SARS-CoV-2 RNA and N Antigen Quantification via Wastewater at the Campus Level, Building Cluster Level, and Individual-Building Level

COVID-19 trends at the University of Tennessee: predictive insights from raw sewage SARS-CoV-2 detection and evaluation and PMMoV as an indicator for human waste

Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring the prevalence of SARS-CoV-2 on university campuses. However, concerns about effectiveness of raw sewage as a COVID-19 early warning system still exist, and it's not clear how useful normalization by simultaneous comparison of Pepper Mild Mottle Virus (PMMoV) is in addressing variations resulting from fecal discharge dilution. This study aims to contribute insights into these aspects by conducting an academic-year field trial at the student residences on the University of Tennessee, Knoxville campus, raw sewage. This was done to investigate the correlations between SARS-CoV-2 RNA load, both with and without PMMoV normalization, and various parameters, including active COVID-19 cases, self-isolations, and their combination among all student residents. Significant positive correlations between SARS-CoV-2 RNA load a week prior, during the monitoring week, and the subsequent week with active cases. Despite these correlations, normalization by PMMoV does not enhance these associations. These findings suggest the potential utility of SARS-CoV-2 RNA load as an early warning indicator and provide valuable insights into the application and limitations of WBE for COVID-19 surveillance specifically within the context of raw sewage on university campuses.

AH, Fernandez S, Huang AT, Vatanaprasan P, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Ngamwongsatit N, Badavath VN, Thuptimdang W, Leelahavanichkul A, Kanjanabuch T, Miyanaga K, Cui L, Nanbo A, Shibuya K, Kupwiwat R, Sano D, Furukawa T, Sei K, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, Ishikawa H, Amarasiri M, Modchang C, Wannigama DL. Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission

This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place.

Beyond linear regression: Modeling COVID-19 clinical cases with wastewater surveillance of SARS-CoV-2 for the city of Athens and Ohio University campus

Wastewater-based surveillance has emerged as a detection tool for population-wide infectious diseases, including coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals shed the virus, which can be detected in wastewater using molecular techniques such as reverse transcription-digital polymerase chain reaction (RT-dPCR). This study examined the association between the number of clinical cases and the concentration of SARS-CoV-2 in wastewater beyond linear regression and for various normalizations of viral loads. Viral loads were measured in a total of 446 wastewater samples during the period from August 2021 to April 2022. These samples were collected from nine different locations, with 220 samples taken from four specific sites within the city of Athens and 226 samples from five sites within Ohio University. The correlation between COVID-19 cases and wastewater viral concentrations, which was estimated using the Pearson correlation coefficient, was statistically significant and ranged from 0.6 to 0.9. In addition, time-lagged cross correlation was applied to identify the lag time between clinical and wastewater data, estimated 4 to 7 days. While we also explored the effect on the correlation coefficients of various normalizations of viral loads accounting for procedural loss or amount of fecal material and of estimated lag times, these alternative specifications did not change our substantive conclusions. Additionally, several linear and non-linear regression models were applied to predict the COVID-19 cases given wastewater data as input. The non-linear approach was found to yield the highest R-squared and Pearson correlation and lowest Mean Absolute Error values between the predicted and actual number of COVID-19 cases for both aggregated OHIO Campus and city data. Our results provide support for previous studies on correlation and time lag and new evidence that non-linear models, approximated with artificial neural networks, should be implemented for WBS of contagious diseases.

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.

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.

Analyzing community wastewater in sub-sewersheds for the small-scale detection of SARS-CoV-2 variants in a German metropolitan area

Wastewater surveillance of SARS-CoV-2 proved useful, including for identifying the local appearance of newly identified virus variants. Previous studies focused on wastewater treatment plants (WWTP) with sewersheds of several hundred thousand people or at single building level, representing only a small number of people. Both approaches may prove inadequate for small-scale intra-urban inferences for early detection of emerging or novel virus variants. Our study aims (i) to analyze SARS-CoV-2 single nucleotide variants (SNVs) in wastewater of sub-sewersheds and WWTP using whole genome sequencing in order to (ii) investigate the potential of small-scale detection of novel known SARS-CoV-2 variants of concern (VOC) within a metropolitan wastewater system. We selected three sub-sewershed sampling sites, based on estimated population- and built environment-related indicators, and the inlet of the receiving WWTP in the Ruhr region, Germany. Untreated wastewater was sampled weekly between October and December 2021, with a total of 22 samples collected. SARS-CoV-2 RNA was analyzed by RT-qPCR and whole genome sequencing. For all samples, genome sequences were obtained, while only 13 samples were positive for RT-qPCR. We identified multiple specific SARS-CoV-2 SNVs in the wastewater samples of the sub-sewersheds and the WWTP. Identified SNVs reflected the dominance of VOC Delta at the time of sampling. Interestingly, we could identify an Omicron-specific SNV in one sub-sewershed. A concurrent wastewater study sampling the same WWTP detected the VOC Omicron one week later. Our observations suggest that the small-scale approach may prove particularly useful for the detection and description of spatially confined emerging or existing virus variants circulating in populations. Future studies applying small-scale sampling strategies taking into account the specific features of the wastewater system will be useful to analyze temporal and spatial variance in more detail.

Detection of SARS-CoV-2 RNA in wastewater from dormitory buildings in a university campus: comparison with individual testing results

Wastewater-based epidemiology (WBE) for monitoring COVID-19 has been largely used to detect the spread of the disease at the community level. From February to December 2022, we collected 24-h composite sewage samples from dormitory buildings in George Mason University (Fairfax, Virginia, USA) housing approximately 5,200 resident students. SARS-CoV-2 RNA extraction was achieved using an automated system based on magnetic nanoparticles. Analysis of SARS-CoV-2 RNA was performed using reverse transcription quantitative PCR based on the Centers for Disease Control and Prevention (CDC) N1 and N2 assays. From the 362 samples collected, 86% showed positive detection of SARS-CoV-2 RNA. Wastewater monitoring was able to detect SARS-CoV-2 RNA in 96% of the samples from buildings housing students with COVID-19. Over the period of study, we observed significant correlations between the SARS-CoV-2 concentration (copy number mL-1) in wastewater and the number of positive cases on campus based on individual saliva testing. Although several reports have been published on the wastewater monitoring of COVID-19 in university campuses, our study is one of the very few that provides results that were obtained during the last phase of the pandemic (roughly the year 2022), when the large majority of students were vaccinated and back on campus.

Monitoring COVID-19 spread in selected Prague's schools based on the presence of SARS-CoV-2 RNA in wastewater

The COVID-19 pandemic has demanded a broad range of techniques to better monitor its extent. Owing to its consistency, non-invasiveness, and cost effectiveness, wastewater-based epidemiology has emerged as a relevant approach to monitor the pandemic's course. In this work, we analyzed the extent of the COVID-19 pandemic in five primary schools in Prague, the Czech Republic, and how different preventive measures impact the presence of SARS-CoV-2 RNA copy numbers in wastewaters. Copy numbers were measured by reverse transcription-multiplex quantitative real-time PCR. These copy numbers were compared to the number of infected individuals in each school identified through regular clinical tests. Each school had a different monitoring regime and subsequent application of preventive measures to thwart the spread of COVID-19. The schools that constantly identified and swiftly quarantined infected individuals exhibited persistently low amounts of SARS-CoV-2 RNA copies in their wastewaters. In one school, a consistent monitoring of infected individuals, coupled with a delayed action to quarantine, allowed for the estimation of a linear model to predict the number of infected individuals based on the presence of SARS-CoV-2 RNA in the wastewater. The results show the importance of case detection and quarantining to stop the spread of the pandemic and its impact on the presence of SARS-CoV-2 RNA in wastewaters. This work also shows that wastewater-based epidemiological models can be reliably used even in small water catchments, but difficulties arise to fit models due to the nonconstant input of viral particles into the wastewater systems.

Wastewater monitoring of SARS-CoV-2 RNA at K-12 schools: comparison to pooled clinical testing data

Background

Wastewater measurements of SARS-CoV-2 RNA have been extensively used to supplement clinical data on COVID-19. Most examples in the literature that describe wastewater monitoring for SARS-CoV-2 RNA use samples from wastewater treatment plants and individual buildings that serve as the primary residence of community members. However, wastewater surveillance can be an attractive supplement to clinical testing in K-12 schools where individuals only spend a portion of their time but interact with others in close proximity, increasing risk of potential transmission of disease.

Methods

Wastewater samples were collected from two K-12 schools in California and divided into solid and liquid fractions to be processed for detection of SARS-CoV-2. The resulting detection rate in each wastewater fraction was compared to each other and the detection rate in pooled clinical specimens.

Results

Most wastewater samples were positive for SARS-CoV-2 RNA when clinical testing was positive (75% for solid samples and 100% for liquid samples). Wastewater samples continued to test positive for SARS-CoV-2 RNA when clinical testing was negative or in absence of clinical testing (83% for both solid and liquid samples), indicating presence of infected individuals in the schools. Wastewater solids had a higher concentration of SARS-CoV-2 than wastewater liquids on an equivalent mass basis by three orders of magnitude.

Wastewater surveillance of SARS-CoV-2 and chemical markers in campus dormitories in an evolving COVID - 19 pandemic

In this study, we report the implementation of a comprehensive wastewater surveillance testing program at a university campus in Singapore to identify Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected individuals and the usage of pharmaceuticals and personal care products (PPCPs) as well as other emerging contaminants (ECs). This unique co-monitoring program simultaneously measured SARS-CoV-2 with chemical markers/contaminants as the COVID-19 situation evolved from pandemic to endemic stages, following a nationwide mass vaccination drive. SARS-CoV-2 RNA concentrations in wastewater from campus dormitories were measured using real-time reverse transcription-polymerase chain reaction (RT-qPCR) and corroborated with the number of symptomatic COVID-19 cases confirmed with the antigen rapid test (ART). Consistent results were observed where the concentrations of SARS-CoV-2 RNA detected in wastewater increased proportionately with the number of COVID-19 infected individuals residing on campus. Similarly, a wide range of ECs, including disinfectants and antibiotics, were detected through sensitive liquid chromatography with tandem mass spectrometry (LC-MS/MS) techniques to establish PPCPs consumption patterns during various stages of the COVID-19 pandemic in Singapore. Statistical correlation of SARS-CoV-2 RNA was observed with few ECs belonging to disinfectants, PCPs and antibiotics. A high concentration of disinfectants and subsequent positive correlation with the number of reported cases on the university campus indicates that disinfectants could serve as a chemical marker during such unprecedented times.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Contextualizing Wastewater-Based surveillance in the COVID-19 vaccination era

SARS-CoV-2 wastewater-based surveillance (WBS) offers a tool for cost-effective oversight of a population's infections. In the past two years, WBS has proven to be crucial for managing the pandemic across different geographical regions. However, the changing context of the pandemic due to high levels of COVID-19 vaccination warrants a closer examination of its implication towards SARS-CoV-2 WBS. Two main questions were raised: 1) Does vaccination cause shedding of viral signatures without infection? 2) Does vaccination affect the relationship between wastewater and clinical data? To answer, we review historical reports of shedding from viral vaccines in use prior to the COVID-19 pandemic including for polio, rotavirus, influenza and measles infection and provide a perspective on the implications of different COVID-19 vaccination strategies with regard to the potential shedding of viral signatures into the sewershed. Additionally, we reviewed studies that looked into the relationship between wastewater and clinical data and how vaccination campaigns could have affected the relationship. Finally, analyzing wastewater and clinical data from the Netherlands, we observed changes in the relationship concomitant with increasing vaccination coverage and switches in dominant variants of concern. First, that no vaccine-derived shedding is expected from the current commercial pipeline of COVID-19 vaccines that may confound interpretation of WBS data. Secondly, that breakthrough infections from vaccinated individuals contribute significantly to wastewater signals and must be interpreted in light of the changing dynamics of shedding from new variants of concern.