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dc.contributor.authorArts, Eric
dc.contributor.authorBrown, Stephen
dc.contributor.authorBulir, David
dc.contributor.authorCharles, Trevor C.
dc.contributor.authorDeGroot, Christopher T.
dc.contributor.authorDelatolla, Robert
dc.contributor.authorDesaulniers, Jean-Paul
dc.contributor.authorEdwards, Elizabeth A.
dc.contributor.authorFuzzen, Meghan
dc.contributor.authorGilbride, Kimberly
dc.contributor.authorGilchrist, Jodi
dc.contributor.authorGoodridge, Lawrence
dc.contributor.authorGraber, Tyson E.
dc.contributor.authorHabash, Marc
dc.contributor.authorJüni, Peter
dc.contributor.authorKirkwood, Andrea
dc.contributor.authorKnockleby, James
dc.contributor.authorKyle, Christopher
dc.contributor.authorLandgraff, Chrystal
dc.contributor.authorMangat, Chand
dc.contributor.authorManuel, Douglas G.
dc.contributor.authorMcKay, R. Michael
dc.contributor.authorMejia, Edgard
dc.contributor.authorMloszewska, Aleksandra
dc.contributor.authorOrmeci, Banu
dc.contributor.authorOswald, Claire
dc.contributor.authorPayne, Sarah Jane
dc.contributor.authorPeng, Hui
dc.contributor.authorPeterson, Shelley
dc.contributor.authorPoon, Art F. Y.
dc.contributor.authorServos, Mark. R.
dc.contributor.authorSimmons, Denina
dc.contributor.authorSun, Jianxian
dc.contributor.authorYang, Minqing
dc.contributor.authorYbazeta, Gustavo
dc.date.accessioned2022-06-15 16:58:07 (GMT)
dc.date.available2022-06-15 16:58:07 (GMT)
dc.date.issued2022-03-15
dc.identifier.urihttps://doi.org/10.21203/rs.3.rs-1439969/v2
dc.identifier.urihttp://hdl.handle.net/10012/18383
dc.description.abstractWastewater-based surveillance of SARS-CoV-2 RNA has been implemented at building, neighbourhood, and city levels throughout the world. Implementation strategies and analysis methods differ, but they all aim to provide rapid and reliable information about community COVID-19 health states. A viable and sustainable SARS-CoV-2 surveillance network must not only provide reliable and timely information about COVID-19 trends, but also provide for scalability as well as accurate detection of known or unknown emerging variants. Emergence of the SARS-CoV-2 variant of concern Omicron in late Fall 2021 presented an excellent opportunity to benchmark individual and aggregated data outputs of the Ontario Wastewater Surveillance Initiative in Canada; this public health-integrated surveillance network monitors wastewaters from over 10 million people across major population centres of the province. We demonstrate that this coordinated approach provides excellent situational awareness, comparing favourably with traditional clinical surveillance measures. Thus, aggregated datasets compiled from multiple wastewater-based surveillance nodes can provide sufficient sensitivity (i.e., early indication of increasing and decreasing incidence of SARS-CoV-2) and specificity (i.e., allele frequency estimation of emerging variants) with which to make informed public health decisions at regional- and state-levels.en
dc.description.sponsorshipOntario Ministry of the Environment, Conservation and Parks|| Genome Canada and Ontario Genomics (OGI-209)||NSERC (ALLRP 555041-20 to C.O.)||Ontario Clean Water Agencyen
dc.language.isoenen
dc.publisherResearch Squareen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectwastewateren
dc.subjectepidemiologyen
dc.subjectVOCen
dc.subjectpublic healthen
dc.subjectsequencingen
dc.subjectPCRen
dc.titleCommunity Surveillance of Omicron in Ontario: Wastewater-based Epidemiology Comes of Ageen
dc.typePreprinten
dcterms.bibliographicCitationCommunity Surveillance of Omicron in Ontario: Wastewater-based Epidemiology Comes of Age. (2022, March 15). https://doi.org/10.21203/rs.3.rs-1439969/v2en
uws.contributor.affiliation1Faculty of Scienceen
uws.contributor.affiliation2Biologyen
uws.contributor.affiliation2Chemistryen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelFacultyen


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