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通过疫情高峰期的基于污水的流行病学监测 COVID-19 浪潮的时间变化:北卡罗来纳州夏洛特市为期六个月的研究。

Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: A six-month long study in Charlotte, North Carolina.

机构信息

Department of Civil and Environmental Engineering, University of North Carolina Charlotte, 9201 University City Boulevard, Charlotte, NC 28223, USA.

Institute of Marine Sciences, The University of North Carolina at Chapel Hill, Morehead City, NC 28557, USA.

出版信息

Sci Total Environ. 2022 Mar 25;814:152503. doi: 10.1016/j.scitotenv.2021.152503. Epub 2021 Dec 23.

Abstract

The global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus to be the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 10 to 10 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases when lagging 5 to 12 days (ρ = 0.52-0.92, p < 0.001-0.02). A major finding of this study is that RT-qPCR and RT-ddPCR generated SARS-CoV-2 data that was positively correlated (ρ = 0.569, p < 0.0001) and can be successfully used to monitor SARS-CoV-2 signals across the WWTP of different sizes and metropolitan service functions without significant anomalies.

摘要

在世界卫生组织宣布该病毒是导致 2019 年冠状病毒病(COVID-19)全球大流行的病原体后,SARS-CoV-2 的全球传播继续引起严重关注。鉴于受感染个体的粪便中会大量排出 SARS-CoV-2,因此监测废水是评估社区流行情况的有用工具,无论他们是否无症状或有症状。使用废水流行病学(WBE)方法的一部分工具,并结合分子分析,废水监测成为评估趋势和量化特定社区、市或服务区域 COVID-19 感染规模和动态的关键信息。本研究使用实时定量 PCR(RT-qPCR)和实时数字 PCR(RT-ddPCR)平台,调查了北卡罗来纳州夏洛特地区四个市政污水处理厂(WWTP)的六个月进水 SARS-CoV-2 RNA 定量。进水废水分析了核衣壳(N)基因 N1 和 N2。RT-qPCR 和 RT-ddPCR 均能很好地检测和定量 N1 靶标中的 SARS-CoV-2,而对于 N2 靶标,RT-ddPCR 更灵敏。所有四个工厂的 SARS-CoV-2 浓度范围为 10 到 10 拷贝/L。当滞后 5 到 12 天时,RT-qPCR 和 RT-ddPCR 均显示 SARS-CoV-2 浓度与临床报告的 COVID-19 病例的 7 天滚动平均值之间存在显著正相关(ρ=0.52-0.92,p<0.001-0.02)。本研究的一个主要发现是,RT-qPCR 和 RT-ddPCR 生成的 SARS-CoV-2 数据呈正相关(ρ=0.569,p<0.0001),并且可以成功用于监测不同规模和大都市服务功能的 WWTP 中的 SARS-CoV-2 信号,而没有明显异常。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/261a/8697423/9955ec0cab04/ga1_lrg.jpg

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