Context-Aware Recommendations for the Prevention of Urban Arbovirus Outbreaks - Arouca, Murilo Guerreiro; Durão, Frederico Aráujo (Anais do Simpósio Brasileiro de Sistemas Colaborativos (SBSC); 2026: Anais do XXI Simpósio Brasileiro de Sistemas ColaborativosDO - 10.5753/sbsc.2026.20270, 2026)
Urban arboviruses pose significant public health challenges in vulnerable urban areas, where traditional surveillance is often reactive and limited in delivering timely, localized guidance. This paper proposes a context-aware recommender system that integrates climatic data and crowdsourced environmental reports to proactively identify risk areas and deliver personalized preventive recommendations. A spatio-temporal clustering approach (ST-DBSCAN) identifies dynamic risk areas, and a multi-criteria model combines environmental and climatic indicators into a normalized risk score classified into operational levels. Based on these levels, the system generates context-sensitive recommendations, enabling proactive and localized interventions.