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Título: | Spatial and temporal distribution of SARS-CoV-2 diversity circulating in wastewater |
Autor: | Pérez-Cataluña, Alba CSIC ORCID; Chiner-Oms, Álvaro CSIC ORCID ; Cuevas Ferrando, Enric CSIC ORCID; Díaz-Reolid, Azahara CSIC; Falcó, Irene CSIC ORCID; Randazzo, Walter CSIC ORCID; Girón-Guzmán, Inés CSIC ORCID; Allende, Ana CSIC ORCID ; Bracho, María Alma; Comas, Iñaki CSIC ORCID ; Sánchez Moragas, Gloria CSIC ORCID | Palabras clave: | Genome sequencing SARS-CoV-2 Spike mutations Variants of concern Variants of interest Wastewater |
Fecha de publicación: | 1-mar-2022 | Editor: | Elsevier | Citación: | Water Research 211: 118007 (2022) | Resumen: | Wastewater-based epidemiology (WBE) has proven to be an effective tool for epidemiological surveillance of SARS-CoV-2 during the current COVID-19 pandemic. Furthermore, combining WBE together with high-throughput sequencing techniques can be useful for the analysis of SARS-CoV-2 viral diversity present in a given sample. The present study focuses on the genomic analysis of SARS-CoV-2 in 76 sewage samples collected during the three epidemiological waves that occurred in Spain from 14 wastewater treatment plants distributed throughout the country. The results obtained demonstrate that the metagenomic analysis of SARS-CoV-2 in wastewater allows the detection of mutations that define the B.1.1.7 lineage and the ability of the technique to anticipate the detection of certain mutations before they are detected in clinical samples. The study proves the usefulness of sewage sequencing to track Variants of Concern that can complement clinical testing to help in decision-making and in the analysis of the evolution of the pandemic. | Versión del editor: | https://doi.org/10.1016/j.watres.2021.118007 | URI: | http://hdl.handle.net/10261/264797 | DOI: | 10.1016/j.watres.2021.118007 | ISSN: | 0043-1354 |
Aparece en las colecciones: | (CEBAS) Artículos (IBV) Artículos (IATA) Artículos (PTI Salud Global) Colección Especial COVID-19 |
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Fichero | Descripción | Tamaño | Formato | |
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Water Res 2022-Perez.pdf | Artículo principal | 3,35 MB | Adobe PDF | Visualizar/Abrir |
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