Reverse QMRA as a Decision Support Tool: Setting Acceptable Concentration Limits for Pseudomonas aeruginosa and Naegleria fowleri

Abstract

Opportunistic premise plumbing pathogens such as Pseudomonas aeruginosa and Naegleria fowleri are a growing concern in building water systems because of their potential risks to human health. The aim of this study was to determine the critical concentrations of P. aeruginosa and N. fowleri in water that are associated with meaningful public health risks. To determine these concentrations, a reverse quantitative microbial risk assessment (QMRA) was conducted. Environmental concentrations of P. aeruginosa and N. fowleri corresponding to the risk target of one micro-disability-adjusted life year (DALY) per person per year and 10−4 annual risks of illness were calculated for several applicable exposure scenarios. To calculate the concentration of P. aeruginosa, cleaning contact lenses with potentially contaminated tap water in the absence of an appropriate cleaning solution was considered. For N. fowleri, two exposure scenarios, recreational exposure (swimming) and nasal cleansing (via the use of a neti pot™ or similar device) were considered. The highest critical concentration for P. aeruginosa was found to be 33 CFU/L with a 95% confidence interval of (2.0, 118) for the drop exposure scenario using the 10−4 annual risk target. For N. fowleri, based on the DALY approach, critical concentrations were 0.000030 N. fowleri/L for swimming and 0.00000060 N. fowleri/L for neti pot™ use scenario. Considering heat inactivation, the critical concentration limits for P. aeruginosa using the DALY approach and the 10−4 annual risk target approach were found to be 0.55 CFU/L and 55 CFU/L, respectively. For N. fowleri, the 10−4 annual risk target approach resulted in 0.022 N. fowleri/L and the DALY approach resulted in 0.00000064 N. fowleri/L for the neti pot™ scenario. For P. aeruginosa, N50 (the median infective dose) and alpha (α) contributed the most and contact rates the least to the variability and uncertainty of the estimates for all the scenarios. For N. fowleri, N50 and contact rates contributed the most and α the least to the variability and uncertainty to calculate the concentrations for all the scenarios. The QMRA framework implemented in this research can be used to incorporate more information regarding opportunistic pathogens to inform management decisions, and to prioritize the best interventions regarding estimated reduction in infections caused by opportunistic pathogens.