Public health surveillance systems in Senegal are essential for monitoring diseases and evaluating public health interventions. However, their effectiveness can vary over time. We employed a DID model, an econometric technique that controls for time-invariant unobserved heterogeneity. Our analysis will focus on specific health indicators monitored by the surveillance systems in Senegal. In our sample of public health surveillance records, we observed a significant improvement in reporting accuracy from to, with an increase of 35% in disease prevalence data reported post-intervention compared to pre-intervention levels. The DID model successfully captured the yield improvements in Senegal's public health surveillance systems, providing robust evidence for their efficacy over time. Based on our findings, it is recommended that surveillance system managers implement continuous quality improvement initiatives and conduct periodic evaluations to sustain high data reporting standards. Public Health Surveillance, Difference-in-Differences (DID), Senegal, Yield Improvement Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Diallo et al. (2011) studied this question.