Water consumption in the United States has decreased in recent decades due to improved water efficiency and adoption of water conservation practices. However, plumbing design guidance has not been updated to reflect this change, resulting in increased hydraulic retention time, disinfectant decay, and the proliferation of opportunistic premise plumbing pathogens (OPPPs) such as Legionella pneumophila. Time spent in premise plumbing systems has been shown to impact water quality through such mechanisms as the loss of residual disinfectant, leaching of pipe materials, biofilm formation, and increased concentrations of opportunistic pathogens such as Legionella spp.Quantitative Microbial Risk Assessment (QMRA) is a tool used to evaluate human health risks, and has been used to assess risks associated with Legionella. However, these assessments require data regarding the concentration of Legionella in water. Due to the ubiquity of Legionella in plumbing systems, their growth in biofilms, and the sporadic nature of biofilm detachment, Legionella concentrations are poorly understood, thus limiting the utility of QMRA in this instance. Factors which influence the prevalence of Legionella have been studied at the bench scale, but never in a full-scale building water system. The work presented herein takes a risk factor approach in exploring how to better monitor or predict concentrations of Legionella spp. This dissertation presents research to help better understand factors which best predict Legionella spp. Research objectives of this work were to: (1) identify variables which most effectively predict Legionella spp. concentrations using multiple relevant statistical methods, (2) determine the time water spends stored in building plumbing prior to use using a novel model, and (3) determine whether compliance with common temperature guidelines to limit Legionella proliferation has a significant influence on Legionella spp. concentrations. This research employs a rich data set from a full-scale home, equipped with flowmeters and temperature sensors to assess water conditions. Analytical samples were also collected to determine common water quality variables, as well as enumeration of Legionella spp. Multiple statistical analyses, including Spearman’s rank correlation, principal component analysis, generalized linear modeling, and a Bayesian variable selection technique were used to investigate variable relationships and to evaluate the value of model results in predicting Legionella spp. concentrations. Principal component analysis suggests that water age and biofilm detachment are the primary drivers of changes observed in water quality, accounting for 53% of the total variance in the data. General linear modeling revealed that heterotrophic plate count, total organic carbon, total cell count, maxTSL and meanTSL (metrics describing water use), and modeled water age were each significant predictors of Legionella spp. concentrations at the p < 0.05 level. Bayesian variable selection indicated that the 95th percentile of water age and maxTSL were most predictive of Legionella spp. concentrations. Results from the water age model were evaluated, indicating that modeled water age is indeed a statistically significant (p < 0.05) predictor of Legionella spp. Compliance with common temperature guidelines was found to be significantly correlated (ρ = 0.22, p < 0.001) to Legionella spp Results of this research indicate that water quality and water use have significant implications to Legionella occurrence. These results provide a framework to investigate Legionella spp. using a limited set of variables which are more commonly and cheaply measured than direct measurement, which could encourage more widespread monitoring for Legionella and ultimately reduce the incidence of illness. While water age remains poorly understood, these results show that water age is a critical factor in determining Legionella spp. prevalence. This knowledge should be applied to plumbing design and maintenance to limit water age and thereby Legionella spp. concentrations. Statistical significance between compliance with commonly cited temperature guidelines and Legionella spp. concentrations indicate that these guidelines do provide some level of control, and should be considering in design and operation of premise plumbing systems.
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