Wastewater surveillance (WWS) is useful to better understand the spreading of coronavirus disease 2019 (COVID-19) in communities, which can help design and implement suitable mitigation measures. The main objective of this study was to develop the Wastewater Viral Load Risk Index (WWVLRI) for three Saskatchewan cities to offer a simple metric to interpret WWS. The index was developed by considering relationships between reproduction number, clinical data, daily per capita concentrations of virus particles in wastewater, and weekly viral load change rate. Trends of daily per capita concentrations of SARS-CoV-2 in wastewater for Saskatoon, Prince Albert, and North Battleford were similar during the pandemic, suggesting that per capita viral load can be useful to quantitatively compare wastewater signals among cities and develop an effective and comprehensible WWVLRI. The effective reproduction number (Rt) and the daily per capita efficiency adjusted viral load thresholds of 85 × 106 and 200 × 106 N2 gene counts (gc)/population day (pd) were determined. These values with rates of change were used to categorize the potential for COVID-19 outbreaks and subsequent declines. The weekly average was considered 'low risk' when the per capita viral load was 85 × 106 N2 gc/pd. A 'medium risk' occurs when the per capita copies were between 85 × 106 and 200 × 106 N2 gc/pd. with a rate of change <100 %. The start of an outbreak is indicated by a 'medium-high' risk classification when the week-over-week rate of change was >100 %, and the absolute magnitude of concentrations of viral particles was >85 × 106 N2 gc/pd. Lastly, a 'high risk' occurs when the viral load exceeds 200 × 106 N2 gc/pd. This methodology provides a valuable resource for decision-makers and health authorities, specifically given the limitation of COVID-19 surveillance based on clinical data.

Wastewater surveillance (WWS) is useful to better understand the spreading of coronavirus disease 2019 (COVID-19) in communities, which can help design and implement suitable mitigation measures. The main objective of this study was to develop the Wastewater Viral Load Risk Index (WWVLRI) for three Saskatchewan cities to offer a simple metric to interpret WWS. The index was developed by considering relationships between reproduction number, clinical data, daily per capita concentrations of virus particles in wastewater, and weekly viral load change rate. Trends of daily per capita concentrations of SARS-CoV-2 in wastewater for Saskatoon, Prince Albert, and North Battleford were similar during the pandemic, suggesting that per capita viral load can be useful to quantitatively compare wastewater signals among cities and develop an effective and comprehensible WWVLRI. The effective reproduction number (Rt) and the daily per capita efficiency adjusted viral load thresholds of 85 × 106 and 200 × 106 N2 gene counts (gc)/population day (pd) were determined. These values with rates of change were used to categorize the potential for COVID-19 outbreaks and subsequent declines. The weekly average was considered 'low risk' when the per capita viral load was 85 × 106 N2 gc/pd. A 'medium risk' occurs when the per capita copies were between 85 × 106 and 200 × 106 N2 gc/pd. with a rate of change <100 %. The start of an outbreak is indicated by a 'medium-high' risk classification when the week-over-week rate of change was >100 %, and the absolute magnitude of concentrations of viral particles was >85 × 106 N2 gc/pd. Lastly, a 'high risk' occurs when the viral load exceeds 200 × 106 N2 gc/pd. This methodology provides a valuable resource for decision-makers and health authorities, specifically given the limitation of COVID-19 surveillance based on clinical data.

As fragments of SARS-CoV-2 RNA can be quantified and measured temporally in wastewater, surveillance of concentrations of SARS-CoV-2 in wastewater has become a vital resource for tracking the spread of COVID-19 in and among communities. However, the absence of standardized methods has affected the interpretation of data for public health efforts. In particular, analyzing either the liquid or solid fraction has implications for the interpretation of how viral RNA is quantified. Characterizing how SARS-CoV-2 or its RNA fragments partition in wastewater is a central part of understanding fate and behaviour in wastewater. In this study, partitioning of SARS-CoV-2 was investigated by use of centrifugation with varied durations of spin and centrifugal force, polyethylene glycol (PEG) precipitation followed by centrifugation, and ultrafiltration of wastewater. Partitioning of the endogenous pepper mild mottled virus (PMMoV), used to normalize the SARS-CoV-2 signal for fecal load in trend analysis, was also examined. Additionally, two surrogates for coronavirus, human coronavirus 229E and murine hepatitis virus, were analyzed as process controls. Even though SARS-CoV-2 has an affinity for solids, the total RNA copies of SARS-CoV-2 per wastewater sample, after centrifugation (12,000 g, 1.5 h, no brake), were partitioned evenly between the liquid and solid fractions. Centrifugation at greater speeds for longer durations resulted in a shift in partitioning for all viruses toward the solid fraction except for PMMoV, which remained mostly in the liquid fraction. The surrogates more closely reflected the partitioning of SARS-CoV-2 under high centrifugation speed and duration while PMMoV did not. Interestingly, ultrafiltration devices were inconsistent in estimating RNA copies in wastewater, which can influence the interpretation of partitioning. Developing a better understanding of the fate of SARS-CoV-2 in wastewater and creating a foundation of best practices is the key to supporting the current pandemic response and preparing for future potential infectious diseases.

As fragments of SARS-CoV-2 RNA can be quantified and measured temporally in wastewater, surveillance of concentrations of SARS-CoV-2 in wastewater has become a vital resource for tracking the spread of COVID-19 in and among communities. However, the absence of standardized methods has affected the interpretation of data for public health efforts. In particular, analyzing either the liquid or solid fraction has implications for the interpretation of how viral RNA is quantified. Characterizing how SARS-CoV-2 or its RNA fragments partition in wastewater is a central part of understanding fate and behaviour in wastewater. In this study, partitioning of SARS-CoV-2 was investigated by use of centrifugation with varied durations of spin and centrifugal force, polyethylene glycol (PEG) precipitation followed by centrifugation, and ultrafiltration of wastewater. Partitioning of the endogenous pepper mild mottled virus (PMMoV), used to normalize the SARS-CoV-2 signal for fecal load in trend analysis, was also examined. Additionally, two surrogates for coronavirus, human coronavirus 229E and murine hepatitis virus, were analyzed as process controls. Even though SARS-CoV-2 has an affinity for solids, the total RNA copies of SARS-CoV-2 per wastewater sample, after centrifugation (12,000 g, 1.5 h, no brake), were partitioned evenly between the liquid and solid fractions. Centrifugation at greater speeds for longer durations resulted in a shift in partitioning for all viruses toward the solid fraction except for PMMoV, which remained mostly in the liquid fraction. The surrogates more closely reflected the partitioning of SARS-CoV-2 under high centrifugation speed and duration while PMMoV did not. Interestingly, ultrafiltration devices were inconsistent in estimating RNA copies in wastewater, which can influence the interpretation of partitioning. Developing a better understanding of the fate of SARS-CoV-2 in wastewater and creating a foundation of best practices is the key to supporting the current pandemic response and preparing for future potential infectious diseases.

Fish live in continuous contact with various stressors and antigenic material present within their environments. The impact of stressors associated with wastewater-exposed environments on fish has become of particular interest in toxicology studies. The objectives of this study were to examine potential effects of wastewater treatment plant (WWTP) effluent-associated stressors on innate cytokine expression within the gills of darter species (Etheostoma spp.), using both field and laboratory approaches. Male and female darters (rainbow, greenside, fantail, and johnny darters) were collected upstream and downstream of the Waterloo WWTP in the Grand River, Ontario. Gill samples were collected from fish in the field and from a second subset of fish brought back to the laboratory. Laboratory fish were acutely exposed (96-h) to an environmentally relevant concentration of venlafaxine (1.0 μg/L), a commonly prescribed antidepressant. To assess the impacts of these stressors on the innate immunity of darters, the expression of key innate cytokines was examined. Minor significant effects on innate cytokine expression were observed between upstream and downstream fish. Moderate effects on cytokine expression were observed in venlafaxine-exposed fish compared to their control counterparts however, changes were not indicative of a biologically significant immune response occurring due to the exposure. Although the results of this study did not display extensive impacts of effluent and pharmaceutical exposure on innate cytokine expression within the gills, they provide a novel avenue of study, illustrating the importance of examining potential impacts that effluent-associated stressors can have on fundamental immune responses of native fish species.

Fish live in continuous contact with various stressors and antigenic material present within their environments. The impact of stressors associated with wastewater-exposed environments on fish has become of particular interest in toxicology studies. The objectives of this study were to examine potential effects of wastewater treatment plant (WWTP) effluent-associated stressors on innate cytokine expression within the gills of darter species (Etheostoma spp.), using both field and laboratory approaches. Male and female darters (rainbow, greenside, fantail, and johnny darters) were collected upstream and downstream of the Waterloo WWTP in the Grand River, Ontario. Gill samples were collected from fish in the field and from a second subset of fish brought back to the laboratory. Laboratory fish were acutely exposed (96-h) to an environmentally relevant concentration of venlafaxine (1.0 μg/L), a commonly prescribed antidepressant. To assess the impacts of these stressors on the innate immunity of darters, the expression of key innate cytokines was examined. Minor significant effects on innate cytokine expression were observed between upstream and downstream fish. Moderate effects on cytokine expression were observed in venlafaxine-exposed fish compared to their control counterparts however, changes were not indicative of a biologically significant immune response occurring due to the exposure. Although the results of this study did not display extensive impacts of effluent and pharmaceutical exposure on innate cytokine expression within the gills, they provide a novel avenue of study, illustrating the importance of examining potential impacts that effluent-associated stressors can have on fundamental immune responses of native fish species.

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.

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.

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.

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.

Wastewater-based surveillance has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription polymerase chain reaction (RT-PCR) or whole genome sequencing (WGS). Rapid, reliable RT-PCR assays continue to be needed to determine the relative frequencies of VOCs and sub-lineages in wastewater-based surveillance programs. The presence of multiple mutations in a single region of the N-gene allowed for the design of a single amplicon, multiple probe assay, that can distinguish among several VOCs in wastewater RNA extracts. This approach which multiplexes probes designed to target mutations associated with specific VOC's along with an intra-amplicon universal probe (non-mutated region) was validated in singleplex and multiplex. The prevalence of each mutation (i.e. VOC) is estimated by comparing the abundance of the targeted mutation with a non-mutated and highly conserved region within the same amplicon. This is advantageous for the accurate and rapid estimation of variant frequencies in wastewater. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from several communities in Ontario, Canada in near real time from November 28, 2021 to January 4, 2022. This includes the period of the rapid replacement of the Delta variant with the introduction of the Omicron variant in these Ontario communities in early December 2021. The frequency estimates using this assay were highly reflective of clinical WGS estimates for the same communities. This style of qPCR assay, which simultaneously measures signal from a non-mutated comparator probe and multiple mutation-specific probes contained within a single qPCR amplicon, can be applied to future assay development for rapid and accurate estimations of variant frequencies.

Wastewater-based surveillance has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription polymerase chain reaction (RT-PCR) or whole genome sequencing (WGS). Rapid, reliable RT-PCR assays continue to be needed to determine the relative frequencies of VOCs and sub-lineages in wastewater-based surveillance programs. The presence of multiple mutations in a single region of the N-gene allowed for the design of a single amplicon, multiple probe assay, that can distinguish among several VOCs in wastewater RNA extracts. This approach which multiplexes probes designed to target mutations associated with specific VOC's along with an intra-amplicon universal probe (non-mutated region) was validated in singleplex and multiplex. The prevalence of each mutation (i.e. VOC) is estimated by comparing the abundance of the targeted mutation with a non-mutated and highly conserved region within the same amplicon. This is advantageous for the accurate and rapid estimation of variant frequencies in wastewater. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from several communities in Ontario, Canada in near real time from November 28, 2021 to January 4, 2022. This includes the period of the rapid replacement of the Delta variant with the introduction of the Omicron variant in these Ontario communities in early December 2021. The frequency estimates using this assay were highly reflective of clinical WGS estimates for the same communities. This style of qPCR assay, which simultaneously measures signal from a non-mutated comparator probe and multiple mutation-specific probes contained within a single qPCR amplicon, can be applied to future assay development for rapid and accurate estimations of variant frequencies.

For over a decade, intersex has been observed in rainbow darter (RD) (Etheostoma caeruleum) populations living downstream wastewater treatment plants (WWTPs) in the Grand River, Ontario, Canada. To further our understanding of intersex development in adult male fish, the current study addressed three objectives: i) can intersex be induced in adult male fish, ii) is there a specific window of exposure when adult male fish are more susceptible to developing intersex, and iii) can pre-exposed adult male fish recover from intersex? To assess intersex induction in adult male fish, wild male RD were exposed in the laboratory for 22 weeks (during periods of spawning, gonadal regression, and gonadal recrudescence) to environmentally relevant concentrations of 17α-ethinylestradiol (EE2) including nominal 0, 1, and 10 ng/L. Intersex rates and severity at 10 ng/L EE2 were similar to those observed historically in adult male populations living downstream WWTPs in the Grand River and confirmed previous predictions that 1–10 ng/L EE2 would cause these adverse effects. To assess a window of sensitivity in developing intersex, male RD were exposed to nominal 0, 1 or 10 ng/L EE2 for 4 weeks during three different periods of gonadal development, including (i) spawning, (ii) early recrudescence and (iii) late recrudescence. These short-term exposures revealed that intersex incidence and severity were greater when RD were exposed while gonads were fully developed (during spawning) compared to periods of recrudescence. To assess if RD recover from intersex, wild fish were collected downstream WWTPs in the Grand River and assessed for intersex both before and after a 22-week recovery period in clean water that included gonadal regression and recrudescence. Results showed that fish did not recover from intersex, with intersex rates and severity similar to those both before and after the transition to clean water. This study further advances our knowledge on intersex manifestation in adult male fish including their sensitivity to endocrine active compounds during different periods of their annual reproductive cycle and their limited ability to recover from intersex after onset of the condition.

For over a decade, intersex has been observed in rainbow darter (RD) (Etheostoma caeruleum) populations living downstream wastewater treatment plants (WWTPs) in the Grand River, Ontario, Canada. To further our understanding of intersex development in adult male fish, the current study addressed three objectives: i) can intersex be induced in adult male fish, ii) is there a specific window of exposure when adult male fish are more susceptible to developing intersex, and iii) can pre-exposed adult male fish recover from intersex? To assess intersex induction in adult male fish, wild male RD were exposed in the laboratory for 22 weeks (during periods of spawning, gonadal regression, and gonadal recrudescence) to environmentally relevant concentrations of 17α-ethinylestradiol (EE2) including nominal 0, 1, and 10 ng/L. Intersex rates and severity at 10 ng/L EE2 were similar to those observed historically in adult male populations living downstream WWTPs in the Grand River and confirmed previous predictions that 1–10 ng/L EE2 would cause these adverse effects. To assess a window of sensitivity in developing intersex, male RD were exposed to nominal 0, 1 or 10 ng/L EE2 for 4 weeks during three different periods of gonadal development, including (i) spawning, (ii) early recrudescence and (iii) late recrudescence. These short-term exposures revealed that intersex incidence and severity were greater when RD were exposed while gonads were fully developed (during spawning) compared to periods of recrudescence. To assess if RD recover from intersex, wild fish were collected downstream WWTPs in the Grand River and assessed for intersex both before and after a 22-week recovery period in clean water that included gonadal regression and recrudescence. Results showed that fish did not recover from intersex, with intersex rates and severity similar to those both before and after the transition to clean water. This study further advances our knowledge on intersex manifestation in adult male fish including their sensitivity to endocrine active compounds during different periods of their annual reproductive cycle and their limited ability to recover from intersex after onset of the condition.

Wastewater monitoring and epidemiology have seen renewed interest during the recent COVID-19 pandemic. As a result, there is an increasing need to normalize wastewater-derived viral loads in local populations. Chemical tracers, both exogenous and endogenous compounds, have proven to be more stable and reliable for normalization than biological indicators. However, differing instrumentation and extraction methods can make it difficult to compare results. This review examines current extraction and quantification methods for ten common population indicators: creatinine, coprostanol, nicotine, cotinine, sucralose, acesulfame, androstenedione 5-hydroindoleacetic acid (5-HIAA), caffeine, and 1,7-dimethyluric acid. Some wastewater parameters such as ammonia, total nitrogen, total phosphorus, and daily flowrate were also evaluated. The analytical methods included direct injection, dilute and shoot, liquid/liquid, and solid phase extraction (SPE). Creatine, acesulfame, nicotine, 5-HIAA and androstenedione have been analysed by direct injection into LC-MS; however, most authors prefer to include SPE steps to avoid matrix effects. Both LC-MS and GC-MS have been successfully used to quantify coprostanol in wastewater, and the other selected indicators have been quantified successfully with LC-MS. Acidification to stabilize the sample before freezing to maintain the integrity of samples has been reported to be beneficial. However, there are arguments both for and against working at acidic pHs. Wastewater parameters mentioned earlier are quick and easy to quantify, but the data does not always represent the human population effectively. A preference for population indicators originating solely from humans is apparent. This review summarises methods employed for chemical indicators in wastewater, provides a basis for choosing an appropriate extraction and analysis method, and highlights the utility of accurate chemical tracer data for wastewater-based epidemiology.

Wastewater monitoring and epidemiology have seen renewed interest during the recent COVID-19 pandemic. As a result, there is an increasing need to normalize wastewater-derived viral loads in local populations. Chemical tracers, both exogenous and endogenous compounds, have proven to be more stable and reliable for normalization than biological indicators. However, differing instrumentation and extraction methods can make it difficult to compare results. This review examines current extraction and quantification methods for ten common population indicators: creatinine, coprostanol, nicotine, cotinine, sucralose, acesulfame, androstenedione 5-hydroindoleacetic acid (5-HIAA), caffeine, and 1,7-dimethyluric acid. Some wastewater parameters such as ammonia, total nitrogen, total phosphorus, and daily flowrate were also evaluated. The analytical methods included direct injection, dilute and shoot, liquid/liquid, and solid phase extraction (SPE). Creatine, acesulfame, nicotine, 5-HIAA and androstenedione have been analysed by direct injection into LC-MS; however, most authors prefer to include SPE steps to avoid matrix effects. Both LC-MS and GC-MS have been successfully used to quantify coprostanol in wastewater, and the other selected indicators have been quantified successfully with LC-MS. Acidification to stabilize the sample before freezing to maintain the integrity of samples has been reported to be beneficial. However, there are arguments both for and against working at acidic pHs. Wastewater parameters mentioned earlier are quick and easy to quantify, but the data does not always represent the human population effectively. A preference for population indicators originating solely from humans is apparent. This review summarises methods employed for chemical indicators in wastewater, provides a basis for choosing an appropriate extraction and analysis method, and highlights the utility of accurate chemical tracer data for wastewater-based epidemiology.

The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain "non-standard" data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modeling approaches by reflecting well-understood mechanisms for random error in microbial data. This work showed that data diverging from the log-linear regression model at low concentrations as well as non-detects can be seamlessly integrated into enhanced standard curve analysis. The newly developed model provides improved representation of standard curve data at low concentrations while converging asymptotically upon conventional log-linear regression at high concentrations and adding no fitting parameters. Such modeling facilitates exploration of the effects of various random error mechanisms in experiments generating standard curve data, enables quantification of uncertainty in standard curve parameters, and is an important step toward quantifying uncertainty in qPCR-based concentration estimates. Improving understanding of the random error in qPCR data and standard curve modeling is especially important when low concentrations are of particular interest and inappropriate analysis can unduly affect interpretation, conclusions regarding lab performance, reported concentration estimates, and associated decision-making.

The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain "non-standard" data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modeling approaches by reflecting well-understood mechanisms for random error in microbial data. This work showed that data diverging from the log-linear regression model at low concentrations as well as non-detects can be seamlessly integrated into enhanced standard curve analysis. The newly developed model provides improved representation of standard curve data at low concentrations while converging asymptotically upon conventional log-linear regression at high concentrations and adding no fitting parameters. Such modeling facilitates exploration of the effects of various random error mechanisms in experiments generating standard curve data, enables quantification of uncertainty in standard curve parameters, and is an important step toward quantifying uncertainty in qPCR-based concentration estimates. Improving understanding of the random error in qPCR data and standard curve modeling is especially important when low concentrations are of particular interest and inappropriate analysis can unduly affect interpretation, conclusions regarding lab performance, reported concentration estimates, and associated decision-making.

Municipal wastewater treatment plant (WWTP) effluent is one of several point sources of contaminants (nutrients, pharmaceuticals, estrogens, etc.) which can lead to adverse responses in aquatic life. Studies of WWTP effluent impacts on rainbow darter (Etheostoma caeruleum) collected downstream of WWTPs in the Grand River, Ontario have reported disruption at multiple levels of biological organization, including altered vitellogenin gene expression, lower levels of in vitro steroid production, and high frequency of intersex. However, major upgrades have occurred at treatment plants in the central Grand River over the last decade. Treatment upgrades to the Waterloo WWTP were initiated in 2009 but due to construction delays, the upgrades came fully on-line in 2017/2018. Responses in rainbow darter have been followed at sites associated with the outfall consistently over this entire time period. The treatment plant upgrade resulted in nitrification of effluent, and once complete there was a major reduction in effluent ammonia, selected pharmaceuticals, and estrogenicity. This study compared several key responses in rainbow darter associated with the Waterloo WWTP outfall prior to and post upgrades. Stable isotopes signatures in fish were used to track exposure to effluent and changed dramatically over time, corresponding to the effluent quality. Disruptions in in vitro steroid production and intersex in the darters that had been identified prior to the upgrades were no longer statistically different from the upstream reference sites after the upgrades. Although annual variations in water temperature and flow can potentially mask or exacerbate the effects of the WWTP effluent, major capital investments in wastewater treatment targeted at improving effluent quality have corresponded with the reduction of adverse responses in fish in the receiving environment.

Municipal wastewater treatment plant (WWTP) effluent is one of several point sources of contaminants (nutrients, pharmaceuticals, estrogens, etc.) which can lead to adverse responses in aquatic life. Studies of WWTP effluent impacts on rainbow darter (Etheostoma caeruleum) collected downstream of WWTPs in the Grand River, Ontario have reported disruption at multiple levels of biological organization, including altered vitellogenin gene expression, lower levels of in vitro steroid production, and high frequency of intersex. However, major upgrades have occurred at treatment plants in the central Grand River over the last decade. Treatment upgrades to the Waterloo WWTP were initiated in 2009 but due to construction delays, the upgrades came fully on-line in 2017/2018. Responses in rainbow darter have been followed at sites associated with the outfall consistently over this entire time period. The treatment plant upgrade resulted in nitrification of effluent, and once complete there was a major reduction in effluent ammonia, selected pharmaceuticals, and estrogenicity. This study compared several key responses in rainbow darter associated with the Waterloo WWTP outfall prior to and post upgrades. Stable isotopes signatures in fish were used to track exposure to effluent and changed dramatically over time, corresponding to the effluent quality. Disruptions in in vitro steroid production and intersex in the darters that had been identified prior to the upgrades were no longer statistically different from the upstream reference sites after the upgrades. Although annual variations in water temperature and flow can potentially mask or exacerbate the effects of the WWTP effluent, major capital investments in wastewater treatment targeted at improving effluent quality have corresponded with the reduction of adverse responses in fish in the receiving environment.

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.

Abstract Wastewater-based surveillance (WBS) has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Quantities of viral fragments of SARS-CoV-2 in wastewater are related to numbers of clinical cases of COVID-19 reported within the corresponding sewershed. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription quantitative polymerase chain reaction (RT-qPCR) or sequencing. A multiplex RT-qPCR assay to detect and estimate the prevalence of multiple VOCs, including Omicron/Alpha, Beta, Gamma, and Delta, in wastewater RNA extracts was developed and validated. The probe-based multiplex assay, named “N200” focuses on amino acids 199-202, a region of the N gene that contains several mutations that are associated with variants of SARS- CoV-2 within a single amplicon. Each of the probes in the N200 assay are specific to the targeted mutations and worked equally well in single- and multi-plex modes. To estimate prevalence of each VOC, the abundance of the targeted mutation was compared with a non- mutated region within the same amplified region. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from six sewersheds in Ontario, Canada collected between December 1, 2021, and January 4, 2022. Using the N200 assay, the replacement of the Delta variant along with the introduction and rapid dominance of the Omicron variant were monitored in near real-time, as they occurred nearly simultaneously at all six locations. The N200 assay is robust and efficient for wastewater surveillance can be adopted into VOC monitoring programs or replace more laborious assays currently being used to monitor SARS- CoV-2 and its VOCs.

Abstract Wastewater monitoring of SARS-CoV-2 allows for early detection and monitoring of COVID-19 burden in communities and can track specific variants of concern. Targeted assays enabled relative proportions of SARS-CoV-2 Omicron and Delta variants to be determined across 30 municipalities covering >75% of the province of Alberta (pop. 4.5M) in Canada, from November 2021 to January 2022. Larger cities like Calgary and Edmonton exhibited a more rapid emergence of Omicron relative to smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a more remote northern city with a large fly-in worker population. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden prior to the observed increase in newly diagnosed clinical cases throughout Alberta, which peaked two weeks later. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of emerging pathogens including SARS-CoV-2 variants.

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.

The Grand River (GR) extends throughout the majority of Southern Ontario with its final outlet at Lake Erie and accommodates thirty wastewater treatment plants (WWTP) with varied filtration processes. Many WWTPs are unable to effectively eliminate several contaminants of concern (CECs) from final released effluent, leading to measurable concentrations in surface waters and ultimately chronically exposing aquatic species to mixed CECs. Exposures to CECs have reported impacts on oxidative stress, measurable through reactive oxygen species (ROS) and the antioxidant defense response. This research focuses on the effects of WWTP effluent on four Etheostoma (Darter) species endemic to the GR. Objectives of this study examined if any oxidative stress markers are present in darter brains downstream from the effluent release point compared to an upstream reference site relative to the Waterloo, ON WWTP across two separate years (Fall 2020 and 2021). This was assessed using transcriptional and enzyme analysis of antioxidant enzymes (SOD, GPX, CAT) and an enzyme involved in serotonin synthesis. In fall 2020, significant differences in transcript expression of markers were found between sites and sexes in greenside darters (GSD) with SOD and CAT showing increased expression downstream. Changes in transcript expression aligned with antioxidative enzyme activity where interactive effects with sex-related differences were observed in fish collected the Fall of 2020. In contrast, transcription markers measured in Fall 2021 were increased upstream compared to downstream species. Continued investigation on the impacts of pharmaceutical exposures in non-target organisms is crucial to further the knowledge of WWTP effluent impacts.

Abstract Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021–January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.

The Grand River watershed is the largest in southern Ontario and assimilates thirty wastewater treatment plants (WWTP) with varied degrees of treatment. Many WWTPs are unable to effectively eliminate several contaminants of emerging concern (CECs) from final effluent, leading to measurable concentrations in surface waters. Exposures to CECs have reported impacts on oxidative stress measured through antioxidative enzymes (SOD, CAT, GPX). This study focuses on the effects of WWTP effluent on four Etheostoma (Darter) species endemic to the Grand River, by investigating if increased antioxidative response markers are present in darter brains downstream from the effluent outfall compared to an upstream reference site relative to the Waterloo, ON WWTP across two separate years (Oct 2020 and Oct 2021). This was assessed using transcriptional and enzyme analysis of antioxidant enzymes and an enzyme involved in serotonin synthesis, tryptophan hydroxylase (tph). In fall 2020, significant differences in transcript markers were found between sites and sexes in GSD with SOD and CAT showing increased expression downstream, in JD with both sexes showing increased SOD downstream, and an interactive effect for tph in RBD. Changes in transcripts aligned with enzyme activity where interactive effects with sex-related differences were observed in fish collected fall 2020. In contrast, transcripts measured in fall 2021 were increased upstream compared to downstream species in RBD and GSD. This study additionally displayed yearly, species and sex differences in antioxidant responses. Continued investigation on the impacts of CECs in effluent in non-target species is required to better understand WWTP effluent impacts.

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.

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

Evaluations of analytical performance through interlaboratory comparisons and proficiency tests are underway globally for biomolecular-based methods [e.g., reverse-transcription quantitative polymerase chain reaction (RT-qPCR)] used in the surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. These evaluations often rely on sharing a common reference wastewater sample that is split among participating laboratories. A known quantity of recovery surrogates can be introduced to the wastewater matrix by the coordinating laboratory as an exogenous control in a spike-and-recovery approach; however, split-sample comparisons are increasingly performed to evaluate in situ quantities of SARS-CoV-2 genetic signal native to the sample due to the lack of a universally accepted recovery surrogate of SARS-CoV-2. A reproducible procedure that minimizes the variability of SARS-CoV-2 genetic signal among split wastewater aliquots is therefore necessary to facilitate the method comparisons, especially when a large number of aliquots are required. Emerging literature has suggested that SARS-CoV-2 genetic signal in wastewater is linked to the solids fraction. Accordingly, a protocol that allows for equal distribution of solids content evenly among wastewater aliquots was also likely to facilitate even distribution of the SARS-CoV-2 genetic signal. Based on this premise, we reviewed existing sample splitting apparatus and approaches used for solids-based parameters in environmental samples. A portable batch reactor was designed, comprised of readily accessible materials and equipment. This design was validated through splitting of real wastewater samples collected from a municipal wastewater treatment facility serving a population with reported cases of COVID-19. This work applies well-established solid-liquid mixing theory and concepts that are likely unfamiliar to molecular microbiologists and laboratory analysts, providing (1) a prototype adaptable for a range of sample quantities, aliquot sizes, microbial targets, and water matrices; and (2) a pragmatic demonstration of critical considerations for design and validation of a reproducible and effective sample splitting protocol.

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.

Detection of SARS-CoV-2 RNA in wastewater is a promising tool for informing public health decisions during the COVID-19 pandemic. However, approaches for its analysis by use of reverse transcription quantitative polymerase chain reaction (RT-qPCR) are still far from standardized globally. To characterize inter- and intra-laboratory variability among results when using various methods deployed across Canada, aliquots from a real wastewater sample were spiked with surrogates of SARS-CoV-2 (gamma-radiation inactivated SARS-CoV-2 and human coronavirus strain 229E [HCoV-229E]) at low and high levels then provided "blind" to eight laboratories. Concentration estimates reported by individual laboratories were consistently within a 1.0-log10 range for aliquots of the same spiked condition. All laboratories distinguished between low- and high-spikes for both surrogates. As expected, greater variability was observed in the results amongst laboratories than within individual laboratories, but SARS-CoV-2 RNA concentration estimates for each spiked condition remained mostly within 1.0-log10 ranges. The no-spike wastewater aliquots provided yielded non-detects or trace levels (<20 gene copies/mL) of SARS-CoV-2 RNA. Detections appear linked to methods that included or focused on the solids fraction of the wastewater matrix and might represent in-situ SARS-CoV-2 to the wastewater sample. HCoV-229E RNA was not detected in the no-spike aliquots. Overall, all methods yielded comparable results at the conditions tested. Partitioning behavior of SARS-CoV-2 and spiked surrogates in wastewater should be considered to evaluate method effectiveness. A consistent method and laboratory to explore wastewater SARS-CoV-2 temporal trends for a given system, with appropriate quality control protocols and documented in adequate detail should succeed.

Detection of SARS-CoV-2 RNA in wastewater is a promising tool for informing public health decisions during the COVID-19 pandemic. However, approaches for its analysis by use of reverse transcription quantitative polymerase chain reaction (RT-qPCR) are still far from standardized globally. To characterize inter- and intra-laboratory variability among results when using various methods deployed across Canada, aliquots from a real wastewater sample were spiked with surrogates of SARS-CoV-2 (gamma-radiation inactivated SARS-CoV-2 and human coronavirus strain 229E [HCoV-229E]) at low and high levels then provided "blind" to eight laboratories. Concentration estimates reported by individual laboratories were consistently within a 1.0-log10 range for aliquots of the same spiked condition. All laboratories distinguished between low- and high-spikes for both surrogates. As expected, greater variability was observed in the results amongst laboratories than within individual laboratories, but SARS-CoV-2 RNA concentration estimates for each spiked condition remained mostly within 1.0-log10 ranges. The no-spike wastewater aliquots provided yielded non-detects or trace levels (<20 gene copies/mL) of SARS-CoV-2 RNA. Detections appear linked to methods that included or focused on the solids fraction of the wastewater matrix and might represent in-situ SARS-CoV-2 to the wastewater sample. HCoV-229E RNA was not detected in the no-spike aliquots. Overall, all methods yielded comparable results at the conditions tested. Partitioning behavior of SARS-CoV-2 and spiked surrogates in wastewater should be considered to evaluate method effectiveness. A consistent method and laboratory to explore wastewater SARS-CoV-2 temporal trends for a given system, with appropriate quality control protocols and documented in adequate detail should succeed.

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.

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.

• RT-ddPCR is more sensitive to inhibitors than RT-qPCR for primary clarified sludge. • Primary clarified sludge has elevated frequency of SARS-CoV-2 RNA detection. • Primary clarified sludge allows detection of RNA during low COVID-19 incidence. • PMMoV normalization of RNA data reduces noise and increases precision. • PMMoV normalization of RNA shows strongest correlation to epidemiological metrics. In the absence of an effective vaccine to prevent COVID-19 it is important to be able to track community infections to inform public health interventions aimed at reducing the spread and therefore reduce pressures on health-care, improve health outcomes and reduce economic uncertainty. Wastewater surveillance has rapidly emerged as a potential tool to effectively monitor community infections through measuring trends of RNA signal in wastewater systems. In this study SARS-CoV-2 viral RNA N1 and N2 gene regions are quantified in solids collected from influent post grit solids (PGS) and primary clarified sludge (PCS) in two water resource recovery facilities (WRRF) serving Canada's national capital region, i.e., the City of Ottawa, ON (pop. ≈ 1.1M) and the City of Gatineau, QC (pop. ≈ 280K). PCS samples show signal inhibition using RT-ddPCR compared to RT-qPCR, with PGS samples showing similar quantifiable concentrations of RNA using both assays. RT-qPCR shows higher frequency of detection of N1 and N2 gene regions in PCS (92.7, 90.6%, n = 6) as compared to PGS samples (79.2, 82.3%, n = 5). Sampling of PCS may therefore be an effective approach for SARS-CoV-2 viral quantification, especially during periods of declining and low COVID-19 incidence in the community. The pepper mild mottle virus (PMMoV) is determined to have a less variable RNA signal in PCS over a three month period for two WRRFs, regardless of environmental conditions, compared to Bacteroides 16S rRNA or human 18S rRNA, making PMMoV a potentially useful biomarker for normalization of SARS-CoV-2 signal. PMMoV-normalized PCS RNA signal from WRRFs of two cities correlated with the regional public health epidemiological metrics, identifying PCS normalized to a fecal indicator (PMMoV) as a potentially effective tool for monitoring trends during decreasing and low-incidence of infection of SARS-Cov-2 in communities.

Industrial wastewaters and urban discharges contain complex mixtures of chemicals capable of impacting reproductive performance in freshwater fish, called endocrine-disrupting compounds (EDCs). In Chile, the issue was highlighted by our group beginning over 15 years ago, by analyzing the impacts of pulp and paper mill effluents (PPME) in the Biobio, Itata, and Cruces River basins. All of the rivers studied are important freshwater ecosystems located in the Mediterranean region of Central Chile, each with a unique fish biodiversity. Sequentially, we developed a strategy based on laboratory assays, semicontrolled-field experiments (e.g., caging) and wild fish population assessments to explore the issue of reproductive impacts on both introduced and native fish in Chile. The integration of watershed, field, and laboratory studies was effective at understanding the endocrine responses in Chilean freshwater systems. The studies demonstrated that regardless of the type of treatment, pulp mill effluents can contain compounds capable of impacting endocrine systems. Urban wastewater treatment plant effluents (WWTP) were also investigated using the same integrated strategy. Although not directly compared, PPME and WWTP effluent seem to cause similar estrogenic effects in fish after waterborne exposure, with differing intensities. This body of work underscores the urgent need for further studies on the basic biology of Chilean native fish species, and an improved understanding on reproductive development and variability across Chilean ecosystems. The lack of knowledge of the ontogeny of Chilean fish, especially maturation and sexual development, with an emphasis on associated habitats and landscapes, are impediment factors for their conservation and protection against the threat of EDCs. The assessment of effects on native species in the receiving environment is critical for supporting and designing protective regulations and remediation strategies, and for conserving the unique Chilean fish biodiversity.

Curtailing the Spring 2020 COVID-19 surge required sweeping and stringent interventions by governments across the world. Wastewater-based COVID-19 epidemiology programs have been initiated in many countries to provide public health agencies with a complementary disease tracking metric and non-discriminating surveillance tool. However, their efficacy in prospectively capturing resurgences following a period of low prevalence is unclear. In this study, the SARS-CoV-2 viral signal was measured in primary clarified sludge harvested every two days at the City of Ottawa's water resource recovery facility during the summer of 2020, when clinical testing recorded daily percent positivity below 1%. In late July, increases of >400% in normalized SARS-CoV-2 RNA signal in wastewater were identified 48 h prior to reported >300% increases in positive cases that were retrospectively attributed to community-acquired infections. During this resurgence period, SARS-CoV-2 RNA signal in wastewater preceded the reported >160% increase in community hospitalizations by approximately 96 h. This study supports wastewater-based COVID-19 surveillance of populations in augmenting the efficacy of diagnostic testing, which can suffer from sampling biases or timely reporting as in the case of hospitalization census.

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.

The combination of photocatalysis and biodegradation was investigated for the removal of nine selected pharmaceuticals as a means to reduce loadings into the environment. The combined process, consisting of a resource-efficient mild photocatalysis and a subsequent biological treatment, was compared to single processes of intensive photocatalysis and biological treatment. The UV-TiO2 based photocatalysis effectively removed atorvastatin, atenolol and fluoxetine (>80%). Biological treatment after mild photocatalytic pretreatment removed diclofenac effectively (>99%), while it persisted during the single biological treatment (

The effluent from municipal wastewater treatment plants is a major point source of contamination in Canadian waterways. The improvement of effluent quality to reduce contaminants, such as pharmaceuticals and personal care products, before being released into the environment is necessary to reduce the impacts on organisms that live in the river downstream. Here, we aimed to characterize the metabolic and gill physiological responses of rainbow (Etheostoma caeruleum), fantail (Etheostoma flabellare), and greenside (Etheostoma blennioides) darters to the effluent in the Grand River from the recently upgraded Waterloo municipal wastewater treatment plant. The routine metabolism of darters was not affected by effluent exposure, but some species had increased maximum metabolic rates, leading to an increased aerobic scope. The rainbow darter aerobic scope increased by 2.2 times and the fantail darter aerobic scope increased by 2.7 times compared to the reference site. Gill samples from effluent-exposed rainbow darters and greenside darters showed evidence of more pathologies and variations in morphology. These results suggest that darters can metabolically adjust to effluent-contaminated water and may also be adapting to the urban and agricultural inputs. The modification and damage to the gills provide a useful water quality indicator but does not necessarily reflect how well acclimated the species is to the environment due to a lack of evidence of poor fish health.

Aquatic organisms are continuously exposed to multiple environmental stressors working cumulatively to alter ecosystems. Wastewater-dominated environments are often riddled by a myriad of stressors, such as chemical and thermal stressors. The objective of this study was to examine the effects of an environmentally relevant concentration of a commonly prescribed antidepressant, venlafaxine (VFX) [1.0 μg/L], in addition to a 5°C increase in water temperature on zebrafish metabolism. Fish were chronically exposed (21 days) to one of four conditions: (i) 0 μg/L VFX at 27°C; (ii) 1.0 μg/L VFX at 27°C; (iii) 0 μg/L VFX at 32°C; (iv) 1.0 μg/L VFX at 32°C. Following exposure, whole-body metabolism was assessed by routine metabolic rate (RMR) measurements, whereas tissue-specific metabolism was assessed by measuring the activities of major metabolic enzymes in addition to glucose levels in muscle. RMR was significantly higher in the multi-stressed group relative to Control. The combination of both stressors resulted in elevated pyruvate kinase activity and glucose levels, while lipid metabolism was depressed, as measured by 3-hydroxyacyl CoA dehydrogenase activity. Citrate synthase activity increased with the onset of temperature, but only in the group treatment without VFX. Catalase activity was also elevated with the onset of the temperature stressor, however, that was not the case for the multi-stressed group, potentially indicating a deleterious effect of VFX on the anti-oxidant defense mechanism. The results of this study highlight the importance of multiple-stressor research, as it able to further bridge the gap between field and laboratory studies, as well as have the potential of yielding surprising results that may have not been predicted using a conventional single-stressor approach.

Decades of studies on endocrine disruption have suggested the need to manage the release of key estrogens from municipal wastewater treatment plants (WWTP). However, the proposed thresholds are below the detection limits of most routine chemical analysis, thereby restricting the ability of watershed managers to assess the environmental exposure appropriately. In this study, we demonstrated the utility of a mechanistic model to address the data gaps on estrogen exposure. Concentrations of the prominent estrogenic contaminants in wastewaters (estrone, estradiol, and ethinylestradiol) were simulated in the Grand River in southern Ontario (Canada) for nine years, including a period when major WWTP upgrades occurred. The predicted concentrations expressed as total estrogenicity (E2 equivalent concentrations) were contrasted to a key estrogenic response (i.e., intersex) in rainbow darter (Etheostoma caeruleum), a wild sentinel fish species. A predicted total estrogenicity in the river of ≥10 ng/L E2 equivalents was associated with high intersex incidence and severity, whereas concentrations <0.1 ng/L E2 equivalents were associated with minimal intersex expression. Exposure to a predicted river concentration of 0.4 ng/L E2 equivalents, the environmental quality standard (EQS) proposed by the European Union for estradiol, was associated with 34% (95% CI:30-38) intersex incidence and a very low severity score of 0.6 (95% CI:0.5-0.7). This exposure is not predicted to cause adverse effects in rainbow darter. The analyses completed in this study were only based on the predicted presence of three major estrogens (E1, E2, EE2), so caution must be exercised when interpreting the results. Nevertheless, this study illustrates the use of models for exposure assessment, especially when measured data are not available.

In this study, the estrogenicity of two major wastewater treatment plant (WWTP) effluents located in the central reaches of the Grand River watershed in southern Ontario was estimated using population demographics, excretion rates, and treatment plant-specific removals. Due to the lack of data on estrogen concentrations from direct measurements at WWTPs, the treatment efficiencies through the plants were estimated using the information obtained from an effects-directed analysis. The results show that this approach could effectively estimate the estrogenicity of WWTP effluents, both before and after major infrastructure upgrades were made at the Kitchener WWTP. The model was then applied to several possible future scenarios including population growth and river low flow conditions. The scenario analyses showed that post-upgrade operation of the Kitchener WWTP will not release highly estrogenic effluent under the 2041 projected population increase (36%) or summer low flows. Similarly, the Waterloo WWTP treatment operation is also expected to improve once the upgrades have been fully implemented and is expected to effectively treat estrogens even under extreme scenarios of population growth and river flows. The developed model may be employed to support decision making on wastewater management strategies designed for environmental protection, especially on reducing the endocrine effects in fish exposed to WWTP effluents.

The objective of this study was to assess the effects of municipal wastewater treatment plant effluent on the energetics and stress response of rainbow darter (Etheostoma caeruleum). Male and female rainbow darter were collected upstream and downstream of the Waterloo WWTP in the Grand River watershed, ON, Canada. To assess the effects of wastewater treatment plant effluent on whole-body and tissue specific metabolic capacity, closed-chamber respirometry and muscle-enzyme activity analyses were performed. Plasma cortisol was also collected from fish before and after an acute air-exposure stressor to evaluate the cortisol stress response in fish exposed to additional stressors. Male and female rainbow darter collected downstream of the effluent had higher oxygen consumption rates, while differences in enzyme activities were primarily associated with sex rather than collection site. No impairment in the cortisol stress response between downstream and upstream fish was observed, however baseline cortisol levels in female fish from the downstream site were significantly higher compared to other baseline groups. Stress-induced cortisol levels were also higher in female fish from both sites when compared to their male counterparts. Overall, this study demonstrates that chronic exposure to WWTP effluent impacts whole-body metabolic performance. This study was also able to demonstrate that sex-differences are a key determinant of various metabolic changes in response to physiological stress, thereby, providing a novel avenue to be considered and further explored.

Intersex in fish downstream of municipal wastewater treatment plants (MWWTPs) is a global concern. Consistent high rates of intersex in male rainbow darter (Etheostoma caeruleum) have been reported for several years in the Grand River, in southern Ontario, Canada, in close proximity to two MWWTPs. The larger MWWTP (Kitchener) recently underwent upgrades that included the conversion from a carbonaceous activated sludge to nitrifying activated sludge treatment process. This created a unique opportunity to assess whether upgrades designed to improve effluent quality could also remediate the intersex previously observed in wild fish. Multiple years (2007-2012) of intersex data on male rainbow darter collected before the upgrades at sites associated with the MWWTP outfall were compared with intersex data collected in postupgrade years (2013-2015). These upgrades resulted in a reduction from 70 to 100% intersex incidence (preupgrade) to <10% in postupgrade years. Although the cause of intersex remains unknown, indicators of effluent quality including nutrients, pharmaceuticals, and estrogenicity improved in the effluent after the upgrades. This study demonstrated that investment in MWWTP upgrades improved effluent quality and was associated with an immediate change in biological responses in the receiving environment. This is an important finding considering the tremendous cost of wastewater infrastructure.

The present study examined in vitro 11-ketotestosterone and testosterone production by the testes of rainbow darter (Etheostoma caeruleum) collected from selected reference sites and downstream of 2 municipal wastewater treatment plants (MWWTPs; Waterloo and Kitchener) on the central Grand River (Ontario, Canada), over a 6-yr period (2011-2016). The main objective was to investigate if infrastructure upgrades at the Kitchener MWWTP in 2012 resulted in a recovery of this response in the post-upgrade period (2013-2016). Two supporting studies showed that the fall season is appropriate for measuring in vitro sex steroid production because it provides stable detection of steroid patterns, and that the sample handling practiced in the present study did not introduce a bias. Infrastructure upgrades of the Kitchener MWWTP resulted in significant reductions in ammonia and estrogenicity. After the upgrades, 11-ketotestosterone production by MWWTP-exposed fish increased in 2013 and it continued to recover throughout the study period of 2014 through 2016, returning to levels measured in reference fish. Testosterone production was less sensitive and it lacked consistency. The Waterloo MWWTP underwent some minor upgrades but the level of ammonia and estrogenicity remained variable over time. The production of 11-ketotestosterone and testosterone in rainbow darter below the Waterloo MWWTP was variable and without a clear recovery pattern over the course of the present study. The results of the present study demonstrated that measuring production of sex steroids (especially 11-ketotestosterone) over multiple years can be relevant for assessing responses in fish to environmental changes such as those resulting from major infrastructure upgrades. Environ Toxicol Chem 2018;37:501-514. © 2017 SETAC.