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Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective

Lookup NU author(s): Professor David GrahamORCiD

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Abstract

© 2023In 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 102 (October 2020) to 1.4 x 104 (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.


Publication metadata

Author(s): Kumar M, Joshi M, Jiang G, Yamada R, Honda R, Srivastava V, Mahlknecht J, Barcelo D, Chidambram S, Khursheed A, Graham DW, Goswami R, Kuroda K, Tiwari A, Joshi C

Publication type: Article

Publication status: Published

Journal: Environmental Pollution

Year: 2023

Volume: 337

Print publication date: 15/11/2023

Online publication date: 29/08/2023

Acceptance date: 26/08/2023

ISSN (print): 0269-7491

ISSN (electronic): 1873-6424

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.envpol.2023.122471

DOI: 10.1016/j.envpol.2023.122471

PubMed id: 37652227


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