Sewage surveillance for SARS-CoV-2: Molecular detection, quantification, and normalization factors

Hydrological and physicochemical parameters associated with SARS-CoV-2 and pepper mild mottle virus wastewater concentrations for a large-combined sewer system

During COVID-19, surveillance of SARS-CoV-2 in wastewater has been a promising tool for tracking viral infection at the community level. However, in addition to the shedding rates within the community, SARS-CoV-2 concentrations in raw wastewater are influenced by several environmental factors. This study investigated the effects of wastewater characteristics on the viral quantification of SARS-CoV-2 and pepper mild mottle virus (PMMoV) for a large wastewater system with combined sewers. Principal component analysis illustrated that water temperature negatively correlates with SARS-CoV-2 and PMMoV in wastewater, but flow rate and EC are highly correlated with SARS-CoV-2 in spring and winter. The normalization using EC enhanced the correlation with clinical data compared to normalization using pH, flow rate, and raw SARS-CoV-2. The normalization using PMMoV reduced the correlation with clinical data. Multiple linear and random forest (RF) applied to predict the concentrations of SARS-CoV-2 in wastewater, given the confirmed cases and physicochemical parameters. RF regression was the best model to predict SARS-CoV-2 in wastewater (R2=0.8), with the most important variables being the confirmed cases followed by water temperature. RF model is a potent predictor of the presence of SARS-CoV-2 in wastewater. This enhances the degree of reliability between community outbreaks and SARS-CoV-2 monitoring.

Assessment of crAssphage as a biological variable for SARS-CoV-2 data normalization in wastewater surveillance

AIMS

This study aimed to assess the use of cross-assembled phage (crAssphage) as an endogenous control employing a multivariate normalization analysis and its application as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data normalizer.

METHODS AND RESULTS

A total of 188 twelve-hour composite raw sewage samples were obtained from eight wastewater treatment plants (WWTP) during a 1-year monitoring period. Employing the N1 and N2 target regions, SARS-CoV-2 RNA was detected in 94% (177) and 90% (170) of the samples, respectively, with a global median of 5 log10 genomic copies per liter (GC l-1). CrAssphage was detected in 100% of the samples, ranging from 8.29 to 10.43 log10 GC l-1, with a median of 9.46 ± 0.40 log10 GC l-1, presenting both spatial and temporal variabilities.

CONCLUSIONS

Although SARS-CoV-2 data normalization employing crAssphage revealed a correlation with clinical cases occurring during the study period, crAssphage normalization by the flow per capita per day of each WWTP increased this correlation, corroborating the importance of normalizing wastewater surveillance data in disease trend monitoring.

Wastewater surveillance for bacterial targets: current challenges and future goals

Wastewater-based epidemiology (WBE) expanded rapidly in response to the COVID-19 pandemic. As the public health emergency has ended, researchers and practitioners are looking to shift the focus of existing wastewater surveillance programs to other targets, including bacteria. Bacterial targets may pose some unique challenges for WBE applications. To explore the current state of the field, the National Science Foundation-funded Research Coordination Network (RCN) on Wastewater Based Epidemiology for SARS-CoV-2 and Emerging Public Health Threats held a workshop in April 2023 to discuss the challenges and needs for wastewater bacterial surveillance. The targets and methods used in existing programs were diverse, with twelve different targets and nine different methods listed. Discussions during the workshop highlighted the challenges in adapting existing programs and identified research gaps in four key areas: choosing new targets, relating bacterial wastewater data to human disease incidence and prevalence, developing methods, and normalizing results. To help with these challenges and research gaps, the authors identified steps the larger community can take to improve bacteria wastewater surveillance. This includes developing data reporting standards and method optimization and validation for bacterial programs. Additionally, more work is needed to understand shedding patterns for potential bacterial targets to better relate wastewater data to human infections. Wastewater surveillance for bacteria can help provide insight into the underlying prevalence in communities, but much work is needed to establish these methods.IMPORTANCEWastewater surveillance was a useful tool to elucidate the burden and spread of SARS-CoV-2 during the pandemic. Public health officials and researchers are interested in expanding these surveillance programs to include bacterial targets, but many questions remain. The NSF-funded Research Coordination Network for Wastewater Surveillance of SARS-CoV-2 and Emerging Public Health Threats held a workshop to identify barriers and research gaps to implementing bacterial wastewater surveillance programs.

Tracing the footprints of SARS-CoV-2 in oceanic waters

The detection of SARS-CoV-2 in water environments has predominantly focused on wastewater, neglecting its presence in oceanic waters. This study aimed to fill this knowledge gap by investigating the occurrence of SARS-CoV-2 in remote sea and oceanic waters, at large distances from the coastline. Forty-three 500-liter samples were collected between May 2022 and January 2023 from the Atlantic Ocean, the Mediterranean Sea, the Arctic region, the Persian Gulf and the Red Sea. Using molecular detection methods including real-time RT-qPCR and nested PCR followed by sequencing, we successfully detected SARS-CoV-2 RNA in 7 of the 43 marine water samples (16.3 %), and specifically in samples taken from the Atlantic Ocean and the Mediterranean Sea. The estimated concentrations of SARS-CoV-2 genome copies in the positive samples ranged from 6 to 470 per 100 l. The presence of mutations characteristic of the Omicron variant was identified in these samples by amplicon sequencing. These findings provide evidence of the unforeseen presence of SARS-CoV-2 in marine waters even at distances of miles from the coastline and in open ocean waters. It is important to consider that these findings only display the occurrence of SARS-CoV-2 RNA, and further investigations are required to assess if infectious virus can be present in the marine environment.

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.

Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage (Carjivirus communis) load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.

Comparison of ordinary reverse transcription real-time polymerase chain reaction (qRT-PCR) with a newly developed one-step single-tube nested real-time RT-PCR (OSN-qRT-PCR) for sensitive detection of SARS-CoV-2 in wastewater

Wastewater monitoring has proven to be an important approach to detecting and controlling the development of the SARS-CoV-2 pandemic. Various tests based on reverse transcription real-time PCR (qRT-PCR) have been developed and used for the detection of SARS-CoV-2 in wastewater samples. In this study, we attempted to increase the sensitivity of qRT-PCR by developing a one-step single-tube nested qRT-PCR assay (OSN-qRT-PCR). Two variants were developed, oriented to nucleocapsid phosphoprotein gene (N) and to spike protein gene (S), respectively. The performance of conventional qRT-PCR assays oriented to these genes with two novel OSN-qRT-PCR assays were firstly optimized using wastewater artificially contaminated with two encapsidated RNA mimic systems harboring a portion either N or S gene (ENRM and ESRM, respectively). The assays were coupled to a polyethylene glycol-based RNA precipitation/extraction method and applied to detect SARS-CoV-2 in wastewater samples from four cities in Slovakia. Both novel OSN-qRT-PCR assays demonstrated higher detection rates than the ordinary qRT-PCR counterparts. The virus levels in the analyzed wastewater samples had a high or very high relation with the numbers of clinical cases in the monitored regions. In fact, correlation with a 3-, 4-, or 5-day temporal offset was revealed. The OSN-qRT-PCR assays demonstrated robustness, mainly in samples with low viral loads.

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.

Comparison of the methods for isolation and detection of SARS-CoV-2 RNA in municipal wastewater

Introduction

Coronavirus SARS-CoV-2 is a causative agent responsible for the current global pandemic situation known as COVID-19. Clinical manifestations of COVID-19 include a wide range of symptoms from mild (i.e., cough, fever, dyspnea) to severe pneumonia-like respiratory symptoms. SARS-CoV-2 has been demonstrated to be detectable in the stool of COVID-19 patients. Waste-based epidemiology (WBE) has been shown as a promising approach for early detection and monitoring of SARS-CoV-2 in the local population performed via collection, isolation, and detection of viral pathogens from environmental sources.

Methods

In order to select the optimal protocol for monitoring the COVID-19 epidemiological situation in region Turiec, Slovakia, we (1) compared methods for SARS-CoV-2 separation and isolation, including virus precipitation by polyethylene glycol (PEG), virus purification via ultrafiltration (Vivaspin®) and subsequent isolation by NucleoSpin RNA Virus kit (Macherey-Nagel), and direct isolation from wastewater (Zymo Environ Water RNA Kit); (2) evaluated the impact of water freezing on SARS- CoV-2 separation, isolation, and detection; (3) evaluated the role of wastewater filtration on virus stability; and (4) determined appropriate methods including reverse transcription-droplet digital PCR (RT-ddPCR) and real-time quantitative polymerase chain reaction (RT-qPCR) (targeting the same genes, i.e., RdRp and gene E) for quantitative detection of SARS-CoV-2 in wastewater samples.

Results

(1) Usage of Zymo Environ Water RNA Kit provided superior quality of isolated RNA in comparison with both ultracentrifugation and PEG precipitation. (2) Freezing of wastewater samples significantly reduces the RNA yield. (3) Filtering is counterproductive when Zymo Environ Water RNA Kit is used. (4) According to the specificity and sensitivity, the RT-ddPCR outperforms RT-qPCR.

Discussion

The results of our study suggest that WBE is a valuable early warning alert and represents a non-invasive approach to monitor viral pathogens, thus protects public health on a regional and national level. In addition, we have shown that the sensitivity of testing the samples with a nearer detection limit can be improved by selecting the appropriate combination of enrichment, isolation, and detection methods.

Tracing COVID-19 Trails in Wastewater: A Systematic Review of SARS-CoV-2 Surveillance with Viral Variants

The emergence of new variants of SARS-CoV-2 associated with varying infectivity, pathogenicity, diagnosis, and effectiveness against treatments challenged the overall management of the COVID-19 pandemic. Wastewater surveillance (WWS), i.e., monitoring COVID-19 infections in communities through detecting viruses in wastewater, was applied to track the emergence and spread of SARS-CoV-2 variants globally. However, there is a lack of comprehensive understanding of the use and effectiveness of WWS for new SARS-CoV-2 variants. Here we systematically reviewed published articles reporting monitoring of different SARS-CoV-2 variants in wastewater by following the PRISMA guidelines and provided the current state of the art of this study area. A total of 80 WWS studies were found that reported different monitoring variants of SARS-CoV-2 until November 2022. Most of these studies (66 out of the total 80, 82.5%) were conducted in Europe and North America, i.e., resource-rich countries. There was a high variation in WWS sampling strategy around the world, with composite sampling (50/66 total studies, 76%) as the primary method in resource-rich countries. In contrast, grab sampling was more common (8/14 total studies, 57%) in resource-limited countries. Among detection methods, the reverse transcriptase polymerase chain reaction (RT-PCR)-based sequencing method and quantitative RT-PCR method were commonly used for monitoring SARS-CoV-2 variants in wastewater. Among different variants, the B1.1.7 (Alpha) variant that appeared earlier in the pandemic was the most reported (48/80 total studies), followed by B.1.617.2 (Delta), B.1.351 (Beta), P.1 (Gamma), and others in wastewater. All variants reported in WWS studies followed the same pattern as the clinical reporting within the same timeline, demonstrating that WWS tracked all variants in a timely way when the variants emerged. Thus, wastewater monitoring may be utilized to identify the presence or absence of SARS-CoV-2 and follow the development and transmission of existing and emerging variants. Routine wastewater monitoring is a powerful infectious disease surveillance tool when implemented globally.

Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches

Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.

Spectrum of environmental surveillance of SARS-CoV-2 fragments: Questions, quests, and conquest

This works examines the entire spectrum of 'Environmental Surveillance (EnvSurv)' of SARS-CoV-2 fragments i.e. the questions, quests, and conquests of the technology since early year 2020. The prime focus of the present work to document the journey with achieved objectives and remaining ambitions associated with the technology. Despite the EnvSurv may be regarded as the techniques, which rather achieved more than expected, will it win the struggle for its existence or lose its way once the pandemic and fear associated with it completely fades. Pertaining to this discussions, major researched topics were investigated, followed by enlisting of ten bullets of the past experiences along with corresponding challenges, and finally key targets for the techniques are enlisted. The article targets to be a simple guide of the journey of EnvSur in terms of its effectiveness for treatment, infectivity, monitoring & estimation (TIME) till date.

From Alpha to Omicron BA.2: New digital RT-PCR approach and challenges for SARS-CoV-2 VOC monitoring and normalization of variant dynamics in wastewater

Throughout the COVID-19 pandemic, new variants have continuously emerged and spread in populations. Among these, variants of concern (VOC) have been the main culprits of successive epidemic waves, due to their transmissibility, pathogenicity or ability to escape the immune response. Quantification of the SARS-CoV-2 genomes in raw wastewater is a reliable approach well-described and widely deployed worldwide to monitor the spread of SARS-CoV-2 in human populations connected to sewage systems. Discrimination of VOCs in wastewater is also a major issue and can be achieved by genome sequencing or by detection of specific mutations suggesting the presence of VOCs. This study aimed to date the emergence of these VOCs (from Alpha to Omicron BA.2) by monitoring wastewater from the greater Paris area, France, but also to model the propagation dynamics of these VOCs and to characterize the replacement kinetics of the prevalent populations. These dynamics were compared to various individual-centered public health data, such as regional incidence and the proportions of VOCs identified by sequencing of strains isolated from patient. The viral dynamics in wastewater highlighted the impact of the vaccination strategy on the viral circulation within human populations but also suggested its potential effect on the selection of variants most likely to be propagated in immunized populations. Normalization of concentrations to capture population movements appeared statistically more reliable using variations in local drinking water consumption rather than using PMMoV concentrations because PMMoV fecal shedding was subject to variability and was not sufficiently relevant in this study. The dynamics of viral spread was observed earlier (about 13 days on the wave related to Omicron VOC) in raw wastewater than the regional incidence alerting to a possible risk of decorrelation between incidence and actual virus circulation probably resulting from a lower severity of infection in vaccinated populations.

Adsorption of SARS-CoV-2 onto granular activated carbon (GAC) in wastewater: Implications for improvements in passive sampling

Based on recent studies, passive sampling is a promising method for detecting SARS-CoV-2 in wastewater surveillance (WWS) applications. Passive sampling has many advantages over conventional sampling approaches. However, the potential benefits of passive sampling are also coupled with apparent limitations. We established a passive sampling technique for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater using electronegative filters. Though, it was evident that the adsorption capacity of the filters constrained their use. This work intends to demonstrate an optimized passive sampling technique for SARS-CoV-2 in wastewater using granular activated carbon (GAC). Through bench-scale batch-adsorption studies and sewershed deployments, we established the adsorption characteristics of SARS-CoV-2 and two human feacal viruses (PMMoV and CrAssphage) onto GAC. A pseudo-second-order model best-described adsorption kinetics for SARS-CoV-2 in either deionized (DI) water and SARS-CoV-2, CrAssphage, and PMMoV in wastewater. In both laboratory batch-adsorption experiments and in-situ sewershed deployments, the maximum amount of SARS-CoV-2 adsorbed by GAC occurred at ~60 h in wastewater. In wastewater, the maximum adsorption of PMMoV and CrAssphage by GAC occurred at ~60 h. In contrast, the adsorption capacity was reached in DI water seeded with SARS-CoV-2 after ~35 h. The equilibrium assay modeled the maximum adsorption quantity (qmax) in wastewater with spiked SARS-CoV-2 concentrations using a Hybrid Langmuir-Freundlich equation, a qmax of 2.5 × 109 GU/g was calculated. In paired sewershed deployments, it was found that GAC adsorbs SARS-CoV-2 in wastewater more effectively than electronegative filters. Based on the anticipated viral loading in wastewater, bi-weekly sampling intervals with deployments up to ~96 h are highly feasible without reaching adsorption capacity with GAC. GAC offers improved sensitivity and reproducibility to capture SARS-CoV-2 RNA in wastewater, promoting a scalable and convenient alternative for capturing viral pathogens in wastewater.

SARS-CoV-2 Monitoring in Wastewater Reveals Novel Variants and Biomarkers of Infection

Wastewater-based epidemiology (WBE) is a popular tool for the early indication of community spread of infectious diseases. WBE emerged as an effective tool during the COVID-19 pandemic and has provided meaningful information to minimize the spread of infection. Here, we present a combination of analyses using the correlation of viral gene copies with clinical cases, sequencing of wastewater-derived RNA for the viral mutants, and correlative analyses of the viral gene copies with the bacterial biomarkers. Our study provides a unique platform for potentially using the WBE-derived results to predict the spread of COVID-19 and the emergence of new variants of concern. Further, we observed a strong correlation between the presence of SARS-CoV-2 and changes in the microbial community of wastewater, particularly the significant changes in bacterial genera belonging to the families of Lachnospiraceae and Actinomycetaceae. Our study shows that microbial biomarkers could be utilized as prediction tools for future infectious disease surveillance and outbreak responses. Overall, our comprehensive analyses of viral spread, variants, and novel bacterial biomarkers will add significantly to the growing body of literature on WBE and COVID-19.