RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern

Emerging hazardous chemicals and biological pollutants in Canadian aquatic systems and remediation approaches: A comprehensive status report

Emerging contaminants can be natural or synthetic materials, as well as materials of a chemical, or biological origin; these materials are typically not controlled or monitored in the environment. Canada is home to nearly 7 % of the world's renewable water supply and a wide range of different kinds of water systems, including the Great Lake, rivers, canals, gulfs, and estuaries. Although the majority of these pollutants are present in trace amounts (μg/L - ng/L concentrations), several studies have reported their detrimental impact on both human health and the biota. In Canadian aquatic environments, concentrations of pharmaceuticals (as high as 115 μg/L), pesticides (as high as 1.95 μg/L), bioavailable heavy metals like dissolved mercury (as high as 135 ng/L), and hydrocarbon/crude oil spills (as high as 4.5 million liters) have been documented. Biological threats such as genetic materials of the contagious SARS-CoV-2 virus have been reported in the provinces of Québec, Ontario, Saskatchewan and Manitoba provinces, as well as in the Nunavut territory, with a need for more holistic research. These toxins and emerging pollutants are associated with nefarious short and long-term health effects, with the potential for bioaccumulation in the environment. Hence, this Canadian-focused report provides the footprints for water and environmental sustainability, in light of this emerging threat to the environment and society. Several remediation pathways/tools that have been explored by Canadian researchers, existing challenges and prospects are also discussed. The review concludes with preventive measures and strategies for managing the inventory of emerging contaminants in the environment.

Reporting population size in wastewater-based epidemiology: A scoping review

Knowledge of the number of people present in a catchment is fundamental for the assessment of spatio-temporal trends in wastewater-based epidemiology (WBE). Accurately estimating the number of people connected to wastewater catchments is challenging however, because populations are dynamic. Methods used to estimate population size can significantly influence the calculation and interpretation of population-normalised wastewater data (PNWD). This paper systematically reviews the reporting of population data in 339 WBE studies. Studies were evaluated based on their reporting of population size, the source of population data, the population calculation methods, and the uncertainties in population estimates. Most papers reported population size (96 %) and the source of population data (60 %). Fewer studies reported the uncertainties in their population data (50 %) and the methods used to calculate these estimates (28 %). This is relevant because different methods have unique strengths and limitations which can affect the accuracy of PNWD. Only 64 studies (19 %) reported all four components of population data. The reporting of population data has remained consistent in the past decade. Based on the findings, we recommend generalised reporting criteria for population data in WBE. As WBE is further mainstreamed and applied, the clear and comprehensive reporting of population data will only become increasingly important.

Current state and future perspectives on de facto population markers for normalization in wastewater-based epidemiology: A systematic literature review

Wastewater-based epidemiology (WBE) and wastewater surveillance have become a valuable complementary data source to collect information on community-wide exposure through the measurement of human biomarkers in influent wastewater (IWW). In WBE, normalization of data with the de facto population that corresponds to a wastewater sample is crucial for a correct interpretation of spatio-temporal trends in exposure and consumption patterns. However, knowledge gaps remain in identifying and validating suitable de facto population biomarkers (PBs) for refinement of WBE back-estimations. WBE studies that apply de facto PBs (including hydrochemical parameters, utility consumption data sources, endo- and exogenous chemicals, biological biomarkers and signalling records) for relative trend analysis and absolute population size estimation were systematically reviewed from three databases (PubMed, Web of Science, SCOPUS) according to the PRISMA guidelines. We included in this review 81 publications that accounted for daily variations in population sizes by applying de facto population normalization. To date, a wide range of PBs have been proposed for de facto population normalization, complicating the comparability of normalized measurements across WBE studies. Additionally, the validation of potential PBs is complicated by the absence of an ideal external validator, magnifying the overall uncertainty for population normalization in WBE. Therefore, this review proposes a conceptual tier-based cross-validation approach for identifying and validating de facto PBs to guide their integration for i) relative trend analysis, and ii) absolute population size estimation. Furthermore, this review also provides a detailed evaluation of the uncertainty observed when comparing different de jure and de facto population estimation approaches. This study shows that their percentual differences can range up to ±200 %, with some exceptions showing even larger variations. This review underscores the need for collaboration among WBE researchers to further streamline the application of de facto population normalization and to evaluate the robustness of different PBs in different socio-demographic communities.

The role of catchment population size, data normalization, and chronology of public health interventions on wastewater-based COVID-19 viral trends

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic presented the most challenging global crisis in recent times. A pandemic caused by a novel pathogen such as SARS-CoV-2 necessitated the development of innovative techniques for the monitoring and surveillance of COVID-19 infections within communities. Wastewater surveillance (WWS) is recognized as a non-invasive, cost-effective, and valuable epidemiological tool to monitor the prevalence of COVID-19 infections in communities. Seven municipal wastewater sampling sites representing distinct sewershed communities were selected for the surveillance of the SARS-CoV-2 virus in Durham Region, Ontario, Canada over 8 months from March 2021 to October 2021. Viral RNA fragments of SARS-CoV-2 and the normalization target pepper mild mottle virus (PMMoV) were concentrated from wastewater influent using the PEG/NaCl superspeed centrifugation method and quantified using RT-qPCR. Strong significant correlations (Spearman's rs = 0.749 to 0.862, P < 0.001) were observed between SARS-CoV-2 gene copies/mL of wastewater and clinical cases reported in each delineated sewershed by onset date. Although raw wastewater offered higher correlation coefficients with clinical cases by onset date compared to PMMoV normalized data, only one site had a statistically significantly higher Spearman's correlation coefficient value for raw data than normalized data. Implementation of community stay-at-home orders and vaccinations over the course of the study period in 2021 were found to strongly correspond to decreasing SARS-CoV-2 wastewater trends in the wastewater treatment plants and upstream pumping stations.

Influences of 23 different equations used to calculate gene copies of SARS-CoV-2 during wastewater-based epidemiology

Following the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the use of wastewater-based surveillance (WBS) has increased dramatically along with associated infrastructure globally. However, due to the global nature of its application, and various workflow adaptations (e.g., sample collection, water concentration, RNA extraction kits), numerous methods for back-calculation of gene copies per volume (gc/L) of sewage have also emerged. Many studies have considered the comparability of processing methods (e.g., water concentration, RNA extraction); however, for equations used to calculate gene copies in a wastewater sample and subsequent influences on monitoring viral trends in a community and its association with epidemiological data, less is known. Due to limited information on how many formulas exist for the calculation of SARS-CoV-2 gene copies in wastewater, we initially attempted to quantify how many equations existed in the referred literature. We identified 23 unique equations, which were subsequently applied to an existing wastewater dataset. We observed a range of gene copies based on use of different equations, along with variability of AUC curve values, and results from correlation and regression analyses. Though a number of individual laboratories appear to have independently converged on a similar formula for back-calculation of viral load in wastewater, and share similar relationships with epidemiological data, differential influences of various equations were observed for variation in PCR volumes, RNA extraction volumes, or PCR assay parameters. Such observations highlight challenges when performing comparisons among WBS studies when numerous methodologies and back-calculation methods exist. To facilitate reproducibility among studies, the different gc/L equations were packaged as an R Shiny app, which provides end users the ability to investigate variability within their datasets and support comparisons among studies.

New prospects of environmental RNA metabarcoding research in biological diversity, ecotoxicological monitoring, and detection of COVID-19: a critical review

Ecosystems are multifaceted and complex systems and understanding their composition is crucial for the implementation of efficient conservation and management. Conventional approaches to biodiversity surveys can have limitations in detecting the complete range of species present. In contrast, the study of environmental RNA (eRNA) offers a non-invasive and comprehensive method for monitoring and evaluating biodiversity across different ecosystems. Similar to eDNA, the examination of genetic material found in environmental samples can identify and measure many species, including ones that pose challenges to traditional methods. However, eRNA is degraded quickly and therefore shows promise in detection of living organisms closer to their actual location than eDNA methods. This method provides a comprehensive perspective on the well-being of ecosystems, facilitating the development of focused conservation approaches to save at-risk species and uphold ecological equilibrium. Furthermore, eRNA has been recognized as a valuable method for the identification of COVID-19 in the environment, besides its established uses in biodiversity protection. The SARS-CoV-2 virus, which is accountable for the worldwide epidemic, releases RNA particles into the surrounding environment via human waste, providing insights into the feasibility of detecting it in wastewater and other samples taken from the environment. In this article, we critically reviewed the recent research activities that use the eRNA method, including its utilization in biodiversity conservation, ecological surveillance, and ecotoxicological monitoring as well as its innovative potential in identifying COVID-19. Through this review, the reader can understand the recent developments, prospects, and challenges of eRNA research in ecosystem management and biodiversity conservation.

Emergence and spread of SARS-CoV-2 variants of concern in Canada: a retrospective analysis from clinical and wastewater data

BACKGROUND

The spread of SARS-CoV-2 has been studied at unprecedented levels worldwide. In jurisdictions where molecular analysis was performed on large scales, the emergence and competition of numerous SARS-CoV-2lineages have been observed in near real-time. Lineage identification, traditionally performed from clinical samples, can also be determined by sampling wastewater from sewersheds serving populations of interest. Variants of concern (VOCs) and SARS-CoV-2 lineages associated with increased transmissibility and/or severity are of particular interest.

METHOD

Here, we consider clinical and wastewater data sources to assess the emergence and spread of VOCs in Canada retrospectively.

RESULTS

We show that, overall, wastewater-based VOC identification provides similar insights to the surveillance based on clinical samples. Based on clinical data, we observed synchrony in VOC introduction as well as similar emergence speeds across most Canadian provinces despite the large geographical size of the country and differences in provincial public health measures.

CONCLUSION

In particular, it took approximately four months for VOC Alpha and Delta to contribute to half of the incidence. In contrast, VOC Omicron achieved the same contribution in less than one month. This study provides significant benchmarks to enhance planning for future VOCs, and to some extent for future pandemics caused by other pathogens, by quantifying the rate of SARS-CoV-2 VOCs invasion in Canada.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

Assessment of rapid wastewater surveillance for determination of communicable disease spread in municipalities

Wastewater surveillance (WS) helps to improve the understanding of the spread of communicable diseases in communities. WS can assist public health decision-makers in the design and implementation of timely mitigation measures. There is an increased need to use reliable, cost-effective, simple, and rapid WS systems, given traditional analytical (or 'gold-standard') programs are instrument/time-intensive, and dependent on highly skilled personnel. This study investigated the application of the portable GeneXpert platform for WS of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IAV), influenza B virus (IBV), and respiratory syncytial virus (RSV). The GeneXpert system with the Xpert Xpress-SARS-CoV-2/Flu/RSV test kit uses reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to analyze wastewater samples. From September 2022 through January 2023, wastewater samples were collected from the influents of municipal wastewater treatment plants (MWTPs) of Saskatoon, Prince Albert, and North Battleford in the province of Saskatchewan, Canada. Both raw and concentrated wastewater samples were subjected to the GeneXpert analysis. Results showed that the Saskatoon wastewater viral loads were significantly correlated to Saskatchewan's influenza and COVID-19 clinical cases, with a lead time of 10 days for IAV and a lag time of 4 days for SARS-CoV-2. Additionally, the GeneXpert analysis of the three cities' wastewater samples showed that the raw WS could capture the dynamics of SARS-CoV-2 and IAV due to their correlation with concentrated WS. Interestingly, IBV loads were not detected in any wastewater samples, while the Saskatoon and Prince Albert wastewater samples collected following the 2023 holiday season (end of December and beginning of January) were positive for RSV. This study indicates that the GeneXpert has excellent potential for use in the development of an early warning system for transmissible disease in municipalities and limited-resource communities while simultaneously providing stakeholders with an efficient WS methodology.

Assessment of seasonality and normalization techniques for wastewater-based surveillance in Ontario, Canada

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.

Understanding common population markers for SARS-CoV-2 RNA normalization in wastewater - A review

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.

Omicron COVID-19 Case Estimates Based on Previous SARS-CoV-2 Wastewater Load, Regional Municipality of Peel, Ontario, Canada

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.

An efficient method to enhance recovery and detection of SARS-CoV-2 RNA in wastewater

Wastewater surveillance (WS) of SARS-CoV-2 currently requires multiple steps and suffers low recoveries and poor sensitivity. Here, we report an improved analytical method with high sensitivity and recovery to quantify SARS-CoV-2 RNA in wastewater. To improve the recovery, we concentrated SARS-CoV-2 viral particles and RNA from both the solid and aqueous phases of wastewater using an electronegative membrane (EM). The captured viral particles and RNA on the EM were incubated in our newly developed viral inactivation and RNA preservation (VIP) buffer. Subsequently, the RNA was concentrated on magnetic beads and inhibitors removed by washing. Without eluting, the RNA on the magnetic beads was directly detected using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Analysis of SARS-CoV-2 pseudovirus (SARS-CoV-2 RNA in a noninfectious viral coat) spiked to wastewater samples showed an improved recovery of 80%. Analysis of 120 wastewater samples collected twice weekly between May 2021 and February 2022 from two wastewater treatment plants showed 100% positive detection, which agreed with the results independently obtained by a provincial public health laboratory. The concentrations of SARS-CoV-2 RNA in these wastewater samples ranged from 2.4×102 to 2.9×106 copies per 100 mL of wastewater. Our method's capability of detecting trace and diverse concentrations of SARS-CoV-2 in complex wastewater samples is attributed to the enhanced recovery of SARS-CoV-2 RNA and efficient removal of PCR inhibitors. The improved method for the recovery and detection of viral RNA in wastewater is important for wastewater surveillance, complementing clinical diagnostic tests for public health protection.

Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.

A wastewater-based risk index for SARS-CoV-2 infections among three cities on the Canadian Prairie

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.

Monitoring COVID-19 spread in selected Prague's schools based on the presence of SARS-CoV-2 RNA in wastewater

The COVID-19 pandemic has demanded a broad range of techniques to better monitor its extent. Owing to its consistency, non-invasiveness, and cost effectiveness, wastewater-based epidemiology has emerged as a relevant approach to monitor the pandemic's course. In this work, we analyzed the extent of the COVID-19 pandemic in five primary schools in Prague, the Czech Republic, and how different preventive measures impact the presence of SARS-CoV-2 RNA copy numbers in wastewaters. Copy numbers were measured by reverse transcription-multiplex quantitative real-time PCR. These copy numbers were compared to the number of infected individuals in each school identified through regular clinical tests. Each school had a different monitoring regime and subsequent application of preventive measures to thwart the spread of COVID-19. The schools that constantly identified and swiftly quarantined infected individuals exhibited persistently low amounts of SARS-CoV-2 RNA copies in their wastewaters. In one school, a consistent monitoring of infected individuals, coupled with a delayed action to quarantine, allowed for the estimation of a linear model to predict the number of infected individuals based on the presence of SARS-CoV-2 RNA in the wastewater. The results show the importance of case detection and quarantining to stop the spread of the pandemic and its impact on the presence of SARS-CoV-2 RNA in wastewaters. This work also shows that wastewater-based epidemiological models can be reliably used even in small water catchments, but difficulties arise to fit models due to the nonconstant input of viral particles into the wastewater systems.

VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples

BACKGROUND

The genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the Delta variant B.1.617.2 or Omicron variant B.1.1.529). Proportions of these variants circulating in a human population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample.

RESULTS

We propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluate the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of the Alpha variant.

CONCLUSIONS

VirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.

Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.

Wastewater-Based Epidemiology for SARS-CoV-2 Biomarkers: Evaluation of Normalization Methods in Small and Large Communities in Southern Germany

In the context of the COVID-19 pandemic, wastewater-based epidemiology (WBE) emerged as a useful tool to account for the prevalence of SARS-CoV-2 infections on a population scale. In this study, we analyzed wastewater samples from three large (>300,000 people served) and four small (<25,000 people served) communities throughout southern Germany from August to December 2021, capturing the fourth infection wave in Germany dominated by the Delta variant (B.1.617.2). As dilution can skew the SARS-CoV-2 biomarker concentrations in wastewater, normalization to wastewater parameters can improve the relationship between SARS-CoV-2 biomarker data and clinical prevalence data. In this study, we investigated the suitability and performance of various normalization parameters. Influent flow data showed strong relationships to precipitation data; accordingly, flow-normalization reacted distinctly to precipitation events. Normalization by surrogate viruses CrAssphage and pepper mild mottle virus showed varying performance for different sampling sites. The best normalization performance was achieved with a mixed fecal indicator calculated from both surrogate viruses. Analyzing the temporal and spatial variation of normalization parameters proved to be useful to explain normalization performance. Overall, our findings indicate that the performance of surrogate viruses, flow, and hydro-chemical data is site-specific. We recommend testing the suitability of normalization parameters individually for specific sewage systems.

RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern

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.

Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities

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.

Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities

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.

Wastewater Surveillance for SARS-CoV-2 RNA in Canada

Wastewater surveillance for SARS-CoV-2 RNA is a relatively recent adaptation of long-standing wastewater surveillance for infectious and other harmful agents. Individuals infected with COVID-19 were found to shed SARS-CoV-2 in their faeces. Researchers around the world confirmed that SARS-CoV-2 RNA fragments could be detected and quantified in community wastewater. Canadian academic researchers, largely as volunteer initiatives, reported proof-of-concept by April 2020. National collaboration was initially facilitated by the Canadian Water Network.

Many public health officials were initially skeptical about actionable information being provided by wastewater surveillance even though experience has shown that public health surveillance for a pandemic has no single, perfect approach. Rather, different approaches provide different insights, each with its own strengths and limitations. Public health science must triangulate among different forms of evidence to maximize understanding of what is happening or may be expected. Well-conceived, resourced, and implemented wastewater-based platforms can provide a cost-effective approach to support other conventional lines of evidence. Sustaining wastewater monitoring platforms for future surveillance of other disease targets and health states is a challenge. Canada can benefit from taking lessons learned from the COVID-19 pandemic to develop forward-looking interpretive frameworks and capacity to implement, adapt, and expand such public health surveillance capabilities.