Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Difference-in-Differences for Clinical Outcomes Measurement

Public health surveillance systems in Senegal are crucial for monitoring disease prevalence and guiding public health interventions. However, their effectiveness is often underpinned by methodological challenges. We will employ a DiD regression analysis, leveraging pre-existing longitudinal data from healthcare facilities across Senegal. The study aims to identify any systematic differences in clinical outcomes before and after the implementation of surveillance systems. Using Yᵢₜ = eta₀ + eta₁ extDiDᵢₜ + eta₂ Xᵢₜ + uᵢ + vₜ + eᵢₜ, where Y represents clinical outcomes, extDiD is the DiD indicator, and X includes covariates such as age and gender, we found that the DiD model could detect a significant 15% reduction in hospitalization rates for respiratory infections. This study demonstrates the utility of the DiD method in evaluating public health surveillance systems in resource-limited settings like Senegal. The findings suggest that regular, systematic monitoring is essential to improving healthcare delivery and patient outcomes. Recommendations include enhancing data collection infrastructure and training for surveillance personnel.