Public health surveillance systems are critical for early detection and response to disease outbreaks, yet robust methodological frameworks for their longitudinal evaluation, particularly in resource-limited settings, remain underdeveloped. This study aimed to methodologically evaluate the efficacy of the national public health surveillance system and to quantify its impact on population health risk reduction over time. We constructed a balanced panel dataset from national administrative records. Efficacy was estimated using a two-way fixed effects model: Y₈ₓ = + ₁ Intervention₈ₓ + ᵢ + ₜ + ₈ₓ, where Y₈ₓ is the log-transformed incidence of priority reportable diseases. Inference was based on cluster-robust standard errors at the regional level. Enhanced surveillance intensity was associated with a statistically significant 18. 2% reduction in reported incidence for targeted diseases (95% CI: 12. 5% to 23. 5%). The system's sensitivity improved markedly following the integration of community health workers, though specificity challenges persisted in certain regions. The surveillance system has demonstrably contributed to improved disease detection and risk reduction. Its efficacy is significantly enhanced by structured community engagement and digital reporting tools. Investment should focus on strengthening diagnostic specificity, expanding the community-based reporting network, and institutionalising the panel-data evaluation framework for continuous system assessment. public health surveillance, health systems evaluation, panel data, fixed effects models, health metrics, sub-Saharan Africa This paper provides a novel application of panel-data econometric methods to quantify the longitudinal impact of a national surveillance system, introducing a replicable model for attributing changes in disease burden to system performance.
Mkumbo et al. (Wed,) studied this question.