Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology

Abstract Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerges to scientific research and monitoring of wastewaters to predict the spread of the virus in the community. Our study investigated the COVID-19 disease in Bratislava, ba...

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Autores principales:	Naďa Krivoňáková, Andrea Šoltýsová, Michal Tamáš, Zdenko Takáč, Ján Krahulec, Andrej Ficek, Miroslav Gál, Marián Gall, Miroslav Fehér, Anna Krivjanská, Ivana Horáková, Noemi Belišová, Paula Bímová, Andrea Butor Škulcová, Tomáš Mackuľak
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/36c8c96abfa84e4ca804f66e37ac7ccd
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spelling	oai:doaj.org-article:36c8c96abfa84e4ca804f66e37ac7ccd2021-12-02T18:51:07ZMathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology10.1038/s41598-021-98653-x2045-2322https://doaj.org/article/36c8c96abfa84e4ca804f66e37ac7ccd2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98653-xhttps://doaj.org/toc/2045-2322Abstract Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerges to scientific research and monitoring of wastewaters to predict the spread of the virus in the community. Our study investigated the COVID-19 disease in Bratislava, based on wastewater monitoring from September 2020 until March 2021. Samples were analyzed from two wastewater treatment plants of the city with reaching 0.6 million monitored inhabitants. Obtained results from the wastewater analysis suggest significant statistical dependence. High correlations between the number of viral particles in wastewater and the number of reported positive nasopharyngeal RT-qPCR tests of infected individuals with a time lag of 2 weeks/12 days (R2 = 83.78%/R2 = 52.65%) as well as with a reported number of death cases with a time lag of 4 weeks/27 days (R2 = 83.21%/R2 = 61.89%) was observed. The obtained results and subsequent mathematical modeling will serve in the future as an early warning system for the occurrence of a local site of infection and, at the same time, predict the load on the health system up to two weeks in advance.Naďa KrivoňákováAndrea ŠoltýsováMichal TamášZdenko TakáčJán KrahulecAndrej FicekMiroslav GálMarián GallMiroslav FehérAnna KrivjanskáIvana HorákováNoemi BelišováPaula BímováAndrea Butor ŠkulcováTomáš MackuľakNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Naďa Krivoňáková Andrea Šoltýsová Michal Tamáš Zdenko Takáč Ján Krahulec Andrej Ficek Miroslav Gál Marián Gall Miroslav Fehér Anna Krivjanská Ivana Horáková Noemi Belišová Paula Bímová Andrea Butor Škulcová Tomáš Mackuľak Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology
description	Abstract Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerges to scientific research and monitoring of wastewaters to predict the spread of the virus in the community. Our study investigated the COVID-19 disease in Bratislava, based on wastewater monitoring from September 2020 until March 2021. Samples were analyzed from two wastewater treatment plants of the city with reaching 0.6 million monitored inhabitants. Obtained results from the wastewater analysis suggest significant statistical dependence. High correlations between the number of viral particles in wastewater and the number of reported positive nasopharyngeal RT-qPCR tests of infected individuals with a time lag of 2 weeks/12 days (R2 = 83.78%/R2 = 52.65%) as well as with a reported number of death cases with a time lag of 4 weeks/27 days (R2 = 83.21%/R2 = 61.89%) was observed. The obtained results and subsequent mathematical modeling will serve in the future as an early warning system for the occurrence of a local site of infection and, at the same time, predict the load on the health system up to two weeks in advance.
format	article
author	Naďa Krivoňáková Andrea Šoltýsová Michal Tamáš Zdenko Takáč Ján Krahulec Andrej Ficek Miroslav Gál Marián Gall Miroslav Fehér Anna Krivjanská Ivana Horáková Noemi Belišová Paula Bímová Andrea Butor Škulcová Tomáš Mackuľak
author_facet	Naďa Krivoňáková Andrea Šoltýsová Michal Tamáš Zdenko Takáč Ján Krahulec Andrej Ficek Miroslav Gál Marián Gall Miroslav Fehér Anna Krivjanská Ivana Horáková Noemi Belišová Paula Bímová Andrea Butor Škulcová Tomáš Mackuľak
author_sort	Naďa Krivoňáková
title	Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology
title_short	Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology
title_full	Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology
title_fullStr	Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology
title_full_unstemmed	Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology
title_sort	mathematical modeling based on rt-qpcr analysis of sars-cov-2 in wastewater as a tool for epidemiology
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/36c8c96abfa84e4ca804f66e37ac7ccd
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Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology

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