A user-friendly digital prediction tool for dengue prevention

The Mekong Delta Region (MDR) of Vietnam is vulnerable to climate change which results in more frequent and intense mosquito-borne dengue outbreaks. Current dengue control measures are mostly reactive due to the absence of an early warning system (EWS) tailored to the needs of the local health systems. Local health practitioners and the community are, therefore, not adequately empowered to deploy preventive actions to reduce the impact of a dengue outbreak. We propose to develop and evaluate a digital dengue early warning system (E-DENGUE), based on a prediction model, to assist the local health systems and the local communities affected by dengue to proactively mitigate the impact of outbreaks in the MDR. The specific aims are: i) to build a predictive dengue model that accurately predicts dengue risk, at the district level, two months in advance; ii) to develop E-DENGUE--an open-source software system with a user-friendly web-based and mobile-app interface--aimed at local health practitioners to predict dengue incidence and outbreaks at the district level; iii) to evaluate the effectiveness of E-DENGUE in reducing dengue incidence using a cluster-randomised control trial based in the MDR; iv) To evaluate the cost-effectiveness of E-DENGUE for outbreak prevention in the MDR.