Three years of wastewater surveillance for new psychoactive substances from 16 countries.

The proliferation of new psychoactive substances (NPS) over recent years has made their surveillance complex. The analysis of raw municipal influent wastewater can allow a broader insight into community consumption patterns of NPS. This study examines data from an international wastewater surveillance program that collected and analysed influent wastewater samples from up to 47 sites in 16 countries between 2019 and 2022. Influent wastewater samples were collected over the New Year period and analysed using validated liquid chromatography - mass spectrometry methods. Over the three years, a total of 18 NPS were found in at least one site. Synthetic cathinones were the most found class followed by phenethylamines and designer benzodiazepines. Furthermore, two ketamine analogues, one plant based NPS (mitragynine) and methiopropamine were also quantified across the three years. This work demonstrates that NPS are used across different continents and countries with the use of some more evident in particular regions. For example, mitragynine has highest mass loads in sites in the United States, while eutylone and 3-methylmethcathinone increased considerably in New Zealand and in several European countries, respectively. Moreover, 2F-deschloroketamine, an analogue of ketamine, has emerged more recently and could be quantified in several sites, including one in China, where it is considered as one of the drugs of most concern. Finally, some NPS were detected in specific regions during the initial sampling campaigns and spread to additional sites by the third campaign. Hence, wastewater surveillance can provide an insight into temporal and spatial trends of NPS use.

Quaternary Ammonium Compounds: A Chemical Class of Emerging Concern.

Quaternary ammonium compounds (QACs), a large class of chemicals that includes high production volume substances, have been used for decades as antimicrobials, preservatives, and antistatic agents and for other functions in cleaning, disinfecting, personal care products, and durable consumer goods. QAC use has accelerated in response to the COVID-19 pandemic and the banning of 19 antimicrobials from several personal care products by the US Food and Drug Administration in 2016. Studies conducted before and after the onset of the pandemic indicate increased human exposure to QACs. Environmental releases of these chemicals have also increased. Emerging information on adverse environmental and human health impacts of QACs is motivating a reconsideration of the risks and benefits across the life cycle of their production, use, and disposal. This work presents a critical review of the literature and scientific perspective developed by a multidisciplinary, multi-institutional team of authors from academia, governmental, and nonprofit organizations. The review evaluates currently available information on the ecological and human health profile of QACs and identifies multiple areas of potential concern. Adverse ecological effects include acute and chronic toxicity to susceptible aquatic organisms, with concentrations of some QACs approaching levels of concern. Suspected or known adverse health outcomes include dermal and respiratory effects, developmental and reproductive toxicity, disruption of metabolic function such as lipid homeostasis, and impairment of mitochondrial function. QACs' role in antimicrobial resistance has also been demonstrated. In the US regulatory system, how a QAC is managed depends on how it is used, for example in pesticides or personal care products. This can result in the same QACs receiving different degrees of scrutiny depending on the use and the agency regulating it. Further, the US Environmental Protection Agency's current method of grouping QACs based on structure, first proposed in 1988, is insufficient to address the wide range of QAC chemistries, potential toxicities, and exposure scenarios. Consequently, exposures to common mixtures of QACs and from multiple sources remain largely unassessed. Some restrictions on the use of QACs have been implemented in the US and elsewhere, primarily focused on personal care products. Assessing the risks posed by QACs is hampered by their vast structural diversity and a lack of quantitative data on exposure and toxicity for the majority of these compounds. This review identifies important data gaps and provides research and policy recommendations for preserving the utility of QAC chemistries while also seeking to limit adverse environmental and human health effects.

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. Graphical Unlabelled Image

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.

Baseline Sequencing Surveillance of Public Clinical Testing, Hospitals, and Community Wastewater Reveals Rapid Emergence of SARS-CoV-2 Omicron Variant of Concern in Arizona, USA.

The adaptive evolution of SARS-CoV-2 variants is driven by selection for increased viral fitness in transmissibility and immune evasion. Understanding the dynamics of how an emergent variant sweeps across populations can better inform public health response preparedness for future variants. Here, we investigated the state-level genomic epidemiology of SARS-CoV-2 through baseline genomic sequencing surveillance of 27,071 public testing specimens and 1,125 hospital inpatient specimens diagnosed between November 1, 2021, and January 31, 2022, in Arizona. We found that the Omicron variant rapidly displaced Delta variant in December 2021, leading to an "Omicron surge" of COVID-19 cases in early 2022. Wastewater sequencing surveillance of 370 samples supported the synchronous sweep of Omicron in the community. Hospital inpatient COVID-19 cases of Omicron variant presented to three major hospitals 10.51 days after its detection from public clinical testing. Nonsynonymous mutations in nsp3, nsp12, and nsp13 genes were significantly associated with Omicron hospital cases compared to community cases. To model SARS-CoV-2 transmissions across the state population, we developed a scalable sequence network methodology and showed that the Omicron variant spread through intracounty and intercounty transmissions. Finally, we demonstrated that the temporal emergence of Omicron BA.1 to become the dominant variant (17.02 days) was 2.3 times faster than the prior Delta variant (40.70 days) or subsequent Omicron sublineages BA.2 (39.65 days) and BA.5 (35.38 days). Our results demonstrate the uniquely rapid sweep of Omicron BA.1. These findings highlight how integrated public health surveillance can be used to enhance preparedness and response to future variants. IMPORTANCE SARS-CoV-2 continues to evolve new variants throughout the pandemic. However, the temporal dynamics of how SARS-CoV-2 variants emerge to become the dominant circulating variant is not precisely known. Genomic sequencing surveillance offers unique insights into how SARS-CoV-2 spreads in communities and the lead-up to hospital cases during a surge. Specifically, baseline sequencing surveillance through random selection of positive diagnostic specimens provides a representative outlook of the virus lineages circulating in a geographic region. Here, we investigated the emergence of the Omicron variant of concern in Arizona by leveraging baseline genomic sequence surveillance of public clinical testing, hospitals, and community wastewater. We tracked the spread and evolution of the Omicron variant as it first emerged in the general public, and its rapid shift in hospital admissions in the state health system. This study demonstrates the timescale of public health preparedness needed to respond to an antigenic shift in SARS-CoV-2.

Leveraging an established neighbourhood-level, open access wastewater monitoring network to address public health priorities: a population-based study.

BACKGROUND: Before the COVID-19 pandemic, the US opioid epidemic triggered a collaborative municipal and academic effort in Tempe, Arizona, which resulted in the world's first open access dashboard featuring neighbourhood-level trends informed by wastewater-based epidemiology (WBE). This study aimed to showcase how wastewater monitoring, once established and accepted by a community, could readily be adapted to respond to newly emerging public health priorities. METHODS: In this population-based study in Greater Tempe, Arizona, an existing opioid monitoring WBE network was modified to track SARS-CoV-2 transmission through the analysis of 11 contiguous wastewater catchments. Flow-weighted and time-weighted 24 h composite samples of untreated wastewater were collected at each sampling location within the wastewater collection system for 3 days each week (Tuesday, Thursday, and Saturday) from April 1, 2020, to March 31, 2021 (Area 7 and Tempe St Luke's Hospital were added in July, 2020). Reverse transcription quantitative PCR targeting the E gene of SARS-CoV-2 isolated from the wastewater samples was used to determine the number of genome copies in each catchment. Newly detected clinical cases of COVID-19 by zip code within the City of Tempe, Arizona were reported daily by the Arizona Department of Health Services from May 23, 2020. Maricopa County-level new positive cases, COVID-19-related hospitalisations, deaths, and long-term care facility deaths per day are publicly available and were collected from the Maricopa County Epidemic Curve Dashboard. Viral loads of SARS-CoV-2 (genome copies per day) measured in wastewater from each catchment were aggregated at the zip code level and city level and compared with the clinically reported data using root mean square error to investigate early warning capability of WBE. FINDINGS: Between April 1, 2020, and March 31, 2021, 1556 wastewater samples were analysed. Most locations showed two waves in viral levels peaking in June, 2020, and December, 2020-January, 2021. An additional wave of viral load was seen in catchments close to Arizona State University (Areas 6 and 7) at the beginning of the fall (autumn) semester in late August, 2020. Additionally, an early infection hotspot was detected in the Town of Guadalupe, Arizona, starting the week of May 4, 2020, that was successfully mitigated through targeted interventions. A shift in early warning potential of WBE was seen, from a leading (mean of 8·5 days [SD 2·1], June, 2020) to a lagging (-2·0 days [1·4], January, 2021) indicator compared with newly reported clinical cases. INTERPRETATION: Lessons learned from leveraging an existing neighbourhood-level WBE reporting dashboard include: (1) community buy-in is key, (2) public data sharing is effective, and (3) sub-ZIP-code (postal code) data can help to pinpoint populations at risk, track intervention success in real time, and reveal the effect of local clinical testing capacity on WBE's early warning capability. This successful demonstration of transitioning WBE efforts from opioids to COVID-19 encourages an expansion of WBE to tackle newly emerging and re-emerging threats (eg, mpox and polio). FUNDING: National Institutes of Health's RADx-rad initiative, National Science Foundation, Virginia G Piper Charitable Trust, J M Kaplan Fund, and The Flinn Foundation.

Systematic scoping review evaluating the potential of wastewater-based epidemiology for monitoring cardiovascular disease and cancer.

Cardiovascular disease (CVD) and cancer are collectively responsible for tens of millions of global deaths each year. These rates are projected to intensify as the COVID-19 pandemic has caused delays in individualized diagnostics, or exacerbated prevalence due to Post Acute Coronavirus (COVID-19) Syndrome. Wastewater-based epidemiology (WBE) has successfully been employed as a useful tool for generating population-level health assessments, and was examined here in this systematic scoping literature review to (i) identify endogenous human biomarkers reported to indicate CVD or cancer in clinical practice, (ii) assess specificity to the indicated diseases, (iii) evaluate the utility for estimating population-level disease prevalence in community wastewater, and (iv) contextualize the obtained information for monitoring CVD and cancer presence via WBE. A total of 48 peer-reviewed papers were critically examined identifying five urinary protein biomarkers: cardiac troponin I (cTnI) (heart attack/heart failure), cystatin C (atherosclerosis), normetanephrine (tumor presence), α-fetoprotein (prostate and liver cancer), and microtubule assisted serine/threonine kinase 4 (MAST4) (breast cancer). Next, urinary excretion information was utilized to predict biomarker concentrations extant in community wastewater, resulting in average healthy concentrations ranging from 0.02 to 1159 ng/L, and disease-indicating thresholds from 0.16 to 3041 ng/L. Finally, estimating prevalence-adjusted wastewater measurements was explored in order to assess community-level CVD and cancer presence utilizing U.S. reported prevalence rates. Results obtained suggest that WBE can serve as a viable tool in support of current methods for CVD and cancer assessment to reduce morbidities and mortalities worldwide.

Occurrence of Z-drugs, benzodiazepines, and ketamine in wastewater in the United States and Mexico during the Covid-19 pandemic.

Z-drugs, benzodiazepines and ketamine are classes of psychotropic drugs prescribed for treating anxiety, sleep disorders and depression with known side effects including an elevated risk of addiction and substance misuse. These drugs have a strong potential for misuse, which has escalated over the years and was hypothesized here to have been exacerbated during the COVID-19 pandemic. Wastewater-based epidemiology (WBE) constitutes a fast, easy, and relatively inexpensive approach to epidemiological surveys for understanding the incidence and frequency of uses of these drugs. In this study, we analyzed wastewater (n = 376) from 50 cities across the United States and Mexico from July to October 2020 to estimate drug use rates during a pandemic event. Both time and flow proportional composite and grab samples of untreated municipal wastewater were analyzed using solid-phase extraction followed by liquid chromatography-tandem mass spectrometry to determine loadings of alprazolam, clonazepam, diazepam, ketamine, lorazepam, nordiazepam, temazepam, zolpidem, and zaleplon in raw wastewater. Simultaneously, prescription data of the aforementioned drugs were extracted from the Medicaid database from 2019 to 2021. Results showed high detection frequencies of ketamine (90 %), lorazepam (87 %), clonazepam (76 %) and temazepam (73 %) across both Mexico and United States and comparatively lower detection frequencies for zaleplon (22 %), zolpidem (9 %), nordiazepam (<1 %), diazepam (<1 %), and alprazolam (<1 %) during the pandemic. Average mass consumption rates, estimated using WBE and reported in units of mg/day/1000 persons, ranged between 62 (temazepam) and 1100 (clonazepam) in the United States. Results obtained from the Medicaid database also showed a significant change (p < 0.05) in the prescription volume between the first quarter of 2019 (before the pandemic) and the first quarter of 2021 (pandemic event) for alprazolam, clonazepam and lorazepam. Study results include the first detections of zaleplon and zolpidem in wastewater from North America.

Monkeypox outbreak: Wastewater and environmental surveillance perspective.

Monkeypox disease (MPXD), a viral disease caused by the monkeypox virus (MPXV), is an emerging zoonotic disease endemic in some countries of Central and Western Africa but seldom reported outside the affected region. Since May 2022, MPXD has been reported at least in 74 countries globally, prompting the World Health Organization to declare the MPXD outbreak a Public Health Emergency of International Concern. As of July 24, 2022; 92 % (68/74) of the countries with reported MPXD cases had no historical MPXD case reports. From the One Health perspective, the spread of MPXV in the environment poses a risk not only to humans but also to small mammals and may, ultimately, spread to potent novel host populations. Wastewater-based surveillance (WBS) has been extensively utilized to monitor communicable diseases, particularly during the ongoing COVID-19 pandemic. It helped in monitoring infectious disease caseloads as well as specific viral variants circulating in communities. The detection of MPXV DNA in lesion materials (e.g. skin, vesicle fluid, crusts), skin rashes, and various body fluids, including respiratory and nasal secretions, saliva, urine, feces, and semen of infected individuals, supports the possibility of using WBS as an early proxy for the detection of MPXV infections. WBS of MPXV DNA can be used to monitor MPXV activity/trends in sewerage network areas even before detecting laboratory-confirmed clinical cases within a community. However, several factors affect the detection of MPXV in wastewater including, but not limited to, routes and duration time of virus shedding by infected individuals, infection rates in the relevant affected population, environmental persistence, the processes and analytical sensitivity of the used methods. Further research is needed to identify the key factors that impact the detection of MPXV biomarkers in wastewater and improve the utility of WBS of MPXV as an early warning and monitoring tool for safeguarding human health. In this review, we shortly summarize aspects of the MPXV outbreak relevant to wastewater monitoring and discuss the challenges associated with WBS.

Mass trends of parabens, triclocarban and triclosan in Arizona wastewater collected after the 2017 FDA ban on antimicrobials and during the COVID-19 pandemic.

Antimicrobials like parabens, triclosan (TCS), and triclocarban (TCC) are of public health concern worldwide due to their endocrine-disrupting properties and ability to promote antimicrobial drug resistance in human pathogens. The overall use of antimicrobials presumably has increased during the COVID-19 pandemic, whereas TCS and TCC may have experienced reductions in use due to their recent ban from thousands of over-the-counter (OTC) personal care products by the U.S. Food and Drug Administration (FDA). No quantitative data are available on the use of parabens or the impact the FDA ban had on TCC and TCS. Here, we use wastewater samples (n = 1514) from 10 different communities in Arizona to measure the presence of the six different antimicrobial products (TCS, TCC, and four alkylated parabens [methylparaben (MePb), ethylparaben (EtPb), propylparaben (PrPb), butylparaben (BuPb)]) collected before and during the COVID-19 pandemic using a combination of solid-phase extraction, liquid chromatography/tandem mass spectrometry (LC-MS/MS), and isotope dilution for absolute quantitation. The average mass loadings of all antimicrobials combined (1,431 ± 22 mg/day per 1,000 people) after the onset of the local epidemic (March 2020 - October 2020) were significantly higher (945 ± 62 mg/day per 1,000 people; p < 0.05) than before the pandemic (January 2019 - February 2020). Overall, parabens (∑Pbs = 999 ± 16 mg/day per 1,000 people) were the most used antimicrobials, followed by TCS (117 ± 14 mg/day per 1,000 people) and TCC (117 ± 14 mg/day per 1,000 people). After the 2017 U.S. FDA ban, we found a statistically significant (p < 0.05) reduction in the mass loadings of TCS (-89%) and TCC (-80%) but a rise in paraben use (+72%). Mass flows of 3 of a total of 4 parabens (MePb, EtPb, and PrPb) in wastewater were significantly higher upon the onset of the epidemic locally (p < 0.05). This is the first longitudinal study investigating the use of antimicrobials during the COVID-19 pandemic by employing wastewater-based epidemiology. Whereas an overall increase in the use of antimicrobials was evident from analyzing Arizona wastewater, a notable reduction in the use of TCS and TCC was evident during the pandemic, triggered by the U.S. FDA ban.

Extensive Wastewater-Based Epidemiology as a Resourceful Tool for SARS-CoV-2 Surveillance in a Low-to-Middle-Income Country through a Successful Collaborative Quest: WBE, Mobility, and Clinical Tests

The COVID-19 pandemic has challenged healthcare systems worldwide. Efforts in low-to-middle-income countries (LMICs) cannot keep stride with infection rates, especially during peaks. A strong international collaboration between Arizona State University (ASU), Tec de Monterrey (TEC), and Servicios de Agua y Drenaje de Monterrey (Local Water Utilities) is acting to integrate wastewater-based epidemiology (WBE) of SARS-CoV-2 in the region as a complementary approach to aid the healthcare system. Wastewater was collected from four sewer catchments in the Monterrey Metropolitan area in Mexico (pop. 4,643,232) from mid-April 2020 to February 2021 (44 weeks, n = 644). Raw wastewater was filtered and filter-concentrated, the RNA was extracted using columns, and the Charité/Berlin protocol was used for the RT-qPCR. The viral loads obtained between the first (June 2020) and second waves (February 2021) of the pandemic were similar;in contrast, the clinical cases were fewer during the first wave, indicating poor coverage. During the second wave of the pandemic, the SARS-CoV-2 quantification in wastewater increased 14 days earlier than the COVID-19 clinical cases reported. This is the first long-term WBE study in Mexico and demonstrates its value in pandemic management.

A framework for wastewater sample collection from a sewage cleanout to inform building-scale wastewater-based epidemiology studies.

Wastewater-based epidemiology (WBE) is a public health tool utilized for drug surveillance, and more recently, infectious disease monitoring of SARS-CoV-2. Sample collection is historically performed at a wastewater treatment plant, however, at this spatial resolution, much information related to actionable and contextually relevant community health data may be lost. Sampling from within the sewer collection system is now being employed more widely, bringing unique challenges, including health and safety concerns related to sample collection. As proof of concept, we tested the efficacy of sampling at the building-level from a sewer cleanout at an undisclosed location in Greater Phoenix, AZ, USA, to (i) test the feasibility of wastewater sample collection from this alternative access point, (ii) assess the advantages and limitations experienced for both maintenance-hole and cleanout-level sampling, (iii) screen for chemical analytes to evaluate detectability, and (iv) create a sampling framework for future near-source WBE investigations. Results indicate that use of a sewer cleanout compared to a maintenance hole is cost-effective, practical, and safe, while still preserving the anonymity and privacy for the contributing population. Additionally, of the 37 biomarkers screened over two sampling events, 20 were detected that cover a wide range of human behavior, exposure, and activity, indicating use of a sewer cleanout to be entirely feasible for downstream analysis. This reported success of sewer cleanout sampling for WBE and corresponding framework may allow practitioners to isolate specific complexes or buildings of interest, while avoiding challenges that can arise from maintenance hole sampling, thus allowing for widescale implementation of WBE for public health purposes.

Opportunities and limits of wastewater-based epidemiology for tracking global health and attainment of UN sustainable development goals.

Wastewater-based epidemiology (WBE) emerged as a powerful, actionable health management tool during the COVID-19 pandemic. Hypothesizing future uses, we explored its potential for real-time, tracking of progress in attaining United Nations Sustainable Development Goals (SDGs) globally as a non-expensive method using existing infrastructure. We inventoried (i) literature-documented sewerage infrastructure, (ii) demographics of populations served, and (iii) WBE markers informative of 9 SDGs. Among the 17 different sustainable development goals listed by the UN 2030 agenda, more than half of these may be monitored by using WBE monitoring at centralized treatment infrastructure as tabulated in this study. Driven mainly by COVID-19, WBE currently is practiced in at least 55 countries, reaching about 300 million people. Expansion of WBE to 109,000 + treatment plants inventoried in 129 countries would increase global coverage 9-fold to 34.7% or 2.7 billion, leaving out 5 billion people not served by centralized sewerage systems. Associations between population demographics and present-day infrastructure are explored, and geospatial regions particularly vulnerable to infectious disease outbreaks are identified. The results suggest that difference in the differential outcomes in well-being is an outcome of the sanitation infrastructure inequalities and lack of sanitation infrastructure creates doubly disadvantaged populations at risk of poor hygiene and cut off from the early-warning benefits of conventional WBE. This is the first study to explore the feasibility and potential barriers to the use of WBE for tracking the attainment of SDGs globally with at least 9 out of 17 SDGs.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus.

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

Wastewater-Based Epidemiology and Long-Read Sequencing to Identify Enterovirus Circulation in Three Municipalities in Maricopa County, Arizona, Southwest United States between June and October 2020.

We used wastewater-based epidemiology and amplicon-based long-read high-throughput sequencing for surveillance of enteroviruses (EVs) in Maricopa County, Arizona, Southwest United States. We collected 48 samples from 13 sites in three municipalities between 18 June and 1 October 2020, and filtered (175 mL each; 0.45 µm pore size) and extracted RNA from the filter-trapped solids. The RNA was converted to cDNA and processed through two workflows (Sanger sequencing (SSW) and long-read Illumina sequencing (LRISW)) each including a nested polymerase chain reaction (nPCR) assay. We subjected the ~350 bp amplicon from SSW to Sanger sequencing and the ~1900-2400 bp amplicon from LRISW to Illumina sequencing. We identified EV contigs from 11 of the 13 sites and 41.67% (20/48) of screened samples. Using the LRISW, we detected nine EV genotypes from three species (Enterovirus A (CVA4, EV-A76, EV-A90), Enterovirus B (E14) and Enterovirus C (CVA1, CVA11, CVA13, CVA19 and CVA24)) with Enterovirus C representing approximately 90% of the variants. However, the SSW only detected the five Enterovirus C types. Similarity and phylogenetic analysis showed that multiple Enterovirus C lineages were circulating, co-infecting and recombining in the population during the season despite the SARS-CoV-2 pandemic and the non-pharmaceutical public health measures taken to curb transmission.

Pan-Enterovirus Amplicon-Based High-Throughput Sequencing Detects the Complete Capsid of a EVA71 Genotype C1 Variant via Wastewater-Based Epidemiology in Arizona.

We describe the complete capsid of a genotype C1-like Enterovirus A71 variant recovered from wastewater in a neighborhood in the greater Tempe, Arizona area (Southwest United States) in May 2020 using a pan-enterovirus amplicon-based high-throughput sequencing strategy. The variant seems to have been circulating for over two years, but its sequence has not been documented in that period. As the SARS-CoV-2 pandemic has resulted in changes in health-seeking behavior and overwhelmed pathogen diagnostics, our findings highlight the importance of wastewater-based epidemiology (WBE ) as an early warning system for virus surveillance.

Standardizing data reporting in the research community to enhance the utility of open data for SARS-CoV-2 wastewater surveillance.

SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of metainformation to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what metainformation should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting.