A Foundational Dataset for the Predictive Prevention of Waterborne Disease

We propose the creation of a new, open, and continuous dataset generated by a global network of autonomous, solar-powered smart buoys. Today, the fight against waterborne diseases like cholera and typhoid is fundamentally reactive, crippled by a critical data bottleneck: the lack of timely, high-resolution information on water quality. Manual sampling is slow, sparse, and expensive, meaning authorities only learn of a contamination event after people are already sick. By providing a continuous stream of molecular-level pathogen data fused with environmental metrics, this dataset will, for the first time, enable the AI community to build sophisticated, real-time forecasting models for disease outbreaks. Our vision is to catalyze a global, AI-powered early warning system that transforms public health from a reactive to a proactive science, preventing outbreaks and saving lives in the world's most vulnerable communities.