2023
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Assessment of seasonality and normalization techniques for wastewater-based surveillance in Ontario, Canada
Hadi A. Dhiyebi,
Joud Abu Farah,
Heather Ikert,
Nivetha Srikanthan,
Samina Hayat,
Leslie M. Bragg,
Asim Qasim,
Mark Payne,
Linda Kaleis,
Caitlyn Paget,
Dominika Celmer‐Repin,
Arianne M. Folkema,
Stephen Drew,
Robert Delatolla,
John P. Giesy,
Mark R. Servos,
Hadi A. Dhiyebi,
Joud Abu Farah,
Heather Ikert,
Nivetha Srikanthan,
Samina Hayat,
Leslie M. Bragg,
Asim Qasim,
Mark Payne,
Linda Kaleis,
Caitlyn Paget,
Dominika Celmer‐Repin,
Arianne M. Folkema,
Stephen Drew,
Robert Delatolla,
John P. Giesy,
Mark R. Servos
Frontiers in Public Health, Volume 11
Introduction Wastewater-based surveillance is at the forefront of monitoring for community prevalence of COVID-19, however, continued uncertainty exists regarding the use of fecal indicators for normalization of the SARS-CoV-2 virus in wastewater. Using three communities in Ontario, sampled from 2021–2023, the seasonality of a viral fecal indicator (pepper mild mottle virus, PMMoV) and the utility of normalization of data to improve correlations with clinical cases was examined. Methods Wastewater samples from Warden, the Humber Air Management Facility (AMF), and Kitchener were analyzed for SARS-CoV-2, PMMoV, and crAssphage. The seasonality of PMMoV and flow rates were examined and compared by Season-Trend-Loess decomposition analysis. The effects of normalization using PMMoV, crAssphage, and flow rates were analyzed by comparing the correlations to clinical cases by episode date (CBED) during 2021. Results Seasonal analysis demonstrated that PMMoV had similar trends at Humber AMF and Kitchener with peaks in January and April 2022 and low concentrations (troughs) in the summer months. Warden had similar trends but was more sporadic between the peaks and troughs for PMMoV concentrations. Flow demonstrated similar trends but was not correlated to PMMoV concentrations at Humber AMF and was very weak at Kitchener ( r = 0.12). Despite the differences among the sewersheds, unnormalized SARS-CoV-2 (raw N1–N2) concentration in wastewater ( n = 99–191) was strongly correlated to the CBED in the communities ( r = 0.620–0.854) during 2021. Additionally, normalization with PMMoV did not improve the correlations at Warden and significantly reduced the correlations at Humber AMF and Kitchener. Flow normalization ( n = 99–191) at Humber AMF and Kitchener and crAssphage normalization ( n = 29–57) correlations at all three sites were not significantly different from raw N1–N2 correlations with CBED. Discussion Differences in seasonal trends in viral biomarkers caused by differences in sewershed characteristics (flow, input, etc.) may play a role in determining how effective normalization may be for improving correlations (or not). This study highlights the importance of assessing the influence of viral fecal indicators on normalized SARS-CoV-2 or other viruses of concern. Fecal indicators used to normalize the target of interest may help or hinder establishing trends with clinical outcomes of interest in wastewater-based surveillance and needs to be considered carefully across seasons and sites.
DOI
bib
abs
Assessment of seasonality and normalization techniques for wastewater-based surveillance in Ontario, Canada
Hadi A. Dhiyebi,
Joud Abu Farah,
Heather Ikert,
Nivetha Srikanthan,
Samina Hayat,
Leslie M. Bragg,
Asim Qasim,
Mark Payne,
Linda Kaleis,
Caitlyn Paget,
Dominika Celmer‐Repin,
Arianne M. Folkema,
Stephen Drew,
Robert Delatolla,
John P. Giesy,
Mark R. Servos,
Hadi A. Dhiyebi,
Joud Abu Farah,
Heather Ikert,
Nivetha Srikanthan,
Samina Hayat,
Leslie M. Bragg,
Asim Qasim,
Mark Payne,
Linda Kaleis,
Caitlyn Paget,
Dominika Celmer‐Repin,
Arianne M. Folkema,
Stephen Drew,
Robert Delatolla,
John P. Giesy,
Mark R. Servos
Frontiers in Public Health, Volume 11
Introduction Wastewater-based surveillance is at the forefront of monitoring for community prevalence of COVID-19, however, continued uncertainty exists regarding the use of fecal indicators for normalization of the SARS-CoV-2 virus in wastewater. Using three communities in Ontario, sampled from 2021–2023, the seasonality of a viral fecal indicator (pepper mild mottle virus, PMMoV) and the utility of normalization of data to improve correlations with clinical cases was examined. Methods Wastewater samples from Warden, the Humber Air Management Facility (AMF), and Kitchener were analyzed for SARS-CoV-2, PMMoV, and crAssphage. The seasonality of PMMoV and flow rates were examined and compared by Season-Trend-Loess decomposition analysis. The effects of normalization using PMMoV, crAssphage, and flow rates were analyzed by comparing the correlations to clinical cases by episode date (CBED) during 2021. Results Seasonal analysis demonstrated that PMMoV had similar trends at Humber AMF and Kitchener with peaks in January and April 2022 and low concentrations (troughs) in the summer months. Warden had similar trends but was more sporadic between the peaks and troughs for PMMoV concentrations. Flow demonstrated similar trends but was not correlated to PMMoV concentrations at Humber AMF and was very weak at Kitchener ( r = 0.12). Despite the differences among the sewersheds, unnormalized SARS-CoV-2 (raw N1–N2) concentration in wastewater ( n = 99–191) was strongly correlated to the CBED in the communities ( r = 0.620–0.854) during 2021. Additionally, normalization with PMMoV did not improve the correlations at Warden and significantly reduced the correlations at Humber AMF and Kitchener. Flow normalization ( n = 99–191) at Humber AMF and Kitchener and crAssphage normalization ( n = 29–57) correlations at all three sites were not significantly different from raw N1–N2 correlations with CBED. Discussion Differences in seasonal trends in viral biomarkers caused by differences in sewershed characteristics (flow, input, etc.) may play a role in determining how effective normalization may be for improving correlations (or not). This study highlights the importance of assessing the influence of viral fecal indicators on normalized SARS-CoV-2 or other viruses of concern. Fecal indicators used to normalize the target of interest may help or hinder establishing trends with clinical outcomes of interest in wastewater-based surveillance and needs to be considered carefully across seasons and sites.
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Omicron COVID-19 Case Estimates Based on Previous SARS-CoV-2 Wastewater Load, Regional Municipality of Peel, Ontario, Canada
Lydia Cheng,
Hadi A. Dhiyebi,
Monali Varia,
Kyle Atanas,
Nivetha Srikanthan,
Samina Hayat,
Heather Ikert,
Meghan Fuzzen,
Carly Sing-Judge,
Yash Badlani,
Eli Zeeb,
Leslie M. Bragg,
Robert Delatolla,
John P. Giesy,
Elaine Gilliland,
Mark R. Servos,
Lydia Cheng,
Hadi A. Dhiyebi,
Monali Varia,
Kyle Atanas,
Nivetha Srikanthan,
Samina Hayat,
Heather Ikert,
Meghan Fuzzen,
Carly Sing-Judge,
Yash Badlani,
Eli Zeeb,
Leslie M. Bragg,
Robert Delatolla,
John P. Giesy,
Elaine Gilliland,
Mark R. Servos
Emerging Infectious Diseases, Volume 29, Issue 8
We determined correlations between SARS-CoV-2 load in untreated water and COVID-19 cases and patient hospitalizations before the Omicron variant (September 2020-November 2021) at 2 wastewater treatment plants in the Regional Municipality of Peel, Ontario, Canada. Using pre-Omicron correlations, we estimated incident COVID-19 cases during Omicron outbreaks (November 2021-June 2022). The strongest correlation between wastewater SARS-CoV-2 load and COVID-19 cases occurred 1 day after sampling (r = 0.911). The strongest correlation between wastewater load and COVID-19 patient hospitalizations occurred 4 days after sampling (r = 0.819). At the peak of the Omicron BA.2 outbreak in April 2022, reported COVID-19 cases were underestimated 19-fold because of changes in clinical testing. Wastewater data provided information for local decision-making and are a useful component of COVID-19 surveillance systems.
DOI
bib
abs
Omicron COVID-19 Case Estimates Based on Previous SARS-CoV-2 Wastewater Load, Regional Municipality of Peel, Ontario, Canada
Lydia Cheng,
Hadi A. Dhiyebi,
Monali Varia,
Kyle Atanas,
Nivetha Srikanthan,
Samina Hayat,
Heather Ikert,
Meghan Fuzzen,
Carly Sing-Judge,
Yash Badlani,
Eli Zeeb,
Leslie M. Bragg,
Robert Delatolla,
John P. Giesy,
Elaine Gilliland,
Mark R. Servos,
Lydia Cheng,
Hadi A. Dhiyebi,
Monali Varia,
Kyle Atanas,
Nivetha Srikanthan,
Samina Hayat,
Heather Ikert,
Meghan Fuzzen,
Carly Sing-Judge,
Yash Badlani,
Eli Zeeb,
Leslie M. Bragg,
Robert Delatolla,
John P. Giesy,
Elaine Gilliland,
Mark R. Servos
Emerging Infectious Diseases, Volume 29, Issue 8
We determined correlations between SARS-CoV-2 load in untreated water and COVID-19 cases and patient hospitalizations before the Omicron variant (September 2020-November 2021) at 2 wastewater treatment plants in the Regional Municipality of Peel, Ontario, Canada. Using pre-Omicron correlations, we estimated incident COVID-19 cases during Omicron outbreaks (November 2021-June 2022). The strongest correlation between wastewater SARS-CoV-2 load and COVID-19 cases occurred 1 day after sampling (r = 0.911). The strongest correlation between wastewater load and COVID-19 patient hospitalizations occurred 4 days after sampling (r = 0.819). At the peak of the Omicron BA.2 outbreak in April 2022, reported COVID-19 cases were underestimated 19-fold because of changes in clinical testing. Wastewater data provided information for local decision-making and are a useful component of COVID-19 surveillance systems.
2021
Circulating plasma microRNAs (miRNAs) are well established as biomarkers of several diseases in humans and have recently been used as indicators of environmental exposures in fish. However, the role of plasma miRNAs in regulating acute stress responses in fish is largely unknown. Tissue and plasma miRNAs have recently been associated with excreted miRNAs; however, external miRNAs have never been measured in fish. The objective of this study was to identify the altered plasma miRNAs in response to acute stress in rainbow trout ( Oncorhynchus mykiss ), as well as altered miRNAs in fish epidermal mucus and the surrounding ambient water. Small RNA was extracted and sequenced from plasma, mucus, and water collected from rainbow trout pre- and 1 h-post a 3-min air stressor. Following small RNA-Seq and pathway analysis, we identified differentially expressed plasma miRNAs that targeted biosynthetic, degradation, and metabolic pathways. We successfully isolated miRNA from trout mucus and the surrounding water and detected differences in miRNA expression 1-h post air stress. The expressed miRNA profiles in mucus and water were different from the altered plasma miRNA profile, which indicated that the plasma miRNA response was not associated with or immediately reflected in external samples, which was further validated through qPCR. This research expands understanding of the role of plasma miRNA in the acute stress response of fish and is the first report of successful isolation and profiling of miRNA from fish mucus or samples of ambient water. Measurements of miRNA from plasma, mucus, or water can be further studied and have potential to be applied as non-lethal indicators of acute stress in fish.