Public health surveillance systems are essential for monitoring diseases and managing outbreaks effectively in developing countries like Senegal. A mixed-method approach was employed to assess the implementation and effectiveness of surveillance systems. Multilevel logistic regression models were used to analyse data from surveys conducted among healthcare workers and communities. Multilevel regression analyses revealed that adoption rates varied significantly across levels, with national-level systems showing higher adherence (85%) compared to regional (60%) and community (40%). The multilevel regression analysis provided insights into the factors influencing system adoption at various levels. Further research should focus on enhancing communication channels between levels to improve overall system effectiveness. Public health surveillance, Senegal, Multilevel regression, Adoption rates Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Diop et al. (Fri,) studied this question.