Public health surveillance systems in Senegal are crucial for monitoring infectious diseases such as malaria and tuberculosis (TB). These systems aim to reduce disease incidence by identifying and responding to outbreaks promptly. A multilevel regression model was employed to analyse the impact of public health surveillance systems on disease incidence at various geographical scales. This approach allows for accounting for clustering effects within regions and across different administrative divisions in Senegal. The analysis revealed a significant reduction (p < 0. 05) in TB incidence rates by 15% when surveillance systems were operational, indicating that these systems play a pivotal role in risk reduction. This study underscores the importance of robust public health surveillance systems for effective disease management in Senegal. Given the positive findings, it is recommended to enhance coordination and resource allocation within existing surveillance networks to ensure continuous improvement in public health outcomes. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Marie Diop Ndiaye (Tue,) studied this question.