{ "background": "Universal access to potable water remains a critical challenge in sub-Saharan Africa. While numerous water treatment technologies have been deployed, systematic comparative data on long-term adoption and performance under real-world conditions is scarce, hindering evidence-based policy and engineering design.", "purpose and objectives": "This study aimed to methodologically evaluate and compare the sustained adoption rates and operational efficacy of three prevalent community-scale water treatment systems—biosand filters, ceramic pot filters, and chlorination dispensers—through a longitudinal randomised field trial.", "methodology": "A cluster-randomised controlled trial was implemented across 120 rural communities. Adoption was modelled using a mixed-effects logistic regression: $\\logit(p{ij}) = \\beta0 + \\beta1 T{ij} + \\beta2 X{ij} + uj$, where $p{ij}$ is the probability of adoption for household $i$ in cluster $j$, $T{ij}$ represents treatment technology, $X{ij}$ a vector of household covariates, and $u_j$ a cluster random effect. Primary metrics included verified usage rates and functional status, assessed via quarterly surveys and technical audits.", "findings": "Ceramic pot filters demonstrated a significantly higher sustained adoption rate (68%, 95% CI [62, 74]) compared to biosand filters (52%, CI [46, 58]) and chlorination (41%, CI [35, 47]). The odds ratio for adoption of ceramic filters versus chlorination was 3.05 (p<0.001). Key determinants of adoption included maintenance accessibility and perceived taste improvement.", "conclusion": "The choice of water treatment technology significantly influences long-term community adoption, with household-level ceramic filters showing superior sustained uptake under the trial conditions. Technological reliability and user experience are as critical as initial efficacy.", "recommendations": "Engineering design and implementation policy should prioritise technologies with low recurrent maintenance burdens and positive user sensory feedback. Programmes should integrate robust, longitudinal adoption