Localised wastewater SARS-CoV-2 levels linked to COVID-19 cases: A long-term multisite study in England.

IF 8.2 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Science of the Total Environment Pub Date : 2025-01-25 Epub Date: 2025-01-14 DOI:10.1016/j.scitotenv.2025.178455
Natalia R Jones, Richard Elson, Matthew J Wade, Shannon McIntyre-Nolan, Andrew Woods, James Lewis, Diane Hatziioanou, Roberto Vivancos, Paul R Hunter, Iain R Lake
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Abstract

Wastewater-based surveillance (WBS) can monitor for the presence of human health pathogens in the population. During COVID-19, WBS was widely used to determine wastewater SARS-CoV-2 RNA concentration (concentrations) providing information on community COVID-19 cases (cases). However, studies examining the relationship between concentrations and cases tend to be localised or focussed on small-scale institutional settings. Few have examined this relationship in multiple settings, over long periods, with large sample numbers, nor attempted to quantify the relationship between concentrations and cases or detail how catchment characteristics affected these. This 18-month study (07/20-12/21) explored the correlation and quantitative relationship between concentrations and cases using censored regression. Our analysis used >94,000 wastewater samples collected from 452 diverse sampling sites (259 Sewage Treatment Works (STW) and 193 Sewer Network Sites (SNS)) covering ~65 % of the English population. Wastewater concentrations were linked to ~6 million diagnostically confirmed COVID-19 cases. High correlation coefficients were found between concentrations and cases (STW: median r = 0.66, IQR: 0.57-0.74; SNS: median r = 0.65, IQR: 0.54-0.74). The quantitative relationship (regression coefficient) between concentrations and cases was variable between catchments. Catchment and sampling characteristics (e.g. size of population and grab vs automated sampling) had significant but small effects on correlation and regression coefficients. During the last six months of the study correlation coefficients reduced and regression coefficients became highly variable between catchments. This coincided with a shift towards younger cases, a highly vaccinated population and rapid emergence of the variant Omicron. The English WBS programme was rapidly introduced at scale during COVID-19. Laboratory methods evolved and study catchments were highly diverse in size and characteristics. Despite this diversity, findings indicate that WBS provides an effective proxy for establishing COVID-19 dynamics across a wide variety of communities. While there is potential for predicting COVID-19 cases from wastewater concentration, this may be more effective at smaller scales.

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当地废水中SARS-CoV-2水平与COVID-19病例有关:英国的一项长期多地点研究
基于废水的监测(WBS)可以监测人群中人类健康病原体的存在。在COVID-19期间,WBS被广泛用于测定废水中SARS-CoV-2 RNA浓度(浓度),为社区COVID-19病例(病例)提供信息。然而,审查集中度和病例之间关系的研究往往是地方性的或集中于小规模机构环境。很少有人在长时间、大样本数的多种情况下检验这种关系,也没有人试图量化浓度与病例之间的关系,或详细说明集水区特征如何影响这些关系。这项为期18个月的研究(07/20-12/21)利用删节回归探讨了浓度与病例之间的相关性和定量关系。我们的分析使用了从452个不同采样点(259个污水处理厂(STW)和193个下水道网络站点(SNS))收集的bb94,000个废水样本,覆盖了约65%的英国人口。废水浓度与约600万诊断确诊的COVID-19病例有关。浓度与病例呈高相关(STW:中位数r = 0.66, IQR: 0.57-0.74;SNS:中位r = 0.65, IQR: 0.54-0.74)。浓度与病例之间的定量关系(回归系数)在不同的集水区是不同的。集水区和抽样特征(如人口规模和抓取量与自动抽样)对相关系数和回归系数有显著但较小的影响。在研究的最后六个月,流域之间的相关系数降低,回归系数变化很大。这与向年轻病例的转变,高度接种疫苗的人群和变异Omicron的迅速出现相吻合。英国WBS项目在2019冠状病毒病期间迅速大规模推出。实验室方法不断发展,研究的集水区在大小和特征上高度多样化。尽管存在这种多样性,但研究结果表明,WBS为在各种社区建立COVID-19动态提供了有效的代理。虽然有可能通过废水浓度预测COVID-19病例,但在较小规模上可能更有效。
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来源期刊
Science of the Total Environment
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.
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