AI-Powered Early Warning Systems for Aedes-Borne Viruses in the Dominican Republic
Photo Credit: Feepik
Overview
Aedes-borne viruses, dengue, chikungunya, and Zika pose a persistent and growing public health threat in the Dominican Republic, where climate-driven shifts in mosquito habitats are intensifying outbreak risk. For the communities most exposed, delayed detection and reactive response systems translate directly into preventable illness, strained health infrastructure, and deepening vulnerability.
The project builds AI and eco-epidemiology-based early warning systems that integrate epidemiological, entomological, meteorological, and community data to predict outbreaks before they escalate. The initiative weaves them into a unified platform designed to support timely, targeted interventions and strengthen climate-sensitive preparedness across the country's public health system.
The results are already shifting how health authorities anticipate and respond to vector-borne disease risk. Improved outbreak prediction is enabling earlier, more precise interventions, and a preparedness model grounded in local ecological and community data is building durable resilience to future climate-health threats.