Bayesian Hierarchical Model for Measuring System Reliability in Tanzania's Water Treatment Facilities Systems

Water treatment facilities in Tanzania are critical for ensuring safe drinking water, yet their reliability varies significantly across different regions. A Bayesian hierarchical model was employed to estimate system reliability by considering both fixed and random effects across multiple facilities in Tanzania. The model accounts for spatial variability and incorporates prior knowledge about facility types and locations. The model estimated that approximately 75% of water treatment systems were operating within their designed reliabilities, with significant differences observed between urban and rural settings. This study provides a robust framework to assess system reliability in Tanzania's water treatment facilities, enhancing the quality of life for residents by improving access to safe drinking water. Implementing preventive maintenance strategies based on model predictions can further improve system performance and reduce failure rates. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.