AWWA JAW57438

In the May 2002 issue of Journal AWWA, Stewart and co-workers summarized an investigation that addresses the potential health consequences related to consuming water from a reservoir at which body-contact recreation is permitted (Stewart et al, 2002). The investigation used a water quality model to estimate pathogen loading from recreationists and to calculate predicted pathogen concentrations at the outlet tower of the reservoir. Based on those data, risk to drinking water consumers was predicted. The authors reported that the annual risk of waterborne illness would increase three times above background, despite conventional water treatment before distribution as potable water. Although the authors used a powerful combination of modeling techniques for assimilating a wide range of disparate data, the substantial uncertainty associated with the model parameters most directly affecting risk is not articulated and/or analyzed in the findings of the investigation. The unspecified effect of uncertainty in this investigation casts doubts on the conclusions. These uncertainty issues, furthermore, suggest that the use of the Stewart et al document as guidance for policymakers and stakeholders who are examining issues associated with body-contact recreation and drinking water should be reexamined. The authors raised the fact that high levels of uncertainty may affect the analysis. They report: "The model was highly sensitive to parameters associated with pathogen loading" (page 87). Pathogen loading to the reservoir was assumed to occur in two ways: shedding of residual fecal material from recreationists' bodies upon contact with the water (shedding); and, accidental fecal releases (AFRs) and therefore was computed as a function of the number of infected individuals recreating in the reservoir. The percentages of recreationists assumed to be infected in each simulation varied by pathogen as follows: Cryptosporidium 0-5%, rotavirus 5-20%, Giardia 0-10%, and poliovirus 5-20%, and the frequency of an AFR was 0-0.2%. This discussion focuses on parameter estimates for Cryptosporidium prevalence, rotavirus prevalence, and AFRs as well as the risk management implications of those ranges. Includes 13 references.