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2023 年期间埃塞俄比亚基于污水的 SARS-CoV-2 纵向监测。

Longitudinal wastewater-based surveillance of SARS-CoV-2 during 2023 in Ethiopia.

机构信息

Ethiopian Public Health Institute (EPHI), Addis Ababa, Ethiopia.

Global Health, The Association of Public Health Laboratories (APHL), Addis Ababa, Ethiopia.

出版信息

Front Public Health. 2024 Oct 7;12:1394798. doi: 10.3389/fpubh.2024.1394798. eCollection 2024.

Abstract

INTRODUCTION

Although wastewater-based epidemiology (WBE) successfully functioned as a tool for monitoring the coronavirus disease 2019 (COVID-19) pandemic globally, relatively little is known about its utility in low-income countries. This study aimed to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater, estimate the number of infected individuals in the catchment areas, and correlate the results with the clinically reported COVID-19 cases in Addis Ababa, Ethiopia.

METHODS

A total of 323 influent and 33 effluent wastewater samples were collected from three Wastewater Treatment Plants (WWTPs) using a 24-h composite Moore swab sampling method from February to November 2023. The virus was captured using Ceres Nanotrap® Enhancement Reagent 2 and Nanotrap® Microbiome A Particles, and then nucleic acids were extracted using the Qiagen QIAamp Viral RNA Mini Kit. The ThermoFisher TaqPath™ COVID-19 kit was applied to perform real-time reverse transcriptase polymerase chain reaction (qRT-PCR) to quantify the SARS-CoV-2 RNA. Wastewater viral concentrations were normalized using flow rate and number of people served. In the sampling period, spearman correlation was used to compare the SARS-CoV-2 target gene concentration to the reported COVID-19 cases. The numbers of infected individuals under each treatment plant were calculated considering the target genes' concentration, the flow rate of treatment plants, a gram of feces per person-day, and RNA copies per gram of feces.

RESULTS

SARS-CoV-2 was detected in 94% of untreated wastewater samples. All effluent wastewater samples ( = 22) from the upflow anaerobic sludge blanket (UASB) reactor and membrane bioreactor (MBR) technology were SARS-COV-2 RNA negative. In contrast, two out of 11 effluents from Waste Stabilization Pond were found positive. Positive correlations were observed between the weekly average SARS-CoV-2 concentration and the cumulative weekly reported COVID-19 cases in Addis Ababa. The estimated number of infected people in the Kality Treatment catchment area was 330 times the number of COVID-19 cases reported during the study period in Addis Ababa.

DISCUSSION

This study revealed that SARS-CoV-2 was circulating in the community and confirmed previous reports of more asymptomatic COVID-19 cases in Ethiopia. Additionally, this study provides further evidence of the importance of wastewater-based surveillance in general to monitor infectious diseases in low-income settings.

CONCLUSION

Wastewater-based surveillance of SARS-CoV-2 can be a useful method for tracking the increment of COVID-19 cases before it spreads widely throughout the community.

摘要

简介

尽管基于废水的流行病学(WBE)成功地作为一种监测全球 2019 年冠状病毒病(COVID-19)大流行的工具,但对于其在低收入国家的应用知之甚少。本研究旨在定量检测废水中的严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)RNA,估算集水区内感染个体的数量,并将结果与埃塞俄比亚亚的斯亚贝巴临床报告的 COVID-19 病例进行相关性分析。

方法

本研究于 2023 年 2 月至 11 月期间,采用 24 小时复合 Moore 拭子采样方法,从三个污水处理厂(WWTP)共采集了 323 份进水和 33 份出水废水样本。使用 Ceres Nanotrap® Enhancement Reagent 2 和 Nanotrap® Microbiome A Particles 捕获病毒,然后使用 Qiagen QIAamp Viral RNA Mini Kit 提取核酸。应用 ThermoFisher TaqPath™ COVID-19 试剂盒进行实时逆转录聚合酶链反应(qRT-PCR)以定量 SARS-CoV-2 RNA。通过流量和服务人数对废水病毒浓度进行归一化。在采样期间,采用 Spearman 相关性分析比较 SARS-CoV-2 靶基因浓度与报告的 COVID-19 病例。考虑到目标基因浓度、处理厂流量、每人每天粪便量和粪便中 RNA 拷贝数,计算每个处理厂下感染个体的数量。

结果

未经处理的废水样本中 94%检测到 SARS-CoV-2。上流式厌氧污泥床(UASB)反应器和膜生物反应器(MBR)技术的所有出水废水样本( = 22)均为 SARS-COV-2 RNA 阴性。相比之下,有两个来自污水稳定塘的出水样本呈阳性。每周平均 SARS-CoV-2 浓度与亚的斯亚贝巴每周累计报告 COVID-19 病例呈正相关。估计在 Kality 处理集水区感染的人数是该研究期间报告的亚的斯亚贝巴 COVID-19 病例的 330 倍。

讨论

本研究表明 SARS-CoV-2 在社区中传播,并证实了之前在埃塞俄比亚报告的更多无症状 COVID-19 病例。此外,本研究进一步证明了在低收入环境中,基于废水的监测对监测传染病的重要性。

结论

基于废水的 SARS-CoV-2 监测可以作为一种有用的方法,在社区广泛传播之前跟踪 COVID-19 病例的增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61c3/11491403/63e0c53231a6/fpubh-12-1394798-g001.jpg

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