{ "background": "Universal access to safe drinking water remains a critical challenge in sub-Saharan Africa. While numerous water treatment systems have been deployed, rigorous evidence on their sustained adoption and technical performance post-installation is limited, hindering effective policy and engineering interventions.", "purpose and objectives": "This study aimed to quantify the long-term adoption rates of community-scale water treatment systems and to identify the key engineering and contextual factors determining their operational performance and sustainability.", "methodology": "A quasi-experimental design was employed, comparing villages with new treatment systems against matched control villages without. Performance data were collected via sensor logs and technician surveys. Adoption was modelled using a logistic regression: $\\logit(p{i}) = \\beta0 + \\beta1 X{1i} + \\beta2 Z{i} + \\epsilon{i}$, where $pi$ is the probability of consistent use, $X$ represents technical variables, and $Z$ captures socio-economic factors. Inference was based on cluster-robust standard errors.", "findings": "The estimated adoption rate for systems under evaluation was 58% (95% CI: 52% to 64%). System performance was strongly associated with the availability of locally trained maintenance personnel; villages with such support were 3.2 times more likely to sustain operations. Water quality compliance was 40% higher in systems with routine monitoring protocols.", "conclusion": "Sustained adoption of water treatment technology is substantially below installation targets. Long-term functionality is not guaranteed by initial technical specifications alone but is critically dependent on embedded operational support structures.", "recommendations": "Engineering projects must integrate dedicated, locally-resourced maintenance and monitoring programmes from the design phase. National policies should shift focus from installation metrics to performance-based funding, tied to verified operational outcomes.", "key words": "water treatment, adoption, sustainability, quasi-experimental, maintenance, sub-Saharan Africa", "contribution statement": "This paper provides a novel longitudinal dataset and a robust quasi