Intraday variability of indicator and pathogenic viruses in 1-h and 24-h composite wastewater samples: Implications for wastewater-based epidemiology

Comparative assessment of sewer sampling methods for infectious disease surveillance: Insights from transport modeling and simulations of SARS-CoV-2 emissions

Emerging infectious diseases like COVID-19 present significant public health challenges, necessitating effective surveillance methods. Wastewater-based epidemiology (WBE), detecting viral pathogens in wastewater, has emerged as a proactive tool for monitoring infections. This study evaluated various wastewter sampling methods through SARS-CoV-2 transport simulations in an urban sewer network in Sejong City, South Korea, to identify cost-effective strategies for accurate infection monitoring. Using the U.S. EPA's Storm Water Management Model (SWMM) and Markov chain Monte Carlo (MCMC) sampling, we simulated wastewater flow and viral concentrations based on reported COVID-19 case data for the year 2021. In this study, we used reported COVID-19 cases as a hypothetical estimate of the number of infected individuals in the simulation. The SWMM effectively replicated daily and monthly patterns in sewer flow rates. Combining the SWMM with MCMC sampling from the probability distributions of spatio-temporal virus emission patterns, we generated an ensemble time series dataset of hourly virus concentrations based on 200 simulations, forming the basis for evaluating sampling alternatives. Results showed a strong correlation (R2 = 0.81) between daily average virus concentrations and daily infection rates on the fifth day following new infections, consistent with simulated viral emission patterns. Flow-weighted and equally timed sampling methods provided highly reliable infection pattern estimates, suggesting that equally timed sampling is a cost-effective alternative. In contrast, grab sampling performed poorly due to difficulties in capturing peak viral emission periods. We found that a minimum sampling duration of four to six hours was crucial for accurate detection, with performance increasing if the sampling was applied in the morning (R2 ≈ 0.7). Longer durations steadily, but only slightly, improved results. While this simulation-based approach focused on predicting daily virus concentration patterns in wastewater rather than precisely estimating its absolute levels, it provides valuable insights for optimizing WBE in public health surveillance and underscores the need for further validation with real-world data.

Assessing the viral enrichment methods and their roles in indicating wastewater-associated pollution in aquatic environments

With the increasing need for monitoring viral contamination in aquatic environments, research has increasingly focused on utilizing viruses as indicators for microbial contamination assessment. However, studies on enrichment techniques for waterborne viruses and their occurrence and risk characteristics in the environment remain relatively limited. In this study, samples were collected over one year from a wastewater treatment plant and its receiving stream to evaluate the optimal enrichment method and to assess the presence of four representative viral indicators-human adenovirus (HAdV), crAssPhage, enterovirus (EV), and the pepper mild mottle virus (PMMoV)-in the urban water environment. The results showed that skimmed milk flocculation (SMF) and silica attachment method (SAM) achieved better viral enrichment performance in both wastewater and surface water, demonstrating greater seasonal consistency compared to other methods. Seasonal variations in virus concentrations were observed, with HAdV and crAssphage peaking in winter, while EV and PMMoV peaked in summer. Virus concentrations in wastewater treatment plants were reduced by 8.61 log10 copies/L from influent to effluent. However, residual viruses discharged into receiving streams still pose a significant environmental exposure risk, as indicated by Quantitative Microbial Risk Assessment (QMRA) results, which exhibited a strong correlation with population density. This study highlights the importance of waterborne viral indicators in developing effective water quality management strategies to ensure the safe control of viruses in aquatic environments.

Monkeypox Virus Occurrence in Wastewater Environment and Its Correlation with Incidence Cases of Mpox: A Systematic Review and Meta-Analytic Study

The COVID-19 pandemic has increased the interest in the use of wastewater-based surveillance (WBS) strategy for infectious disease monitoring, especially when clinical cases are underreported. The excretion of monkey virus (MPXV) in the feces of both symptomatic and preclinical individuals has further driven the interest in WBS applicability to MPXV monitoring in wastewater to support its mitigation efforts. We performed a systematic review with meta-analysis, using six databases to assess MPXV detection in wastewater. We performed a random-effects model meta-analysis to calculate the pooled prevalence at a 95% confidence interval (95% CI). Also, we carried out a subgroup analysis according to the country regions and a sensitivity analysis excluding studies classified as having a high risk of bias. The overall MPXV positivity rate in wastewater was estimated at 22% (95% CI: 14-30%; I2 = 94.8%), with more detection rate in North America (26%, 95% CI: 8-43%) compared to Europe and Asia (22%, 95% CI: 12-31%). The MPXV detection rate was significantly higher in 2022 studies (22%, 95% CI: 13-31%) compared to 2023 (19%, 95% CI: 14-25%). The real-time PCR platform significantly detected more MPXV (24%, 95% CI: 14-34%) than the digital droplet PCR-based studies (17%, 95% CI: 4-31%), which was used less frequently. Viral concentration with centrifugation procedure indicated higher detection rates (21%, 95% CI: 10-33%) than other known sample concentration protocols. Generally, MPXV detection rates in wastewater samples strongly correlate with incidence cases of mpox (range of R = 0.78-0.94; p < 0.05). Findings from this study suggest that WBS of MPXV could be employed as an epidemiological early warning tool for disease monitoring and mpox outbreak prediction similar to the clinical case-based surveillance strategies.

Wastewater-Based Epidemiological Surveillance in France: The SUM'EAU Network

Wastewater surveillance is a powerful public health tool which gained global prominence during the COVID-19 pandemic. This article describes the development and implementation of the national wastewater surveillance network in France: SUM'EAU. Preliminary work included defining a sampling strategy, evaluating/optimising analytical methods, launching a call for tenders to select network laboratories and producing wastewater monitoring indicators. SUM'EAU was then deployed in three stages: (i) a pilot study, (ii) the transfer of analytical activities from the National Reference Laboratory to four selected network laboratories, and (iii) the extension of the system to additional sampling sites. Currently, SUM'EAU monitors SARS-CoV-2 across 54 wastewater treatment plants in mainland France. Once a week on business days, 24 h flow-proportional composite samples are collected at plant inlets and transported at 5 °C (±3 °C) to partner laboratories for analysis. The analytical process involves sample concentration, RNA extraction, and digital RT-PCR/q-RT-PCR to detect and quantify the presence of the SARS-CoV-2 genome in wastewater. Subsequently, data are transferred to Santé publique France, the French National Public Health Agency, for analysis and interpretation. While SUM'EAU has been instrumental in monitoring the COVID-19 pandemic and holds significant potential for broader application, securing sustainable funding for its operation remains a major challenge.

Monitoring and preventing foodborne outbreaks: are we missing wastewater as a key data source?

In 2022, the number of foodborne outbreaks in Europe increased by 43.9%, highlighting the need to improve surveillance systems and design outbreak predictive tools. This review aims to assess the scientific literature describing wastewater surveillance to monitor foodborne pathogens in association with clinical data. In the selected studies, the relationship between peaks of pathogen concentration in wastewater and reported clinical cases is described. Moreover, details on analytical methods to detect and quantify pathogens as well as wastewater sampling procedures are discussed. Few papers show a statistically significant correlation between high concentrations of foodborne pathogens in wastewater and the occurrence of clinical cases. However, monitoring pathogen concentration in wastewater looks like a promising and cost-effective strategy to improve foodborne outbreak surveillance. Such a strategy can be articulated in three steps, where the first one is testing wastewater with an untargeted method, like shotgun metagenomic, to detect microorganisms belonging to different domains. The second consists of testing wastewater with a targeted method, such as quantitative polymerase chain reaction, to quantify those specific pathogens that in the metagenomic dataset display an increasing trend or exceed baseline concentration thresholds. The third involves the integrated wastewater and clinical data analysis and modeling to find meaningful epidemiological correlations and make predictions.

A Narrative Review of High Throughput Wastewater Sample Processing for Infectious Disease Surveillance: Challenges, Progress, and Future Opportunities

During the recent COVID-19 pandemic, wastewater-based epidemiological (WBE) surveillance played a crucial role in evaluating infection rates, analyzing variants, and identifying hot spots in a community. This expanded the possibilities for using wastewater to monitor the prevalence of infectious diseases. The full potential of WBE remains hindered by several factors, such as a lack of information on the survival of pathogens in sewage, heterogenicity of wastewater matrices, inconsistent sampling practices, lack of standard test methods, and variable sensitivity of analytical techniques. In this study, we review the aforementioned challenges, cost implications, process automation, and prospects of WBE for full-fledged wastewater-based community health screening. A comprehensive literature survey was conducted using relevant keywords, and peer reviewed articles pertinent to our research focus were selected for this review with the aim of serving as a reference for research related to wastewater monitoring for early epidemic detection.

The different adsorption-degradation behaviors of SARS-CoV-2 by bioactive chemicals in wastewater: The suppression kinetics and their implications for wastewater-based epidemiology

Wastewater-Based Epidemiology (WBE) is widely used to monitor the progression of SARS-CoV-2 pandemic. While there is a clear correlation between the number of COVID patients in a sewershed and the viral load in the wastewater, there is notable variability across different treatment plants. In particular, some facilities consistently exhibit higher viral content per diagnosed patient, implying a potential underestimation of the number of COVID patients, while others show a low viral load per diagnosed case, indicating potential attenuation of genetic material from the sewershed. In this study, we investigated the impact of nonylphenol ethoxylate (NPHE), linear alkylbenzene sulfonic acid (LABS), bisoctyl dimethyl ammonium chloride (BDAC), and didecyldimethylammonium chloride (DDAC), the surfactants that have been commonly used as detergents, emulsifiers, wetting agents on the stability of SARS-CoV-2 in wastewater. The results showed multiple and dynamic mechanisms, including degradation and desorption, can occur simultaneously during the interaction between SARS-CoV-2 and different chemicals depending on the physicochemical properties of each chemical. Through the elucidation of the dynamic interactions, the findings from this study could help the state health organizations and scientific community to optimize the SARS-CoV-2 wastewater-based epidemiology strategies.

A framework for integrating wastewater-based epidemiology and public health

Wastewater-based epidemiology (WBE) is an environmental approach to monitor community health through the analysis of sewage. The COVID-19 pandemic catalyzed scientists and public health professionals to revisit WBE as a tool to optimize resource allocation to mitigate disease spread and prevent outbreaks. Some studies have highlighted the value of WBE programs that coordinate with public health professionals; however, the details necessary for implementation are not well-characterized. To respond to this knowledge gap, this article documents the framework of a successful WBE program in Arizona, titled Wastewater Analysis for Tactical Epidemiological Response Systems (WATERS), detailing the developed structure and methods of communication that enabled public health preparedness and response actions. This communication illustrates how program operations were employed to reduce outbreak severity. The structure outlined here is customizable and may guide other programs in the implementation of WBE as a public health tool.

Wastewater surveillance for viral pathogens: A tool for public health

A focus on water quality has intensified globally, considering its critical role in sustaining life and ecosystems. Wastewater, reflecting societal development, profoundly impacts public health. Wastewater-based epidemiology (WBE) has emerged as a surveillance tool for detecting outbreaks early, monitoring infectious disease trends, and providing real-time insights, particularly in vulnerable communities. WBE aids in tracking pathogens, including viruses, in sewage, offering a comprehensive understanding of community health and lifestyle habits. With the rise in global COVID-19 cases, WBE has gained prominence, aiding in monitoring SARS-CoV-2 levels worldwide. Despite advancements in water treatment, poorly treated wastewater discharge remains a threat, amplifying the spread of water-, sanitation-, and hygiene (WaSH)-related diseases. WBE, serving as complementary surveillance, is pivotal for monitoring community-level viral infections. However, there is untapped potential for WBE to expand its role in public health surveillance. This review emphasizes the importance of WBE in understanding the link between viral surveillance in wastewater and public health, highlighting the need for its further integration into public health management.

SARS-CoV-2 wastewater surveillance at two university campuses: lessons learned and insights on intervention strategies for public health guidance

Wastewater surveillance has been a tool for public health officials throughout the COVID-19 pandemic. Universities established pandemic response committees to facilitate safe learning for students, faculty, and staff. These committees met to analyze both wastewater and clinical data to propose mitigation strategies to limit the spread of COVID-19. This paper reviews the initial efforts of utilizing campus data inclusive of wastewater surveillance for SARS-CoV-2 RNA concentrations, clinical case data from university response teams, and mitigation strategies from Grand Valley State University in West Michigan (population 21,648 students) and Oakland University in East Michigan (population 18,552 students) from November 2020 to April 2022. Wastewater positivity rates for both universities ranged from 32.8 to 46.8%. Peak viral signals for both universities directly corresponded to variant points of entry within the campus populations from 2021 to 2022. It was found that the organization of clinical case data and variability of wastewater testing data were large barriers for both universities to effectively understand disease dynamics within the university population. We review the initial efforts of onboarding wastewater surveillance and provide direction for structuring ongoing surveillance workflows and future epidemic response strategies based on those that led to reduced viral signals in campus wastewater.

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.

Zooming in to the neighborhood level: A year-long wastewater-based epidemiology monitoring campaign for COVID-19 in small intraurban catchments

In recent years, wastewater-based epidemiology (WBE) has emerged as a valuable and cost-effective tool for monitoring the prevalence of COVID-19. Large-scale monitoring efforts have been implemented in numerous countries, primarily focusing on sampling at the entrance of wastewater treatment plants (WWTPs) to cover a large population. However, sampling at a finer spatial scale, such as at the neighborhood level (NGBs), pose new challenges, including the absence of composite sampling infrastructure and increased uncertainty due to the dynamics of small catchments. This study aims to investigate the feasibility and accuracy of WBE when deployed at the neighborhood level (sampling in sewers) compared to the city level (sampling at the entrance of a WWTP). To achieve this, we deployed specific WBE sampling stations at the intraurban scale within three NGBs in Barcelona, Spain. The study period covers the 5th and the 6th waves of COVID-19 in Spain, spanning from March 2021 to March 2022, along with the WWTP downstream from the NGBs. The results showed a strong correlation between the dynamics of COVID-19 clinical cases and wastewater SARS-CoV-2 loads at both the NGB and city levels. Notably, during the 5th wave, which was dominated by the Delta SARS-CoV-2 variant, wastewater loads were higher than during the 6th wave (Omicron variant), despite a lower number of clinical cases recorded during the 5th wave. The correlations between wastewater loads and clinical cases at the NGB level were stronger than at the WWTP level. However, the early warning potential varied across neighborhoods and waves, with some cases showing a one-week early warning and others lacking any significant early warning signal. Interestingly, the prevalence of COVID-19 did not exhibit major differences among NGBs with different socioeconomic statuses.

Environmental monitoring of SARS-CoV-2 in the metropolitan area of Porto Alegre, Rio Grande do Sul (RS), Brazil

Since starts the coronavirus disease 2019 (COVID-19) pandemic identified the presence of genomic fragments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in various environmental matrices: domestic sewage, surface waters, and contaminated freshwater. Environmental monitoring of SARS-CoV-2 is a tool for evaluating trend curves over the months, compared to several clinical cases of the disease. The objective of this study was to monitor the SARS-CoV-2 in environmental samples collected in different sites in a metropolitan area of Porto Alegre, Southern Brazil. During 10 months from 2020 to 2021, 300 samples were collected weekly and biweekly from nine points located in 3 cities: one point from a wastewater treatment plant (WWTP) in São Leopoldo (fortnightly collection), two points in Dilúvio Stream in Porto Alegre (fortnightly collection), two points in Pampa and Luiz Rau Streams (weekly collection), and two points in public fountains (fortnightly collection) in Novo Hamburgo. After collection, samples were concentrated by ultracentrifugation, and viral nucleic acids were extracted using MagMax® Core Nucleic Acid Purifications kits and submitted to RT-qPCR, using E, N1, and N2 gene targets of SARS-CoV-2. Only 7% (3/41) samples from public fountains were positive, with a mean viral load (VL) of SARS-CoV-2 RNA of 5.02 × 101 gc/l (2.41~8.59 × 101 gc/l), while the streams had average VL of 7.43 × 105 gc/l (Pampa), 7.06 × 105 gc/l (Luiz Rau), 2.01 × 105 gc/l (Dilúvio), and 4.46 × 105 cg/l (WWTP). The results showed varying levels of viral presence in different sample types, with a demonstrated correlation between environmental viral load and clinical COVID-19 cases. These findings contribute to understanding virus persistence and transmission pathways in the environment. Continuous monitoring, especially in less developed regions, is crucial for early detection of vaccine resistance, new variants, and potential COVID-19 resurgence.

Enhanced detection of mpox virus in wastewater using a pre-amplification approach: A pilot study informing population-level monitoring of low-titer pathogens

A recent outbreak of the mpox virus (MPXV) occurred in non-endemic regions of the world beginning in May 2022. Pathogen surveillance systems faced pressure to quickly establish response protocols, offering an opportunity to employ wastewater-based epidemiology (WBE) for population-level monitoring. The pilot study reported herein aimed to: (i) develop a reliable protocol for MPXV DNA detection in wastewater which would reduce false negative reporting, (ii) test this protocol on wastewater from various regions across the United States, and (iii) conduct a state of the science review of the current literature reporting on experimental methods for MPXV detection using WBE. Twenty-four-hour composite samples of untreated municipal wastewater were collected from the states of New Jersey, Georgia, Illinois, Texas, Arizona, and Washington beginning July 3rd, 2022 through October 16th, 2022 (n = 60). Samples underwent vacuum filtration, DNA extraction from captured solids, MPXV DNA pre-amplification, and qPCR analysis. Of the 60 samples analyzed, a total of eight (13%) tested positive for MPXV in the states of Washington, Texas, New Jersey, and Illinois. The presence of clade IIb MPXV DNA in these samples was confirmed via Sanger sequencing and integration of pre-amplification prior to qPCR decreased the rate of false negative detections by 87% as compared to qPCR analysis alone. Wastewater-derived detections of MPXV were compared to clinical datasets, with 50% of detections occurring as clinical cases were increasing/peaking and 50% occurring as clinical cases waned. Results from the literature review (n = 9 studies) revealed successful strategies for the detection of MPXV DNA in wastewater, however also emphasized a need for further method optimization and standardization. Overall, this work highlights the use of pre-amplification prior to qPCR detection as a means to capture the presence of MPXV DNA in community wastewater and offers guidance for monitoring low-titer pathogens via WBE.

Diurnal changes in pathogenic and indicator virus concentrations in wastewater

Wastewater-based epidemiology (WBE) has been commonly used for monitoring SARS-CoV-2 outbreaks. As sampling times and methods (i.e. grab vs composite) may vary, diurnal changes of viral concentrations in sewage should be better understood. In this study, we collected untreated wastewater samples hourly for 4 days at two wastewater treatment plants in Wales to establish diurnal patterns in virus concentrations and the physico-chemical properties of the water. Simultaneously, we also trialled three absorbent materials as passive samples as a simple and cost-efficient alternative for the collection of composite samples. Ninety-six percent of all liquid samples (n = 74) and 88% of the passive samplers (n = 59) were positive for SARS-CoV-2, whereas 87% and 97% of the liquid and passive samples were positive for the faecal indicator virus crAssphage, respectively. We found no significant daily variations in the concentration of the target viruses, ammonium and orthophosphate, and the pH and electrical conductivity levels were also stable. Weak positive correlations were found between some physico-chemical properties and viral concentrations. More variation was observed in samples taken from the influent stream as opposed to those taken from the influent tank. Of the absorbent materials trialled as passive samples, we found that tampons provided higher viral recoveries than electronegative filter paper and cotton gauze swabs. For all materials tested, viral recovery was dependent on the virus type. Our results indicate that grab samples may provide representative alternatives to 24-h composite samples if taken from the influent tank, hence reducing the costs of sampling for WBE programmes. Tampons are also viable alternatives for cost-efficient sampling; however, viral recovery should be optimised prior to use.

Expanding a Wastewater-Based Surveillance Methodology for DNA Isolation from a Workflow Optimized for SARS-CoV-2 RNA Quantification

Wastewater-based surveillance (WBS) is a noninvasive, epidemiological strategy for assessing the spread of COVID-19 in communities. This strategy was based upon wastewater RNA measurements of the viral target, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The utility of WBS for assessing the spread of COVID-19 has motivated research to measure targets beyond SARS-CoV-2, including pathogens containing DNA. The objective of this study was to establish the necessary steps for isolating DNA from wastewater by modifying a long-standing RNA-specific extraction workflow optimized for SARS-CoV-2 detection. Modifications were made to the sample concentration process and included an evaluation of bead bashing prior to the extraction of either DNA or RNA. Results showed that bead bashing reduced detection of RNA from wastewater but improved recovery of DNA as assessed by quantitative polymerase chain reaction (qPCR). Bead bashing is therefore not recommended for the quantification of RNA viruses using qPCR. Whereas for Mycobacterium bacterial DNA isolation, bead bashing was necessary for improving qPCR quantification. Overall, we recommend 2 separate workflows, one for RNA viruses that does not include bead bashing and one for other microbes that use bead bashing for DNA isolation. The experimentation done here shows that current-standing WBS program methodologies optimized for SARS-CoV-2 need to be modified and reoptimized to allow for alternative pathogens to be readily detected and monitored, expanding its utility as a tool for public health assessment.

Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage

Inadequate sampling approaches to wastewater analyses can introduce biases, leading to inaccurate results such as false negatives and significant over- or underestimation of average daily viral concentrations, due to the sporadic nature of viral input. To address this challenge, we conducted a field trial within the University of Tennessee residence halls, employing different composite sampling modes that encompassed different time intervals (1 h, 2 h, 4 h, 6 h, and 24 h) across various time windows (morning, afternoon, evening, and late-night). Our primary objective was to identify the optimal approach for generating representative composite samples of SARS-CoV-2 from raw wastewater. Utilizing reverse transcription-quantitative polymerase chain reaction, we quantified the levels of SARS-CoV-2 RNA and pepper mild mottle virus (PMMoV) RNA in raw sewage. Our findings consistently demonstrated that PMMoV RNA, an indicator virus of human fecal contamination in water environment, exhibited higher abundance and lower variability compared to pathogenic SARS-CoV-2 RNA. Significantly, both SARS-CoV-2 and PMMoV RNA exhibited greater variability in 1 h individual composite samples throughout the entire sampling period, contrasting with the stability observed in other time-based composite samples. Through a comprehensive analysis of various composite sampling modes using the Quade Nonparametric ANCOVA test with date, PMMoV concentration and site as covariates, we concluded that employing a composite sampler during a focused 6 h morning window for pathogenic SARS-CoV-2 RNA is a pragmatic and cost-effective strategy for achieving representative composite samples within a single day in wastewater-based epidemiology applications. This method has the potential to significantly enhance the accuracy and reliability of data collected at the community level, thereby contributing to more informed public health decision-making during a pandemic.

Public Health Interventions Guided by Houston's Wastewater Surveillance Program During the COVID-19 Pandemic

Since the start of the COVID-19 pandemic, wastewater surveillance has emerged as a powerful tool used by public health authorities to track SARS-CoV-2 infections in communities. In May 2020, the Houston Health Department began working with a coalition of municipal and academic partners to develop a wastewater monitoring and reporting system for the city of Houston, Texas. Data collected from the system are integrated with other COVID-19 surveillance data and communicated through different channels to local authorities and the general public. This information is used to shape policies and inform actions to mitigate and prevent the spread of COVID-19 at municipal, institutional, and individual levels. Based on the success of this monitoring and reporting system to drive public health protection efforts, the wastewater surveillance program is likely to become a standard part of the public health toolkit for responding to infectious diseases and, potentially, other disease-causing outbreaks.

Influence of storage conditions and multiple freeze-thaw cycles on N1 SARS-CoV-2, PMMoV, and BCoV signal

Wastewater-based epidemiology/wastewater-based surveillance (WBE/WBS) continues to serve as an effective means of monitoring various diseases, including COVID-19 and the emergence of SARS-CoV-2 variants, at the population level. As the use of WBE expands, storage conditions of wastewater samples will play a critical role in ensuring the accuracy and reproducibility of results. In this study, the impacts of water concentration buffer (WCB), storage temperature, and freeze-thaw cycles on the detection of SARS-CoV-2 and other WBE-related gene targets were examined. Freeze-thawing of concentrated samples did not significantly affect (p > 0.05) crossing/cycle threshold (Ct) value for any of the gene targets studied (SARS-CoV-2 N1, PMMoV, and BCoV). However, use of WCB during concentration resulted in a significant (p < 0.05) decrease in Ct for all targets, and storage at -80 °C (in contrast to -20 °C) appeared preferable for wastewater storage signal stability based on decreased Ct values, although this was only significantly different (p < 0.05) for the BCoV target. Interestingly, when Ct values were converted to gene copies per influent sample, no significant differences (p > 0.05) were observed in any of the targets examined. Stability of RNA targets in concentrated wastewater against freeze-thaw degradation supports archiving of concentrated samples for use in retrospective examination of COVID-19 trends and tracing SARS-CoV-2 variants and potentially other viruses, and provides a starting point for establishing a consistent procedure for specimen collection and storage for the WBE/WBS community.

Correlative analysis of wastewater trends with clinical cases and hospitalizations through five dominant variant waves of COVID-19

Wastewater-based epidemiology (WBE) has been utilized to track community infections of Coronavirus Disease 2019 (COVID-19) by detecting RNA of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), within samples collected from wastewater. The correlations between community infections and wastewater measurements of the RNA can potentially change as SARS-CoV-2 evolves into new variations by mutating. This study analyzed SARS-CoV-2 RNA, and indicators of human waste in wastewater from two sewersheds of different scales (University of Miami (UM) campus and Miami-Dade County Central District wastewater treatment plant (CDWWTP)) during five internally defined COVID-19 variant dominant periods (Initial, Pre-Delta, Delta, Omicron and Post-Omicron wave). SARS-CoV-2 RNA quantities were compared against COVID-19 clinical cases and hospitalizations to evaluate correlations with wastewater SARS-CoV-2 RNA. Although correlations between documented clinical cases and hospitalizations were high, prevalence for a given wastewater SARS-CoV-2 level varied depending upon the variant analyzed. The correlative relationship was significantly steeper (more cases per level found in wastewater) for the Omicron-dominated period. For hospitalization, the relationships were steepest for the Initial wave, followed by the Delta wave with flatter slopes during all other waves. Overall results were interpreted in the context of SARS-CoV-2 virulence and vaccination rates among the community.

Analysis of sampling strategies for pulse loads of SARS-CoV-2: implications for wastewater-based epidemiology

A faecal transport model was applied to a 11.3 km2 wastewater servicing area in Toronto, Ontario, Canada to explore the role that different wastewater sampling campaigns have on estimating the prevalence of SARS-CoV-2 in a population of 60,000. A stochastic wastewater and water quality model was used to evaluate the effectiveness of 11 sampling campaigns during periods of high and low COVID-19 infection among the population, tested using virtual sampling during dry-weather flow. The virtual sampling campaigns were based on the most common automatic sampler programming capabilities and widely used wastewater-based epidemiology (WBE) sampling campaigns reported in the literature. Sampling campaigns differ in weighting method (time, volume, or flow-weighted sampling), sample count, collection period, or sample time. Results suggest that grab samples should be avoided and/or that sampling campaigns with the greatest sample counts and durations are the most robust at capturing COVID-19 infection among the population. Most surprisingly, changes to the weighting method were negligible indicating that a greater number of samples, and larger sample volumes are preferred. This work suggests that investment in flow monitoring equipment for flow- or volume-weighted sampling will not improve WBE results, and that standard time based sampling is sufficient.

Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center

Introduction

Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices.

Methods

Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony.

Results

It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors.

Discussion

These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.

Measurement of SARS-CoV-2 RNA in wastewater: A case study of the Northern Cape, South Africa

The SARS-CoV-2 pandemic has resulted in the infection and death of many South Africans. This is in part due to a lack of testing facilities, equipment, and staff in many areas, particularly those with low population densities. The study focused on the infection dynamics of the virus in the Northern Cape province in all five municipalities investigating wastewater-based surveillance for the province. Reverse transcription was used to identify the virus, and SARS-CoV-2 RNA was detected in a batch of wastewater from four of the five areas sampled and was collected in the months that fall within the third wave of COVID as well as the winter season (May-July). The detection of the SARS-CoV-2 RNA correlated with infection statistics as well as the seasonality of the virus. This research showed a positive result in using wastewater epidemiology to track the spread of the virus but also highlighted the need for improved methodology when it comes to this surveillance. This includes sampling smaller areas and frequent sampling in multiple areas to show clear patterns within smaller, sparsely populated communities.

Temporal and spatial relationships of CrAssphage and enteric viral and bacterial pathogens in wastewater in North Carolina

Enteric disease remains one of the most common concerns for public health, particularly when it results from human exposure to surface and recreational waters contaminated with wastewater. Characterizing the temporal and spatial variation of enteric pathogens prevalent in wastewater is critical to develop approaches to mitigate their distribution in the environment. In this study, we aim to characterize pathogen variability and test the applicability of the human-associated wastewater indicator crAssphage as an indicator of enteric viral and bacterial pathogens. We conducted weekly samplings for 14 months from four wastewater treatment plants in North Carolina, USA. Untreated wastewater samples were processed using hollow fiber ultrafiltration, followed by secondary concentration methods. Adenovirus, norovirus, enterovirus, Salmonella, Shiga toxin 2 (stx2), Campylobacter, and crAssphage were measured by quantitative polymerase chain reaction (qPCR) and reverse transcriptase (rt)-qPCR. Our results revealed significant correlations between crAssphage and human adenovirus, enterovirus, norovirus, Salmonella, and Campylobacter (p<0.01). Pathogens and crAssphage concentrations in untreated wastewater showed distinct seasonal patterns, with peak concentrations of crAssphage and viral pathogens in fall and winter, while bacterial pathogens showed peaked concentrations in either winter (Campylobacter), fall (Salmonella), or summer (stx2). This study enhances the understanding of crAssphage as an alternative molecular indicator for both bacterial and viral pathogens. The findings of this study can also inform microbial modeling efforts for the prediction of the impact of wastewater pathogens on surface waters due to increased flooding events and wastewater overflows associated with climate change.

Wastewater surveillance beyond COVID-19: a ranking system for communicable disease testing in the tri-county Detroit area, Michigan, USA

Introduction

Throughout the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has been utilized to monitor the disease in the United States through routine national, statewide, and regional monitoring projects. A significant canon of evidence was produced showing that wastewater surveillance is a credible and effective tool for disease monitoring. Hence, the application of wastewater surveillance can extend beyond monitoring SARS-CoV-2 to encompass a diverse range of emerging diseases. This article proposed a ranking system for prioritizing reportable communicable diseases (CDs) in the Tri-County Detroit Area (TCDA), Michigan, for future wastewater surveillance applications at the Great Lakes Water Authority's Water Reclamation Plant (GLWA's WRP).

Methods

The comprehensive CD wastewater surveillance ranking system (CDWSRank) was developed based on 6 binary and 6 quantitative parameters. The final ranking scores of CDs were computed by summing the multiplication products of weighting factors for each parameter, and then were sorted based on decreasing priority. Disease incidence data from 2014 to 2021 were collected for the TCDA. Disease incidence trends in the TCDA were endowed with higher weights, prioritizing the TCDA over the state of Michigan.

Results

Disparities in incidences of CDs were identified between the TCDA and state of Michigan, indicating epidemiological differences. Among 96 ranked CDs, some top ranked CDs did not present relatively high incidences but were prioritized, suggesting that such CDs require significant attention by wastewater surveillance practitioners, despite their relatively low incidences in the geographic area of interest. Appropriate wastewater sample concentration methods are summarized for the application of wastewater surveillance as per viral, bacterial, parasitic, and fungal pathogens.

Discussion

The CDWSRank system is one of the first of its kind to provide an empirical approach to prioritize CDs for wastewater surveillance, specifically in geographies served by centralized wastewater collection in the area of interest. The CDWSRank system provides a methodological tool and critical information that can help public health officials and policymakers allocate resources. It can be used to prioritize disease surveillance efforts and ensure that public health interventions are targeted at the most potentially urgent threats. The CDWSRank system can be easily adopted to geographical locations beyond the TCDA.

Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications

Wastewater-based epidemiology (WBE) has been demonstrated for its great potential in tracking of coronavirus disease 2019 (COVID-19) transmission among populations despite some inherent methodological limitations. These include non-optimized sampling approaches and analytical methods; stability of viruses in sewer systems; partitioning/retention in biofilms; and the singular and inaccurate back-calculation step to predict the number of infected individuals in the community. Future research is expected to (1) standardize best practices in wastewater sampling, analysis and data reporting protocols for the sensitive and reproducible detection of viruses in wastewater; (2) understand the in-sewer viral stability and partitioning under the impacts of dynamic wastewater flow, properties, chemicals, biofilms and sediments; and (3) achieve smart wastewater surveillance with artificial intelligence and big data models. Further specific research is essential in the monitoring of other viral pathogens with pandemic potential and subcatchment applications to maximize the benefits of WBE beyond COVID-19.

Improving wastewater-based epidemiology performance through streamlined automation

Wastewater-based epidemiology (WBE) has enabled us to describe Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections in populations. However, implementation of wastewater monitoring of SARS-CoV-2 is limited due to the need for expert staff, expensive equipment, and prolonged processing times. As WBE increases in scope (beyond SARS-CoV-2) and scale (beyond developed regions), there is a need to make WBE processes simpler, cheaper, and faster. We developed an automated workflow based on a simplified method termed exclusion-based sample preparation (ESP). Our automated workflow takes 40 min from raw wastewater to purified RNA, which is several times faster than conventional WBE methods. The total assay cost per sample/replicate is $6.50 which includes consumables and reagents for concentration, extraction, and RT-qPCR quantification. The assay complexity is reduced significantly, as extraction and concentration steps are integrated and automated. The high recovery efficiency of the automated assay (84.5 ± 25.4%) yielded an improved Limit of Detection (LoDAutomated=40 copies/mL) compared to the manual process (LoDManual=206 copies/mL), increasing analytical sensitivity. We validated the performance of the automated workflow by comparing it with the manual method using wastewater samples from several locations. The results from the two methods correlated strongly (r = 0.953), while the automated method was shown to be more precise. In 83% of the samples, the automated method showed lower variation between replicates, which is likely due to higher technical errors in the manual process e.g., pipetting. Our automated wastewater workflow can support the expansion of WBE in the fight against Coronavirus Disease of 2019 (COVID-19) and other epidemics.

Degradation rates influence the ability of composite samples to represent 24-hourly means of SARS-CoV-2 and other microbiological target measures in wastewater

The utility of using severe-acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA for assessing the prevalence of COVID-19 within communities begins with the design of the sample collection program. The objective of this study was to assess the utility of 24-hour composites as representative samples for measuring multiple microbiological targets in wastewater, and whether normalization of SARS-CoV-2 by endogenous targets can be used to decrease hour to hour variability at different watershed scales. Two sets of experiments were conducted, in tandem with the same wastewater, with samples collected at the building, cluster, and community sewershed scales. The first set of experiments focused on evaluating degradation of microbiological targets: SARS-CoV-2, Simian Immunodeficiency Virus (SIV) - a surrogate spiked into the wastewater, plus human waste indicators of Pepper Mild Mottle Virus (PMMoV), Beta-2 microglobulin (B2M), and fecal coliform bacteria (FC). The second focused on the variability of these targets from samples, collected each hour on the hour. Results show that SARS-CoV-2, PMMoV, and B2M were relatively stable, with minimal degradation over 24-h. SIV, which was spiked-in prior to analysis, degraded significantly and FC increased significantly over the course of 24 h, emphasizing the possibility for decay and growth within wastewater. Hour-to-hour variability of the source wastewater was large between each hour of sampling relative to the variability of the SARS-CoV-2 levels calculated between sewershed scales; thus, differences in SARS-CoV-2 hourly variability were not statistically significant between sewershed scales. Results further provided that the quantified representativeness of 24-h composite samples (i.e., statistical equivalency compared against hourly collected grabs) was dependent upon the molecular target measured. Overall, improvements made by normalization were minimal within this study. Degradation and multiplication for other targets should be evaluated when deciding upon whether to collect composite or grab samples in future studies.

Number of COVID-19 cases required in a population to detect SARS-CoV-2 RNA in wastewater in the province of Alberta, Canada: Sensitivity assessment

With a unique and large size of testing results of 1,842 samples collected from 12 wastewater treatment plants (WWTP) for 14 months through from low to high prevalence of COVID-19, the sensitivity of RT-qPCR detection of SARS-CoV-2 RNA in wastewater that correspond to the communities was computed by using Probit analysis. This study determined the number of new COVID-19 cases per 100,000 population required to detect SARS-CoV-2 RNA in wastewater at defined probabilities and provided an evidence-based framework of wastewater-based epidemiology surveillance (WBE). Input data were positive and negative test results of SARS-CoV-2 RNA in wastewater samples and the corresponding new COVID-19 case rates per 100,000 population served by each WWTP. The analyses determined that RT-qPCR-based SARS-CoV-2 RNA detection threshold at 50%, 80% and 99% probability required a median of 8 (range: 4-19), 18 (9-43), and 38 (17-97) of new COVID-19 cases /100,000, respectively. Namely, the positive detection rate at 50%, 80% and 99% probability were 0.01%, 0.02%, and 0.04% averagely for new cases in the population. This study improves understanding of the performance of WBE SARS-CoV-2 RNA detection using the large datasets and prolonged study period. Estimated COVID-19 burden at a community level that would result in a positive detection of SARS-CoV-2 in wastewater is critical to support WBE application as a supplementary warning/monitoring system for COVID-19 prevention and control.

Persistence of endogenous RNA biomarkers of SARS-CoV-2 and PMMoV in raw wastewater: Impact of temperature and implications for wastewater-based epidemiology

Understanding the persistence of SARS-CoV-2 biomarkers in wastewater should guide wastewater-based epidemiology users in selecting best RNA biomarkers for reliable detection of the virus during current and future waves of the pandemic. In the present study, the persistence of endogenous SARS-CoV-2 were assessed during one month for six different RNA biomarkers and for the pepper mild mottle virus (PMMoV) at three different temperatures (4, 12 and 20 °C) in one wastewater sample. All SARS-CoV-2 RNA biomarkers were consistently detected during 6 days at 4° and differences in signal persistence among RNA biomarkers were mostly observed at 20 °C with N biomarkers being globally more persistent than RdRP, E and ORF1ab ones. SARS-CoV-2 signal persistence further decreased in a temperature dependent manner. At 12 and 20 °C, RNA biomarker losses of 1-log10 occurred on average after 6 and 4 days, and led to a complete signal loss after 13 and 6 days, respectively. Besides the effect of temperature, SARS-CoV-2 RNA signals were more persistent in the particulate phase compared to the aqueous one. Finally, PMMoV RNA signal was highly persistent in both phases and significantly differed from that of SARS-CoV-2 biomarkers. We further provide a detailed overview of the latest literature on SARS-CoV-2 and PMMoV decay rates in sewage matrices.

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

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

Diurnal Variability of SARS-CoV-2 RNA Concentrations in Hourly Grab Samples of Wastewater Influent during Low COVID-19 Incidence

Wastewater-based epidemiology (WBE) has been widely deployed during the COVID-19 pandemic, but with limited evaluation of the utility of discrete sampling for large sewersheds and low COVID-19 incidence. In this study, SARS-CoV-2 RNA was measured in 72 consecutive hourly influent grab samples collected at a wastewater treatment plant serving nearly 500 000 residents when incidence was low (approximately 20 cases per 100 000). We characterized diurnal variability and relationships between SARS-CoV-2 RNA detection and physicochemical covariates [flow rate, total ammonia nitrogen (TAN), and total solids (TS)]. The highest detection rate observed was 82% during the first peak flow, which occurred in the early afternoon (14:00). Higher detection rates were also observed when sampling above median TAN concentrations (71%; p < 0.01; median = 40.26 mg of NH4/L). SARS-CoV-2 RNA concentrations were weakly correlated with flow rate (Kendall's τ = 0.16; p < 0.01), TAN (τ = 0.19; p < 0.05), and TS (τ = 0.18; p < 0.01), suggesting generally low RNA sewer discharges as expected at low incidence. Our results elucidated sensible adjustments to maximize detection rates, including using multiple gene targets, collecting duplicate samples, and sampling during higher flow and TAN discharges. Optimizing the lower-incidence bounds of WBE can help assess its suitability for verifying COVID-19 reemergence or eradication.

Detection, Quantification, and Simplified Wastewater Surveillance Model of SARS-CoV-2 RNA in the Tijuana River

The COVID-19 pandemic and the detection of SARS-CoV-2 RNA in sewage has expanded global interest in wastewater surveillance. However, many underserved communities throughout the world lack improved sanitation and use informal combined sanitary and storm sewer systems. Sewage is transported via open channels, ditches, and rivers, where it mixes with surface water and/or stormwater. There is a need to develop better methods for the surveillance of pathogens such as SARS-CoV-2 RNA in this context. We developed a simplified surveillance system and monitored flow rates and concentrations of SARS-CoV-2 RNA in the Tijuana River at two locations downstream of the United States-Mexico border in California, United States. SARS-CoV-2 RNA was detected in the upstream location on six out of eight occasions, two of which were at concentrations as high as those reported in untreated wastewater from California sanitary sewer systems. The virus was not detected in any of the eight samples collected at the downstream (estuarine) sampling location, despite the consistent detection of PMMoV RNA. Synchrony was observed between the number of cases reported in Tijuana and the SARS-CoV-2 RNA concentrations measured with the CDC N1 assay when the latter were normalized by the reported flow rates in the river.

Case Study: Impact of Diurnal Variations and Stormwater Dilution on SARS-CoV-2 RNA Signal Intensity at Neighborhood Scale Wastewater Pumping Stations

Wastewater based epidemiology (WBE) has emerged as a tool to track the spread of SARS-CoV-2. However, sampling at wastewater treatment plants (WWTPs) cannot identify transmission hotspots within a city. Here, we sought to understand the diurnal variations (24 h) in SARS-CoV-2 RNA titers at the neighborhood level, using pump stations that serve vulnerable communities (e.g., essential workers, more diverse communities). Hourly composite samples were collected from wastewater pump stations located in (i) a residential area and (ii) a shopping district. In the residential area, SARS-CoV-2 RNA concentration (N1, N2, and E assays) varied by up to 42-fold within a 24 h period. The highest viral load was observed between 5 and 7 am, when viral RNA was not diluted by stormwater. Normalizing peak concentrations during this time window with nutrient concentrations (N and P) enabled correcting for rainfall to connect sewage to clinical cases reported in the sewershed. Data from the shopping district pump station were inconsistent, probably due to the fluctuation of customers shopping at the mall. This work indicates pump stations serving the residential area offer a narrow time period of high signal intensity that could improve the sensitivity of WBE, and tracer compounds (N, P concentration) can be used to normalize SARS-CoV-2 signals during rainfall.

The wave of the SARS-CoV-2 Omicron variant resulted in a rapid spike and decline as highlighted by municipal wastewater surveillance

This paper highlights the extraordinarily rapid spread of SARS-CoV-2 loads in wastewater that during the Omicron wave in December 2021-February 2022, compared with the profiles acquired in 2020-21 with 410 samples from two wastewater treatment plants (Trento+suburbs, 132,500 inhabitants). Monitoring of SARS-CoV-2 in wastewater focused on: (i) 3 samplings/week and analysis, (ii) normalization to calculate genomic units (GU) inh-1 d-1; (iii) calculation of a 7-day moving average to smooth daily fluctuations; (iv) comparison with the 'current active cases'/100,000 inh progressively affected by the mass vaccination. The time profiles of SARS-CoV-2 in wastewater matched the waves of active cases. In February-April 2021, a viral load of 1.0E＋07 GU inh-1 d- 1 corresponded to 700 active cases/100,000 inh. In July-September 2021, although the low current active cases, sewage revealed an appreciable SARS-CoV-2 circulation (in this period 2.2E＋07 GU inh-1 d-1 corresponded to 90 active cases/100,000 inh). Omicron was not detected in wastewater until mid-December 2021. The Omicron spread caused a 5-6 fold increase of the viral load in two weeks, reaching the highest peak (2.0-2.2E＋08 GU inh-1 d-1 and 4500 active cases/100,000 inh) during the pandemic. In this period, wastewater surveillance anticipated epidemiological data by about 6 days. In winter 2021-22, despite the 4-7 times higher viral loads in wastewater, hospitalizations were 4 times lower than in winter 2020-21 due to the vaccination coverage >80%. The Omicron wave demonstrated that SARS-CoV-2 monitoring of wastewater anticipated epidemiological data, confirming its importance in long-term surveillance.

Relationship between SARS-CoV-2 in wastewater and clinical data from five wastewater sheds

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has resulted in a global pandemic starting in 2019 with nearly 500 million confirmed cases as of April 2022. Infection with SARS-CoV-2 is accompanied by shedding of virus in stool, and its presence in wastewater samples has been documented globally. Therefore, monitoring of SARS-CoV-2 in wastewater offers a promising approach to assess the pandemic situation covering pre-symptomatic and asymptomatic cases in areas with limited clinical testing. In this study, the presence of SARS-CoV-2 RNA in wastewater from five wastewater resource recovery facilities (WRRFs), located in two adjacent counties, was investigated and compared with the number of clinical COVID-19 cases during a 2020-2021 outbreak in United States. Statistical correlation analyses of SARS-CoV-2 viral abundance in wastewater and COVID-19 daily vs weekly clinical cases was performed. While a weak correlation on a daily basis was observed, this correlation improved when weekly clinical case data were applied. The viral fecal indicator Pepper Mild Mottle Virus (PMMoV) was furthermore used to assess the effects of normalization and the impact of dilution due to infiltration in the wastewater sheds. Normalization did not improve the correlations with clinical data. However, PMMoV provided important information about infiltration and presence of industrial wastewater discharge in the wastewater sheds. This study showed the utility of WBE to assist in public health responses to COVID-19, emphasizing that routine monitoring of large WRRFs could provide sufficient information for large-scale dynamics.

Distribution of human fecal marker genes and their association with pathogenic viruses in untreated wastewater determined using quantitative PCR

Quantitative microbial risk assessment (QMRA) of human health risks using human fecal marker genes (HFMGs) is an useful water quality management tool. To inform accurate QMRA analysis, generation of probability distribution functions for HFMGs, and reference pathogenic viruses can be improved by input of correlation and ratios based upon measurement of HFMGs and gene copies (GC) of pathogenic viruses in untreated wastewater. The concentrations of four HFMGs (Bacteroides HF183, Lachnospiraceae Lachno3, CrAssphage and pepper mild mottle virus (PMMoV)), and GC of three reference pathogenic viruses human adenovirus 40/41 (HAdV 40/41), human norovirus GI + GII HNoV GI + GII and enterovirus (EV) were measured in untreated wastewater samples collected over a period of 12 months from two wastewater treatment plants in Sydney, Australia using quantitative polymerase chain reaction (qPCR) and reverse transcription qPCR (RT-qPCR). Over the course of the study, the GC of potential pathogenic viruses were 3-5 orders of magnitude lower than HFMGs in untreated wastewater. The GC of pathogenic viruses were highly variable over the course of the study, which contrasted with the concentrations of HFMGs that were quite stable with little variation observed within and between WWTPs. Among the HFMGs, HF183, CrAssphage and PMMoV correlated well with pathogenic virus GC, whereas weak or negative correlations were observed between Lachno3 and pathogenic virus GC. While the two assessed WWTPs had dissimilar population service sizes, the ratios between log₁₀ transformed pathogenic virus GC and HFMGs demonstrated similar central tendency and variability for the same combinations between WWTP A and WWTP B with no difference between the WWTPs. This suggests the widespread presence of these HFMGs in both populations serviced by these two WWTPs. The observed correlation and ratios of HFMGs and GC of reference pathogenic viruses can contribute to improved QMRA of human health risks in environmental waters subject to fresh sewer overflows.

Quantification of SARS-CoV-2 RNA in wastewater treatment plants mirrors the pandemic trend in Hong Kong

Wastewater-based epidemiology (WBE) for the SARS-CoV-2 virus in wastewater treatment plants (WWTPs) has emerged as a cost-effective and unbiased tool for population-level testing in the community. In the present study, we conducted a 6-month wastewater monitoring campaign from three WWTPs of different flow rates and catchment area characteristics, which serve 28 % (2.1 million people) of Hong Kong residents in total. Wastewater samples collected daily or every other day were concentrated using ultracentrifugation and the SARS-CoV-2 virus RNA in the supernatant was detected using the N1 and E primer sets. The results showed significant correlations between the virus concentration and the number of daily new cases in corresponding catchment areas of the three WWTPs when using 7-day moving average values (Kendall's tau-b value: 0.227-0.608, p < 0.001). SARS-CoV-2 virus concentration was normalized to a fecal indicator using PMMoV concentration and daily flow rates, but the normalization did not enhance the correlation. The key factors contributing to the correlation were also evaluated, including the sampling frequency, testing methods, and smoothing days. This study demonstrates the applicability of wastewater surveillance to monitor overall SARS-CoV-2 pandemic dynamics in a densely populated city like Hong Kong, and provides a large-scale longitudinal reference for the establishment of the long-term sentinel surveillance in WWTPs for WBE of pathogens which could be combined into a city-wide public health observatory.

Wastewater-based epidemiology in countries with poor wastewater treatment - Epidemiological indicator function of SARS-CoV-2 RNA in surface waters

Wastewater-based epidemiology (WBE) surveillance of COVID-19 and other future outbreaks is a challenge for developing countries as most households are not connected to a sewerage system. In December 2019, SARS-CoV-2 RNA was detected in the Danube River at a site severely affected by wastewaters from Belgrade. Rivers are much more complex systems than wastewater systems, and efforts are needed to address all the factors influencing the adoption of WBE as an alternative to targeting raw wastewater. Our objective was to provide a more detailed insight into the potential of SARS-CoV-2 surveillance in Serbian surface waters for epidemiological purposes. Water samples were collected at 12 sites along the Sava and Danube rivers in Belgrade during the fourth COVID-19 wave in Serbia that started in late February 2021. RNA was concentrated using Amicon Ultra-15 centrifugal filters and quantified using RT-qPCR with primer sets targeting nucleocapsid (N1 and N2) and envelope (E) protein genes. Microbiological (faecal indicator bacteria and human and animal genetic faecal source tracking markers), epidemiological, physicochemical and hydromorphological parameters were analysed in parallel. From 44 samples, SARS-CoV-2 RNA was detected in 31, but only at 4 concentrations above the level of quantification (ranging from 8.47 × 103 to 2.07 × 104 gc/L). The results indicated that surveillance of SARS-CoV-2 RNA in surface waters as ultimate recipients could be used as an epidemiological early-warning tool in countries lacking wastewater treatment and proper sewerage infrastructure. The performance of the applied approach, including advanced sampling site characterization to trace and identify sites with significant raw sewage influence from human populations, could be further improved by adaptation of the methodology for processing higher volumes of samples and enrichment factors, which should provide the quantitative instead of qualitative data needed for WBE.

The Catalan Surveillance Network of SARS-CoV-2 in Sewage: design, implementation, and performance

Wastewater-based epidemiology has shown to be an efficient tool to track the circulation of SARS-CoV-2 in communities assisted by wastewater treatment plants (WWTPs). The challenge comes when this approach is employed to help Health authorities in their decision-making. Here, we describe the roadmap for the design and deployment of SARSAIGUA, the Catalan Surveillance Network of SARS-CoV-2 in Sewage. The network monitors, weekly or biweekly, 56 WWTPs evenly distributed across the territory and serving 6 M inhabitants (80% of the Catalan population). Each week, samples from 45 WWTPs are collected, analyzed, results reported to Health authorities, and finally published within less than 72 h in an online dashboard ( https://sarsaigua.icra.cat ). After 20 months of monitoring (July 20-March 22), the standardized viral load (gene copies/day) in all the WWTPs monitored fairly matched the cumulative number of COVID-19 cases along the successive pandemic waves, showing a good fit with the diagnosed cases in the served municipalities (Spearman Rho = 0.69). Here we describe the roadmap of the design and deployment of SARSAIGUA while providing several open-access tools for the management and visualization of the surveillance data.

Population level SARS-CoV-2 fecal shedding rates determined via wastewater-based epidemiology

Wastewater-based epidemiology (WBE) has been utilized as an early warning tool to anticipate disease outbreaks, especially during the COVID-19 pandemic. However, COVID-19 disease models built from wastewater-collected data have been limited by the complexities involved in estimating SARS-CoV-2 fecal shedding rates. In this study, wastewater from six municipalities in Arizona and Florida with distinct demographics were monitored for SARS-CoV-2 RNA between September 2020 and December 2021. Virus concentrations with corresponding clinical case counts were utilized to estimate community-wide fecal shedding rates that encompassed all infected individuals. Analyses suggest that average SARS-CoV-2 RNA fecal shedding rates typically occurred within a consistent range (7.53-9.29 log10 gc/g-feces); and yet, were unique to each community and influenced by population demographics. Age, ethnicity, and socio-economic factors may have influenced shedding rates. Interestingly, populations with median age between 30 and 39 had the greatest fecal shedding rates. Additionally, rates remained relatively constant throughout the pandemic provided conditions related to vaccination and variants were unchanged. Rates significantly increased in some communities when the Delta variant became predominant. Findings in this study suggest that community-specific shedding rates may be appropriate in model development relating wastewater virus concentrations to clinical case counts.

Research needs for optimising wastewater-based epidemiology monitoring for public health protection

Wastewater-based epidemiology (WBE) is an unobtrusive method used to observe patterns in illicit drug use, poliovirus, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The pandemic and need for surveillance measures have led to the rapid acceleration of WBE research and development globally. With the infrastructure available to monitor SARS-CoV-2 from wastewater in 58 countries globally, there is potential to expand targets and applications for public health protection, such as other viral pathogens, antimicrobial resistance (AMR), pharmaceutical consumption, or exposure to chemical pollutants. Some applications have been explored in academic research but are not used to inform public health decision-making. We reflect on the current knowledge of WBE for these applications and identify barriers and opportunities for expanding beyond SARS-CoV-2. This paper critically reviews the applications of WBE for public health and identifies the important research gaps for WBE to be a useful tool in public health. It considers possible uses for pathogenic viruses, AMR, and chemicals. It summarises the current evidence on the following: (1) the presence of markers in stool and urine; (2) environmental factors influencing persistence of markers in wastewater; (3) methods for sample collection and storage; (4) prospective methods for detection and quantification; (5) reducing uncertainties; and (6) further considerations for public health use.

Wastewater treatment plant operators report high capacity to support wastewater surveillance for COVID-19 across New York State, USA

Wastewater surveillance for infectious disease expanded greatly during the COVID-19 pandemic. As a collaboration between sanitation engineers and scientists, the most cost-effective deployment of wastewater surveillance routinely tests wastewater samples from wastewater treatment plants. To evaluate the capacity of treatment plants of different sizes and characteristics to participate in surveillance efforts, we developed and distributed a survey to New York State municipal treatment plant supervisors in the summer and fall of 2021. The goal of the survey was to assess the knowledge, capacity, and attitudes toward wastewater surveillance as a public health tool. Our objectives were to: (1) determine what treatment plant operators know about wastewater surveillance for public health; (2) assess how plant operators feel about the affordability and benefits of wastewater surveillance; and (3) determine how frequently plant personnel can take and ship samples using existing resources. Results show that 62% of respondents report capacity to take grab samples twice weekly. Knowledge about wastewater surveillance was mixed with most supervisors knowing that COVID-19 can be tracked via wastewater but having less knowledge about surveillance for other public health issues such as opioids. We found that attitudes toward wastewater testing for public health were directly associated with differences in self-reported capacity of the plant to take samples. Further, findings suggest a diverse capacity for sampling across sewer systems with larger treatment plants reporting greater capacity for more frequent sampling. Findings provide guidance for outreach activities as well as important insight into treatment plant sampling capacity as it is connected to internal factors such as size and resource availability. These may help public health departments understand the limitations and ability of wastewater surveillance for public health benefit.

CrAssphage as an indicator of human-fecal contamination in water environment and virus reduction in wastewater treatment

Viral indicators of human-fecal contamination in wastewaters and environmental waters have been getting much attention in the past decade. Cross-assembly phage (crAssphage) is the most abundant DNA virus in human feces. Recently, the usefulness of crAssphage as a microbial source tracking and water quality monitoring tool for human-fecal contamination has been highlighted. Here, we conducted a comprehensive review on crAssphage in water, focusing on detection methodology, concentration range in various waters and wastewaters, specificity to human-fecal contamination, and reduction in wastewater treatment systems. This review highlights that crAssphage is globally distributed in wastewaters and various fecal-contaminated water bodies at high concentrations without seasonal fluctuations. CrAssphage is highly specific to human-fecal contamination and is rarely found in animal feces. It also has a good potential as a performance indicator to ensure virus reduction in wastewater treatment systems. Accordingly, crAssphage could be an effective tool for monitoring of human-fecal contamination and potential presence of fecal pathogenic microbes in environmental waters. Bridging the research gaps highlighted in this review would make crAssphage a powerful tool to support the control of water-related health risks.

Monitoring of SARS-CoV-2 in sewersheds with low COVID-19 cases using a passive sampling technique

Monitoring SARS-CoV-2 RNA in sewer systems, upstream of a wastewater treatment plant, is an effective approach for understanding potential COVID-19 transmission in communities with higher spatial resolutions. Passive sampling devices provide a practical solution for frequent sampling within sewer networks where the use of autosamplers is not feasible. Currently, the design of upstream sampling is impeded by limited understanding of the fate of SARS-CoV-2 RNA in sewers and the sensitivity of passive samplers for the number of infected individuals in a catchment. In this study, passive samplers containing electronegative membranes were applied for at least 24-h continuous sampling in sewer systems. When monitoring SARS-CoV-2 along a trunk sewer pipe, we found RNA signals decreased proportionally to increasing dilutions, with non-detects occurring at the end of pipe. The passive sampling membranes were able to detect SARS-CoV-2 shed by >2 COVID-19 infection cases in 10,000 people. Moreover, upstream monitoring in multiple sewersheds using passive samplers identified the emergence of SARS-CoV-2 in wastewater one week ahead of clinical reporting and reflected the spatiotemporal spread of a COVID-19 cluster within a city. This study provides important information to guide the development of wastewater surveillance strategies at catchment and subcatchment levels using different sampling techniques.

Wastewater surveillance for SARS-CoV-2 to support return to campus: Methodological considerations and data interpretation

The COVID-19 pandemic has been challenging for various institutions such as school systems due to widespread closures. As schools re-open their campuses to in-person education, there is a need for frequent screening and monitoring of the virus to ensure the safety of students and staff and to limit risk to the surrounding community. Wastewater surveillance (WWS) of SARS-CoV-2 is a rapid and economical approach to determine the extent of COVID-19 in the community. The focus of this review is on the emergence of WWS as a tool for safe return to school campuses, taking into account methodological considerations such as site selection, sample collection and processing, SARS-CoV-2 quantification, and data interpretation. Recently published studies on the implementation of COVID-19 WWS on school and college campuses were reviewed. While there are several logistical and technical challenges, WWS can be used to inform decision-making at the school campus and/or building level.

Sampling strategies for wastewater surveillance: Evaluating the variability of SARS-COV-2 RNA concentration in composite and grab samples

The shedding of SARS-CoV-2 RNA titers by infected individuals, even asymptomatic and oligosymptomatic ones, allows the use of wastewater monitoring to track the COVID-19 spread in a community. This approach is interesting especially for emerging countries with limited clinical testing capabilities. However, there are still important methodological aspects that need validation so that wastewater monitoring data become more representative and useful for public health. This study evaluated the between-day and within-day variability of SARS-CoV-2 RNA concentrations in 24-hour composite and grab samples from three different sampling points, including two wastewater treatment plants (WTTP) and a sewer manhole. In the between-day evaluation (17 weeks of monitoring), a good agreement between the SARS-CoV-2 RNA concentration of each sampling method was observed. There were no significant differences between the mean concentrations of the grab and composite samples (p-value > 0.05), considering N1 and N2 gene assays. The strong relationship between composite and grab samples was proven by correlation coefficients: Pearson's r of 0.83 and Spearman's rho of 0.78 (p-value < 0.05). In within-day evaluation, 24-hour cycles were analyzed and low variability in hourly viral concentrations was observed for three sampling points. The coefficient of variation (CV) values ranged from 3.0% to 11.5%. Overall, 24-hour profiles showed that viral RNA concentrations had less variability and greater agreement with the mean values between 8 a.m. and 10 a.m, the recommended time for grab sampling. Therefore, this study provides important information on wastewater sampling techniques for COVID-19 surveillance. Wastewater monitoring information will only be useful to public health and decision-makers if we ensure data quality through best practices.

Factors influencing SARS-CoV-2 RNA concentrations in wastewater up to the sampling stage: A systematic review

Wastewater-based surveillance (WBS) for SARS-CoV-2 RNA is a promising complementary approach to monitor community viral circulation. A myriad of factors, however, can influence RNA concentrations in wastewater, impeding its epidemiological value. This article aims to provide an overview and discussion of factors up to the sampling stage that impact SARS-CoV-2 RNA concentration estimates in wastewater. To this end, a systematic review was performed in three databases (MEDLINE, Web of Science and Embase) and two preprint servers (MedRxiv and BioRxiv). Two authors independently screened and selected articles published between January 1, 2019 and May 4, 2021. A total of 22 eligible articles were included in this systematic review. The following factors up to sampling were identified to have an influence on SARS-CoV-2 RNA concentrations in wastewater and its interpretation: (i) shedding-related factors, including faecal shedding parameters (i.e. shedding pattern, recovery, rate, and load distribution), (ii) population size, (iii) in-sewer factors, including solid particles, organic load, travel time, flow rate, wastewater pH and temperature, and (iv) sampling strategy. In conclusion, factors influencing SARS-CoV-2 RNA concentration estimates in wastewater were identified and research gaps were discussed. The identification of these factors supports the need for further research on WBS for COVID-19.

Validating and optimizing the method for molecular detection and quantification of SARS-CoV-2 in wastewater

Wastewater surveillance of SARS-CoV-2 has become a promising tool to estimate population-level changes in community infections and the prevalence of COVID-19 disease. Although many studies have reported the detection and quantification of SARS-CoV-2 in wastewater, remarkable variation remains in the methodology. In this study, we validated a molecular testing method by concentrating viruses from wastewater using ultrafiltration and detecting SARS-CoV-2 using one-step RT-qPCR assay. The following parameters were optimized including sample storage condition, wastewater pH, RNA extraction and RT-qPCR assay by quantification of SARS-CoV-2 or spiked human coronavirus strain 229E (hCoV-229E). Wastewater samples stored at 4 °C after collection showed significantly enhanced detection of SARS-CoV-2 with approximately 2-3 PCR-cycle threshold (Ct) values less when compared to samples stored at -20 °C. Pre-adjustment of the wastewater pH to 9.6 to aid virus desorption followed by pH readjustment to neutral after solid removal significantly increased the recovery of spiked hCoV-229E. Of the five commercially available RNA isolation kits evaluated, the MagMAX-96 viral RNA isolation kit showed the best recovery of hCoV-229E (50.1 ± 20.1%). Compared with two-step RT-qPCR, one-step RT-qPCR improved sensitivity for SARS-CoV-2 detection. Salmon DNA was included for monitoring PCR inhibition and pepper mild mottle virus (PMMoV), a fecal indicator indigenous to wastewater, was used to normalize SARS-CoV-2 levels in wastewater. Our method for molecular detection of SARS-CoV-2 in wastewater provides a useful tool for public health surveillance of COVID-19.

SARS-CoV-2 RNA surveillance in large to small centralized wastewater treatment plants preceding the third COVID-19 resurgence in Bangkok, Thailand

Wastewater surveillance for SARS-CoV-2 RNA has been a successful indicator of COVID-19 outbreaks in populations prior to clinical testing. However, this has been mostly conducted in high-income countries, which means there is a dearth of performance investigations in low- and middle-income countries with different socio-economic settings. This study evaluated the applicability of SARS-CoV-2 RNA monitoring in wastewater (n = 132) to inform COVID-19 infection in the city of Bangkok, Thailand using CDC N1 and N2 RT-qPCR assays. Wastewater influents (n = 112) and effluents (n = 20) were collected from 19 centralized wastewater treatment plants (WWTPs) comprising four large, four medium, and 11 small WWTPs during seven sampling events from January to April 2021 prior to the third COVID-19 resurgence that was officially declared in April 2021. The CDC N1 assay showed higher detection rates and mostly lower Ct values than the CDC N2. SARS-CoV-2 RNA was first detected at the first event when new reported cases were low. Increased positive detection rates preceded an increase in the number of newly reported cases and increased over time with the reported infection incidence. Wastewater surveillance (both positive rates and viral loads) showed strongest correlation with daily new COVID-19 cases at 22-24 days lag (Spearman's Rho = 0.85-1.00). Large WWTPs (serving 432,000-580,000 of the population) exhibited similar trends of viral loads and new cases to those from all 19 WWTPs, emphasizing that routine monitoring of the four large WWTPs could provide sufficient information for the city-scale dynamics. Higher sampling frequency at fewer sites, i.e., at the four representative WWTPs, is therefore suggested especially during the subsiding period of the outbreak to indicate the prevalence of COVID-19 infection, acting as an early warning of COVID-19 resurgence.