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阿联酋污水 SARS-CoV-2 监测的长期研究。

Long-term study on wastewater SARS-CoV-2 surveillance across United Arab Emirates.

机构信息

Center for Membranes and Advanced Water Technology (CMAT), Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.

Department of Biology, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates.

出版信息

Sci Total Environ. 2023 Aug 20;887:163785. doi: 10.1016/j.scitotenv.2023.163785. Epub 2023 May 4.

DOI:10.1016/j.scitotenv.2023.163785
PMID:37149161
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10156646/
Abstract

Wastewater-based epidemiology (WBE) demonstrates an efficient tool to monitor and predict SARS-CoV-2 community distribution. Many countries across the world have adopted the technique, however, most of these studies were conducted for a short duration with a limited sampling size. In this study, long-term reliability and quantification of wastewater SARS-CoV-2 surveillance is reported via analyzing 16,858 samples collected from 453 different locations across the United Arab Emirates (UAE) from May 2020 to June 2022. The collected composite samples were first incubated at 60 °C followed by filtration, concentration, and then RNA extraction using commercially available kits. The extracted RNA was then analyzed by one-step RT-qPCR and RT-ddPCR, and the data was compared to the reported clinical cases. The average positivity rate in the wastewater samples was found to be 60.61 % (8.41-96.77 %), however, the positivity rate obtained from the RT-ddPCR was significantly higher than the RT-qPCR suggesting higher sensitivity of RT-ddPCR. Time-lagged correlation analysis indicated an increase in positive cases in the wastewater samples when the clinical positive cases declined suggesting that wastewater data are highly affected by the unreported asymptomatic, pre-symptomatic and recovering individuals. The weekly SARS-CoV-2 viral count in the wastewater samples are positively correlated with the diagnosed new clinical cases throughout the studied period and the studied locations. Viral count in wastewater peaked approximately one to two weeks prior to the peaks appearing in active clinical cases indicating that wastewater viral concentrations are effective in predicting clinical cases. Overall, this study further confirms the long-term sensitivity and robust approach of WBE to detect trends in SARS-CoV-2 spread and helps contribute to pandemic management.

摘要

污水流行病学(WBE)展示了一种监测和预测 SARS-CoV-2 社区分布的有效工具。世界上许多国家都采用了该技术,但这些研究大多持续时间短,采样规模有限。在这项研究中,通过分析 2020 年 5 月至 2022 年 6 月期间从阿联酋 453 个不同地点采集的 16858 个样本,报告了污水中 SARS-CoV-2 监测的长期可靠性和定量结果。收集的复合样本首先在 60°C 下孵育,然后过滤、浓缩,最后使用市售试剂盒提取 RNA。然后使用一步法 RT-qPCR 和 RT-ddPCR 分析提取的 RNA,并将数据与报告的临床病例进行比较。发现污水样本的平均阳性率为 60.61%(8.41-96.77%),但 RT-ddPCR 获得的阳性率明显高于 RT-qPCR,表明 RT-ddPCR 的灵敏度更高。时间滞后相关性分析表明,当临床阳性病例减少时,污水样本中的阳性病例增加,表明污水数据受到未报告的无症状、症状前和康复个体的高度影响。整个研究期间和研究地点的污水样本中 SARS-CoV-2 病毒载量与诊断的新临床病例呈正相关。污水中的病毒载量在活跃临床病例出现峰值前约 1 至 2 周达到峰值,表明污水病毒浓度可有效预测临床病例。总体而言,这项研究进一步证实了 WBE 长期监测 SARS-CoV-2 传播趋势的敏感性和稳健性方法,并有助于大流行管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/983b440553f5/gr7_lrg.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/983b440553f5/gr7_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/748fcd752865/ga1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/c504deffe34b/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/d99fe4baa197/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/8bcca1ea5f12/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/3382b8a871c4/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/1423a064f6d8/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/fb1f482e0136/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da5/10156646/983b440553f5/gr7_lrg.jpg

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