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深圳解除严格的 COVID-19 策略后,通过污水监测揭示了快速广泛的 SARS-CoV-2 奥密克戎变异株感染浪潮。

Rapid and extensive SARS-CoV-2 Omicron variant infection wave revealed by wastewater surveillance in Shenzhen following the lifting of a strict COVID-19 strategy.

机构信息

Shenzhen Center for Disease Control and Prevention, Shenzhen, China.

Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China.

出版信息

Sci Total Environ. 2024 Nov 1;949:175235. doi: 10.1016/j.scitotenv.2024.175235. Epub 2024 Aug 3.

Abstract

Wastewater-based epidemiology (WBE) has emerged as a promising tool for monitoring the spread of COVID-19, as SARS-CoV-2 can be shed in the faeces of infected individuals, even in the absence of symptoms. This study aimed to optimize a prediction model for estimating COVID-19 infection rates based on SARS-CoV-2 RNA concentrations in wastewater, and reveal the infection trends and variant diversification in Shenzhen, China following the lifting of a strict COVID-19 strategy. Faecal samples (n = 4337) from 1204 SARS-CoV-2 infected individuals hospitalized in a designated hospital were analysed to obtain Omicron variant-specific faecal shedding dynamics. Wastewater samples from 6 wastewater treatment plants (WWTPs) and 9 pump stations, covering 3.55 million people, were monitored for SARS-CoV-2 RNA concentrations and variant abundance. We found that the viral load in wastewater increased rapidly in December 2022 in the two districts, demonstrating a sharp peak in COVID-19 infections in late-December 2022, mainly caused by Omicron subvariants BA.5.2.48 and BF.7.14. The prediction model, based on the mass balance between total viral load in wastewater and individual faecal viral shedding, revealed a surge in the cumulative infection rate from <0.1 % to over 70 % within three weeks after the strict COVID-19 strategy was lifted. Additionally, 39 cryptic SARS-CoV-2 variants were identified in wastewater, in addition to those detected through clinical surveillance. These findings demonstrate the effectiveness of WBE in providing comprehensive and efficient assessments of COVID-19 infection rates and identifying cryptic variants, highlighting its potential for monitoring emerging pathogens with faecal shedding.

摘要

基于污水的流行病学(WBE)已成为监测 COVID-19 传播的一种很有前途的工具,因为感染个体的粪便中可能会排出 SARS-CoV-2,即使没有症状也是如此。本研究旨在优化一种基于污水中 SARS-CoV-2 RNA 浓度预测 COVID-19 感染率的模型,并揭示中国深圳在解除严格的 COVID-19 策略后感染趋势和变异多样化。对 1204 名在指定医院住院的 SARS-CoV-2 感染个体的粪便样本(n=4337)进行了分析,以获得奥密克戎变异株特异性粪便脱落动力学。对 6 个污水处理厂(WWTP)和 9 个泵站的污水样本进行了监测,这些样本覆盖了 355 万人,以检测 SARS-CoV-2 RNA 浓度和变异丰度。我们发现,2022 年 12 月,这两个区的污水中病毒载量迅速增加,表明 2022 年 12 月下旬 COVID-19 感染急剧增加,主要由奥密克戎亚变异株 BA.5.2.48 和 BF.7.14 引起。基于污水中总病毒载量与个体粪便病毒脱落之间的质量平衡的预测模型显示,在严格的 COVID-19 策略解除后三周内,累计感染率从<0.1%飙升至 70%以上。此外,在污水中还发现了 39 种隐匿性 SARS-CoV-2 变异株,除了通过临床监测发现的变异株外。这些发现表明,WBE 在提供 COVID-19 感染率的全面和高效评估以及识别隐匿性变异株方面是有效的,突出了其在监测具有粪便脱落的新兴病原体方面的潜力。

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