High-resolution within-sewer SARS-CoV-2 surveillance facilitates informed intervention

Comparative performance of electronegative membrane filtration and automated concentrating pipette for detection of antibiotic resistance genes and microbial markers in river water samples

The target viral and bacterial concentrations in river water are essential for environmental monitoring and public health studies. Filtration-based methods are commonly employed, yet challenges arise due to recoverability and filter pore size. This study aimed to compare the performance of electronegative membrane filtration (EMF) and automated Concentrating Pipette (CP) Select (InnovaPrep) methods for quantifying antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and bacterial and viral markers in river water samples. Fifty-four river water samples were collected from upstream and downstream locations in a river in Japan. The CP Select method was modified by adding MgCl2 and using different tips. The recovery efficiencies for total coliforms and Escherichia coli were assessed, and class 1 integron-integrase gene (intI1), 16S rRNA, gene encoding sulfonamide resistance (sul1), cross-assembly phage (crAssphage), pepper mild mottle virus (PMMoV), and Escherichia coli gene (sfmD) were detected. CP Select showed recovery efficiencies of 45 %-63 % for total coliforms and 17 %-35 % for E. coli. The intI1, 16S rRNA, sul1, crAssphage, PMMoV, and sfmD concentrations using the modified CP Select method were 10.1 ± 0.5, 8.7 ± 0.2, 7.7 ± 0.2, 6.7 ± 0.2, 5.4 ± 0.2, and 3.5 ± 0.5 log10 copies/L, respectively. Higher intI1 and sul1 concentrations were observed downstream, with the highest contribution percentage (22 % and 21 %) using CP Select or EMF. The modified CP Select method with 0.05 μm tips yielded more quantifiable results for all target genes and greater PMMoV concentrations (p < 0.05). Positive correlations were found among bacterial, ARG/MGE, and viral markers (Spearman's ρ = 0.71 for 16S rRNA and sfmD, 0.88 for intI1 and sul1, and 0.64 for PMMoV and crAssphage). The modified CP Select method demonstrated effective recovery of bacteria and quantification of ARGs, MGEs, and microbial markers in river water. Further studies are required to validate these methods and confirm their applicability in diverse environmental contexts.

Evaluation of a field deployable, high-throughput RT-LAMP device as an early warning system for COVID-19 through SARS-CoV-2 measurements in wastewater

Quantification of SARS-CoV-2 RNA copies in wastewater can be used to estimate COVID-19 prevalence in communities. While such results are important for mitigating disease spread, SARS-CoV-2 measurements require sophisticated equipment and trained personnel, for which a centralized laboratory is necessary. This significantly impacts the time to result, defeating its purpose as an early warning detection tool. The objective of this study was to evaluate a field portable device (called MINI) for detecting SARS-CoV-2 viral loads in wastewater using real-time reverse transcriptase loop-mediated isothermal amplification (real-time RT-LAMP). The device was tested using wastewater samples collected from buildings (with 430 to 1430 inhabitants) that had known COVID-19-positive cases. Results show comparable performance of RT-LAMP against reverse transcriptase polymerase chain reaction (RT-qPCR) when detecting SARS-CoV-2 copies in wastewater. Both RT-LAMP and RT-qPCR detected SARS-CoV-2 in wastewater from buildings with at least three positive individuals within a 6-day time frame prior to diagnosis. The large 96-well throughput provided by MINI provided scalability to multi-building detection. The portability of the MINI device enabled decentralized on-site detection, significantly reducing the time to result. The overall findings support the use of RT-LAMP within the MINI configuration as an early detection system for COVID-19 infection using wastewater collected at the building scale.

Mapping the heterogeneous removal landscape of wastewater virome in effluents of different advanced wastewater treatment systems of swine farm

In advanced wastewater treatment plants on pig farms, meticulous design aims to eliminate intrinsic pollutants such as organic matter, heavy metals, and biological contaminants. In our field survey across Southern China, a notable disparity in wastewater treatment procedures among various farming facilities lies in the utilization of terminal chemical oxidation post-sedimentation tank. However, recent focus in wastewater surveillance has predominantly centered on antibiotic resistance genes, leaving the efficacy of virus removal in different effluent systems largely unexplored. To profile virus composition at the effluent, assess the virus elimination efficiency of chemical oxidation at the effluent end, and the potential environmental driver of virus abundance, we deployed a meta-transcriptomics approach to first determine the total virome in effluent specimens of terminal clean water tank system (CWT) and terminal chemical oxidation system (TCO) in Southern China pig farms, respectively. From these data, 172 viruses were identified, with a median reads per million (RPM) of 27,789 in CWT and 19,982 in TCO. Through the integration of analyses encompassing the co-occurrence patterns within viral communities, the ecology of viral diversity, and a comparative assessment of average variation degrees, we have empirically demonstrated that the procedure of TCO may perturb viral communities and diminish their abundance, particularly impacting RNA viral communities. However, despite the diminished abundance, pathogenic viruses such as PEDV and PRRSV persisted in the effluent following chemical deoxidation at a moderate RPM value, indicating a substantial in situ presence at effluent. Our environmental driver modeling, employing GLM and mantel tests, substantiated the intricate nature of virus community variation within the effluent, influenced heterogeneously by diverse factors. Notably, pond temperature emerged as the foremost determinant, while fishing farming exhibited a positive correlation with virus diversity (p < 0.05). This revelation of the cryptic persistence of virus communities in wastewater effluent expands our understanding of the varied responses of different virus categories to oxidation. Such insights transcend mere virus characterization, offering valuable implications for enhancing biosafety measures in farming practices and informing wastewater-based epidemiological surveillance.

COVID-19 cases, vaccination, and SARS-CoV-2 in wastewater: insights from a Brazilian municipality

Vaccines combatting COVID-19 demonstrate the ability to protect against disease and hospitalization, and reduce the likelihood of death caused by SARS-CoV-2. In addition, monitoring viral loads in sewage emerges as another crucial strategy in the epidemiological context, enabling early and collective detection of outbreaks. The study aimed to monitor the viral concentration of SARS-CoV-2 in untreated sewage in a Brazilian municipality. Also, it attempted to correlate these measurements with the number of clinical cases and deaths resulting from COVID-19 between July 2021 and July 2022. SARS-CoV-2 viral RNA was quantified by RT-qPCR. Pearson's correlation was performed to analyze the variables' relationship using the number of cases, deaths, vaccinated individuals, and viral concentration of SARS-CoV-2. The results revealed a significant negative correlation (p < 0.05) between the number of vaccinated individuals and the viral concentration of SARS-CoV-2, suggesting that after vaccination, the RNA viral load concentration was reduced in the sample population by the circulating concentration of wastewater. Consequently, wastewater monitoring, in addition to functioning as an early warning system for the circulation of SARS-CoV-2 and other pathogens, can offer a novel perspective that enhances decision-making, strengthens vaccination campaigns, and contributes to authorities establishing systematic networks for monitoring SARS-CoV-2.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

Structured Ethical Review for Wastewater-Based Testing in Support of Public Health

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of WBT measured biomarkers for research activities and for the pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process, introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary workshop developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11 questions derived from primarily public health guidance. This study retrospectively applied these questions to SARS-CoV-2 monitoring programs covering the emergent phase of the pandemic (3/2020-2/2022 (n = 53)). Of note, 43% of answers highlight a lack of reported information to assess. Therefore, a systematic framework would at a minimum structure the communication of ethical considerations for applications of WBT. Consistent application of an ethical review will also assist in developing a practice of updating approaches and techniques to reflect the concerns held by both those practicing and those being monitored by WBT supported programs.

Wastewater Surveillance for SARS-CoV-2 at Long-Term Care Facilities: Mixed Methods Evaluation

BACKGROUND

Wastewater surveillance provided early indication of COVID-19 in US municipalities. Residents of long-term care facilities (LTCFs) experienced disproportionate morbidity and mortality early in the COVID-19 pandemic. We implemented LTCF building-level wastewater surveillance for SARS-CoV-2 at 6 facilities in Kentucky to provide early warning of SARS-CoV-2 in populations considered vulnerable.

OBJECTIVE

This study aims to evaluate the performance of wastewater surveillance for SARS-CoV-2 at LTCFs in Kentucky.

METHODS

We conducted a mixed methods evaluation of wastewater surveillance following Centers for Disease Control and Prevention (CDC) guidelines for evaluating public health surveillance systems. Evaluation steps in the CDC guidelines were engaging stakeholders, describing the surveillance system, focusing the evaluation design, gathering credible evidence, and generating conclusions and recommendations. We purposively recruited stakeholders for semistructured interviews and undertook thematic content analysis of interview data. We integrated wastewater, clinical testing, and process data to characterize or calculate 7 surveillance system performance attributes (simplicity, flexibility, data quality, sensitivity and positive predictive value [PPV], timeliness, representativeness, and stability).

RESULTS

We conducted 8 stakeholder interviews. The surveillance system collected wastewater samples (N=811) 2 to 4 times weekly at 6 LTCFs in Kentucky from March 2021 to February 2022. Synthesis of credible evidence indicated variable surveillance performance. Regarding simplicity, surveillance implementation required moderate human resource and technical capacity. Regarding flexibility, the system efficiently adjusted surveillance frequency and demonstrated the ability to detect additional pathogens of interest. Regarding data quality, software identified errors in wastewater sample metadata entry (110/3120, 3.53% of fields), technicians identified polymerase chain reaction data issues (140/7734, 1.81% of reactions), and staff entered all data corrections into a log. Regarding sensitivity and PPV, using routine LTCF SARS-CoV-2 clinical testing results as the gold standard, a wastewater SARS-CoV-2 signal of >0 RNA copies/mL was 30.6% (95% CI 24.4%-36.8%) sensitive and 79.7% (95% CI 76.4%-82.9%) specific for a positive clinical test at the LTCF. The PPV of the wastewater signal was 34.8% (95% CI 27.9%-41.7%) at >0 RNA copies/mL and increased to 75% (95% CI 60%-90%) at >250 copies/mL. Regarding timeliness, stakeholders received surveillance data 24 to 72 hours after sample collection, with delayed reporting because of the lack of weekend laboratory staff. Regarding representativeness, stakeholders identified challenges delineating the population contributing to LTCF wastewater because of visitors, unknown staff toileting habits, and the use of adult briefs by some residents preventing their waste from entering the sewer system. Regarding stability, the reoccurring cost to conduct 1 day of wastewater surveillance at 1 facility was approximately US $144.50, which included transportation, labor, and materials expenses.

CONCLUSIONS

The LTCF wastewater surveillance system demonstrated mixed performance per CDC criteria. Stakeholders found surveillance feasible and expressed optimism regarding its potential while also recognizing challenges in interpreting and acting on surveillance data.

Structured Ethical Review for Wastewater-Based Testing

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of the field blurred the boundary between measuring biomarkers for research activities and for pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process (or associated data management safeguards), introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary group developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11-questions derived from primarily public health guidance because of the common exemption of wastewater samples to human subject research considerations. This study retrospectively applied the set of questions to peer- reviewed published reports on SARS-CoV-2 monitoring campaigns covering the emergent phase of the pandemic from March 2020 to February 2022 (n=53). Overall, 43% of the responses to the questions were unable to be assessed because of lack of reported information. It is therefore hypothesized that a systematic framework would at a minimum improve the communication of key ethical considerations for the application of WBT. Consistent application of a standardized ethical review will also assist in developing an engaged practice of critically applying and updating approaches and techniques to reflect the concerns held by both those practicing and being monitored by WBT supported campaigns.

Abstract Figure

Synopsis

Development of a structured ethical review facilitates retrospective analysis of published studies and drafted scenarios in the context of wastewater-based testing.

SARS-CoV-2 wastewater-based epidemiology in an enclosed compound: A 2.5-year survey to identify factors contributing to local community dissemination

Long-term (>2.5 years) surveillance of SARS-CoV-2 RNA concentrations in wastewater was conducted within an enclosed university compound. This study aims to demonstrate how coupling wastewater-based epidemiology (WBE) with meta-data can identify which factors contribute toward the dissemination of SARS-CoV-2 within a local community. Throughout the pandemic, the temporal dynamics of SARS-CoV-2 RNA concentrations were tracked by quantitative polymerase chain reaction and analyzed in the context of the number of positive swab cases, the extent of human movement, and intervention measures. Our findings suggest that during the early phase of the pandemic, when strict lockdown was imposed, the viral titer load in the wastewater remained below detection limits, with <4 positive swab cases reported over a 14-day period in the compound. After the lockdown was lifted and global travel gradually resumed, SARS-CoV-2 RNA was first detected in the wastewater on 12 August 2020 and increased in frequency thereafter, despite high vaccination rates and mandatory face-covering requirements in the community. Accompanied by a combination of the Omicron surge and significant global travel by community members, SARS-CoV-2 RNA was detected in most of the weekly wastewater samples collected in late December 2021 and January 2022. With the cease of mandatory face covering, SARS-CoV-2 was detected in at least two of the four weekly wastewater samples collected from May through August 2022. Retrospective Nanopore sequencing revealed the presence of the Omicron variant in the wastewater with a multitude of amino acid mutations, from which we could infer the likely geographical origins through bioinformatic analysis. This study demonstrated that long-term tracking of the temporal dynamics and sequencing of variants in wastewater would aid in identifying which factors contribute the most to SARS-CoV-2 dissemination within the local community, facilitating an appropriate public health response to control future outbreaks as we now live with endemic SARS-CoV-2.

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.

Parallel deployment of passive and composite samplers for surveillance and variant profiling of SARS-CoV-2 in sewage

Wastewater-based epidemiology during the COVID-19 pandemic has proven useful for public health decision-making but is often hampered by sampling methodology constraints, particularly at the building- or neighborhood-level. Time-weighted composite samples are commonly used; however, autosamplers are expensive and can be affected by intermittent flows in sub-sewershed contexts. In this study, we compared time-weighted composite, grab, and passive sampling via Moore swabs, at four locations across a college campus to understand the utility of passive sampling. After optimizing the methods for sample handling and processing for viral RNA extraction, we quantified SARS-CoV-2 N1 and N2, as well as a fecal strength indicator, PMMoV, by ddRT-PCR and applied tiled amplicon sequencing of the SARS-CoV-2 genome. Passive samples compared favorably with composite samples in our study area: for samples collected concurrently, 42 % of the samples agreed between Moore swab and composite samples and 58 % of the samples were positive for SARS-CoV-2 using Moore swabs while composite samples were below the limit of detection. Variant profiles from Moore swabs showed a shift from variant BA.1 to BA.2, consistent with in-person saliva samples. These data have implications for the broader implementation of sewage surveillance without advanced sampling technologies and for the utilization of passive sampling approaches for other emerging pathogens.

Managing the Transition to Widespread Metagenomic Monitoring: Policy Considerations for Future Biosurveillance

The technological possibilities and future public health importance of metagenomic sequencing have received extensive attention, but there has been little discussion about the policy and regulatory issues that need to be addressed if metagenomic sequencing is adopted as a key technology for biosurveillance. In this article, we introduce metagenomic monitoring as a possible path to eventually replacing current infectious disease monitoring models. Many key enablers are technological, whereas others are not. We therefore highlight key policy challenges and implementation questions that need to be addressed for "widespread metagenomic monitoring" to be possible. Policymakers must address pitfalls like fragmentation of the technological base, private capture of benefits, privacy concerns, the usefulness of the system during nonpandemic times, and how the future systems will enable better response. If these challenges are addressed, the technological and public health promise of metagenomic sequencing can be realized.

Using geographic information systems to link population estimates to wastewater surveillance data in New York State, USA

Sewer systems provide many services to communities that have access to them beyond removal of waste and wastewater. Understanding of these systems' geographic coverage is essential for wastewater-based epidemiology (WBE), which requires accurate estimates for the population contributing wastewater. Reliable estimates for the boundaries of a sewer service area or sewershed can be used to link upstream populations to wastewater samples taken at treatment plants or other locations within a sewer system. These geographic data are usually managed by public utilities, municipal offices, and some government agencies, however, there are no centralized databases for geographic information on sewer systems in New York State. We created a database for all municipal sewersheds in New York State for the purpose of supporting statewide wastewater surveillance efforts to support public health. We used a combination of public tax records with sewer access information, physical maps, and municipal records to organize and draw digital boundaries compatible with geographic information systems. The methods we employed to create these data will be useful to inform similar efforts in other jurisdictions and the data have many public health applications as well as being informative for water/environmental research and infrastructure projects.

Retrospective Analysis of Wastewater-Based Epidemiology of SARS-CoV-2 in Residences on a Large College Campus: Relationships between Wastewater Outcomes and COVID-19 Cases across Two Semesters with Different COVID-19 Mitigation Policies

Wastewater-based epidemiology (WBE) has been utilized for outbreak monitoring and response efforts in university settings during the coronavirus disease 2019 (COVID-19) pandemic. However, few studies examined the impact of university policies on the effectiveness of WBE to identify cases and mitigate transmission. The objective of this study was to retrospectively assess relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater outcomes and COVID-19 cases in residential buildings of a large university campus across two academic semesters (August 2020-May 2021) under different COVID-19 mitigation policies. Clinical case surveillance data of student residents were obtained from the university COVID-19 response program. We collected and processed building-level wastewater for detection and quantification of SARS-CoV-2 RNA by RT-qPCR. The odds of obtaining a positive wastewater sample increased with COVID-19 clinical cases in the fall semester (OR = 1.50, P value = 0.02), with higher odds in the spring semester (OR = 2.63, P value < 0.0001). We observed linear associations between SARS-CoV-2 wastewater concentrations and COVID-19 clinical cases (parameter estimate = 1.2, P value = 0.006). Our study demonstrated the effectiveness of WBE in the university setting, though it may be limited under different COVID-19 mitigation policies. As a complementary surveillance tool, WBE should be accompanied by robust administrative and clinical testing efforts for the COVID-19 pandemic response.

Multimodal surveillance of SARS-CoV-2 at a university enables development of a robust outbreak response framework

BACKGROUND

Universities are vulnerable to infectious disease outbreaks, making them ideal environments to study transmission dynamics and evaluate mitigation and surveillance measures. Here, we analyze multimodal COVID-19-associated data collected during the 2020-2021 academic year at Colorado Mesa University and introduce a SARS-CoV-2 surveillance and response framework.

METHODS

We analyzed epidemiological and sociobehavioral data (demographics, contact tracing, and WiFi-based co-location data) alongside pathogen surveillance data (wastewater and diagnostic testing, and viral genomic sequencing of wastewater and clinical specimens) to characterize outbreak dynamics and inform policy. We applied relative risk, multiple linear regression, and social network assortativity to identify attributes or behaviors associated with contracting SARS-CoV-2. To characterize SARS-CoV-2 transmission, we used viral sequencing, phylogenomic tools, and functional assays.

FINDINGS

Athletes, particularly those on high-contact teams, had the highest risk of testing positive. On average, individuals who tested positive had more contacts and longer interaction durations than individuals who never tested positive. The distribution of contacts per individual was overdispersed, although not as overdispersed as the distribution of phylogenomic descendants. Corroboration via technical replicates was essential for identification of wastewater mutations.

CONCLUSIONS

Based on our findings, we formulate a framework that combines tools into an integrated disease surveillance program that can be implemented in other congregate settings with limited resources.

FUNDING

This work was supported by the National Science Foundation, the Hertz Foundation, the National Institutes of Health, the Centers for Disease Control and Prevention, the Massachusetts Consortium on Pathogen Readiness, the Howard Hughes Medical Institute, the Flu Lab, and the Audacious Project.

Wastewater-Based Epidemiology Mitigates COVID-19 Outbreaks at a Food Processing Facility near the Mexico-U.S. Border-November 2020-March 2022

Background: Wastewater-based epidemiology (WBE) has the potential to inform activities to contain infectious disease outbreaks in both the public and private sectors. Although WBE for SARS-CoV-2 has shown promise over short time intervals, no other groups have evaluated how a public-private partnership could influence disease spread through public health action over time. The aim of this study was to characterize and assess the application of WBE to inform public health response and contain COVID-19 infections in a food processing facility. Methods: Over the period November 2020-March 2022, wastewater in an Arizona food processing facility was monitored for the presence of SARS-CoV-2 using Real-Time Quantitative PCR. Upon positive detection, partners discussed public health intervention strategies, including infection control reinforcement, antigen testing, and vaccination. Results: SARS-CoV-2 RNA was detected on 18 of 205 days in which wastewater was sampled and analyzed (8.8%): seven during Wild-type predominance and 11 during Omicron-variant predominance. All detections triggered the reinforcement of infection control guidelines. In five of the 18 events, active antigen testing identified asymptomatic workers. Conclusions: These steps heightened awareness to refine infection control protocols and averted possible transmission events during periods where detection occurred. This public-private partnership has potentially decreased human illness and economic loss during the COVID-19 pandemic.

Predicting COVID-19 Infected Individuals in a Defined Population from Wastewater RNA Data

Wastewater surveillance of SARS-CoV-2 RNA has become an important tool for tracking the presence of the virus and serving as an early indicator for the onset of rapid transmission. Nevertheless, wastewater data are still not commonly used to predict the number of infected individuals in a sewershed. The main objective of this study was to calibrate a susceptible-exposed-infectious-recovered (SEIR) model using RNA copy rates in sewage (i.e., gene copies per liter times flow rate) and the number of SARS-CoV-2 saliva-test-positive infected individuals in a university student population that was subject to repeated weekly testing during the Spring 2021 semester. A strong correlation was observed between the RNA copy rates and the number of infected individuals. The parameter in the SEIR model that had the largest impact on calibration was the maximum shedding rate, resulting in a mean value of 7.72 log10 genome copies per gram of feces. Regressing the saliva-test-positive infected individuals on predictions from the SEIR model based on the RNA copy rates yielded a slope of 0.87 (SE=0.11), which is statistically consistent with a 1:1 relationship between the two. These findings demonstrate that wastewater surveillance of SARS-CoV-2 can be used to estimate the number of infected individuals in a sewershed.

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.

Comparative Analysis of RNA-Extraction Approaches and Associated Influences on RT-qPCR of the SARS-CoV-2 RNA in a University Residence Hall and Quarantine Location

Wastewater-based epidemiology (WBE) provides an early warning and trend analysis approach for determining the presence of COVID-19 in a community and complements clinical testing in assessing the population level, even as viral loads fluctuate. Here, we evaluate combinations of two wastewater concentration methods (i.e., ultrafiltration and composite supernatant-solid), four pre-RNA extraction modifications, and three nucleic acid extraction kits using two different wastewater sampling locations. These consisted of a quarantine facility containing clinically confirmed COVID-19-positive inhabitants and a university residence hall. Of the combinations examined, composite supernatant-solid with pre-RNA extraction consisting of water concentration and RNA/DNA shield performed the best in terms of speed and sensitivity. Further, of the three nucleic acid extraction kits examined, the most variability was associated with the Qiagen kit. Focusing on the quarantine facility, viral concentrations measured in wastewater were generally significantly related to positive clinical cases, with the relationship dependent on method, modification, kit, target, and normalization, although results were variable-dependent on individual time points (Kendall's Tau-b (τ) = 0.17 to 0.6) or cumulatively (Kendall's Tau-b (τ) = -0.048 to 1). These observations can support laboratories establishing protocols to perform wastewater surveillance and monitoring efforts for COVID-19.

Quantitative Reverse Transcription PCR Surveillance of SARS-CoV-2 Variants of Concern in Wastewater of Two Counties in Texas, United States

After its emergence in late November/December 2019, the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) rapidly spread globally. Recognizing that this virus is shed in feces of individuals and that viral RNA is detectable in wastewater, testing for SARS-CoV-2 in sewage collections systems has allowed for the monitoring of a community's viral burden. Over a 9 month period, the influents of two regional wastewater treatment facilities were concurrently examined for wild-type SARS-CoV-2 along with variants B.1.1.7 and B.1.617.2 incorporated as they emerged. Epidemiological data including new confirmed COVID-19 cases and associated hospitalizations and fatalities were tabulated within each location. RNA from SARS-CoV-2 was detectable in 100% of the wastewater samples, while variant detection was more variable. Quantitative reverse transcription PCR (RT-qPCR) results align with clinical trends for COVID-19 cases, and increases in COVID-19 cases were positively related with increases in SARS-CoV-2 RNA load in wastewater, although the strength of this relationship was location specific. Our observations demonstrate that clinical and wastewater surveillance of SARS-CoV-2 wild type and constantly emerging variants of concern can be combined using RT-qPCR to characterize population infection dynamics. This may provide an early warning for at-risk communities and increases in COVID-19 related hospitalizations.

A Metagenomic Investigation of Spatial and Temporal Changes in Sewage Microbiomes across a University Campus

Wastewater microbial communities are not static and can vary significantly across time and space, but this variation and the factors driving the observed spatiotemporal variation often remain undetermined. We used a shotgun metagenomic approach to investigate changes in wastewater microbial communities across 17 locations in a sewer network, with samples collected from each location over a 3-week period. Fecal material-derived bacteria constituted a relatively small fraction of the taxa found in the collected samples, highlighting the importance of environmental sources to the sewage microbiome. The prokaryotic communities were highly variable in composition depending on the location within the sampling network, and this spatial variation was most strongly associated with location-specific differences in sewage pH. However, we also observed substantial temporal variation in the composition of the prokaryotic communities at individual locations. This temporal variation was asynchronous across sampling locations, emphasizing the importance of independently considering both spatial and temporal variation when assessing the wastewater microbiome. The spatiotemporal patterns in viral community composition closely tracked those of the prokaryotic communities, allowing us to putatively identify the bacterial hosts of some of the dominant viruses in these systems. Finally, we found that antibiotic resistance gene profiles also exhibit a high degree of spatiotemporal variability, with most of these genes unlikely to be derived from fecal bacteria. Together, these results emphasize the dynamic nature of the wastewater microbiome, the challenges associated with studying these systems, and the utility of metagenomic approaches for building a multifaceted understanding of these microbial communities and their functional attributes. IMPORTANCE Sewage systems harbor extensive microbial diversity, including microbes derived from both human and environmental sources. Studies of the sewage microbiome are useful for monitoring public health and the health of our infrastructure, but the sewage microbiome can be highly variable in ways that are often unresolved. We sequenced DNA recovered from wastewater samples collected over a 3-week period at 17 locations in a single sewer system to determine how these communities vary across time and space. Most of the wastewater bacteria, and the antibiotic resistance genes they harbor, were not derived from human feces, but human usage patterns did impact how the amounts and types of bacteria and bacterial genes we found in these systems varied over time. Likewise, the wastewater communities, including both bacteria and their viruses, varied depending on location within the sewage network, highlighting the challenges and opportunities in efforts to monitor and understand the sewage microbiome.

Effectiveness of building-level sewage surveillance during both community-spread and sporadic-infection phases of SARS-CoV-2 in a university campus population

Pathogen surveillance within wastewater rapidly progressed during the SARS-CoV-2 pandemic and informed public health management. In addition to the successful monitoring of entire sewer catchment basins at the treatment facility scale, subcatchment or building-level monitoring enabled targeted support of resource deployment. However, optimizing the temporal and spatial resolution of these monitoring programs remains complex due to population dynamics and within-sewer physical, chemical, and biological processes. To address these limitations, this study explores the advancement of the building-scale network that monitored the on-campus residential population at the University of Colorado Boulder between August 2020 and May 2021 through a daily SARS-CoV-2 surveillance campaign. During the study period, SARS-CoV-2 infection prevalence transitioned from robust community spread in Fall 2020 to sporadic infections in Spring 2021. Temporally, these distinct phases enabled investigating the effectiveness of resource commitment by exploring subsets of the original daily sampling data. Spatially, select sampling sites were installed along the flow path of the pipe network, enabling the exploration of the conservation of viral concentrations within the wastewater. Infection prevalence and resource commitment for informed action displayed an inverted relationship: higher temporal and spatial resolution surveillance is more imperative during sporadic infection phases than during high prevalence periods. This relationship was reinforced when norovirus (two minor clusters) and influenza (primarily absent) were additionally surveilled at a weekly frequency. Overall, resource commitment should scale to meet the objectives of the monitoring campaign-providing a general prevalence estimate requires fewer resources than an early-warning and targeted-action monitoring framework.

Quantifying the Relationship between SARS-CoV-2 Wastewater Concentrations and Building-Level COVID-19 Prevalence at an Isolation Residence: A Passive Sampling Approach

SARS-CoV-2 RNA loads can be detected in the excreta of individuals with COVID-19 and have demonstrated positive correlations with clinical infection trends. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor community-level prevalence of infections. The majority of wastewater specimens are gathered as either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and can be challenging to maintain in cold weather, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Passive sampling can provide an affordable, practical, and scalable sampling system while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from 1 February 2021-21 May 2021. Samples (n = 64) were collected 3-5 times weekly and remained within the sewer for a median duration of 24 h. SARS-CoV-2 RNA was quantified using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) targeting the N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform building-level public health responses.

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

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

Passive sampling to scale wastewater surveillance of infectious disease: Lessons learned from COVID-19

Much of what is known and theorized concerning passive sampling techniques has been developed considering chemical analytes. Yet, historically, biological analytes, such as Salmonella typhi, have been collected from wastewater via passive sampling with Moore swabs. In response to the COVID-19 pandemic, passive sampling is re-emerging as a promising technique to monitor SARS-CoV-2 RNA in wastewater. Method comparisons and disease surveillance using composite, grab, and passive sampling for SARS-CoV-2 RNA detection have found passive sampling with a variety of materials routinely produced qualitative results superior to grab samples and useful for sub-sewershed surveillance of COVID-19. Among individual studies, SARS-CoV-2 RNA concentrations derived from passive samplers demonstrated heterogeneous correlation with concentrations from paired composite samples ranging from weak (R2 = 0.27, 0.31) to moderate (R2 = 0.59) to strong (R2 = 0.76). Among passive sampler materials, electronegative membranes have shown great promise with linear uptake of SARS-CoV-2 RNA observed for exposure durations of 24 to 48 h and in several cases RNA positivity on par with composite samples. Continuing development of passive sampling methods for the surveillance of infectious diseases via diverse forms of fecal waste should focus on optimizing sampler materials for the efficient uptake and recovery of biological analytes, kit-free extraction, and resource-efficient testing methods capable of rapidly producing qualitative or quantitative data. With such refinements passive sampling could prove to be a fundamental tool for scaling wastewater surveillance of infectious disease, especially among the 1.8 billion persons living in low-resource settings served by non-traditional wastewater collection infrastructure.

Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis

Continuous surveillance of COVID-19 diffusion remains crucial to control its diffusion and to anticipate infection waves. Detecting viral RNA load in wastewater samples has been suggested as an effective approach for epidemic monitoring and the development of an effective warning system. However, its quantitative link to the epidemic status and the stages of outbreak is still elusive. Modelling is thus crucial to address these challenges. In this study, we present a novel mechanistic model-based approach to reconstruct the complete epidemic dynamics from SARS-CoV-2 viral load in wastewater. Our approach integrates noisy wastewater data and daily case numbers into a dynamical epidemiological model. As demonstrated for various regions and sampling protocols, it quantifies the case numbers, provides epidemic indicators and accurately infers future epidemic trends. Following its quantitative analysis, we also provide recommendations for wastewater data standards and for their use as warning indicators against new infection waves. In situations of reduced testing capacity, our modelling approach can enhance the surveillance of wastewater for early epidemic prediction and robust and cost-effective real-time monitoring of local COVID-19 dynamics.

Sheet, Surveillance, Strategy, Salvage and Shield in global biodefense system to protect the public health and tackle the incoming pandemics

The pandemic of COVID-19 challenges the global health system and raises our concerns on the next waves of other emerging infectious diseases. Considering the lessons from the failure of world's pandemic warning system against COVID-19, many scientists and politicians have mentioned different strategies to improve global biodefense system, among which Sheet, Surveillance, Strategy, Salvage and Shield (5S) are frequently discussed. Nevertheless, the current focus is mainly on the optimization and management of individual strategy, and there are limited attempts to combine the five strategies as an integral global biodefense system. Sheet represents the biosafety datasheet for biohazards in natural environment and human society, which helps our deeper understanding on the geographical pattern, transmission routes and infection mechanism of pathogens. Online surveillance and prognostication network is an environmental Surveillance tool for monitoring the outbreak of pandemic diseases and alarming the risks to take emergency actions, targeting aerosols, waters, soils and animals. Strategy is policies and legislations for social distancing, lockdown and personal protective equipment to block the spread of infectious diseases in communities. Clinical measures are Salvage on patients by innovating appropriate medicines and therapies. The ultimate defensive Shield is vaccine development to protect healthy crowds from infection. Fighting against COVID-19 and other emerging infectious diseases is a long rocky journey, requiring the common endeavors of scientists and politicians from all countries around the world. 5S in global biodefense system bring a ray of light to the current darkest and future road from environmental and geographical perspectives.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Quantifying the relationship between SARS-CoV-2 wastewater concentrations and building-level COVID-19 prevalence at an isolation residence using a passive sampling approach

SARS-CoV-2 RNA can be detected in the excreta of individuals with COVID-19 and has demonstrated a positive correlation with various clinical parameters. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor the community-level prevalence of infections. Over 270 higher education campuses monitor wastewater for SARS-CoV-2, with most gathering either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and challenging to manage with seasonal variability, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Prior studies have demonstrated encouraging results utilizing passive sampling swabs. Such methods can offer affordable, practical, and scalable alternatives to traditional methods while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from February 1, 2021 â€" May 21, 2021. Samples were collected several times weekly and remained within the sewer for a minimum of 24 hours (n = 64). SARS-CoV-2 RNA was quantified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) targeting the viral N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform public health responses in a range of settings.

Highlights

Daily SARS-CoV-2 RNA loads in building-level wastewater were positively associated with the total number of COVID-19 positive individuals in the residenceThe variation in individual fecal shedding rates of SARS-CoV-2 extended four orders of magnitudeWastewater sample replicates were highly correlated using distinct processing pipelines in two independent laboratoriesWhile the isolation residence was occupied, SARS-CoV-2 RNA was detected in all passive samples.

Wastewater Surveillance for SARS-CoV-2 RNA in Canada

Wastewater surveillance for SARS-CoV-2 RNA is a relatively recent adaptation of long-standing wastewater surveillance for infectious and other harmful agents. Individuals infected with COVID-19 were found to shed SARS-CoV-2 in their faeces. Researchers around the world confirmed that SARS-CoV-2 RNA fragments could be detected and quantified in community wastewater. Canadian academic researchers, largely as volunteer initiatives, reported proof-of-concept by April 2020. National collaboration was initially facilitated by the Canadian Water Network.

Many public health officials were initially skeptical about actionable information being provided by wastewater surveillance even though experience has shown that public health surveillance for a pandemic has no single, perfect approach. Rather, different approaches provide different insights, each with its own strengths and limitations. Public health science must triangulate among different forms of evidence to maximize understanding of what is happening or may be expected. Well-conceived, resourced, and implemented wastewater-based platforms can provide a cost-effective approach to support other conventional lines of evidence. Sustaining wastewater monitoring platforms for future surveillance of other disease targets and health states is a challenge. Canada can benefit from taking lessons learned from the COVID-19 pandemic to develop forward-looking interpretive frameworks and capacity to implement, adapt, and expand such public health surveillance capabilities.

The devil is in the details: emerging insights on the relevance of wastewater surveillance for SARS-CoV-2 to public health

The severe health consequences and global spread of the COVID-19 pandemic have necessitated the rapid development of surveillance programs to inform public health responses. Efforts to support surveillance capacity have included an unprecedented global research response into the use of genetic signals of SARS-CoV-2 in wastewater following the initial demonstration of the virus' detectability in wastewater in early 2020. The confirmation of fecal shedding of SARS-CoV-2 from asymptomatic, infected and recovering individuals further supports the potential for wastewater analysis to augment public health conventional surveillance techniques based on clinical testing of symptomatic individuals. We have reviewed possible capabilities projected for wastewater surveillance to support pandemic management, including independent, objective and cost-effective data generation that complements and addresses attendant limitations of clinical surveillance, early detection (i.e., prior to clinical reporting) of infection, estimation of disease prevalence, tracking of trends as possible indicators of success or failure of public health measures (mask mandates, lockdowns, vaccination, etc.), informing and engaging the public about pandemic trends, an application within sewer networks to identify infection hotspots, monitoring for presence or changes in infections from institutions (e.g., long-term care facilities, prisons, educational institutions and vulnerable industrial plants) and tracking of appearance/progression of viral variants of concern.

Averting an Outbreak of SARS-CoV-2 in a University Residence Hall through Wastewater Surveillance

A wastewater surveillance program targeting a university residence hall was implemented during the spring semester 2021 as a proactive measure to avoid an outbreak of COVID-19 on campus. Over a period of 7 weeks from early February through late March 2021, wastewater originating from the residence hall was collected as grab samples 3 times per week. During this time, there was no detection of SARS-CoV-2 by reverse transcriptase quantitative PCR (RT-qPCR) in the residence hall wastewater stream. Aiming to obtain a sample more representative of the residence hall community, a decision was made to use passive samplers beginning in late March onwards. Adopting a Moore swab approach, SARS-CoV-2 was detected in wastewater samples just 2 days after passive samplers were deployed. These samples also tested positive for the B.1.1.7 (Alpha) variant of concern (VOC) using RT-qPCR. The positive result triggered a public health case-finding response, including a mobile testing unit deployed to the residence hall the following day, with testing of nearly 200 students and staff, which identified two laboratory-confirmed cases of Alpha variant COVID-19. These individuals were relocated to a separate quarantine facility, averting an outbreak on campus. Aggregating wastewater and clinical data, the campus wastewater surveillance program has yielded the first estimates of fecal shedding rates of the Alpha VOC of SARS-CoV-2 in individuals from a nonclinical setting. IMPORTANCE Among early adopters of wastewater monitoring for SARS-CoV-2 have been colleges and universities throughout North America, many of whom are using this approach to monitor congregate living facilities for early evidence of COVID-19 infection as an integral component of campus screening programs. Yet, while there have been numerous examples where wastewater monitoring on a university campus has detected evidence for infection among community members, there are few examples where this monitoring triggered a public health response that may have averted an actual outbreak. This report details a wastewater-testing program targeting a residence hall on a university campus during spring 2021, when there was mounting concern globally over the emergence of SARS-CoV-2 variants of concern, reported to be more transmissible than the wild-type Wuhan strain. In this communication, we present a clear example of how wastewater monitoring resulted in actionable responses by university administration and public health, which averted an outbreak of COVID-19 on a university campus.

Making waves: Defining the lead time of wastewater-based epidemiology for COVID-19

Individuals infected with SARS-CoV-2, the virus that causes COVID-19, may shed the virus in stool before developing symptoms, suggesting that measurements of SARS-CoV-2 concentrations in wastewater could be a "leading indicator" of COVID-19 prevalence. Multiple studies have corroborated the leading indicator concept by showing that the correlation between wastewater measurements and COVID-19 case counts is maximized when case counts are lagged. However, the meaning of "leading indicator" will depend on the specific application of wastewater-based epidemiology, and the correlation analysis is not relevant for all applications. In fact, the quantification of a leading indicator will depend on epidemiological, biological, and health systems factors. Thus, there is no single "lead time" for wastewater-based COVID-19 monitoring. To illustrate this complexity, we enumerate three different applications of wastewater-based epidemiology for COVID-19: a qualitative "early warning" system; an independent, quantitative estimate of disease prevalence; and a quantitative alert of bursts of disease incidence. The leading indicator concept has different definitions and utility in each application.