实施以废水为基础的流行病学预测工具的挑战：以SARS-CoV-2为例

IF 8 1区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES

Science of the Total Environment Pub Date : 2025-05-06 DOI:10.1016/j.scitotenv.2025.179593

Dimosthenis Chochlakis , Georgios Tzedakis , Areti Kokkinomagoula , Eleftheria Tzamali , Artemisia Ntoula , Maria Malliarou , Evaggelia Intze , Anastasia Koutsolioutsou , Christina Kotsifaki , Despina Kalisperi , Evangelos Dolapsakis , Krystalia Sifakaki , Emmanouil G. Spanakis , Vangelis Sakkalis , Anna Psaroulaki

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引用次数: 0

摘要

基于废水的流行病学（WBE）已被确定为监测和预测社区中SARS-CoV-2模式的工具。有几个因素可能导致病毒遗传物质测量的日常变化。从希腊克里特岛的两个主要污水处理厂系统地收集了废水样本。检测理化因素，RT-real - time PCR检测病毒浓度，并将结果归一化。讨论了限制措施、降雨和物化剂等因素的影响。应用统计学和机器学习（ML）来预测人类病例。共分析了781份样品。RNA浓度在封锁期间降低，并受到雨水的影响。pH值和总固体浓度的波动与病毒载量的变化有关。电导率主要与氯离子有关。在伊拉克利翁，废水病毒载量比人类病例平均早三天。交叉相关估计在中国没有同样的效果。据ML称，与第一波相比，污水RNA测量与报告病例的比例有所下降，这是由于不同的变异、气候参数、检测率和与寻求医疗保健有关的行为。所建立的模型显示，记录的病例与预测的病例非常接近。总固形物、pH、电导率、雨水和抑制剂等参数对病毒RNA的回收率有显著影响。废水中的病毒载量与人类病例之间的关系并不直接。ML的应用可能会填补一些空白，但不是所有的空白。现有模型不能直接适用于不同的污水处理厂或国家。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Challenges on the implementation of wastewater-based epidemiology as a prediction tool: the paradigm of SARS-CoV-2

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Challenges on the implementation of wastewater-based epidemiology as a prediction tool: the paradigm of SARS-CoV-2

Wastewater Based Epidemiology (WBE) has been identified as a tool for monitoring and predicting patterns of SARS-CoV-2 in communities. Several factors may lead to a day-to-day variation in the measurement of viral genetic material.

Wastewater samples are systematically collected from the two major wastewater treatment plants in Crete, Greece. Physico-chemical factors were tested, viral concentration was determined by RT-real time PCR and the results were normalized. The influence of restriction measures, rain and physico-chemical agents was addressed. Statistics together with machine learning (ML) were applied to predict human cases.

781 samples were analyzed. RNA concentration was reduced during lockdown and was impacted by rain. Fluctuations in pH and total solids' concentrations were associated with changes in viral load. Conductivity was mainly related to chloride ions. In Heraklion, wastewater viral load preceded human cases by three days on average. Cross- correlation estimates did not perform likewise in Chania. According to ML, the ratio of sewage RNA measurements to reported cases decreased in comparison to the first wave, due to different variants, climatological parameters, testing rate and behaviors related to seeking healthcare. The model developed showed a close approximation between recorded and predicted cases.

Parameters such as total solids, pH, conductivity, rain and inhibitors can significantly impact the recovery of viral RNA. The correlation between viral load in wastewater and human cases is not straightforward. The application of ML may fill some but not every gap. Existing models cannot be directly applied to different Wastewater Treatment Plants or countries.

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来源期刊

Science of the Total Environment 环境科学-环境科学

CiteScore

17.60

自引率

10.20%

发文量

8726

审稿时长

2.4 months

期刊介绍： The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere. The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.