This study focuses on evaluating water treatment facilities in Senegal to assess their effectiveness in reducing risks associated with waterborne diseases. Bayesian hierarchical models were utilised to assess the effectiveness of water treatment facilities in reducing risks associated with waterborne diseases. The model accounts for spatial variability and heterogeneity in water quality across Senegal's diverse regions. The Bayesian hierarchical model revealed that certain advanced filtration systems significantly reduced the risk of waterborne diseases by up to 80% compared to basic treatment methods, highlighting regional variations where specific technologies were more effective. This study provides a robust methodological framework for evaluating and improving water treatment facilities in Senegal, with implications for public health policy and resource allocation. The findings suggest prioritising the implementation of advanced filtration systems in regions with higher risks to maximise risk reduction. Future research should explore long-term sustainability and cost-effectiveness. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Diop et al. (Thu,) studied this question.