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http://hdl.handle.net/2445/200624
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DC Field | Value | Language |
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dc.contributor.author | Mattei, Mattia | - |
dc.contributor.author | Pintó Solé, Rosa María | - |
dc.contributor.author | Guix Arnau, Susana | - |
dc.contributor.author | Bosch, Albert | - |
dc.contributor.author | Arenas, Àlex | - |
dc.date.accessioned | 2023-07-13T12:32:31Z | - |
dc.date.available | 2023-07-13T12:32:31Z | - |
dc.date.issued | 2023-06-14 | - |
dc.identifier.issn | 0043-1354 | - |
dc.identifier.uri | http://hdl.handle.net/2445/200624 | - |
dc.description.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. | - |
dc.format.extent | 9 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Elsevier Ltd | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1016/j.watres.2023.120223 | - |
dc.relation.ispartof | Water Research, 2023, vol. 242, num. 120223, p. 1-9 | - |
dc.relation.uri | https://doi.org/10.1016/j.watres.2023.120223 | - |
dc.rights | cc-by-nc-nd (c) Mattei, Mattia et al., 2023 | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | - |
dc.source | Articles publicats en revistes (Genètica, Microbiologia i Estadística) | - |
dc.subject.classification | SARS-CoV-2 | - |
dc.subject.classification | Models matemàtics | - |
dc.subject.other | SARS-CoV-2 | - |
dc.subject.other | Mathematical models | - |
dc.title | Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 737458 | - |
dc.date.updated | 2023-07-13T12:32:31Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Genètica, Microbiologia i Estadística) |
Files in This Item:
File | Description | Size | Format | |
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737458.pdf | 4.3 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License