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Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology
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 wa...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484274/ https://www.ncbi.nlm.nih.gov/pubmed/34593871 http://dx.doi.org/10.1038/s41598-021-98653-x |
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author | Krivoňáková, Naďa Šoltýsová, Andrea Tamáš, Michal Takáč, Zdenko Krahulec, Ján Ficek, Andrej Gál, Miroslav Gall, Marián Fehér, Miroslav Krivjanská, Anna Horáková, Ivana Belišová, Noemi Bímová, Paula Škulcová, Andrea Butor Mackuľak, Tomáš |
author_facet | Krivoňáková, Naďa Šoltýsová, Andrea Tamáš, Michal Takáč, Zdenko Krahulec, Ján Ficek, Andrej Gál, Miroslav Gall, Marián Fehér, Miroslav Krivjanská, Anna Horáková, Ivana Belišová, Noemi Bímová, Paula Škulcová, Andrea Butor Mackuľak, Tomáš |
author_sort | Krivoňáková, Naďa |
collection | PubMed |
description | 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 (R(2) = 83.78%/R(2) = 52.65%) as well as with a reported number of death cases with a time lag of 4 weeks/27 days (R(2) = 83.21%/R(2) = 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 | Online Article Text |
id | pubmed-8484274 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84842742021-10-01 Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology Krivoňáková, Naďa Šoltýsová, Andrea Tamáš, Michal Takáč, Zdenko Krahulec, Ján Ficek, Andrej Gál, Miroslav Gall, Marián Fehér, Miroslav Krivjanská, Anna Horáková, Ivana Belišová, Noemi Bímová, Paula Škulcová, Andrea Butor Mackuľak, Tomáš Sci Rep Article 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 (R(2) = 83.78%/R(2) = 52.65%) as well as with a reported number of death cases with a time lag of 4 weeks/27 days (R(2) = 83.21%/R(2) = 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. Nature Publishing Group UK 2021-09-30 /pmc/articles/PMC8484274/ /pubmed/34593871 http://dx.doi.org/10.1038/s41598-021-98653-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Krivoňáková, Naďa Šoltýsová, Andrea Tamáš, Michal Takáč, Zdenko Krahulec, Ján Ficek, Andrej Gál, Miroslav Gall, Marián Fehér, Miroslav Krivjanská, Anna Horáková, Ivana Belišová, Noemi Bímová, Paula Škulcová, Andrea Butor Mackuľak, Tomáš Mathematical modeling based on RT-qPCR analysis of SARS-CoV-2 in wastewater as a tool for epidemiology |
title | 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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484274/ https://www.ncbi.nlm.nih.gov/pubmed/34593871 http://dx.doi.org/10.1038/s41598-021-98653-x |
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