在2002年5月的AWWA杂志上， 斯图尔特及其同事总结了一项调查 解决与健康相关的潜在健康后果 从身体接触的蓄水池喝水 允许娱乐（Stewart等人，2002年）。调查 使用水质模型来估计病原体 消遣者的负载和计算预测值 水库出口塔的病原体浓度。 根据这些数据，饮用水消费者面临的风险 这是预言。作者报告说，每年 水传播疾病的风险将增加三倍以上 背景:尽管之前有常规的水处理 作为饮用水进行分配。 尽管作者使用了一个强大的 同化各种不同数据的建模技术 数据，与 最直接影响风险的模型参数不是 在调查结果中阐明和/或分析。 本次调查中不确定性的未明确影响 对结论表示怀疑。此外，这些不确定性问题表明，使用Stewart等人的文件作为政策制定者和利益相关者的指导，他们正在研究与身体健康相关的问题- 应重新检查接触娱乐和饮用水。 作者提出了一个事实，即高度的不确定性可能会影响分析。他们报道:“模型 对相关参数高度敏感 病原体加载”（第87页）。病原体加载到 假设储层以两种方式出现:脱落 从游憩者身上残留的排泄物 与水接触（脱落）；还有，意外粪便 释放（AFR），因此作为一个函数进行计算 在该地区重新感染的感染者人数 水库 娱乐者的百分比假定为 每个模拟中的感染情况因病原体而异，如下所示: 隐孢子虫0-5%，轮状病毒5-20%，贾第虫 0-10%，脊髓灰质炎病毒5-20%，以及 AFR为0-0.2%。本讨论的重点是参数 隐孢子虫流行率、轮状病毒的估计 患病率、AFRs以及风险管理 这些范围的影响。 包括13篇参考文献。

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.