Lawrence Goodridge


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Community Surveillance of Omicron in Ontario: Wastewater-based Epidemiology Comes of Age.
Authors presented in alphabetical order:, Jos Arts, R. Stephen Brown, David Bulir, Trevor C. Charles, Christopher T. DeGroot, Robert Delatolla, Jean‐Paul Desaulniers, Elizabeth A. Edwards, Meghan Fuzzen, Kimberley Gilbride, Jodi Gilchrist, Lawrence Goodridge, Tyson E. Graber, Marc Habash, Peter Jüni, Andrea E. Kirkwood, James Knockleby, Christopher J. Kyle, Chrystal Landgraff, Chand Mangat, Douglas Manuel, R. Michael L. McKay, Edgard M. Mejia, Aleksandra Mloszewska, Banu Örmeci, Claire J. Oswald, Sarah Jane Payne, Hui Peng, Shelley Peterson, Art F. Y. Poon, Mark R. Servos, Denina Simmons, Jianxian Sun, Minqing Ivy Yang, Gustavo Ybazeta

Abstract Wastewater-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.

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Metagenomics of Wastewater Influent from Wastewater Treatment Facilities across Ontario in the Era of Emerging SARS-CoV-2 Variants of Concern
Opeyemi U. Lawal, Linkang Zhang, Valeria R. Parreira, R. Stephen Brown, Charles Chettleburgh, Nora Dannah, Robert Delatolla, Kimberly Gilbride, Tyson E. Graber, Golam Islam, James Knockleby, Siying Ma, Hanlan McDougall, R. Michael L. McKay, Aleksandra Mloszewska, Claire J. Oswald, Mark R. Servos, Megan Swinwood-Sky, Gustavo Ybazeta, Marc Habash, Lawrence Goodridge
Microbiology Resource Announcements, Volume 11, Issue 7

We report metagenomic sequencing analyses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in composite wastewater influent from 10 regions in Ontario, Canada, during the transition between Delta and Omicron variants of concern. The Delta and Omicron BA.1/BA.1.1 and BA.2-defining mutations occurring in various frequencies were reported in the consensus and subconsensus sequences of the composite samples.


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Near real-time determination of B.1.1.7 in proportion to total SARS-CoV-2 viral load in wastewater using an allele-specific primer extension PCR strategy
Tyson E. Graber, Kamya Bhatnagar, Élisabeth Mercier, Meghan Fuzzen, Patrick M. D’Aoust, Huy-Dung Hoang, Xin Tian, Syeda Tasneem Towhid, Julio Plaza Diaz, Tommy Alain, Ainslie Butler, Lawrence Goodridge, Mark R. Servos, Robert Delatolla

Abstract The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed millions of lives to date. Antigenic drift has resulted in viral variants with putatively greater transmissibility, virulence, or both. Early and near real-time detection of these variants of concern (VOC) and the ability to accurately follow their incidence and prevalence in communities is wanting. Wastewater-based epidemiology (WBE), which uses nucleic acid amplification tests to detect viral fragments, is a faithful proxy of COVID-19 incidence and prevalence, and thus offers the potential to monitor VOC viral load in a given population. Here, we describe and validate a primer extension PCR strategy targeting a signature mutation in the N gene of SARS-CoV-2. This allows quantification of the proportional expression of B.1.1.7 versus non-B.1.1.7 alleles in wastewater without the need to employ quantitative RT-PCR standard curves. We show that the wastewater B.1.1.7 profile correlates with its clinical counterpart and benefits from a near real-time and facile data collection and reporting pipeline. This assay can be quickly implemented within a current SARS-CoV-2 WBE framework with minimal cost; allowing early and contemporaneous estimates of B.1.1.7 community transmission prior to, or in lieu of, clinical screening and identification. Our study demonstrates that this strategy can provide public health units with an additional and much needed tool to rapidly triangulate VOC incidence/prevalence with high sensitivity and lineage specificity.