AINeutralarXiv – CS AI · 7h ago6/10
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Bayesian Inference of Nonlinear Malaria Dynamics in Ghana via an Ensemble Markov Chain Monte Carlo Sampler
Researchers developed a Bayesian machine learning framework to model malaria dynamics in Ghana using health facility data from 2014-2023, achieving 99.58% accuracy in capturing non-linear, age-specific disease patterns. The model forecasts a gradual resurgence in malaria cases through 2026, with projections ranging from 137,000-149,000 cases in children under five and 348,000-375,000 in older populations, enabling data-driven public health decision-making.