brichacek, Vence M Bonham, Hannah Lee, Manu M Platt, Nicole FarmerAbstract
Background
Sickle cell disease (SCD) is a chronic hematologic condition characterized by episodic vaso-occlusive crises and heightened sensitivity to environmental stressors, including heat exposure. Elevated ambient temperatures and heat waves have been associated with increased rates of pain episodes, dehydration, and hospitalizations among individuals with SCD. Despite growing recognition of climate-related health risks, few studies have systematically linked patient-level geographic data with standardized environmental heat vulnerability metrics. The Heat Health Index (HHI) integrates climatologic, demographic, and social vulnerability indicators to characterize community-level susceptibility to heat-related illness. The objective of this study was to link SCD study participant locations to HHI geographies and characterize heat vulnerability exposure among participants by extracting and mapping the overall HHI score values for matched geographic identifiers.
Methods
We conducted a cross-sectional linkage analysis between an existing SCD research cohort dataset and a publicly available HHI dataset. Participant residential locations were geocoded and assigned geographic identifiers (GeoIDs) corresponding to U.S. Census-based spatial units, then matched to HHI GeoIDs. For matched records, the overall HHI score was extracted and categorized into three vulnerability tiers: high (≥0.70), moderate (0.40–0.69), and low (< 0.40). Descriptive statistics were generated to summarize the distribution of heat vulnerability exposure across the SCD cohort. Analyses were conducted using standard data management and visualization software (RStudio). Gender disaggregation was not available for the current analytic extract and will be incorporated in subsequent analyses.
Results
A total of 64 SCD study participants with available geographic identifiers were included in the linkage analysis. Of these, 100% were successfully matched to corresponding HHI GeoIDs. Eleven Thirteen participants (20.30%) resided in high heat vulnerability areas (HHI ≥0.70). The remaining participants were distributed across moderate (42.2%) and low (37.5%) vulnerability categories. High-HHI locations were geographically clustered in the southeastern and south-central United States, including parts of Texas (e.g., 77004, 77061, 77088, 75150), Georgia (e.g., 30315 and 31701), South Carolina (e.g, 29048), Alabama, Mississippi, Maryland, and Kentucky (e.g., 41840). Additional notable high-HHI GeoIDs included 21217, 21213, and 25401 in the Mid-Atlantic region. Moderate-HHI participant locations were observed across additional southeastern and Midwestern regions, while low-HHI locations were comparatively fewer and dispersed. The spatial overlay demonstrated that a substantial proportion of SCD participants resided in communities characterized by elevated composite heat vulnerability scores.
Conclusions
This study demonstrates the feasibility and utility of linking patient-level SCD geographic data with a standardized HHI to characterize environmental heat vulnerability exposure. Over 20% of SCD participants in this cohort resided in high-HHI areas, highlighting a potentially important environmental risk context for a population already susceptible to heat-related complications. Spatial clustering of high-vulnerability locations in the southeastern and south-central United States underscores the intersection of climatic, demographic, and social determinants of health in shaping risk for individuals with SCD. These findings support the integration of environmental vulnerability metrics into SCD research and care planning to inform targeted prevention strategies, patient education, and climate-adaptive interventions. Future work will incorporate gender-disaggregated analyses, longitudinal clinical outcomes, and refined spatial units to evaluate associations between heat vulnerability, SCD morbidity, and healthcare utilization.