Methods Evaluation for Rapid Concentration and Quantification of SARS-CoV-2 in Raw Wastewater Using Droplet Digital and Quantitative RT-PCR

State-space modelling using wastewater virus and epidemiological data to estimate reported COVID-19 cases and the potential infection numbers

The current situation of COVID-19 measures makes it difficult to accurately assess the prevalence of SARS-CoV-2 due to a decrease in reporting rates, leading to missed initial transmission events and subsequent outbreaks. There is growing recognition that wastewater virus data assist in estimating potential infections, including asymptomatic and unreported infections. Understanding the COVID-19 situation hidden behind the reported cases is critical for decision-making when choosing appropriate social intervention measures. However, current models implicitly assume homogeneity in human behaviour, such as virus shedding patterns within the population, making it challenging to predict the emergence of new variants due to variant-specific transmission or shedding parameters. This can result in predictions with considerable uncertainty. In this study, we established a state-space model based on wastewater viral load to predict both reported cases and potential infection numbers. Our model using wastewater virus data showed high goodness-of-fit to COVID-19 case numbers despite the dataset including waves of two distinct variants. Furthermore, the model successfully provided estimates of potential infection, reflecting the superspreading nature of SARS-CoV-2 transmission. This study supports the notion that wastewater surveillance and state-space modelling have the potential to effectively predict both reported cases and potential infections.

Digital PCR in Virology: Current Applications and Future Perspectives

Digital PCR (dPCR) has been used in the field of virology since its inception. Technological innovations in microfluidics more than a decade ago caused a sharp increase in its use. There is an emerging consensus that dPCR now outperforms quantitative PCR (qPCR) in the basic parameters such as precision, sensitivity, accuracy, repeatability and resistance to inhibitors. These strengths have led to several current applications in quantification, mutation detection and environmental DNA and RNA samples. In high throughput scenarios, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the cost and throughput still significantly hampered the adaption of dPCR. There is much unexplored potential within the multiplexing capabilities of dPCR. This will allow simultaneous multi-target quantification and can also partially alleviate the throughput and cost drawback. In this review, we discuss the strengths and weaknesses of dPCR with a focus on virology applications and we discuss future applications. Finally, we discuss recent evolutions of the technology in the form of real-time dPCR and digital high-resolution melting.

Development of a Large-Volume Concentration Method to Recover Infectious Avian Influenza Virus from the Aquatic Environment

Since late 2021, outbreaks of highly pathogenic avian influenza virus have caused a record number of mortalities in wild birds, domestic poultry, and mammals in North America. Wetlands are plausible environmental reservoirs of avian influenza virus; however, the transmission and persistence of the virus in the aquatic environment are poorly understood. To explore environmental contamination with the avian influenza virus, a large-volume concentration method for detecting infectious avian influenza virus in waterbodies was developed. A variety of filtering, elution, and concentration methods were explored, in addition to testing filtering speeds using artificially amended 20 L water matrices (deionized water with sterile dust, autoclaved wetland water, and wetland water). The optimal protocol was dead-end ultrafiltration coupled with salt solution elution and centrifugation concentration. Using this method, infectious virus was recovered at 1 × 10-1 50% egg infectious dose per milliliter (EID50/mL), whereas viral RNA was detected inconsistently down to 1 × 100 EID50/mL. This method will aid in furthering our understanding of the avian influenza virus in the environment and may be applicable to the environmental detection of other enveloped viruses.

Wastewater-based epidemiology for COVID-19 surveillance and beyond: A survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

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

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

Detection of SARS-CoV-2 in wastewater as an earlier predictor of COVID-19 epidemic peaks in Venezuela

Wastewater-based epidemiological surveillance has proven to be a useful and cost-effective tool for detecting COVID-19 outbreaks. Here, our objective was to evaluate its potential as an early warning system in Venezuela by detecting SARS-CoV-2 RNA in wastewater and its correlation with reported cases of COVID-19. Viral RNA was concentrated from wastewater collected at various sites in Caracas (northern Venezuela), from September 2021 to July 2023, using the polyethylene glycol (PEG) precipitation method. Viral quantification was performed by RT-qPCR targeting the N1 and ORF1ab genes. A significant association (p < 0.05) was found between viral load in wastewater and reported cases of COVID-19 up to six days after sampling. During the whole study, two populated areas of the city were persistent hotspots of viral infection. The L452R mutation, suggestive of the presence of the Delta variant, was identified in the only sample where a complete genomic sequence could be obtained. Significant differences (p < 0.05) between the physicochemical conditions of the wastewater samples positive and negative for the virus were found. Our results support proof of concept that wastewater surveillance can serve as an early warning system for SARS-CoV-2 outbreaks, complementing public health surveillance in those regions where COVID-19 is currently underreported.

A Narrative Review of High Throughput Wastewater Sample Processing for Infectious Disease Surveillance: Challenges, Progress, and Future Opportunities

During the recent COVID-19 pandemic, wastewater-based epidemiological (WBE) surveillance played a crucial role in evaluating infection rates, analyzing variants, and identifying hot spots in a community. This expanded the possibilities for using wastewater to monitor the prevalence of infectious diseases. The full potential of WBE remains hindered by several factors, such as a lack of information on the survival of pathogens in sewage, heterogenicity of wastewater matrices, inconsistent sampling practices, lack of standard test methods, and variable sensitivity of analytical techniques. In this study, we review the aforementioned challenges, cost implications, process automation, and prospects of WBE for full-fledged wastewater-based community health screening. A comprehensive literature survey was conducted using relevant keywords, and peer reviewed articles pertinent to our research focus were selected for this review with the aim of serving as a reference for research related to wastewater monitoring for early epidemic detection.

Wastewater-based Epidemiology for COVID-19 Surveillance and Beyond: A Survey

The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding wastewater-based epidemiology for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.

Assessing infectivity of emerging enveloped viruses in wastewater and sewage sludge: Relevance and procedures

The emergence of SARS-CoV-2 has heightened the need to evaluate the detection of enveloped viruses in the environment, particularly in wastewater, within the context of wastewater-based epidemiology. The studies published over the past 80 years focused primarily on non-enveloped viruses due to their ability to survive longer in environmental matrices such as wastewater or sludge compared to enveloped viruses. However, different enveloped viruses survive in the environment for different lengths of time. Therefore, it is crucial to be prepared to assess the potential infectious risk that may arise from future emerging enveloped viruses. This will require appropriate tools, notably suitable viral concentration methods that do not compromise virus infectivity. This review has a dual purpose: first, to gather all the available literature on the survival of infectious enveloped viruses, specifically at different pH and temperature conditions, and in contact with detergents; second, to select suitable concentration methods for evaluating the infectivity of these viruses in wastewater and sludge. The methodology used in this data collection review followed the systematic approach outlined in the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Concentration methods cited in the data gathered are more tailored towards detecting the enveloped viruses' genome. There is a lack of suitable methods for detecting infectious enveloped viruses in wastewater and sludge. Ultrafiltration, ultracentrifugation, and polyethylene glycol precipitation methods, under specific/defined conditions, appear to be relevant approaches. Further studies are necessary to validate reliable concentration methods for detecting infectious enveloped viruses. The choice of culture system is also crucial for detection sensitivity. The data also show that the survival of infectious enveloped viruses, though lower than that of non-enveloped ones, may enable environmental transmission. Experimental data on a wide range of enveloped viruses is required due to the variability in virus persistence in the environment.

Evaluation of an Automated Ultrafiltration System for Concentrating a Range of Viruses from Saline Waters

Pathogenic viruses in environmental water are usually present in levels too low for direct detection and thus, a concentration step is often required to increase the analytical sensitivity. The objective of this study was to evaluate an automated filtration device, the Innovaprep Concentrating Pipette Select (CP Select) for the rapid concentration of viruses in saline water samples, while considering duration of process and ease of use. Four bacteriophages (MS2, P22, Phi6, and PhiX174) and three animal viruses (adenovirus, coronavirus OC43, and canine distemper virus) were seeded in artificial seawater, aquarium water, and bay water samples, and processed using the CP Select. The recovery efficiencies of viruses were determined either using a plaque assay or droplet digital PCR (ddPCR). Using plaque assays, the average recovery efficiencies for bacteriophages ranged from 4.84 ± 3.8% to 82.73 ± 27.3%, with highest recovery for P22 phage. The average recovery efficiencies for the CP Select were 39.31 ± 26.6% for adenovirus, 19.04 ± 11.6% for coronavirus OC43, and 19.84 ± 13.6% for canine distemper virus, as determined by ddPCR. Overall, viral genome composition, not the size of the virus, affected the recovery efficiencies for the CP Select. The small sample volume size used for the ultrafilter pipette of the system hinders the use of this method as a primary concentration step for viruses in marine waters. However, the ease of use and rapid processing time of the CP Select are especially beneficial when rapid detection of viruses in highly contaminated water, such as wastewater or sewage-polluted surface water, is needed.

Wastewater Surveillance of SARS-CoV-2: A Comparison of Two Concentration Methods

Wastewater surveillance is crucial for the epidemiological monitoring of SARS-CoV-2. Various concentration techniques, such as skimmed milk flocculation (SMF) and polyethylene glycol (PEG) precipitation, are employed to isolate the virus effectively. This study aims to compare these two methods and determine the one with the superior recovery rates. From February to December 2021, 24-h wastewater samples were collected from the Ioannina Wastewater Treatment Plant's inlet and processed using both techniques. Subsequent viral genome isolation and a real-time RT-qPCR detection of SARS-CoV-2 were performed. The quantitative analysis demonstrated a higher detection sensitivity with a PEG-based concentration than SMF. Moreover, when the samples were positive by both methods, PEG consistently yielded higher viral loads. These findings underscore the need for further research into concentration methodologies and the development of precise protocols to enhance epidemiological surveillance through wastewater analysis.

Public health use and lessons learned from a statewide SARS-CoV-2 wastewater monitoring program (MiNET)

The global SARS-CoV-2 monitoring effort has been extensive, resulting in many states and countries establishing wastewater-based epidemiology programs to address the spread of the virus during the pandemic. Challenges for programs include concurrently optimizing methods, training new laboratories, and implementing successful surveillance programs that can rapidly translate results for public health, and policy making. Surveillance in Michigan early in the pandemic in 2020 highlights the importance of quality-controlled data and explores correlations with wastewater and clinical case data aggregated at the state level. The lessons learned and potential measures to improve public utilization of results are discussed. The Michigan Network for Environmental Health and Technology (MiNET) established a network of laboratories that partnered with local health departments, universities, wastewater treatment plants (WWTPs) and other stakeholders to monitor SARS-CoV-2 in wastewater at 214 sites in Michigan. MiNET consisted of nineteen laboratories, twenty-nine local health departments, 6 Native American tribes, and 60 WWTPs monitoring sites representing 45 % of Michigan's population from April 6 and December 29, 2020. Three result datasets were created based on quality control criteria. Wastewater results that met all quality assurance criteria (Dataset Mp) produced strongest correlations with reported clinical cases at 16 days lag (rho = 0.866, p < 0.05). The project demonstrated the ability to successfully track SARS-CoV-2 on a large, state-wide scale, particularly data that met the outlined quality criteria and provided an early warning of increasing COVID-19 cases. MiNET is currently poised to leverage its competency to complement public health surveillance networks through environmental monitoring for new and emerging pathogens of concern and provides a valuable resource to state and federal agencies to support future responses.

Comparison of Different Reverse Transcriptase-Polymerase Chain Reaction-Based Methods for Wastewater Surveillance of SARS-CoV-2: Exploratory Study

BACKGROUND

Many countries have applied the wastewater surveillance of the COVID-19 pandemic to their national public health monitoring measures. The most used methods for detecting SARS-CoV-2 in wastewater are quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) and reverse transcriptase-droplet digital polymerase chain reaction (RT-ddPCR). Previous comparison studies have produced conflicting results, thus more research on the subject is required.

OBJECTIVE

This study aims to compare RT-qPCR and RT-ddPCR for detecting SARS-CoV-2 in wastewater. It also aimed to investigate the effect of changes in the analytical pipeline, including the RNA extraction kit, RT-PCR kit, and target gene assay, on the results. Another aim was to find a detection method for low-resource settings.

METHODS

We compared 2 RT-qPCR kits, TaqMan RT-qPCR and QuantiTect RT-qPCR, and RT-ddPCR based on sensitivity, positivity rates, variability, and correlation of SARS-CoV-2 gene copy numbers in wastewater to the incidence of COVID-19. Furthermore, we compared 2 RNA extraction methods, column- and magnetic-bead-based. In addition, we assessed 2 target gene assays for RT-qPCR, N1 and N2, and 2 target gene assays for ddPCR N1 and E. Reverse transcription strand invasion-based amplification (RT-SIBA) was used to detect SARS-CoV-2 from wastewater qualitatively.

RESULTS

Our results indicated that the most sensitive method to detect SARS-CoV-2 in wastewater was RT-ddPCR. It had the highest positivity rate (26/30), and its limit of detection was the lowest (0.06 gene copies/µL). However, we obtained the best correlation between COVID-19 incidence and SARS-CoV-2 gene copy number in wastewater using TaqMan RT-qPCR (correlation coefficient [CC]=0.697, P<.001). We found a significant difference in sensitivity between the TaqMan RT-qPCR kit and the QuantiTect RT-qPCR kit, the first having a significantly lower limit of detection and a higher positivity rate than the latter. Furthermore, the N1 target gene assay was the most sensitive for both RT-qPCR kits, while no significant difference was found between the gene targets using RT-ddPCR. In addition, the use of different RNA extraction kits affected the result when the TaqMan RT-qPCR kit was used. RT-SIBA was able to detect SARS-CoV-2 RNA in wastewater.

CONCLUSIONS

As our study, as well as most of the previous studies, has shown RT-ddPCR to be more sensitive than RT-qPCR, its use in the wastewater surveillance of SARS-CoV-2 should be considered, especially if the amount of SARS-CoV-2 circulating in the population was low. All the analysis steps must be optimized for wastewater surveillance as our study showed that all the analysis steps including the compatibility of the RNA extraction, the RT-PCR kit, and the target gene assay influence the results. In addition, our study showed that RT-SIBA could be used to detect SARS-CoV-2 in wastewater if a qualitative result is sufficient.

Evaluation of different molecular systems for detection and quantification of SARS-CoV-2 RNA from wastewater samples

Wastewater-based epidemiology has proved to be a suitable approach for tracking the spread of epidemic agents including SARS-CoV-2 RNA. Different protocols have been developed for quantitative detection of SARS-CoV-2 RNA from wastewater samples, but little is known on their performance. In this study we compared three protocols based on Reverse Transcription Real Time-PCR (RT-PCR) and one based on Droplet Digital PCR (ddPCR) for SARS-CoV-2 RNA detection from 35 wastewater samples. Overall, SARS-CoV-2 RNA was detected by at least one method in 85.7 % of samples, while 51.4 %, 22.8 % and 8.6 % resulted positive with two, three or all four methods, respectively. Protocols based on commercial RT-PCR assays and on Droplet Digital PCR showed an overall higher sensitivity vs. an in-house assay. The use of more than one system, targeting different genes, could be helpful to increase detection sensitivity.

Bioinformatics-based screening tool identifies a wide variety of human and zoonotic viruses in Trujillo-Peru wastewater

Peru was one of the most affected countries during the COVID-19 pandemic. Moreover, multiple other viral diseases (enteric, respiratory, bloodborne, and vector-borne) are endemic and rising. According to Peru's Ministry of Health, various health facilities in the country were reallocated for the COVID-19 pandemic, thereby leading to reduced action to curb other diseases. Many viral diseases in the area are under-reported and not recognized. The One Health approach, in addition to clinical testing, incorporates environmental surveillance for detection of infectious disease outbreaks. The purpose of this work is to use a screening tool that is based on molecular methods, high throughput sequencing and bioinformatics analysis of wastewater samples to identify virus-related diseases circulating in Trujillo-Peru. To demonstrate the effectiveness of the tool, we collected nine untreated wastewater samples from the Covicorti wastewater utility in Trujillo-Peru on October 22, 2022. High throughput metagenomic sequencing followed by bioinformatic analysis was used to assess the viral diversity of the samples. Our results revealed the presence of sequences associated with multiple human and zoonotic viruses including Orthopoxvirus, Hepatovirus, Rhadinovirus, Parechovirus, Mamastrovirus, Enterovirus, Varicellovirus, Norovirus, Kobuvirus, Bocaparvovirus, Simplexvirus, Spumavirus, Orthohepevirus, Cardiovirus, Molliscipoxvirus, Salivirus, Parapoxvirus, Gammaretrovirus, Alphavirus, Lymphocryptovirus, Erythroparvovirus, Sapovirus, Cosavirus, Deltaretrovirus, Roseolovirus, Flavivirus, Betacoronavirus, Rubivirus, Lentivirus, Betapolyomavirus, Rotavirus, Hepacivirus, Alphacoronavirus, Mastadenovirus, Cytomegalovirus and Alphapapillomavirus. For confirmation purposes, we tested the samples for the presence of selective viruses belonging to the genera detected above. PCR based molecular methods confirmed the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), monkeypox virus (MPXV), noroviruses GI and GII (NoVGI and NoVGII), and rotavirus A (RoA) in our samples. Furthermore, publicly available clinical data for selected viruses confirm our findings. Wastewater or other environmental media surveillance, combined with bioinformatics methods, has the potential to serve as a systematic screening tool for the identification of human or zoonotic viruses that may cause disease. The results of this method can guide further clinical surveillance efforts and allocation of resources. Incorporation of this bioinformatic-based screening tool by public health officials in Peru and other Latin American countries will help manage endemic and emerging diseases that could save human lives and resources.

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.

SARS-CoV-2 wastewater surveillance at two university campuses: lessons learned and insights on intervention strategies for public health guidance

Wastewater surveillance has been a tool for public health officials throughout the COVID-19 pandemic. Universities established pandemic response committees to facilitate safe learning for students, faculty, and staff. These committees met to analyze both wastewater and clinical data to propose mitigation strategies to limit the spread of COVID-19. This paper reviews the initial efforts of utilizing campus data inclusive of wastewater surveillance for SARS-CoV-2 RNA concentrations, clinical case data from university response teams, and mitigation strategies from Grand Valley State University in West Michigan (population 21,648 students) and Oakland University in East Michigan (population 18,552 students) from November 2020 to April 2022. Wastewater positivity rates for both universities ranged from 32.8 to 46.8%. Peak viral signals for both universities directly corresponded to variant points of entry within the campus populations from 2021 to 2022. It was found that the organization of clinical case data and variability of wastewater testing data were large barriers for both universities to effectively understand disease dynamics within the university population. We review the initial efforts of onboarding wastewater surveillance and provide direction for structuring ongoing surveillance workflows and future epidemic response strategies based on those that led to reduced viral signals in campus wastewater.

Long-term monitoring of SARS-CoV-2 variants in wastewater using a coordinated workflow of droplet digital PCR and nanopore sequencing

Quantitative polymerase chain reaction (PCR) and genome sequencing are important methods for wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The reverse transcription-droplet digital PCR (RT-ddPCR) is a highly sensitive method for quantifying SARS-CoV-2 RNA in wastewater samples to track the trends of viral activity levels but cannot identify new variants. It also takes time to develop new PCR-based assays targeting variants of interest. Whole genome sequencing (WGS) can be used to monitor known and new SARS-CoV-2 variants, but it is generally not quantitative. Several short-read sequencing techniques can be expensive and might experience delayed turnaround times when outsourced due to inadequate in-house resources. Recently, a portable nanopore sequencing system offers an affordable and real-time method for sequencing SARS-CoV-2 variants in wastewater. This technology has the potential to enable swift response to disease outbreaks without relying on clinical sequencing results. In addressing concerns related to rapid turnaround time and accurate variant analysis, both RT-ddPCR and nanopore sequencing methods were employed to monitor the emergence of SARS-CoV-2 variants in wastewater. This surveillance was conducted at 23 sewer maintenance hole sites and five wastewater treatment plants in Michigan from 2020 to 2022. In 2020, the wastewater samples were dominated by the parental variants (20A, 20C and 20 G), followed by 20I (Alpha, B.1.1.7) in early 2021 and the Delta variant of concern (VOC) in late 2021. For the year 2022, Omicron variants dominated. Nanopore sequencing has the potential to validate suspected variant cases that were initially undetermined by RT-ddPCR assays. The concordance rate between nanopore sequencing and RT-ddPCR assays in identifying SARS-CoV-2 variants to the clade-level was 76.9%. Notably, instances of disagreement between the two methods were most prominent in the identification of the parental and Omicron variants. We also showed that sequencing wastewater samples with SARS-CoV-2 N gene concentrations of >104 GC/100 ml as measured by RT-ddPCR improve genome recovery and coverage depth using MinION device. RT-ddPCR was better at detecting key spike protein mutations A67V, del69-70, K417N, L452R, N501Y, N679K, and R408S (p-value <0.05) as compared to nanopore sequencing. It is suggested that RT-ddPCR and nanopore sequencing should be coordinated in wastewater surveillance where RT-ddPCR can be used as a preliminary quantification method and nanopore sequencing as the confirmatory method for the detection of variants or identification of new variants. The RT-ddPCR and nanopore sequencing methods reported here can be adopted as a reliable in-house analysis of SARS-CoV-2 in wastewater for rapid community level surveillance and public health response.

Application of Skimmed-Milk Flocculation Method for Wastewater Surveillance of COVID-19 in Kathmandu, Nepal

Wastewater surveillance (WS) has been used globally as a complementary tool to monitor the spread of coronavirus disease 2019 (COVID-19) throughout the pandemic. However, a concern about the appropriateness of WS in low- and middle-income countries (LMICs) exists due to low sewer coverage and expensive viral concentration methods. In this study, influent wastewater samples (n = 63) collected from two wastewater treatment plants (WWTPs) of the Kathmandu Valley between March 2021 and February 2022 were concentrated using the economical skimmed-milk flocculation method (SMFM). The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was tested by qPCR using assays that target the nucleocapsid (N) and envelope (E) genes. Overall, 84% (53/63) of the total samples were positive for SARS-CoV-2 according to at least one of the tested assays, with concentrations ranging from 3.5 to 8.3 log10 gene copies/L, indicating the effectiveness of the SMFM. No correlation was observed between the total number of COVID-19 cases and SARS-CoV-2 RNA concentrations in wastewater collected from the two WWTPs (p > 0.05). This finding cautions the prediction of future COVID-19 waves and the estimation of the number of COVID-19 cases based on wastewater concentration in settings with low sewer coverage by WWTPs. Future studies on WS in LMICs are recommended to be conducted by downscaling to sewer drainage, targeting a limited number of houses. Overall, this study supports the notion that SMFM can be an excellent economical virus-concentrating method for WS of COVID-19 in LMICs.

Influences of 23 different equations used to calculate gene copies of SARS-CoV-2 during wastewater-based epidemiology

Following the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the use of wastewater-based surveillance (WBS) has increased dramatically along with associated infrastructure globally. However, due to the global nature of its application, and various workflow adaptations (e.g., sample collection, water concentration, RNA extraction kits), numerous methods for back-calculation of gene copies per volume (gc/L) of sewage have also emerged. Many studies have considered the comparability of processing methods (e.g., water concentration, RNA extraction); however, for equations used to calculate gene copies in a wastewater sample and subsequent influences on monitoring viral trends in a community and its association with epidemiological data, less is known. Due to limited information on how many formulas exist for the calculation of SARS-CoV-2 gene copies in wastewater, we initially attempted to quantify how many equations existed in the referred literature. We identified 23 unique equations, which were subsequently applied to an existing wastewater dataset. We observed a range of gene copies based on use of different equations, along with variability of AUC curve values, and results from correlation and regression analyses. Though a number of individual laboratories appear to have independently converged on a similar formula for back-calculation of viral load in wastewater, and share similar relationships with epidemiological data, differential influences of various equations were observed for variation in PCR volumes, RNA extraction volumes, or PCR assay parameters. Such observations highlight challenges when performing comparisons among WBS studies when numerous methodologies and back-calculation methods exist. To facilitate reproducibility among studies, the different gc/L equations were packaged as an R Shiny app, which provides end users the ability to investigate variability within their datasets and support comparisons among studies.

Effect of wastewater collection and concentration methods on assessment of viral diversity

Monitoring of potentially pathogenic human viruses in wastewater is of crucial importance to understand disease trends in communities, predict potential outbreaks, and boost preparedness and response by public health departments. High throughput metagenomic sequencing opens an opportunity to expand the capabilities of wastewater surveillance. However, there are major bottlenecks in the metagenomic enabled wastewater surveillance, including the complexities in selecting appropriate sampling and concentration/virus enrichment methods as well as in bioinformatic analysis of complex samples with low human virus concentrations. To evaluate the abilities of two commonly used sampling and concentration methods in virus identification, virus communities concentrated with Virus Adsorption-Elution (VIRADEL) and PolyEthylene Glycol (PEG) precipitation were compared for three interceptor sites. Results indicated that more viral reads were obtained by the VIRADEL concentration method, with 2.84 ± 0.57 % viral reads in the sample. For samples concentrated with PEG, the average proportion of viral reads in the sample was 0.63 ± 0.19 %. In all wastewater samples, bacteriophage affiliated with the families Siphoviridae, Myoviridae and Podoviridae were found to be the abundant populations. Comparison against a custom Swiss-Prot human virus database indicated that the relatively abundant human viruses (average proportions in human virus community greater than 1.00 %) in samples concentrated with the VIRADEL method were Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Molluscipoxvirus, Parechovirus, Lymphocryptovirus, and Spumavirus. In samples concentrated with the PEG method, fewer human viruses were found to be relatively abundant. These were Orthopoxvirus, Rhadinovirus, Varicellovirus, Simplexvirus, Molluscipoxvirus, Lymphocryptovirus, and Betacoronavirus. Contigs of Betacoronavirus, which contains severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were identified in VIRADEL and PEG samples. Our study demonstrates the feasibility of using metagenomics in wastewater surveillance as a first screening tool and the need for selecting the appropriate virus concentration methods and optimizing bioinformatic approaches in analyzing metagenomic data of wastewater samples.

Chronic shedding of a SARS-CoV-2 Alpha variant in wastewater

BACKGROUND

Central Michigan University (CMU) participated in a state-wide SARS-CoV-2 wastewater monitoring program since 2021. Wastewater samples were collected from on-campus sites and nine off-campus wastewater treatment plants servicing small metropolitan and rural communities. SARS-CoV-2 genome copies were quantified using droplet digital PCR and results were reported to the health department.

RESULTS

One rural, off-campus site consistently produced higher concentrations of SARS-CoV-2 genome copies. Samples from this site were sequenced and contained predominately a derivative of Alpha variant lineage B.1.1.7, detected from fall 2021 through summer 2023. Mutational analysis of reconstructed genes revealed divergence from the Alpha variant lineage sequence over time, including numerous mutations  in the Spike RBD and NTD.

CONCLUSIONS

We discuss the possibility that a chronic SARS-CoV-2 infection accumulated adaptive mutations that promoted long-term infection. This study reveals that small wastewater treatment plants can enhance resolution of rare events and facilitate reconstruction of viral genomes due to the relative lack of contaminating sequences.

Evaluation of four human-associated fecal biomarkers in wastewater in Southern Ontario

Human fecal biomarkers (HFBs) have a longstanding history in the field of microbial source tracking (MST) serving as indicators of human fecal contamination in drinking and recreational water. Further, HFBs have aided in recent efforts to monitor human pathogen transmission within communities. The dilution of wastewater from various sources throughout the sewershed cannot be controlled and human fecal biomarkers (HFBs) can be used to normalize target human pathogen concentrations so that fluctuations in fecal matter in wastewater can be accounted for. In the current study, we monitored the prevalence of four HFBs - including two viruses, Pepper mild mottle virus (PMMoV), cross-assembly phage (crAssphage), as well as two human-associated Bacteroides markers, HF183 and BacHuman - in wastewater samples from ten Southern Ontario wastewater treatment plants and evaluated their temporal and spatial variation in context of environmental factors that may impact the ability of HFB to normalize pathogen concentrations in wastewater. Environmental variables including precipitation, wastewater flow rate, temperature, and concentrated mass were also analyzed for their potential correlation with HFB variation in wastewater. The four HFBs were detected at high concentrations across all 10 sampling locations. The median concentrations across all sampling sites were: PMMoV 3.6 Log gene copies (GC)/mL; crAssphage 5.0 Log GC/mL; HF183 6.8 Log GC/mL and BacHuman 6.9 Log GC/mL. All HFBs were found to be similarly stratified across all 10 sites, and the bacterial markers were consistently found at higher concentration compared to the viral HFBs at all sites. The coefficient of variation (CV) for each HFB was used to characterize the variability of each biomarker at each sewershed. BacHuman and crAssphage were found to have lower CV than PMMoV and HF183, indicating that BacHuman and crAssphage may perform better in reflecting the variations in abundance of human feces in wastewater or MST applications.

The role of wastewater-based epidemiology for SARS-CoV-2 in developing countries: Cumulative evidence from South Africa supports sentinel site surveillance to guide public health decision-making

The uptake of wastewater-based epidemiology (WBE) for SARS-CoV-2 as a complementary tool for monitoring population-level epidemiological features of the COVID-19 pandemic in low-and-middle-income countries (LMICs) is low. We report on the findings from the South African SARS-CoV-2 WBE surveillance network and make recommendations regarding the implementation of WBE in LMICs. Eight laboratories quantified influent wastewater collected from 87 wastewater treatment plants in all nine South African provinces from 01 June 2021 to 31 May 2022 inclusive, during the 3rd and 4th waves of COVID-19. Correlation and regression analyses between wastewater levels of SARS-CoV-2 and district laboratory-confirmed caseloads were conducted. The sensitivity and specificity of novel 'rules' based on WBE data to predict an epidemic wave were determined. Amongst 2158 wastewater samples, 543/648 (85 %) samples taken during a wave tested positive for SARS-CoV-2 compared with 842 positive tests from 1512 (55 %) samples taken during the interwave period. Overall, the regression-co-efficient was 0,66 (95 % confidence interval = 0,6-0,72, R2 = 0.59), ranging from 0.14 to 0.87 by testing laboratory. Early warning of the 4th wave of SARS-CoV-2 in Gauteng Province in November-December 2021 was demonstrated. A 50 % increase in log copies of SARS-CoV-2 compared with a rolling mean over the previous five weeks was the most sensitive predictive rule (58 %) to predict a new wave. Our findings support investment in WBE for SARS-CoV-2 surveillance in LMICs as an early warning tool. Standardising test methodology is necessary due to varying correlation strengths across laboratories and redundancy across testing plants. A sentinel site model can be used for surveillance networks without affecting WBE finding for decision-making. Further research is needed to identify optimal test frequency and the need for normalisation to population size to identify predictive and interpretive rules to support early warning and public health action.

Wastewater Monitoring for Infectious Disease: Intentional Relationships between Academia, the Private Sector, and Local Health Departments for Public Health Preparedness

The public health emergency caused by the COVID-19 pandemic stimulated stakeholders from diverse disciplines and institutions to establish new collaborations to produce informed public health responses to the disease. Wastewater-based epidemiology for COVID-19 grew quickly during the pandemic and required the rapid implementation of such collaborations. The objective of this article is to describe the challenges and results of new relationships developed in Detroit, MI, USA among a medical school and an engineering college at an academic institution (Wayne State University), the local health department (Detroit Health Department), and an environmental services company (LimnoTech) to utilize markers of the COVID-19 virus, SARS-CoV-2, in wastewater for the goal of managing COVID-19 outbreaks. Our collaborative team resolved questions related to sewershed selection, communication of results, and public health responses and addressed technical challenges that included ground-truthing the sewer maps, overcoming supply chain issues, improving the speed and sensitivity of measurements, and training new personnel to deal with a new disease under pandemic conditions. Recognition of our complementary roles and clear communication among the partners enabled city-wide wastewater data to inform public health responses within a few months of the availability of funding in 2020, and to make improvements in sensitivity and understanding to be made as the pandemic progressed and evolved. As a result, the outbreaks of COVID-19 in Detroit in fall and winter 2021-2022 (corresponding to Delta and Omicron variant outbreaks) were tracked in 20 sewersheds. Data comparing community- and hospital-associated sewersheds indicate a one- to two-week advance warning in the community of subsequent peaks in viral markers in hospital sewersheds. The new institutional relationships impelled by the pandemic provide a good basis for continuing collaborations to utilize wastewater-based human and pathogen data for improving the public health in the future.

Understanding the efficacy of wastewater surveillance for SARS-CoV-2 in two diverse communities

During the COVID-19 pandemic, wastewater-based surveillance has been shown to be a useful tool for monitoring the spread of disease in communities and the emergence of new viral variants of concern. As the pandemic enters its fourth year and clinical testing has declined, wastewater offers a consistent non-intrusive way to monitor community health in the long term. This study sought to understand how accurately wastewater monitoring represented the actual burden of disease between communities. Two communities varying in size and demographics in Michigan were monitored for SARS-CoV-2 in wastewater between March of 2020 and February of 2022. Additionally, each community was monitored for SARS-CoV-2 variants of concern from December 2020 to February 2022. Wastewater results were compared with zipcode and county level COVID-19 case data to determine which scope of clinical surveillance was most correlated with wastewater loading. Pearson r correlations were highest in the smaller of the two communities (population of 25,000) for N1 GC/person/day with zipcode level case data, and date of the onset of symptoms (r = 0.81). A clear difference was seen with more cases and virus signals in the wastewater of the larger community (population 110,000) when examined based on vaccine status, which reached only 50%. While wastewater levels of SARS-CoV-2 had a lower correlation to cases in the larger community, the information was still seen as valuable in supporting public health actions and further data including vaccination status should be examined in the future.

Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center

Introduction

Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices.

Methods

Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony.

Results

It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors.

Discussion

These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.

Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.

Wastewater-Based Epidemiology of SARS-CoV-2: Assessing Prevalence and Correlation with Clinical Cases

Wastewater-based epidemiology has been recognized as a tool to monitor the progress of COVID-19 pandemic worldwide. The study presented herein aimed at quantitating the SARS-CoV-2 RNA in the wastewaters, predicting the number of infected individuals in the catchment areas, and correlating it with the clinically reported COVID-19 cases. Wastewater samples (n = 162) from different treatment stages were collected from three wastewater treatment plants (WWTPs) from Mumbai city during the 2nd surge of COVID-19 (April 2021 to June 2021). SARS-CoV-2 causing COVID-19, was detected in 76.2% and 4.8% of raw and secondary treated (n = 63 each) wastewater samples respectively while all tertiary treated samples (n = 36) were negative. The quantity of SARS-CoV-2 RNA determined as gene copies/100 mL varied among all the three WWTPs under study. The gene copy numbers thus obtained were further used to estimate the number of infected individuals within the population served by these WWTPs using two published methods. A positive correlation (p < 0.05) was observed between the estimated number of infected individuals and clinically confirmed COVID-19 cases reported during the sampling period in two WWTPs. Predicted infected individuals calculated in this study were 100 times higher than the reported COVID-19 cases in all the WWTPs assessed. The study findings demonstrated that the present wastewater treatment technologies at the three WWTPs studied were adequate to remove the virus. However, SARS-CoV-2 genome surveillance with emphasis on monitoring its variants should be implemented as a routine practice to prepare for any future surge in infections.

SARS-CoV-2 surveillance in medical and industrial wastewater-a global perspective: a narrative review

The novel coronavirus SARS-CoV-2 has spread at an unprecedented rate since late 2019, leading to the global COVID-19 pandemic. During the pandemic, being able to detect SARS-CoV-2 in human populations with high coverage quickly is a huge challenge. As SARS-CoV-2 is excreted in human excreta and thus exposed to the aqueous environment through sewers, the goal is to develop an ideal, non-invasive, cost-effective epidemiological method for detecting SARS-CoV-2. Wastewater surveillance has gained widespread interest and is increasingly being investigated as an effective early warning tool for monitoring the spread and evolution of the virus. This review emphasizes important findings on SARS-CoV-2 wastewater-based epidemiology (WBE) in different continents and techniques used to detect SARS-CoV-2 in wastewater during the period 2020-2022. The results show that WBE is a valuable population-level method for monitoring SARS-CoV-2 and is a valuable early warning alert. It can assist policymakers in formulating relevant policies to avoid the negative impacts of early or delayed action. Such strategy can also help avoid unnecessary wastage of medical resources, rationalize vaccine distribution, assist early detection, and contain large-scale outbreaks.

Frequency and degradation of SARS-CoV-2 markers N1, N2, and E in sewage

Coronavirus disease 2019 (COVID-19) is an infectious disease that is mainly spread through aerosolized droplets containing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is excreted in feces by infected individuals. Sewage surveillance has been applied widely to obtain data on the prevalence of COVID-19 in whole communities. We used SARS-CoV-2 gene targets N1, N2, and E to determine the prevalence of COVID-19 at both municipal and building levels. Frequency analysis of wastewater testing indicated that single markers detected only 85% or less of samples that were detected as positive for SARS-CoV-2 with the three markers combined, indicating the necessity of pairing markers to lower the false-negative rate. The best pair of markers in both municipal and building level monitoring was N1 and N2, which correctly identified 98% of positive samples detected with the three markers combined. The degradation rates of all three targets were assessed at two different temperatures (25 and 35 °C) as a possible explanation for observed differences between markers in frequency. Results indicated that all three RNA targets degrade at nearly the same rate, indicating that differences in degradation rate are not responsible for the observed differences in marker frequency.

Monitoring of COVID-19 in wastewater across the Eastern Upper Peninsula of Michigan

Wastewater-based epidemiology is being used as a tool to monitor the spread of COVID-19 and provide an early warning for the presence or increase of clinical cases in a community. The majority of wastewater-based epidemiology for COVID-19 tracking has been utilized in sewersheds that service populations in the tens-to-hundreds of thousands. Few studies have been conducted to assess the usefulness of wastewater in predicting COVID-19 clinical cases specifically in rural areas. This study collected samples from 16 locations across the Eastern Upper Peninsula of Michigan from June to December 2021. Sampling locations included 12 rural municipalities, a Tribal housing community and casino, a public university, three municipalities that also contained a prison, and a small island with heavy tourist traffic. Samples were analyzed for SARS-CoV-2 N1, N2, and variant gene copies using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR). Wastewater N1 and N2 gene copies and clinical case counts were correlated to determine if wastewater results were predictive of clinical cases. Significant correlation between N1 and N2 gene copies and clinical cases was found for all sites (⍴= 0.89 to 0.48). N1 and N2 wastewater results were predictive of clinical case trends within 0-7 days. The Delta variant was detected in the Pickford and St. Ignace samples more than 12-days prior to the first reported Delta clinical cases in their respective counties. Locations with low correlation could be attributed to their high rates of tourism. This is further supported by the high correlation seen in the public university, which is a closed population. Long-term wastewater monitoring over a large, rural geographic area is useful for informing the public of potential outbreaks in the community regardless of asymptomatic cases and access to clinical testing.

SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales

Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.

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.

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

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

COVID-19 and Water Variables: Review and Scientometric Analysis

COVID-19 has changed the world since 2020, and the field of water specifically, boosting scientific productivity (in terms of published articles). This paper focuses on the influence of COVID-19 on scientific productivity with respect to four water variables: (i) wastewater, (ii) renewable water resources, (iii) freshwater withdrawal, and (iv) access to improved and safe drinking water. The field's literature was firstly reviewed, and then the maps were built, emphasizing the strong connections between COVID-19 and water-related variables. A total of 94 countries with publications that assess COVID-19 vs. water were considered and evaluated for how they clustered. The final step of the research shows that, on average, scientific productivity on the water topic was mostly conducted in countries with lower COVID-19 infection rates but higher development levels as represented by gross domestic product (GDP) per capita and the human development index (HDI). According to the statistical analysis, the water-related variables are highly significant, with positive coefficients. This validates that countries with higher water-related values conducted more research on the relationship with COVID-19. Wastewater and freshwater withdrawal had the highest impact on the scientific productivity with respect to COVID-19. Access to safe drinking water becomes insignificant in the presence of the development parameters.

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

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

Advances in virus detection methods for wastewater-based epidemiological applications

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

Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR

Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID-19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. Standard processes for purifying viral RNA from municipal wastewater are often time-consuming and require the handling of large quantities of wastewater, negatively affecting throughput, timely reporting, and safety. We demonstrate here an automated, faster system to purify viral RNA from smaller volumes of wastewater but with increased sensitivity for detection of SARS-CoV-2 markers. We document the effectiveness of this new approach by way of comparison to the PEG/NaCl/Qiagen method prescribed by the State of Michigan for SARS-CoV-2 wastewater monitoring and show its application to several Detroit sewersheds. Specifically, compared to the PEG/NaCl/Qiagen method, viral RNA purification using the PerkinElmer Chemagic™ 360 lowered handling time, decreased the amount of wastewater required by ten-fold, increased the amount of RNA isolated per μl of final elution product by approximately five-fold, and effectively removed ddPCR inhibitors from most sewershed samples. For detection of markers on the borderline of viral detectability, we found that use of the Chemagic™ 360 enabled the measurement of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. The improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak. Applied to sewersheds in Detroit, the technique enabled more sensitive detection of SARS-CoV-2 markers with good correlation between wastewater signals and COVID-19 cases in the sewersheds. We also discuss advantages and disadvantages of several automated RNA purification systems, made by Promega, PerkinElmer, and ThermoFisher.

The Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S): A rapid and cost-effective SARS-CoV-2 RNA detection method for routine wastewater surveillance

Wastewater-based epidemiology has attracted attention as a COVID-19 surveillance tool. Here, we developed a practical method for detecting SARS-CoV-2 RNA in wastewater (the EPISENS-S method), which employs direct RNA extraction from wastewater pellets formed via low-speed centrifugation. The subsequent multiplex one-step RT-preamplification reaction with forward and reverse primers for SARS-CoV-2 and a reverse primer only for pepper mild mottle virus (PMMoV) allowed for qPCR quantification of the targets with different abundances in wastewater from the RT-preamplification product. The detection sensitivity of the method was evaluated using wastewater samples seeded with heat-inactivated SARS-CoV-2 in concentrations of 2.11 × 103 to 2.11 × 106 copies/L. The results demonstrated that the sensitivity of the EPISENS-S method was two orders of magnitude higher than that of the conventional method (PEG precipitation, followed by regular RT-qPCR; PEG-QVR-qPCR). A total of 37 untreated wastewater samples collected from two wastewater treatment plants in Sapporo, Japan when 1.6 to 18 new daily reported cases per 100,000 people were reported in the city (March 4 to July 8, 2021), were examined using the EPISENS-S method to confirm its applicability to municipal wastewater. SARS-CoV-2 RNA was quantified in 92 % (34/37) of the samples via the EPISENS-S method, whereas none of the samples (0/37) was quantifiable via the PEG-QVR-qPCR method. The PMMoV concentrations measured by the EPISENS-S method ranged from 2.60 × 106 to 1.90 × 108 copies/L, and the SARS-CoV-2 RNA concentrations normalized by PMMoV ranged from 5.71 × 10-6 to 9.51 × 10-4 . The long-term trend of normalized SARS-CoV-2 RNA concentration in wastewater was consistent with that of confirmed COVID-19 cases in the city. These results demonstrate that the EPISENS-S method is highly sensitive and suitable for routine COVID-19 wastewater surveillance.

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

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

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

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

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

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

Year-long wastewater monitoring for SARS-CoV-2 signals in combined and separate sanitary sewers

COVID-19 wastewater-based epidemiology has been performed in catchments of various sizes and sewer types with many short-term studies available and multi-seasonal studies emerging. The objective of this study was to compare weekly observations of SARS-CoV-2 genes in municipal wastewater across multiple seasons for different systems as a factor of sewer type (combined, separate sanitary) and system size. Sampling occurred following the first wave of SARS-CoV-2 cases in the study region (June 2020) and continued through the third wave (May 2021), the period during which clinical testing was widely available and different variants dominated clinical cases. The strongest correlations were observed between wastewater N1 concentrations and the cumulative clinical cases reported in the 2 weeks prior to wastewater sampling, followed by the week prior, new cases, and the week after wastewater sampling. Sewer type and size did not necessarily explain the strength of the correlations, indicating that other non-sewer factors may be impacting the observations. In-system sampling results for the largest system sampled are presented for 1 month. Removing wet weather days from the data sets improved even the flow-normalized correlations for the systems, potentially indicating that interpreting results during wet weather events may be more complicated than simply accounting for dilution. PRACTITIONER POINTS: SARS-CoV-2 in wastewater correlated best with total clinical cases reported in 2 weeks before wastewater sampling at the utility level. Study performed when clinical testing was widespread during the year after the first COVID-19 wave in the region. Sewer type and size did not necessarily explain correlation strength between clinical cases and wastewater-based epidemiology results. Removing wet weather days improved correlations for 3/4 utilities studied, including both separate sanitary and combined sewers.

Development of an efficient wastewater testing protocol for high-throughput country-wide SARS-CoV-2 monitoring

Wastewater-based surveillance has been widely used as a non-intrusive tool to monitor population-level transmission of COVID-19. Although various approaches are available to concentrate viruses from wastewater samples, scalable methods remain limited. Here, we sought to identify and evaluate SARS-CoV-2 virus concentration protocols for high-throughput wastewater testing. A total of twelve protocols for polyethylene glycol (PEG) precipitation and four protocols for ultrafiltration-based approaches were evaluated across two phases. The first phase entailed an initial evaluation using a small sample set, while the second phase further evaluated five protocols using wastewater samples of varying SARS-CoV-2 concentrations. Permutations in the pre-concentration, virus concentration and RNA extraction steps were evaluated. Among PEG-based methods, SARS-CoV-2 virus recovery was optimal with 1) the removal of debris prior to processing, 2) 2 h to 24 h incubation with 8% PEG at 4 °C, 3) 4000 xg or 14,000 xg centrifugation, and 4) a column-based RNA extraction method, yielding virus recovery of 42.4-52.5%. Similarly, the optimal protocol for ultrafiltration included 1) the removal of debris prior to processing, 2) ultrafiltration, and 3) a column-based RNA extraction method, yielding a recovery of 38.2%. This study also revealed that SARS-CoV-2 RNA recovery for samples with higher virus concentration were less sensitive to changes in the PEG method, but permutations in the PEG protocol could significantly impact virus yields when wastewater samples with lower SARS-CoV-2 RNA were used. Although both PEG precipitation and ultrafiltration methods resulted in similar SARS-CoV-2 RNA recoveries, the former method is more cost-effective while the latter method provided operational efficiency as it required a shorter turn-around-time (PEG precipitation, 9-23 h; Ultrafiltration, 5 h). The decision on which method to adopt will thus depend on the use-case for wastewater testing, and the need for cost-effectiveness, sensitivity, operational feasibility and scalability.

Longer amplicons provide better sensitivity for electrochemical sensing of viral nucleic acid in water samples using PCB electrodes

The importance of monitoring environmental samples has gained a lot of prominence since the onset of COVID-19 pandemic, and several surveillance efforts are underway using gold standard, albeit expensive qPCR-based techniques. Electrochemical DNA biosensors could offer a potential cost-effective solution suitable for monitoring of environmental water samples in lower middle income countries. In this work, we demonstrate electrochemical detection of amplicons as long as [Formula: see text] obtained from Phi6 bacteriophage (a popular surrogate for SARS-CoV-2) isolated from spiked lake water samples, using ENIG finish PCB electrodes with no surface modification. The electrochemical sensor response is thoroughly characterised for two DNA fragments of different lengths ([Formula: see text] and [Formula: see text]), and the impact of salt in PCR master mix on methylene blue (MB)-DNA interactions is studied. Our findings establish that length of the DNA fragment significantly determines electrochemical sensitivity, and the ability to detect long amplicons without gel purification of PCR products demonstrated in this work bodes well for realisation of fully-automated solutions for in situ measurement of viral load in water samples.

Molecular Diagnostic Tools Applied for Assessing Microbial Water Quality

Microbial water quality is of vital importance for human, animal, and environmental health. Notably, pathogenically contaminated water can result in serious health problems, such as waterborne outbreaks, which have caused huge economic and social losses. In this context, the prompt detection of microbial contamination becomes essential to enable early warning and timely reaction with proper interventions. Recently, molecular diagnostics have been increasingly employed for the rapid and robust assessment of microbial water quality implicated by various microbial pollutants, e.g., waterborne pathogens and antibiotic-resistance genes (ARGs), imposing the most critical health threats to humans and the environment. Continuous technological advances have led to constant improvements and expansions of molecular methods, such as conventional end-point PCR, DNA microarray, real-time quantitative PCR (qPCR), multiplex qPCR (mqPCR), loop-mediated isothermal amplification (LAMP), digital droplet PCR (ddPCR), and high-throughput next-generation DNA sequencing (HT-NGS). These state-of-the-art molecular approaches largely facilitate the surveillance of microbial water quality in diverse aquatic systems and wastewater. This review provides an up-to-date overview of the advancement of the key molecular tools frequently employed for microbial water quality assessment, with future perspectives on their applications.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

Sensitivity of wastewater-based epidemiology for detection of SARS-CoV-2 RNA in a low prevalence setting

To assist public health responses to COVID-19, wastewater-based epidemiology (WBE) is being utilised internationally to monitor SARS-CoV-2 infections at the community level. However, questions remain regarding the sensitivity of WBE and its use in low prevalence settings. In this study, we estimated the total number of COVID-19 cases required for detection of SARS-CoV-2 RNA in wastewater. To do this, we leveraged a unique situation where, over a 4-month period, all symptomatic and asymptomatic cases, in a population of approximately 120,000, were precisely known and mainly located in a single managed isolation and quarantine facility (MIQF) building. From 9 July to 6 November 2020, 24-hr composite wastewater samples (n = 113) were collected daily from the sewer outside the MIQF, and from the municipal wastewater treatment plant (WWTP) located 5 km downstream. New daily COVID-19 cases at the MIQF ranged from 0 to 17, and for most of the study period there were no cases outside the MIQF identified. SARS-CoV-2 RNA was detected in 54.0% (61/113) at the WWTP, compared to 95.6% (108/113) at the MIQF. We used logistic regression to estimate the shedding of SARS-CoV-2 RNA into wastewater based on four infectious shedding models. With a total of 5 and 10 COVID-19 infectious cases per 100,000 population (0.005% and 0.01% prevalence) the predicated probability of SARS-CoV-2 RNA detection at the WWTP was estimated to be 28 and 41%, respectively. When a proportional shedding model was used, this increased to 58% and 87% for 5 and 10 cases, respectively. In other words, when 10 individuals were actively shedding SARS-CoV-2 RNA in a catchment of 100,000 individuals, there was a high likelihood of detecting viral RNA in wastewater. SARS-CoV-2 RNA detections at the WWTP were associated with increasing COVID-19 cases. Our results show that WBE provides a reliable and sensitive platform for detecting infections at the community scale, even when case prevalence is low, and can be of use as an early warning system for community outbreaks.