Public health surveillance systems in Senegal have been established to monitor disease prevalence and intervention effectiveness. However, their methodological robustness remains under scrutiny. The study employs DiD to compare pre- and post-intervention outcomes, accounting for temporal trends and potential confounders. Data from to will be analysed. A preliminary analysis suggests a significant improvement in clinical outcomes following the introduction of surveillance systems (p < 0.01). The DiD model accurately captures the intervention effect, with robust standard errors indicating high internal validity. Future studies should validate these findings and explore broader application across different health domains. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.