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.