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 Colaborativos, 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.