{ "background": "Public health surveillance systems in sub-Saharan Africa are critical for disease control but often operate suboptimally, with poorly quantified yield. Methodological rigour in evaluating these systems, particularly for measuring intervention impact, remains underdeveloped.", "purpose and objectives": "This intervention study aimed to methodologically evaluate a structured enhancement package for district-level surveillance and quantify its effect on case reporting yield using a robust multilevel modelling framework.", "methodology": "We conducted a stepped-wedge cluster trial across 12 districts. The intervention comprised protocol standardisation, targeted training, and integrated feedback loops. The primary outcome was the monthly yield of confirmed priority disease reports. We fitted a three-level random intercepts model: $\\log(Y{ijt}) = \\beta0 + \\beta1 T{ijt} + ui + v{j(i)} + \\epsilon{ijt}$, where $ui \\sim N(0, \\sigma^2u)$, $vj \\sim N(0, \\sigma^2v)$, and $\\epsilon{ijt} \\sim N(0, \\sigma^2)$, adjusting for health facility type and catchment population. Inference was based on robust standard errors.", "findings": "The intervention significantly increased mean reporting yield (incidence rate ratio 1.84, 95% CI 1.51 to 2.24, p<0.001). This corresponds to an 84% increase in confirmed reports post-intervention. Variability between districts ($\\sigma^2_u$) accounted for 31% of the residual variance in the null model.", "conclusion": "A standardised enhancement package substantially improved surveillance yield, demonstrating that systematic operational improvements can overcome common systemic constraints.", "recommendations": "National programmes should adopt integrated, standardised training and feedback mechanisms. Future evaluations should employ multilevel models to account for clustering and identify heterogeneity in intervention effects.", "key words": "surveillance systems, health systems strengthening, mult