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当前针对因休闲活动导致诺如病毒污染饮用水集水区的定量微生物风险评估 (QMRA) 的假设:更新。

Current assumptions for quantitative microbial risk assessment (QMRA) of Norovirus contamination of drinking water catchments due to recreational activities: an update.

机构信息

Water Futures and Water Research Australia, Sydney, Australia.

Harry Butler Institute, Murdoch University, Perth, Australia E-mail:

出版信息

J Water Health. 2022 Oct;20(10):1543-1557. doi: 10.2166/wh.2022.114.

Abstract

Contamination of drinking water from Norovirus (NoV) and other waterborne viruses is a major public health concern globally. Increasingly, quantitative microbial risk assessment (QMRA) is being used to assess the various risks from waterborne pathogens and evaluate control strategies. As urban populations grow and expand, there is increasing demand for recreational activities in drinking water catchments. QMRA relies on context-specific data to map out the pathways by which viruses can enter water and be transferred to drinking water consumers and identify risk factors and appropriate controls. This review examines the current evidence base and assumptions for QMRA analysis of NoV and other waterborne viral pathogens and recommends numerical values based on the most recent evidence to better understand the health risks associated with recreators in Australian drinking water sources; these are broadly applicable to all drinking water sources where recreational access is allowed. Key issues include the lack of an agreed upon data and dose-response models for human infectious NoV genotypes, faecal shedding by bathers, the extent of NoV infectivity and aggregation, resistance (secretor status) to NoV and the extent of secondary transmission.

摘要

饮用水中诺如病毒(NoV)和其他肠道病毒的污染是一个全球性的主要公共卫生问题。越来越多的定量微生物风险评估(QMRA)被用于评估水源性病原体的各种风险,并评估控制策略。随着城市人口的增长和扩张,对饮用水集水区的娱乐活动的需求也在不断增加。QMRA 依赖于特定于上下文的数据来描绘病毒进入水并传播到饮用水消费者的途径,并确定风险因素和适当的控制措施。本综述审查了当前用于 NoV 和其他肠道病毒病原体的 QMRA 分析的证据基础和假设,并建议基于最新证据的数值,以更好地了解与澳大利亚饮用水源中的娱乐使用者相关的健康风险;这些广泛适用于所有允许娱乐进入的饮用水源。关键问题包括缺乏针对人类感染性 NoV 基因型、游泳者粪便脱落、NoV 传染性和聚集性的程度、对 NoV 的抵抗力(分泌状态)以及二次传播的程度等方面的数据和剂量反应模型。

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