Chrystal Landgraff


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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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RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern
Yuwei Xie, Jonathan K. Challis, Femi F. Oloye, Mohsen Asadi, Jenna Cantin, Markus Brinkmann, Kerry N. McPhedran, Natacha S. Hogan, Mike Sadowski, Paul D. Jones, Chrystal Landgraff, Chand Mangat, Mark R. Servos, John P. Giesy
ACS ES&T Water, Volume 2, Issue 11

There are no standardized protocols for quantifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater to date, especially for population normalization. Here, a pipeline was developed, applied, and assessed to quantify SARS-CoV-2 and key variants of concern (VOCs) RNA in wastewater at Saskatoon, Canada. Normalization approaches using recovery ratio and extraction efficiency, wastewater parameters, or population indicators were assessed by comparing to daily numbers of new cases. Viral load was positively correlated with daily new cases reported in the sewershed. Wastewater surveillance (WS) had a lead time of approximately 7 days, which indicated surges in the number of new cases. WS revealed the variant α and δ driving the third and fourth wave, respectively. The adjustment with the recovery ratio and extraction efficiency improved the correlation between viral load and daily new cases. Normalization of viral concentration to concentrations of the artificial sweetener acesulfame K improved the trend of viral load during the Christmas and New Year holidays when populations were dynamic and variable. Acesulfame K performed better than pepper mild mottle virus, creatinine, and ammonia for population normalization. Hence, quality controls to characterize recovery ratios and extraction efficiencies and population normalization with acesulfame are promising for precise WS programs supporting decision-making in public health.

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Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities
Femi F. Oloye, Yuwei Xie, Mohsen Asadi, Jenna Cantin, Jonathan K. Challis, Markus Brinkmann, Kerry N. McPhedran, Kevin Kristian, Mark P. Keller, Mike Sadowski, Paul D. Jones, Chrystal Landgraff, Chand Mangat, Meghan Fuzzen, Mark R. Servos, John P. Giesy
Science of The Total Environment, Volume 841

Monitoring the communal incidence of COVID-19 is important for both government and residents of an area to make informed decisions. However, continuous reliance on one means of monitoring might not be accurate because of biases introduced by government policies or behaviours of residents. Wastewater surveillance was employed to monitor concentrations of SARS-CoV-2 RNA in raw influent wastewater from wastewater treatment plants serving three Canadian Prairie cities with different population sizes. Data obtained from wastewater are not directly influenced by government regulations or behaviours of individuals. The means of three weekly samples collected using 24 h composite auto-samplers were determined. Viral loads were determined by RT-qPCR, and whole-genome sequencing was used to charaterize variants of concern (VOC). The dominant VOCs in the three cities were the same but with different proportions of sub-lineages. Sub-lineages of Delta were AY.12, AY.25, AY.27 and AY.93 in 2021, while the major sub-lineage of Omicron was BA.1 in January 2022, and BA.2 subsequently became a trace-level sub-variant then the predominant VOC. When each VOC was first detected varied among cities; However, Saskatoon, with the largest population, was always the first to present new VOCs. Viral loads varied among cities, but there was no direct correlation with population size, possibly because of differences in flow regimes. Population is one of the factors that affects trends in onset and development of local outbreaks during the pandemic. This might be due to demography or the fact that larger populations had greater potential for inter- and intra-country migration. Hence, wastewater surveillance data from larger cities can typically be used to indicate what to expect in smaller communities.