MATHEMATICAL STABILITY ANALYSIS OF HIERARCHICAL BAYESIAN EPIDEMIC MODELS UNDER CLIMATE VARIABILITY

We examine how climate variability shapes epidemic stability and how institutional preparedness alters this relationship using the Climate Adaptive Epidemic Stability Model applied to Ghana between 2020 and 2025. The analysis integrates the Climate Driven Epidemic Variability Dataset which links temperature fluctuation rainfall variability humidity dynamics health system preparedness and epidemic stability indicators derived from national surveillance and climate monitoring systems. Empirical evidence shows that rising temperature instability rainfall variability and humidity dynamics intensify epidemic transmission conditions through vector expansion environmental exposure and atmospheric pathogen persistence. However stronger surveillance coverage laboratory capacity emergency response capability and public health funding moderate these pressures and strengthen epidemic containment performance. Infection stability improves transmission control rises outbreak frequency declines and recovery efficiency increases during the observation period despite increasing climate volatility. These results extend environmental epidemiology theory by demonstrating that epidemic stability emerges from the interaction between climate exposure and institutional resilience rather than environmental pressure alone. The findings provide policy guidance for integrating climate monitoring with health preparedness systems to strengthen epidemic resilience in climate sensitive regions and global health surveillance frameworks.