Vol. 1 No. 1 (2020)

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A Multilevel Regression Analysis of Water Treatment System Performance and Risk Reduction in Tanzania

Grace Mrema, Department of Mechanical Engineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha Neema Mwambene, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam Juma Kavishe, Department of Mechanical Engineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha Abasi Mwakyembe, Department of Civil Engineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha
DOI: 10.5281/zenodo.18973102
Published: March 21, 2020

Abstract

{ "background": "Inadequate access to safe drinking water remains a critical public health challenge in many regions. The performance of centralised water treatment systems is a key determinant of health risk reduction, yet comprehensive, system-level evaluations linking technical performance to quantified risk are limited.", "purpose and objectives": "This study aimed to develop and apply a multilevel regression framework to evaluate the technical performance of urban water treatment systems and quantify its association with microbial risk reduction.", "methodology": "We conducted a cross-sectional field study of centralised treatment facilities. Performance data (turbidity, chlorine residual) and microbial water quality indicators (E. coli, total coliforms) were collected at multiple points within each system. A two-level hierarchical model was fitted, with sampling points nested within facilities. The core model was: $\\log(\\text{Risk}\\text{ij}) = \\beta{0} + \\beta{1}X\\text{ij} + u\\text{j} + e\\text{ij}$, where $u\\text{j} \\sim N(0, \\sigma^2u)$. Inference was based on robust standard errors.", "findings": "A one-unit increase in final treated water turbidity (NTU) was associated with a 17.3% increase in estimated microbial risk (95% CI: 9.8% to 25.4%). Substantial variation in performance was attributable to facility-level management factors, accounting for approximately 35% of the total variance in risk outcomes.", "conclusion": "The technical performance of treatment, particularly final turbidity control, is a statistically significant and modifiable predictor of microbial risk. Facility-level management practices are a critical source of performance variation.", "recommendations": "Routine monitoring should prioritise final turbidity as a key performance indicator. Regulatory frameworks should mandate and audit facility-specific performance management plans to reduce inter-facility variability.", "key words": "water safety, hierarchical model, turbidity,

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How to Cite

Grace Mrema, Neema Mwambene, Juma Kavishe, Abasi Mwakyembe (2020). A Multilevel Regression Analysis of Water Treatment System Performance and Risk Reduction in Tanzania. African Civil Engineering Journal, Vol. 1 No. 1 (2020). https://doi.org/10.5281/zenodo.18973102

Keywords

Water treatmentMultilevel modellingSub-Saharan AfricaPublic health engineeringRisk assessmentInfrastructure performanceDrinking water quality

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Vol. 1 No. 1 (2020)
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