Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater.

As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QuaID, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).

Adeno-Associated Virus 2 and Human Adenovirus F41 in Wastewater during Outbreak of Severe Acute Hepatitis in Children, Ireland.

During April-July 2022, outbreaks of severe acute hepatitis of unknown etiology (SAHUE) were reported in 35 countries. Five percent of cases required liver transplantation, and 22 patients died. Viral metagenomic studies of clinical samples from SAHUE cases showed a correlation with human adenovirus F type 41 (HAdV-F41) and adeno-associated virus type 2 (AAV2). To explore the association between those DNA viruses and SAHUE in children in Ireland, we quantified HAdV-F41 and AAV2 in samples collected from a wastewater treatment plant serving 40% of Ireland's population. We noted a high correlation between HAdV-F41 and AAV2 circulation in the community and SAHUE clinical cases. Next-generation sequencing of the adenovirus hexon in wastewater demonstrated HAdV-F41 was the predominant HAdV type circulating. Our environmental analysis showed increased HAdV-F41 and AAV2 prevalence in the community during the SAHUE outbreak. Our findings highlight how wastewater sampling could aid in surveillance for respiratory adenovirus species.

Wastewater monitoring can anchor global disease surveillance systems.

To inform the development of global wastewater monitoring systems, we surveyed programmes in 43 countries. Most programmes monitored predominantly urban populations. In high-income countries (HICs), composite sampling at centralised treatment plants was most common, whereas grab sampling from surface waters, open drains, and pit latrines was more typical in low-income and middle-income countries (LMICs). Almost all programmes analysed samples in-country, with an average processing time of 2·3 days in HICs and 4·5 days in LMICs. Whereas 59% of HICs regularly monitored wastewater for SARS-CoV-2 variants, only 13% of LMICs did so. Most programmes share their wastewater data internally, with partnering organisations, but not publicly. Our findings show the richness of the existing wastewater monitoring ecosystem. With additional leadership, funding, and implementation frameworks, thousands of individual wastewater initiatives can coalesce into an integrated, sustainable network for disease surveillance-one that minimises the risk of overlooking future global health threats.

Opinions of former jail residents about self-collection of SARS-CoV-2 specimens, paired with wastewater surveillance: A qualitative study rapidly examining acceptability of COVID-19 mitigation measures.

In year one of the COVID-19 epidemic, the incidence of infection for US carceral populations was 5.5-fold higher than that in the community. Prior to the rapid roll out of a comprehensive jail surveillance program of Wastewater-Based Surveillance (WBS) and individual testing for SARS-CoV-2, we sought the perspectives of formerly incarcerated individuals regarding mitigation strategies against COVID-19 to inform acceptability of the new program. In focus groups, participants discussed barriers to their receiving COVID-19 testing and vaccination. We introduced WBS and individual nasal self-testing, then queried if wastewater testing to improve surveillance of emerging outbreaks before case numbers surged, and specimen self-collection, would be valued. The participants' input gives insight into ways to improve the delivery of COVID-19 interventions. Hearing the voices of those with lived experiences of incarceration is critical to understanding their views on infection control strategies and supports including justice-involved individuals in decision-making processes regarding jail-based interventions.

Utilizing a National Wastewater Monitoring Program to Address the U.S. Opioid Epidemic: A Focus on Metro Atlanta, Georgia.

The opioid epidemic has continued to be an ongoing public health crisis within Metro Atlanta for the last three decades. However, estimating opioid use and exposure in a large population is almost impossible, and alternative methods are being explored, including wastewater-based epidemiology. Wastewater contains various contaminants that can be monitored to track pathogens, infectious diseases, viruses, opioids, and more. This commentary is focusing on two issues: use of opioid residue data in wastewater as an alternative method for opioid exposure assessment in the community, and the adoption of a streamlined approach that can be utilized by public health officials. Opioid metabolites travel through the sanitary sewer through urine, fecal matter, and improper disposal of opioids to local wastewater treatment plants. Public health officials and researchers within various entities have utilized numerous approaches to reduce the impacts associated with opioid use. National wastewater monitoring programs and wastewater-based epidemiology are approaches that have been utilized globally by researchers and public health officials to combat the opioid epidemic. Currently, public health officials and policy makers within Metro Atlanta are exploring different solutions to reduce opioid use and opioid-related deaths throughout the community. In this commentary, we are proposing a new innovative approach for monitoring opioid use and analyzing trends by utilizing wastewater-based epidemiologic methods, which may help public health officials worldwide manage the opioid epidemic in a large metro area in the future.

Global trends in the research and development of medical/pharmaceutical wastewater treatment over the half-century.

The COVID-19 pandemic has severely impacted public health and the worldwide economy. The overstretched operation of health systems around the world is accompanied by potential and ongoing environmental threats. At present, comprehensive scientific assessments of research on temporal changes in medical/pharmaceutical wastewater (MPWW), as well as estimations of researcher networks and scientific productivity are lacking. Therefore, we conducted a thorough literature study, using bibliometrics to reproduce research on medical wastewater over nearly half a century. Our primary goal is systematically to map the evolution of keyword clusters over time, and to obtain the structure and credibility of clusters. Our secondary objective was to measure research network performance (country, institution, and author) using CiteSpace and VOSviewer. We extracted 2306 papers published between 1981 and 2022. The co-cited reference network identified 16 clusters with well-structured networks (Q = 0.7716, S = 0.896). The main trends were as follows: 1) Early MPWW research prioritized sources of wastewater, and this cluster was considered to be the mainstream research frontier and direction, representing an important source and priority research area. 2) Mid-term research focused on characteristic contaminants and detection technologies. Particularly during 2000-2010, a period of rapid developments in global medical systems, pharmaceutical compounds (PhCs) in MPWW were recognized as a major threat to human health and the environment. 3) Recent research has focused on novel degradation technologies for PhC-containing MPWW, with high scores for research on biological methods. Wastewater-based epidemiology has emerged as being consistent with or predictive of the number of confirmed COVID-19 cases. Therefore, the application of MPWW in COVID-19 tracing will be of great interest to environmentalists. These results could guide the future direction of funding agencies and research groups.

SARS-CoV-2 Variants Detection Strategies in Wastewater Samples Collected in the Bangkok Metropolitan Region.

Wastewater surveillance is considered a promising approach for COVID-19 surveillance in communities. In this study, we collected wastewater samples between November 2020 and February 2022 from twenty-three sites in the Bangkok Metropolitan Region to detect the presence of SARS-CoV-2 and its variants for comparison to standard clinical sampling. A total of 215 wastewater samples were collected and tested for SARS-CoV-2 RNA by real-time PCR with three targeted genes (N, E, and ORF1ab); 102 samples were positive (42.5%). The SARS-CoV-2 variants were determined by a multiplex PCR MassARRAY assay to distinguish four SARS-CoV-2 variants, including Alpha, Beta, Delta, and Omicron. Multiple variants of Alpha-Delta and Delta-Omicron were detected in the wastewater samples in July 2021 and January 2022, respectively. These wastewater variant results mirrored the country data from clinical specimens deposited in GISAID. Our results demonstrated that wastewater surveillance using multiple signature mutation sites for SARS-CoV-2 variant detection is an appropriate strategy to monitor the presence of SARS-CoV-2 variants in the community at a low cost and with rapid turn-around time. However, it is essential to note that sequencing surveillance of wastewater samples should be considered complementary to whole genome sequencing of clinical samples to detect novel variants.

Analysis of metatranscriptomic methods to enable wastewater-based biosurveillance of all infectious diseases.

Introduction: Wastewater-based surveillance emerged during the COVID-19 pandemic as an efficient way to quickly screen large populations, monitor infectious disease transmission over time, and identify whether more virulent strains are becoming more prevalent in the region without burdening the health care system with individualized testing. Ohio was one of the first states to implement wastewater monitoring through its Ohio Coronavirus Wastewater Monitoring Network (OCWMN), originally tracking the prevalence of COVID-19 by quantitative qPCR from over 67 sites across the state. The OCWMN evolved along with the pandemic to include sequencing the SARS-CoV-2 genome to assess variants of concern circulating within the population. As the pandemic wanes, networks such as OCWMN can be expanded to monitor other infectious diseases and outbreaks of interest to the health department to reduce the burden of communicable diseases. However, most surveillance still utilizes qPCR based diagnostic tests for individual pathogens, which is hard to scale for surveillance of multiple pathogens. Methods: Here we have tested several genomic methods, both targeted and untargeted, for wastewater-based biosurveillance to find the most efficient procedure to detect and track trends in reportable infectious diseases and outbreaks of known pathogens as well as potentially novel pathogens or variants on the rise in our communities. RNA extracts from the OCWMN were provided weekly from 10 sites for 6 weeks. Total RNA was sequenced from the samples on the Illumina NextSeq and on the MinION to identify pathogens present. The MinION long read platform was also used to sequence SARS-CoV-2 with the goal of reducing the complexity of variant calling in mixed populations as occurs with short Illumina reads. Finally, a targeted hybridization approach was tested for compatibility with wastewater RNA samples. Results and discussion: The data analyzed here provides a baseline assessment that demonstrates that wastewater is a rich resource for infectious disease epidemiology and identifies technology gaps and potential solutions to enable this resource to be used by public health laboratories to monitor the infectious disease landscape of the regions they serve.

A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19.

Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.

Drug consumption in German cities and municipalities during the COVID-19 lockdown: a wastewater analysis.

Analysis of illicit drugs, medicines, and pathogens in wastewater is a powerful tool for epidemiological studies to monitor public health trends. The aims of this study were to (i) assess spatial and temporal trends of population-normalized mass loads of illicit drugs and nicotine in raw wastewater in the time of regulations against SARS-CoV-2 infections (2020-21) and (ii) find substances that are feasible markers for characterizing the occurrence of selected drugs in wastewater. Raw sewage 24-h composite samples were collected in catchment areas of 15 wastewater treatment plants (WWTPs) in urban, small-town, and rural areas in Germany during different lockdown phases from April 2020 to December 2021. Parent substances (amphetamine, methamphetamine, MDMA, carbamazepine, gabapentin, and metoprolol) and the metabolites of cocaine (benzoylecgonine) and nicotine (cotinine) were measured. The daily discharge of WWTP influents were used to calculate the daily load (mg/day) normalized by population equivalents (PE) in drained catchment areas (in mg/1,000 persons/day). A weekend trend for illicit drugs was visible with higher amounts on Saturdays and Sundays in larger WWTPs. An influence of the regulations to reduce SARS-CoV-2 infections such as contact bans and border closures on drug consumption has been proven in some cases and refuted in several. In addition, metoprolol and cotinine were found to be suitable as marker substances for the characterization of wastewater. A change in drug use was visible at the beginning of the SARS-CoV-2 crisis. Thereafter from mid-2020, no obvious effect was detected with regard to the regulations against SARS-CoV-2 infections on concentration of drugs in wastewater. Wastewater-based epidemiology is suitable for showing changes in drug consumption during the COVID-19 lockdown.

Early detection of local SARS-CoV-2 outbreaks by wastewater surveillance: a feasibility study.

Wastewater surveillance and quantitative analysis of SARS-CoV-2 RNA are increasingly used to monitor the spread of COVID-19 in the community. We studied the feasibility of applying the surveillance data for early detection of local outbreaks. A Monte Carlo simulation model was constructed, applying data on reported variation in RNA gene copy concentration in faeces and faecal masses shed. It showed that, even with a constant number of SARS-CoV-2 RNA shedders, the variation in concentrations found in wastewater samples will be large, and that it will be challenging to translate viral concentrations into incidence estimates, especially when the number of shedders is low. Potential signals for early detection of hypothetical outbreaks were analysed for their performance in terms of sensitivity and specificity of the signals. The results suggest that a sudden increase in incidence is not easily identified on the basis of wastewater surveillance data, especially in small sampling areas and in low-incidence situations. However, with a high number of shedders and when combining data from multiple consecutive tests, the performance of wastewater sampling is expected to improve considerably. The developed modelling approach can increase our understanding of the results from wastewater surveillance of SARS-CoV-2.

A global aircraft-based wastewater genomic surveillance network for early warning of future pandemics.

International airports can have a key role in screening, detecting, and mitigating cross-border transmission of SARS-CoV-2 and potentially other infectious diseases. With aircraft passengers representing a subpopulation of a country or region, aircraft-based wastewater surveillance can be a promising approach to effectively identifying emerging viruses, tracing their evolution, and mapping global spread with international flights. Therefore, we propose the development of a global aircraft-based wastewater genomic surveillance network, with the busiest international airports as central nodes and continuing air travel journeys as vectors. This surveillance programme requires routinely collecting aircraft wastewater samples for microbiological analysis and sequencing and linking the resulting data with associated international air traffic information. With the creation of a strong international alliance between the airline industry and health authorities, this surveillance network will potentially complement public health systems with a true early warning ability to inform decision making for new variants and future global health risks.

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.

On-site treatment of hospital wastewater in a full-scale treatment plant in Germany: SARS-CoV-2 and treatment performance.

The separate, advanced treatment of hospital wastewater might be a promising approach to prevent the dissemination of residual compounds of high environmental concern, like pharmaceuticals, viruses and pathogenic microorganisms. This study investigates the performance of a full-scale, on-site treatment plant, consisting of a membrane bioreactor and a subsequent ozonation, at a German hospital. We analysed the elimination of pharmaceutical residues, microbiological parameters and SARS-CoV-2 RNA fragments. Additionally, we conducted an orienting study on the practicability of implementing targeted wastewater monitoring at a hospital. Our results demonstrate that after 10 years of stable operation, the treatment plant works highly efficiently regarding the elimination of pharmaceuticals and bacterial indicators. Elimination rates for pharmaceutical substances were above 90%, and log reductions of up to 6 log10 units for microbiological parameters were achieved. SARS-CoV-2 RNA could be detected and quantified in the influent but not in the effluent. The RNA load in the raw wastewater showed good correspondence with COVID-19 case numbers in the hospital. We showed that the full-scale on-site treatment of hospital wastewater is technically feasible and contributes to sustainable hospital effluent management and that monitoring biological markers on the building level might be a useful complementary tool for disease surveillance.

Optimised protocol for monitoring SARS-CoV-2 in wastewater using reverse complement PCR-based whole-genome sequencing.

Monitoring the spread of viral pathogens in the population during epidemics is crucial for mounting an effective public health response. Understanding the viral lineages that constitute the infections in a population can uncover the origins and transmission patterns of outbreaks and detect the emergence of novel variants that may impact the course of an epidemic. Population-level surveillance of viruses through genomic sequencing of wastewater captures unbiased lineage data, including cryptic asymptomatic and undiagnosed infections, and has been shown to detect infection outbreaks and novel variant emergence before detection in clinical samples. Here, we present an optimised protocol for quantification and sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in influent wastewater, used for high-throughput genomic surveillance in England during the COVID-19 pandemic. This protocol utilises reverse compliment PCR for library preparation, enabling tiled amplification across the whole viral genome and sequencing adapter addition in a single step to enhance efficiency. Sequencing of synthetic SARS-CoV-2 RNA provided evidence validating the efficacy of this protocol, while data from high-throughput sequencing of wastewater samples demonstrated the sensitivity of this method. We also provided guidance on the quality control steps required during library preparation and data analysis. Overall, this represents an effective method for high-throughput sequencing of SARS-CoV-2 in wastewater which can be applied to other viruses and pathogens of humans and animals.

Wastewater surveillance of SARS-CoV-2 genomic populations on a country-wide scale through targeted sequencing.

SARS-CoV-2 surveillance of viral populations in wastewater samples is recognized as a useful tool for monitoring epidemic waves and boosting health preparedness. Next generation sequencing of viral RNA isolated from wastewater is a convenient and cost-effective strategy to understand the molecular epidemiology of SARS-CoV-2 and provide insights on the population dynamics of viral variants at the community level. However, in low- and middle-income countries, isolated groups have performed wastewater monitoring and data has not been extensively shared in the scientific community. Here we report the results of monitoring the co-circulation and abundance of variants of concern (VOCs) of SARS-CoV-2 in Uruguay, a small country in Latin America, between November 2020-July 2021 using wastewater surveillance. RNA isolated from wastewater was characterized by targeted sequencing of the Receptor Binding Domain region within the spike gene. Two computational approaches were used to track the viral variants. The results of the wastewater analysis showed the transition in the overall predominance of viral variants in wastewater from No-VOCs to successive VOCs, in agreement with clinical surveillance from sequencing of nasal swabs. The mutations K417T, E484K and N501Y, that characterize the Gamma VOC, were detected as early as December 2020, several weeks before the first clinical case was reported. Interestingly, a non-synonymous mutation described in the Delta VOC, L452R, was detected at a very low frequency since April 2021 when using a recently described sequence analysis tool (SAM Refiner). Wastewater NGS-based surveillance of SARS-CoV-2 is a reliable and complementary tool for monitoring the introduction and prevalence of VOCs at a community level allowing early public health decisions. This approach allows the tracking of symptomatic and asymptomatic individuals, who are generally under-reported in countries with limited clinical testing capacity. Our results suggests that wastewater-based epidemiology can contribute to improving public health responses in low- and middle-income countries.

Evaluation of variant calling algorithms for wastewater-based epidemiology using mixed populations of SARS-CoV-2 variants in synthetic and wastewater samples.

Wastewater-based epidemiology has been used extensively throughout the COVID-19 (coronavirus disease 19) pandemic to detect and monitor the spread and prevalence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and its variants. It has proven an excellent, complementary tool to clinical sequencing, supporting the insights gained and helping to make informed public-health decisions. Consequently, many groups globally have developed bioinformatics pipelines to analyse sequencing data from wastewater. Accurate calling of mutations is critical in this process and in the assignment of circulating variants; yet, to date, the performance of variant-calling algorithms in wastewater samples has not been investigated. To address this, we compared the performance of six variant callers (VarScan, iVar, GATK, FreeBayes, LoFreq and BCFtools), used widely in bioinformatics pipelines, on 19 synthetic samples with known ratios of three different SARS-CoV-2 variants of concern (VOCs) (Alpha, Beta and Delta), as well as 13 wastewater samples collected in London between the 15th and 18th December 2021. We used the fundamental parameters of recall (sensitivity) and precision (specificity) to confirm the presence of mutational profiles defining specific variants across the six variant callers. Our results show that BCFtools, FreeBayes and VarScan found the expected variants with higher precision and recall than GATK or iVar, although the latter identified more expected defining mutations than other callers. LoFreq gave the least reliable results due to the high number of false-positive mutations detected, resulting in lower precision. Similar results were obtained for both the synthetic and wastewater samples.