Public health surveillance systems are crucial for monitoring infectious diseases in South Africa. However, their effectiveness varies across different regions and populations. The study employed a meta-analysis approach, synthesizing data from multiple studies on public health surveillance effectiveness. Multilevel regression analysis was used to account for variability at different levels (e. g. , national vs. regional). Multilevel regression analysis revealed significant heterogeneity in risk reduction measures across regions, with some areas showing substantial reductions of up to 40%. The multilevel regression approach highlighted the need for targeted interventions and data standardization to enhance surveillance system effectiveness. Standardised reporting protocols should be implemented, and regional-specific risk reduction strategies developed based on analysis findings. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Mncube et al. (Tue,) studied this question.