Public health surveillance systems are crucial for monitoring infectious diseases in resource-limited settings like Senegal. However, their effectiveness can vary significantly across different regions and healthcare facilities. Multilevel regression analysis was employed, incorporating data from multiple sources including surveillance reports, clinic records, and demographic information. The model accounts for both within-facility variation and facility differences in disease reporting accuracy. The multilevel regression analysis revealed that the proportion of timely disease notifications increased by 15% (95% CI: [7%, 23%]) after implementing quality control measures at healthcare facilities, indicating improved system performance. Quality control interventions significantly enhanced the public health surveillance systems in Senegal, leading to more accurate and prompt reporting of infectious diseases. Further research should focus on scaling up these quality control measures across all healthcare facilities in Senegal to maximise yield improvement. Public Health Surveillance, Quality Control, Multilevel Regression Analysis, Infectious Diseases, Resource-Limited Settings Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.