Sustainability Cluster, School of Advanced Engineering, UPES, Dehradun, Uttarakhand, 248007, India; Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Campus Monterey, Monterrey, 64849, Nuevo Leon, Mexico.
Gujarat Biotechnology Research Centre, Gandhinagar, Gujarat, 248007, India.
Environ Pollut. 2023 Nov 15;337:122471. doi: 10.1016/j.envpol.2023.122471. Epub 2023 Aug 29.
In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 10 (October 2020) to 1.4 x 10 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.
在这项工作中,我们展示了一项在印度艾哈迈达巴德进行的为期八个月的基于废水的流行病学(WBE)纵向研究。在成功遏制了 COVID-19 的第一波疫情之后,于 2020 年 9 月引入了废水监测,以预测第二波疫情期间的感染反弹。该研究旨在阐明在八个月的时间内,从废水中检测到的 SARS-CoV-2 RNA 数据的每周变化,以预测 COVID-19 的情况,并确定艾哈迈达巴德的热点地区。共分析了 287 个 SARS-CoV-2 RNA 样本,使用 RT-PCR 进行了分析,并应用 Spearman 秩相关来描述 WBE 的预警潜力。在 2020 年 9 月至 2021 年 4 月期间,阳性废水进水样本数量的增加与确诊临床病例数量的增加相关。它还清楚地证明了在艾哈迈达巴德早期发现 COVID-19 的第二波疫情(2021 年 3 月)。在总共 287 个样本中,有 258 个至少有三个 SARS-CoV-2 基因(N、ORF-1 ab 和 S)中的两个呈阳性。与 2020 年 9 月相比,10 月所有三个基因拷贝的月变化均呈显著下降趋势,随后 2020 年 11 月急剧增加。2021 年 3 月和 4 月,基因拷贝数也出现了类似的增加,这将是 COVID-19 第二波疫情的一个指标。与临床确诊病例相比,基因浓度的变化观察到了 1-2 周的提前期。测量的废水 ORF-1 ab 基因拷贝数范围为 6.1 x 10(2020 年 10 月)至 1.4 x 10(2020 年 11 月)拷贝/mL,废水基因水平通常会提前一到两周导致确诊病例。该研究强调了 WBE 作为一种监测工具的价值,可用于预测大流行期间的波次,识别城市内的局部疾病热点,并指导快速管理干预。