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Quantitative microbial risk assessments (QMRAs) of contaminated drinking water usually assume the daily intake volume is consumed once a day. However, individuals could consume water at multiple time points over 1 day, so the objective was to determine if the number of consumption events per day impacted the risk of infection from Campylobacter jejuni during short-term contamination events. A probabilistic hydraulic and risk model was used to evaluate the impact of multiple consumption events as compared to one consumption event on the health risk from the intake of contaminated tap water. The fraction of the population that experiences greater than 10(-4) risk of infection per event at the median dose was 6.8% (5th-95th percentile: 6.5-7.2%) for one consumption event per day, 18.2% (5th-95th: 17.6-18.7%) for three consumption events per day, and 19.8% (5th-95th: 14.0-24.4%) when the number of consumption events varied around 3.49 events/day. While the daily intake volume remained consistent across scenarios, the results suggest that multiple consumption events per day increases the probability of infection during short-term, high level contamination events due to the increased coincidence of a consumption event during the contamination peak. Therefore, it will be important to accurately characterize this parameter in drinking water QMRAs.

Quantitative microbial risk assessment (QMRA) is increasingly applied to estimate drinking water safety. In QMRA the risk of infection is calculated from pathogen concentrations in drinking water, water consumption and dose response relations. Pathogen concentrations in drinking water are generally low and monitoring provides little information for QMRA. Therefore pathogen concentrations are monitored in the raw water and reduction of pathogens by treatment is modelled stochastically with Monte Carlo simulations. The method was tested in a case study with Campylobacter monitoring data of rapid sand filtration and ozonation processes. This study showed that the currently applied method did not predict the monitoring data used for validation. Consequently the risk of infection was over estimated by one order of magnitude. An improved method for model validation was developed. It combines non-parametric bootstrapping with statistical extrapolation to rare events. Evaluation of the treatment model was improved by presenting monitoring data and modelling results in CCDF graphs, which focus on the occurrence of rare events. Apart from calculating the yearly average risk of infection, the model results were presented in FN curves. This allowed for evaluation of both the distribution of risk and the uncertainty associated with the assessment.

The volume of cold tap water consumed is an essential element in quantitative microbial risk assessment. This paper presents a review of tap water consumption studies. Study designs were evaluated and statistical distributions were fitted to water consumption data from The Netherlands, Great Britain, Germany and Australia. We conclude that the diary is to be preferred for collecting water consumption data. If a diary is not feasible, a 24 h recall would be the best alternative, preferably repeated at least once. From the studies evaluated, the mean daily consumption varies from 0.10 L to 1.55 L. No conclusions could be drawn regarding the effects of season, age and gender on tap water consumption. Physical activity, yearly income and perceived health status were reported to influence water consumption. Comparison of the different statistical probability distribution functions of the datasets demonstrated that the Poisson distribution performed better than the lognormal distribution as suggested by Roseberry and Burmaster. For quantitative microbiological risk assessment (QMRA) it is recommended to use country-specific consumption data and statistical distributions, if available. If no country specific data are available we recommend to use the Australian distribution data from the Melbourne diary study (Poisson, lambda=3.49 glasses/d) as a conservative estimate.

Quantitative Microbiological Risk Assessment (QMRA) is increasingly being used to complement traditional verification of drinking water safety through the absence of indicator bacteria. However, the full benefit of QMRA is often not achieved because of a lack of appropriate data on the fate and behaviour of pathogens. In the UK, statutory monitoring for Cryptosporidium has provided a unique dataset of pathogens directly measured in large volumes of treated drinking water. Using this data a QMRA was performed to determine the benefits and limitations of such state-of-the-art monitoring for risk assessment. Estimates of the risk of infection at the 216 assessed treatment sites ranged from 10(-6.5) to 10(-2.5) person(-1) d(-1). In addition, Cryptosporidium monitoring data in source water was collected at eight treatment sites to determine how Cryptosporidium removal could be quantified for QMRA purposes. Cryptosporidium removal varied from 1.8 to 5.2 log units and appeared to be related to source water Cryptosporidium concentration. Application of general removal credits can either over- or underestimate Cryptosporidium removal by full-scale sedimentation and filtration. State-of-the-art pathogen monitoring can identify poorly performing systems, although it is ineffective to verify drinking water safety to the level of 10(-4) infections person(-1) yr(-1).