Public health surveillance systems are crucial for monitoring infectious diseases in Senegal, a country with diverse epidemiological patterns and limited resources. Panel data analysis was conducted on surveillance data from to , employing a fixed effects regression model. The robust standard errors were used for inference. The estimated coefficient of the year variable in the panel data model suggests a moderate increase (p=0.03) in system reliability over time, indicating potential improvements. While initial results show some improvement, further longitudinal studies are needed to validate these findings and identify specific areas for enhancement. Investigate the impact of training programmes on surveillance staff and explore automation solutions to enhance efficiency without compromising accuracy. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.