SPATIAL MODELLING OF DENGUE OUTBREAK RISK BY INTEGRATING LARVAL DENSITY AND SOCIO-ENVIRONMENTAL FACTORS IN AN URBAN AREA

Abstract

Dengue Hemorrhagic Fever (DHF) remains a significant public health challenge in Indonesia. Effective prevention requires moving beyond reactive case-based responses to proactive, spatially-targeted interventions based on comprehensive risk factors. This study explores a spatial model to assess DHF outbreak risk in the working area of the Somba Opu Health Center, Gowa Regency, Indonesia. Primary and secondary data were integrated through GIS overlay analysis. Key parameters included larval density (House Index, Container Index, Breteau Index), microclimate (temperature, humidity), socio-environmental vulnerability (population and building density), and community capacity (implementation of the PSN 3M program). Results: Spatial analysis revealed significant heterogeneity in dengue hemorrhagic fever risk across the study area. High-risk clusters were identified in Katangka, Tompobalang, and Tombolo villages, associated with high larval indices, optimal microclimates, and high population density. Larval density showed a significant positive correlation with these optimal temperature and humidity ranges. In contrast, villages with consistent Mosquito Nest Eradication implementation, such as Kalegowa and Bonto-Bontoa, exhibited higher larva-free rates and lower overall risk. The integrated spatial model, incorporating entomological, climatic, and socio-environmental data, successfully categorized the region into low, medium, and high-risk zones. This precise mapping enables targeted, cost-effective vector control and allows health authorities to prioritize interventions in high-risk areas for sustainable dengue prevention.

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