Y. Asare Afrane

This study proposes a hybrid Gaussian Process Regression and Holt-Winters smoothing framework to accurately forecast under-five malaria admissions in Ghana, achieving high predictive accuracy and providing probabilistic uncertainty estimates.

This study develops a Bayesian nonlinear inference framework to model age-specific malaria dynamics in Ghana, providing probabilistic forecasts of resurgence and quantifying significant spatial heterogeneity.

A consensus anomaly detection framework was used to identify atypical malaria transmission patterns in Ghana (2014-2023), revealing spatial distinctions between anomaly burden and frequency.