Pathogen monitoring offers questionable protection against drinking-water risks: a QMRA (Quantitative Microbial Risk Analysis) approach to assess management strategies

Abstract

Risk mitigation provided by human monitoring and control over a water supply system has been consistently overlooked when estimating pathogen exposure to consumers. The Systems-Actions-Management (SAM) framework lends itself neatly to Quantitative Microbial Risk Assessment (QMRA) as one way to establish this link. The general premise is that an organisational protocol will influence how a human controller behaves, in turn influencing the system performance. For illustrative purposes, the framework was applied to a hypothetical water supply system to quantify the risk reduction offered by routine Cryptosporidium monitoring and the response to oocyst 'detects'. Our findings suggest that infrequent direct pathogen monitoring may provide a negligible risk barrier. The practice of sampling treated water to verify microbiological integrity is also dubious: oocyst densities were largely under-estimated, in part due to the spatial dispersion of oocysts in the waterbody, but predominantly from imperfect detection methods. The development of 'event-driven' monitoring schemes with barrier performance-based treatment verification methods, as promoted in new guidelines, is supported as a pressing issue to reduce the likelihood of undetected pathogen passage through a treatment plant.

The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems

“…Secondly, in environmental aquatic ecosystems, interactions between abiotic and biotic factors both for regular and event-based dynamics can be studied with considerable detail using this approach (Pronk et al, 2006; Stadler et al, 2010; Butscher et al, 2011). Thirdly, automated measuring of microbial parameters renders event monitoring for quantitative microbial risk assessment considerably much more feasible (Signor and Ashbolt, 2006). Finally, a large variety of laboratory-based research can benefit from high temporal resolution and automation.…”

Evaluating Monitoring Strategies to Detect Precipitation-Induced Microbial Contamination Events in Karstic Springs Used for Drinking Water

“…This can result from natural fluctuations in raw water sources (e.g., precipitation events, snowmelt) as well as operational changes (e.g., filter backwashing, intermittent flow) during treatment (Stevenson, 1997 ; Pronk et al, 2006 ; Madrid and Zayas, 2007 ; Stadler et al, 2008 ; Bakker et al, 2013 ). Short-term dynamics and especially peak concentrations strongly influence water quality—and the infection risk in the case of pathogens—especially in raw water but also in treated water (Gauthier et al, 2001 ; Kistemann et al, 2002 ; Vreeburg et al, 2004 ; Farnleitner et al, 2005 ; Signor and Ashbolt, 2006 ; Astrom et al, 2007 ; Pronk et al, 2007 ; Stadler et al, 2008 ). Furthermore, many small water utilities using spring water or groundwater have either no or very limited water treatment in place and are thus directly exposed to changes and associated risks in raw water quality.…”

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

“…In this context, the short-term dynamics (hours-to-weeks) of natural and especially operational events have so far mainly been looked at with respect to hydrology and abiotic water quality, but only scarcely from the perspective of microbial water quality5252627. Monitoring the microbial quality of extracted groundwater for drinking water is typically confined to the conventional approach of infrequent grab sampling and conventional cultivation-based detection methodology28. The costs and labor-intensive nature of the latter hinder the investigation of short-term dynamics at adequate temporal resolution.…”