Public health surveillance systems in South Africa play a critical role in detecting and responding to infectious diseases. However, their efficiency varies across different regions and levels of government. A multilevel regression model was employed to analyse data from various sources including district health information systems, national disease reporting databases, and government reports. The model accounted for both fixed effects (e.g., regional differences) and random effects (e.g., within-district variations). The analysis revealed significant heterogeneity in system performance across districts, with some regions showing up to a 20% improvement in detection rates when compared to the national average. Multilevel regression analysis provides valuable insights into the efficiency of public health surveillance systems and highlights areas for targeted intervention and resource allocation. Efforts should be directed towards enhancing data collection practices, increasing training opportunities for healthcare workers, and improving infrastructure in underperforming districts. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.