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http://hdl.handle.net/2445/200624
Title: | Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases |
Author: | Mattei, Mattia Pintó Solé, Rosa María Guix Arnau, Susana Bosch, Albert Arenas, Àlex |
Keywords: | SARS-CoV-2 Models matemàtics SARS-CoV-2 Mathematical models |
Issue Date: | 14-Jun-2023 |
Publisher: | Elsevier Ltd |
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. |
Note: | Reproducció del document publicat a: https://doi.org/10.1016/j.watres.2023.120223 |
It is part of: | Water Research, 2023, vol. 242, num. 120223, p. 1-9 |
URI: | http://hdl.handle.net/2445/200624 |
Related resource: | https://doi.org/10.1016/j.watres.2023.120223 |
ISSN: | 0043-1354 |
Appears in Collections: | Articles publicats en revistes (Genètica, Microbiologia i Estadística) |
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