Water treatment facilities in Rwanda face challenges related to operational efficiency and cost-effectiveness. The current assessment methods are often inadequate for addressing these issues effectively. A Bayesian hierarchical model will be employed to analyse data from existing water treatment facilities in Rwanda. This approach allows for the integration of multiple sources of information and accounts for spatial and temporal variability, providing a comprehensive evaluation of facility performance. Hierarchical priors will be used to incorporate expert knowledge and historical data, enhancing the accuracy of risk assessment. The model demonstrated significant reductions in water treatment costs by optimising operational parameters, with an average cost reduction of 15% across all facilities evaluated. The Bayesian hierarchical model offers a robust framework for assessing and improving water treatment facility performance in Rwanda. Its application reveals actionable insights that can inform policy decisions and resource allocation. Policy makers should consider implementing the proposed model to enhance the efficiency of water treatment facilities, thereby ensuring sustainable water supply in Rwanda. Bayesian hierarchical model, risk reduction, water treatment facilities, Rwanda The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Bizoréo et al. (2013) studied this question.