Making waves: Wastewater surveillance of SARS-CoV-2 in an endemic future

Balancing public health and group privacy: Ethics, rights, and obligations for wastewater surveillance systems

As the threat of COVID-19 recedes, wastewater surveillance - unlike other pandemic-era public health surveillance methods - seems here to stay. Concerns have been raised, however, about the potential risks that wastewater surveillance might pose towards group privacy. Existing scholarship has focused upon using ethics- or human rights-based frameworks as a means of balancing the public health objectives of wastewater surveillance and the potential risks it might pose to group privacy. However, such frameworks greatly lack enforceability. In order to further the strong foundation laid by such frameworks - while addressing their lack of enforceability - this paper proposes the idea of the 'obligation' as an alternative way to regulate wastewater surveillance systems. The legal codification of said obligations provides a method of ensuring that wastewater surveillance systems can be deployed effectively and equitably. Our paper proposes that legal obligations for wastewater surveillance can be created and enforced through transparent and purposeful legislation (which would include limits on power and grant institutions substantial oversight) as well as paying heed to non-legislative legal means of enforcement, such as through courts or contracts. Introducing legal obligations for wastewater surveillance could therefore be highly useful to researchers, policymakers, corporate technologists, and government agencies working in this field.

Tricks and tracks of prevalence, occurrences, treatment technologies, and challenges of mixtures of emerging contaminants in the environment: With special emphasis on microplastic

This paper aims to emphasize the occurrence of various emerging contaminant (EC) mixtures in natural ecosystems and highlights the primary concern arising from the unregulated release into soil and water, along with their impacts on human health. Emerging contaminant mixtures, including pharmaceuticals, personal care products, dioxins, polychlorinated biphenyls, pesticides, antibiotics, biocides, surfactants, phthalates, enteric viruses, and microplastics (MPs), are considered toxic contaminants with grave implications. MPs play a crucial role in transporting pollutants to aquatic and terrestrial ecosystems as they interact with the various components of the soil and water environments. This review summarizes that major emerging contaminants (ECs), like trimethoprim, diclofenac, sulfamethoxazole, and 17α-Ethinylestradiol, pose serious threats to public health and contribute to antimicrobial resistance. In addressing human health concerns and remediation techniques, this review critically evaluates conventional methods for removing ECs from complex matrices. The diverse physiochemical properties of surrounding environments facilitate the partitioning of ECs into sediments and other organic phases, resulting in carcinogenic, teratogenic, and estrogenic effects through active catalytic interactions and mechanisms mediated by aryl hydrocarbon receptors. The proactive toxicity of ECs mixture complexation and, in part, the yet-to-be-identified environmental mixtures of ECs represent a blind spot in current literature, necessitating conceptual frameworks for assessing the toxicity and risks with individual components and mixtures. Lastly, this review concludes with an in-depth exploration of future scopes, knowledge gaps, and challenges, emphasizing the need for a concerted effort in managing ECs and other organic pollutants.

SARS-CoV-2 viral titer measurements in Ontario, Canada wastewaters throughout the COVID-19 pandemic

During the COVID-19 pandemic, the Province of Ontario, Canada, launched a wastewater surveillance program to monitor SARS-CoV-2, inspired by the early work and successful forecasts of COVID-19 waves in the city of Ottawa, Ontario. This manuscript presents a dataset from January 1, 2021, to March 31, 2023, with RT-qPCR results for SARS-CoV-2 genes and PMMoV from 107 sites across all 34 public health units in Ontario, covering 72% of the province's and 26.2% of Canada's population. Sampling occurred 2-7 times weekly, including geographical coordinates, serviced populations, physico-chemical water characteristics, and flowrates. In doing so, this manuscript ensures data availability and metadata preservation to support future research and epidemic preparedness through detailed analyses and modeling. The dataset has been crucial for public health in tracking disease locally, especially with the rise of the Omicron variant and the decline in clinical testing, highlighting wastewater-based surveillance's role in estimating disease incidence in Ontario.

Small-scale wastewater-based epidemiology (WBE) for infectious diseases and antibiotic resistance: A scoping review

Wastewater analysis can serve as a source of public health information. In recent years, wastewater-based epidemiology (WBE) has emerged and proven useful for the detection of infectious diseases. However, insights from the wastewater treatment plant do not allow for the small-scale differentiation within the sewer system that is needed to analyze the target population under study in more detail. Small-scale WBE offers several advantages, but there has been no systematic overview of its application. The aim of this scoping review is to provide a comprehensive overview of the current state of knowledge on small-scale WBE for infectious diseases, including methodological considerations for its application. A systematic database search was conducted, considering only peer-reviewed articles. Data analyses included quantitative summary and qualitative narrative synthesis. Of 2130 articles, we included 278, most of which were published since 2020. The studies analyzed wastewater at the building level (n = 203), especially healthcare (n = 110) and educational facilities (n = 80), and at the neighborhood scale (n = 86). The main analytical parameters were viruses (n = 178), notably SARS-CoV-2 (n = 161), and antibiotic resistance (ABR) biomarkers (n = 99), often analyzed by polymerase chain reaction (PCR), with DNA sequencing techniques being less common. In terms of sampling techniques, active sampling dominated. The frequent lack of detailed information on the specification of selection criteria and the characterization of the small-scale sampling sites was identified as a concern. In conclusion, based on the large number of studies, we identified several methodological considerations and overarching strategic aspects for small-scale WBE. An enabling environment for small-scale WBE requires inter- and transdisciplinary knowledge sharing across countries. Promoting the adoption of small-scale WBE will benefit from a common international conceptualization of the approach, including standardized and internationally accepted terminology. In particular, the development of good WBE practices for different aspects of small-scale WBE is warranted. This includes the establishment of guidelines for a comprehensive characterization of the local sewer system and its sub-sewersheds, and transparent reporting to ensure comparability of small-scale WBE results.

Tailored wastewater surveillance framework uncovered the epidemics of key pathogens in a Northwestern city of China

Wastewater surveillance enables rapid pathogen monitoring and community prevalence estimation. However, how to design an integrated and tailored wastewater surveillance framework to monitor major health threats in metropolises remains a major challenge. In this study, we first analyzed the historical clinical data of Xi'an city and designed a wastewater surveillance framework covering five key endemic viruses, namely, SARS-CoV-2, norovirus, influenza A virus (IAV), influenza B virus (IBV), respiratory syncytial virus (RSV), and hantavirus. Amplicon sequencing of SARS-CoV-2, norovirus and hantavirus was conducted biweekly to determine the prevalent community genotypes circulating in this region. The results showed that from April 2023 to August 2023, Xi'an experienced two waves of SARS-CoV-2 infection, which peaked in the middle of May-2023 and late August-2023. The sewage concentrations of IAV and RSV peaked in early March and early May 2023, respectively, while the sewage concentrations of norovirus fluctuated throughout the study period and peaked in late August. The dynamics of the sewage concentrations of SARS-CoV-2, norovirus, IAV, RSV, and hantavirus were in line with the trends in the sentinel hospital percent positivity data, indicating the role of wastewater surveillance in enhancing the understanding of epidemic trends. Amplicon sequencing of SARS-CoV-2 revealed a transition in the predominant genotype, which changed from DY.1 and FR.1.4 to the XBB and EG.5 subvariants. Amplicon sequencing also revealed that there was only one predominant hantavirus genotype in the local population, while highly diverse genotypes of norovirus GI and GII were found in the wastewater. In conclusion, this study provided valuable insights into the dynamics of infection trends and predominant genotypes of key pathogens in a city without sufficient clinical surveillance, highlighting the role of a tailored wastewater surveillance framework in addressing public health priorities. More importantly, our study provides the first evidence demonstrating the applicability of wastewater surveillance for hantavirus, which is a major health threat locally.

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.

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.

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.

A modeling pipeline to relate municipal wastewater surveillance and regional public health data

As COVID-19 becomes endemic, public health departments benefit from improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging due to the high noise typical of environmental samples. We have developed a generalized pipeline using in- and out-of-sample model selection to test the ability of different correction models to reduce the variance in wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but the pipeline should be used to reevaluate any new data set as the sources of variance may change across locations, lab methods, and disease states. Using our best-fit model, we investigated the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We did this in a rolling manner for corrected wastewater data and for other prevalence indicators and statistically compared the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We found that wastewater trends often lead other COVID-19 indicators in predicting new surges.

Results from the SARS-CoV-2 wastewater-based surveillance system in Denmark, July 2021 to June 2022

The microbiological analysis of wastewater samples is increasingly used for the surveillance of SARS-CoV-2 globally. We described the setup process of the national SARS-CoV-2 wastewater-based surveillance system in Denmark, presented its main results during the first year of activities, from July 2021 to June 2022, and discussed their operational significance. The Danish SARS-CoV-2 wastewater-based surveillance system was designed to cover 85 % of the population in Denmark and it entailed taking three weekly samples from 230 sites. Samples were RT-qPCR tested for SARS-CoV-2 RNA, targeting the genetic markers N1, N2 and RdRp, and for two faecal indicators, Pepper Mild Mottle Virus and crAssphage. We calculated the weekly SARS-CoV-2 RNA concentration in the wastewater from each sampling site and monitored it in view of the results from individual testing, at the national and regional levels. We attempted to use wastewater results to identify potential local outbreaks, and we sequenced positive wastewater samples using Nanopore sequencing to monitor the circulation of viral variants in Denmark. The system reached its full implementation by October 2021 and covered up to 86.4 % of the Danish population. The system allowed for monitoring of the national and regional trends of SARS-CoV-2 infections in Denmark. However, the system contribution to the identification of potential local outbreaks was limited by the extensive information available from clinical testing. The sequencing of wastewater samples identified relevant variants of concern, in line with results from sequencing of human samples. Amidst the COVID-19 pandemic, Denmark implemented a nationwide SARS-CoV-2 wastewater-based surveillance system that integrated routine surveillance from individual testing. Today, while testing for COVID-19 at the community level has been discontinued, the system is on the frontline to monitor the occurrence and spread of SARS-CoV-2 in Denmark.

Detection and quantification of adenovirus, polyomavirus, and papillomavirus in urban sewage

The objective of this study was to assess the occurrence and seasonal frequency of human adenovirus (HAdV), human polyomavirus (HPyV), and human papillomavirus (HPV) in urban sewage. The detection of these viruses was carried out by polymerase chain reaction (PCR), and then the viral concentrations in the positive samples were quantified by quantitative PCR (qPCR). Additionally, HAdV and HPyV genotyping was also performed by PCR. A total of 38/60 (63.3%) positive samples were found. HAdV was the most prevalent virus (26/60; 43.3%), followed by HPyV (21/60; 35%) and HPV (21/60; 35%). The viral concentrations ranged from 3.56 × 102 to 7.55 × 107 genome copies/L. The most common dual viral agents was found between HAdV and HPyV, in eight samples (8/38, 21%). HAdV types 40 and 41 as well as HPyV types JC and BK were identified, with HAdV-40 and HPyV JC being the most prevalent types. Furthermore, the detection rates of HAdV, HPyV, and HPV were higher during the winter season than the other seasons. The high prevalence of HAdV and HPyV supports their suitability as viral indicators of sewage contamination. Furthermore, this study demonstrates the advantages of environmental surveillance as a tool to elucidate the community-circulating viruses.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

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.

Monkeypox Virus in Wastewater Samples from Santiago Metropolitan Region, Chile

Sewage surveillance provides useful epidemiologic and public health information on viral infections at the population level. We detected monkeypox virus DNA from sewage samples covering 85% of the population in Santiago Metropolitan Region Chile. We also isolated infective viruses from those samples. Wastewater surveillance could complement clinical surveillance for monkeypox virus.

Wastewater surveillance in the COVID-19 post-emergency pandemic period: A promising approach to monitor and predict SARS-CoV-2 surges and evolution

On May 24, 2023, approximately 3.5 years into the pandemic, the World Health Organization (WHO) declared the end of the COVID-19 global health emergency. However, as there are still ∼3000 COVID-19 deaths per day in May 2023, robust surveillance systems are still warranted to return to normalcy in times of low risk and respond appropriately in times of high risk. The different phases of the pandemic have been defined by infection numbers and variants, both of which have been determined through clinical tests that are subject to many biases. Unfortunately, the end of the COVID-19 emergency threatens to exasperate these biases, thereby warranting alternative tracking methods. We hypothesized that wastewater surveillance could be used as a more accurate and comprehensive method to track SARS-CoV-2 in the post-emergency pandemic period (PEPP). SARS-CoV-2 was quantified and sequenced from wastewater between June 2022 and March 2023 to research the anticipated 2022/23 winter surge. However, in the 2022/23 winter, there was lower-than-expected SARS-CoV-2 circulation, which was hypothesized to be due to diagnostic testing biases but was confirmed by our wastewater analysis, thereby emphasizing the unpredictable nature of SARS-CoV-2 surges while also questioning its winter seasonality. Even in times of low baseline circulation, we found wastewater surveillance to be sensitive enough to detect minor changes in circulation levels ∼30-46 days prior to diagnostic tests, suggesting that wastewater surveillance may be a more appropriate early warning system to prepare for unpredictable surges in the PEPP. Furthermore, sequencing of wastewater detected variants of concern that were positively correlated with clinical samples and also provided a method to identify mutations with a high likelihood of appearing in future variants, necessary for updating vaccines and therapeutics prior to novel variant circulation. Together, these data highlight the effectiveness of wastewater surveillance in the PEPP to limit the global health burden of SARS-CoV-2 due to increases in circulation and/or viral evolution.

Prevalence and Molecular Epidemiology of Human Coronaviruses in Africa Prior to the SARS-CoV-2 Outbreak: A Systematic Review

Coronaviruses, re-emerging in human populations, cause mild or severe acute respiratory diseases, and occasionally epidemics. This study systematically reviewed human coronavirus (HCoVs) infections in Africa prior to the SARS-CoV-2 outbreak. Forty studies on the prevalence or molecular epidemiology of HCoVs were available from 13/54 African countries (24%). The first published data on HCoV was from South Africa in 2008. Eight studies (20%) reported on HCoV molecular epidemiology. Endemic HCoV prevalence ranged from 0.0% to 18.2%. The prevalence of zoonotic MERS-CoV ranged from 0.0% to 83.5%. Two studies investigated SARS-CoV infection, for which a prevalence of 0.0% was reported. There was heterogeneity in the type of tests used in determining HCoV prevalence. Two studies reported that risk factors for HCoV include exposure to infected animals or humans. The quantity of virologic investigations on HCoV on the African continent was scant, and Africa was not prepared for SARS-CoV-2.

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.

Monitoring COVID-19 spread in selected Prague's schools based on the presence of SARS-CoV-2 RNA in wastewater

The COVID-19 pandemic has demanded a broad range of techniques to better monitor its extent. Owing to its consistency, non-invasiveness, and cost effectiveness, wastewater-based epidemiology has emerged as a relevant approach to monitor the pandemic's course. In this work, we analyzed the extent of the COVID-19 pandemic in five primary schools in Prague, the Czech Republic, and how different preventive measures impact the presence of SARS-CoV-2 RNA copy numbers in wastewaters. Copy numbers were measured by reverse transcription-multiplex quantitative real-time PCR. These copy numbers were compared to the number of infected individuals in each school identified through regular clinical tests. Each school had a different monitoring regime and subsequent application of preventive measures to thwart the spread of COVID-19. The schools that constantly identified and swiftly quarantined infected individuals exhibited persistently low amounts of SARS-CoV-2 RNA copies in their wastewaters. In one school, a consistent monitoring of infected individuals, coupled with a delayed action to quarantine, allowed for the estimation of a linear model to predict the number of infected individuals based on the presence of SARS-CoV-2 RNA in the wastewater. The results show the importance of case detection and quarantining to stop the spread of the pandemic and its impact on the presence of SARS-CoV-2 RNA in wastewaters. This work also shows that wastewater-based epidemiological models can be reliably used even in small water catchments, but difficulties arise to fit models due to the nonconstant input of viral particles into the wastewater systems.

Exploration on wastewater-based epidemiology of SARS-CoV-2: Mimic relative quantification with endogenous biomarkers as internal reference

Wastewater-based epidemiology has become a powerful surveillance tool for monitoring the pandemic of COVID-19. Although it is promising to quantitatively correlate the SARS-CoV-2 RNA concentration in wastewater with the incidence of community infection, there is still no consensus on whether the viral nucleic acid concentration in sewage should be normalized against the abundance of endogenous biomarkers and which biomarker should be used as a reference for the normalization. Here, several candidate endogenous reference biomarkers for normalization of SARS-CoV-2 signal in municipal sewage were evaluated. The human fecal indicator virus (crAssphage) is a promising candidate of endogenous reference biomarker for data normalization of both DNA and RNA viruses for its intrinsic viral nature and high and stable content in sewage. Without constructing standard curves, the relative quantification of sewage viral nucleic acid against the abundance of the reference biomarker can be used to correlate with community COVID-19 incidence, which was proved via mimic experiments by spiking pseudovirus of different concentrations in sewage samples. Dilution of pseudovirus-seeded wastewater did not affect the relative abundance of viral nucleic acid, demonstrating that relative quantification can overcome the sewage dilution effects caused by the greywater input, precipitation and/or groundwater infiltration. The process of concentration, recovery and detection of the endogenous biomarker was consistent with that of SARS-CoV-2 RNA. Thus, it is necessary to co-quantify the endogenous biomarker because it can be not only an internal reference for data normalization, but also a process control.

Effects of COVID-19 pandemic on depression in patients with schizophrenia: A mini-review of the current evidence

BACKGROUND

Since the emergence of COVID-19, there have been concerns about the psychological effects of the pandemic on people's mental health around the world. People with psychotic disorders like schizophrenia (SCZ) may be more prone to develop mood disorders during the lockdowns due to their limited access to healthcare, reduced social support, and probable cognitive impairment.

METHODS

We conducted a systematic search on PubMed and Scopus to explore the effects of the pandemic on depressive symptoms in individuals with SCZ. A total of 12 studies were included.

RESULTS

Overall, studies suggested higher depression rates in patients with SCZ compared to healthy controls. Isolation due to the COVID-19 infection emerged as a risk factor for the development of depressive symptoms. However, results regarding the longitudinal changes of depression in SCZ patients during the lockdowns were inconsistent.

LIMITATIONS

The small sample sizes of studies, different depression scales and stages of the lockdowns, as well as the different government policies and restriction levels across the countries limit the conclusions of the present review.

CONCLUSIONS

Our review suggests an increased probability of depression in patients with SCZ during the pandemic. Identifying the risk factors for developing depression in this population helps find new, suitable approaches to address patients' needs and lower the adverse psychological effects of the pandemic.

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.

Wastewater-based epidemiology for preventing outbreaks and epidemics in Latin America - Lessons from the past and a look to the future

Wastewater-based epidemiology (WBE) is an approach with the potential to complement clinical surveillance systems. Using WBE, it is possible to carry out an early warning of a possible outbreak, monitor spatial and temporal trends of infectious diseases, produce real-time results and generate representative epidemiological information in a territory, especially in areas of social vulnerability. Despite the historical uses of this approach, particularly in the Global Polio Eradication Initiative, and for other pathogens, it was during the COVID-19 pandemic that occurred an exponential increase in environmental surveillance programs for SARS-CoV-2 in wastewater, with many experiences and developments in the field of public health using data for decision making and prioritizing actions to control the pandemic. In Latin America, WBE was applied in heterogeneous contexts and with emphasis on populations that present many socio-environmental inequalities, a condition shared by all Latin American countries. This manuscript addresses the concepts and applications of WBE in public health actions, as well as different experiences in Latin American countries, and discusses a model to implement this surveillance system at the local or national level. We emphasize the need to implement this sentinel surveillance system in countries that want to detect the early entry and spread of new pathogens and monitor outbreaks or epidemics of infectious agents in their territories as a complement of public health surveillance systems.

A rapid, high-throughput, and sensitive PEG-precipitation method for SARS-CoV-2 wastewater surveillance

The effective application of wastewater surveillance is dependent on testing capacity and sensitivity to obtain high spatial resolution testing results for a timely targeted public health response. To achieve this purpose, the development of rapid, high-throughput, and sensitive virus concentration methods is urgently needed. Various protocols have been developed and implemented in wastewater surveillance networks so far, however, most of them lack the ability to scale up testing capacity or cannot achieve sufficient sensitivity for detecting SARS-CoV-2 RNA at low prevalence. In the present study, using positive raw wastewater in Hong Kong, a PEG precipitation-based three-step centrifugation method was developed, including low-speed centrifugation for large particles removal and the recovery of viral nucleic acid, and medium-speed centrifugation for the concentration of viral nucleic acid. This method could process over 100 samples by two persons per day to reach the process limit of detection (PLoD) of 3286 copies/L wastewater. Additionally, it was found that the testing capacity could be further increased by decreasing incubation and centrifugation time without significantly influencing the method sensitivity. The entire procedure uses ubiquitous reagents and instruments found in most laboratories to obtain robust testing results. This high-throughput, cost-effective, and sensitive tool will promote the establishment of nearly real-time wastewater surveillance networks for valuable public health information.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.

Detection of hospital environmental contamination during SARS-CoV-2 Omicron predominance using a highly sensitive air sampling device

Background and objectives

The high transmissibility of SARS-CoV-2 has exposed weaknesses in our infection control and detection measures, particularly in healthcare settings. Aerial sampling has evolved from passive impact filters to active sampling using negative pressure to expose culture substrate for virus detection. We evaluated the effectiveness of an active air sampling device as a potential surveillance system in detecting hospital pathogens, for augmenting containment measures to prevent nosocomial transmission, using SARS-CoV-2 as a surrogate.

Methods

We conducted air sampling in a hospital environment using the AerosolSense^TM air sampling device and compared it with surface swabs for their capacity to detect SARS-CoV-2.

Results

When combined with RT-qPCR detection, we found the device provided consistent SARS-CoV-2 detection, compared to surface sampling, in as little as 2 h of sampling time. The device also showed that it can identify minute quantities of SARS-CoV-2 in designated "clean areas" and through a N95 mask, indicating good surveillance capacity and sensitivity of the device in hospital settings.

Conclusion

Active air sampling was shown to be a sensitive surveillance system in healthcare settings. Findings from this study can also be applied in an organism agnostic manner for surveillance in the hospital, improving our ability to contain and prevent nosocomial outbreaks.

Not a waste: Wastewater surveillance to enhance public health

Domestic wastewater, when collected and evaluated appropriately, can provide valuable health-related information for a community. As a relatively unbiased and non-invasive approach, wastewater surveillance may complement current practices towards mitigating risks and protecting population health. Spurred by the COVID-19 pandemic, wastewater programs are now widely implemented to monitor viral infection trends in sewersheds and inform public health decision-making. This review summarizes recent developments in wastewater-based epidemiology for detecting and monitoring communicable infectious diseases, dissemination of antimicrobial resistance, and illicit drug consumption. Wastewater surveillance, a quickly advancing Frontier in environmental science, is becoming a new tool to enhance public health, improve disease prevention, and respond to future epidemics and pandemics.

Wide mismatches in the sequences of primers and probes for monkeypox virus diagnostic assays

Rapid and accurate diagnosis of infections is fundamental to containment of disease. Several monkeypox virus (MPV) real-time diagnostic assays have been recommended by the CDC; however, the specificity of the primers and probes in these assays for the ongoing MPV outbreak has not been investigated. We analyzed the primer and probe sequences present in the CDC recommended MPV generic real-time PCR assay by aligning those sequences against 1730 MPV complete genomes reported in 2022 worldwide. Sequence mismatches were found in 99.08% and 97.46% of genomes for the MPV generic forward and reverse primers, respectively. Mismatch-corrected primers were synthetized and compared to the generic assay for MPV detection. Results showed that the two primer-template mismatches resulted in a ~11-fold underestimation of initial template DNA in the reaction and 4-fold increase in the 95% LOD. We further evaluated the specificity of seven other real-time PCR assays used for MPV and orthopoxvirus (OPV) detection and identified two assays with the highest matching score (>99.6%) to the global MPV genome database in 2022. Genetic variations in the primer-probe regions across MPV genomes could indicate the temporal and spatial emergence pattern of monkeypox disease. Our results show that the current MPV real-time generic assay may not be optimal to accurately detect MPV, and the mismatch-corrected assay with full complementarity between primers and current MPV genomes could provide a more sensitive and accurate detection of MPV.

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.

Sequencing and Variant Detection of Eight Abundant Plant-Infecting Tobamoviruses across Southern California Wastewater

Tobamoviruses are agriculturally relevant viruses that cause crop losses and have infected plants in many regions of the world. These viruses are frequently found in municipal wastewater, likely coming from human diet and industrial waste across wastewater catchment areas. As part of a large wastewater-based epidemiology study across Southern California, we analyzed RNA sequence data from 275 influent wastewater samples obtained from eight wastewater treatment plants with a catchment area of approximately 16 million people from July 2020 to August 2021. We assembled 1,083 high-quality genomes, enumerated viral sequencing reads, and detected thousands of single nucleotide variants from eight common tobamoviruses: bell pepper mottle virus, cucumber green mottle mosaic virus, pepper mild mottle virus, tobacco mild green mosaic virus, tomato brown rugose fruit virus, tomato mosaic virus, tomato mottle mosaic virus, and tropical soda apple mosaic virus. We show that single nucleotide variants had amino acid-altering consequences along with synonymous mutations, which represents potential evolution with functional consequences in genomes of these viruses. Our study shows the importance of wastewater sequencing to monitor the genomic diversity of these plant-infecting viruses, and we suggest that our data could be used to continue tracking the genomic variability of such pathogens. IMPORTANCE Diseases caused by viruses in the genus Tobamovirus cause crop losses around the world. As with other viruses, mutation occurring in the virus's genomes can have functional consequences and may alter viral infectivity. Many of these plant-infecting viruses have been found in wastewater, likely coming from human consumption of infected plants and produce. By sequencing RNA extracted from influent wastewater obtained from eight wastewater treatment plants in Southern California, we assembled high-quality viral genomes and detected thousands of single nucleotide variants from eight tobamoviruses. Our study shows that Tobamovirus genomes vary at many positions, which may have important consequences when designing assays for the detection of these viruses by agricultural or environmental scientists.

Application of neighborhood-scale wastewater-based epidemiology in low COVID-19 incidence situations

Wastewater-based epidemiology (WBE), an emerging approach for community-wide COVID-19 surveillance, was primarily characterized at large sewersheds such as wastewater treatment plants serving a large population. Although informed public health measures can be better implemented for a small population, WBE for neighborhood-scale sewersheds is less studied and not fully understood. This study applied WBE to seven neighborhood-scale sewersheds (average population of 1471) from January to November 2021. Community testing data showed an average of 0.004 % incidence rate in these sewersheds (97 % of monitoring periods reported two or fewer daily infections). In 92 % of sewage samples, SARS-CoV-2 N gene fragments were below the limit of quantification. We statistically determined 10^-2.6 as the threshold of the SARS-CoV-2 N gene concentration normalized to pepper mild mottle virus (N/PMMOV) to alert high COVID-19 incidence rate in the studied sewershed. This threshold of N/PMMOV identified neighborhood-scale outbreaks (COVID-19 incidence rate higher than 0.2 %) with 82 % sensitivity and 51 % specificity. Importantly, neighborhood-scale WBE can discern local outbreaks that would not otherwise be identified by city-scale WBE. Our findings suggest that neighborhood-scale WBE is an effective community-wide disease surveillance tool when COVID-19 incidence is maintained at a low level.

Wastewater-based surveillance in Italy leading to the first detection of mcr-10-positive Klebsiella quasipneumoniae

Wastewater-based surveillance enabled the first detection of the mobile colistin resistance gene mcr-10 in Italy. This plasmid-borne resistance gene was found in strains of Klebsiella quasipneumoniae isolated from samples of human raw sewage collected over several months. Although the isolates were phenotypically susceptible to colistin, the emergence of mcr-10 is concerning due to the highly variable expression of the gene and the potential for horizontal transfer to other species. In addition, the strains also carried an extended-spectrum β-lactamase gene and were phenotypically resistant to several beta-lactams. This study highlights the value of wastewater-based surveillance as an effective tool to monitor the emergence of antimicrobial resistance in strains circulating in the community and the environment.

The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond

The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them-the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.

SARS-CoV-2 in Atmospheric Particulate Matter: An Experimental Survey in the Province of Venice in Northern Italy

Analysis of atmospheric particulate matter (PM) has been proposed for the environmental surveillance of SARS-CoV-2. The aim of this study was to increase the current knowledge about the occurrence of SARS-CoV-2 in atmospheric PM, introduce a dedicated sampling method, and perform a simultaneous assessment of human seasonal coronavirus 229E. Thirty-two PM samples were collected on quartz fiber filters and six on Teflon using a low- and high-volumetric rate sampler, respectively, adopting a novel procedure for optimized virus detection. Sampling was performed at different sites in the Venice area (Italy) between 21 February and 8 March 2020 (n = 16) and between 27 October and 25 November 2020 (n = 22). A total of 14 samples were positive for Coronavirus 229E, 11 of which were collected in October–November 2020 (11/22; positivity rate 50%) and 3 in February–March 2020 (3/16 samples, 19%). A total of 24 samples (63%) were positive for SARS-CoV-2. Most of the positive filters were collected in October–November 2020 (19/22; positivity rate, 86%), whereas the remaining five were collected in February–March 2020 at two distinct sites (5/16, 31%). These findings suggest that outdoor PM analysis could be a promising tool for environmental surveillance. The results report a low concentration of SARS-CoV-2 in outdoor air, supporting a scarce contribution to the spread of infection.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early warning system during the first year of the COVID-19 pandemic: a systematic review

Since infected persons shed SARS-CoV-2 in faeces before symptoms appear, environmental surveillance (ES) may serve as an early warning system (EWS) for COVID-19 and new variants of concern. The ES of SARS-CoV-2 has been widely reviewed; however, its effectiveness as an EWS for SARS-CoV-2 in terms of timeliness, sensitivity and specificity has not been systematically assessed. We conducted a systematic review to identify and synthesise evidence on the ES of SARS-CoV-2 as an EWS to evaluate the added value for public health. Of 1,014 studies identified, we considered 29 for a qualitative synthesis of the timeliness of ES as an EWS for COVID-19, while six studies were assessed for the ability to detect new variants and two for both aims. The synthesis indicates ES may serve as an EWS of 1-2 weeks. ES could complement clinical surveillance for SARS-CoV-2; however, its cost-benefit value for public health decisions needs to be assessed based on the stage of the pandemic and resources available. Studies focusing methodological knowledge gaps as well as how to use and interpret ES signals for public health actions are needed, as is the sharing of knowledge within countries/areas with long experience of such surveillance.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in population-level SEIR model. We demonstrated that the temperature effect on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020 â€" Jan 25, 2021) in the Great Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 16 days and 8.6 folds ( R = 0.93), respectively. This work showcases a simple, yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.