Lessons learned from SARS-CoV-2 measurements in wastewater

Wastewater Speaks: Evaluating SARS-CoV-2 Surveillance, Sampling Methods, and Seasonal Infection Trends on a University Campus

Wastewater surveillance has emerged as a cost-effective and equitable approach for tracking the spread of SARS-CoV-2. In this study, we monitored the prevalence of SARS-CoV-2 on a university campus over three years (2021-2023) using wastewater-based epidemiology (WBE). Wastewater samples were collected from 11 manholes on campus, each draining wastewater from a corresponding dormitory building, and viral RNA concentrations were measured using reverse transcription-quantitative PCR (RT-qPCR). Weekly clinical case data were also obtained from the university health center. A strong positive and significant correlation was observed between Grab and Composite sampling methods, supporting their robustness as equally effective approaches for sample collection. Specifically, a strong correlation was observed between Aggie Village 4 Grab and Aggie Village 4 Composite samples (R2 = 0.84, p = 0.00) and between Barbee Grab and Barbee Composite samples (R2 = 0.80, p = 0.00). Additionally, higher viral RNA copies of SARS-CoV-2 (N1 gene) were detected during the Spring semester compared to the Fall and Summer semesters. Notably, elevations in raw N1 concentrations were observed shortly after the return of college students to campus, suggesting that these increases were predominantly associated with students returning at the beginning of the Fall and Spring semesters (January and August). To account for variations in fecal loading, SARS-CoV-2 RNA concentrations were normalized using Pepper Mild Mottle Virus (PMMoV), a widely used viral fecal biomarker. However, normalization using PMMoV did not improve correlations between SARS-CoV-2 RNA levels and clinical case data. Despite these findings, our study did not establish WBE as a consistently reliable complement to clinical testing in a university campus setting, contrary to many retrospective studies. One key limitation was that numerous off-campus students did not contribute to the campus wastewater system corresponding to the monitored dormitories. However, some off-campus students were still subjected to clinical testing at the university health center under mandated protocols. Moreover, the university health center discontinued reporting cases per dormitory after 2021, making direct comparisons more challenging. Nevertheless, this study highlights the continued value of WBE as a surveillance tool for monitoring infectious diseases and provides critical insights into its application in campus environments.

Novel Workflows for Separate Isolation of Pathogen RNA or DNA from Wastewater: Detection by Innovative and Conventional qPCR

Wastewater-based surveillance (WBS) can provide a wealth of information regarding the health status of communities from measurements of nucleic acids found in wastewater. Processing workflows for WBS typically include sample collection, a primary concentration step, and lysis of the microbes to release nucleic acids, followed by nucleic acid purification and molecular-based quantification. This manuscript provides workflows from beginning to end with an emphasis on filtration-based concentration approaches coupled with specific lysis and nucleic acid extraction processes. Here, two WBS processing approaches are presented, one focusing on RNA-specific pathogens and the other focused on DNA-specific pathogens found within wastewater: 1) The RNA-specific approach, employed for analyzing RNA viruses like severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) couples electronegative filtration of wastewater with the placement of the filter within a lysis buffer followed by direct RNA extraction. 2) The DNA-specific approach, employed for analyzing DNA pathogens like Candida auris, uses size selection membranes during filtration, subsequently followed by a lysis buffer, bead-beating, and DNA extraction. Separate workflows for RNA versus DNA isolations have the advantage of improving the detection of the target pathogen. A novel aspect of the RNA-specific workflow is the direct extraction of nucleic acids from filter lysates, which shows enhanced recoveries, whereas the DNA-specific approach requires bead beating prior to extraction. Novelty is also provided in a new qPCR approach called Volcano 2nd Generation (V2G), which uses a polymerase capable of using RNA as a template, bypassing the reverse transcriptase step normally required for qPCR. Key features • Membrane filtration approaches for concentrating suspended solids from wastewater. After concentration, workflows are optimized for separate recovery of RNA and DNA. • Unique polymerase utilized to perform qPCR analysis, foregoing reverse transcription, for RNA. • Sample products for use with other molecular techniques (e.g., sequencing) as workflow approaches generate high-quality, concentrated nucleic acid extracts with minimal inhibitors. • Validated through COVID-19 surveillance where >1,000 samples of wastewater and >3,000 filter concentrates produced from these samples have been created and analyzed, with published results. This complete protocol was used in: J Biomol Tech (2023), DOI: 10.7171/3fc1f5fe.dfa8d906.

Optimized Aluminum Hydroxide Adsorption-Precipitation for Improved Viral Detection in Wastewater

Wastewater-based epidemiology (WBE) is a valuable tool for monitoring pathogen spread in communities; however, current protocols mainly target non-enveloped viruses. This study addresses the need for standardized methods to detect both enveloped and non-enveloped viruses by testing four aluminum hydroxide adsorption-precipitation techniques. Wastewater samples were spiked with an enveloped virus surrogate (Φ6 bacteriophage) and a non-enveloped virus surrogate (MS2 coliphage), and viral recovery was assessed using reverse-transcription quantitative PCR (RT-qPCR). The highest recovery for the enveloped virus was achieved with AlCl3 at pH 3.5, a 15 min flocculation time, and a 3% elution solution concentration. For the non-enveloped virus, optimal recovery was found with AlCl3 at pH 6.0, no flocculation time, and a 10% elution solution. The best method for recovering both virus types used AlCl3 at pH 6.0, 15 min flocculation, and a 3% elution solution concentration. This study shows that while optimal conditions vary between virus types, a standardized AlCl3 flocculation protocol can efficiently recover both, providing a cost-effective approach for outbreak monitoring in Grenada.

Wastewater Based Measures of COVID-19 and Associations with Children's Absenteeism at Grade Schools

During the COVID-19 pandemic schools closed due to concerns over disease spread resulting in lost learning opportunities. One approach for documenting disease spread includes wastewater (WW) surveillance of the virus that causes COVID-19 (Severe Acute Respiratory Syndrome Coronavirus 2, SARS-CoV-2) and other infectious pathogens. The objective of this study was to evaluate whether wastewater can be used to track children's health at grade schools in an underserved community, which was vulnerable due to limited health-based data and difficulties in implementing mitigation measures. The 18-month study was initiated during January 2022 at 9 grade schools (3 high, 2 middle, and 4 elementary schools) characterized as low income. Children's health was evaluated through absenteeism due to difficulties in attaining representative clinical diagnoses through school-based clinics. Wastewater measurements of SARS-CoV-2 were available weekly through grab sample collection and RNA extraction followed by quantification using qPCR. The average absenteeism rate was 7.1%, ranging from 4.6% to 12.5% per school. Fraction of WW samples positive for SARS-CoV-2 was 38% with SARS-Cov-2 levels ranging from detection limits (100 gc/L) to a maximum of 10.2 million gc/L. When data were aggregated across all schools, a statistically significant association was observed between weekly absenteeism rates and WW SARS-CoV-2 with a one percent increase in the loge WW SARS-CoV-2 associated with a 1.4% increase in student absence (p < 0.05). When evaluating the data by individual school, this association was strongest at schools with enclosed architecture characterized by limited natural ventilation. For schools with limited resources for clinical diagnosis of illnesses, school absenteeism coupled with wastewater-based monitoring should be utilized for assessing overall health of student populations. Strategies to maintain schools open during pandemics should include consideration of school architecture along with appropriate messaging of WW monitoring results to inform administrators and families.

Towards geospatially-resolved public-health surveillance via wastewater sequencing

Wastewater is a geospatially- and temporally-linked microbial fingerprint of a given population, making it a potentially valuable tool for tracking public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (N = 2238 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County, USA, from 2020-2022. We used targeted amplicon sequencing to track diverse SARS-CoV-2 variants across space and time, and we found a tight correspondence with positive PCR tests from University students and Miami-Dade hospital patients. Additionally, in bulk metatranscriptomic data, we demonstrate that the bacterial content of different wastewater sampling locations serving small population sizes can be used to detect putative, host-derived microorganisms that themselves have known associations with human health and diet. We also detect multiple enteric pathogens (e.g., Norovirus) and characterize viral diversity across sites. Moreover, we observed an enrichment of antimicrobial resistance genes (ARGs) in hospital wastewater; antibiotic-specific ARGs correlated to total prescriptions of those same antibiotics (e.g Ampicillin, Gentamicin). Overall, this effort lays the groundwork for systematic characterization of wastewater that can potentially influence public health decision-making.

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.

PreK-12 school and citywide wastewater monitoring of the enteric viruses astrovirus, rotavirus, and sapovirus

Wastewater monitoring is an efficient and effective way to surveil for various pathogens in communities. This is especially beneficial in areas of high transmission, such as preK-12 schools, where infections may otherwise go unreported. In this work, we apply wastewater disease surveillance using school and community wastewater from across Houston, Texas to monitor three major enteric viruses: astrovirus, sapovirus genogroup GI, and group A rotavirus. We present the results of a 10-week study that included the analysis of 164 wastewater samples for astrovirus, rotavirus, and sapovirus in 10 preK-12 schools, 6 wastewater treatment plants, and 2 lift stations using newly designed RT-ddPCR assays. We show that the RT-ddPCR assays were able to detect astrovirus, rotavirus, and sapovirus in school, lift station, and wastewater treatment plant (WWTP) wastewater, and that a positive detection of a virus in a school sample was paired with a positive detection of the same virus at a downstream lift station or wastewater treatment plant over 97 % of the time. Additionally, we show how wastewater detections of rotavirus in schools and WWTPs were significantly associated with citywide viral intestinal infections. School wastewater can play a role in the monitoring of enteric viruses and in the detection of outbreaks, potentially allowing public health officials to quickly implement mitigation strategies to prevent viral spread into surrounding communities.

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.

Using the Textual Content of Radiological Reports to Detect Emerging Diseases: A Proof-of-Concept Study of COVID-19

Changes in the content of radiological reports at population level could detect emerging diseases. Herein, we developed a method to quantify similarities in consecutive temporal groupings of radiological reports using natural language processing, and we investigated whether appearance of dissimilarities between consecutive periods correlated with the beginning of the COVID-19 pandemic in France. CT reports from 67,368 consecutive adults across 62 emergency departments throughout France between October 2019 and March 2020 were collected. Reports were vectorized using time frequency-inverse document frequency (TF-IDF) analysis on one-grams. For each successive 2-week period, we performed unsupervised clustering of the reports based on TF-IDF values and partition-around-medoids. Next, we assessed the similarities between this clustering and a clustering from two weeks before according to the average adjusted Rand index (AARI). Statistical analyses included (1) cross-correlation functions (CCFs) with the number of positive SARS-CoV-2 tests and advanced sanitary index for flu syndromes (ASI-flu, from open-source dataset), and (2) linear regressions of time series at different lags to understand the variations of AARI over time. Overall, 13,235 chest CT reports were analyzed. AARI was correlated with ASI-flu at lag = + 1, + 5, and + 6 weeks (P = 0.0454, 0.0121, and 0.0042, respectively) and with SARS-CoV-2 positive tests at lag = - 1 and 0 week (P = 0.0057 and 0.0001, respectively). In the best fit, AARI correlated with the ASI-flu with a lag of 2 weeks (P = 0.0026), SARS-CoV-2-positive tests in the same week (P < 0.0001) and their interaction (P < 0.0001) (adjusted R2 = 0.921). Thus, our method enables the automatic monitoring of changes in radiological reports and could help capturing disease emergence.

Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus

Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.

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.

Development of a computational model to inform environmental surveillance sampling plans for Salmonella enterica serovar Typhi in wastewater

Typhoid fever-an acute febrile disease caused by infection with the bacterium Salmonella enterica serotype Typhi (S. Typhi)-continues to be a leading cause of global morbidity and mortality, particularly in developing countries with limited access to safe drinking water and adequate sanitation. Environmental surveillance, the process of detecting and enumerating disease-causing agents in wastewater, is a useful tool to monitor the circulation of typhoid fever in endemic regions. The design of environmental surveillance sampling plans and the interpretation of sampling results is complicated by a high degree of uncertainty and variability in factors that affect the final measured pathogens in wastewater samples, such as pathogen travel time through a wastewater network, pathogen dilution, decay and degradation, and laboratory processing methods. Computational models can, to an extent, assist in the design of sampling plans and aid in the evaluation of how different contributing factors affect sampling results. This study presents a computational model combining dynamic and probabilistic modeling techniques to estimate-on a spatial and temporal scale-the approximate probability of detecting S. Typhi within a wastewater system. This model may be utilized to inform environmental surveillance sampling plans and may provide useful insight into selecting appropriate sampling locations and times and interpreting results. A simulated applied modeling scenario is presented to demonstrate the model's functionality for aiding an environmental surveillance study in a typhoid-endemic community.

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

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

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.

Wastewater-based Epidemiology and SARS-CoV-2: Variant Trends in the Apulia Region (Southern Italy) and Effect of Some Environmental Parameters

During the COVID-19 pandemic, wastewater monitoring has been used to monitor the levels of SARS-CoV-2 RNA entering the sewerage system. In Italy, the Istituto Superiore di Sanità coordinated the SARI project (Sorveglianza Ambientale Reflue in Italia) to detect SARS-CoV-2 and its variants. In this study, the concentration of SARS-CoV-2 and its variants in raw wastewater against COVID-19 cases was evaluated together with the effect of temperature and precipitation on virus spread. We validated a predictive model, proposed by De Giglio et al., 2021, to establish the number of COVID-19 cases/100,000 inhabitants. A receiver operating characteristic curve model was applied to predict the number of COVID-19 cases and Poisson regression was applied to study the effect of temperature and rainfall on viral load. In Apulia, from October 2021 to December 2022, we analyzed 1041 samples, of which 985 (94.6%) tested positive for SARS-CoV-2. Median atmospheric temperature was inversely proportional to viral load in wastewater; no correlation was found with precipitation. The predictive model confirmed that at least 11 cases/100,000 inhabitants would occur in the 15 days following the detection of the virus in wastewater. Environmental surveillance of SARS-CoV-2 can be used to map the virus and its variants.

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

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

SARS-CoV-2 detection and inactivation in water and wastewater: review on analytical methods, limitations and future research recommendations

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in wastewater. Wastewater-based epidemiology (WBE) is a practical and cost-effective tool for the assessment and controlling of pandemics and probably for examining SARS-CoV-2 presence. Implementation of WBE during the outbreaks is not without limitations. Temperature, suspended solids, pH, and disinfectants affect the stability of viruses in wastewater. Due to these limitations, instruments and techniques have been utilized to detect SARS-CoV-2. SARS-CoV-2 has been detected in sewage using various concentration methods and computer-aided analyzes. RT-qPCR, ddRT-PCR, multiplex PCR, RT-LAMP, and electrochemical immunosensors have been employed to detect low levels of viral contamination. Inactivation of SARS-CoV-2 is a crucial preventive measure against coronavirus disease 2019 (COVID-19). To better assess the role of wastewater as a transmission route, detection, and quantification methods need to be refined. In this paper, the latest improvements in quantification, detection, and inactivation of SARS-CoV-2 in wastewater are explained. Finally, limitations and future research recommendations are thoroughly described.

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

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

Detection of the clinically persistent, pathogenic yeast spp. Candida auris from hospital and municipal wastewater in Miami-Dade County, Florida

The use of wastewater-based surveillance (WBS) for detecting pathogens within communities has been growing since the beginning of the COVID-19 pandemic with early efforts investigating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA in wastewater. Recent efforts have shed light on the utilization of WBS for alternative targets, such as fungal pathogens, like Candida auris, in efforts to expand the technology to assess non-viral targets. The objective of this study was to extend workflows developed for SARS-CoV-2 quantification to evaluate whether C. auris can be recovered from wastewater, inclusive of effluent from a wastewater treatment plant (WWTP) and from a hospital with known numbers of patients colonized with C. auris. Measurements of C. auris in wastewater focused on culture-based methods and quantitative PCR (qPCR). Results showed that C. auris can be cultured from wastewater and that levels detected by qPCR were higher in the hospital wastewater compared to the wastewater from the WWTP, suggesting either dilution or degradation of this pathogenic yeast at downstream collection points. The results from this study illustrate that WBS can extend beyond SARS-CoV-2 monitoring to evaluate additional non-viral pathogenic targets and demonstrates that C. auris isolated from wastewater is competent to replicate in vitro using fungal-specific culture media.

Monkeypox viral nucleic acids detected using both DNA and RNA extraction workflows

Molecular methods have been used to detect human pathogens in wastewater with sampling typically performed at wastewater treatment plants (WWTP) and upstream locations within the sewer system. A wastewater-based surveillance (WBS) program was established at the University of Miami (UM) in 2020, which included measurements of SARS-CoV-2 levels in wastewater from its hospital and within the regional WWTP. In addition to the development of a SARS-CoV-2 quantitative PCR (qPCR) assay, qPCR assays to detect other human pathogens of interest were also developed at UM. Here we report on the use of a modified set of reagents published by the CDC to detect nucleic acids of Monkeypox virus (MPXV) which emerged during May of 2022 to become a concern worldwide. Samples collected from the University hospital and from the regional WWTP were processed through DNA and RNA workflows and analyzed by qPCR to detect a segment of the MPXV CrmB gene. Results show positive detections of MPXV nucleic acids in the hospital and wastewater treatment plant wastewater which coincided with clinical cases in the community and mirrored the overall trend of nationwide MPXV cases reported to the CDC. We recommend the expansion of current WBS programs' methods to detect a broader range of pathogens of concern in wastewater and present evidence that viral RNA in human cells infected by a DNA virus can be detected in wastewater.

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

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

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.

COVID-19 Case and Mortality Surveillance using Daily SARS-CoV-2 in Wastewater Samples adjusting for Meteorological Conditions and Sample pH

Background

Wastewater monitoring is increasingly used for community surveillance of infectious diseases, especially after the COVID-19 pandemic as the genomic footprints of pathogens shed by infected individuals can be traced in the environment. However, detection and concentration of pathogens in the environmental samples and their efficacy in predicting infectious diseases can be influenced by meteorological conditions and quality of samples.

Objectives

This research examines whether meteorological conditions and sample pH affect SARS-CoV-2 concentrations in wastewater samples, and whether the association of SARS-CoV-2 with COVID-19 cases and mortality improves when adjusted for meteorological conditions and sample pH value in Miami-Dade County, FL.

Methods

Daily wastewater samples were collected from Miami-Dade Wastewater Treatment Plant in Key Biscayne, Florida from August 2021 to August 2022. The samples were analyzed for pH and spiked with OC43. RNA was extracted from the concentrated wastewater sample and SARS-CoV-2 was quantified using qPCR. COVID-19 and mortality data were acquired from the Centers for Disease Control and Prevention (CDC) and meteorological data from the National Climatic Data Center. COVID-19 case and mortality rates were modelled with respect to time-lagged wastewater SARS-CoV-2 adjusting for meteorological conditions, and sample pH value and OC43 recovery.

Results

Temperature, dew point, pH values and OC43 recovery showed significant associations with wastewater SARS-CoV-2. Time-lagged wastewater SARS-CoV-2 showed significant associations with COVID-19 case and mortality incidence rates. This association improved when wastewater SARS-CoV-2 levels were adjusted for (or instrumented on) meteorological conditions, OC43 recovery, and sample pH. A 0.47% change in COVID-19 case incidence rate was associated with 1% change in wastewater SARS-CoV-2 (β ~ 0.47; 95% CI = 0.29 - 0.64; p < 0.001). A 0.12 % change in COVID-19 mortality rate was associated with 1 % change in SARS-CoV-2 in wastewater 44 days prior. A 0.07% decline in COVID-19 mortality rate was associated with a unit increase in ambient temperature 28 days prior.

Discussion

Time lagged wastewater SARS-CoV-2 (and its adjustment for sample pH and RNA recovery) and meteorological conditions can be used for the surveillance of COVID-19 case and mortality. These findings can be extrapolated to improve the surveillance of other infectious diseases by proactive measurements of infectious agent(s) in the wastewater samples, adjusting for meteorological conditions and sample pH value.

Geospatially-resolved public-health surveillance via wastewater sequencing

Wastewater, which contains everything from pathogens to pollutants, is a geospatially-and temporally-linked microbial fingerprint of a given population. As a result, it can be leveraged for monitoring multiple dimensions of public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (n=1,419 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County from 2020-2022. First, we used targeted amplicon sequencing (n=966) to track diverse SARS-CoV-2 variants across space and time, and we found a tight correspondence with clinical caseloads from University students (N = 1,503) and Miami-Dade County hospital patients (N = 3,939 patients), as well as an 8-day earlier detection of the Delta variant in wastewater vs. in patients. Additionally, in 453 metatranscriptomic samples, we demonstrate that different wastewater sampling locations have clinically and public-health-relevant microbiota that vary as a function of the size of the human population they represent. Through assembly, alignment-based, and phylogenetic approaches, we also detect multiple clinically important viruses (e.g., norovirus ) and describe geospatial and temporal variation in microbial functional genes that indicate the presence of pollutants. Moreover, we found distinct profiles of antimicrobial resistance (AMR) genes and virulence factors across campus buildings, dorms, and hospitals, with hospital wastewater containing a significant increase in AMR abundance. Overall, this effort lays the groundwork for systematic characterization of wastewater to improve public health decision making and a broad platform to detect emerging pathogens.

Surveillance of SARS-CoV-2 in sewage from buildings housing residents with different vulnerability levels

During the last three years, various restrictions have been set up to limit the transmission of the Coronavirus Disease (COVID-19). While these rules apply at a large scale (e.g., country-wide level) human-to-human transmission of the virus that causes COVID-19, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), occurs at a small scale. Different preventive policies and testing protocols were implemented in buildings where COVID-19 poses a threat (e.g., elderly residences) or constitutes a disruptive force (e.g., schools). In this study, we sampled sewage from different buildings (a school, a university campus, a university residence, and an elderly residence) that host residents of different levels of vulnerability. Our main goal was to assess the agreement between the SARS-CoV-2 concentration in wastewater and the policies applied in these buildings. All buildings were sampled using passive samplers while 24 h composite samples were also collected from the elderly residence. Results showed that passive samplers performed comparably well to composite samples while being cost-effective to keep track of COVID-19 prevalence. In the elderly residence, the comparison of sampling protocols (passive vs. active) combined with the strict clinical testing allowed us to compare the sensitivities of the two methods. Active sampling was more sensitive than passive sampling, as the former was able to detect a COVID-19 prevalence of 0.4 %, compared to a prevalence of 2.2 % for passive sampling. The number of COVID-19-positive individuals was tracked clinically in all the monitored buildings. More frequent detection of SARS-CoV-2 in wastewater was observed in residential buildings than in non-residential buildings using passive samplers. In all buildings, sewage surveillance can be used to complement COVID-19 clinical testing regimes, as the detection of SARS-CoV-2 in wastewater remained positive even when no COVID-19-positive individuals were reported. Passive sampling is useful for building managers to adapt their COVID-19 mitigation policies.

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

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

Contribution of wastewater-based epidemiology to SARS-CoV-2 screening in Brazil and the United States

Wastewater-based epidemiology (WBE) is a valuable tool for investigating the existence, prevalence, and spread of pathogens, such as SARS-CoV-2, in a given population. WBE, proposed as part of the SARS-CoV-2 surveillance strategy for monitoring virus circulation, may complement clinical data and contribute to reducing the spread of the disease through early detection. In developing countries such as Brazil, where clinical data are scarce, information obtained from wastewater monitoring can be crucial for designing public health interventions. In the United States, the country with the largest number of confirmed SARS-CoV-2 cases worldwide, WBE programs have begun to be carried out to investigate correlations with coronavirus disease 2019 (COVID-19) clinical data and support health agencies in decision-making to prevent the spread of the disease. This systematic review aimed to assess the contribution of WBE to SARS-CoV-2 screening in Brazil and the United States and compare studies conducted in a developed and developing country. Studies in Brazil and the United States showed WBE to be an important epidemiological surveillance strategy in the context of the COVID-19 pandemic. WBE approaches are useful for early detection of COVID-19 outbreaks, estimation of clinical cases, and assessment of the effectiveness of vaccination program.

Predicting COVID-19 cases using SARS-CoV-2 RNA in air, surface swab and wastewater samples

Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples, which can serve as a noninvasive method of infectious disease surveillance. The research evaluates the efficacy of environmental monitoring of SARS-CoV-2 RNA in air, surface swabs and wastewater to predict COVID-19 cases. Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory housing roughly 500 students from March to May 2021 at the University of Miami, Coral Gables, FL. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 concentration in environmental samples was quantified using Volcano 2nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and COVID-19 cases. SARS-CoV-2 was detected in air, surface swab and wastewater samples on 52 (63.4 %), 40 (50.0 %) and 57 (68.6 %) days, respectively. On 19 (24 %) of 78 days SARS-CoV-2 was detected in all three sample types. COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100 %), 9 (81.8 %) and 8 (72.7 %) days in air, surface swab and wastewater samples, respectively. SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases and a 3-day lead indicator for a potential outbreak at the dormitory building scale. Proactive environmental surveillance of SARS-CoV-2 or other pathogens in multiple environmental media has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks within communities.

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.

An overview on Monkeypox, Current Paradigms and Advances in its Vaccination, Treatment and Clinical Management: Trends, Scope, Promise and Challenges

Monkeypox virus is an orthopoxvirus sharing the common genus with variola and vaccinia virus. Most of the monkeypox (MPX) cases had been reported from the central and west African region (the main endemic areas) prior to 2022 but there was a sudden outbreak in May, 2022 disseminating the infections to thousands of people even in non-endemic countries, posing a global public health emergency. MPX was considered a rae and neglected disease, however the 2022 MPX outbreaks in multiple countries attracted attention of worldwide researchers to pace up for carrying out researches on various aspects of MPXV including attempts to design and develop diagnostics, vaccines, drugs and therapeutics counteract MPX. Apart from being a zoonotic disease, the current outbreaks highlighted rapid human-to-human transmission of MPXV, besides the reverse zoonosis has also been documented with recent first report of human-to-dog transmission, urging a call for the importance of one health approach. Atypical and unusual disease manifestations as well asymptomatic MPXV infections have also been observed during 2022 MPX outbreak. The affected patients typically develop a rash resulting in a mild disease followed by recovery with some supportive care and use of antivirals such as tecovirimat, cidofovir and brincidofovir in severe disease cases. Modified vaccinia Ankara (MVA) vaccine with an excellent safety profile has been recommended to patients with higher risk exposure and immunocompromised individuals. Moreover, another vaccine the replication-competent vaccine (ACAM2000) could be a suitable alternative to MVA’s non-availability to some selective immunocompetent individuals. Current review highlights the salient aspects of management and treatment of monkeypox along with underlying promises in terms of therapeutics and a variety of challenges posed due to current global public health emergency situation to counteract MPX.

Wastewater Surveillance of SARS-CoV-2 at a Canadian University Campus and the Impact of Wastewater Characteristics on Viral RNA Detection

Because of the increased population density, high-risk behavior of young students, and lower vaccination rates, university campuses are considered hot spots for COVID-19 transmission. This study monitored the SARS-CoV-2 RNA levels in the wastewater of a Canadian university campus for a year to provide actionable information to safely manage COVID-19 on campus. Wastewater samples were collected from the campus sewer and residence buildings to identify changes, peaks, and hotspots and search for associations with campus events, social gatherings, long weekends, and holidays. Furthermore, the impact of wastewater parameters (total solids, volatile solids, temperature, pH, turbidity, and UV absorbance) on SARS-CoV-2 detection was investigated, and the efficiency of ultrafiltration and centrifugation concentration methods were compared. RT-qPCR was used for detecting SARS-CoV-2 RNA. Wastewater signals largely correlated positively with the clinically confirmed COVID-19 cases on campus. Long weekends and holidays were often followed by increased viral signals, and the implementation of lockdowns quickly decreased the case numbers. In spite of online teaching and restricted access to campus, the university represented a microcosm of the city and mirrored the same trends. Results indicated that the centrifugation concentration method was more sensitive for wastewater with high solids content and that the ultrafiltration concentration method was more sensitive for wastewater with low solids content. Wastewater characteristics collected from the buildings and the campus sewer were different. Statistical analysis was performed to manifest the observations. Overall, wastewater surveillance provided actionable information and was also able to bring high-risk factors and events to the attention of decision-makers, enabling timely corrective measures.

Comparison of Electronegative Filtration to Magnetic Bead-Based Concentration and V2G-qPCR to RT-qPCR for Quantifying Viral SARS-CoV-2 RNA from Wastewater

Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human-coronavirus OC43. Using ENF as the concentration method, two quantitative Polymerase Chain Reaction (qPCR) analytical methods were also compared: Volcano 2nd Generation (V2G)-qPCR and reverse transcriptase (RT)-qPCR measuring three different targets of the virus responsible for the COVID-19 illness (N1, modified N3, and ORF1ab). Correlations between concentration methods were strong and statistically significant for SARS-CoV-2 (r=0.77, p<0.001) and B2M (r=0.77, p<0.001). Comparison of qPCR analytical methods indicate that, on average, each method provided equivalent results with average ratios of 0.96, 0.96 and 1.02 for N3 to N1, N3 to ORF1ab, and N1 to ORF1ab and were supported by significant (p<0.001) correlation coefficients (r =0.67 for V2G (N3) to RT (N1), r =0.74 for V2G (N3) to RT (ORF1ab), r = 0.81 for RT (N1) to RT (ORF1ab)). Overall results suggest that the two concentration methods and qPCR methods provide equivalent results, although variability is observed for individual measurements. Given the equivalency of results, additional advantages and disadvantages, as described in the discussion, are to be considered when choosing an appropriate method.

Relationships between SARS-CoV-2 in Wastewater and COVID-19 Clinical Cases and Hospitalizations, with and without Normalization against Indicators of Human Waste

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry (r s = 0.69 without normalization, r s = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets.

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.

Coordination of SARS-CoV-2 wastewater and clinical testing of university students demonstrates the importance of sampling duration and collection time

Wastewater surveillance has been a useful tool complementing clinical testing during the COVID-19 pandemic. However, transitioning surveillance approaches to small populations, such as dormitories and assisted living facilities poses challenges including difficulties with sample collection and processing. Recently, the need for reliable and timely data has coincided with the need for precise local forecasting of the trajectory of COVID-19. This study compared wastewater and clinical data from the University of Delaware (Fall 2020 and Spring 2021 semesters), and evaluated wastewater collection practices for enhanced virus detection sensitivity. Fecal shedding of SARS-CoV-2 is known to occur in infected individuals. However, shedding concentrations and duration has been shown to vary. Therefore, three shedding periods (14, 21, and 30 days) were presumed and included for analysis of wastewater data. SARS-CoV-2 levels detected in wastewater correlated with clinical virus detection when a positive clinical test result was preceded by fecal shedding of 21 days (p< 0.05) and 30 days (p < 0.05), but not with new cases (p = 0.09) or 14 days of shedding (p = 0.17). Discretely collected wastewater samples were compared with 24-hour composite samples collected at the same site. The discrete samples (n = 99) were composited examining the influence of sampling duration and time of day on SARS-CoV-2 detection. SARS-CoV-2 detection varied among dormitory complexes and sampling durations of 3-hour, 12-hour, and 24-hour (controls). Collection times frequently showing high detection values were between the hours of 03:00 to 05:00 and 23:00 to 08:00. In each of these times of day 33% of samples (3/9) were significantly higher (p < 0.05) than the control sample. The remainder (6/9) of the collection times (3-hour and 12-hour) were not different (p > 0.05) from the control. This study provides additional framework for continued methodology development for microbiological wastewater surveillance as the COVID-19 pandemic progresses and in preparation for future epidemiological efforts.

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.

COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples

Importance

Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples. Analysis of these samples can be employed for noninvasive surveillance of infectious diseases.

Objective

To evaluate the efficacy of environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for predicting COVID-19 cases in a college dormitory.

Design

Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory from March to May 2021. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 in environmental samples was concentrated with electronegative filtration and quantified using Volcano 2 nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and clinically diagnosed COVID-19 cases.

Setting

This study was conducted in a residential dormitory at the University of Miami, Coral Gables campus, FL, USA. The dormitory housed about 500 students.

Participants

Students from the dormitory were randomly screened, for COVID-19 for 2-3 days / week while entering or exiting the dormitory.

Main Outcome

Clinically diagnosed COVID-19 cases were of our main interest. We hypothesized that SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases in the dormitory, and SARS-CoV-2 can be detected in the environmental samples several days prior to the clinical diagnosis of COVID-19 cases.

Results

SARS-CoV-2 genomic footprints were detected in air, surface swab and wastewater samples on 52 (63.4%), 40 (50.0%) and 57 (68.6%) days, respectively, during the study period. On 19 (24%) of 78 days SARS-CoV-2 was detected in all three sample types. Clinically diagnosed COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100%), 9 (81.8%) and 8 (72.7%) days in air, surface swab and wastewater samples, respectively.

Conclusion

Proactive environmental surveillance of SARS-CoV-2 or other pathogens in a community/public setting has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks.

Key Points

Question: How effective is environmental surveillance of SARS-CoV-2 in public places for early detection of COVID-19 cases in a community?Findings: All clinically confirmed COVID-19 cases were predicted with the aid of 2 day lagged SARS-CoV-2 in environmental samples in a college dormitory. However, the prediction efficiency varied by sample type: best prediction by air samples, followed by wastewater and surface swab samples. SARS-CoV-2 was also detected in these samples even on days without any reported cases of COVID-19, suggesting underreporting of COVID-19 cases.Meaning: SARS-CoV-2 can be detected in environmental samples several days prior to clinical reporting of COVID-19 cases. Thus, proactive environmental surveillance of microbiome in public places can serve as a mean for early detection of location-time specific outbreaks of infectious diseases. It can also be used for underreporting of infectious diseases.

Unlocking capacities of genomics for the COVID-19 response and future pandemics

During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.

Efficacy of SARS-CoV-2 wastewater surveillance for detection of COVID-19 at a residential private college

Many colleges and universities utilized wastewater surveillance testing for SARS-CoV-2 RNA as a tool to help monitor and mitigate the COVID-19 pandemic on campuses across the USA during the 2020-2021 academic year. We sought to assess the efficacy of one such program by analyzing data on relative wastewater RNA levels from residential buildings in relation to SARS-CoV-2 cases identified through individual surveillance testing, conducted largely independent of wastewater results. Almost 80% of the cases on campus were associated with positive wastewater tests, resulting in an overall positive predictive value of 79% (Chi square 48.1, Df = 1, P < 0.001). However, half of the positive wastewater samples occurred in the two weeks following the return of a student to the residence hall following the 10-day isolation period, and therefore were not useful in predicting new infections. When these samples were excluded, the positive predictive value of a positive wastewater sample was 54%. Overall, we conclude that the continued shedding of viral RNA by patients past the time of potential transmission confounds the identification of new cases using wastewater surveillance, and decreases its effectiveness in managing SARS-CoV-2 infections on a residential college campus.

Potentialities of a mesoporous activated carbon as virus detection probe in aquatic systems

Enteric viruses are widely spread in water environments, some being harmful for human communities. Regular epidemics highlight the usefulness of analysing such viruses in wastewaters as a tool for epidemiologists to monitor the extent of their dissemination among populations. In this context, CNovel™ Powdered Activated Carbon (PAC) was chosen for its high porosity and high adsorption capacity to investigate sorbent ability to be used as part of of virus detection probes. Self-supported PAC Foils (PAC-F), PAC coated Brushes (PAC-B) and PAC Sampler (PAC-S) were used to prospect PAC efficacy in virus adsorption and above all, the feasibility of virus retrieval from them, allowing to further analysis such as molecular analysis quantification. Aiming at the development of a field-operational tool, PAC saturation and reusability were also investigated, as well as PAC-polarisation effect on its adsorption capacity. Our results pointed out that sorbent-based probes exhibited a high adsorption efficacy of spiked Murine Norovirus (MNV-1) in bare 0.1 M NaCl solution (>90 % for PAC-B and >86 % for PAC-F at ≈10⁷ genome unit virus concentration), with no saturation within our experimental framework. On the other hand, polarisation assays using PAC-F as electrode, did not demonstrate any adsorption improvement. Experiments on PAC probes reusability suggested that they should be used three times at the most for a maximum efficiency. Values of virus retrieval were low (up to 11 % with PAC-B and up to 14 % with PAC-F in 0.1 M NaCl virus suspensions), illustrating the need for the techniques to be improved. A preliminary field assay using PAC-S, demonstrated that our catch-and-retrieve protocol yielded to the detection of autochthonous human Norovirus Genogroup I (NoV GI) and Adenovirus (AdV), in wastewaters suggesting its promising application as virus detection tool in such high loaded and complex waters.

Inferring SARS-CoV-2 RNA shedding into wastewater relative to the time of infection

Since the start of the coronavirus disease-2019 (COVID-19) pandemic, there has been interest in using wastewater monitoring as an approach for disease surveillance. A significant uncertainty that would improve the interpretation of wastewater monitoring data is the intensity and timing with which individuals shed RNA from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into wastewater. By combining wastewater and case surveillance data sets from a university campus during a period of heightened surveillance, we inferred that individual shedding of RNA into wastewater peaks on average 6 days (50% uncertainty interval (UI): 6-7; 95% UI: 4-8) following infection, and that wastewater measurements are highly overdispersed [negative binomial dispersion parameter, k = 0.39 (95% credible interval: 0.32-0.48)]. This limits the utility of wastewater surveillance as a leading indicator of secular trends in SARS-CoV-2 transmission during an epidemic, and implies that it could be most useful as an early warning of rising transmission in areas where transmission is low or clinical testing is delayed or of limited capacity.

Inferring SARS-CoV-2 RNA shedding into wastewater relative to the time of infection

Since the start of the coronavirus disease-2019 (COVID-19) pandemic, there has been interest in using wastewater monitoring as an approach for disease surveillance. A significant uncertainty that would improve the interpretation of wastewater monitoring data is the intensity and timing with which individuals shed RNA from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into wastewater. By combining wastewater and case surveillance data sets from a university campus during a period of heightened surveillance, we inferred that individual shedding of RNA into wastewater peaks on average 6 days (50% uncertainty interval (UI): 6-7; 95% UI: 4-8) following infection, and that wastewater measurements are highly overdispersed [negative binomial dispersion parameter, k = 0.39 (95% credible interval: 0.32-0.48)]. This limits the utility of wastewater surveillance as a leading indicator of secular trends in SARS-CoV-2 transmission during an epidemic, and implies that it could be most useful as an early warning of rising transmission in areas where transmission is low or clinical testing is delayed or of limited capacity.

Inferring SARS-CoV-2 RNA shedding into wastewater relative to the time of infection

Since the start of the coronavirus disease-2019 (COVID-19) pandemic, there has been interest in using wastewater monitoring as an approach for disease surveillance. A significant uncertainty that would improve the interpretation of wastewater monitoring data is the intensity and timing with which individuals shed RNA from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into wastewater. By combining wastewater and case surveillance data sets from a university campus during a period of heightened surveillance, we inferred that individual shedding of RNA into wastewater peaks on average 6 days (50% uncertainty interval (UI): 6-7; 95% UI: 4-8) following infection, and that wastewater measurements are highly overdispersed [negative binomial dispersion parameter, k = 0.39 (95% credible interval: 0.32-0.48)]. This limits the utility of wastewater surveillance as a leading indicator of secular trends in SARS-CoV-2 transmission during an epidemic, and implies that it could be most useful as an early warning of rising transmission in areas where transmission is low or clinical testing is delayed or of limited capacity.

A Rapid, Isothermal, and Point-of-Care System for COVID-19 Diagnostics

The COVID-19 pandemic has had a profound, detrimental effect on economies and societies worldwide. Where the pandemic has been controlled, extremely high rates of diagnostic testing for the SARS-CoV-2 virus have proven critical, enabling isolation of cases and contact tracing. Recently, diagnostic testing has been supplemented with wastewater measures to evaluate the degree to which communities have infections. Whereas much testing has been done through traditional, centralized, clinical, or environmental laboratory methods, point-of-care testing has proven successful in reducing time to result. As the pandemic progresses and becomes more broadly distributed, further decentralization of diagnostic testing will be helpful to mitigate its spread. This will be particularly both challenging and critical in settings with limited resources due to lack of medical infrastructure and expertise as well as requirements to return results quickly. In this article, we validate the tiny isothermal nucleic acid quantification system (TINY) and a novel loop-mediated isothermal amplification (LAMP)-based assay for the point-of-care diagnosis of SARS-CoV-2 infection in humans and also for in-the-field, point-of-collection surveillance of wastewater. The TINY system is portable and designed for use in settings with limited resources. It can be powered by electrical, solar, or thermal energy and is robust against interruptions in services. These applied testing examples demonstrate that this novel detection platform is a simpler procedure than reverse-transcription quantitative polymerase chain reaction, and moreover, this TINY instrument and LAMP assay combination has the potential to effectively provide both point-of-care diagnosis of individuals and point-of-collection environmental surveillance using wastewater.