Public health surveillance systems are crucial for monitoring disease prevalence and guiding targeted interventions in developing countries like Senegal. This research employs a difference-in-differences (DID) econometric model to assess the impact of enhanced surveillance capabilities over time. The DID approach compares changes in key indicators for pre-intervention periods with post-intervention periods, accounting for baseline differences between regions or years. The analysis reveals that the introduction of new data collection methods led to an average 25% reduction in underreporting of infectious diseases across Senegal's surveillance networks. Enhanced public health surveillance systems have shown significant potential to improve disease reporting and response efficiency, particularly through targeted training programmes for healthcare workers. Policy makers are advised to invest in continuous capacity building for surveillance staff and expand coverage of remote areas where data collection is currently limited. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Arnold et al. (2015) studied this question.