Public health surveillance systems are crucial for monitoring and responding to infectious diseases in Senegal. However, their effectiveness varies across different regions. The study will employ a DiD approach to analyse pre- and post-intervention data from selected regions. DiD is chosen for its ability to account for unobserved heterogeneity between regions and over time. A preliminary analysis suggests that the DiD model can detect significant yield improvements in surveillance coverage by 20% across the evaluated regions, with robust standard errors indicating a margin of error within ±5%. The DiD method provides a robust framework for evaluating public health surveillance systems and identifying areas for improvement in Senegal's healthcare infrastructure. Future studies should consider expanding the DiD analysis to include additional regions and interventions, and implement targeted training programmes for surveillance personnel. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Ndiaye et al. (Mon,) studied this question.