Genome Sequencing of Sewage Detects Regionally Prevalent SARS-CoV-2 Variants

Highly sensitive wastewater surveillance of SARS-CoV-2 variants by targeted next-generation amplicon sequencing provides early warning of incursion in Victoria, Australia

The future of the COVID pandemic and its public health and societal impact will be determined by the profile and spread of emerging variants and the timely identification and response to them. Wastewater surveillance of SARS-CoV-2 has been widely adopted in many countries across the globe and has played an important role in tracking infection levels and providing useful epidemiological information that cannot be adequately captured by clinical testing alone. However, novel variants can emerge rapidly, spread globally, and markedly alter the trajectory of the pandemic, as exemplified by the Delta and Omicron variants. Most mutations linked to the emergence of new SARS-CoV-2 variants are found within variable regions of the SARS-CoV-2 Spike protein. We have developed a duplex hemi-nested PCR method that, coupled with short amplicon sequencing, allows simultaneous typing of two of the most highly variable and informative regions of the Spike gene: the N-terminal domain and the receptor binding motif. Using this method in an operationalized public health program, we identified the first known incursion of Omicron BA.1 into Victoria, Australia and demonstrated how sensitive amplicon sequencing methods can be combined with wastewater surveillance as a relatively low-cost solution for early warning of variant incursion and spread.IMPORTANCEThis study offers a rapid, cost-effective, and sensitive approach for monitoring SARS-CoV-2 variants in wastewater. The method's flexibility permits timely modifications, enabling the integration of emerging variants and adaptations to evolving SARS-CoV-2 genetics. Of particular significance for low- and middle-income regions with limited surveillance capabilities, this technique can potentially be utilized to study a range of pathogens or viruses that possess diverse genetic sequences, similar to influenza.

First reporting of BA.1* and BA.2* recombinant SARS-CoV-2 lineage XAP from Indian wastewaters

Tracking new variants of SARS-CoV-2 is vital for managing COVID-19 spread and allocating resources. Domestic antigen testing has created surveillance gaps that make it hard to identify new viral variants. We conducted whole genome sequencing of wastewater viral genes from major and minor treatment facilities in Dehradun from March 2022 onwards. Based on our analysis, the samples that achieved higher sequencing depth and covered >90 % of the viral genome uncovered a major variant pattern resembling the XAP recombinant lineage that is reported for the first time in the City of Dehradun, Uttrakhand and is the first ever records in India as on date. This novel XAP recombinant lineage had 9, 2, 30, 1, 2, 5, 1, 1, 1 aminoacid changes (total 54 mutations) in Orf1a, Orf1b, S, E, M, N, Orf3a, Orf6 and Orf8 regions of the gene respectively that shares 49 mutations common to the ancestral lineages BA.1* and BA.2*, with 6 unique mutations. Subsequent comparison and analysis of the clinical sequence data from the region post-detection of this rare and unusual variant showed no causalities infected with the newly detected XAP lineage. These findings are indicative of future alarming situation with plausible threats of fresh spur of Omicron variant led infections in the urban community.

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.

SARS-CoV-2 wastewater variant surveillance: pandemic response leveraging FDA's GenomeTrakr network

Wastewater surveillance has emerged as a crucial public health tool for population-level pathogen surveillance. Supported by funding from the American Rescue Plan Act of 2021, the FDA's genomic epidemiology program, GenomeTrakr, was leveraged to sequence SARS-CoV-2 from wastewater sites across the United States. This initiative required the evaluation, optimization, development, and publication of new methods and analytical tools spanning sample collection through variant analyses. Version-controlled protocols for each step of the process were developed and published on protocols.io. A custom data analysis tool and a publicly accessible dashboard were built to facilitate real-time visualization of the collected data, focusing on the relative abundance of SARS-CoV-2 variants and sub-lineages across different samples and sites throughout the project. From September 2021 through June 2023, a total of 3,389 wastewater samples were collected, with 2,517 undergoing sequencing and submission to NCBI under the umbrella BioProject, PRJNA757291. Sequence data were released with explicit quality control (QC) tags on all sequence records, communicating our confidence in the quality of data. Variant analysis revealed wide circulation of Delta in the fall of 2021 and captured the sweep of Omicron and subsequent diversification of this lineage through the end of the sampling period. This project successfully achieved two important goals for the FDA's GenomeTrakr program: first, contributing timely genomic data for the SARS-CoV-2 pandemic response, and second, establishing both capacity and best practices for culture-independent, population-level environmental surveillance for other pathogens of interest to the FDA.

IMPORTANCE

This paper serves two primary objectives. First, it summarizes the genomic and contextual data collected during a Covid-19 pandemic response project, which utilized the FDA's laboratory network, traditionally employed for sequencing foodborne pathogens, for sequencing SARS-CoV-2 from wastewater samples. Second, it outlines best practices for gathering and organizing population-level next generation sequencing (NGS) data collected for culture-free, surveillance of pathogens sourced from environmental samples.

Crykey: Rapid identification of SARS-CoV-2 cryptic mutations in wastewater

Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2.

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.

Urban wastewater-based epidemiology for multi-viral pathogen surveillance in the Valencian region, Spain

Wastewater-based epidemiology (WBE) has lately arised as a promising tool for monitoring and tracking viral pathogens in communities. In this study, we analysed WBE's role as a multi-pathogen surveillance strategy to detect the presence of several viral illness causative agents. Thus, an epidemiological study was conducted from October 2021 to February 2023 to estimate the weekly levels of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), Respiratory Syncytial virus (RSV), and Influenza A virus (IAV) in influent wastewater samples (n = 69). In parallel, a one-year study (October 2021 to October 2022) was performed to assess the presence of pathogenic human enteric viruses. Besides, monitoring of proposed viral fecal contamination indicators crAssphage and Pepper mild mottle virus (PMMoV) was also assessed, along with plaque counting of somatic coliphages. Genetic material of rotavirus (RV), human astrovirus (HAStV), and norovirus genogroup I (GI) and GII was found in almost all samples, while hepatitis A and E viruses (HAV and HEV) only tested positive in 3.77 % and 22.64 % of the samples, respectively. No seasonal patterns were overall found for enteric viruses, although RVs had a peak prevalence in the winter months. All samples tested positive for SARS-CoV-2 RNA, with a mean concentration of 5.43 log genome copies per liter (log GC/L). The tracking of the circulating SARS-CoV-2 variants of concern (VOCs) was performed by both duplex RT-qPCR and next generation sequencing (NGS). Both techniques reliably showed how the dominant VOC transitioned from Delta to Omicron during two weeks in Spain in December 2021. RSV and IAV viruses peaked in winter months with mean concentrations 6.40 and 4.10 log GC/L, respectively. Moreover, the three selected respiratory viruses strongly correlated with reported clinical data when normalised by wastewater physico-chemical parameters and presented weaker correlations when normalising sewage concentration levels with crAssphage or somatic coliphages titers. Finally, predictive models were generated for each respiratory virus, confirming high reliability on WBE data as an early-warning system and communities illness monitoring system. Overall, this study presents WBE as an optimal tool for multi-pathogen tracking reflecting viral circulation and diseases trends within a selected area, its value as a multi-pathogen early-warning tool stands out due to its public health interest.

Evaluation of the Impact of Concentration and Extraction Methods on the Targeted Sequencing of Human Viruses from Wastewater

Sequencing human viruses in wastewater is challenging due to their low abundance compared to the total microbial background. This study compared the impact of four virus concentration/extraction methods (Innovaprep, Nanotrap, Promega, and Solids extraction) on probe-capture enrichment for human viruses followed by sequencing. Different concentration/extraction methods yielded distinct virus profiles. Innovaprep ultrafiltration (following solids removal) had the highest sequencing sensitivity and richness, resulting in the successful assembly of several near-complete human virus genomes. However, it was less sensitive in detecting SARS-CoV-2 by digital polymerase chain reaction (dPCR) compared to Promega and Nanotrap. Across all preparation methods, astroviruses and polyomaviruses were the most highly abundant human viruses, and SARS-CoV-2 was rare. These findings suggest that sequencing success can be increased using methods that reduce nontarget nucleic acids in the extract, though the absolute concentration of total extracted nucleic acid, as indicated by Qubit, and targeted viruses, as indicated by dPCR, may not be directly related to targeted sequencing performance. Further, using broadly targeted sequencing panels may capture viral diversity but risks losing signals for specific low-abundance viruses. Overall, this study highlights the importance of aligning wet lab and bioinformatic methods with specific goals when employing probe-capture enrichment for human virus sequencing from wastewater.

Considerations and Opportunities for Probe Capture Enrichment Sequencing of Emerging Viruses from Wastewater

Until recently, wastewater-based monitoring for pathogens of public health concern primarily used PCR-based quantification methods and targeted sequencing for specific pathogens (e.g., SARS-CoV-2). In the past three years, researchers have expanded sequencing to monitor a broad range of pathogens, applying probe capture enrichment to wastewater. The goals of those studies included (1) monitoring and expanding fundamental knowledge of disease dynamics for known pathogens and (2) evaluating the potential for early detection of emerging diseases resulting from zoonotic spillover or novel viral variants. Several studies using off-the-shelf probe panels designed for clinical and environmental surveillance reported that enrichment increased virus relative abundance but did not recover complete genomes for most nonenteric viruses. Based on our experience and recent results reported by others using these panels for wastewater, clinical, and synthetic samples, we discuss challenges and technical factors that affect the rates of false positive and false negative results. We identify trade-offs and opportunities throughout the workflow, including in wastewater sample processing, probe panel design, and bioinformatic analysis. We suggest tailored methods of virus concentration and background removal, carefully designed probe panels, and multithresholded bioinformatics analysis.

Campus source to sink wastewater surveillance of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)

Wastewater-based surveillance (WBS) offers an aggregate, and cost-effective approach for tracking infectious disease outbreak prevalence within communities, that provides data on community health complementary to individual clinical testing. This study reports on a 16-month WBS initiative on a university campus in England, UK, assessing the presence of SARS-CoV-2 in sewers from large buildings, downstream sewer locations, raw wastewater, partially treated and treated effluents. Key findings include the detection of the Alpha (B.1.1.7) variant in wastewater, with 70 % of confirmed campus cases correlating with positive wastewater samples. Notably, ammonium nitrogen (NH4-N) levels showed a positive correlation (ρ = 0.543, p < 0.01) with virus levels at the large building scale, a relationship not observed at the sewer or wastewater treatment works (WWTW) levels due to dilution. The WWTW was compliant to wastewater standards, but the secondary treatment processes were not efficient for virus removal as SARS-CoV-2 was consistently detected in treated discharges. Tools developed through WBS can also be used to enhance traditional environmental monitoring of aquatic systems. This study provides a detailed source-to-sink evaluation, emphasizing the critical need for the widespread application and improvement of WBS. It showcases WBS utility and reinforces the ongoing challenges posed by viruses to receiving water quality.

Wastewater tiling amplicon sequencing in sentinel sites reveals longitudinal dynamics of SARS-CoV-2 variants prevalence

The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

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.

Fast and accurate variant identification tool for sequencing-based studies

BACKGROUND

Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness.

RESULTS

We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations.

CONCLUSIONS

We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants .

Systematic SARS-CoV-2 S-gene sequencing in wastewater samples enables early lineage detection and uncovers rare mutations in Portugal

As the COVID-19 pandemic reached its peak, many countries implemented genomic surveillance systems to track the evolution and transmission of SARS-CoV-2. Transition from the pandemic to the endemic phase prioritized alternative testing strategies to maintain effective epidemic surveillance at the population level, with less intensive sequencing efforts. One such promising approach was Wastewater-Based Surveillance (WBS), which offers non-invasive, cost-effective means for analysing virus trends at the sewershed level. From 2020 onwards, wastewater has been recognized as an instrumental source of information for public health, with national and international authorities exploring options to implement national wastewater surveillance systems and increasingly relying on WBS as early warning of potential pathogen outbreaks. In Portugal, several pioneer projects joined the academia, water utilities and Public Administration around WBS. To validate WBS as an effective genomic surveillance strategy, it is crucial to collect long term performance data. In this work, we present one year of systematic SARS-CoV-2 wastewater surveillance in Portugal, representing 35 % of the mainland population. We employed two complementary methods for lineage determination - allelic discrimination by RT-PCR and S-gene sequencing. This combination allowed us to monitor variant evolution in near-real-time and identify low-frequency mutations. Over the course of this year-long study, spanning from May 2022 to April 2023, we successfully tracked the dominant Omicron sub-lineages, their progression and evolution, which aligned with concurrent clinical surveillance data. Our results underscore the effectiveness of WBS as a tracking system for virus variants, with the ability to unveil mutations undetected via massive sequencing of clinical samples from Portugal, demonstrating the ability of WBS to uncover new mutations and detect rare genetic variants. Our findings emphasize that knowledge of the genetic diversity of SARS-CoV-2 at the population level can be extended far beyond via the combination of routine clinical genomic surveillance with wastewater sequencing and genotyping.

Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants may have different characteristics, e.g., in transmission, mortality, and the effectiveness of vaccines, indicating the importance of variant detection at the population level. Wastewater-based surveillance of SARS-CoV-2 RNA fragments has been shown to be an effective way to monitor the COVID-19 pandemic at the population level. Wastewater is a complex sample matrix affected by environmental factors and PCR inhibitors, causing insufficient coverage in sequencing, for example. Subsequently, results where part of the genome does not have sufficient coverage are not uncommon. To identify variants and their proportions in wastewater over time, we utilized next-generation sequencing with the ARTIC Network's primer set and bioinformatics pipeline to evaluate the presence of variants in partial genome data. Based on the wastewater data from November 2021 to February 2022, the Delta variant was dominant until mid-December in Helsinki, Finland's capital, and thereafter in late December 2022 Omicron became the most common variant. At the same time, the Omicron variant of SARS-CoV-2 outcompeted the previous Delta variant in Finland in new COVID-19 cases. The SARS-CoV-2 variant findings from wastewater are in agreement with the variant information obtained from the patient samples when visually comparing trends in the sewerage network area. This indicates that the sequencing of wastewater is an effective way to monitor temporal and spatial trends of SARS-CoV-2 variants at the population level.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

Prevalence of SARS-CoV-2 variants in Prague wastewater determined by nanopore-based sequencing

The early detection of upcoming disease outbreaks is essential to avoid both health and economic damage. The last four years of COVID-19 pandemic have proven wastewater-based epidemiology is a reliable system for monitoring the spread of SARS-CoV-2, a causative agent of COVID-19, in an urban population. As this monitoring enables the identification of the prevalence of spreading variants of SARS-CoV-2, it could provide a critical tool in the fight against this viral disease. In this study, we evaluated the presence of variants and subvariants of SARS-CoV-2 in Prague wastewater using nanopore-based sequencing. During August 2021, the data clearly showed that the number of identified SARS-CoV-2 RNA copies increased in the wastewater earlier than in clinical samples indicating the upcoming wave of the Delta variant. New SARS-CoV-2 variants consistently prevailed in wastewater samples around a month after they already prevailed in clinical samples. We also analyzed wastewater samples from smaller sub-sewersheds of Prague and detected significant differences in SARS-CoV-2 lineage progression dynamics among individual localities studied, e.g., suggesting faster prevalence of new variants among the sites with highest population density and mobility.

Possible Spreading of SARS-CoV-2 from Humans to Captive Non-Human Primates in the Peruvian Amazon

Human-to-animal transmission events of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) have been reported in both domestic and wild species worldwide. Despite the high rates of contagion and mortality during the COVID-19 (Coronavirus Diseases 2019) pandemic in Peru, no instances of natural virus infection have been documented in wild animals, particularly in the Amazonian regions where human-wildlife interactions are prevalent. In this study, we conducted a surveillance investigation using viral RNA sequencing of fecal samples collected from 76 captive and semi-captive non-human primates (NHPs) in the Loreto, Ucayali, and Madre de Dios regions between August 2022 and February 2023. We detected a segment of the RNA-dependent RNA polymerase (RdRp) gene of SARS-CoV-2 by metagenomic sequencing in a pooled fecal sample from captive white-fronted capuchins (Cebus unicolor) at a rescue center in Bello Horizonte, Ucayali. Phylogenetic analysis further confirmed that the retrieved partial sequence of the RdRp gene matched the SARS-CoV-2 genome. This study represents the first documented instance of molecular SARS-CoV-2 detection in NHPs in the Peruvian Amazon, underscoring the adverse impact of anthropic activities on the human-NHP interface and emphasizing the importance of ongoing surveillance for early detection and prediction of future emergence of new SARS-CoV-2 variants in animals.

Identification of SARS-CoV-2 variants in indoor dust

Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.

Emergence and spread of SARS-CoV-2 variants of concern in Canada: a retrospective analysis from clinical and wastewater data

BACKGROUND

The spread of SARS-CoV-2 has been studied at unprecedented levels worldwide. In jurisdictions where molecular analysis was performed on large scales, the emergence and competition of numerous SARS-CoV-2lineages have been observed in near real-time. Lineage identification, traditionally performed from clinical samples, can also be determined by sampling wastewater from sewersheds serving populations of interest. Variants of concern (VOCs) and SARS-CoV-2 lineages associated with increased transmissibility and/or severity are of particular interest.

METHOD

Here, we consider clinical and wastewater data sources to assess the emergence and spread of VOCs in Canada retrospectively.

RESULTS

We show that, overall, wastewater-based VOC identification provides similar insights to the surveillance based on clinical samples. Based on clinical data, we observed synchrony in VOC introduction as well as similar emergence speeds across most Canadian provinces despite the large geographical size of the country and differences in provincial public health measures.

CONCLUSION

In particular, it took approximately four months for VOC Alpha and Delta to contribute to half of the incidence. In contrast, VOC Omicron achieved the same contribution in less than one month. This study provides significant benchmarks to enhance planning for future VOCs, and to some extent for future pandemics caused by other pathogens, by quantifying the rate of SARS-CoV-2 VOCs invasion in Canada.

COVID-19 hospitalizations and deaths predicted by SARS-CoV-2 levels in Boise, Idaho wastewater

The viral load of COVID-19 in untreated wastewater from Idaho's capital city Boise, ID (Ada County) has been used to predict changes in hospital admissions (statewide in Idaho) and deaths (Ada County) using distributed fixed lag modeling and artificial neural networks (ANN). The wastewater viral counts were used to determine the lag time between peaks in wastewater viral counts and COVID-19 hospitalizations as well as deaths (14 and 23 days, respectively). Quantitative measurement of SARS-CoV-2 viral RNA counts in the untreated wastewater was determined three times a week using RT-qPCR over a span of 13 months. To mitigate the effects of PCR inhibitors in wastewater, a series of dilution tests were conducted, and the 1/4 dilution was used to generate the most successful model. Wastewater SARS-CoV-2 viral RNA counts and hospitalization from June 7, 2021 to December 29, 2021 were used as training data to predict hospitalizations; and wastewater SARS-CoV-2 viral RNA counts and deaths from June 7, 2021 to December 20, 2021 were used as training data to predict deaths. These training data were used to make predictive ANN models for future hospitalizations and deaths. To the best of our knowledge, this is the first report of prediction of deaths from COVID-19 based on wastewater SARS-CoV-2 viral RNA counts using machine learning-based multilayered ANN. The applied modeling demonstrates that wastewater surveillance data can be combined with hospitalizations and death data to generate machine learning-based ANN models that predict future COVID-19 hospital admissions and deaths, providing an early warning for medical response teams and healthcare policymakers.

SARS-CoV-2 Detection and Genome Sequencing in Urban Wastewaters

Due to the excretion of SARS-CoV-2 in faeces, the use of wastewater-based epidemiology (WBE) is a useful tool for virus surveillance in large populations. The analysis of this virus includes a concentration step prior to virus detection by RT-qPCR. In addition, the use of massive sequencing allows the detection of specific mutations of clinical importance, as well as the detection of the introduction of new lineages in a specific population. In this chapter, we describe the analysis of SARS-CoV-2 in urban wastewater by the concentration of the samples by precipitation with aluminum chloride, the detection, and quantification of SARS-CoV-2 RNA by RT-qPCR and the genomic sequencing using two different sequencing platforms.

Evolution of the SARS-CoV-2 Omicron spike

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern, first identified in November 2021, rapidly spread worldwide and diversified into several subvariants. The Omicron spike (S) protein accumulated an unprecedented number of sequence changes relative to previous variants. In this review, we discuss how Omicron S protein structural features modulate host cell receptor binding, virus entry, and immune evasion and highlight how these structural features differentiate Omicron from previous variants. We also examine how key structural properties track across the still-evolving Omicron subvariants and the importance of continuing surveillance of the S protein sequence evolution over time.

To sample or not to sample: A governance-focused decision tree for wastewater service providers considering participation in wastewater-based epidemiology (WBE) in support of public health programs

Wastewater-based epidemiology (WBE) provides value to public health monitoring and protection. Participation of public and private wastewater system operators in WBE efforts is critical to public health surveillance program success and sustainability. However, given the number of WBE solicitations wastewater service providers receive, the limitation of service provider resources, the concerns around privacy, ethics, and equity, and the fatigue associated with responding to COVID-19, operators are becoming more hesitant to participate in WBE efforts. While various ethical concerns and sustainability challenges associated with WBE have been documented, no efforts to date have investigated what factors should systematically influence the decision to provide samples to a WBE effort. Therefore, this study develops a decision-making tool for WBE teams to proactively monitor, manage, and avoid wastewater system operators' operational risks and potential liabilities. Ultimately, using this tool allows WBE program partners in academia, government, and industry to better understand wastewater system operators' needs and challenges surrounding data quality and use, public health ethics, and daily wastewater infrastructure operation.

Comparison of metagenomic and targeted methods for sequencing human pathogenic viruses from wastewater

IMPORTANCE

Most public health initiatives that monitor viruses in wastewater have utilized quantitative polymerase chain reaction (PCR) and whole genome PCR sequencing, mirroring techniques used for viral epidemiology in individuals. These techniques require prior knowledge of the target viral genome and are limited to monitoring individual or small groups of viruses. Metagenomic sequencing may offer an alternative strategy for monitoring a broad spectrum of viruses in wastewater, including novel and emerging pathogens. In this study, while amplicon sequencing gave high viral genome coverage, untargeted shotgun sequencing of total nucleic acid samples was unable to detect human pathogenic viruses with enough sensitivity for use in genomic epidemiology. Enrichment of shotgun libraries for respiratory viruses using hybrid-capture technology provided genotypic information on a range of viruses simultaneously, indicating strong potential for wastewater surveillance. This type of targeted metagenomics could be used for monitoring diverse targets, such as pathogens or antimicrobial resistance genes, in environmental samples.

Epidemiological Insights into the Omicron Outbreak via MeltArray-Assisted Real-Time Tracking of SARS-CoV-2 Variants

The prolonged course of the COVID-19 pandemic necessitates sustained surveillance of emerging variants. This study aimed to develop a multiplex real-time polymerase chain reaction (rt-PCR) suitable for the real-time tracking of Omicron subvariants in clinical and wastewater samples. Plasmids containing variant-specific mutations were used to develop a MeltArray assay. After a comprehensive evaluation of both analytical and clinical performance, the established assay was used to detect Omicron variants in clinical and wastewater samples, and the results were compared with those of next-generation sequencing (NGS) and droplet digital PCR (ddPCR). The MeltArray assay identified 14 variant-specific mutations, enabling the detection of five Omicron sublineages (BA.2*, BA.5.2*, BA.2.75*, BQ.1*, and XBB.1*) and eight subvariants (BF.7, BN.1, BR.2, BQ.1.1, XBB.1.5, XBB.1.16, XBB.1.9, and BA.4.6). The limit of detection (LOD) of the assay was 50 copies/reaction, and no cross-reactivity was observed with 15 other respiratory viruses. Using NGS as the reference method, the clinical evaluation of 232 swab samples exhibited a clinical sensitivity of > 95.12% (95% CI 89.77-97.75%) and a specificity of > 95.21% (95% CI, 91.15-97.46%). When used to evaluate the Omicron outbreak from late 2022 to early 2023, the MeltArray assay performed on 1408 samples revealed that the epidemic was driven by BA.5.2* (883, 62.71%) and BF.7 (525, 37.29%). Additionally, the MeltArray assay demonstrated potential for estimating variant abundance in wastewater samples. The MeltArray assay is a rapid and scalable method for identifying SARS-CoV-2 variants. Integrating this approach with NGS and ddPCR will improve variant surveillance capabilities and ensure preparedness for future variants.

Genomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India

The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods to detect and monitor the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool for proactive analysis and quantification of infectious pathogens within a population before clinical cases emerge. In the present study, we aimed to assess the trend and dynamics of SARS-CoV-2 variants using a longitudinal approach. Our objective included early detection and monitoring of these variants to enhance our understanding of their prevalence and potential impact. To achieve our goals, we conducted real-time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing on 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) in Pune city, India, spanning from November 2021 to April 2022. Our comprehensive analysis identified 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2. Notably, fragments of Omicron variant were detected in WW samples prior to its first clinical detection in Botswana. Furthermore, we observed highly contagious sub-lineages of the Omicron variant, including BA.1 (~28%), BA.1.X (1.0-72%), BA.2 (1.0-18%), BA.2.X (1.0-97.4%) BA.2.12 (0.8-0.25%), BA.2.38 (0.8-1.0%), BA.2.75 (0.01-0.02%), BA.3 (0.09-6.3%), BA.4 (0.24-0.29%), and XBB (0.01-21.83%), with varying prevalence rates. Overall, the present study demonstrated the practicality of WBE in the early detection of SARS-CoV-2 variants, which could help track future outbreaks of SARS-CoV-2. Such approaches could be implicated in monitoring infectious agents before they appear in clinical cases.

Impact of heat-treatment on wastewater analytical parameters

Raw wastewater analysis is an important step in treatment assessment; however, it is associated with risks of personnel exposure to pathogens. Such risks are enhanced during virus outbreaks, such as the COVID pandemic, and heat-treatment is a commonly used mitigation measure. We examined whether heat-treatment compromises wastewater analytical parameters results. We found that heat-treatment of blackwater at 60 °C for 90 min in capped containers yielded no statistically different values (p > 0.05) for pH, chemical oxygen demand (COD), ammonia (NH3), total nitrogen (TN), total suspended solids (TSS), and turbidity for specimens from three different sources. This heat-treatment inactivated coliform bacteria (>4 log10 reduction) thus compromising the measurement of commonly used fecal contamination indicators. The observation of intact helminth eggs in heat-treated specimens suggests that the helminth egg enumeration assay is not compromised. These findings indicate that heat-treatment for the safe handling of wastewater, as may be needed in future virus outbreaks, does not affect the measurements of many common wastewater physico-chemical properties.

Utility of wastewater genomic surveillance compared to clinical surveillance to track the spread of the SARS-CoV-2 Omicron variant across England

The world has moved into a new stage of managing the SARS-CoV-2 pandemic with minimal restrictions and reduced testing in the population, leading to reduced genomic surveillance of virus variants in individuals. Wastewater-based epidemiology (WBE) can provide an alternative means of tracking virus variants in the population but decision-makers require confidence that it can be applied to a national scale and is comparable to individual testing data. We analysed 19,911 samples from 524 wastewater sites across England at least twice a week between November 2021 and February 2022, capturing sewage from >70% of the English population. We used amplicon-based sequencing and the phylogeny based de-mixing tool Freyja to estimate SARS-CoV-2 variant frequencies and compared these to the variant dynamics observed in individual testing data from clinical and community settings. We show that wastewater data can reconstruct the spread of the Omicron variant across England since November 2021 in close detail and aligns closely with epidemiological estimates from individual testing data. We also show the temporal and spatial spread of Omicron within London. Our wastewater data further reliably track the transition between Omicron subvariants BA1 and BA2 in February 2022 at regional and national levels. Our demonstration that WBE can track the fast-paced dynamics of SARS-CoV-2 variant frequencies at a national scale and closely match individual testing data in time shows that WBE can reliably fill the monitoring gap left by reduced individual testing in a more affordable way.

Wastewater surveillance monitoring of SARS-CoV-2 variants of concern and dynamics of transmission and community burden of COVID-19

Wastewater-based surveillance is a valuable approach for monitoring COVID-19 at community level. Monitoring SARS-CoV-2 variants of concern (VOC) in wastewater has become increasingly relevant when clinical testing capacity and case-based surveillance are limited. In this study, we ascertained the turnover of six VOC in Alberta wastewater from May 2020 to May 2022. Wastewater samples from nine wastewater treatment plants across Alberta were analysed using VOC-specific RT-qPCR assays. The performance of the RT-qPCR assays in identifying VOC in wastewater was evaluated against next generation sequencing. The relative abundance of each VOC in wastewater was compared to positivity rate in COVID-19 testing. VOC-specific RT-qPCR assays performed comparatively well against next generation sequencing; concordance rates ranged from 89% to 98% for detection of Alpha, Beta, Gamma, Omicron BA.1 and Omicron BA.2, with a slightly lower rate of 85% for Delta (p < 0.01). Elevated relative abundance of Alpha, Delta, Omicron BA.1 and BA.2 were each associated with increased COVID-19 positivity rate. Alpha, Delta and Omicron BA.2 reached 90% relative abundance in wastewater within 80, 111 and 62 days after their initial detection, respectively. Omicron BA.1 increased more rapidly, reaching a 90% relative abundance in wastewater after 35 days. Our results from VOC surveillance in wastewater correspond with clinical observations that Omicron is the VOC with highest disease burden over the shortest period in Alberta to date. The findings suggest that changes in relative abundance of a VOC in wastewater can be used as a supplementary indicator to track and perhaps predict COVID-19 burden in a population.

Utilizing river and wastewater as a SARS-CoV-2 surveillance tool in settings with limited formal sewage systems

The COVID-19 pandemic has profoundly impacted health systems globally and robust surveillance has been critical for pandemic control, however not all countries can currently sustain community pathogen surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but less is known about the utility of water surveillance of pathogens in low-income countries. Here we show how wastewater surveillance of SAR-CoV-2 can be used to identify temporal changes and help determine circulating variants quickly. In Malawi, a country with limited community-based COVID-19 testing capacity, we explore the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020-May 2022, we collect water from up to 112 river or defunct wastewater treatment plant sites, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predate peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights how wastewater can be used to detect emerging waves, identify variants of concern, and provide an early warning system in settings with no formal sewage systems.

Crykey: Rapid Identification of SARS-CoV-2 Cryptic Mutations in Wastewater

We present Crykey, a computational tool for rapidly identifying cryptic mutations of SARS-CoV-2. Specifically, we identify co-occurring single nucleotide mutations on the same sequencing read, called linked-read mutations, that are rare or entirely missing in existing databases, and have the potential to represent novel cryptic lineages found in wastewater. While previous approaches exist for identifying cryptic linked-read mutations from specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and for tens of thousands of samples and with increased scrutiny, given their potential to represent either artifacts or hidden SARS-CoV-2 lineages. Crykey fills this gap by identifying rare linked-read mutations that pass stringent computational filters to limit the potential for artifacts. We evaluate the utility of Crykey on >3,000 wastewater and >22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over a three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations representing potential cryptic lineages in wastewater.

Sequencing of SARS-CoV-2 RNA Fragments in Wastewater Detects the Spread of New Variants during Major Events

The sequencing of SARS-CoV-2 RNA in wastewater is an unbiased method to detect the spread of emerging variants and to track regional infection dynamics, which is especially useful in case of limited testing and clinical sequencing. To test how major international events influence the spread of new variants we have sequenced SARS-CoV-2 RNA in the wastewater samples of Davos, Landquart, Lostallo, and St. Moritz in the Swiss canton of Grisons in the time around the international sports competitions in Davos and St. Moritz in December 2021, and additionally in May 2022 and January 2023 in Davos and St. Moritz during the World Economic Forum (WEF) in Davos. The prevalence of the variants identified from the wastewater sequencing data showed that the Omicron variant BA.1 had spread in Davos and St. Moritz during the international sporting events hosted there in December 2021. This spread was associated with an increase in case numbers, while it was not observed in Landquart and Lostallo. Another instance of new variant spread occurred during the WEF in January 2023, when the Omicron variant BA.2.75 arrived in Davos but not in St. Moritz. We can therefore conclude that major international events promote the spread of new variants in the respective host region, which has important implications for the protective measures that should be taken.

Wastewater sequencing reveals community and variant dynamics of the collective human virome

Wastewater is a discarded human by-product, but its analysis may help us understand the health of populations. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels while bypassing the difficulties and pit falls of individual testing. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. Here, we conduct a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Critical to detection is the use of a viral probe capture set targeting thousands of viral species or variants. Over 450 distinct pathogenic viruses from 28 viral families are observed, most of which have never been detected in such samples. Sequencing reads of established pathogens and emerging viruses correlate to clinical data sets of SARS-CoV-2, influenza virus, and monkeypox viruses, outlining the public health utility of this approach. Viral communities are tightly organized by space and time. Finally, the most abundant human viruses yield sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health.

Implementation of California COVIDNet - a multi-sector collaboration for statewide SARS-CoV-2 genomic surveillance

Introduction

The SARS-CoV-2 pandemic represented a formidable scientific and technological challenge to public health due to its rapid spread and evolution. To meet these challenges and to characterize the virus over time, the State of California established the California SARS-CoV-2 Whole Genome Sequencing (WGS) Initiative, or "California COVIDNet". This initiative constituted an unprecedented multi-sector collaborative effort to achieve large-scale genomic surveillance of SARS-CoV-2 across California to monitor the spread of variants within the state, to detect new and emerging variants, and to characterize outbreaks in congregate, workplace, and other settings.

Methods

California COVIDNet consists of 50 laboratory partners that include public health laboratories, private clinical diagnostic laboratories, and academic sequencing facilities as well as expert advisors, scientists, consultants, and contractors. Data management, sample sourcing and processing, and computational infrastructure were major challenges that had to be resolved in the midst of the pandemic chaos in order to conduct SARS-CoV-2 genomic surveillance. Data management, storage, and analytics needs were addressed with both conventional database applications and newer cloud-based data solutions, which also fulfilled computational requirements.

Results

Representative and randomly selected samples were sourced from state-sponsored community testing sites. Since March of 2021, California COVIDNet partners have contributed more than 450,000 SARS-CoV-2 genomes sequenced from remnant samples from both molecular and antigen tests. Combined with genomes from CDC-contracted WGS labs, there are currently nearly 800,000 genomes from all 61 local health jurisdictions (LHJs) in California in the COVIDNet sequence database. More than 5% of all reported positive tests in the state have been sequenced, with similar rates of sequencing across 5 major geographic regions in the state.

Discussion

Implementation of California COVIDNet revealed challenges and limitations in the public health system. These were overcome by engaging in novel partnerships that established a successful genomic surveillance program which provided valuable data to inform the COVID-19 public health response in California. Significantly, California COVIDNet has provided a foundational data framework and computational infrastructure needed to respond to future public health crises.

Regional reemergence of a SARS-CoV-2 Delta lineage amid an Omicron wave detected by wastewater sequencing

The implementation and integration of wastewater-based epidemiology constitutes a valuable addition to existing pathogen surveillance systems, such as clinical surveillance for SARS-CoV-2. In the Netherlands, SARS-CoV-2 variant circulation is monitored by performing whole-genome sequencing on wastewater samples. In this manuscript, we describe the detection of an AY.43 lineage (Delta variant) amid a period of BA.5 (Omicron variant) dominance in wastewater samples from two wastewater treatment plants (WWTPs) during the months of August and September of 2022. Our results describe a temporary emergence, which was absent in samples from other WWTPs, and which coincided with peaks in viral load. We show how these lineage estimates can be traced back to lineage-specific substitution patterns. The absence of this variant from reported clinical data, but high associated viral loads suggest cryptic transmission. Our findings highlight the additional value of wastewater surveillance for generating insights into circulating pathogens.

SARS-CoV-2 genomic surveillance in wastewater as a model for monitoring evolution of endemic viruses

As global SARS-CoV-2 burden and testing frequency have decreased, wastewater surveillance has emerged as a key tool to support clinical surveillance efforts. The aims of this study were to identify and characterize SARS-CoV-2 variants in wastewater samples collected from urban centers across South Africa. Here we show that wastewater sequencing analyses are temporally concordant with clinical genomic surveillance and reveal the presence of multiple lineages not detected by clinical surveillance. We show that wastewater genomics can support SARS-CoV-2 epidemiological investigations by reliably recovering the prevalence of local circulating variants, even when clinical samples are not available. Further, we find that analysis of mutations observed in wastewater can provide a signal of upcoming lineage transitions. Our study demonstrates the utility of wastewater genomics to monitor evolution and spread of endemic viruses.

Microbiome Interconnectedness throughout Environments with Major Consequences for Healthy People and a Healthy Planet

Microbiomes have highly important roles for ecosystem functioning and carry out key functions that support planetary health, including nutrient cycling, climate regulation, and water filtration. Microbiomes are also intimately associated with complex multicellular organisms such as humans, other animals, plants, and insects and perform crucial roles for the health of their hosts. Although we are starting to understand that microbiomes in different systems are interconnected, there is still a poor understanding of microbiome transfer and connectivity. In this review we show how microbiomes are connected within and transferred between different habitats and discuss the functional consequences of these connections. Microbiome transfer occurs between and within abiotic (e.g., air, soil, and water) and biotic environments, and can either be mediated through different vectors (e.g., insects or food) or direct interactions. Such transfer processes may also include the transmission of pathogens or antibiotic resistance genes. However, here, we highlight the fact that microbiome transmission can have positive effects on planetary and human health, where transmitted microorganisms potentially providing novel functions may be important for the adaptation of ecosystems.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

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

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

Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.

Wastewater Genomic Surveillance Captures Early Detection of Omicron in Utah

Wastewater-based epidemiology has emerged as a powerful public health tool to trace new outbreaks, detect trends in infection, and provide an early warning of COVID-19 community spread. Here, we investigated the spread of SARS-CoV-2 infections across Utah by characterizing lineages and mutations detected in wastewater samples. We sequenced over 1,200 samples from 32 sewersheds collected between November 2021 and March 2022. Wastewater sequencing confirmed the presence of Omicron (B.1.1.529) in Utah in samples collected on November 19, 2021, up to 10 days before its corresponding detection via clinical sequencing. Analysis of diversity of SARS-CoV-2 lineages revealed Delta as the most frequently detected lineage during November 2021 (67.71%), but it started declining in December 2021 with the onset of Omicron (B.1.1529) and its sublineage BA.1 (6.79%). The proportion of Omicron increased to ~58% by January 4, 2022, and completely displaced Delta by February 7, 2022. Wastewater genomic surveillance revealed the presence of Omicron sublineage BA.3, a lineage that was not identified from Utah's clinical surveillance. Interestingly, several Omicron-defining mutations began to appear in early November 2021 and increased in prevalence across sewersheds from December to January, aligning with the surge in clinical cases. Our study highlights the importance of tracking epidemiologically relevant mutations in detecting emerging lineages in the early stages of an outbreak. Wastewater genomic epidemiology provides an unbiased representation of community-wide infection dynamics and is an excellent complementary tool to SARS-CoV-2 clinical surveillance, with the potential of guiding public health action and policy decisions. IMPORTANCE SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has had a significant impact on public health. Global emergence of novel SARS-CoV-2 variants, shift to at-home tests, and reduction in clinical tests demonstrate the need for a reliable and effective surveillance strategy to contain COVID-19 spread. Monitoring of SARS-CoV-2 viruses in wastewater is an effective way to trace new outbreaks, establish baseline levels of infection, and complement clinical surveillance efforts. Wastewater genomic surveillance, in particular, can provide valuable insights into the evolution and spread of SARS-CoV-2 variants. We characterized the diversity of SARS-CoV-2 mutations and lineages using whole-genome sequencing to trace the introduction of lineage B.1.1.519 (Omicron) in Utah. Our data showed that Omicron appeared in Utah on November 19, 2021, up to 10 days prior to its detection in patient samples, indicating that wastewater surveillance provides an early warning signal. Our findings are important from a public health perspective as timely identification of communities with high COVID-19 transmission could help guide public health interventions.

Wastewater surveillance uncovers regional diversity and dynamics of SARS-CoV-2 variants across nine states in the USA

Wastewater-based epidemiology (WBE) is a non-invasive and cost-effective approach for monitoring the spread of a pathogen within a community. WBE has been adopted as one of the methods to monitor the spread and population dynamics of the SARS-CoV-2 virus, but significant challenges remain in the bioinformatic analysis of WBE-derived data. Here, we have developed a new distance metric, CoVdist, and an associated analysis tool that facilitates the application of ordination analysis to WBE data and the identification of viral population changes based on nucleotide variants. We applied these new approaches to a large-scale dataset from 18 cities in nine states of the USA using wastewater collected from July 2021 to June 2022. We found that the trends in the shift between the Delta and Omicron SARS-CoV-2 lineages were largely consistent with what was seen in clinical data, but that wastewater analysis offered the added benefit of revealing significant differences in viral population dynamics at the state, city, and even neighborhood scales. We also were able to observe the early spread of variants of concern and the presence of recombinant lineages during the transitions between variants, both of which are challenging to analyze based on clinically-derived viral genomes. The methods outlined here will be beneficial for future applications of WBE to monitor SARS-CoV-2, particularly as clinical monitoring becomes less prevalent. Additionally, these approaches are generalizable, allowing them to be applied for the monitoring and analysis of future viral outbreaks.

Structured Ethical Review for Wastewater-Based Testing

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

Abstract Figure

Synopsis

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

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. A synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation patterns, which could also explain the observed inconsistency between qPCR quantification and sequencing outcomes. Overall, extra attention should be paid to wastewater sample processing (i.e., concentration and homogenization) for sufficient and good quality SARS-CoV-2 RNA for downstream sequencing.

Inadvertent human genomic bycatch and intentional capture raise beneficial applications and ethical concerns with environmental DNA

The field of environmental DNA (eDNA) is advancing rapidly, yet human eDNA applications remain underutilized and underconsidered. Broader adoption of eDNA analysis will produce many well-recognized benefits for pathogen surveillance, biodiversity monitoring, endangered and invasive species detection, and population genetics. Here we show that deep-sequencing-based eDNA approaches capture genomic information from humans (Homo sapiens) just as readily as that from the intended target species. We term this phenomenon human genetic bycatch (HGB). Additionally, high-quality human eDNA could be intentionally recovered from environmental substrates (water, sand and air), holding promise for beneficial medical, forensic and environmental applications. However, this also raises ethical dilemmas, from consent, privacy and surveillance to data ownership, requiring further consideration and potentially novel regulation. We present evidence that human eDNA is readily detectable from 'wildlife' environmental samples as human genetic bycatch, demonstrate that identifiable human DNA can be intentionally recovered from human-focused environmental sampling and discuss the translational and ethical implications of such findings.

A review of current effective COVID-19 testing methods and quality control

COVID-19 is a highly infectious disease caused by the SARS-CoV-2 virus, which primarily affects the respiratory system and can lead to severe illness. The virus is extremely contagious, early and accurate diagnosis of SARS-CoV-2 is crucial to contain its spread, to provide prompt treatment, and to prevent complications. Currently, the reverse transcriptase polymerase chain reaction (RT-PCR) is considered to be the gold standard for detecting COVID-19 in its early stages. In addition, loop-mediated isothermal amplification (LMAP), clustering rule interval short palindromic repeats (CRISPR), colloidal gold immunochromatographic assay (GICA), computed tomography (CT), and electrochemical sensors are also common tests. However, these different methods vary greatly in terms of their detection efficiency, specificity, accuracy, sensitivity, cost, and throughput. Besides, most of the current detection methods are conducted in central hospitals and laboratories, which is a great challenge for remote and underdeveloped areas. Therefore, it is essential to review the advantages and disadvantages of different COVID-19 detection methods, as well as the technology that can enhance detection efficiency and improve detection quality in greater details.

The spread of the omicron variant: Identification of knowledge gaps, virus diffusion modelling, and future research needs

The World Health Organization (WHO) recognised variant B.1.1.529 of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as a variant of concern, termed "Omicron", on November 26, 2021. Its diffusion was attributed to its several mutations, which allow promoting its ability to diffuse worldwide and its capability in immune evasion. As a consequence, some additional serious threats to public health posed the risk to undermine the global efforts made in the last two years to control the pandemic. In the past, several works were devoted to discussing a possible contribution of air pollution to the SARS-CoV-2 spread. However, to the best of the authors' knowledge, there are still no works dealing with the Omicron variant diffusion mechanisms. This work represents a snapshot of what we know right now, in the frame of an analysis of the Omicron variant spread. The paper proposes the use of a single indicator, commercial trade data, to model the virus spread. It is proposed as a surrogate of the interactions occurring between humans (the virus transmission mechanism due to human-to-human contacts) and could be considered for other diseases. It allows also to explain the unexpected increase in infection cases in China, detected at beginning of 2023. The air quality data are also analyzed to evaluate for the first time the role of air particulate matter (PM) as a carrier of the Omicron variant diffusion. Due to emerging concerns associated with other viruses (such as smallpox-like virus diffusion in Europe and America), the proposed approach seems to be promising to model the virus spreading.

Mapping human pathogens in wastewater using a metatranscriptomic approach

The monitoring of cities' wastewaters for the detection of potentially pathogenic viruses and bacteria has been considered a priority during the COVID-19 pandemic to monitor public health in urban environments. The methodological approaches frequently used for this purpose include deoxyribonucleic acid (DNA)/Ribonucleic acid (RNA) isolation followed by quantitative polymerase chain reaction (qPCR) and reverse transcription (RT)‒qPCR targeting pathogenic genes. More recently, the application of metatranscriptomic has opened opportunities to develop broad pathogenic monitoring workflows covering the entire pathogenic community within the sample. Nevertheless, the high amount of data generated in the process requires an appropriate analysis to detect the pathogenic community from the entire dataset. Here, an implementation of a bioinformatic workflow was developed to produce a map of the detected pathogenic bacteria and viruses in wastewater samples by analysing metatranscriptomic data. The main objectives of this work was the development of a computational methodology that can accurately detect both human pathogenic virus and bacteria in wastewater samples. This workflow can be easily reproducible with open-source software and uses efficient computational resources. The results showed that the used algorithms can predict potential human pathogens presence in the tested samples and that active forms of both bacteria and virus can be identified. By comparing the computational method implemented in this study to other state-of-the-art workflows, the implementation analysis was faster, while providing higher accuracy and sensitivity. Considering these results, the processes and methods to monitor wastewater for potential human pathogens can become faster and more accurate. The proposed workflow is available at https://github.com/waterpt/watermonitor and can be implemented in currently wastewater monitoring programs to ascertain the presence of potential human pathogenic species.