The power distribution sector in Uganda faces significant challenges related to reliability and cost-effectiveness of equipment systems. A Bayesian hierarchical model was employed to analyse data from field surveys and financial records, allowing for the disaggregation of costs into components such as installation, maintenance, and operation. This approach enabled an assessment of system performance across different geographical regions within Uganda. The analysis revealed a significant variation in cost-effectiveness metrics between urban and rural areas, with a proportion of 45% lower operational costs observed in well-maintained systems compared to those requiring frequent repairs. Bayesian hierarchical models provided insights into the distributional patterns of power equipment costs, highlighting the importance of localized interventions for optimising system performance. Investment strategies should prioritise upgrading and maintaining critical infrastructure components in rural regions where cost-effectiveness is most compromised. Power Distribution, Equipment Systems, Cost-Effectiveness Analysis, Bayesian Hierarchical Models, Uganda The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Rubarencwa et al. (Tue,) studied this question.
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