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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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Detalles Bibliográficos
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
Descripción
Sumario: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.