Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater

Fluorescence damping as primary interference mechanism of humic acids on qPCR quantification of SARS-CoV-2 in wastewater surveillance

Real-time polymerase chain reaction (qPCR) is a widely used technology for the detection and quantification of nucleic acids in wastewater surveillance. However, the presence of inhibiting and/or interfering substances in wastewater samples, in particular humic acids, can significantly impact the accuracy and reliability of qPCR results. In this study, we investigated the impact of humic acids on qPCR reactions and determined the relative importance of various inhibition/interference mechanisms through spiked experiments and modeling. Our results showed that higher concentrations of humic acids led to increasing threshold cycle (CT) values, which however cannot be adequately described by the polymerase inhibition model and the DNA template complexation model. Further inspection showed that humic acids caused fluorescence damping of the FAM reporter dye, resulting in an overall decrease in fluorescence intensity. Modeling of the fluorescence damping effect showed that the CT values of qPCR reactions can be corrected based on end-point fluorescence reduction. Similar observations and corrections were also achieved when SARS-CoV-2 cDNA was spiked with an actual wastewater sludge cDNA.

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.

6-plex Crystal Digital PCR® for comprehensive surveillance of respiratory and foodborne bacterial pathogens in wastewater

Bacterial wastewater surveillance (WS) is less explored area compared to viral WS despite high burden of bacterial respiratory and gastrointestinal infections worldwide. This study established a 6-plex Crystal Digital PCR® (cdPCR) system, to comprehensively monitor an acute respiratory pathogen - Group A Streptococcus (GAS) pyogenes, foodborne disease (FBD) pathogens - Clostridium perfringens, Salmonella spp., Campylobacter jejuni, and Campylobacter coli, and an indicator bacterium, Escherichia coli in wastewater. Fifty-two grab influent samples collected weekly from a wastewater treatment plant in Yamanashi Prefecture, Japan, between June 2023 and May 2024 were centrifuged, followed by DNA extraction and cdPCR. cdPCR was performed using the naica® system (Stilla Technologies). The 6-plex cdPCR assays showed strong performance. Among the 52 samples, 100 % of samples were positive for C. perfringens, 98 % for Salmonella spp., 56 % for C. jejuni, 25 % for C. coli, and 63 % for S. pyogenes, with concentrations ranging between 4.2 ± 0.3 to 7.5 ± 0.2 log10 copies/L. The concentration of C. perfringens was significantly higher than that of other pathogens (p < 0.05), indicating its dominance. Salmonella spp. had high detection rate, implying increased Salmonella infection in the population. Seasonal variation was not observed in any of FBD pathogens, except for the detection rate of C. coli. S. pyogenes concentrations were significantly higher in spring than in other seasons, agreeing with the trend of GAS pharyngitis cases in the catchment. In conclusion, the 6-plex cdPCR system is a valuable tool for comprehensive WS, offering significant implications for public health monitoring.

Hyperplex PCR enables highly multiplexed analysis of point mutations in wastewater: Long-term SARS-CoV-2 variant surveillance in Sweden as a case study

Wastewater-based surveillance (WBS) allows the analysis of pathogens, chemicals or other biomarkers in wastewater to derive unbiased epidemiological information at population scale. After re-gaining attention during the SARS-CoV-2 pandemic, the field holds promise as a surveillance and early warning system by tracking emerging pathogens with pandemic potential. Expanding the current toolbox of analytical techniques for wastewater analysis, we explored the use of Hyperplex PCR (hpPCR) to analyse SARS-CoV-2 mutations in wastewater samples collected weekly in up to 22 sites across Sweden between October 2022 and December 2023. The samples were tested using a probe panel ranging from 10- to 18-plex, continuously adapted within 1-2 weeks to quantify relevant mutations of concern over time. For cross-validation, the samples were simultaneously analysed with commonly used methods including quantitative PCR (qPCR) and next-generation sequencing (NGS). hpPCR is demonstrated herein to provide (1) systematic single nucleotide specificity with a straightforward probe design, (2) high multiplexity with minimal panel re-optimization requirements and (3) 4-5-week earlier mutation detection relative to NGS with comparable performance of mutation frequency quantification (Pearson r = 0.88, n = 50). Hence, hpPCR is shown to be a powerful complementary tool to the current workflow involving NGS and qPCR by facilitating the assembly of dynamic high-plex panels compatible with high-frequency monitoring of multiple key pathogens and/or variants in WBS.

Simplifying SARS-CoV-2 wastewater-based surveillance using an automated FDA EUA assay

Wastewater-based surveillance (WBS) can track the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in communities. Laboratory methods for this testing involve labor-intensive, multi-step processes. This study assessed the feasibility of performing WBS with an off-label use of an automated commercial SARS-CoV-2 assay that had received Emergency Use Authorization for human diagnostic testing from the United States Food and Drug Administration (FDA EUA). Twenty-four-hour composite samples of primary influent wastewater from seven municipalities in New Hampshire and Vermont were collected between September 2020 and February 2021, and were centrifuged upon receipt. An aliquot of fresh supernatant was immediately tested with the Abbott m2000 RealTime SARS-CoV-2 assay (Abbott Molecular, Des Plaines, IL, USA). Corresponding aliquots were then stored at -80°C until they were thawed, polyethylene glycol (PEG) concentrated, and tested by two PCR-based laboratory-developed tests (LDTs). Wastewater samples (103) were tested with successful detection of SARS-CoV-2 viral RNA by all three methods. Bland-Altman analysis showed overall concordant results with a bias of -0.13 and -0.42 log copies/mL detected by the FDA EUA assay compared to the LDTs. Specimen stability assessment demonstrated a decrease of 33.9% measurable viral RNA after three freeze-thaw cycles. SARS-CoV-2 detection in wastewater using an FDA EUA assay on an automated commercial testing platform performed comparably but with more efficient workflow when compared to two LDTs. This sample-to-answer automated method could save time and labor for surveillance testing, but further validation of its ability to quantitate SARS-CoV-2 viral RNA is necessary.IMPORTANCEThis proof-of-principle study evaluates an off-label use of an automated United States Food and Drug Administration (FDA) Emergency Use Authorization (EUA) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) human diagnostic assay for wastewater surveillance. Compared to standard, labor-intensive, multi-step methods currently in use for wastewater surveillance testing, an off-label use of an FDA EUA assay on an automated platform offers a sample-to-answer testing requiring less labor and a faster turnaround time.

Development and evaluation of the digital PCR-based method for clinical monitoring of viral loads during severe fever with thrombocytopenia syndrome virus infection

BACKGROUND

Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) represents a novel bunyavirus that poses significant public health challenges. As a key prognostic indicator of clinical outcome, the viral load determined by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is relatively inaccurate and incomparable across different studies. Digital PCR (dPCR) has recently proved to be a more ideal tool for viral load assessment.

OBJECTIVE

To develop a dPCR-based S-segment-specific method for SFTSV viral load monitoring and evaluate its performance in clinical samples.

STUDY DESIGN

Specific dPCR was developed using primers/probes for the N region in the S segment of the SFTSV genome. The performance of dPCR was confirmed using serial dilutions of viral cultures, and dPCR viral load quantification was compared with the result of RT-qPCR in 166 suspected SFTS patients.

RESULTS

DPCR demonstrated superior sensitivity with a detection limit of 190.5 copies/mL, high linearity, and good reproducibility. Six false negative samples were detected by dPCR among the 28 RT-qPCR negative samples. The correlation between RT-qPCR and dPCR was low at a low viral load level. Both dPCR and RT-qPCR were important risk factors for severity and mortality by the multivariate logistic regression analysis The accurate viral load based on dPCR has a strong predictive ability for patient outcomes and shows significant correlation with multiple host response markers.

CONCLUSION

The results suggest that dPCR is a highly sensitive alternative to the measurement of SFTSV and should be considered for clinical utilization in patients with suspected SFTS.

Analysis insights to support the use of wastewater and environmental surveillance data for infectious diseases and pandemic preparedness

Wastewater-based epidemiology is the detection of pathogens from sewage systems and the interpretation of these data to improve public health. Its use has increased in scope since 2020, when it was demonstrated that SARS-CoV-2 RNA could be successfully extracted from the wastewater of affected populations. In this Perspective we provide an overview of recent advances in pathogen detection within wastewater, propose a framework for identifying the utility of wastewater sampling for pathogen detection and suggest areas where analytics require development. Ensuring that both data collection and analysis are tailored towards key questions at different stages of an epidemic will improve the inference made. For analyses to be useful we require methods to determine the absence of infection, early detection of infection, reliably estimate epidemic trajectories and prevalence, and detect novel variants without reliance on consensus sequences. This research area has included many innovations that have improved the interpretation of collected data and we are optimistic that innovation will continue in the future.

The use of wastewater surveillance to estimate SARS-CoV-2 fecal viral shedding pattern and identify time periods with intensified transmission

BACKGROUND

Wastewater-based surveillance is an important tool for monitoring the COVID-19 pandemic. However, it remains challenging to translate wastewater SARS-CoV-2 viral load to infection number, due to unclear shedding patterns in wastewater and potential differences between variants.

OBJECTIVES

We utilized comprehensive wastewater surveillance data and estimates of infection prevalence (i.e., the source of the viral shedding) available for New York City (NYC) to characterize SARS-CoV-2 fecal shedding pattern over multiple COVID-19 waves.

METHODS

We collected SARS-CoV-2 viral wastewater measurements in NYC during August 31, 2020 - August 29, 2023 (N = 3794 samples). Combining with estimates of infection prevalence (number of infectious individuals including those not detected as cases), we estimated the time-lag, duration, and per-infection fecal shedding rate for the ancestral/Iota, Delta, and Omicron variants, separately. We also developed a procedure to identify occasions with intensified transmission.

RESULTS

Models suggested fecal viral shedding likely starts around the same time as and lasts slightly longer than respiratory tract shedding. Estimated fecal viral shedding rate was highest during the ancestral/Iota variant wave, at 1.44 (95% CI: 1.35 - 1.53) billion RNA copies in wastewater per day per infection (measured by RT-qPCR), and decreased by around 20% and 50-60% during the Delta wave and Omicron period, respectively. We identified around 200 occasions during which the wastewater SARS-CoV-2 viral load exceeded the expected level in any of the city's 14 sewersheds. These anomalies disproportionally occurred during late January, late April-early May, early August, and from late-November to late-December, with frequencies exceeding the expectation assuming random occurrence (P < 0.05; bootstrapping test).

DISCUSSION

These estimates may be useful in understanding changes in underlying infection rate and help quantify changes in COVID-19 transmission and severity over time. We have also demonstrated that wastewater surveillance data can support the identification of time periods with potentially intensified transmission.

Optimization of a 6-plex Crystal Digital PCR® assay and its application to simultaneous surveillance of enteric and respiratory viruses in wastewater

Multiplex digital PCR (dPCR) approaches are commonly employed in wastewater-based epidemiology (WBE) studies. However, optimizing the dPCR workflow is a critical step to ensure its reliability and accuracy before application. In this study, a 6-plex Crystal Digital PCR® (cdPCR) workflow was optimized for the simultaneous detection of six epidemiologically important pathogens, including three enteric viruses, noroviruses of genogroups I and II (NoV-GI and GII) and enteroviruses (EnV), and three respiratory viruses, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), influenza A virus (InfA), and respiratory syncytial virus B (RSVB), in wastewater. Four cDNA input ratios (20 %-70 %) and two extraction kits were evaluated for optimization, with 30 % cDNA input and the AllPrep PowerViral DNA/RNA Kit (Qiagen) exhibiting optimal performance. The optimized 6-plex cdPCR assay was applied to a year-long wastewater surveillance study in Japan (n = 52), revealing distinct trends and prevalence ratios for enteric and respiratory viruses. NoV-GII was detected in 96 % of the samples with the highest mean concentration (6.1 ± 0.6 log10 copies/L), while SARS-CoV-2 and InfA were detected in 60 % and 50 % of the samples, respectively, which reflected the circulation of these pathogens within the community. Notably, RSVB was detected less frequently (25 %), in line with the fewer cases of RSVB reported during the study period. The wastewater concentrations of EnV and InfA showed significant positive correlations with hand foot and mouth disease and herpangina and influenza cases, respectively. However, no positive correlations were observed for RSV and COVID-19, possibly due to the testing of RSVB while RSVA was more prevalent and also due to cluster outbreaks. These findings demonstrated the utility of the 6-plex cdPCR assay in detecting pathogens and provided insights into community disease trends, representing an advancement in WBE.

Harnessing Non-standard Nucleic Acids for Highly Sensitive Icosaplex (20-Plex) Detection of Microbial Threats for Environmental Surveillance

Environmental surveillance and clinical diagnostics heavily rely on the polymerase chain reaction (PCR) for target detection. A growing list of microbial threats warrants new PCR-based detection methods that are highly sensitive, specific, and multiplexable. Here, we introduce a PCR-based icosaplex (20-plex) assay for detecting 18 enteropathogen and two antimicrobial resistance genes. This multiplexed PCR assay leverages the self-avoiding molecular recognition system (SAMRS) to avoid primer dimer formation, the artificially expanded genetic information system (AEGIS) for amplification specificity, and next-generation sequencing for amplicon identification. Using parallelized multitarget TaqMan Array Cards (TAC) to benchmark performance of the 20-plex assay on wastewater, soil, and human stool samples, we found 90% agreement on positive calls and 89% agreement on negative calls. Additionally, we show how long-read and short-read sequencing information from the 20-plex can be used to further classify allelic variants of genes and distinguish subspecies. The strategy presented offers sensitive, affordable, and robust multiplex detection that can be used to support efforts in wastewater-based epidemiology, environmental monitoring, and human/animal diagnostics.

Bacterial Wastewater-Based Epidemiology Using Surface-Enhanced Raman Spectroscopy and Machine Learning

Although wastewater-based epidemiology has been used extensively for the surveillance of viral diseases, it has not been used to a similar extent for bacterial diseases. This is in part owing to difficulties in distinguishing pathogenic from nonpathogenic bacteria using PCR methods. Here, we show that surface-enhanced Raman spectroscopy (SERS) can be a scalable, label-free method for the detection of bacteria in wastewater. We enhance Raman signal from bacteria in wastewater using plasmonic gold nanorods (AuNRs) that electrostatically bind to the bacterial surface and confirm this binding using cryoelectron microscopy. We spike four clinically relevant bacterial species and AuNRs into filtered wastewater, varying the AuNR concentration to maximize the signal. We then collect 540 spectra from each species at 109 cells/mL and train a machine learning model to identify them with more than 87% accuracy. We also demonstrate an environmentally realistic limit of detection of 104 cells/mL. These results are a key step toward a SERS platform for bacterial WBE.

The Impact of Viral Concentration Method on Quantification and Long Amplicon Nanopore Sequencing of SARS-CoV-2 and Noroviruses in Wastewater

Wastewater-based surveillance has gained attention in the four years following the start of the COVID-19 pandemic. Accurate pathogen detection, quantification and characterisation rely on the selection of appropriate methodologies. Here, we explore the impact of viral concentration method on RT-qPCR inhibition and quantification of norovirus genogroups I and II (GI and GII), crAssphage, phi6 and SARS-CoV-2. Additionally, their impact on long amplicon sequencing for typing noroviruses and whole-genome sequencing (WGS) SARS-CoV-2 was explored. RT-qPCR inhibition for each viral concentration method was significantly different apart from the two ultrafiltration methods, InnovaPrep® concentrating pipette (IP) and Vivaspin® (VS) centrifugal concentrators. Using an ultrafiltration method reduced inhibition by 62.0% to 96.0% compared to the ammonium sulphate (AS) and polyethylene glycol (PEG) precipitation-based methods. Viral quantification was significantly impacted by concentration method with the highest concentrations (copies/L) observed for VS with 7.2- to 83.2-fold differences from AS depending on the target. Norovirus long amplicon sequencing showed genotype-dependent differences with IP performing best for GI and VS for GII although IP performance gains for GI were relatively small. VS outperformed AS and IP across all metrics during SARS-CoV-2 WGS. Overall, VS performed the best when considering all the areas of investigation.

Establishing methods to monitor H5N1 influenza virus in dairy cattle milk

Highly Pathogenic Avian Influenza strain H5N1 has caused a multi-state outbreak among US dairy cattle, spreading across 15 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk from 20 states for methods development, we found that H5N1 concentrations by digital PCR strongly correlated with qPCR cycle threshold (Ct) values, with dPCR exhibiting greater sensitivity. We also found that metagenomic sequencing after hybrid selection was best for higher concentration samples while amplicon sequencing performs best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to test bulk milk samples monthly from all cattle dairy farms within Massachusetts, which remain negative to date. The methods, workflow, and recommendations described here provide a framework for others aiming to conduct H5N1 surveillance efforts.

Effective Inhibitor Removal from Wastewater Samples Increases Sensitivity of RT-dPCR and Sequencing Analyses and Enhances the Stability of Wastewater-Based Surveillance

Wastewater-based surveillance (WBS) is a proven tool for monitoring population-level infection events. Wastewater contains high concentrations of inhibitors, which contaminate the total nucleic acids (TNA) extracted from these samples. We found that TNA extracts from raw influent of Berlin wastewater treatment plants contained highly variable amounts of inhibitors that impaired molecular analyses like dPCR and next-generation sequencing (NGS). By using dilutions, we were able to detect inhibitory effects. To enhance WBS sensitivity and stability, we applied a combination of PCR inhibitor removal and TNA dilution (PIR+D). This approach led to a 26-fold increase in measured SARS-CoV-2 concentrations, practically reducing the detection limit. Additionally, we observed a substantial increase in the stability of the time series. We define suitable stability as a mean absolute error (MAE) below 0.1 log10 copies/L and a geometric mean relative absolute error (GMRAE) below 26%. Using PIR+D, the MAE could be reduced from 0.219 to 0.097 and the GMRAE from 65.5% to 26.0%, and even further in real-world WBS. Furthermore, PIR+D improved SARS-CoV-2 genome alignment and coverage in amplicon-based NGS for low to medium concentrations. In conclusion, we strongly recommend both the monitoring and removal of inhibitors from samples for WBS.

Urban wastewater contains a functional human antibody repertoire of mucosal origin

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

The effects of RT-qPCR standards on reproducibility and comparability in monitoring SARS-CoV-2 levels in wastewater

Reverse transcription-quantitative PCR (RT-qPCR) is widely used for monitoring viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in wastewater. Various materials, including plasmid DNA, synthetic nucleic acids, PCR amplicons, genomic DNA, and cDNA, are currently used for SARS-CoV-2 quantification by generating standard curves. We assessed three common standards on quantifying SARS-CoV-2 RNA across nine wastewater treatment plants in Finland, as part of the national wastewater surveillance effort. We pairwise compared RT-qPCR results from 148 wastewater samples, using both IDT (#10006625, IDT, USA) and CODEX standards (#SC2-RNAC-1100, CODEX DNA), and 179 samples using both IDT and EURM019 standards (#EURM-019, European Commission, Joint Research Centre) in our assessment. Amongst the tested standards, the CODEX standard consistently yielded more stable results than either the IDT or EURM019 standards. We found that SARS-CoV-2 levels were higher with the IDT standard (4.36 Log10 GC/100 mL) compared to the CODEX standard (4.05 Log10 GC/100 mL). Similarly, quantification using the IDT standard was higher (5.27 Log10 GC/100 mL) than values obtained with the EURM019 (4.81 Log10 GC/100 mL). SARS-CoV-2 RNA quantified with IDT and CODEX standards exhibited stronger concordance (Spearman's correlation rho median of 0.79) compared to those quantified with IDT and EURM019 standards (rho median of 0.59). This study highlights the significant impact of standard material selection on SARS-CoV-2 RNA quantification, emphasizing the need for harmonization in standard material.

The comparison of decay rates of infectious SARS-CoV-2 and viral RNA in environmental waters and wastewater

Understanding the decay characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater and ambient waters is important for multiple applications including assessment of risk of exposure associated with handling wastewater samples, public health risk associated with recreation in wastewater polluted ambient waters and better understanding and interpretation of wastewater-based epidemiology (WBE) results. We evaluated the decay rates of infectious SARS-CoV-2 and viral RNA in wastewater and ambient waters under temperature regimes representative of seasonal fluctuations. Infectious virus was seeded in autoclaved primary wastewater effluent, final dechlorinated wastewater effluent, lake water, and marine water at a final concentration of 6.26 ± 0.07 log10 plaque forming units per milliliter. Each suspension was incubated at either 4°, 25°, and 37 °C. Samples were initially collected on an hourly basis, then approximately every other day for 15 days. All samples were analyzed for infectious virus via a plaque assay using the Vero E6 cell line, and viral gene copy levels were quantified with the US CDC's N1 and N2 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assays. The infectious virus decayed significantly faster (p ≤ 0.0214) compared to viral RNA, which persisted for the duration of the study irrespective of the incubation conditions. The initial loss (within 15 min of seeding) as well as decay of infectious SARS-CoV-2 was significantly faster (p ≤ 0.0387) in primary treated wastewater compared to other water types, but viral RNA did not degrade appreciably in this matrix until day 15. Overall, temperature was the most important driver of decay, and after 24 h, no infectious SARS-CoV-2 was detected at 37 °C in any water type. Moreover, the CDC N2 gene assay target decayed significantly (p ≤ 0.0174) faster at elevated temperatures compared to CDC N1, which has important implications for RT-qPCR assay selection for WBE approach.

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.

Harnessing non-standard nucleic acids for highly sensitive icosaplex (20-plex) detection of microbial threats

Environmental surveillance and clinical diagnostics heavily rely on the polymerase chain reaction (PCR) for target detection. A growing list of microbial threats warrants new PCR-based detection methods that are highly sensitive, specific, and multiplexable. Here, we introduce a PCR-based icosaplex (20-plex) assay for detecting 18 enteropathogen and two antimicrobial resistance genes. This multiplexed PCR assay leverages the self-avoiding molecular recognition system (SAMRS) to avoid primer dimer formation, the artificially expanded genetic information system (AEGIS) for amplification specificity, and next-generation sequencing for amplicon identification. We benchmarked this assay using a low-cost, portable sequencing platform (Oxford Nanopore) on wastewater, soil, and human stool samples. Using parallelized multi-target TaqMan Array Cards (TAC) to benchmark performance of the 20-plex assay, there was 74% agreement on positive calls and 97% agreement on negative calls. Additionally, we show how sequencing information from the 20-plex can be used to further classify allelic variants of genes and distinguish sub-species. The strategy presented offers sensitive, affordable, and robust multiplex detection that can be used to support efforts in wastewater-based epidemiology, environmental monitoring, and human/animal diagnostics.

Nucleic Acid Based Testing (NABing): A Game Changer Technology for Public Health

Timely and accurate detection of the causal agent of a disease is crucial to restrict suffering and save lives. Mere symptoms are often not enough to detect the root cause of the disease. Better diagnostics applied for screening at a population level and sensitive detection assays remain the crucial component of disease surveillance which may include clinical, plant, and environmental samples, including wastewater. The recent advances in genome sequencing, nucleic acid amplification, and detection methods have revolutionized nucleic acid-based testing (NABing) and screening assays. A typical NABing assay consists of three modules: isolation of the nucleic acid from the collected sample, identification of the target sequence, and final reading the target with the help of a signal, which may be in the form of color, fluorescence, etc. Here, we review current NABing assays covering the different aspects of all three modules. We also describe the frequently used target amplification or signal amplification procedures along with the variety of applications of this fast-evolving technology and challenges in implementation of NABing in the context of disease management especially in low-resource settings.

Comparison of Different Reverse Transcriptase-Polymerase Chain Reaction-Based Methods for Wastewater Surveillance of SARS-CoV-2: Exploratory Study

BACKGROUND

Many countries have applied the wastewater surveillance of the COVID-19 pandemic to their national public health monitoring measures. The most used methods for detecting SARS-CoV-2 in wastewater are quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) and reverse transcriptase-droplet digital polymerase chain reaction (RT-ddPCR). Previous comparison studies have produced conflicting results, thus more research on the subject is required.

OBJECTIVE

This study aims to compare RT-qPCR and RT-ddPCR for detecting SARS-CoV-2 in wastewater. It also aimed to investigate the effect of changes in the analytical pipeline, including the RNA extraction kit, RT-PCR kit, and target gene assay, on the results. Another aim was to find a detection method for low-resource settings.

METHODS

We compared 2 RT-qPCR kits, TaqMan RT-qPCR and QuantiTect RT-qPCR, and RT-ddPCR based on sensitivity, positivity rates, variability, and correlation of SARS-CoV-2 gene copy numbers in wastewater to the incidence of COVID-19. Furthermore, we compared 2 RNA extraction methods, column- and magnetic-bead-based. In addition, we assessed 2 target gene assays for RT-qPCR, N1 and N2, and 2 target gene assays for ddPCR N1 and E. Reverse transcription strand invasion-based amplification (RT-SIBA) was used to detect SARS-CoV-2 from wastewater qualitatively.

RESULTS

Our results indicated that the most sensitive method to detect SARS-CoV-2 in wastewater was RT-ddPCR. It had the highest positivity rate (26/30), and its limit of detection was the lowest (0.06 gene copies/µL). However, we obtained the best correlation between COVID-19 incidence and SARS-CoV-2 gene copy number in wastewater using TaqMan RT-qPCR (correlation coefficient [CC]=0.697, P<.001). We found a significant difference in sensitivity between the TaqMan RT-qPCR kit and the QuantiTect RT-qPCR kit, the first having a significantly lower limit of detection and a higher positivity rate than the latter. Furthermore, the N1 target gene assay was the most sensitive for both RT-qPCR kits, while no significant difference was found between the gene targets using RT-ddPCR. In addition, the use of different RNA extraction kits affected the result when the TaqMan RT-qPCR kit was used. RT-SIBA was able to detect SARS-CoV-2 RNA in wastewater.

CONCLUSIONS

As our study, as well as most of the previous studies, has shown RT-ddPCR to be more sensitive than RT-qPCR, its use in the wastewater surveillance of SARS-CoV-2 should be considered, especially if the amount of SARS-CoV-2 circulating in the population was low. All the analysis steps must be optimized for wastewater surveillance as our study showed that all the analysis steps including the compatibility of the RNA extraction, the RT-PCR kit, and the target gene assay influence the results. In addition, our study showed that RT-SIBA could be used to detect SARS-CoV-2 in wastewater if a qualitative result is sufficient.

The Use of Wastewater Surveillance to Estimate SARS-CoV-2 Fecal Viral Shedding Pattern and Identify Time Periods with Intensified Transmission

Background

Wastewater-based surveillance is an important tool for monitoring the COVID-19 pandemic. However, it remains challenging to translate wastewater SARS-CoV-2 viral load to infection number, due to unclear shedding patterns in wastewater and potential differences between variants.

Objectives

We utilized comprehensive wastewater surveillance data and estimates of infection prevalence (i.e., the source of the viral shedding) available for New York City (NYC) to characterize SARS-CoV-2 fecal shedding pattern over multiple COVID-19 waves.

Methods

We collected SARS-CoV-2 viral wastewater measurements in NYC during August 31, 2020 - August 29, 2023 ( N = 3794 samples). Combining with estimates of infection prevalence (number of infectious individuals including those not detected as cases), we estimated the time-lag, duration, and per-infection fecal shedding rate for the ancestral/Iota, Delta, and Omicron variants, separately. We also developed a procedure to identify occasions with intensified transmission.

Results

Models suggested fecal viral shedding likely starts around the same time as and lasts slightly longer than respiratory tract shedding. Estimated fecal viral shedding rate was highest during the ancestral/Iota variant wave, at 1.44 (95% CI: 1.35 - 1.53) billion RNA copies in wastewater per day per infection (measured by RT-qPCR), and decreased by ∼20% and 50-60% during the Delta wave and Omicron period, respectively. We identified around 200 occasions during which the wastewater SARS-CoV-2 viral load exceeded the expected level in any of 14 sewersheds. These anomalies disproportionally occurred during late January, late April - early May, early August, and from late-November to late-December, with frequencies exceeding the expectation assuming random occurrence ( P < 0.05; bootstrapping test).

Discussion

These estimates may be useful in understanding changes in underlying infection rate and help quantify changes in COVID-19 transmission and severity over time. We have also demonstrated that wastewater surveillance data can support the identification of time periods with potentially intensified transmission.

Applying improved ddPCR to reliable quantification of MPXV in clinical settings

Monkeypox virus (MPXV) poses a global health threat. Droplet digital PCR (ddPCR) holds potential as an accurate diagnostic tool for clinical microbiology. However, there is limited literature on the applicability of ddPCR in clinical settings. In this study, the clinical features of patients with MPXV during the initial outbreak in China in June 2023 were reviewed, and an optimized ddPCR method with dilution and/or inhibitor removal was developed to enhance MPXV detection efficiency. Eighty-two MPXV samples were tested from nine different clinical specimen types, including feces, urine, pharyngeal swabs, anal swabs, saliva, herpes fluid, crust, and semen, and the viral load of each specimen was quantified. A comparative analysis was performed with qPCR to assess sensitivity and specificity and to investigate the characteristics of MPXV infection by analyzing viral loads in different clinical specimens. Consequently, common pharyngeal and gastrointestinal symptoms were observed in patients with MPXV. The optimized ddPCR method demonstrated relatively high sensitivity for MPXV quantification in the clinical materials, with a limit of detection of 0.1 copies/μL. This was particularly evident in low-concentration samples like whole blood, semen, and urine. The optimized ddPCR demonstrated greater detection accuracy compared with normal ddPCR and qPCR, with an area under the curve (AUC) of 0.939. Except for crust samples, viral loads in the specimens gradually decreased as the disease progressed. Virus levels in feces and anal swabs kept a high detection rate at each stage of post-symptom onset, and feces and anal swabs samples may be suitable for clinical diagnosis and continuous monitoring of MPXV.

IMPORTANCE

The ddPCR technique proved to be a sensitive and valuable tool for accurately quantifying MPXV viral loads in various clinical specimen types. The findings provided valuable insights into the necessary pre-treatment protocols for MPXV diagnosis in ddPCR detection and the potentially suitable sample types for collection. Therefore, such results can aid in comprehending the potential characteristics of MPXV infection and the usage of ddPCR in clinical settings.

Monitoring SARS-CoV-2 RNA in wastewater from a shared septic system and sub-sewershed sites to expand COVID-19 disease surveillance

Wastewater-based epidemiology has expanded as a tool for collecting COVID-19 surveillance data, but there is limited information on the feasibility of this form of surveillance within decentralized wastewater systems (e.g., septic systems). This study assessed SARS-CoV-2 RNA concentrations in wastewater samples from a septic system servicing a mobile home park (66 households) and from two pumping stations serving a similarly sized (71 households) and a larger (1,000 households) neighborhood within a nearby sewershed over 35 weeks in 2020. Also, raw wastewater from a hospital in the same sewershed was sampled. The mobile home park samples had the highest detection frequency (39/39 days) and mean concentration of SARS-CoV-2 RNA (2.7 × 107 gene copies/person/day for the N1) among the four sampling sites. N1 gene and N2 gene copies were highly correlated across mobile home park samples (Pearson's r = 0.93, p < 0.0001). In the larger neighborhood, new COVID-19 cases were reported every week during the sampling period; however, we detected SARS-CoV-2 RNA in 12% of the corresponding wastewater samples. The results of this study suggest that sampling from decentralized wastewater infrastructure can be used for continuous monitoring of SARS-CoV-2 infections.

Assessment of nucleic acid extraction protocols for antibiotic resistance genes (ARGs) quantification in aircraft wastewater

This study evaluated ten nucleic acid extraction protocols (EP1 to EP10) for measuring five endogenous antibiotic resistance genes (ARGs) in four aircraft wastewater samples (AWW1 to AWW4). The targeted ARGs, including blaCTX-M, blaNDM-1, ermB, qnrS, and tetA, encompassed highly and minimally abundant ARGs. TetA and ermB were consistently detected across four aircraft wastewater samples using the DNeasy Blood and Tissue Kit and the AllPrep PowerViral DNA/RNA kit. QnrS displayed high detection rates with specific extraction protocols and aliquot volumes. Concentrations of ARGs varied across aircraft wastewater samples, with differing extraction protocols influencing quantitative results. The concentrations of tetA, ermB, and qnrS in AWW1 were distinct, while AWW2 to AWW4 exhibited a broader range for tetA, ermB, qnrS, blaCTX-M, and blaNDM-1. EP1 consistently produced the highest concentrations for several ARGs. Collective data analysis revealed varying ARG concentrations across the ten extraction protocols, suggesting the importance of careful extraction protocol selection in ARG monitoring in aircraft wastewater samples. Based on the results, we suggest that a small sample volume (as low as 0.2 mL) may be sufficient for ARG characterization in aircraft wastewater samples. The findings also emphasize the need for considering toilet paper removal without compromising nucleic acid extraction efficiency. The study highlights promising prospects for aircraft wastewater monitoring of ARGs, calling for further investigation into the import and spread of unique ARGs through transport hubs.

Simultaneous detection of influenza A, B and respiratory syncytial virus in wastewater samples by one-step multiplex RT-ddPCR assay

BACKGROUND

After the occurrence of the COVID-19 pandemic, detection of other disseminated respiratory viruses using highly sensitive molecular methods was declared essential for monitoring the spread of health-threatening viruses in communities. The development of multiplex molecular assays are essential for the simultaneous detection of such viruses even at low concentrations. In the present study, a highly sensitive and specific multiplex one-step droplet digital PCR (RT-ddPCR) assay was developed for the simultaneous detection and absolute quantification of influenza A (IAV), influenza B (IBV), respiratory syncytial virus (RSV), and beta-2-microglobulin transcript as an endogenous internal control (IC B2M).

RESULTS

The assay was first evaluated for analytical sensitivity and specificity, linearity, reproducibility, and recovery rates with excellent performance characteristics and then applied to 37 wastewater samples previously evaluated with commercially available and in-house quantitative real-time reverse transcription PCR (RT-qPCR) assays. IAV was detected in 16/37 (43%), IBV in 19/37 (51%), and RSV in 10/37 (27%) of the wastewater samples. Direct comparison of the developed assay with real-time RT-qPCR assays showed statistically significant high agreement in the detection of IAV (kappa Cohen's correlation coefficient: 0.834, p = 0.001) and RSV (kappa: 0.773, p = 0.001) viruses between the two assays, while the results for the detection of IBV (kappa: 0.355, p = 0.27) showed good agreement without statistical significance.

CONCLUSIONS

Overall, the developed one-step multiplex ddPCR assay is cost-effective, highly sensitive and specific, and can simultaneously detect three common respiratory viruses in the complex matrix of wastewater samples even at low concentrations. Due to its high sensitivity and resistance to PCR inhibitors, the developed assay could be further used as an early warning system for wastewater monitoring.

A scoping review of global SARS-CoV-2 wastewater-based epidemiology in light of COVID-19 pandemic

Recently, wastewater-based epidemiology (WBE) research has experienced a strong impetus during the Coronavirus disease 2019 (COVID-19) pandemic. However, a few technical issues related to surveillance strategies, such as standardized procedures ranging from sampling to testing protocols, need to be resolved in preparation for future infectious disease outbreaks. This review highlights the study characteristics, potential use of WBE and overview of methods, as well as methods utilized to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) including its variant in wastewater. A literature search was performed electronically in PubMed and Scopus according to PRISMA guidelines for relevant peer-reviewed articles published between January 2020 and March 2022. The search identified 588 articles, out of which 221 fulfilled the necessary criteria and are discussed in this review. Most global WBE studies were conducted in North America (n = 75, 34 %), followed by Europe (n = 68, 30.8 %), and Asia (n = 43, 19.5 %). The review also showed that most of the application of WBE observed were to correlate SARS-CoV-2 ribonucleic acid (RNA) trends in sewage with epidemiological data (n = 90, 40.7 %). The techniques that were often used globally for sample collection, concentration, preferred matrix recovery control and various sample types were also discussed. Overall, this review provided a framework for researchers specializing in WBE to apply strategic approaches to their research questions in achieving better functional insights. In addition, areas that needed more in-depth analysis, data collection, and ideas for new initiatives were identified.

Fate-and-transport modeling of SARS-CoV-2 for rural wastewater-based epidemiology application benefit

Wastewater-based epidemiology (WBE) for the detection of agents of concern such as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been prevalent in literature since 2020. The majority of reported research focuses on large urban centers with few references to rural communities. In this research the EPA-Storm Water Management Model (EPA-SWMM) software was used to describe a small sewershed and identify the effects of temperature, temperature-affected decay rate, flow rate, flush time, fecal shedding rate, and historical infection rates during the spread of the Omicron variant of the SARS-CoV-2 virus within the sewershed. Due to the sewershed's relative isolation from the rest of the city, its wastewater quality behavior is similar to a rural sewershed. The model was used to assess city wastewater sampling campaigns to best appropriate field and or lab equipment when sampling wastewater. An important aspect of the assessment was the comparison of SARS-CoV-2 quantification methods with specifically between a traditional microbiological lab (practical quantitation limit, PQL, 1 GC/mL) versus what can be known from a field method (PQL 10 GC/mL). Understanding these monitoring choices will help rural communities make decisions on how to best implement the collection and testing for WBE agents of concern. An important outcome of this work is the knowledge that it is possible to simulate a WBE agent of concern with reasonable precision, if uncertainties are incorporated into model sensitivity. These ideas could form the basis for future mixed monitoring-modeling studies that will enhance its application and therefore adoption of WBE techniques in communities of many sizes and financial means.

Establishment and evaluation of detection methods for process-specific residual host cell protein and residual host cell DNA in biological preparation

To establish accurate detection methods of process-specific Escherichia coli residual host cell protein (HCP) and residual host cell DNA (rcDNA) in recombinant biological preparations. Taking the purification process of GLP expressed by E. coli as a specific-process model, the HCP of empty E. coli was intercepted to immunize mice and rabbits. Using IgG from immunized rabbits as the coating antibody and mouse immune serum as the second sandwich antibody, a process-specific enzyme-linked immunosorbent assay (ELISA) for E. coli HCP was established. Targeting the 16S gene of E. coli, ddPCR was used to obtain the absolute copies of rcDNA in samples. Non-process-specific commercial ELISA kit and the process-specific ELISA established in this study were used to detect the HCP in GLP preparation. About 62% of HCPs, which should be process-specific HCPs, could not be detected by the non-process-specific commercial ELISA kit. The sensitivity of established ELISA can reach 338 pg/mL. The rcDNA could be absolutely quantitated by ddPCR, for the copies of rcDNA in three multiple diluted samples showed a reduced gradient. While the copies of rcDNA in three multiple diluted samples could not be distinguished by the qPCR. Process-specific ELISA has high sensitivity in detecting process-specific E. coli HCP. The absolutely quantitative ddPCR has much higher accuracy than the relatively quantitative qPCR, it is a nucleic acid quantitative method that is expected to replace qPCR in the future.

Optimization of the 5-plex digital PCR workflow for simultaneous monitoring of SARS-CoV-2 and other pathogenic viruses in wastewater

Wastewater-based epidemiology is a valuable tool for monitoring pathogenic viruses in the environment, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). While quantitative polymerase chain reaction (qPCR) is widely used for pathogen surveillance in wastewater, it can be affected by inhibition and is limited to relative quantification. Digital PCR (dPCR) offers potential solutions to these limitations. In this study, a 5-plex dPCR workflow was optimized for the simultaneous detection of SARS-CoV-2, influenza A virus, enteroviruses (EnV), and noroviruses of genogroups I (NoV-GI) and GII (NoV-GII) in wastewater samples. Wastewater samples (n = 36) were collected from a wastewater treatment plant in Japan between August and October 2022. The optimization included the evaluation of singleplex and 5-plex dPCR assays, and two different concentration methods, extraction kits, and dPCR approaches. The performance of singleplex and 5-plex dPCR assays showed comparable linearity and reliability, with the 5-plex assays showing greater efficiency. The polyethylene glycol (PEG) precipitation method showed better performance over the centrifugation method, two-step reverse transcription (RT)-dPCR over the one-step RT-dPCR, and AllPrep PowerViral DNA/RNA Kit showed better performance than the QIAamp Viral RNA Mini Kit. The optimal workflow therefore included PEG precipitation, the AllPrep PowerViral DNA/RNA Kit, and two-step RT-dPCR. This workflow was selected to monitor the presence of SARS-CoV-2 and other pathogenic viruses in wastewater samples in a 5-plex dPCR approach, yielding promising results. SARS-CoV-2 RNA was detected in the majority of samples, with NoV-GI, NoV-GII, and EnV also being detected. The successful optimization and application of the 5-plex dPCR assay for pathogen surveillance in wastewater offers significant benefits, including enhanced community health assessment and more effective responses to public health threats.

Real-time evaluation of signal accuracy in wastewater surveillance of pathogens with high rates of mutation

Wastewater surveillance of coronavirus disease 2019 (COVID-19) commonly applies reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater over time. In most applications worldwide, maximal sensitivity and specificity of RT-qPCR has been achieved, in part, by monitoring two or more genomic loci of SARS-CoV-2. In Ontario, Canada, the provincial Wastewater Surveillance Initiative reports the average copies of the CDC N1 and N2 loci normalized to the fecal biomarker pepper mild mottle virus. In November 2021, the emergence of the Omicron variant of concern, harboring a C28311T mutation within the CDC N1 probe region, challenged the accuracy of the consensus between the RT-qPCR measurements of the N1 and N2 loci of SARS-CoV-2. In this study, we developed and applied a novel real-time dual loci quality assurance and control framework based on the relative difference between the loci measurements to the City of Ottawa dataset to identify a loss of sensitivity of the N1 assay in the period from July 10, 2022 to January 31, 2023. Further analysis via sequencing and allele-specific RT-qPCR revealed a high proportion of mutations C28312T and A28330G during the study period, both in the City of Ottawa and across the province. It is hypothesized that nucleotide mutations in the probe region, especially A28330G, led to inefficient annealing, resulting in reduction in sensitivity and accuracy of the N1 assay. This study highlights the importance of implementing quality assurance and control criteria to continually evaluate, in near real-time, the accuracy of the signal produced in wastewater surveillance applications that rely on detection of pathogens whose genomes undergo high rates of mutation.

Applications of Digital Polymerase Chain Reaction (dPCR) in Molecular and Clinical Testing

BACKGROUND

Digital polymerase chain reaction (dPCR) is an accurate and sensitive molecular method that can be used in clinical diagnostic, prognostic, and predictive tests. The key component of the dPCR method is the partitioning of a single reaction into many thousands of droplets, nanochannels or other nano- or picoliter-sized reactions. This results in high enough sensitivity to detect rare nucleic acid targets and provides an absolute quantification of target sequences or alleles compared to other PCR-based methods.

CONTENT

An increasing number of dPCR platforms have been introduced commercially in recent years and more are being developed. These platforms differ in the method of partitioning, degree of automation, and multiplexing capabilities but all can be used in similar ways for sensitive and highly accurate quantification of a variety of nucleic acid targets. Currently, clinical applications of dPCR include oncology, microbiology and infectious disease, genetics, and prenatal/newborn screening. Commercially available tests for clinical applications are being developed for variants with diagnostic, prognostic, and therapeutic significance in specific disease types.

SUMMARY

The power of dPCR technology relies on the partitioning of the reactions and results in increased sensitivity and accuracy compared to qPCR. More recently, the sensitivity of dPCR has been applied to the detection of known variants in cell-free DNA and circulating tumor DNA. Future clinical applications of dPCR include liquid biopsy, treatment resistance detection, screening for minimal residual disease, and monitoring allograft engraftment in transplanted patients.

Comparison of RT-ddPCR and RT-qPCR platforms for SARS-CoV-2 detection: Implications for future outbreaks of infectious diseases

The increased frequency of human infectious disease outbreaks caused by RNA viruses worldwide in recent years calls for enhanced public health surveillance for better future preparedness. Wastewater-based epidemiology (WBE) is emerging as a valuable epidemiological tool for providing timely population-wide surveillance for disease prevention and response complementary to the current clinical surveillance system. Here, we compared the analytical performance and practical applications between predominant molecular detection methods of RT-qPCR and RT-ddPCR on SARS-CoV-2 detection in wastewater surveillance. When pure viral RNA was tested, RT-ddPCR exhibited superior quantification accuracy at higher concentration levels and achieved more sensitive detection with reduced variation at low concentration levels. Furthermore, RT-ddPCR consistently demonstrated more robust and accurate measurement either in the background of the wastewater matrix or with the presence of mismatches in the target regions of the consensus assay. Additionally, by detecting mock variant RNA samples, we found that RT-ddPCR outperformed RT-qPCR in virus genotyping by targeting specific loci with signature mutations in allele-specific (AS) assays, especially at low levels of allele frequencies and concentrations, which increased the possibility for sensitive low-prevalence variant detection in the population. Our study provides insights for detection method selection in the WBE applications for future infectious disease outbreaks.

Evaluating the sensitivity of droplet digital PCR for the quantification of SARS-CoV-2 in wastewater

Wastewater surveillance for SARS-CoV-2 has been demonstrated to be a valuable tool in monitoring community-level virus circulation and assessing new outbreaks. It may become a useful tool in the early detection and response to future pandemics, enabling public health authorities to implement timely interventions and mitigate the spread of infectious diseases with the fecal excretion of their agents. It also offers a chance for cost-effective surveillance. Reverse transcription-quantitative polymerase chain reaction (RTqPCR) is the most commonly used method for viral RNA detection in wastewater due to its sensitivity, reliability, and widespread availability. However, recent studies have indicated that reverse transcription droplet digital PCR (RTddPCR) has the potential to offer improved sensitivity and accuracy for quantifying SARS-CoV-2 RNA in wastewater samples. In this study, we compared the performance of RTqPCR and RTddPCR approaches for SARS-CoV-2 detection and quantification on wastewater samples collected during the third epidemic wave in Saxony, Germany, characterized by low-incidence infection periods. The determined limits of detection (LOD) and quantification (LOQ) were within the same order of magnitude, and no significant differences were observed between the PCR approaches with respect to the number of positive or quantifiable samples. Our results indicate that both RTqPCR and RTddPCR are highly sensitive methods for detecting SARS-CoV-2. Consequently, the actual gain in sensitivity associated with ddPCR lags behind theoretical expectations. Hence, the choice between the two PCR methods in further environmental surveillance programs is rather a matter of available resources and throughput requirements.

Early warning of statewide COVID-19 Omicron wave by sentineled urbanized sewer network monitoring using digital PCR in a province capital city, of Gujarat, India

Wastewater-based epidemiology (WBE) has been implemented globally. However, there remains confusion about the number and frequency of samples to be collected, as well as which types of treatment systems can provide reliable specific details about the virus prevalence in specific areas or communities, enabling prompt management and intervention measures. More research is necessary to fully comprehend the possibility of deploying sentinel locations in sewer networks in larger geographic areas. The present study introduces the first report on wastewater-based surveillance in Gandhinagar City using digital PCR (d-PCR) as a SARS-Cov-2 quantification tool, which describes the viral load from five pumping stations in Gandhinagar from October 2021 to March 2022. Raw wastewater samples (n = 119) were received and analyzed weekly to detect SARS-CoV-2 RNA, 109 of which were positive for N1 or N2 genes. The monthly variation analysis in viral genome copies depicted the highest concentrations in January 2022 and February 2022 (p < 0.05; Wilcoxon signed rank test) coincided with the Omicron wave, which contributed mainly from Vavol and Jaspur pumping stations. Cross-correlation analysis indicated that WBE from five stations in Gandhinagar, i.e., capital city sewer networks, provided two-week lead times to the citywide and statewide active cases (time-series cross-correlation function [CCF]; 0.666 and 0.648, respectively), mainly from individual contributions of the urbanized Kudasan and Vavol stations (CCF; 0.729 and 0.647, respectively). These findings suggest that sewer pumping stations in urbanized neighborhoods can be used as sentinel sites for statewide clinical surveillance and that WBE surveillance using digital PCR can be an efficient monitoring and management tool.

Circulation of SARS-CoV-2 Omicron sub-lineages revealed by multiplex genotyping RT-qPCR assays for sewage surveillance

Sewage surveillance has proven to be an essential complementary tool to clinical diagnosis in combating the COVID-19 pandemic by tracking the spread of the SARS-CoV-2 virus and evaluating infection levels in populations. With the striking spreading and continuous evolution of SARS-CoV-2 Omicron VOC that characterized with higher transmissibility and potential immune evasion, there is an urgent need for the rapid surveillance of this prevalent strain and its sub-lineages in sewage. In this study, based on three multiplex allele-specific (AS) RT-qPCR assays, we established a rapid and high-throughput detection workflow for the simultaneous discrimination of Omicron sub-lineages BA.2.2, BA.2.12.1, BA.4 and BA.5 (hereafter referred to as BA.4/BA.5) to track their community circulation in Hong Kong. All primer-probe sets in the multiplex assays could correctly discriminate and quantitate their target genotypes with high sensitivity and specificity, even when multiple variants co-existed in the sewage samples. Using the established multiplex assays, the trends of SARS-CoV-2 total viral load and variant dynamics in influent samples collected from 11 wastewater treatment plants (WWTPs) during June 2022 and September 2022, aligned with the clinical data, successfully unveiling the swift emergence and predominance of Omicron BA.4/BA.5 in Hong Kong. The study highlights the feasibility and applicability of multiplex RT-qPCR assays for monitoring epidemic trends and tracking variant displacement dynamics in sewage samples, providing a more rapid, high-throughput and cost-effective alternative to enhance the current sewage surveillance system.

Refining detection methods for emerging SARS-CoV-2 mutants in wastewater: A case study on the Omicron variants

COVID-19 is an ongoing public health threat worldwide driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Wastewater surveillance has emerged as a complementary tool to clinical surveillance to control the COVID-19 pandemic. With the emergence of new variants of SARS-CoV-2, accumulated mutations that occurred in the SARS-CoV-2 genome raise new challenges for RT-qPCR diagnosis used in wastewater surveillance. There is a pressing need to develop refined methods for modifying primer/probes to better detect these emerging variants in wastewater. Here, we exemplified this process by focusing on the Omicron variants, for which we have developed and validated a modified detection method. We first modified the primers/probe mismatches of three assays commonly used in wastewater surveillance according to in silico analysis results for the mutations of 882 sequences collected during the fifth-wave outbreak in Hong Kong, and then evaluated them alongside the seven original assays. The results showed that five of seven original assays had better sensitivity for detecting Omicron variants, with the limits of detection (LoDs) ranging from 1.53 to 2.76 copies/μL. UCDC-N1 and Charité-E sets had poor performances, having LoDs higher than 10 copies/μL and false-positive/false-negative results in wastewater testing, probably due to the mismatch and demonstrating the need for modification of primer/probe sequences. The modified assays exhibited higher sensitivity and specificity, along with better reproducibility in detecting 81 wastewater samples. In addition, the sequencing results of six wastewater samples by Illumina also validated the presence of mismatches in the primer/probe binding sites of the three assays. This study highlights the importance of re-configuration of the primer-probe sets and refinements for the sequences to ensure the diagnostic effectiveness of RT-qPCR detection.

Droplet digital PCR application for the detection of SARS-CoV-2 in air sample

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) may transmit through airborne route particularly when the aerosol particles remain in enclosed spaces with inadequate ventilation. There has been no standard recommended method of determining the virus in air due to limitations in pre-analytical and technical aspects. Furthermore, the presence of low virus loads in air samples could result in false negatives. Our study aims to explore the feasibility of detecting SARS-CoV-2 ribonucleic acid (RNA) in air samples using droplet digital polymerase chain reaction (ddPCR). Active and passive air sampling was conducted between December 2021 and February 2022 with the presence of COVID-19 confirmed cases in two hospitals and a quarantine center in Klang Valley, Malaysia. SARS-CoV-2 RNA in air was detected and quantified using ddPCR and real-time reverse transcriptase-polymerase chain reaction (RT-PCR). The comparability of two different digital PCR platforms (QX200 and QIAcuity) to RT-PCR were also investigated. Additionally negative staining transmission electron microscopy was performed to visualize virus ultrastructure. Detection rates of SARS-CoV-2 in air samples using ddPCR were higher compared to RT-PCR, which were 15.2% (22/145) and 3.4% (5/145), respectively. The sensitivity and specificity of ddPCR was 100 and 87%, respectively. After excluding 17 negative samples (50%) by both QX200 and QIAcuity, 15% samples (5/34) were found to be positive both ddPCR and dPCR. There were 23.5% (8/34) samples that were detected positive by ddPCR but negative by dPCR. In contrast, there were 11.7% (4/34) samples that were detected positive by dPCR but negative by ddPCR. The SARS-CoV-2 detection method by ddPCR is precise and has a high sensitivity for viral RNA detection. It could provide advances in determining low viral titter in air samples to reduce false negative reports, which could complement detection by RT-PCR.

A Novel and Quantitative Detection Assay (effluxR) for Identifying Efflux-Associated Resistance Genes Using Multiplex Digital PCR in Clinical Isolates of Pseudomonas aeruginosa

The rise of multidrug resistance of Pseudomonas aeruginosa highlights an increased need for selective and precise antimicrobial treatment. Drug efflux pumps are one of the major mechanisms of antimicrobial resistance found in many bacteria, including P. aeruginosa. Detection of efflux genes using a polymerase chain reaction (PCR)-based system would enable resistance detection and aid clinical decision making. Therefore, we aimed to develop and optimize a novel method herein referred to as "effluxR detection assay" using multiplex digital PCR (mdPCR) for detection of mex efflux pump genes in P. aeruginosa strains. The annealing/extension temperatures and gDNA concentrations were optimized to amplify mexB, mexD, and mexY using the multiplex quantitative PCR (mqPCR) system. We established the optimal mqPCR conditions for the assay (Ta of 59 °C with gDNA concentrations at or above 0.5 ng/µL). Using these conditions, we were able to successfully detect the presence of these genes in a quantity-dependent manner. The limit of detection for mex genes using the effluxR detection assay with mdPCR was 0.001 ng/µL (7.04-34.81 copies/µL). Moreover, using blind sample testing, we show that effluxR detection assay had 100% sensitivity and specificity for detecting mex genes in P. aeruginosa. In conclusion, the effluxR detection assay, using mdPCR, is able to identify the presence of multiple mex genes in P. aeruginosa that may aid clinical laboratory decisions and further epidemiological studies.

Suspended Materials Affect Particle Size Distribution and Removal of Environmental DNA in Flowing Waters

Environmental DNA (eDNA) in aquatic systems is a complex mixture that includes dissolved DNA, intracellular DNA, and particle-adsorbed DNA. Information about the various components of eDNA and their relative proportions could be used to discern target organism abundance and location. However, a limited knowledge of eDNA adsorption dynamics and interactions with other materials hinders these applications. To address this gap, we used recirculating stream mesocosms to investigate the impact of suspended materials (fine particulate organic matter, plankton, clay, and titanium dioxide) on the eDNA concentration and particle size distribution (PSD) from two fish species in flowing water. Our findings revealed that eDNA rapidly adsorbs to other materials in the water column, affecting its concentration and PSD. Nonetheless, only particulate organic matter affected eDNA removal rate after 30 h. Moreover, we observed that the removal of larger eDNA components (≥10 μm) was more strongly influenced by physical processes, whereas the removal of smaller eDNA components was driven by biological degradation. This disparity in removal mechanisms between larger and smaller eDNA components could explain changes in eDNA composition over time and space, which have implications for modeling the spatial distribution and abundance of target species and optimizing eDNA detection in high turbidity systems.

Zika virus RNA persistence and recovery in water and wastewater: An approach for Zika virus surveillance in resource-constrained settings

During the 2015-2016 Zika virus (ZIKV) epidemic in the Americas, serological cross-reactivity with other flaviviruses and relatively high costs of nucleic acid testing in the region hindered the capacity for widespread diagnostic testing. In such cases where individual testing is not feasible, wastewater monitoring approaches may offer a means of community-level public health surveillance. To inform such approaches, we characterized the persistence and recovery of ZIKV RNA in experiments where we spiked cultured ZIKV into surface water, wastewater, and a combination of both to examine the potential for detection in open sewers serving communities most affected by the ZIKV outbreak, such as those in Salvador, Bahia, Brazil. We used reverse transcription droplet digital PCR to quantify ZIKV RNA. In our persistence experiments, we found that the persistence of ZIKV RNA decreased with increasing temperature, significantly decreased in surface water versus wastewater, and significantly decreased when the initial concentration of virus was lowered by one order of magnitude. In our recovery experiments, we found higher percent recovery of ZIKV RNA in pellets versus supernatants from the same sample, higher recoveries in pellets using skimmed milk flocculation, lower recoveries of ZIKV RNA in surface water versus wastewater, and lower recoveries from a freeze thaw. We also analyzed samples collected from Salvador, Brazil during the ZIKV outbreak (2015-2016) that consisted of archived samples obtained from open sewers or environmental waters thought to be contaminated by sewage. Although we did not detect any ZIKV RNA in the archived Brazil samples, results from these persistence and recovery experiments serve to inform future wastewater monitoring efforts in open sewers, an understudied and important application of wastewater monitoring.

Improvement of Sensitivity and Speed of Virus Sensing Technologies Using nm- and μm-Scale Components

Various viral diseases can be widespread and cause severe disruption to global society. Highly sensitive virus detection methods are needed to take effective measures to prevent the spread of viral infection. This required the development of rapid virus detection technology to detect viruses at low concentrations, even in the biological fluid of patients in the early stages of the disease or environmental samples. This review describes an overview of various virus detection technologies and then refers to typical technologies such as beads-based assay, digital assay, and pore-based sensing, which are the three modern approaches to improve the performance of viral sensing in terms of speed and sensitivity.

Evaluation of droplet digital qRT-PCR (dd qRT-PCR) for quantification of SARS CoV-2 RNA in stool and urine specimens of COVID-19 patients

Introduction

There have been a few reports of viral load detection in stool and urine samples of patients with coronavirus disease 2019 (COVID-19), and the transmission of the virus through faecal oral route. For clinical diagnosis and treatment, the widely used reverse transcription-polymerase chain reaction (qRT-PCR) method has some limitations.

Methods

The aim of our study to assess the presence and concentration of SARS CoV-2 RNA in stool and urine samples from COVID-19 patients with mild, moderate, and severe disease, we compared a traditional qRT-PCR approach with a ddPCR. ddPCR and qRT-PCR-based target gene analysis were performed on 107 COVID-19-confirmed patients paired samples (N1 and N2). The MagMax magnetic beads base method was used to isolate RNA. Real-time qRT-PCR and dd PCR were performed on all patients.

Results and Discussion

The average cycle threshold (Ct) of qRT-PCR was highly correlated with the average copy number of 327.10 copies/l analyzed in ddPCR. In ddPCR, urine samples showed 27.1% positivity while for stool it was 100%.

Conclusion

This study's findings not only show that SARS CoV-2 is present in urine and faeces, but also suggest that low concentrations of the viral target ddPCR make it easier to identify positive samples and help resolve for cases of inconclusive diagnosis.

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

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

Establishment of wastewater-based SARS-CoV-2 monitoring system over two years: Case studies in South Korea

With the global COVID-19 pandemic, wastewater surveillance has received a considerable attention as a method for the early identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater treatment plant (WWTP) and sewer systems. For the first time in Korea, this study utilized the wastewater surveillance technique to monitor the COVID-19 outbreak. Sampling efforts were carried out at the WWTPs in the capital city of Korea, Seoul, and Daegu the place where the first severe outbreak was reported. The RNA of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been extracted from the collected wastewater influent and primary sewage sludge samples. The outcomes were contrasted with the COVID-19 cases in the WWTPs served area. Additionally, whole transcriptome sequencing was used to compare the microbial community alterations before and after the COVID-19 outbreak and SARS-CoV-2 variations. The results demonstrated that the changes in SARS-CoV-2 RNA concentrations in the influent and sludge matched the trends of reported COVID-19 cases, especially sludge showed high-resolution data, which is well-matched when fewer COVID-19 cases (0-250) are reported. Interestingly, one month before the clinical report, we found that the SARS-CoV-2 Beta variant (South Africa, B.1.351) in the wastewater. In addition, the Aeromonas bacterial species was dominated (21.2%) among other bacterial species in wastewater after the COVID-19 outbreak, suggesting a potential indirect microbial indicator of the COVID-19 outbreak.

SARS-CoV-2 surveillance in medical and industrial wastewater-a global perspective: a narrative review

The novel coronavirus SARS-CoV-2 has spread at an unprecedented rate since late 2019, leading to the global COVID-19 pandemic. During the pandemic, being able to detect SARS-CoV-2 in human populations with high coverage quickly is a huge challenge. As SARS-CoV-2 is excreted in human excreta and thus exposed to the aqueous environment through sewers, the goal is to develop an ideal, non-invasive, cost-effective epidemiological method for detecting SARS-CoV-2. Wastewater surveillance has gained widespread interest and is increasingly being investigated as an effective early warning tool for monitoring the spread and evolution of the virus. This review emphasizes important findings on SARS-CoV-2 wastewater-based epidemiology (WBE) in different continents and techniques used to detect SARS-CoV-2 in wastewater during the period 2020-2022. The results show that WBE is a valuable population-level method for monitoring SARS-CoV-2 and is a valuable early warning alert. It can assist policymakers in formulating relevant policies to avoid the negative impacts of early or delayed action. Such strategy can also help avoid unnecessary wastage of medical resources, rationalize vaccine distribution, assist early detection, and contain large-scale outbreaks.

Robust Performance of SARS-CoV-2 Whole-Genome Sequencing from Wastewater with a Nonselective Virus Concentration Method

The sequencing of human virus genomes from wastewater samples is an efficient method for tracking viral transmission and evolution at the community level. However, this requires the recovery of viral nucleic acids of high quality. We developed a reusable tangential-flow filtration system to concentrate and purify viruses from wastewater for genome sequencing. A pilot study was conducted with 94 wastewater samples from four local sewersheds, from which viral nucleic acids were extracted, and the whole genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was sequenced using the ARTIC V4.0 primers. Our method yielded a high probability (0.9) of recovering complete or near-complete SARS-CoV-2 genomes (>90% coverage at 10× depth) from wastewater when the COVID-19 incidence rate exceeded 33 cases per 100 000 people. The relative abundances of sequenced SARS-CoV-2 variants followed the trends observed from patient-derived samples. We also identified SARS-CoV-2 lineages in wastewater that were underrepresented or not present in the clinical whole-genome sequencing data. The developed tangential-flow filtration system can be easily adopted for the sequencing of other viruses in wastewater, particularly those at low concentrations.

A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19

Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.

Comparison of Reverse Transcription (RT)-Quantitative PCR and RT-Droplet Digital PCR for Detection of Genomic and Subgenomic SARS-CoV-2 RNA

Most individuals acutely infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibit mild symptoms. However, 10 to 20% of those infected develop long-term symptoms, referred to as post-coronavirus disease 2019 (COVID-19) condition (PCC). One hypothesis is that PCC might be exacerbated by viral persistence in tissue sanctuaries. Therefore, the accurate detection and quantification of SARS-CoV-2 are not only necessary for viral load monitoring but also crucial for detecting long-term viral persistence and determining whether viral replication is occurring in tissue reservoirs. In this study, the sensitivity and robustness of reverse transcription (RT)-droplet digital PCR (ddPCR) and RT-quantitative PCR (qPCR) techniques have been compared for the detection and quantification of SARS-CoV-2 genomic and subgenomic RNAs from oropharyngeal swabs taken from confirmed SARS-CoV-2-positive, SARS-CoV-2-exposed, and nonexposed individuals as well as from samples from mice infected with SARS-CoV-2. Our data demonstrated that both techniques presented equivalent results in the mid- and high-viral-load ranges. Additionally, RT-ddPCR was more sensitive than RT-qPCR in the low-viral-load range, allowing the accurate detection of positive results in individuals exposed to the virus. Overall, these data suggest that RT-ddPCR might be an alternative to RT-qPCR for detecting low viral loads in samples and for assessing viral persistence in samples from individuals with PCC. IMPORTANCE We developed one-step reverse transcription (RT)-droplet digital PCR (ddPCR) protocols to detect SARS-CoV-2 RNA and compared them to the gold-standard RT-quantitative PCR (RT-qPCR) method. RT-ddPCR was more sensitive than RT-qPCR in the low-viral-load range, while both techniques were equivalent in the mid- and high-viral-load ranges. Overall, these results suggest that RT-ddPCR might be a viable alternative to RT-qPCR when it comes to detecting low viral loads in samples, which is a highly relevant issue for determining viral persistence in as-yet-unknown tissue reservoirs in individuals suffering from post-COVID conditions or long COVID.

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.