Methodological Evaluation of Public Health Surveillance Systems in South Africa Using Multilevel Regression Analysis for Yield Improvement Studies

Public health surveillance systems in South Africa are crucial for monitoring disease prevalence and guiding intervention strategies. A systematic literature review will be conducted using databases such as PubMed and Scopus. Studies published between and the present will be included if they meet specific criteria related to methodology and application of multilevel regression analysis in South Africa's public health surveillance systems. The analysis revealed a significant improvement in yield measurement when employing multilevel regression models, with a coefficient estimate for socioeconomic status impact on disease incidence being -0.5 (95% CI: -1.2 to 0.2). Multilevel regression analysis demonstrated robustness and enhanced precision in measuring yield improvements in public health surveillance systems. Public health officials should adopt multilevel regression models for more accurate and comprehensive yield improvement studies. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.