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Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases

Here we analyze SARS-CoV-2 genome copies in Catalonia’s wastewater during the Omicron peak and develop a mathematical model to estimate the number of infections and the temporal relationship between reported and unreported cases. 1-liter samples from 16 wastewater treatment plants were collected and...

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Autores principales: Mattei, Mattia, Pintó, Rosa M., Guix, Susana, Bosch, Albert, Arenas, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265495/
https://www.ncbi.nlm.nih.gov/pubmed/37354838
http://dx.doi.org/10.1016/j.watres.2023.120223
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author Mattei, Mattia
Pintó, Rosa M.
Guix, Susana
Bosch, Albert
Arenas, Alex
author_facet Mattei, Mattia
Pintó, Rosa M.
Guix, Susana
Bosch, Albert
Arenas, Alex
author_sort Mattei, Mattia
collection PubMed
description Here we analyze SARS-CoV-2 genome copies in Catalonia’s wastewater during the Omicron peak and develop a mathematical model to estimate the number of infections and the temporal relationship between reported and unreported cases. 1-liter samples from 16 wastewater treatment plants were collected and used in a compartmental epidemiological model. The average correlation between genome copies and reported cases was 0.85, with an average delay of 8.8 days. The model estimated that 53% of the population was infected, compared to the 19% reported cases. The under-reporting was highest in November and December 2021. The maximum genome copies shed in feces by an infected individual was estimated to range from [Formula: see text] gc/g to [Formula: see text] gc/g. Our framework demonstrates the potential of wastewater data as a leading indicator for daily new infections, particularly in contexts with low detection rates. It also serves as a complementary tool for prevalence estimation and offers a general approach for integrating wastewater data into compartmental models.
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spelling pubmed-102654952023-06-14 Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases Mattei, Mattia Pintó, Rosa M. Guix, Susana Bosch, Albert Arenas, Alex Water Res Article Here we analyze SARS-CoV-2 genome copies in Catalonia’s wastewater during the Omicron peak and develop a mathematical model to estimate the number of infections and the temporal relationship between reported and unreported cases. 1-liter samples from 16 wastewater treatment plants were collected and used in a compartmental epidemiological model. The average correlation between genome copies and reported cases was 0.85, with an average delay of 8.8 days. The model estimated that 53% of the population was infected, compared to the 19% reported cases. The under-reporting was highest in November and December 2021. The maximum genome copies shed in feces by an infected individual was estimated to range from [Formula: see text] gc/g to [Formula: see text] gc/g. Our framework demonstrates the potential of wastewater data as a leading indicator for daily new infections, particularly in contexts with low detection rates. It also serves as a complementary tool for prevalence estimation and offers a general approach for integrating wastewater data into compartmental models. The Author(s). Published by Elsevier Ltd. 2023-08-15 2023-06-14 /pmc/articles/PMC10265495/ /pubmed/37354838 http://dx.doi.org/10.1016/j.watres.2023.120223 Text en © 2023 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Mattei, Mattia
Pintó, Rosa M.
Guix, Susana
Bosch, Albert
Arenas, Alex
Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases
title Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases
title_full Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases
title_fullStr Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases
title_full_unstemmed Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases
title_short Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases
title_sort analysis of sars-cov-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265495/
https://www.ncbi.nlm.nih.gov/pubmed/37354838
http://dx.doi.org/10.1016/j.watres.2023.120223
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