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...

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Bibliographic Details
Published in:Scientific reports 2021-09, Vol.11 (1), p.1-10, Article 19456
Main Authors: 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
Format: Article
Language:English
Subjects:
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639/705
704/172
Coronaviruses
COVID-19
Epidemiology
Humanities and Social Sciences
Mathematical models
multidisciplinary
Pandemics
Science
Science (multidisciplinary)
Severe acute respiratory syndrome coronavirus 2
Statistical analysis
Wastewater analysis
Wastewater treatment
Wastewater treatment plants
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Summary: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.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-021-98653-x