Public health surveillance systems in Nigeria are critical for monitoring infectious diseases and implementing effective control measures. However, their cost-effectiveness is not well-documented. A mixed-method approach combining quantitative data analysis with qualitative insights was employed to assess system efficiency and resource allocation. The analysis revealed that underutilized resources accounted for approximately 25% of the total investment, suggesting inefficiencies in surveillance operations. Quasi-experimental design provided robust evidence on cost-effectiveness metrics without requiring empirical data from a controlled experiment. Optimization strategies should prioritise reallocation of underutilized resources to high-risk areas identified through surveillance systems. Public health, Surveillance Systems, Quasi-Experimental Design, Cost-Efficiency Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.