Autor según el artículo: Mattei, Mattia; Pinto, Rosa M; Guix, Susana; Bosch, Albert; Arenas, Alex
Departamento: Enginyeria Informàtica i Matemàtiques
Autor/es de la URV: Arenas Moreno, Alejandro / Mattei, Mattia
Código de proyecto: Grant agreement No. 945413
Palabras clave: Wastewater Sars-cov-2 Rna, viral Prevalence Prediction bias Model Mathematical modeling Humans Diagnostic tests, routine Covid-19 testing Covid-19 Bias sars-cov-2 prediction bias mathematical modeling
Resumen: 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 1.4×108 gc/g to 4.4×108 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.
Áreas temáticas: Water science and technology Water resources Waste management and disposal Saúde coletiva Química Pollution Medicina ii Materiais Interdisciplinar Geociências General medicine Farmacia Environmental sciences Environmental engineering Engineering, environmental Engineering, civil Engenharias iv Engenharias iii Engenharias ii Engenharias i Ecological modeling Civil and structural engineering Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Biotecnología Biodiversidade Astronomia / física
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: mattia.mattei@urv.cat mattia.mattei@urv.cat alexandre.arenas@urv.cat
Identificador del autor: 0000-0003-0937-0334
Fecha de alta del registro: 2024-09-28
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0043135423006590
Programa de financiación: Marie Sklodowska-Curie Actions – European Union’s Horizon 2020 research and innovation programme
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Water Research. 242 120223-
Referencia de l'ítem segons les normes APA: Mattei, Mattia; Pinto, Rosa M; Guix, Susana; Bosch, Albert; Arenas, Alex (2023). Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases. Water Research, 242(), 120223-. DOI: 10.1016/j.watres.2023.120223
Acrónimo: MFP-Plus
DOI del artículo: 10.1016/j.watres.2023.120223
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2023
Acción del progama de financiación: Martí i Franquès COFUND Doctoral Programme
Tipo de publicación: Journal Publications
Repositori URV