“Geographic Information Systems for Dengue Hotspot Identification in Central India: A Spatial Risk Assessment Framework”

Dengue fever remains a critical public health challenge in India, with spatial and temporal distribution patterns influenced by environmental, demographic, and entomological factors. This study applies Geographic Information System (GIS) technology to analyze dengue spatial distribution, identify high-risk zones, and establish temporal patterns across Betul District, Madhya Pradesh. Analysis of confirmed dengue cases across three seasons (monsoon, summer, and winter) alongside entomological vector indices (House Index, Container Index, and Breteau Index), population density, rainfall, and humidity data revealed significant seasonal clustering and persistent hotspots in Betul and Amla tehsils. Monsoon transmission accounted for 68% of annual dengue cases, with spatial autocorrelation analysis (Morans I = 0.32, p < 0.05) confirming statistically significant clustering. Breteau Index emerged as the strongest predictor of outbreak risk, with densely populated urban tehsils (>300 persons/km²) showing consistently elevated transmission. GIS-based risk mapping successfully identified priority intervention areas and demonstrated the effectiveness of integrated spatial analysis for targeting vector control strategies and resource allocation in endemic regions.