"background": "Ensuring reliable access to safe drinking water remains a critical challenge in many regions, with system failures often linked to maintenance and governance shortcomings rather than technical design. There is a lack of robust, diagnostic methodologies to empirically quantify these operational failures and their drivers in field settings. ", "purpose and objectives": "This study aimed to develop and apply a novel diagnostic framework to evaluate the functional reliability of rural water treatment systems. The primary objective was to quantify system downtime and identify the principal technical and institutional factors contributing to operational failure. ", "methodology": "A quasi-experimental design was employed, comparing 32 intervention facilities receiving a new maintenance protocol against 32 matched control facilities. Reliability was measured as the proportion of scheduled operational time. Data from monthly technical audits and supervisory logs over an 18-month period were analysed using a difference-in-differences model: Y{it = \0 + \1 + \2 + \3 (\) +, with inference based on cluster-robust standard errors. ", "findings": "The intervention group demonstrated a statistically significant increase in operational reliability. The estimated treatment effect was 14. 7 percentage points (95% CI: 8. 2, 21. 2). Diagnostic analysis identified that failures of chlorination components and delays in spare parts procurement, linked to specific governance procedures, were the most prevalent causes of downtime in control systems. ", "conclusion": "The applied framework successfully isolated measurable effects of a maintenance intervention and diagnosed specific, recurring points of failure. System reliability is substantially influenced by governance-linked procurement processes and targeted component durability. ", "recommendations": "Water sector policies should integrate routine diagnostic reliability assessments. Procurement protocols for critical spare parts must be streamlined, and maintenance training should focus on high-failure-rate components identified by the diagnostic framework. ", "key words": "water treatment
Uwimana et al. (Sun,) studied this question.