Nipah virus (NiV) is a high-consequence zoonotic pathogen associated with severe neurological and respiratory disease, high case-fatality ratios (40 %–75 %), and documented human-to-human transmission, including in healthcare settings. Current surveillance for NiV remains predominantly clinical and reactive, limiting the ability of infection prevention and control (IPC) programs to implement proportionate measures prior to healthcare exposure. Wastewater-based surveillance (WBS) has emerged as a complementary surveillance approach capable of detecting novel viral outbreaks, often before clinical case recognition. WBS has now been operationalized for multiple pathogens relevant to human health but the usefulness of WBS for tracking NiV outbreaks has not yet been demonstrated. As a result, this narrative review synthesizes evidence on NiV animal and human infections, transmission dynamics, viral shedding, molecular detection methods, and environmental considerations to evaluate the plausibility of WBS as an IPC-supporting surveillance approach. We distinguish biological feasibility (NiV shedding into wastewater), technical feasibility (recovery and quantification of NiV RNA from wastewater matrices), and operational feasibility (implementation within BSL-4 biosafety and infrastructure constraints). The available evidence indicates that NiV shedding in urine and respiratory secretions provides a biologically plausible route by which viral RNA could enter wastewater, particularly from hospital effluents. However, human fecal shedding remains unconfirmed and the recovery, persistence, and partitioning of NiV RNA in wastewater have not been characterized. WBS for NiV is therefore biologically plausible but has not yet technically or operationally demonstrated. We suggest that targeted pilot studies and the development of independent, open-source RT-qPCR assays are required before NiV WBS could be considered for deployment.

Since the pandemic, interest in Wastewater and environmental surveillance (WES) has expanded rapidly, alongside advances in PCR-based detection and the need for reliable normalization strategies. One widely adopted approach to quantification in WES involves normalizing pathogen measurements using human-associated fecal biomarkers such as tobamoviruses. While pepper mild mottle virus and tomato brown rugose fruit virus have been extensively studied and utilized in hundreds of WES studies, the broader tobamovirus genus remains relatively underexplored. We reviewed over 270 published studies, assessed the suitability of 43 tobamoviruses for application as indicators of human fecal contamination or for normalization biomarkers for WES applications. Tobamoviruses were systematically evaluated based on host range, likelihood of human dietary exposure and gastrointestinal passage, environmental persistence, and evidence of detection in wastewater. This analysis identifies 11 tobamoviruses with significant potential as current or emerging biomarkers across diverse geographic and dietary contexts. Our analyses identify 11 tobamoviruses with significant potential as biomarkers across global wastewater contexts. Tobamoviruses have proven suitable for wastewater and environmental surveillance normalization due to their frequent and high-volume introduction into the human food chain through staple crops, in which they induce only mild or asymptomatic infections. This results in reliable, high-abundance measurements in municipal wastewater.

Introduction: Nipah virus (NiV) is a high-consequence zoonotic paramyxovirus with case-fatality ratios of 46–75% and documented human-to-human transmission, including in healthcare settings. Current surveillance is predominantly clinical and reactive, limiting early infection prevention and control (IPC) intervention before healthcare exposure occurs. Wastewater-based surveillance (WBS) has proven valuable for other pathogens, yet its utility for NiV remains unestablished. Methods: We conducted a narrative review of the published literature on NiV transmission dynamics, viral shedding in humans and animals, molecular detection methods, and the environmental stability of NiV RNA to evaluate the feasibility of WBS as an IPC-supporting early warning tool. A structured literature search was performed on February 1, 2026, across five databases using Publish or Perish, followed by duplicate removal, AI-assisted screening, and manual synthesis of relevant studies. Results: NiV RNA is shed in urine and respiratory secretions at 10³–10⁷ genome copies/mL, supporting biological plausibility for WBS detection. However, major barriers exist: no proof-of-concept WBS studies, limited data on RNA stability in tropical wastewater, lack of centralized sewerage in most endemic areas, and BSL-4 biocontainment constraints. Validated RT-qPCR assays targeting the nucleocapsid (N) gene provide the best foundation for future development. Recent outbreaks in Bangladesh and India (2025–2026) underscore the limitations of reactive clinical surveillance. Conclusions: WBS for NiV is biologically plausible but not yet feasible as a primary tool. Priority should be given to developing open-source RT-qPCR and ddPCR assays and conducting pilot studies in hospital wastewater, particularly from encephalitis wards. These should integrate into a broader One Health framework with targeted environmental sampling at pig farms, bat roosts, and date palm sap sites to improve outbreak preparedness. WBS is biologically plausible but not yet feasible as a primary NiV surveillance tool. We recommend the development and validation of optimized RT-qPCR assays for environmental NiV detection, alongside pilot studies in hospital wastewater settings, as preparedness measures ahead of future outbreaks.

The emergence of COVID-19 in Canada has led to over 4.9 million cases and 59,000 deaths by May 2024. Traditional clinical surveillance metrics (hospital admissions and clinical laboratory-positive cases) were complemented with wastewater and environmental monitoring (WEM) to monitor SARS-CoV-2 incidence. However, challenges in public health integration of WEM persist due to perceived limitations of WEM data quality, potentially driving inconsistent correlations variability and lead times. This study investigates how factors like population size, WEM measurement magnitude, site isolation status, hospital admissions, and clinical laboratory-positive cases affect WEM data correlations and variability in Ontario. The analysis uncovers a direct relationship between clinical surveillance data and the population size of the surveyed sewersheds, while WEM measurement magnitude was not directly impacted by population size. Higher variability in clinical surveillance data was observed in smaller sewersheds, likely reducing correlation strength for inferring COVID-19 incidence. Population size significantly influenced correlation quality, with thresholds identified at ∼66,000 inhabitants for strong WEM-hospital admissions correlations and ∼68,000 inhabitants for WEM-laboratory-positive cases during waned vaccination periods in Ontario (the Omicron BA.1 wave). During significant vaccination immunization (the Omicron BA.2 wave), these thresholds increased to ∼187,000 and 238,000, respectively. These findings highlight the benefit of WEM for strategic public health monitoring and interventions, especially in smaller communities. This study provides insights for enhancing public health decision making and disease monitoring through WEM, applicable to COVID-19 and potentially other diseases.

Clinical genomic surveillance is regarded as the gold standard for monitoring SARS-CoV-2 variants globally. However, as the pandemic wanes, reduced testing poses a risk to effectively tracking the trajectory of these variants within populations. Wastewater-based genomic surveillance that estimates variant frequency based on its defining set of alleles derived from clinical genomic surveillance has been successfully implemented. This method has its challenges, and allele-specific (AS) RT-qPCR or RT-dPCR may instead be used as a complementary method for estimating variant prevalence. Demonstrating equivalent performance of these methods is a prerequisite for their continued application in current and future pandemics. Here, we compared single-allele frequency using AS-RT-qPCR, to single-allele or haplotype frequency estimations derived from amplicon-based sequencing to estimate variant prevalence in wastewater during emergent and prevalent periods of Delta, Omicron, and two sub-lineages of Omicron. We found that all three methods of frequency estimation were concordant and contained sufficient information to describe the trajectory of variant prevalence. We further confirmed the accuracy of these methods by quantifying the diagnostic performance through Youden's index. The Youden's index of AS-RT-qPCR was reduced during the low prevalence period of a particular variant while the same allele in sequencing was negatively influenced due to insufficient read depth. Youden's index of haplotype-based calls was negatively influenced when alleles were common between variants. Coupling AS-RT-qPCR with sequencing can overcome the shortcomings of either platform and provide a comprehensive picture to the stakeholders for public health responses.

Abstract Background Clinical genomic surveillance is the gold standard for monitoring SARS-CoV-2 variants globally, but as the pandemic wanes, reduced testing increases the risk of missing the emergence of variants of concern or failing to accurately follow their trajectory in populations. Wastewater-based genomic surveillance (WWS) that estimates variant frequency based on its defining set of alleles derived from clinical genomic surveillance has been successfully implemented. However, this method has its challenges, and allele-specific (AS) RT-qPCR that monitors a single, variant-defining, allele is used as a complementary method for estimating variant prevalence. Demonstrating equivalent performance of the methods is a prerequisite for their continued application of WWS in current and future pandemics.Figure 1:Comparison of AS-RT-qPCR and amplicon-based sequencing methods for estimating SARS-CoV-2 variants frequency in wastewaters; A) N: D63G and B.1.617.2 haplotype, B) N: P13L and B.1.1.529 haplotype, C) S: H69+/V70+ and BA.1 haplotype, and D) S: H69-/V70- and BA.2 haplotype. Methods We compared single-allele frequency estimation using AS-RT-qPCR, to single-allele or haplotype frequency estimations derived from amplicon-based sequencing to estimate variant prevalence in municipal wastewater collected during emergent and prevalent periods of Delta, Omicron, and two of its sub-lineages in Ottawa, Canada.Table 1:Youden index of targeted alleles (N: D63G, N: P13L, S: H69+/V70+ and S: H69-/V70-) in wastewaters using AS-RT-qPCR and sequencing as well as haplotype of each variant. Results We found that all three methods of frequency estimation were concordant and contained sufficient information to describe the trajectory of variant prevalence in wastewater across time (Figure 1). We further evaluated the accuracy of these methods by quantifying the diagnostic performance (i.e., method accuracy expressed as Youden’s index), based on available clinical genomic prevalence data. Youden’s index confirms the accuracy of methods employed for variant frequency estimation in wastewater (Table 1), but accuracy of each method can be influenced by different factors. Conclusion WWS emerges as a crucial epidemiological tool for monitoring infectious disease in the population during the COVID-19 pandemic. This study validates the accuracy of WWS in SARS-CoV-2 variants monitoring using AS-RT-qPCR or sequencing methods and provides comprehensive perspective for implementing public health interventions against infectious diseases. Disclosures All Authors: No reported disclosures

Passive sampling has proven to be a reliable and cost-effective method in wastewater and environmental surveillance (WES) during the COVID-19 pandemic. In passive sampling, wastewater solids were collected from the wastewater networks, homogenized in solutes and analyzed the supernatant to measure the SARS-CoV-2 RNA concentrations in wastewater. However, the direct impact of wastewater solids content collected via passive sampling on SARS-CoV-2 RNA measurements has not been previously evaluated. In this study, we analyzed wastewater solids collected using Auto, Torpedo, COSCa-ball samplers, and primary sludge samples from a wastewater treatment plant to measure SARS-CoV-2 RNA concentrations in wastewater. Results showed significant variation (p < 0.05) in wastewater solids content (i.e., TS and VS) across Auto, Torpedo, COSCa-ball samplers, and primary sludge samples. Despite differences in solids content, SARS-CoV-2 RNA concentrations in wastewater solids from passive samplers can be effectively compared (p > 0.05) to autosampler and primary sludge samples. To evaluate the influences of wastewater solids content on SARS-CoV-2 RNA measurement, we used a linear mixed-effects model. The model demonstrated that wastewater solids content had no direct effect on SARS-CoV-2 RNA measurements across the sampling methods and primary sludge samples. Overall, this study established a standardized experimental approach for implementing passive samplers as a viable alternative to conventional autosampler in WES for emerging pathogens.

The global wastewater-based epidemiology (WBE) landscape has primarily concentrated on high-profile diseases, creating a narrow scope of application. However, there's a significant and significant untapped potential in using WBE to address chronic and noncommunicable diseases (NCDs), particularly in developing nations. NCDs, including heart disease and diabetes, now significantly impact low- and middle-income nations, straining their healthcare systems and economies. WBE offers a cost-effective, real-time health monitoring solution and presents a real opportunity for change in global research policy focus to hone into these diseases. By prioritizing research on the detection of chronic illness health markers in wastewater, WBE has the potential to provide accurate community-level health data and guide equitable resource allocation, addressing both high-profile infectious diseases and NCDs simultaneously. However, the potential of WBE in addressing NCDs remains largely untapped by the research community. Effective implementation requires the development of standardized methodologies, effective ethical frameworks, and robust international cooperation. This approach is essential to address the silent epidemic of NCDs effectively and ensure that developing nations are equipped with the tools necessary for sustainable healthcare management and evidence-based policymaking.

Wastewater genomic surveillance (WWGS) of SARS-CoV-2 is typically performed using influent wastewater, but the approach is challenging due to degradation as well as low target concentrations in wastewater. This could be alleviated by utilizing primary sludge; however, this matrix is prone to sequencing library failures. Our study focuses on developing a robust primary sludge-based SARS-CoV-2 genome sequencing method. The study was conducted using 30 parallel influent wastewater and primary sludge samples collected during three different time periods, under three clinically predominant SARS-CoV-2 Omicron lineages in Ottawa, Canada. Results showed that our approach consistently recovered near-complete (≥90%) SARS-CoV-2 genomes from both influent wastewater and primary sludge samples. Prevalent lineage and single nucleotide variant (SNV) profiles were identical (p > 0.05) between influent wastewater and primary sludge. Further analysis indicated that a similar (p > 0.05) number of rare SNVs were detected between influent wastewater and primary sludge. Overall, our approach enables the sequencing of the most concentrated sources of genetic material within the wastewater matrix, providing valuable insights for public health forecasting of infectious disease prevalence beyond the COVID-19 pandemic.

ADVERTISEMENT RETURN TO ISSUEPREVViewpointNEXTA Call to Wastewater Researchers to Support Phage Therapy in the Global Fight against Antibiotic ResistanceOcean Thakali*Ocean ThakaliDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaChildren's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, Canada*[email protected]More by Ocean ThakaliView Biographyhttps://orcid.org/0000-0002-6649-2322, Shen WanShen WanDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Shen Wan, Md. Pervez KabirMd. Pervez KabirDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Md. Pervez Kabir, Xin TianXin TianDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Xin Tian, Patrick D'AoustPatrick D'AoustDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Patrick D'Aoust, Anand TiwariAnand TiwariExpert Microbiology Unit, Finnish Institute for Health and Welfare, 70701 Kuopio, FinlandMore by Anand Tiwari, Kyle BibbyKyle BibbyDepartment of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United StatesMore by Kyle Bibbyhttps://orcid.org/0000-0003-3142-6090, Samendra SherchanSamendra SherchanCenter of Research Excellence in Wastewater-based Epidemiology, Morgan State University, Baltimore, Maryland 21251, United StatesMore by Samendra Sherchan, Charles GerbaCharles GerbaWater & Energy Sustainable Technology Center, University of Arizona, Tucson, Arizona 85745, United StatesMore by Charles Gerba, Anthony William MaressoAnthony William MaressoTAILΦR Laboratories, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas 77030, United StatesMore by Anthony William Maresso, Tyson GraberTyson GraberChildren's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, CanadaMore by Tyson Graber, and Robert DelatollaRobert DelatollaDepartment of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, CanadaMore by Robert DelatollaCite this: ACS EST Water 2024, 4, 4, 1177–1179Publication Date (Web):February 7, 2024Publication History Received29 December 2023Accepted23 January 2024Revised20 January 2024Published online7 February 2024Published inissue 12 April 2024https://doi.org/10.1021/acsestwater.3c00844Copyright © 2024 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views766Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (2 MB) Get e-AlertscloseSUBJECTS:Antibiotic resistance,Bacteria,Therapeutics,Viruses,Wastewater Get e-Alerts

During the COVID-19 pandemic, the Province of Ontario, Canada, launched a wastewater surveillance program to monitor SARS-CoV-2, inspired by the early work and successful forecasts of COVID-19 waves in the city of Ottawa, Ontario. This manuscript presents a dataset from January 1, 2021, to March 31, 2023, with RT-qPCR results for SARS-CoV-2 genes and PMMoV from 107 sites across all 34 public health units in Ontario, covering 72% of the province's and 26.2% of Canada's population. Sampling occurred 2-7 times weekly, including geographical coordinates, serviced populations, physico-chemical water characteristics, and flowrates. In doing so, this manuscript ensures data availability and metadata preservation to support future research and epidemic preparedness through detailed analyses and modeling. The dataset has been crucial for public health in tracking disease locally, especially with the rise of the Omicron variant and the decline in clinical testing, highlighting wastewater-based surveillance's role in estimating disease incidence in Ontario.

Wastewater surveillance (WWS) of SARS-CoV-2 has become a crucial tool for monitoring COVID-19 cases and outbreaks. Previous studies have indicated that SARS-CoV-2 RNA measurement from testing solid-rich primary sludge yields better sensitivity compared to testing wastewater influent. Furthermore, measurement of pepper mild mottle virus (PMMoV) signal in wastewater allows for precise normalization of SARS-CoV-2 viral signal based on solid content, enhancing disease prevalence tracking. However, despite the widespread adoption of WWS, a knowledge gap remains regarding the impact of ferric sulfate coagulation, commonly used in enhanced primary clarification, the initial stage of wastewater treatment where solids are sedimented and removed, on SARS-CoV-2 and PMMoV quantification in wastewater-based epidemiology. This study examines the effects of ferric sulfate addition, along with the associated pH reduction, on the measurement of SARS-CoV-2 and PMMoV viral measurements in wastewater primary clarified sludge through jar testing. Results show that the addition of Fe 3+ concentrations in the conventional 0 to 60 mg/L range caused no effect on SARS-CoV-2 N1 and N2 gene region measurements in wastewater solids. However, elevated Fe 3+ concentrations were shown to be associated with a statistically significant increase in PMMoV viral measurements in wastewater solids, which consequently resulted in the underestimation of PMMoV-normalized SARS-CoV-2 viral signal measurements (N1 and N2 copies/copies of PMMoV). The observed pH reduction from coagulant addition did not contribute to the increased PMMoV measurements, suggesting that this phenomenon arises from the partitioning of PMMoV viral particles into wastewater solids.

Wastewater-based surveillance (WBS) is increasingly used for monitoring disease targets in wastewaters around the world. This study, performed in Ottawa, Canada, identifies a decrease in SARS-CoV-2 wastewater measurements during snowmelt-induced sewer flushing events. Observations first revealed a correlation between suppressed viral measurements and periods of increased sewage flowrates, air temperatures above 0 °C during winter months, and solids mass flux increases. These correlations suggest that high sewage flowrates from snowmelt events or intense precipitation events lead to the scouring of previously settled solids in sewers and the subsequent entrainment of these solids into the transported wastewaters. Collection of WBS samples during flushing events hence contains a heterogeneous mixture of solids, including resuspended solids with varying degrees of decay. Therefore flushing events can present a challenge for accurately measuring disease target viral signals when using solids-based analytical methods. This study demonstrates that resuspended solids entrained in the wastewaters during flushing events retain PMMoV signal while the SARS-CoV-2 signal is significantly reduced due to the slower decay rate of pepper mild mottle virus (PMMoV) compared to SARS-CoV-2 within wastewaters. Hence current normalization methods using PMMoV are shown to be ineffective in correcting for flushing events and the associated resuspension of settled solids, as the PMMoV signal of settled solids within sewers does not account for the differential decay rates experiences by SARS-CoV-2 signal in settled solids. Instead, this study identifies RNA to PMMoV correction factor as an effective approach to correct for flushing events and to realign SARS-CoV-2 signal with COVID-19 hospital admission rates within communities. As such, the study highlights the key physicochemical parameters necessary to identify flushing events that affect SARS-CoV-2 WBS measurements and introduces a novel RNA to PMMoV correction factor approach for solids-based analysis of SARS-CoV-2 during flushing events, enhancing the accuracy of WBS data for public health decision-making.

Wastewater-based surveillance of human disease offers timely insights to public health, helping to mitigate infectious disease outbreaks and decrease downstream morbidity and mortality. These systems rely on nucleic acid amplification tests for monitoring disease trends, while antibody-based seroprevalence surveys gauge community immunity. However, serological surveys are resource-intensive and subject to potentially long lead times and sampling bias. We identified and characterized a human antibody repertoire, predominantly secretory IgA, isolated from a central wastewater treatment plant and building-scale wastewater collection points. These antibodies partition to the solids fraction and retain immunoaffinity for SARS-CoV-2 and Influenza A virus antigens. This stable pool could enable real-time tracking for correlates of vaccination, infection, and immunity, aiding in establishing population-level thresholds for immune protection and assessing the efficacy of future vaccine campaigns.

This study presents a comprehensive analysis of the decay patterns of endogenous SARS-CoV-2 and Pepper mild mottle virus (PMMoV) within wastewaters spiked with stool from infected patients expressing COVID-19 symptoms, and hence explores the decay of endogenous SARS-CoV-2 and PMMoV targets in wastewaters from source to collection of the sample. Stool samples from infected patients were used as endogenous viral material to more accurately mirror real-world decay processes compared to more traditionally used lab-propagated spike-ins. As such, this study includes data on early decay stages of endogenous viral targets in wastewaters that are typically overlooked when performing decay studies on wastewaters harvested from wastewater treatment plants that contain already-degraded endogenous material. The two distinct sewer transport conditions of dynamic suspended sewer transport and bed and near-bed sewer transport were simulated in this study at temperatures of 4 °C, 12 °C and 20 °C to elucidate decay under these two dominant transport conditions within wastewater infrastructure. The dynamic suspended sewer transport was simulated over 35 h, representing typical flow conditions, whereas bed and near-bed transport extended to 60 days to reflect the prolonged settling of solids in sewer systems during reduced flow periods. In dynamic suspended sewer transport, no decay was observed for SARS-CoV-2, PMMoV, or total RNA over the 35-h period, and temperature ranging from 4 °C to 20 °C had no noticeable effect. Conversely, experiments simulating bed and near-bed transport conditions revealed significant decreases in SARS-CoV-2 and total RNA concentrations by day 2, and PMMoV concentrations by day 3. Only PMMoV exhibited a clear trend of increasing decay constant with higher temperatures, suggesting that while temperature influences decay dynamics, its impact may be less significant than previously assumed, particularly for endogenous RNA that is bound to dissolved organic matter in wastewater. First order decay models were inadequate for accurately fitting decay curves of SARS-CoV-2, PMMoV, and total RNA in bed and near-bed transport conditions. F-tests confirmed the superior fit of the two-phase decay model compared to first order decay models across temperatures of 4 °C-20 °C. Finally, and most importantly, total RNA normalization emerged as an appropriate approach for correcting the time decay of SARS-CoV-2 exposed to bed and near-bed transport conditions. These findings highlight the importance of considering decay from the point of entry in the sewers, sewer transport conditions, and normalization strategies when assessing and modelling the impact of viral decay rates in wastewater systems. This study also emphasizes the need for ongoing research into the diverse and multifaceted factors that influence these decay rates, which is crucial for accurate public health monitoring and response strategies.

IntroductionDetection of community respiratory syncytial virus (RSV) infections informs the timing of immunoprophylaxis programs and hospital preparedness for surging pediatric volumes. In many jurisdictions, this relies upon RSV clinical test positivity and hospitalization (RSVH) trends, which are lagging indicators. Wastewater-based surveillance (WBS) may be a novel strategy to accurately identify the start of the RSV season and guide immunoprophylaxis administration and hospital preparedness.MethodsWe compared citywide wastewater samples and pediatric RSVH in Ottawa and Hamilton between August 1, 2022, and March 5, 2023. 24-h composite wastewater samples were collected daily and 5 days a week at the wastewater treatment facilities in Ottawa and Hamilton, Ontario, Canada, respectively. RSV WBS samples were analyzed in real-time for RSV by RT-qPCR.ResultsRSV WBS measurements in both Ottawa and Hamilton showed a lead time of 12 days when comparing the WBS data set to pediatric RSVH data set (Spearman’s ρ = 0.90). WBS identify early RSV community transmission and declared the start of the RSV season 36 and 12 days in advance of the provincial RSV season start (October 31) for the city of Ottawa and Hamilton, respectively. The differing RSV start dates in the two cities is likely associated with geographical and regional variation in the incidence of RSV between the cities.DiscussionQuantifying RSV in municipal wastewater forecasted a 12-day lead time of the pediatric RSVH surge and an earlier season start date compared to the provincial start date. These findings suggest an important role for RSV WBS to inform regional health system preparedness, reduce RSV burden, and understand variations in community-related illness as novel RSV vaccines and monoclonal antibodies become available.

Recent MPOX viral resurgences have mobilized public health agencies around the world. Recognizing the significant risk of MPOX outbreaks, large-scale human testing, and immunization campaigns have been initiated by local, national, and global public health authorities. Recently, traditional clinical surveillance campaigns for MPOX have been complemented with wastewater surveillance (WWS), building on the effectiveness of existing wastewater programs that were built to monitor SARS-CoV-2 and recently expanded to include influenza and respiratory syncytial virus surveillance in wastewaters. In the present study, we demonstrate and further support the finding that MPOX viral fragments agglomerate in the wastewater solids fraction. Furthermore, this study demonstrates that the current, most commonly used MPOX assays are equally effective at detecting low titers of MPOX viral signal in wastewaters. Finally, MPOX WWS is shown to be more effective at passively tracking outbreaks and/or resurgences of the disease than clinical testing alone in smaller communities with low human clinical case counts of MPOX.