Spatial Optimization and District-Level Allocation of Heat-Health Relief Centers in West Bengal, India: A Location-Allocation Modeling Study

Background: The increasing frequency and intensity of extreme thermal events pose a severe public health hazard across West Bengal. Conventional ad-hoc infrastructure planning routinely favors ultra-dense metropolitan centers, leaving marginalized peripheral communities critically unprotected. The aim of this study deployed a prescriptive Capitated p-Median location-allocation optimization routine using a multi-dimensional Heat-Health Vulnerability Index (HHVI) to mathematically anchor 20 district-level emergency cooling centers across 840 community clusters. This study deployed a prescriptive Capitated p-Median location-allocation optimization routine using a multi-dimensional Heat-Health Vulnerability Index (HHVI) to mathematically anchor 20 district-level emergency cooling centers across 840 community clusters. Material and Methods: Regional distances were modeled using the Haversine Great-Circle Distance formula. Statistical analysis used: To balance operational efficiency with regional administrative equity, a spatially stratified policy scenario was executed to secure exactly one relief medoid within each individual district boundary. Results: The empirical HHVI revealed an extensive continuous risk gradient spanning from 0.0873 to 0.6293. Built-environment insulation traps (Iroof) held the strongest positive correlation with vulnerability (r = 0.6956). Conversely, population density displayed a notable negative correlation (r = -0.3143), revealing an "urban infrastructure paradox" where dense metropolitan centers enjoy superior structural adaptive capacity over isolated rural areas. The optimization algorithm successfully selected urban locations in 15 districts but dynamically bypassed metropolitan bias to establish rural hubs in five agricultural zones, where severe housing deficits and absolute medical isolation overrode raw population density. Conclusion: This spatial optimization framework provides disaster management authorities with a scientifically validated blueprint to maximize climate resilience and equitable public health protection.

Keywords: Climate Change, Cooling Centers, Heat Stress, India, Spatial Analysis, Vulnerable Population.