Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus

Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. I...

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Autores principales:	Smruthi Karthikeyan, Andrew Nguyen, Daniel McDonald, Yijian Zong, Nancy Ronquillo, Junting Ren, Jingjing Zou, Sawyer Farmer, Greg Humphrey, Diana Henderson, Tara Javidi, Karen Messer, Cheryl Anderson, Robert Schooley, Natasha K. Martin, Rob Knight
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/7f1bbb14b2a74421873ec6a441a1b760
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spelling	oai:doaj.org-article:7f1bbb14b2a74421873ec6a441a1b7602021-12-02T19:35:57ZRapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus2379-507710.1128/mSystems.00793-21https://doaj.org/article/7f1bbb14b2a74421873ec6a441a1b7602021-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00793-21https://doaj.org/toc/2379-5077 Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. In the present study, a large-scale wastewater surveillance was successfully implemented on a large university campus enabling early detection of 85% of COVID-19 cases thereby averting potential outbreaks.Smruthi KarthikeyanAndrew NguyenDaniel McDonaldYijian ZongNancy RonquilloJunting RenJingjing ZouSawyer FarmerGreg HumphreyDiana HendersonTara JavidiKaren MesserCheryl AndersonRobert SchooleyNatasha K. MartinRob KnightAmerican Society for MicrobiologyarticleMicrobiologyQR1-502ENmSystems, Vol 6, Iss 4 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Microbiology QR1-502
spellingShingle	Microbiology QR1-502 Smruthi Karthikeyan Andrew Nguyen Daniel McDonald Yijian Zong Nancy Ronquillo Junting Ren Jingjing Zou Sawyer Farmer Greg Humphrey Diana Henderson Tara Javidi Karen Messer Cheryl Anderson Robert Schooley Natasha K. Martin Rob Knight Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus
description	Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. In the present study, a large-scale wastewater surveillance was successfully implemented on a large university campus enabling early detection of 85% of COVID-19 cases thereby averting potential outbreaks.
format	article
author	Smruthi Karthikeyan Andrew Nguyen Daniel McDonald Yijian Zong Nancy Ronquillo Junting Ren Jingjing Zou Sawyer Farmer Greg Humphrey Diana Henderson Tara Javidi Karen Messer Cheryl Anderson Robert Schooley Natasha K. Martin Rob Knight
author_facet	Smruthi Karthikeyan Andrew Nguyen Daniel McDonald Yijian Zong Nancy Ronquillo Junting Ren Jingjing Zou Sawyer Farmer Greg Humphrey Diana Henderson Tara Javidi Karen Messer Cheryl Anderson Robert Schooley Natasha K. Martin Rob Knight
author_sort	Smruthi Karthikeyan
title	Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus
title_short	Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus
title_full	Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus
title_fullStr	Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus
title_full_unstemmed	Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus
title_sort	rapid, large-scale wastewater surveillance and automated reporting system enable early detection of nearly 85% of covid-19 cases on a university campus
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/7f1bbb14b2a74421873ec6a441a1b760
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Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus

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