Assessing sensitivity and reproducibility of RT-ddPCR and RT-qPCR for the quantification of SARS-CoV-2 in wastewater

Surveillance of SARS-CoV-2 in wastewater by quantitative PCR and digital PCR: a case study in Shijiazhuang city, Hebei province, China

In this study, we reported the first long-term monitoring of SARS-CoV-2 in wastewater in Mainland China from November 2021 to October 2023. The city of Shijiazhuang was employed for this case study. We developed a triple reverse transcription droplet digital PCR (RT-ddPCR) method using triple primer-probes for simultaneous detection of the N1 gene, E gene, and Pepper mild mottle virus (PMMoV) to achieve accurate quantification of SARS-CoV-2 RNA in wastewater. Both the RT-ddPCR method and the commercial multiplex reverse transcription quantitative polymerase chain reaction (RT-qPCR) method were implemented for the detection of SARS-CoV-2 in wastewater in Shijiazhuang City over a 24-month period. Results showed that SARS-CoV-2 was detected for the first time in the wastewater of Shijiazhuang City on 10 November 2022. The peak of COVID-19 cases occurred in the middle of December 2022, when the concentration of SARS-CoV-2 in the wastewater was highest. The trend of virus concentration increases and decreases forming a "long-tailed" shape in the COVID-19  outbreak and recession cycle. The results indicated that both multiplex RT-ddPCR and RT-qPCR are effective in detecting SARS-CoV-2 in wastewater, but RT-ddPCR is capable of detecting low concentrations of SARS-CoV-2 in wastewater which is more efficient. The SARS-CoV-2 abundance in wastewater is correlated to clinical data, outlining the public health utility of this work.HighlightsFirst long-term monitoring of SARS-CoV-2 in wastewater in Mainland ChinaCOVID-19 outbreak was tracked in Shijiazhuang City from outbreak to containmentWastewater was monitored simultaneously using RT-ddPCR and RT-qPCR methodsTriple primer-probe RT-ddPCR detects N1 and E genes of SARS-CoV-2 and PMMoV.

Comparative analyses of SARS-CoV-2 RNA concentrations in Detroit wastewater quantified with CDC N1, N2, and SC2 assays reveal optimal target for predicting COVID-19 cases

To monitor COVID-19 through wastewater surveillance, global researchers dedicated significant endeavors and resources to develop and implement diverse RT-qPCR or RT-ddPCR assays targeting different genes of SARS-CoV-2. Effective wastewater surveillance hinges on the appropriate selection of the most suitable assay, especially for resource-constrained regions where scant technical and socioeconomic resources restrict the options for testing with multiple assays. Further research is imperative to evaluate the existing assays through comprehensive comparative analyses. Such analyses are crucial for health agencies and wastewater surveillance practitioners in the selection of appropriate methods for monitoring COVID-19. In this study, untreated wastewater samples were collected weekly from the Detroit wastewater treatment plant, Michigan, USA, between January and December 2023. Polyethylene glycol precipitation (PEG) was applied to concentrate the samples followed by RNA extraction and RT-ddPCR. Three assays including N1, N2 (US CDC Real-Time Reverse Transcription PCR Panel for Detection of SARS-CoV-2), and SC2 assay (US CDC Influenza SARS-CoV-2 Multiplex Assay) were implemented to detect SARS-CoV-2 in wastewater. The limit of blank and limit of detection for the three assays were experimentally determined. SARS-CoV-2 RNA concentrations were evaluated and compared through three statistical approaches, including Pearson and Spearman's rank correlations, Dynamic Time Warping, and vector autoregressive models. N1 and N2 demonstrated the highest correlation and most similar time series patterns. Conversely, N2 and SC2 assay demonstrated the lowest correlation and least similar time series patterns. N2 was identified as the optimal target to predict COVID-19 cases. This study presents a rigorous effort in evaluating and comparing SARS-CoV-2 RNA concentrations quantified with N1, N2, and SC2 assays and their interrelations and correlations with clinical cases. This study provides valuable insights into identifying the optimal target for monitoring COVID-19 through wastewater surveillance.

Aptamer-Mediated Electrochemical Detection of SARS-CoV-2 Nucleocapsid Protein in Saliva

Gold standard detection of SARS-CoV-2 by reverse transcription quantitative PCR (RT-qPCR) can achieve ultrasensitive viral detection down to a few RNA copies per sample. Yet, the lengthy detection and labor-intensive protocol limit its effectiveness in community screening. In view of this, a structural switching electrochemical aptamer-based biosensor (E-AB) targeting the SARS-CoV-2 nucleocapsid (N) protein was developed. Four N protein-targeting aptamers were characterized on an electrochemical cell configuration using square wave voltammetry (SWV). The sensor was investigated in an artificial saliva matrix optimizing the aptamer anchoring orientation, SWV interrogation frequency, and target incubation time. Rapid detection of the N protein was achieved within 5 min at a low nanomolar limit of detection (LOD) with high specificity. Specific N protein detection was also achieved in simulated positive saliva samples, demonstrating its feasibility for saliva-based rapid diagnosis. Further research will incorporate novel signal amplification strategies to improve sensitivity for early diagnosis.

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.

An international inter-laboratory study to compare digital PCR with ISO standardized qPCR assays for the detection of norovirus GI and GII in oyster tissue

An optimized digital RT-PCR (RT-dPCR) assay for the detection of human norovirus GI and GII RNA was compared with ISO 15216-conform quantitative real-time RT-PCR (RT-qPCR) assays in an interlaboratory study (ILS) among eight laboratories. A duplex GI/GII RT-dPCR assay, based on the ISO 15216-oligonucleotides, was used on a Bio-Rad QX200 platform by six laboratories. Adapted assays for Qiagen Qiacuity or ThermoFisher QuantStudio 3D were used by one laboratory each. The ILS comprised quantification of norovirus RNA in the absence of matrix and in oyster tissue samples. On average, results of the RT-dPCR assays were very similar to those obtained by RT-qPCR assays. The coefficient of variation (CV%) of norovirus GI results was, however, much lower for RT-dPCR than for RT-qPCR in intra-laboratory replicates (eight runs) and between the eight laboratories. The CV% of norovirus GII results was in the same range for both detection formats. Had in-house prepared dsDNA standards been used, the CV% of norovirus GII could have been in favor of the RT-dPCR assay. The ratio between RT-dPCR and RT-qPCR results varied per laboratory, despite using the distributed RT-qPCR dsDNA standards. The study indicates that the RT-dPCR assay is likely to increase uniformity of quantitative results between laboratories.

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.

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.

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.

Making waves: The benefits and challenges of responsibly implementing wastewater-based surveillance for rural communities

The sampling and analysis of sewage for pathogens and other biomarkers offers a powerful tool for monitoring and understanding community health trends and potentially predicting disease outbreaks. Since the early months of the COVID-19 pandemic, the use of wastewater-based testing for public health surveillance has increased markedly. However, these efforts have focused on urban and peri‑urban areas. In most rural regions of the world, healthcare service access is more limited than in urban areas, and rural public health agencies typically have less disease outcome surveillance data than their urban counterparts. The potential public health benefits of wastewater-based surveillance for rural communities are therefore substantial - though so too are the methodological and ethical challenges. For many rural communities, population dynamics and insufficient, aging, and inadequately maintained wastewater collection and treatment infrastructure present obstacles to the reliable and responsible implementation of wastewater-based surveillance. Practitioner observations and research findings indicate that for many rural systems, typical implementation approaches for wastewater-based surveillance will not yield sufficiently reliable or actionable results. We discuss key challenges and potential strategies to address them. However, to support and expand the implementation of responsible, reliable, and ethical wastewater-based surveillance for rural communities, best practice guidelines and standards are needed.

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.

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.

SARS-CoV-2 in digital era: Diagnostic techniques and importance of nucleic acid quantification with digital PCRs

Studies related to clinical diagnosis and research of SARS-CoV-2 are important in the current pandemic era. Although molecular biology has emphasised the importance of qualitative analysis, quantitative analysis with nucleic acids in relation to SARS-CoV-2 needs to be clearly emphasised, which can provide perspective for viral dynamic studies of SARS-CoV-2. In this regard, the requirement and utilization of digital PCR in COVID-19 research has substantially increased during the pandemic, necessitating the aggregation of its cardinal applications and future scopes. Hence, this meta-review comprehensively addresses and emphasises the importance of nucleic acid quantification of SARS-CoV-2 RNA with digital PCR (dPCR). Various quantitative techniques of clinical significance like immunological, proteomic and nucleic acid-based diagnosis and quantification, have been comparatively discussed. Furthermore, the core part of the article focusses on the working principle and advantages of digital PCR, along with its applications in COVID-19 research. Several important applications like viral load quantitation, environmental surveillance and assay validation have been extensively investigated and discussed. Certain key future scopes of clinical importance, like mortality prediction, viral/variant-symbiosis, and antiviral studies were also identified, suggesting several possible digital PCR applications in COVID-19 research.

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.

Detection of SARS-CoV-2 RNA in wastewater from an enclosed college campus serves as an early warning surveillance system

SARS-CoV-2, the causative agent of Covid-19, is shed from infected persons in respiratory droplets, feces, and urine. Using quantitative PCR (qPCR), our group hypothesized that we could detect SARS-CoV-2 in wastewater samples collected on a university campus prior to the detection of the virus in individuals on campus. Wastewater samples were collected 3 times a week from 5 locations on the main campus of the University of North Carolina Wilmington (UNCW) from July 24, 2020 to December 21, 2020. Post-collection, total RNA was extracted and SARS-CoV-2 RNA in the samples was detected by qPCR. SARS-CoV-2 signal was detected on campus beginning on August 19 as classes began and the signal increased in both intensity and breadth as the Fall semester progressed. A comparison of two RNA extraction methods from wastewater showed that SARS-CoV-2 was detected more frequently on filter samples versus the direct extracts. Aligning our wastewater data with the reported SARS-CoV-2 cases on the campus Covid-19 dashboard showed the virus signal was routinely detected in the wastewater prior to clusters of individual cases being reported. These data support the testing of wastewater for the presence of SARS-CoV-2 and may be used as part of a surveillance program for detecting the virus in a community prior to an outbreak occurring and could ultimately be incorporated with other SARS-CoV-2 metrics to better inform public health enabling a quick response to contain or mitigating spread of the virus.

Comparison between droplet digital PCR and reverse transcription-quantitative PCR methods to measure ecotoxicology biomarkers

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is currently the gold-standard technique for detecting and quantifying messenger RNA. However, without proper validation, the method may produce artefactual and non-reproducible cycle threshold values generating poor-quality data. The newer droplet digital PCR (ddPCR) method allows for the absolute quantification of targeted nucleic acids providing more sensitive and accurate measurements without requiring external standards. This study compared these two PCR-based methods to measure the expression of well-documented genes used in ecotoxicology studies. We exposed Mediterranean mussels (Mytilus galloprovincialis) to copper and analyzed gene expression in gills and digestive glands using RT-qPCR and ddPCR assays. A step-by-step methodology to optimize and compare the two technologies is described. After ten-fold serial complementary DNA dilution, both RT-qPCR and ddPCR exhibited comparable linearity and efficiency and produced statistically similar results. We conclude that ddPCR is a suitable method to assess gene expression in an ecotoxicological context. However, RT-qPCR has a shorter processing time and remains more cost-effective.

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.

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.

Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network

In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.

Rapid Assessment of SARS-CoV-2 Variant-Associated Mutations in Wastewater Using Real-Time RT-PCR

Within months of the COVID-19 pandemic being declared on March 20, 2020, novel, more infectious variants of SARS-CoV-2 began to be detected in geospatially distinct regions of the world. With international travel being a lead cause of spread of the disease, the importance of rapidly identifying variants entering a country is critical. In this study, we utilized wastewater-based epidemiology (WBE) to monitor the presence of variants in wastewater generated in managed COVID-19 quarantine facilities for international air passengers entering the United Kingdom. Specifically, we developed multiplex reverse transcription quantitative PCR (RT-qPCR) assays for the identification of defining mutations associated with Beta (K417N), Gamma (K417T), Delta (156/157DEL), and Kappa (E154K) variants which were globally prevalent at the time of sampling (April to July 2021). The assays sporadically detected mutations associated with the Beta, Gamma, and Kappa variants in 0.7%, 2.3%, and 0.4% of all samples, respectively. The Delta variant was identified in 13.3% of samples, with peak detection rates and concentrations observed in May 2021 (24%), concurrent with its emergence in the United Kingdom. The RT-qPCR results correlated well with those from sequencing, suggesting that PCR-based detection is a good predictor for variant presence; although, inadequate probe binding may lead to false positive or negative results. Our findings suggest that WBE coupled with RT-qPCR may be used as a rapid, initial assessment to identify emerging variants at international borders and mass quarantining facilities. IMPORTANCE With the global spread of COVID-19, it is essential to identify emerging variants which may be more harmful or able to escape vaccines rapidly. To date, the gold standard to assess variants circulating in communities has been the sequencing of the S gene or the whole genome of SARS-CoV-2; however, that approach is time-consuming and expensive. In this study, we developed two duplex RT-qPCR assays to detect and quantify defining mutations associated with the Beta, Gamma, Delta, and Kappa variants. The assays were validated using RNA extracts derived from wastewater samples taken at quarantine facilities. The results showed good correlation with the results of sequencing and demonstrated the emergence of the Delta variant in the United Kingdom in May 2021. The assays developed here enable the assessment of variant-specific mutations within 2 h after the RNA extract was generated which is essential for outbreak rapid response.

Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

Simple Wastewater Preparation Protocol Applied to Monitor the Emergence of the Omicron 21L/BA.2 Variant by Genome Sequencing

Detecting and monitoring viruses in wastewater samples have been reported as useful ways of tracking SARS-CoV-2 epidemic trends. However, there is currently no unanimously recognised method of processing samples to identify and quantify SARS-CoV-2 variants in wastewater. We aimed to implement a method that was as simple as possible in order to be used universally. In a study performed between January 2022 and June 2022 in the city of Marseille, France, we first evaluated the impact of the sample preservation strategy. We then compared ultracentrifugation to ultrafiltration and several steps of filtration to determine the optimal approach for virus concentration. As a proof-of-concept, the definitive protocol was applied to next-generation sequencing of SARS-CoV-2 in wastewater to monitor the emergence of the Omicron variant in the city. For sewage water to be processed in the week following the sampling, storage at +4 °C is sufficient, with less than 1 Ct loss. Filtration with a 5 µm syringe filter, then with a 0.8 µm filtration unit, followed by ultrafiltration was the optimal protocol, leading to an average increase of 3.24 Ct when the starting Ct was on average 38 in the wastewater. This made it possible to observe the emergence of the Omicron 21L/BA.2 variant after Omicron 21K/BA.1 by genome sequencing over a period ranging from 20 February to 10 April 2022 in agreement with observations based on patient data. To conclude, by using a simple method requiring only basic filters and a centrifuge as equipment, it is possible to accurately track the relative incidence rates and the emergence of SARS-CoV-2 variants based on sewage samples.

Assessment of two volumetrically different concentration approaches to improve sensitivities for SARS-CoV-2 detection during wastewater monitoring

Wastewater monitoring for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), the virus responsible for the global coronavirus disease 2019 (COVID-19) pandemic, has highlighted the need for methodologies capable of assessing viral prevalence during periods of low population infection. To address this need, two volumetrically different, methodologically similar concentration approaches were compared for their abilities to detect viral nucleic acid and infectious SARS-CoV-2 signal from primary influent samples. For Method 1, 2 L of SARS-CoV-2 seeded wastewater was evaluated using a dead-end hollow fiber ultrafilter (D-HFUF) for primary concentration, followed by the CP Select™ for secondary concentration. For Method 2, 100 mL of SARS-CoV-2 seeded wastewater was evaluated using the CP Select™ procedure. Following D-HFUF concentration (Method 1), significantly lower levels of infectious SARS-CoV-2 were lost (P value range: 0.0398-0.0027) compared to viral gene copy (GC) levels detected by the US Centers for Disease Control (CDC) N1 and N2 reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) assays. Subsamples at different steps in the concentration process were also taken to better characterize the losses of SARS-CoV-2 during the concentration process. During the centrifugation step (prior to CP Select™ concentration), significantly higher losses (P value range: 0.0003 to <0.0001) occurred for SARS-CoV-2 GC levels compared to infectious virus for Method 1, while between the methods, significantly higher infectious viral losses were observed for Method 2 (P = 0.0002). When analyzing overall recovery of endogenous SARS-CoV-2 in wastewater samples, application of Method 1 improved assay sensitivities (P = <0.0001) compared with Method 2; this was especially evident during periods of lower COVID-19 case rates within the sewershed. This study describes a method which can successfully concentrate infectious SARS-CoV-2 and viral RNA from wastewater. Moreover, we demonstrated that large volume wastewater concentration provides additional sensitivity needed to improve SARS-CoV-2 detection, especially during low levels of community disease prevalence.

Evaluation of viral concentration and extraction methods for SARS-CoV-2 recovery from wastewater using droplet digital and quantitative RT-PCR

The ongoing pandemic caused by the emergence of SARS-CoV-2 has resulted in millions of deaths worldwide despite the various measures announced by the authorities. Wastewater-based epidemiology has the ability to provide a day-to-day estimation of the number of infected people in a fast and cost-effective manner. However, owing to the complex nature of wastewater, wastewater monitoring for viral genome copies is affected by the extensive viral fragmentation that takes place all the way to the sewage and the analytical lab. The aim of this study was to evaluate different methodologies for the concentration and extraction of viruses in wastewaters and to select and improve an option that maximizes the recovery of SARS-CoV-2. We compare 5 different concentration methods and 4 commercially available kits for the RNA extraction. To evaluate the performance and the recovery of these, SARS-CoV-2 isolated from patients was used as a spike control. Additionally, the presence of SARS-CoV-2 in all wastewater samples was determined using reverse transcription quantitative PCR (RT-qPCR) and reverse transcription droplet digital PCR (RT-ddPCR), targeting three genetic markers (N1, N2 and N3). Using spiked samples, recoveries were estimated 2.1-37.6% using different extraction kits and 0.1-2.1% using different concentration kits. It was found that a direct capture-based method, evaluated against a variety of concentration methods, is the best in terms of recovery, time and cost. Interestingly, we noticed a good agreement between the results provided by RT-qPCR and RT-ddPCR in terms of recovery. This evaluation can serve as a guide for laboratories establishing a protocol to perform wastewater monitoring of SARS-CoV-2. Overall, data presented here reinforces the validity of WBE for SARS-CoV-2 surveillance, uncovers potential caveats in the selection of concentration and extraction protocols and points towards optimal solutions to maximize its potential.

Importance of wastewater-based epidemiology for detecting and monitoring SARS-CoV-2

Coronavirus disease caused by the SARS-CoV-2 virus has emerged as a global challenge in terms of health and disease monitoring. COVID-19 infection is mainly spread through the SARS-CoV-2 infection leading to the development of mild to severe clinical manifestations. The virus binds to its cognate receptor ACE2 which is widely expressed among different tissues in the body. Notably, SARS-CoV-2 shedding in the fecal samples has been reported through the screening of sewage water across various countries. Wastewater screening for the presence of SARS-CoV-2 provides an alternative method to monitor infection threat, variant identification, and clinical evaluation to restrict the virus progression. Multiple cohort studies have reported the application of wastewater treatment approaches and epidemiological significance in terms of virus monitoring. Thus, the manuscript outlines consolidated and systematic information regarding the application of wastewater-based epidemiology in terms of monitoring and managing a viral disease outbreak like COVID-19.

Advances in virus detection methods for wastewater-based epidemiological applications

Wastewater-based epidemiology (WBE) is a powerful tool that has the potential to reveal the extent of an ongoing disease outbreak or to predict an emerging one. Recent studies have shown that SARS-CoV-2 concentration in wastewater may be correlated with the number of COVID-19 cases in the corresponding population. Most of the recent studies and applications of wastewater-based surveillance of SARS-CoV-2 applied the "gold standard" real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) detection method. However, this method also has its limitations. The paper aimed to present recent improvements and applications of the PCR-based methods for SARS-CoV-2 monitoring in wastewater. Furthermore, it aimed to review alternative methods utilized and/or proposed for the detection of the virus in wastewater matrices. From the review, it was found that several studies have investigated the use of reverse-transcription digital polymerase reaction (RT-dPCR), which was generally shown to have a lower limit of detection (LOD) over the RT-qPCR. Aside from this, non-PCR-based and non-RNA based methods have also been explored for the detection of SARS-CoV-2 in wastewater, with detailed attention given to the detection of SARS-CoV-2 proteins. The potential methods for protein detection include mass spectrometry, the use of immunosensors, and nanotechnological applications. In addition, the review of recent studies also revealed two types of emerging methods related to the detection of SARS-CoV-2 in wastewater: i) capsid-integrity assays to infer about the infectivity of SARS-CoV-2 present in wastewater, and ii) alternative methods for detection of SARS-CoV-2 variants of concern (VOCs) in wastewater. The recent studies on proposed methods of SARS-CoV-2 detection in wastewater have considered improving this approach in one or more of the following aspects: rapidity, simplicity, cost, sensitivity, and specificity. However, further studies are needed in order to realize the full application of these methods for WBE in the field.

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

We compared reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RT digital PCR (RT-dPCR) platforms for the trace detection of SARS-CoV-2 RNA in low-prevalence COVID-19 locations in Queensland, Australia, using CDC N1 and CDC N2 assays. The assay limit of detection (ALOD), PCR inhibition rates, and performance characteristics of each assay, along with the positivity rates with the RT-qPCR and RT-dPCR platforms, were evaluated by seeding known concentrations of exogenous SARS-CoV-2 in wastewater. The ALODs using RT-dPCR were approximately 2-5 times lower than those using RT-qPCR. During sample processing, the endogenous (n = 96) and exogenous (n = 24) SARS-CoV-2 wastewater samples were separated, and RNA was extracted from both wastewater eluates and pellets (solids). The RT-dPCR platform demonstrated a detection rate significantly greater than that of RT-qPCR for the CDC N1 and CDC N2 assays in the eluate (N1, p = 0.0029; N2, p = 0.0003) and pellet (N1, p = 0.0015; N2, p = 0.0067) samples. The positivity results also indicated that for the analysis of SARS-CoV-2 RNA in wastewater, including the eluate and pellet samples may further increase the detection sensitivity using RT-dPCR.

Subsewershed SARS-CoV-2 Wastewater Surveillance and COVID-19 Epidemiology Using Building-Specific Occupancy and Case Data

To evaluate the use of wastewater-based surveillance and epidemiology to monitor and predict SARS-CoV-2 virus trends, over the 2020-2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech's main campus. We used data from external door swipe card readers and student isolation/quarantine status to estimate building-specific occupancy and COVID-19 case counts at a daily resolution. After analyzing 673 wastewater samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), we reanalyzed 329 samples from isolation and nonisolation dormitories and the campus sewage outflow using reverse transcription digital droplet polymerase chain reaction (RT-ddPCR). Population-adjusted viral copy means from isolation dormitory wastewater were 48% and 66% higher than unadjusted viral copy means for N and E genes (1846/100 mL to 2733/100 mL/100 people and 2312/100 mL to 3828/100 mL/100 people, respectively; n = 46). Prespecified analyses with random-effects Poisson regression and dormitory/cluster-robust standard errors showed that the detection of N and E genes were associated with increases of 85% and 99% in the likelihood of COVID-19 cases 8 days later (incident-rate ratio (IRR) = 1.845, p = 0.013 and IRR = 1.994, p = 0.007, respectively; n = 215), and one-log increases in swipe card normalized viral copies (copies/100 mL/100 people) for N and E were associated with increases of 21% and 27% in the likelihood of observing COVID-19 cases 8 days following sample collection (IRR = 1.206, p < 0.001, n = 211 for N; IRR = 1.265, p < 0.001, n = 211 for E). One-log increases in swipe normalized copies were also associated with 40% and 43% increases in the likelihood of observing COVID-19 cases 5 days after sample collection (IRR = 1.403, p = 0.002, n = 212 for N; IRR = 1.426, p < 0.001, n = 212 for E). Our findings highlight the use of building-specific occupancy data and add to the evidence for the potential of wastewater-based epidemiology to predict COVID-19 trends at subsewershed scales.

Wastewater-Based Epidemiology for COVID-19: Handling qPCR Nondetects and Comparing Spatially Granular Wastewater and Clinical Data Trends

Wastewater-based epidemiology (WBE) is a useful complement to clinical testing for managing COVID-19. While community-scale wastewater and clinical data frequently correlate, less is known about subcommunity relationships between the two data types. Moreover, nondetects in qPCR wastewater data are typically handled through methods known to bias results, overlooking perhaps better alternatives. We address these knowledge gaps using data collected from September 2020-June 2021 in Davis, California (USA). We hypothesize that coupling the expectation maximization (EM) algorithm with the Markov Chain Monte Carlo (MCMC) method could improve estimation of "missing" values in wastewater qPCR data. We test this hypothesis by applying EM-MCMC to city wastewater treatment plant data and comparing output to more conventional nondetect handling methods. Dissimilarities in results (i) underscore the importance of specifying nondetect handling method in reporting and (ii) suggest that using EM-MCMC may yield better agreement between community-scale clinical and wastewater data. We also present a novel framework for spatially aligning clinical data with wastewater data collected upstream of a treatment plant (i.e., distributed across a sewershed). Applying the framework to data from Davis reveals reasonable agreement between wastewater and clinical data at highly granular spatial scales-further underscoring the public-health value of WBE.

Application of digital PCR for public health-related water quality monitoring

Digital polymerase chain reaction (dPCR) is emerging as a reliable platform for quantifying microorganisms in the field of water microbiology. This paper reviews the fundamental principles of dPCR and its application for health-related water microbiology. The relevant literature indicates increasing adoption of dPCR for measuring fecal indicator bacteria, microbial source tracking marker genes, and pathogens in various aquatic environments. The adoption of dPCR has accelerated recently due to increasing use for wastewater surveillance of Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) - the virus that causes Coronavirus Disease 2019 (COVID-19). The collective experience in the scientific literature indicates that well-optimized dPCR assays can quantify genetic material from microorganisms without the need for a calibration curve and often with superior analytical performance (i.e., greater sensitivity, precision, and reproducibility) than quantitative polymerase chain reaction (qPCR). Nonetheless, dPCR should not be viewed as a panacea for the fundamental uncertainties and limitations associated with measuring microorganisms in water microbiology. With dPCR platforms, the sample analysis cost and processing time are typically greater than qPCR. However, if improved analytical performance (i.e., sensitivity and accuracy) is critical, dPCR can be an alternative option for quantifying microorganisms, including pathogens, in aquatic environments.

Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities

Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.

Direct comparison of RT-ddPCR and targeted amplicon sequencing for SARS-CoV-2 mutation monitoring in wastewater

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3; hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing.

Direct comparison of RT-ddPCR and targeted amplicon sequencing for SARS-CoV-2 mutation monitoring in wastewater

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3; hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing.

RT-qPCR and ATOPlex sequencing for the sensitive detection of SARS-CoV-2 RNA for wastewater surveillance

During the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has become an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. In particular, reverse transcription-quantitative PCR (RT-qPCR) has been used to detect and quantify SARS-CoV-2 RNA in wastewater, while monitoring viral genome mutations requires separate approaches such as deep sequencing. A high throughput sequencing platform (ATOPlex) that uses a multiplex tiled PCR-based enrichment technique has shown promise in detecting variants of concern (VOC) while also providing virus quantitation data. However, detection sensitivities of both RT-qPCR and sequencing can be impacted through losses occurring during sample handling, virus concentration, nucleic acid extraction, and RT-qPCR. Therefore, process limit of detection (PLOD) assessments are required to estimate the gene copies of target molecule to attain specific probability of detection. In this study, we compare the PLOD of four RT-qPCR assays (US CDC N1 and N2, China CDC N and ORF1ab) for detection of SARS-CoV-2 to that of ATOPlex sequencing by seeding known concentrations of gamma-irradiated SARS-CoV-2 into wastewater. Results suggest that among the RT-qPCR assays, US CDC N1 was the most sensitive, especially at lower SARS-CoV-2 seed levels. However, when results from all RT-qPCR assays were combined, it resulted in greater detection rates than individual assays, suggesting that application of multiple assays is better suited for the trace detection of SARS-CoV-2 from wastewater samples. Furthermore, while ATOPlex offers a promising approach to SARS-CoV-2 wastewater surveillance, this approach appears to be less sensitive compared to RT-qPCR under the experimental conditions of this study, and may require further refinements. Nonetheless, the combination of RT-qPCR and ATOPlex may be a powerful tool to simultaneously detect/quantify SARS-CoV-2 RNA and monitor emerging VOC in wastewater samples.

Evaluating the impact of sample storage, handling, and technical ability on the decay and recovery of SARS-CoV-2 in wastewater

Wastewater based epidemiology (WBE) is useful for tracking and monitoring the level of disease prevalence in a community and has been used extensively to complement clinical testing during the current COVID-19 pandemic. Despite the numerous benefits, sources of variability in sample storage, handling, and processing methods can make WBE data difficult to generalize. We performed an experiment to determine sources of variability in WBE data including the impact of storage time, handling, and processing techniques on the concentration of SARS-CoV-2 in wastewater influent from three wastewater treatment plants (WWTP) in North Carolina over 19 days. The SARS-CoV-2 concentration in influent samples held at 4°C did not degrade significantly over the 19-day experiment. Heat pasteurization did not significantly impact the concentration of SARS-CoV-2 at two of the three WWTP but did reduce viral recovery at the WWTP with the smallest population size served. On each processing date, one filter from each sample was processed immediately while a replicate filter was frozen at -80°C. Once processed, filters previously frozen were found to contain slightly higher concentrations (<0.2 log copies/L) than their immediately processed counterparts, indicating freezing filters is a viable method for delayed quantification and may even improve recovery at WWTP with low viral concentrations. Investigation of factors contributing to variability during sample processing indicated that analyst experience level contributed significantly (p<0.001) to accepted droplet generation while extraction efficiency and reverse transcription efficiency contributed significantly (p<0.05) to day-to-day SARS-CoV-2 variability. This study provides valuable practical information for minimizing decay and/or loss of SARS CoV-2 in wastewater influent while adhering to safety procedures, promoting efficient laboratory workflows, and accounting for sources of variability.

Evaluation of process limit of detection and quantification variation of SARS-CoV-2 RT-qPCR and RT-dPCR assays for wastewater surveillance

Effective wastewater surveillance of SARS-CoV-2 RNA requires the rigorous characterization of the limit of detection resulting from the entire sampling process - the process limit of detection (PLOD). Yet to date, no studies have gone beyond quantifying the assay limit of detection (ALOD) for RT-qPCR or RT-dPCR assays. While the ALOD is the lowest number of gene copies (GC) associated with a 95% probability of detection in a single PCR reaction, the PLOD represents the sensitivity of the method after considering the efficiency of all processing steps (e.g., sample handling, concentration, nucleic acid extraction, and PCR assays) to determine the number of GC in the wastewater sample matrix with a specific probability of detection. The primary objective of this study was to estimate the PLOD resulting from the combination of primary concentration and extraction with six SARS-CoV-2 assays: five RT-qPCR assays (US CDC N1 and N2, China CDC N and ORF1ab (CCDC N and CCDC ORF1ab), and E_Sarbeco RT-qPCR, and one RT-dPCR assay (US CDC N1 RT-dPCR) using two models (exponential survival and cumulative Gaussian). An adsorption extraction (AE) concentration method (i.e., virus adsorption on membrane and the RNA extraction from the membrane) was used to concentrate gamma-irradiated SARS-CoV-2 seeded into 36 wastewater samples. Overall, the US CDC N1 RT-dPCR and RT-qPCR assays had the lowest ALODs (< 10 GC/reaction) and PLODs (<3,954 GC/50 mL; 95% probability of detection) regardless of the seeding level and model used. Nevertheless, consistent amplification and detection rates decreased when seeding levels were < 2.32 × 103 GC/50 mL even for US CDC N1 RT-qPCR and RT-dPCR assays. Consequently, when SARS-CoV-2 RNA concentrations are expected to be low, it may be necessary to improve the positive detection rates of wastewater surveillance by analyzing additional field and RT-PCR replicates. To the best of our knowledge, this is the first study to assess the SARS-CoV-2 PLOD for wastewater and provides important insights on the analytical limitations for trace detection of SARS-CoV-2 RNA in wastewater.

Integrating Virus Monitoring Strategies for Safe Non-potable Water Reuse

Wastewater reclamation and reuse have the potential to supplement water supplies, offering resiliency in times of drought and helping meet increased water demands associated with population growth. Non-potable water reuse represents the largest potential reuse market. Yet economic constraints for new water reuse infrastructure and safety concerns due to microbial water quality, and especially viral pathogen exposure, limit widespread implementation of water reuse. Cost-effective, real-time methods to measure or indicate viral quality of recycled water would do much to instill greater confidence in the practice. This manuscript discusses advancements in monitoring and modeling of viral health risks in the context of water reuse. First, we describe the current wastewater reclamation processes and treatment technologies with an emphasis on virus removal. Second, we review technologies for the measurement of viruses, both culture- and molecular-based, along with their advantages and disadvantages. We introduce promising viral surrogates and specific pathogenic viruses that can serve as indicators of viral risk for water reuse. We suggest metagenomic analyses for viral screening and flow cytometry for quantification of virus-like particles as new approaches to complement more traditional methods. Third, we describe modeling to assess health risks through quantitative microbial risk assessments (QMRAs), the most common strategy to couple data on virus concentrations with human exposure scenarios. We then explore the potential of artificial neural networks (ANNs) to incorporate suites of data from wastewater treatment processes, water quality parameters, and viral surrogates. We recommend ANNs as a means to utilize existing water quality data, alongside new complementary measures of viral quality, to achieve cost-effective strategies to assess risks associated with infectious human viruses in recycled water. Given the review, we conclude that technologies are ready for identifying and implementing viral surrogates for health risk reduction in the next decade. Incorporating modeling with monitoring data would likely result in more robust assessment of water reuse risk.

Improving correlation of wastewater SARS-CoV-2 gene copy numbers with COVID-19 public health cases using readily available biomarkers

The COVID-19 pandemic has highlighted the potential role that wastewater-based epidemiology can play in assessing aggregate community health. However, efforts to translate SARS-CoV-2 gene copy numbers obtained from wastewater samples into meaningful community health indicators are nascent. In this study, SARS-CoV-2 nucleocapsid (N) genes (N1 and N2) were quantified weekly using reverse transcriptase droplet digital PCR from two municipal wastewater treatment plants for seven months. Four biomarkers (ammonium, biological oxygen demand (BOD), creatinine, and human mitochondrial gene NADH dehydrogenase subunit 5) were quantified and used to normalize SARS-CoV-2 gene copy numbers. These were correlated to daily new case data and one-, two-, and three-week cumulative case data. Over the course of the study, the strongest correlations were observed with a one-day case data lag. However, early measurements were strongly correlated with a five-day case data lag. This indicates that in the early stages of the pandemic, the wastewater samples may have indicated active COVID-19 cases before clinical indications. Mitochondrial and creatinine normalization methods showed the strongest correlations throughout the study, indicating that human-specific biomarkers were better at normalizing wastewater data than ammonium or BOD. Granger causality tests supported this observation and showed that gene copies in wastewater could be predictive of new cases in a sewershed.

Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: A six-month long study in Charlotte, North Carolina

The global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus to be the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 103 to 105 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases when lagging 5 to 12 days (ρ = 0.52-0.92, p < 0.001-0.02). A major finding of this study is that RT-qPCR and RT-ddPCR generated SARS-CoV-2 data that was positively correlated (ρ = 0.569, p < 0.0001) and can be successfully used to monitor SARS-CoV-2 signals across the WWTP of different sizes and metropolitan service functions without significant anomalies.

SARS-CoV-2 detection in bioaerosols using a liquid impinger collector and ddPCR

The airborne route is the dominant form of COVID-19 transmission, and therefore, the development of methodologies to quantify SARS-CoV-2 in bioaerosols is needed. We aimed to identify SARS-CoV-2 in bioaerosols by using a highly efficient sampler for the collection of 1-3 µm particles, followed by a highly sensitive detection method. 65 bioaerosol samples were collected in hospital rooms in the presence of a COVID-19 patient using a liquid impinger sampler. The SARS-CoV-2 genome was detected by ddPCR using different primer/probe sets. 44.6% of the samples resulted positive for SARS-CoV-2 following this protocol. By increasing the sampled air volume from 339 to 650 L, the percentage of positive samples went from 41% to 50%. We detected five times less positives with a commercial one-step RT-PCR assay. However, the selection of primer/probe sets might be one of the most determining factor for bioaerosol SARS-CoV-2 detection since with the ORF1ab set more than 40% of the samples were positive, compared to <10% with other sets. In conclusion, the use of a liquid impinger collector and ddPCR is an adequate strategy to detect SARS-CoV-2 in bioaerosols. However, there are still some methodological aspects that must be adjusted to optimize and standardize a definitive protocol.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Wastewater surveillance to infer COVID-19 transmission: A systematic review

Successful detection of SARS-COV-2 in wastewater suggests the potential utility of wastewater-based epidemiology (WBE) for COVID-19 community surveillance. This systematic review aims to assess the performance of wastewater surveillance as early warning system of COVID-19 community transmission. A systematic search was conducted in PubMed, Medline, Embase and the WBE Consortium Registry according to PRISMA guidelines for relevant articles published until 31st July 2021. Relevant data were extracted and summarized. Quality of each paper was assessed using an assessment tool adapted from Bilotta et al.'s tool for environmental science. Of 763 studies identified, 92 studies distributed across 34 countries were shortlisted for qualitative synthesis. A total of 26,197 samples were collected between January 2020 and May 2021 from various locations serving population ranging from 321 to 11,400,000 inhabitants. Overall sample positivity was moderate at 29.2% in all examined settings with the spike (S) gene having maximum rate of positive detections and nucleocapsid (N) gene being the most targeted. Wastewater signals preceded confirmed cases by up to 63 days, with 13 studies reporting sample positivity before the first cases were detected in the community. At least 50 studies reported an association of viral load with community cases. While wastewater surveillance cannot replace large-scale diagnostic testing, it can complement clinical surveillance by providing early signs of potential transmission for more active public health responses. However, more studies using standardized and validated methods are required along with risk analysis and modelling to understand the dynamics of viral outbreaks.

Wastewater surveillance demonstrates high predictive value for COVID-19 infection on board repatriation flights to Australia

Controlling importation and transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from overseas travelers is essential for countries, such as Australia, New Zealand, and other island nations, that have adopted a suppression strategy to manage very low community transmission. Wastewater surveillance of SARS-CoV-2 RNA has emerged as a promising tool employed in public health response in many countries globally. This study aimed to establish whether the surveillance of aircraft wastewater can be used to provide an additional layer of information to augment individual clinical testing. Wastewater from 37 long-haul flights chartered to repatriate Australians was tested for the presence of SARS-CoV-2 RNA. Children 5 years or older on these flights tested negative for coronavirus disease 19 (COVID-19) (deep nasal and oropharyngeal reverse-transcription (RT)-PCR swab) 48 h before departure. All passengers underwent mandatory quarantine for 14-day post arrival in Howard Springs, NT, Australia. Wastewater from 24 (64.9 %) of the 37 flights tested positive for SARS-CoV-2 RNA. During the 14 day mandatory quarantine, clinical testing identified 112 cases of COVID-19. Surveillance for SARS-CoV-2 RNA in repatriation flight wastewater using pooled results from three RT-qPCR assays demonstrated a positive predictive value (PPV) of 87.5 %, a negative predictive value (NPV) of 76.9 % and 83.7% accuracy for COVID-19 cases during the post-arrival 14-day quarantine period. The study successfully demonstrates that the surveillance of wastewater from aircraft for SARS-CoV-2 can provide an additional and effective tool for informing the management of returning overseas travelers and for monitoring the importation of SARS CoV-2 and other clinically significant pathogens.

Performance evaluation of virus concentration methods for implementing SARS-CoV-2 wastewater based epidemiology emphasizing quick data turnaround

Wastewater based epidemiology (WBE) has drawn significant attention as an early warning tool to detect and predict the trajectory of COVID-19 cases in a community, in conjunction with public health data. This means of monitoring for outbreaks has been used at municipal wastewater treatment centers to analyze COVID-19 trends in entire communities, as well as by universities and other community living environments to monitor COVID-19 spread in buildings. Sample concentration is crucial, especially when viral abundance in raw wastewater is below the threshold of detection by RT-qPCR analysis. We evaluated the performance of a rapid ultrafiltration-based virus concentration method using InnovaPrep Concentrating Pipette (CP) Select and compared this to the established electronegative membrane filtration (EMF) method. We evaluated sensitivity of SARS-CoV-2 quantification, surrogate virus recovery rate, and sample processing time. Results suggest that the CP Select concentrator is more efficient at concentrating SARS-CoV-2 from wastewater compared to the EMF method. About 25% of samples that tested negative when concentrated with the EMF method produced a positive signal with the CP Select protocol. Increased recovery of the surrogate virus control using the CP Select confirms this observation. We optimized the CP Select protocol by adding AVL lysis buffer and sonication, to increase the recovery of virus. Sonication increased Bovine Coronavirus (BCoV) recovery by 19%, which seems to compensate for viral loss during centrifugation. Filtration time decreases by approximately 30% when using the CP Select protocol, making this an optimal choice for building surveillance applications where quick turnaround time is necessary.

Molecular Methods for Pathogenic Bacteria Detection and Recent Advances in Wastewater Analysis

With increasing concerns about public health and the development of molecular techniques, new detection tools and the combination of existing approaches have increased the abilities of pathogenic bacteria monitoring by exploring new biomarkers, increasing the sensitivity and accuracy of detection, quantification, and analyzing various genes such as functional genes and antimicrobial resistance genes (ARG). Molecular methods are gradually emerging as the most popular detection approach for pathogens, in addition to the conventional culture-based plate enumeration methods. The analysis of pathogens in wastewater and the back-estimation of infections in the community, also known as wastewater-based epidemiology (WBE), is an emerging methodology and has a great potential to supplement current surveillance systems for the monitoring of infectious diseases and the early warning of outbreaks. However, as a complex matrix, wastewater largely challenges the analytical performance of molecular methods. This review synthesized the literature of typical pathogenic bacteria in wastewater, types of biomarkers, molecular methods for bacterial analysis, and their recent advances in wastewater analysis. The advantages and limitation of these molecular methods were evaluated, and their prospects in WBE were discussed to provide insight for future development.

Looking for a needle in a haystack. SARS-CoV-2 variant characterization in sewage

SARS-CoV-2 variants are emerging worldwide, and monitoring them is key in providing early warnings. Here, we summarize the different analytical approaches currently used to study the dissemination of SARS-CoV-2 variants in wastewater and discuss their advantages and disadvantages. We also provide preliminary results of two sensitive and cost-effective approaches: variant-specific reverse transcription-nested PCR assays and a nonvariant-specific amplicon deep sequencing strategy that targets three key regions of the viral spike protein. Next-generation sequencing approaches enable the simultaneous detection of signature mutations of different variants of concern in a single assay and may be the best option to explore the real picture at a particular time. Targeted PCR approaches focused on specific signature mutations will need continuous updating but are sensitive and cost-effective.

Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus

The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.