Public health surveillance systems are crucial for monitoring infectious diseases in Senegal. These systems aim to provide timely and accurate data on disease incidence, which is essential for effective public health interventions. A mixed-method approach was employed, combining quantitative panel-data regression models with qualitative interviews and observations. Panel Data Estimation Techniques (PDET) were used to evaluate the reliability of public health surveillance data over time. The analysis revealed a significant positive relationship between timely reporting by healthcare facilities and accurate disease incidence estimates, indicating that enhanced reporting systems could improve system reliability. This study provides insights into the effectiveness of current public health surveillance practices in Senegal and offers recommendations for improving data collection and accuracy. The findings suggest that strengthening training programmes for healthcare workers and implementing robust data management protocols are necessary to enhance the reliability of public health surveillance systems. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.