This research improves disease mapping by using mixture modeling to capture sharp spatial differences in health risk. Unlike traditional models that assume smooth patterns, this approach better identifies high-risk areas, enabling more accurate resource allocation, improved public health policy, and reduced health inequalities during disease outbreaks.

This research uses data fusion and spatial statistics to combine official and citizen weather data, improving real-time, high-resolution wind forecasts across Ireland. By validating and correcting personal weather stations, the approach reduces uncertainty in renewable energy forecasting and supports efficient grid management toward Ireland’s 2050 net-zero targets.