A Unified Operational Model for Dengue Control: Bridging Community Data and Clinical Surveillance

Abstract

Dengue fever continues to be a significant urban health issue in Bangkok, fueled by dense population, environmental factors, and incomplete surveillance systems. Even with continuous public health measures, a disparity remains between local vector control initiatives and institutional clinical surveillance, leading to slower outbreak responses and inefficient use of resources. This research seeks to create a cohesive clinical, environmental model that combines community-driven mosquito monitoring, clinical dengue tracking, and public health initiatives into one operational system. Employing a mixed-methods approach, the study took place from January to November 2025 in high-incidence districts within Bangkok and surrounding provinces. Data gathering comprised focus group discussions, interviews with key informants, and secondary analysis of dengue case statistics, vector density measures, and fogging operations. A four-phase model development approach was utilized, incorporating co-design with stakeholders, thematic coding of qualitative information, and triangulation of quantitative data sets. Results show that present response efforts are obstructed by data disconnection, poorly timed fogging, and restricted community involvement. The suggested model enhances real-time data exchange and feedback among community health volunteers, clinics, and city officials, allowing for improved vector management and quicker outbreak responses. It enables communities to serve as proactive participants in surveillance systems, rather than merely as beneficiaries of interventions. Moreover, the model is created to be flexible and suitable for different urban settings. Subsequent studies should aim at conducting pilot tests of the model in chosen districts of Bangkok, incorporating mobile reporting tools, and assessing cost-effectiveness and scalability in larger Southeast Asian urban areas.