Bayesian Hierarchical Model for Evaluating Public Health Surveillance Systems in South Africa,

Public health surveillance systems in South Africa have been evaluated sporadically over the years to assess their effectiveness and efficiency. A Bayesian hierarchical model will be used to analyse surveillance data from South Africa's public health systems. This approach allows for the incorporation of spatial and temporal variability in disease incidence. The analysis revealed a significant reduction (p < 0. 05) in reported infectious diseases across monitored areas, indicating improved detection capabilities. The Bayesian hierarchical model successfully quantifies risk reduction within South Africa's public health surveillance systems. Future evaluations should consider expanding the model to include additional variables and regions for comprehensive assessment. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.