Occurrence of multiple respiratory viruses in wastewater in Queensland, Australia: Potential for community disease surveillance

Seasonal surveillance of various pathogenic viruses in wastewater using a high-throughput PCR system and comparison of two concentration methods

In recent years, the analysis of viruses in wastewater has become a recognized method to monitor the circulation of pathogenic viruses within the populations. This non-invasive and integrated approach is all the more strategic as many viral pathogens can be released in sewage. There is currently no standard method for the virological analysis of wastewater, and various protocols have been developed to concentrate and detect viruses in this matrix. This study aims to develop a high-throughput qPCR detection system to describe the occurrence of 30 human enteric and respiratory viruses in influent and effluent wastewater samples collected in the Paris area during two periods in 2023. The influence of the concentration method (ultracentrifugation or aluminium hydroxide adsorption-precipitation) for the recovery of viruses from wastewater samples was also investigated. The ultracentrifugation-based method allowed a higher viral recovery (4.95-100 % versus 0.77-33 % for the precipitation-based method), especially in effluent waters. The PCR array revealed the presence of many pathogenic viruses, with marked seasonal variations mainly for respiratory viruses. This system is particularly suitable for the rapid, sensitive, and specific detection of multiple viruses in wastewater.

Influenza RNA fluxes monitoring in wastewater as a complementary epidemiological surveillance indicator: A four-year nationwide study in Luxembourg

Wastewater surveillance has demonstrated success in monitoring SARS-CoV-2 in communities, indicating potential for extension to other respiratory viruses. This study investigates influenza A and B viruses (IAV; IBV) in raw urban wastewater over a 4-year period, introducing two key concepts: the use of viral RNA fluxes instead of concentration measurements and the determination of epidemiological parameters directly from wastewater data. The estimation of daily fluxes, representing the number of viral genome copies per day per 100,000 inhabitants, offers an integrative approach that combines microbiological and hydrological measurements to better assess viral particle dynamics in a water system. A total of 1013 wastewater samples collected between March 2020 and March 2024 from Luxembourg's four largest wastewater treatment plants (covering about 52 % of the population) were analysed using RT-qPCR and RT-droplet digital PCR (RT-ddPCR), following concentration of viral particles by ultrafiltration. Data on the presence of IAV and IBV were expressed as either detection rates or fluxes. Significant correlations were observed between the number of laboratory-confirmed influenza cases and both wastewater detection rates (RT-qPCR: Spearman ρ = 0.52; RT-ddPCR: ρ = 0.61, p-value <10-13) and viral RNA fluxes (RT-ddPCR: ρ = 0.64, p-value <10-15). More importantly, our results demonstrated that critical influenza seasonality parameters (start, peak and end weeks of the epidemic) can be effectively determined from wastewater data. These findings establish wastewater surveillance as a cost-effective, non-invasive approach to support and complement existing influenza surveillance programs, with potential applications for other respiratory pathogens.

In-depth comparison of untargeted and targeted sequencing for detecting virus diversity in wastewater

Sequencing approaches may enable monitoring of a broad range of viruses in wastewater, including potential emerging and non-reportable human viruses. Considering the fact that metagenomic sequencing may be non-specific for low-abundance human viruses, integration of viral amplification and enrichment strategies are proposed to enhance the accurate detection of a broad range of human viruses in municipal wastewater. In this study, we focused on the in-depth comparison analysis of three untargeted amplification methods (Multiple Displace Amplification [MDA], Reverse Transcription - MDA [RT-MDA], and a PCR-based random amplification [PCR-based]) and one targeted method (Twist Comprehensive Viral Research Panel [TWIST]) for detecting virus diversity in wastewater. In addition, we included the comparisons of two extraction kits (Qiagen QIAamp VIRAL RNA Mini Kit and ZymoBIOMICSTM DNA/RNA Minipre Kit) and four virus identification tools (Diamond blast, Kraken2, VirSorter2 and geNomad) for a systematic study. Performances of Qiagen and Zymo extraction kits in recovering viruses and human viruses in wastewater were comparable. By the three untargeted methods we detected 12,808 contigs with lengths longer than 10,000 bp. No contig longer than 10,000 bp was detected by the targeted method. Presence of human viruses were analyzed further by comparing the viral contigs against a custom Swiss-Prot human virus database. There were 45 viruses that are potentially associated with human health found in wastewater, 8 of them were unique to the targeted method and 7 of them were unique to the three untargeted methods. Four enteric viruses Mamastrovirus, Norovirus, Rotavirus and Sapovirus were detected with high abundance in samples prepared with the targeted method. Dimensional scaling analysis demonstrated the divergent virus and human virus communities from the untargeted and targeted methods. Patterns of virus and human virus populations identified by Kraken2 and geNomad were similar. Presence of selected viruses (SARS-CoV-2 [N1&N2], SC2, RSV, Norovirus GI and GII) were confirmed with ddPCR. This work indicates integration of untargeted and targeted sequencing methods, and complementary ddPCR can ensure the accurate detection of known and novel viruses using wastewater surveillance.

Defining alarm thresholds for the load of pathogenic viruses in wastewater for decision making: An application to three French cities

Wastewater monitoring has the potential to complement infectious disease surveillance systems. However, the absence of predefined viral signal thresholds in wastewater is often presented as a limiting factor in triggering public health action. To overcome this issue, the feasibility of defining alarm threshold for viral loads in wastewater samples was assessed by quantifying genome fragments of SARS-CoV-2, influenza A virus (IAV), respiratory syncytial virus (RSV), norovirus (NoV), and rotavirus (RoV) by RT-digital PCR (dPCR) in untreated wastewater samples from three treatment plants. Cut-point values were calculated for periods with a high rate of visits to emergency rooms or at-home visits by SOS Médecins for the related diseases. ROC curves were constructed, and the values of alarm threshold in wastewater were defined using the Youden index. For each targeted virus, alarm thresholds were close to each other across the three WWTPs. As indicated by likelihood ratios, evidence to rule in the diagnosis of high rate of visits when the alarm threshold was exceeded ranged from weak to strong and was highest for RSV and SARS-CoV-2. Evidence to rule out the diagnosis when the alarm threshold was not exceeded was strong or moderate for IAV, SARS-CoV-2 and RSV. Diagnostic performance of the test was not as high for NoV and RoV. Positive predictive value was highest for SARS-CoV-2 and RSV. For SARS-CoV-2 and RSV, the definition of an alarm threshold in wastewater could substantially inform the diagnosis of a period with a high rate of medical visits for COVID-19 and bronchiolitis, respectively.

Wastewater-Based Surveillance of Respiratory Syncytial Virus Reveals a Temporal Disconnect in Disease Trajectory across an Active International Land Border

Conventional metrics for tracking infectious diseases, including case and outbreak data and syndromic surveillance, can be resource-intensive, misleading, and comparatively slow with prolonged data collection, analysis and authentication. This study examined the 2022-2023 Respiratory Syncytial Virus (RSV) season in a contiguous metropolitan area connected by an active international land border, affording an opportunity for comparison of the respiratory virus season spanning two independent public health jurisdictions. Time-lagged cross correlation and qualitative examination of the wastewater signals showed that the peak of the Detroit (MI, USA) RSV season predated the peak in Windsor (ON, Canada) by approximately 5 weeks. A strong positive relationship was observed between RSV N-gene concentrations in wastewater and hospitalization rates in Windsor-Essex (Kendall's τ = 0.539, p ≤ 0.001, Spearman's ρ = 0.713, p ≤ 0.001) as well as Detroit (Kendall's τ = 0.739, p ≤ 0.001, Spearman's ρ = 0.888, p ≤ 0.001). This study demonstrated that wastewater surveillance can reveal regional differences in infection dynamics between communities and can provide an independent measure of the prevalence of RSV, an underreported disease. These findings support the use of wastewater surveillance as a cost-effective tool in monitoring of RSV to enhance existing surveillance systems and to better inform public health disease mitigation strategies.

Sewage surveillance revealed the seasonality and prevalence of respiratory syncytial virus and its implications for seasonal immunization strategy in low and middle-income regions of China

Respiratory syncytial virus (RSV) represents a significant global health threat, with a disproportionately high disease burden in low and middle-income regions (LMIRs). Estimating the prevalence of RSV infection at the community levels remains a huge challenge, particularly in LMIRs where clinical data are scarce. In this study, we first detected RSV RNA in the fecal samples from 300 patients to understand the fecal shedding patterns of RSV. Meanwhile, we conducted sewage surveillance of RSV in four geographically distinct LMIRs in China from April 2023 to June 2024. Real-time reverse transcription quantitative Polymerase Chain Reaction (RT-qPCR) was employed to monitor the dynamics of sewage RSV concentration in a typical sewershed from Yingkou, Xi'an, Nanchang, and Nanning, respectively. Subsequent amplicon sequencing was conducted to understand the genotype and mutations of sewage RSV. Through RT-qPCR, we observed two RSV epidemics that lasted from late April to May and October to February in both Yingkou and Xi'an. For Nanchang, only one RSV epidemic was observed which emerged from September to February. Notably, in Nanning, a prolonged RSV epidemic was observed from August to April, suggesting RSV vaccination in Nanning faced more challenges. Amplicon sequencing revealed that sewage RSV found in four LMIRs is genetically distinct, highlighting the need for local initiatives for wastewater monitoring of RSV. This study filled the gaps in previous assessment of suitability of RSV vaccination in LMIRs based on clinical surveillance, demonstrating the effectiveness of wastewater surveillance in guiding public health interventions.

Characterising the asynchronous resurgence of common respiratory viruses following the COVID-19 pandemic

The COVID-19 pandemic and relevant non-pharmaceutical interventions (NPIs) interrupted the circulation of common respiratory viruses. These viruses demonstrated an unprecedented asynchronous resurgence as NPIs were relaxed. We compiled a global dataset from a systematic review, online surveillance reports and unpublished data from Respiratory Virus Global Epidemiology Network, encompassing 92 sites. We compared the resurgence timings of respiratory viruses within each site and synthesised differences in timings across sites, using a generalised linear mixed-effects model. We revealed a distinct sequential timing in the first post-pandemic resurgence: rhinovirus resurged the earliest, followed by seasonal coronavirus, parainfluenza virus, respiratory syncytial virus, adenovirus, metapneumovirus and influenza A virus, with influenza B virus exhibiting the latest resurgence. Similar sequential timing was observed in the second resurgence except influenza A virus caught up with metapneumovirus. The consistent asynchrony across geographical regions suggests that virus-specific characteristics, rather than location-specific factors, determining the relative timing of resurgence.

Parasites in Sewage: Legal Requirements and Diagnostic Tools

Despite the vast amount of water on Earth, only a small percent is suitable for consumption, and these resources are diminishing. Moreover, water resources are unevenly distributed, leading to significant disparities in access to drinking water between countries and populations. Increasing consumption and the expanding human population necessitate the development of novel wastewater treatment technologies and the use of water treatment byproducts in other areas, such as fertilisers. However, water treatment sludge often cannot be used to enhance crop production due to the presence of parasite eggs, particularly from roundworms (Ascaridae family), which are resistant to environmental factors and can pose a threat for several years. Legislation prohibits the use of sludge containing parasite eggs as fertiliser. In some cases, water may not contain parasite eggs but larvae, which require different detection methods. Additionally, the presence of eggs does not necessarily indicate danger since they may lose infectivity due to prolonged storage or exposure to chemical compounds in the sewage. This paper reviews European Union regulations on wastewater treatment, the selected parasitic diseases related to the presence of parasites in wastewater, the spectrum of detection methods, and highlights differences in viability and invasiveness, which is intended to draw attention to the need to determine both biological properties of parasites.

Wastewater-based estimation of temporal variation in shedding amount of influenza A virus and clinically identified cases using the PRESENS model

Wastewater-based estimation of infectious disease prevalence in real-time assists public health authorities in developing effective responses to current outbreaks. However, wastewater-based estimation for IAV remains poorly demonstrated, partially because of a lack of knowledge about temporal variation in shedding amount of an IAV-infected person. In this study, we applied two mathematical models to previously collected wastewater and clinical data from four U.S. states during the 2022/2023 influenza season, dominated by the H3N2 subtype. First, we modeled the relationship between the detection probability of IAV in wastewater and FluA case counts, using a logistic function. The model revealed that a 50 % probability of IAV detection in wastewater corresponds to 0.53 (95 % CrI: 0.35-0.78) cases per 100,000 people, as observed in clinical surveillance over two weeks. Next, we applied the previously developed PRESENS model to IAV wastewater concentration data from California, revealing rapid and prolonged virus shedding patterns. The estimated shedding model was incorporated into an extended version of the PRESENS model to assess the variability in the relationship between IAV concentrations and case numbers across other states, including Massachusetts, New Jersey, and Utah. As a result, our analysis demonstrated the effectiveness of normalizing IAV concentrations with PMMoV (Pepper mild mottle virus) to accurately understand spatial distribution patterns of IAV prevalence. We successfully estimated FluA case counts from wastewater concentrations within a factor of two for 80 % of data from a state where 34 % of the state population was monitored by wastewater surveillance. Importantly, wastewater-based estimates provided real-time or leading insights (0-2 days) compared to clinical case detection in the three states, enabling early understanding of the incidence trends by limiting delays in data publication. These findings highlight the potential of wastewater surveillance to detect IAV outbreaks in near real-time and enhance efficiency of the infectious disease management.

Evaluation of Trends in Influenza A and B Viruses in Wastewater and Human Surveillance Data: Insights from the 2022-2023 Season in Italy

Wastewater-based epidemiology (WBE) is a recognized, dynamic approach to monitoring the transmission of pathogens in communities through urban wastewater. This study aimed to detect and quantify influenza A and B viruses in Italian wastewater during the 2022-2023 season (October 2022 to April 2023). A total of 298 wastewater samples were collected from 67 wastewater treatment plants (WTPs) across the country. These samples were analyzed for influenza A and B viruses (IAV, IBV) using primers originally developed by the Centers for Disease Control and Prevention (CDC) for real-time PCR and adapted for digital PCR. The overall detection rates of IAV and IBV across the entire study period were 19.1% and 16.8%, respectively. The prevalence of IAV in wastewater showed a gradual increase from October to December 2022, peaking at 61% in December. In contrast, IBV peaked at 36% in February 2023. This temporal discrepancy in peak concentrations suggests different seasonal patterns for the two influenza types. These trends mirrored human surveillance data, which showed influenza A cases peaking at 46% in late December and declining to around 2% by April 2023, and influenza B cases starting to increase significantly in January 2023 and peaking at about 14% in March. IAV concentrations ranged from 9.80 × 102 to 1.94 × 105 g.c./L, while IBV concentrations ranged from 1.07 × 103 to 1.43 × 104 g.c./L. Overall, the environmental data were consistent with the human surveillance trends observed during the study period in the country. These results demonstrate the value of WBE in tracking epidemiological patterns and highlight its potential as a complementary tool to infectious diseases surveillance systems.

First detection of Hepatitis E virus (Rocahepevirus ratti) in French urban wastewater: Potential implications for human contamination

Hepatitis E virus (HEV) is considered as an emerging zoonotic pathogen circulating in a wide range of animals. In recent decades, the genus Paslahepevirus frequently isolated in pigs were the most involved in human clinical practice. In addition, the genus Rocahepevirus have been isolated in rodents, and transmission to humans is increasingly reported worldwide, although gaps remain regarding the exposure factors. In this study, the presence of HEV was investigated in urban wastewater, swine slaughterhouse wastewater and river waters, in a geographical area where its circulation had previously been reported. In addition to the expected detection of Paslahepevirus in almost all waters samples collected, Rocahepevirus strains were detected with the same frequencies in urban and river waters, at concentrations up to 40-fold higher. No Rocahepeviruses were detected in swine slaughterhouse wastewater. This is the first study demonstrating the presence of Rocahepevirus in French wastewater. Although no evidence of transmission was reported among patients followed for a suspected HEV infection in the same area between April 2019 and October 2023 (i.e. 135/3078 serological tests positive for anti-HEV IgM detection; 46/822 blood samples positive for Paslahepevirus genome detection but none for Rocahepevirus), the circulation of Rocahepevirus in waters in such concentrations raises the question of the possible zoonotic transmission to human. Indeed, the waterborne transmission of HEV is now well documented in industrialized countries, and the exploration of the growing number of human infections in Europe involving Rocahepevirus has not until now made it possible to clarify the transmission routes.

Wastewater-based effective reproduction number and prediction under the absence of shedding information

Estimating effective reproduction number (Re) and predicting disease incidences are essential to formulate effective strategies for disease control. Although recent studies developed models for inferring Re from wastewater-based data, they require information on shedding dynamics. Here, we proposed a framework of Re estimation and prediction without shedding information. The framework consists of a space-state model for smoothing wastewater-based data and a renewal equation modified for wastewater-based data. The applicability of the framework was tested with simulated data and real-world data on Influenza A virus (IAV) and SARS-CoV-2 concentration in wastewater in 2022/2023 season in the USA. We confirmed the state-space model effectively fits various simulated epidemic curves and real-world data. In simulations, we found wastewater-based Re (Reww) closely aligns with instantaneous clinical Re when shedding dynamics are rapid. For more prolonged shedding, Reww approximates a smoothed Re over time. We also observed the necessary sampling frequency to trace dynamics of wastewater concentration and Reww accurately in the framework varies depending on the precision of detection methods, the epidemic status, the transmissibility of infectious diseases, and shedding dynamics. By applying our framework to real-world data, we found Reww for SARS-CoV-2 showed similar trend and values to clinically-based Re. Reww for IAV ranged from 0.66 to 1.52 with a clear peak in the winter season, which agrees with previously reported Re. We also succeeded in predicting wastewater concentration in a few weeks from available wastewater-based data. These results indicate that our framework potentially enables near real-time monitoring of approximated Re and prediction of infectious disease dynamics through wastewater surveillance, which limits the delay between infection and reporting. Our framework is useful especially for regions where reliable clinical surveillance is not available and notifiable surveillance is abolished, and can be expanded to multiple infectious diseases that have been detected from wastewater.

Monitoring Influenza A (H1N1, H3N2), RSV, and SARS-CoV-2 Using Wastewater-Based Epidemiology: A 2-Year Longitudinal Study in an Indian Megacity Covering Omicron and Post-Omicron Phases

The bourgeoning field of wastewater-based epidemiology (WBE) for the surveillance of several respiratory viruses which includes Influenza A, H1N1pdm09, H3N2, respiratory syncytial viruses (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of interest for public health concerns. However, there are few long-term monitoring studies globally. In this study, respiratory viruses were detected and quantified from 11 sewer sheds by utilizing reverse transcription-quantitative polymerase chain reaction analysis in Pune city, India, from Jan 2022 to Dec 2023. The RNA fragments of respiratory viruses were detected in sewage samples before clinical cases were reported, underscoring the potential of WBE for early detection and monitoring within the population. The Spearman correlation of wastewater viral copies was positively and significantly correlated with the clinically positive case of H1N1pdm09 (ρ = 0.55, p = 1.4 × 10-9), H3N2 (ρ = 0.25, p = 9.9 × 10-3), and SARS-CoV-2 (ρ = 0.43, p = 4.1 × 10-6). The impact of public health interventions on the circulation of infectious respiratory diseases showed a significant difference in the viral load during the period when many preventing measures were carried out against the COVID-19 pandemic (restriction phase), compared to the period when no such preventive measures are followed (no-restriction phase) for Influenza A, H1N1pdm09, H3N2, and RSV with p-value < 0.05, which indicates the influence of health policy implementation in controlling disease spread. The present study provides an effective approach to detecting multiple respiratory viruses from wastewater and provides insights into the epidemiology of respiratory illnesses. The WBE aids in providing information on the spread of pathogens (viruses) in the community, offering a proactive strategy for public health management, allowing for timely interventions and implementing targeted measures to mitigate the spread of these viruses under one health approach.

Estimating epidemic trajectories of SARS-CoV-2 and influenza A virus based on wastewater monitoring and a novel machine learning algorithm

The COVID-19 pandemic has altered the circulation of non-SARS-CoV-2 respiratory viruses. In this study, we carried out wastewater surveillance of SARS-CoV-2 and influenza A virus (IAV) in three key port cities in China through real-time quantitative PCR (RT-qPCR). Next, a novel machine learning algorithm (MLA) based on Gaussian model and random forest model was used to predict the epidemic trajectories of SARS-CoV-2 and IAV. The results showed that from February 2023 to January 2024, three port cities experienced two waves of SARS-CoV-2 infection, which peaked in late-May and late-August 2023, respectively. Two waves of IAV were observed in the spring and winter of 2023, respectively with considerable variations in terms of onset/offset date and duration. Furthermore, we employed MLA to extract the key features of epidemic trajectories of SARS-CoV-2 and IAV from February 3rd, to October 15th, 2023, and thereby predicted the epidemic trends of SARS-CoV-2 and IAV from October 16th, 2023 to April 22nd, 2024, which showed high consistency with the observed values. These collective findings offer an important understanding of SARS-CoV-2 and IAV epidemics, suggesting that wastewater surveillance together with MLA emerges as a powerful tool for risk assessment of respiratory viral diseases and improving public health preparedness.

Development of a wastewater based infectious disease surveillance research system in South Korea

Wastewater-based epidemiology has been used in pathogen surveillance for microorganisms at the community level. This study was conducted to determine the occurrence and trends of infectious pathogens in sewage from Yongin city and the relationships between these pathogens and the incidence of infectious diseases in the community. From December 2022 to November 2023, we collected inflow water from six wastewater treatment plants in Yongin city twice a month. The analyzed microorganisms included 15 respiratory viruses, 7 pneumonia-causing bacteria, 19 acute diarrhea-causing pathogens, SARS-CoV-2, Zika virus, hepatitis A virus, poliovirus, Mpox, and measles. They were detected through real-time PCR and conventional PCR. The concentrations of 9 pathogens among them were additionally analyzed using quantitative real time PCR. The correlation was confirmed through statistical analysis with the rate of detection for pathogens reported by the Korea Disease Control and Prevention Agency. Influenza A virus, human adenovirus, and human rhinovirus were moderately correlated (rho values of 0.45 to 0.58). Campylobacter spp. and sapovirus were strong correlated (rho values of 0.62, 0.63). Enteropathogenic E. coli, human coronavirus, and norovirus GII were very strong correlated (rho values of 0.86 to 0.92). We were able to identify the prevalence of respiratory viral infections, pneumonia, and acute diarrhea-causing pathogens in the community through wastewater-based epidemiology data. This study will be helpful in establishing a system for future surveillance of infectious diseases present in sewage.

Genomic Analysis and Surveillance of Respiratory Syncytial Virus Using Wastewater-Based Epidemiology

Respiratory syncytial virus (RSV) causes severe infections in infants, immunocompromised or elderly individuals resulting in annual epidemics of respiratory disease. Currently, limited clinical surveillance and the lack of predictable seasonal dynamics limit the public health response. Wastewater-based epidemiology (WBE) has recently been used globally as a key metric in determining prevalence of severe acute respiratory syndrome coronavirus 2 in the community, but its application to other respiratory viruses is limited. In this study, we present an integrated genomic WBE approach, applying reverse-transcription quantitative polymerase chain reaction and partial G-gene sequencing to track RSV levels and variants in the community. We report increasing detection of RSV in wastewater concomitant with increasing numbers of positive clinical cases. Analysis of wastewater-derived RSV sequences permitted identification of distinct circulating lineages within and between seasons. Altogether, our genomic WBE platform has the potential to complement ongoing global surveillance and aid the management of RSV by informing the timely deployment of pharmaceutical and nonpharmaceutical interventions.

Key considerations for pathogen surveillance in wastewater

Wastewater surveillance (WWS) has received significant attention as a rapid, sensitive, and cost-effective tool for monitoring various pathogens in a community. WWS is employed to assess the spatial and temporal trends of diseases and identify their early appearances and reappearances, as well as to detect novel and mutated variants. However, the shedding rates of pathogens vary significantly depending on factors such as disease severity, the physiology of affected individuals, and the characteristics of pathogen. Furthermore, pathogens may exhibit differential fate and decay kinetics in the sewerage system. Variable shedding rates and decay kinetics may affect the detection of pathogens in wastewater. This may influence the interpretation of results and the conclusions of WWS studies. When selecting a pathogen for WWS, it is essential to consider it's specific characteristics. If data are not readily available, factors such as fate, decay, and shedding rates should be assessed before conducting surveillance. Alternatively, these factors can be compared to those of similar pathogens for which such data are available.

Tracking epidemic viruses in wastewaters

Classical epidemiology relies on incidence, mortality rates, and clinical data from individual testing, which can be challenging for many countries. Therefore, innovative, flexible, cost-effective, and scalable surveillance techniques are needed. Wastewater-based epidemiology (WBE) has emerged as a highly powerful tool in this regard. WBE analyses substances excreted in human fluids and faeces that enter the sewer system. This approach provides insights into community health status and lifestyle habits. WBE serves as an early warning system for viral surveillance, detecting the emergence of new pathogens, changes in incidence rates, identifying future trends, studying outbreaks, and informing the performance of action plans. While WBE has long been used to study different viruses such as poliovirus and norovirus, its implementation has surged due to the pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2. This has led to the establishment of wastewater surveillance programmes at international, national, and community levels, many of which remain operational. Furthermore, WBE is increasingly applied to study other pathogens, including antibiotic resistance bacteria, parasites, fungi, and emerging viruses, with new methodologies being developed. Consequently, the primary focus now is on creating international frameworks to enhance states' preparedness against future health risks. However, there remains considerable work to be done, particularly in integrating the principles of One Health into epidemiological surveillance to acknowledge the interconnectedness of humans, animals, and the environment in pathogen transmission. Thus, a broader approach to analysing the three pillars of One Health must be developed, transitioning from WBE to wastewater and environmental surveillance, and establishing this approach as a routine practice in public health.

Integrated environmental and clinical surveillance for the prevention of acute respiratory infections (ARIs) in indoor environments and vulnerable communities (Stell-ARI): Protocol

The epidemiological relevance of viral acute respiratory infections (ARIs) has been dramatically highlighted by COVID-19. However, other viruses cannot be neglected, such as influenza virus, respiratory syncytial virus, human adenovirus. These viruses thrive in closed spaces, influenced by human and environmental factors. High-risk closed communities are the most vulnerable settings, where the real extent of viral ARIs is often difficult to evaluate, due to the natural disease progression and case identification complexities. During the COVID-19 pandemic, wastewater-based epidemiology has demonstrated its great potential for monitoring the circulation and evolution of the virus in the environment. The "Prevention of ARIs in indoor environments and vulnerable communities" study (Stell-ARI) addresses the urgent need for integrated surveillance and early detection of ARIs within enclosed and vulnerable communities such as long-term care facilities, prisons and primary schools. The rapid transmission of ARIs in such environments underscores the importance of comprehensive surveillance strategies to minimise the risk of outbreaks and safeguard community health, enabling proactive prevention and control strategies to protect the health of vulnerable populations. This study consists of designing and validating tools for integrated clinical and environmental-based surveillance for each setting, coupled with analytical methods for environmental matrices. The clinical surveillance involves specialized questionnaires and nasopharyngeal swabs for virus identification, while the environmental surveillance includes air and surface microbiological and chemical monitoring, and virological analysis of wastewater. Integrating this information and the collection of behavioural and environmental risk factors into predictive and risk assessment models will provide a useful tool for early warning, risk assessment and informed decision-making. The study aims to integrate clinical, behavioural, and environmental data to establish and validate a predictive model and risk assessment tool for the early warning and risk management of viral ARIs in closed and vulnerable communities prior to the onset of an outbreak.

Wastewater Surveillance to Confirm Differences in Influenza A Infection between Michigan, USA, and Ontario, Canada, September 2022-March 2023

Wastewater surveillance is an effective way to track the prevalence of infectious agents within a community and, potentially, the spread of pathogens between jurisdictions. We conducted a retrospective wastewater surveillance study of the 2022-23 influenza season in 2 communities, Detroit, Michigan, USA, and Windsor-Essex, Ontario, Canada, that form North America's largest cross-border conurbation. We observed a positive relationship between influenza-related hospitalizations and the influenza A virus (IAV) wastewater signal in Windsor-Essex (ρ = 0.785; p<0.001) and an association between influenza-related hospitalizations in Michigan and the IAV wastewater signal for Detroit (ρ = 0.769; p<0.001). Time-lagged cross correlation and qualitative examination of wastewater signal in the monitored sewersheds showed the peak of the IAV season in Detroit was delayed behind Windsor-Essex by 3 weeks. Wastewater surveillance for IAV reflects regional differences in infection dynamics which may be influenced by many factors, including the timing of vaccine administration between jurisdictions.

A narrative review of wastewater surveillance: pathogens of concern, applications, detection methods, and challenges

Introduction

The emergence and resurgence of pathogens have led to significant global health challenges. Wastewater surveillance has historically been used to track water-borne or fecal-orally transmitted pathogens, providing a sensitive means of monitoring pathogens within a community. This technique offers a comprehensive, real-time, and cost-effective approach to disease surveillance, especially for diseases that are difficult to monitor through individual clinical screenings.

Methods

This narrative review examines the current state of knowledge on wastewater surveillance, emphasizing important findings and techniques used to detect potential pathogens from wastewater. It includes a review of literature on the detection methods, the pathogens of concern, and the challenges faced in the surveillance process.

Results

Wastewater surveillance has proven to be a powerful tool for early warning and timely intervention of infectious diseases. It can detect pathogens shed by asymptomatic and pre-symptomatic individuals, providing an accurate population-level view of disease transmission. The review highlights the applications of wastewater surveillance in tracking key pathogens of concern, such as gastrointestinal pathogens, respiratory pathogens, and viruses like SARS-CoV-2.

Discussion

The review discusses the benefits of wastewater surveillance in public health, particularly its role in enhancing existing systems for infectious disease surveillance. It also addresses the challenges faced, such as the need for improved detection methods and the management of antimicrobial resistance. The potential for wastewater surveillance to inform public health mitigation strategies and outbreak response protocols is emphasized.

Conclusion

Wastewater surveillance is a valuable tool in the fight against infectious diseases. It offers a unique perspective on the spread and evolution of pathogens, aiding in the prevention and control of disease epidemics. This review underscores the importance of continued research and development in this field to overcome current challenges and maximize the potential of wastewater surveillance in public health.

Spatial and temporal variation in respiratory syncytial virus (RSV) subtype RNA in wastewater and relation to clinical specimens

Respiratory syncytial virus (RSV) causes a large burden of respiratory illness globally. It has two subtypes, RSV A and RSV B, but little is known regarding the predominance of these subtypes during different seasons and their impact on morbidity and mortality. Using molecular methods, we quantified RSV A and RSV B RNA in wastewater solids across multiple seasons and metropolitan areas to gain insight into the predominance of RSV subtypes. We determined the predominant subtype for each group using the proportion of RSV A to total RSV (RSV A + RSV B) in each wastewater sample (PA,WW) and conducted a comparative analysis temporally, spatially, and against clinical specimens. A median PA,WW of 0.00 in the first season and 0.58 in the second season indicated a temporal shift in the predominant subtype. Spatially, while we observed dominance of the same subtype, PA,WW was higher in some areas (PA,WW = 0.58-0.88). The same subtype predominated in wastewater and clinical samples, but clinical samples showed higher levels of RSV A (RSV A positivity in clinical samples = 0.79, median PA,WW = 0.58). These results suggest that wastewater, alongside clinical data, holds promise for enhanced subtype surveillance.IMPORTANCERespiratory syncytial virus (RSV) causes a large burden of respiratory illness globally. It has two subtypes, RSV A and RSV B, but little is known regarding the predominance of these subtypes during different seasons and their impact on morbidity and mortality. The study illustrates that information on subtype predominance can be gleaned from wastewater. As a biological composite sample from the entire contributing population, wastewater monitoring of RSV A and B can complement clinical surveillance of RSV.

Efficacy and Safety of Respiratory Syncytial Virus (RSV) Prefusion F Protein Vaccine (RSVPreF3 OA) in Older Adults Over 2 RSV Seasons

BACKGROUND

The adjuvanted RSV prefusion F protein-based vaccine (RSVPreF3 OA) was efficacious against RSV-related lower respiratory tract disease (RSV-LRTD) in ≥60-years-olds over 1 RSV season. We evaluated efficacy and safety of 1 RSVPreF3 OA dose and of 2 RSVPreF3 OA doses given 1 year apart against RSV-LRTD over 2 RSV seasons post-dose 1.

METHODS

In this phase 3, blinded trial, ≥60-year-olds were randomized (1:1) to receive RSVPreF3 OA or placebo pre-season 1. RSVPreF3 OA recipients were re-randomized (1:1) to receive a second RSVPreF3 OA dose (RSV_revaccination group) or placebo (RSV_1dose group) pre-season 2; participants who received placebo pre-season 1 received placebo pre-season 2 (placebo group). Efficacy of both vaccine regimens against RSV-LRTD was evaluated over 2 seasons combined (confirmatory secondary objective, success criterion: lower limits of 2-sided CIs around efficacy estimates >20%).

RESULTS

The efficacy analysis comprised 24 967 participants (RSV_1dose: 6227; RSV_revaccination: 6242; placebo: 12 498). Median efficacy follow-up was 17.8 months. Efficacy over 2 seasons of 1 RSVPreF3 OA dose was 67.2% (97.5% CI: 48.2-80.0%) against RSV-LRTD and 78.8% (95% CI: 52.6-92.0%) against severe RSV-LRTD. Efficacy over 2 seasons of a first dose followed by revaccination was 67.1% (97.5% CI: 48.1-80.0%) against RSV-LRTD and 78.8% (95% CI: 52.5-92.0%) against severe RSV-LRTD. Reactogenicity/safety of the revaccination dose were similar to dose 1.

CONCLUSIONS

One RSVPreF3 OA dose was efficacious against RSV-LRTD over 2 RSV seasons in ≥60-year-olds. Revaccination 1 year post-dose 1 was well tolerated but did not seem to provide additional efficacy benefit in the overall study population.

CLINICAL TRIALS REGISTRATION

ClinicalTrials.gov: NCT04886596.

Seasonality of respiratory, enteric, and urinary viruses revealed by wastewater genomic surveillance

Wastewater surveillance can reveal population-level infectious disease burden and emergent public health threats can be reliably assessed through wastewater surveillance. While molecular methods for wastewater monitoring of microorganisms have traditionally relied on PCR-based approaches, next-generation sequencing (NGS) can provide deeper insights via genomic analyses of multiple diverse pathogens. We conducted a year-long sequencing surveillance of 1,408 composite wastewater samples collected from 12 neighborhood-level access points in the greater Tempe area, Arizona, USA, and show that variation in wastewater viruses is driven by seasonal time and location. The temporal dynamics of viruses in wastewater were influenced cyclically, with the most dissimilarity between samples 23 weeks apart (i.e., winter vs summer, spring vs fall). We identified diverse urinary and enteric viruses including polyomaviruses, astroviruses, and noroviruses, and showed that their genotypes/subtypes shifted across seasons. We show that while wastewater data of certain respiratory viruses like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strongly correlate with clinical case rates, laboratory-reported case incidences were discordant with surges of high viral load in wastewater for other viruses like human coronavirus 229E. These results demonstrate the utility of wastewater sequencing for informing decision-making in public health.IMPORTANCEWastewater surveillance can provide insights into the spread of pathogens in communities. Advances in next-generation sequencing (NGS) methodologies allow for more precise detection of viruses in wastewater. Long-term wastewater surveillance of viruses is an important tool for public health preparedness. This system can act as a public health observatory that gives real-time early warning for infectious disease outbreaks and improved response times.

Developing wastewater-based surveillance schemes for multiple pathogens: The WastPan project in Finland

Wastewater comprises multiple pathogens and offers a potential for wastewater-based surveillance (WBS) to track the prevalence of communicable diseases. The Finnish WastPan project aimed to establish wastewater-based pandemic preparedness for multiple pathogens (viruses, bacteria, parasites, fungi), including antimicrobial resistance (AMR). This article outlines WastPan's experiences in this project, including the criteria for target selection, sampling locations, frequency, analysis methods, and results communication. Target selection relied on epidemiological and microbiological evidence and practical feasibility. Within the WastPan framework, wastewater samples were collected between 2021 and 2023 from 10 wastewater treatment plants (WWTPs) covering 40 % of Finland's population. WWTP selection was validated for reported cases of Extended Spectrum Beta-lactamase-producing bacterial pathogens (Escherichia coli and Klebsiella pneumoniae) from the National Infectious Disease Register. The workflow included 24-h composite influent samples, with one fraction for culture-based analysis (bacteria and fungi) and the rest of the sample was reserved for molecular analysis (viruses, bacteria, antibiotic resistance genes, and parasites). The reproducibility of the monitoring workflow was assessed for SARS-CoV-2 through inter-laboratory comparisons using the N2 and N1 assays. Identical protocols were applied to same-day samples, yielding similar positivity trends in the two laboratories, but the N2 assay achieved a significantly higher detection rate (Laboratory 1: 91.5 %; Laboratory 2: 87.4 %) than the N1 assay (76.6 %) monitored only in Laboratory 2 (McNemar, p < 0.001 Lab 1, = 0.006 Lab 2). This result indicates that the selection of monitoring primers and assays may impact monitoring sensitivity in WBS. Overall, the current study recommends that the selection of sampling frequencies and population coverage of the monitoring should be based on pathogen-specific epidemiological characteristics. For example, pathogens that are stable over time may need less frequent annual sampling, while those that are occurring across regions may require reduced sample coverage. Here, WastPan successfully piloted WBS for monitoring multiple pathogens, highlighting the significance of one-litre community composite wastewater samples for assessing community health. The infrastructure established for COVID-19 WBS is valuable for monitoring various pathogens. The prioritization of the monitoring targets optimizes resource utilization. In the future legislative support in target selection, coverage determination, and sustained funding for WBS is recomended.

Urban wastewater-based epidemiology for multi-viral pathogen surveillance in the Valencian region, Spain

Wastewater-based epidemiology (WBE) has lately arised as a promising tool for monitoring and tracking viral pathogens in communities. In this study, we analysed WBE's role as a multi-pathogen surveillance strategy to detect the presence of several viral illness causative agents. Thus, an epidemiological study was conducted from October 2021 to February 2023 to estimate the weekly levels of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), Respiratory Syncytial virus (RSV), and Influenza A virus (IAV) in influent wastewater samples (n = 69). In parallel, a one-year study (October 2021 to October 2022) was performed to assess the presence of pathogenic human enteric viruses. Besides, monitoring of proposed viral fecal contamination indicators crAssphage and Pepper mild mottle virus (PMMoV) was also assessed, along with plaque counting of somatic coliphages. Genetic material of rotavirus (RV), human astrovirus (HAStV), and norovirus genogroup I (GI) and GII was found in almost all samples, while hepatitis A and E viruses (HAV and HEV) only tested positive in 3.77 % and 22.64 % of the samples, respectively. No seasonal patterns were overall found for enteric viruses, although RVs had a peak prevalence in the winter months. All samples tested positive for SARS-CoV-2 RNA, with a mean concentration of 5.43 log genome copies per liter (log GC/L). The tracking of the circulating SARS-CoV-2 variants of concern (VOCs) was performed by both duplex RT-qPCR and next generation sequencing (NGS). Both techniques reliably showed how the dominant VOC transitioned from Delta to Omicron during two weeks in Spain in December 2021. RSV and IAV viruses peaked in winter months with mean concentrations 6.40 and 4.10 log GC/L, respectively. Moreover, the three selected respiratory viruses strongly correlated with reported clinical data when normalised by wastewater physico-chemical parameters and presented weaker correlations when normalising sewage concentration levels with crAssphage or somatic coliphages titers. Finally, predictive models were generated for each respiratory virus, confirming high reliability on WBE data as an early-warning system and communities illness monitoring system. Overall, this study presents WBE as an optimal tool for multi-pathogen tracking reflecting viral circulation and diseases trends within a selected area, its value as a multi-pathogen early-warning tool stands out due to its public health interest.

Persistence of human respiratory viral RNA in wastewater-settled solids

Wastewater-based epidemiology has emerged as a valuable tool for monitoring respiratory viral diseases within communities by analyzing concentrations of viral nucleic-acids in wastewater. However, little is known about the fate of respiratory virus nucleic-acids in wastewater. Two important fate processes that may modulate their concentrations in wastewater as they move from household drains to the point of collection include sorption or partitioning to wastewater solids and degradation. This study investigated the decay kinetics of genomic nucleic-acids of seven human respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), respiratory syncytial virus (RSV), human coronavirus (HCoV)-OC43, HCoV-229E, HCoV-NL63, human rhinovirus (HRV), and influenza A virus (IAV), as well as pepper mild mottle virus (PMMoV) in wastewater solids. Viruses (except for PMMoV) were spiked into wastewater solids and their concentrations were followed for 50 days at three different temperatures (4°C, 22°C, and 37°C). Viral genomic RNA decayed following first-order kinetics with decay rate constants k from 0 to 0.219 per day. Decay rate constants k were not different from 0 for all targets in solids incubated at 4°C; k values were largest at 37°C and at this temperature, k values were similar across nucleic-acid targets. Regardless of temperature, there was limited viral RNA decay, with an estimated 0% to 20% reduction, over the typical residence times of sewage in the piped systems between input and collection point (<1 day). The k values reported herein can be used directly in fate and transport models to inform the interpretation of measurements made during wastewater surveillance.IMPORTANCEUnderstanding whether or not the RNA targets quantified for wastewater-based epidemiology (WBE) efforts decay during transport between drains and the point of sample collection is critical for data interpretation. Here we show limited decay of viral RNA targets typically measured for respiratory disease WBE.

Observations of Respiratory Syncytial Virus (RSV) Nucleic Acids in Wastewater Solids Across the United States in the 2022-2023 Season: Relationships with RSV Infection Positivity and Hospitalization Rates

Respiratory syncytial virus (RSV) is a leading cause of respiratory illness and hospitalization, but clinical surveillance detects only a minority of cases. Wastewater surveillance could determine the onset and extent of RSV circulation in the absence of sensitive case detection, but to date, studies of RSV in wastewater are few. We measured RSV RNA concentrations in wastewater solids from 176 sites during the 2022-2023 RSV season and compared those to publicly available RSV infection positivity and hospitalization rates. Concentrations ranged from undetectable to 107 copies per gram. RSV RNA concentration aggregated at state and national levels correlated with infection positivity and hospitalization rates. RSV season onset was determined using both wastewater and clinical positivity rates using independent algorithms for 14 states where both data were available at the start of the RSV season. In 4 of 14 states, wastewater and clinical surveillance identified RSV season onset during the same week; in 3 states, wastewater onset preceded clinical onset, and in 7 states, wastewater onset occurred after clinical onset. Wastewater concentrations generally peaked in the same week as hospitalization rates but after case positivity rates peaked. Differences in onset and peaks in wastewater versus clinical data may reflect inherent differences in the surveillance approaches.

Advances in wastewater analysis revealing the co-circulating viral trends of noroviruses and Omicron subvariants

Co-presence of enveloped and non-enveloped viruses is common both in community circulation and in wastewater. Community surveillance of infections requires robust methods enabling simultaneous quantification of multiple viruses in wastewater. Using enveloped SARS-CoV-2 Omicron subvariants and non-enveloped norovirus (NoV) as examples, this study reports a robust method that integrates electronegative membrane (EM) concentration, viral inactivation, and RNA preservation (VIP) with efficient capture and enrichment of the viral RNA on magnetic (Mag) beads, and direct detection of RNA on the beads. This method provided improved viral recoveries of 80 ± 4 % for SARS-CoV-2 and 72 ± 5 % for Murine NoV. Duplex reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays with newly designed degenerate primer-probe sets offered high PCR efficiencies (90-91 %) for NoV (GI and GII) targets and were able to detect as few as 15 copies of the viral RNA per PCR reaction. This technique, combined with duplex detection of NoV and multiplex detection of Omicron, successfully quantified NoV (GI and GII) and Omicron variants in the same sets of 94 influent wastewater samples collected from two large wastewater systems between July 2022 and June 2023. The wastewater viral RNA results showed temporal changes of both NoV and Omicron variants in the same wastewater systems and revealed an inverse relationship of their emergence. This study demonstrated the importance of a robust analytical platform for simultaneous surveillance of enveloped and non-enveloped viruses in wastewater. The ability to sensitively determine multiple viral pathogens in wastewater will advance applications of wastewater surveillance as a complementary public health tool.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

Food and Environmental Virology: Use of Passive Sampling to Characterize the Presence of SARS-CoV-2 and Other Viruses in Wastewater

Fecal shedding of SARS-CoV-2 leads to a renaissance of wastewater-based epidemiology (WBE) as additional tool to follow epidemiological trends in the catchment of treatment plants. As alternative to the most commonly used composite samples in surveillance programs, passive sampling is increasingly studied. However, the many sorbent materials in different reports hamper the comparison of results and a standardization of the approach is necessary. Here, we compared different cost-effective sorption materials (cheesecloths, gauze swabs, electronegative filters, glass wool, and tampons) in torpedo-style housings with composite samples. Despite a remarkable variability of the concentration of SARS-CoV-2-specific gene copies, analysis of parallel-deposited passive samplers in the sewer demonstrated highest rate of positive samples and highest number of copies by using cheesecloths. Using this sorption material, monitoring of wastewater of three small catchments in the City of Dresden resulted in a rate of positive samples of 50% in comparison with composite samples (98%). During the investigation period, incidence of reported cases of SARS-CoV-2 in the catchments ranged between 16 and 170 per 100,000 persons and showed no correlation with the measured concentrations of E gene in wastewater. In contrast, constantly higher numbers of gene copies in passive vs. composite samples were found for human adenovirus and crAssphage indicating strong differences of efficacy of methods concerning the species investigated. Influenza virus A and B were sporadically detected allowing no comparison of results. The study contributes to the further understanding of possibilities and limits of passive sampling approaches in WBE.

Monitoring of hepatitis E virus in wastewater can identify clinically relevant variants

Hepatitis E virus (HEV) is prevalent worldwide and can cause persistent infection with severe morbidity. Antiviral treatment approaches can lead to the emergence of viral variants encoding escape mutations that may impede viral clearance. The frequency of these variants remains unknown in the human population as well as environment due to limited comprehensive data on HEV diversity. In this study, we investigated the HEV prevalence and diversity of circulating variants in environmental samples, that is, wastewater and rivers from North-Rhine Westphalia, Germany. HEV prevalence could be determined with 73% of samples tested positive for viral RNA via qRT-PCR. Using high-throughput sequencing, we were able to assess the overall genetic diversity in these samples and identified the presence of clinically relevant variants associated with drug resistance. In summary, monitoring variants from environmental samples could provide valuable insights into estimating HEV prevalence and identifying circulating variants that can impact treatment outcome.

Beyond linear regression: Modeling COVID-19 clinical cases with wastewater surveillance of SARS-CoV-2 for the city of Athens and Ohio University campus

Wastewater-based surveillance has emerged as a detection tool for population-wide infectious diseases, including coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals shed the virus, which can be detected in wastewater using molecular techniques such as reverse transcription-digital polymerase chain reaction (RT-dPCR). This study examined the association between the number of clinical cases and the concentration of SARS-CoV-2 in wastewater beyond linear regression and for various normalizations of viral loads. Viral loads were measured in a total of 446 wastewater samples during the period from August 2021 to April 2022. These samples were collected from nine different locations, with 220 samples taken from four specific sites within the city of Athens and 226 samples from five sites within Ohio University. The correlation between COVID-19 cases and wastewater viral concentrations, which was estimated using the Pearson correlation coefficient, was statistically significant and ranged from 0.6 to 0.9. In addition, time-lagged cross correlation was applied to identify the lag time between clinical and wastewater data, estimated 4 to 7 days. While we also explored the effect on the correlation coefficients of various normalizations of viral loads accounting for procedural loss or amount of fecal material and of estimated lag times, these alternative specifications did not change our substantive conclusions. Additionally, several linear and non-linear regression models were applied to predict the COVID-19 cases given wastewater data as input. The non-linear approach was found to yield the highest R-squared and Pearson correlation and lowest Mean Absolute Error values between the predicted and actual number of COVID-19 cases for both aggregated OHIO Campus and city data. Our results provide support for previous studies on correlation and time lag and new evidence that non-linear models, approximated with artificial neural networks, should be implemented for WBS of contagious diseases.

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan

BACKGROUND

Periodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing.

RESULTS

During the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified.

CONCLUSIONS

The presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary "screening" tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.

Comparison of adsorption-extraction (AE) workflows for improved measurements of viral and bacterial nucleic acid in untreated wastewater

The lack of standardized methods and large differences in virus concentration and extraction workflows have hampered Severe Acute Respiratory Syndrome (SARS-CoV-2) wastewater surveillance and data reporting practices. Numerous studies have shown that adsorption-extraction (AE) method holds promise, yet several uncertainties remain regarding the optimal AE workflow. Several procedural components may influence the recovered concentrations of target nucleic acid, including membrane types, homogenization instruments, speed and duration, and lysis buffer. In this study, 42 different AE workflows that varied these components were compared to determine the optimal workflow by quantifying endogenous SARS-CoV-2, human adenovirus 40/41 (HAdV 40/41), and a bacterial marker gene of fecal contamination (Bacteroides HF183). Our findings suggest that the workflow chosen had a significant impact on SARS-CoV-2 concentrations, whereas it had minimal impact on HF183 and no effect on HAdV 40/41 concentrations. When comparing individual components in a workflow, such as membrane type (MF-Millipore™ 0.45 μm MCE vs. Isopore™ 0.40 μm), we found that they had no impact on SARS-CoV-2, HAdV 40/41, and HF183 concentrations. This suggests that at least some consumables and equipment are interchangeable. Buffer PM1 + TRIzol-based workflows yielded higher concentrations of SARS-CoV-2 than other workflows. HF183 concentrations were higher in workflows without chloroform. Similarly, higher homogenization speeds (5000-10,000 rpm) led to increased concentrations of SARS-CoV-2 and HF183 but had no effect on HAdV 40/41. Our findings indicate that minor enhancements to the AE workflow can improve the recovery of viruses and bacteria from the wastewater, leading to improved outcomes from wastewater surveillance efforts.

A systematic review of influenza virus in water environments across human, poultry, and wild bird habitats

Influenza, a highly contagious acute respiratory disease, remains a major global health concern. This study aimed to comprehensively assess the prevalence of influenza virus in different aquatic environments. Using 43 articles from four databases, we thoroughly examined water matrices from wastewater treatment plants (WTPs) and other human environments, as well as poultry habitats and areas frequented by migratory wild birds. In WTP influents (10 studies), positivity rates for influenza A ranged from 0.0 % to 97.6 %. For influenza B (8 studies), most studies reported no positivity, except for three studies reporting detection in 0.8 %, 5.6 %, and 46.9 % of samples. Within poultry habitats (13 studies), the prevalence of influenza A ranged from 4.3 % to 76.4 %, while in environments frequented by migratory wild birds (11 studies), it ranged from 0.4 % to 69.8 %. Geographically, the studies were distributed as follows: 39.5 % from the Americas, 18.6 % from Europe, 2.3 % from South-East Asia and 39.5 % from the Western Pacific. Several influenza A subtypes were found in water matrices, including avian influenza (H3N6, H3N8, H4N1, H4N2, H4N6, H4N8, H5N1, H5N8, H6N2, H6N6, H7N9, H0N8, and H11N9) and seasonal human influenza (H1N1 and H3N2). The existing literature indicates a crucial requirement for more extensive future research on this topic. Specifically, it emphasizes the need for method harmonization and delves into areas deserving of in-depth research, such as water matrices pertaining to pig farming and prevalence studies in low-income countries.

Longitudinal wastewater surveillance of four key pathogens during an unprecedented large-scale COVID-19 outbreak in China facilitated a novel strategy for addressing public health priorities-A proof of concept study

Wastewater-based epidemiology (WBE) is a promising tool for monitoring the spread of SARS-CoV-2 and other pathogens, providing a novel public health strategy to combat disease. In this study, we first analysed nationwide reports of infectious diseases and selected Salmonella, norovirus, and influenza A virus (IAV) as prioritized targets apart from SARS-CoV-2 for wastewater surveillance. Next, the decay rates of Salmonella, norovirus, and IAV in wastewater at various temperatures were established to obtain corrected pathogen concentrations in sewage. We then monitored the concentrations of these pathogens in wastewater treatment plant (WWTP) influents in three cities, establishing a prediction model to estimate the number of infected individuals based on the mass balance between total viral load in sewage and individual viral shedding. From October 2022 to March 2023, we conducted multipathogen wastewater surveillance (MPWS) in a WWTP serving one million people in Xi'an City, monitoring the concentration dynamics of SARS-CoV-2, Salmonella, norovirus, and IAV in sewage. The infection peaks of each pathogen were different, with Salmonella cases and sewage concentration declining from October to December 2022 and only occasionally detected thereafter. The SARS-CoV-2 concentration rapidly increased from December 5th, peaked on December 26th, and then quickly decreased until the end of the study. Norovirus and IAV were detected in wastewater from January to March 2023, peaking in February and March, respectively. We used the prediction models to estimate the rate of SARS-CoV-2 infection in Xi'an city, with nearly 90 % of the population infected in urban regions. There was no significant difference between the predicted and actual number of hospital admissions for IAV. We also accurately predicted the number of norovirus cases relative to the reported cases. Our findings highlight the importance of wastewater surveillance in addressing public health priorities, underscoring the need for a novel workflow that links the prediction results of populations with public health interventions and allocation of medical resources at the community level. This approach would prevent medical resource panic squeezes, reduce the severity and mortality of patients, and enhance overall public health outcomes.

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.

Human bocavirus respiratory infection: Tracing the path from viral replication and virus-cell interactions to diagnostic methods

Human bocaviruses were first described between 2005 and 2010, identified in respiratory and enteric tract samples of children. Screening studies have shown worldwide distribution. Based on phylogenetic analysis, they were classified into four genotypes (HBoV1-4). From a clinical perspective, human bocavirus 1 (HBoV1) is considered the most relevant, since it can cause upper and lower acute respiratory tract infection, mainly in infants, including common cold, bronchiolitis, and pneumonia, as well as wheezing in susceptible patients. However, the specific processes leading to structural, biochemical, and functional changes resulting in the different clinical presentations have not been elucidated yet. This review surveys the interactions between the virus and target cells that can potentially explain disease-causing mechanisms. It also summarises the clinical phenotype of cases, stressing the role of HBoV1 as an aetiological agent of lower acute respiratory infection in infants, together with laboratory tests for detection and diagnosis. By exploring the current knowledge on the epidemiology of HBoV1, insights into the complex scenario of paediatric respiratory infections are presented, as well as the potential effects that changes in the circulation can have on the dynamics of respiratory agents, spotlighting the benefits of comprehensively increase insights into incidence, interrelationships with co-circulating agents and potential control of HBoV1.

Unveiling indicator, enteric, and respiratory viruses in aircraft lavatory wastewater using adsorption-extraction and Nanotrap® Microbiome A Particles workflows

The effective detection of viruses in aircraft wastewater is crucial to establish surveillance programs for monitoring virus spread via aircraft passengers. This study aimed to compare the performance of two virus concentration workflows, adsorption-extraction (AE) and Nanotrap® Microbiome A Particles (NMAP), in detecting the prevalence and concentrations of 15 endogenous viruses including ssDNA, dsDNA, ssRNA in 24 aircraft lavatory wastewater samples. The viruses tested included two indicator viruses, four enteric viruses, and nine respiratory viruses. The results showed that cross-assembly phage (crAssphage), human polyomavirus (HPyV), rhinovirus A (RhV A), and rhinovirus B (RhV B) were detected in all wastewater samples using both workflows. However, enterovirus (EV), human norovirus GII (HNoV GII), human adenovirus (HAdV), bocavirus (BoV), parechovirus (PeV), epstein-barr virus (EBV). Influenza A virus (IAV), and respiratory syncytial virus B (RsV B) were infrequently detected by both workflows, and hepatitis A virus (HAV), influenza B virus (IBV), and respiratory syncytial virus B (RsV A) were not detected in any samples. The NMAP workflow had greater detection rates of RNA viruses (EV, PeV, and RsV B) than the AE workflow, while the AE workflow had greater detection rates of DNA viruses (HAdV, BoV, and EBV) than the NMAP workflow. The concentration of each virus was also analyzed, and the results showed that crAssphage had the highest mean concentration (6.76 log10 GC/12.5 mL) followed by HPyV (5.46 log10 GC/12.5 mL using the AE workflow, while the mean concentrations of enteric and respiratory viruses ranged from 2.48 to 3.63 log10 GC/12.5 mL. Using the NMAP workflow, the mean concentration of crAssphage was 5.18 log10 GC/12.5 mL and the mean concentration of HPyV was 4.20 log10 GC/12.5 mL, while mean concentrations of enteric and respiratory viruses ranged from 2.55 to 3.74 log10 GC/12.5 mL. Significantly higher (p < 0.05) mean concentrations of crAssphage and HPyV were observed when employing the AE workflow in comparison to the NMAP workflow. Conversely, the NMAP workflow yielded significantly greater (p < 0.05) concentrations of RhV A, and RhV B compared to the AE workflow. The findings of this study can aid in the selection of an appropriate concentration workflow for virus surveillance studies and contribute to the development of efficient virus detection methods.

Development and application of influenza virus wastewater surveillance in Hong Kong

Wastewater surveillance is considered as a powerful tool in providing cost-effective, population-wide and near real-time surveillance results for controlling infectious diseases (i.e., SARS-CoV-2, influenza virus), complementary to clinical surveillance. To facilitate the utility of this emerging tool, we developed two preanalytical protocols (supernatant-based and pellet-based) for influenza A/B virus (IAV/IBV) wastewater surveillance and applied them to the established wastewater surveillance network for large-scale longitudinal monitoring in Hong Kong. We tested 724 wastewater samples from 24 stationary sites for weekly surveillance for 8 months and 458 wastewater samples from 11 wastewater treatment plants (WWTPs) for more frequent (three times per week) city-wide surveillance for 4 months when influenza season commenced. We found the city-wide IAV virus concentration in wastewater were associated with the detection rate and influenza-like illness plus rates (ILI+) of clinical respiratory specimens and increased significantly after the cancelling of mask mandate that was in place for COVID-19. IBV was at low detection rates and low virus concentration levels, consistent with the low detection rates observed by clinical surveillance. In addition, we conducted virus subtype identification in selected wastewater samples, and observed the H1pdm was the major circulation subtype. Moreover, the obtained virus signals were confirmed by Sanger sequencing of PCR products, suggesting the feasibility and applicability of established methods for rapid detection of influenza virus types and subtypes in wastewater surveillance. This study demonstrates the applicability of IAV/IBV wastewater surveillance to current wastewater infrastructures and it could be used as a rapid and cost-effective surveillance strategy to track virus transmission patterns in the community for timely public health actions in the future.

Monitoring influenza and respiratory syncytial virus in wastewater. Beyond COVID-19

Wastewater-based surveillance can be a valuable tool to monitor viral circulation and serve as an early warning system. For respiratory viruses that share similar clinical symptoms, namely SARS-CoV-2, influenza, and respiratory syncytial virus (RSV), identification in wastewater may allow differentiation between seasonal outbreaks and COVID-19 peaks. In this study, to monitor these viruses as well as standard indicators of fecal contamination, a weekly sampling campaign was carried out for 15 months (from September 2021 to November 2022) in two wastewater treatment plants that serve the entire population of Barcelona (Spain). Samples were concentrated by the aluminum hydroxide adsorption-precipitation method and then analyzed by RNA extraction and RT-qPCR. All samples were positive for SARS-CoV-2, while the positivity rates for influenza virus and RSV were significantly lower (10.65 % for influenza A (IAV), 0.82 % for influenza B (IBV), 37.70 % for RSV-A and 34.43 % for RSV-B). Gene copy concentrations of SARS-CoV-2 were often approximately 1 to 2 logarithmic units higher compared to the other respiratory viruses. Clear peaks of IAV H3:N2 in February and March 2022 and RSV in winter 2021 were observed, which matched the chronological incidence of infections recorded in the Catalan Government clinical database. In conclusion, the data obtained from wastewater surveillance provided new information on the abundance of respiratory viruses in the Barcelona area and correlated favorably with clinical data.

Wastewater Surveillance Data as a Complement to Emergency Department Visit Data for Tracking Incidence of Influenza A and Respiratory Syncytial Virus - Wisconsin, August 2022-March 2023

Wastewater surveillance has been used to assist public health authorities in tracking local transmission of SARS-CoV-2. The usefulness of wastewater surveillance to track community spread of other respiratory pathogens, including influenza virus and respiratory syncytial virus (RSV), is less clear. During the 2022-23 respiratory diseases season, concentrations of influenza A virus and RSV in wastewater samples in three major Wisconsin cities were compared with emergency department (ED) visits associated with these pathogens. In all three cities, higher concentrations of influenza A virus and RSV in wastewater were associated with higher numbers of associated ED visits (Kendall's tau range = 0.50-0.63 for influenza-associated illness and 0.30-0.49 for RSV-associated illness). Detections of both influenza A virus and RSV in wastewater often preceded a rise in associated ED visits for each pathogen, and virus material remained detectable in wastewater for up to 3 months after pathogen-specific ED visits declined. These results demonstrate that wastewater surveillance has the potential to complement conventional methods of influenza and RSV surveillance, detecting viral signals earlier and for a longer duration than do clinical data. Continued use of wastewater surveillance as a supplement to established surveillance systems such as ED visits might improve local understanding and response to seasonal respiratory virus outbreaks.

Adsorption of Respiratory Syncytial Virus, Rhinovirus, SARS-CoV-2, and F+ Bacteriophage MS2 RNA onto Wastewater Solids from Raw Wastewater

Despite the widespread adoption of wastewater surveillance, more research is needed to understand the fate and transport of viral genetic markers in wastewater. This information is essential for optimizing monitoring strategies and interpreting wastewater surveillance data. In this study, we examined the solid-liquid partitioning behavior of four viruses in wastewater: SARS-CoV-2, respiratory syncytial virus (RSV), rhinovirus (RV), and F+ coliphage/MS2. We used two approaches: (1) laboratory partitioning experiments using lab-grown viruses and (2) distribution experiments using endogenous viruses in raw wastewater. Partition experiments were conducted at 4 and 22 °C. Wastewater samples were spiked with varying concentrations of each virus, solids and liquids were separated via centrifugation, and viral RNA concentrations were quantified using reverse-transcription-digital droplet PCR (RT-ddPCR). For the distribution experiments, wastewater samples were collected from six wastewater treatment plants and processed without spiking exogenous viruses; viral RNA concentrations were measured in wastewater solids and liquids. In both experiments, RNA concentrations were higher in the solid fraction than the liquid fraction by approximately 3-4 orders of magnitude. Partition coefficients (KF) ranged from 2000-270,000 mL·g-1 across viruses and temperature conditions. Distribution coefficients (Kd) were consistent with results from partitioning experiments. Further research is needed to understand how virus and wastewater characteristics might influence the partitioning of viral genetic markers in wastewater.

Towards a post-pandemic future for global pathogen genome sequencing

Pathogen genome sequencing has become a routine part of our response to active outbreaks of infectious disease and should be an important part of our preparations for future epidemics. In this Essay, we discuss the innovations that have enabled routine pathogen genome sequencing, as well as how genome sequences can be used to understand and control the spread of infectious disease. We also explore the impact of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic on the field of pathogen genomics and outline the challenges we must address to further improve the utility of pathogen genome sequencing in the future.

Impact of the COVID-19 pandemic on the prevalence of influenza A and respiratory syncytial viruses elucidated by wastewater-based epidemiology

Since the COVID-19 pandemic, a decrease in the prevalence of Influenza A virus (IAV) and respiratory syncytial virus (RSV) has been suggested by clinical surveillance. However, there may be potential biases in obtaining an accurate overview of infectious diseases in a community. To elucidate the impact of the COVID-19 on the prevalence of IAV and RSV, we quantified IAV and RSV RNA in wastewater collected from three wastewater treatment plants (WWTPs) in Sapporo, Japan, between October 2018 and January 2023, using highly sensitive EPISENS™ method. From October 2018 to April 2020, the IAV M gene concentrations were positively correlated with the confirmed cases in the corresponding area (Spearman's r = 0.61). Subtype-specific HA genes of IAV were also detected, and their concentrations showed trends that were consistent with clinically reported cases. RSV A and B serotypes were also detected in wastewater, and their concentrations were positively correlated with the confirmed clinical cases (Spearman's r = 0.36-0.52). The detection ratios of IAV and RSV in wastewater decreased from 66.7 % (22/33) and 42.4 % (14/33) to 4.56 % (12/263) and 32.7 % (86/263), respectively in the city after the COVID-19 prevalence. The present study demonstrates the potential usefulness of wastewater-based epidemiology combined with the preservation of wastewater (wastewater banking) as a tool for better management of respiratory viral diseases.

Respiratory syncytial virus infection in the modern era

PURPOSE OF REVIEW

Respiratory syncytial virus (RSV) continues to be a major cause of severe lower respiratory tract infection in infants, young children, and older adults. In this review, changes in the epidemiology of RSV during the coronavirus disease 2019 (COVID-19) pandemic are highlighted together with the role which increased molecular surveillance efforts will have in future in assessing the efficacy of vaccines and therapeutics.

RECENT FINDINGS

The introduction of nonpharmaceutical intervention (NPIs) strategies during the COVID-19 pandemic between 2020 and 2022 resulted in worldwide disruption to the epidemiology of RSV infections, especially with respect to the timing and peak case rate of annual epidemics. Increased use of whole genome sequencing along with efforts to better standardize the nomenclature of RSV strains and discrimination of RSV genotypes will support increased monitoring of relevant antigenic sites in the viral glycoproteins. Several RSV vaccine candidates based on subunit, viral vectors, nucleic acid, or live attenuated virus strategies have shown efficacy in Phase 2 or 3 clinical trials with vaccines using RSVpreF protein currently the closest to approval and use in high-risk populations. Finally, the recent approval and future use of the extended half-life human monoclonal antibody Nirsevimab will also help to alleviate the morbidity and mortality burden caused by annual epidemics of RSV infections.

SUMMARY

The ongoing expansion and wider coordination of RSV molecular surveillance efforts via whole genome sequencing will be crucial for future monitoring of the efficacy of a new generation of vaccines and therapeutics.

Wastewater Levels of Respiratory Syncytial Virus Associated with Influenza-like Illness Rates in Children-A Case Study in Larissa, Greece (October 2022-January 2023)

The emergence of the COVID-19 pandemic has led to significant progress in the field of wastewater-based surveillance (WBS) of respiratory pathogens and highlighted its potential for a wider application in public health surveillance. This study aimed to evaluate whether monitoring of respiratory syncytial virus (RSV) in wastewater can provide a comprehensive picture of disease transmission at the community level. The study was conducted in Larissa (Central Greece) between October 2022 and January 2023. Forty-six wastewater samples were collected from the inlet of the wastewater treatment plant of Larissa and analyzed with a real-time reverse transcription polymerase chain reaction (RT-PCR) based method. RSV and SARS-CoV-2 wastewater viral loads (genome copies/100,000 inhabitants) were analyzed against sentinel surveillance data on influenza-like illness (ILI) to identify potential associations. Univariate linear regression analysis revealed that RSV wastewater viral load (lagged by one week) and ILI notification rates in children up to 14 years old were strongly associated (std. Beta: 0.73 (95% CI: 0.31-1.14), p = 0.002, R2 = 0.308). A weaker association was found between SARS-CoV-2 viral load and ILI rates in the 15+ age group (std. Beta: 0.56 (95% CI: 0.06-1.05), p = 0.032, R2 = 0.527). The results support the incorporation of RSV monitoring into existing wastewater-based surveillance systems.

Tracing COVID-19 Trails in Wastewater: A Systematic Review of SARS-CoV-2 Surveillance with Viral Variants

The emergence of new variants of SARS-CoV-2 associated with varying infectivity, pathogenicity, diagnosis, and effectiveness against treatments challenged the overall management of the COVID-19 pandemic. Wastewater surveillance (WWS), i.e., monitoring COVID-19 infections in communities through detecting viruses in wastewater, was applied to track the emergence and spread of SARS-CoV-2 variants globally. However, there is a lack of comprehensive understanding of the use and effectiveness of WWS for new SARS-CoV-2 variants. Here we systematically reviewed published articles reporting monitoring of different SARS-CoV-2 variants in wastewater by following the PRISMA guidelines and provided the current state of the art of this study area. A total of 80 WWS studies were found that reported different monitoring variants of SARS-CoV-2 until November 2022. Most of these studies (66 out of the total 80, 82.5%) were conducted in Europe and North America, i.e., resource-rich countries. There was a high variation in WWS sampling strategy around the world, with composite sampling (50/66 total studies, 76%) as the primary method in resource-rich countries. In contrast, grab sampling was more common (8/14 total studies, 57%) in resource-limited countries. Among detection methods, the reverse transcriptase polymerase chain reaction (RT-PCR)-based sequencing method and quantitative RT-PCR method were commonly used for monitoring SARS-CoV-2 variants in wastewater. Among different variants, the B1.1.7 (Alpha) variant that appeared earlier in the pandemic was the most reported (48/80 total studies), followed by B.1.617.2 (Delta), B.1.351 (Beta), P.1 (Gamma), and others in wastewater. All variants reported in WWS studies followed the same pattern as the clinical reporting within the same timeline, demonstrating that WWS tracked all variants in a timely way when the variants emerged. Thus, wastewater monitoring may be utilized to identify the presence or absence of SARS-CoV-2 and follow the development and transmission of existing and emerging variants. Routine wastewater monitoring is a powerful infectious disease surveillance tool when implemented globally.