Analysis of SARS-CoV-2 in wastewater for ...
URL: https://doi.org/10.1016/j.watres.2023.120223
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.
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Additional Information
Field | Value |
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Data last updated | unknown |
Metadata last updated | unknown |
Created | unknown |
Format | unknown |
License | Open Access |
Authors | Mattei, M.; Pinto, R.M., Guix, S.; Bosch, A.; Arenas, A. |
Publication date | June 14, 2023 |
Access level | info:eu-repo/semantics/openAccess |
Version | unknown |
Created | 18 days ago |
id | 57383713-adc1-4302-91e2-57fdc36c3008 |
license id | info:eu-repo/semantics/openAccess |
license title | Open Access |
license url | https://wiki.surfnet.nl/display/standards/info-eu-repo/ |
package id | 8d738449-a7a6-435a-9f0e-91b2da5420bd |
position | 2 |
revision id | 5cabf865-71e5-41da-96e1-5e72e4bd3aa1 |
state | active |