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在印度古吉拉特邦的一座省会城市,通过利用数字PCR对城市化的哨兵污水管网进行监测,实现对该邦新冠病毒奥密克戎毒株浪潮的早期预警。

Early warning of statewide COVID-19 Omicron wave by sentineled urbanized sewer network monitoring using digital PCR in a province capital city, of Gujarat, India.

作者信息

Kumar Manish, Joshi Madhvi, Prajapati Bhumika, Sirikanchana Kwanrawee, Mongkolsuk Skorn, Kumar Rakesh, Gallage Tharindu Pollwatta, Joshi Chaitanya

机构信息

Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand 248007, India; Escuela de Ingeniería y Ciencias, Technologico de Monterrey, Campus Monterey, Monterrey 64849, Nuevo Leon, Mexico.

Gujarat Biotechnology Research Centre, Gandhinagar, Gujarat 382011, India.

出版信息

Sci Total Environ. 2023 Dec 20;905:167060. doi: 10.1016/j.scitotenv.2023.167060. Epub 2023 Sep 12.

Abstract

Wastewater-based epidemiology (WBE) has been implemented globally. However, there remains confusion about the number and frequency of samples to be collected, as well as which types of treatment systems can provide reliable specific details about the virus prevalence in specific areas or communities, enabling prompt management and intervention measures. More research is necessary to fully comprehend the possibility of deploying sentinel locations in sewer networks in larger geographic areas. The present study introduces the first report on wastewater-based surveillance in Gandhinagar City using digital PCR (d-PCR) as a SARS-Cov-2 quantification tool, which describes the viral load from five pumping stations in Gandhinagar from October 2021 to March 2022. Raw wastewater samples (n = 119) were received and analyzed weekly to detect SARS-CoV-2 RNA, 109 of which were positive for N1 or N2 genes. The monthly variation analysis in viral genome copies depicted the highest concentrations in January 2022 and February 2022 (p < 0.05; Wilcoxon signed rank test) coincided with the Omicron wave, which contributed mainly from Vavol and Jaspur pumping stations. Cross-correlation analysis indicated that WBE from five stations in Gandhinagar, i.e., capital city sewer networks, provided two-week lead times to the citywide and statewide active cases (time-series cross-correlation function [CCF]; 0.666 and 0.648, respectively), mainly from individual contributions of the urbanized Kudasan and Vavol stations (CCF; 0.729 and 0.647, respectively). These findings suggest that sewer pumping stations in urbanized neighborhoods can be used as sentinel sites for statewide clinical surveillance and that WBE surveillance using digital PCR can be an efficient monitoring and management tool.

摘要

基于废水的流行病学(WBE)已在全球范围内实施。然而,对于样本采集的数量和频率,以及哪种类型的处理系统能够提供特定区域或社区病毒流行情况的可靠具体细节,从而实现及时的管理和干预措施,仍然存在困惑。有必要进行更多研究,以全面了解在更大地理区域的下水道网络中设置监测点的可能性。本研究介绍了关于甘地讷格尔市基于废水监测的首份报告,该报告使用数字PCR(d-PCR)作为严重急性呼吸综合征冠状病毒2(SARS-CoV-2)定量工具,描述了2021年10月至2022年3月甘地讷格尔市五个泵站的病毒载量。接收并每周分析原废水样本(n = 119)以检测SARS-CoV-2 RNA,其中109份样本的N1或N2基因呈阳性。病毒基因组拷贝数的月度变化分析显示,2022年1月和2022年2月浓度最高(p < 0.05;Wilcoxon符号秩检验),这与奥密克戎毒株流行期相符,主要来自瓦沃尔和贾斯布尔泵站。交叉相关性分析表明,甘地讷格尔市五个站点(即首都城市下水道网络)的基于废水的流行病学数据,比全市和全州的活跃病例提前两周(时间序列交叉相关性函数[CCF];分别为0.666和0.648),主要来自城市化程度较高的库达桑和瓦沃尔站点的个体贡献(CCF;分别为0.729和0.647)。这些发现表明,城市化社区的下水道泵站可作为全州临床监测的监测点,并且使用数字PCR进行基于废水的流行病学监测可以成为一种有效的监测和管理工具。

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