Universitat Politècnica de Catalunya. Departament de Física
Universitat Politècnica de Catalunya. BIOCOM-SC - Biologia Computacional i Sistemes Complexos
2022-09-05
While wastewater-based epidemiology has proven a useful tool for epidemiological surveillance during the COVID-19 pandemic, few quantitative models comparing virus concentrations in wastewater samples and cumulative incidence have been established. In this work, a simple mathematical model relating virus concentration and cumulative incidence for full contagion waves was developed. The model was then used for short-term forecasting and compared to a local linear model. Both scenarios were tested using a dataset composed of samples from 32 wastewater treatment plants and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence data covering the corresponding geographical areas during a 7-month period, including two contagion waves. A population-averaged dataset was also developed to model and predict the incidence over the full geography. Overall, the mathematical model based on wastewater data showed a good correlation with cumulative cases and allowed us to anticipate SARS-CoV-2 incidence in one week, which is of special relevance in situations where the epidemiological monitoring system cannot be fully implemented.
The authors want to thank the Catalan Institute for Water Research (Institut Català de Recerca de l’Aigua, ICRA) and the Open Data initiative of the Generalitat de Catalunya for publishing the SARS-CoV-2 concentration and incidence data as open access information. The authors also want to acknowledge the funding of the INNO- 4COV-19 (European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 101016203) project City Sentinel V-Sense.
Peer Reviewed
Objectius de Desenvolupament Sostenible::3 - Salut i Benestar
Postprint (published version)
Article
Inglés
Àrees temàtiques de la UPC::Ciències de la salut; COVID-19 (Disease); Diseases -- Mathematical models; Sewage -- Sampling; Water -- Sampling; Epidemiology; Epidemiologia -- Models matemàtics; COVID-19 (Malaltia); Aigües residuals--Mostreig
Nature
https://www.nature.com/articles/s41598-022-18518-9
info:eu-repo/grantAgreement/EC/H2020/101016203/EU/Boosting Innovation for COVID-19 Diagnostic, Prevention and Surveillance./INNO4COV-19
http://creativecommons.org/licenses/by-nc-nd/4.0/
Open Access
Attribution-NonCommercial-NoDerivatives 4.0 International
E-prints [72954]