Author, as appears in the article.: Mattei, Mattia; Pinto, Rosa M; Guix, Susana; Bosch, Albert; Arenas, Alex
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Arenas Moreno, Alejandro / Mattei, Mattia
Project code: Grant agreement No. 945413
Keywords: 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
Abstract: 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.
Thematic Areas: 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
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: mattia.mattei@urv.cat mattia.mattei@urv.cat alexandre.arenas@urv.cat
Author identifier: 0000-0003-0937-0334
Record's date: 2024-09-28
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.sciencedirect.com/science/article/pii/S0043135423006590
Funding program: Marie Sklodowska-Curie Actions – European Union’s Horizon 2020 research and innovation programme
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Water Research. 242 120223-
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
Acronym: MFP-Plus
Article's DOI: 10.1016/j.watres.2023.120223
Entity: Universitat Rovira i Virgili
Journal publication year: 2023
Funding program action: Martí i Franquès COFUND Doctoral Programme
Publication Type: Journal Publications
Repositori URV