Role of environmental poliovirus surveillance in global polio eradication and beyond

Leveraging wastewater-based epidemiology to monitor the spread of neglected tropical diseases in African communities

Neglected tropical diseases continue to cause a significant burden worldwide, with Africa accounting for more than one-third of the global burden. Over the past decade, progress has been made in eliminating, controlling, and eradicating these diseases in Africa. By December 2022, 47 out of 54 African countries had eliminated at least one neglected tropical disease, and more countries were close to achieving this milestone. Between 2020 and 2021, there was an 80 million reduction in people requiring intervention. However, continued efforts are needed to manage neglected tropical diseases and address their social and economic burden, as they deepen marginalisation and stigmatisation. Wastewater-based epidemiology involves analyzing wastewater to detect and quantify biomarkers of disease-causing pathogens. This approach can complement current disease surveillance systems in Africa and provide an additional layer of information for monitoring disease spread and detecting outbreaks. This is particularly important in Africa due to limited traditional surveillance methods. Wastewater-based epidemiology also provides a tsunami-like warning system for neglected tropical disease outbreaks and can facilitate timely intervention and optimised resource allocation, providing an unbiased reflection of the community's health compared to traditional surveillance systems. In this review, we highlight the potential of wastewater-based epidemiology as an innovative approach for monitoring neglected tropical disease transmission within African communities and improving existing surveillance systems. Our analysis shows that wastewater-based epidemiology can enhance surveillance of neglected tropical diseases in Africa, improving early detection and management of Buruli ulcers, hookworm infections, ascariasis, schistosomiasis, dengue, chikungunya, echinococcosis, rabies, and cysticercosis for better disease control.

Metagenomic analysis of sewage for surveillance of bacterial pathogens: A release experiment to determine sensitivity

Accurate monitoring of gastro-enteric and other diseases in large populations poses a challenge for public health management. Sewage represents a larger population, is freely obtainable and non-subject to ethical approval. Metagenomic sequencing offers simultaneous, multiple-target analysis. However, no study has demonstrated the sensitivity of metagenomics for detecting bacteria in sewage. In this study, we spot-released 1013 colony-forming units (CFU) of Staphyloccus hyicus (non-pathogenetic strain 842J-88). The strain was flushed down a toilet into the sewer in the catchment area of a public wastewater treatment plant (WWTP), serving a population of 36,000 people. Raw sewage was continuously sampled at the WWTP's inlet over 30- and 60-minute intervals for a total period of seven hours. The experiment was conducted twice with one week in-between release days and under comparable weather conditions. For the metagenomics analyses, the pure single isolate of S. hyicus was sequenced, assembled and added to a large database of bacterial reference sequences. All sewage samples were analyzed by shotgun metagenome sequencing and mapped against the reference database. S. hyicus was identified in duplicate samples at both of two release days and these sequence fragment counts served as a proxy to estimate the minimum number of sick people or sensitivity required in order to observe at least one sick person at 95% probability. We found the sensitivity to be in the range 41-140 and 16-36 sick people at release days 1 and 2, respectively. The WWTP normally serves 36,000 people giving a normalized sensitivity in the range of one in 257 to 2,250 persons.

Wastewater sequencing as a powerful tool to reveal SARS-CoV-2 variant introduction and spread in French Guiana, South America

The origin of introduction of a new pathogen in a country, the evolutionary dynamics of an epidemic within a country, and the role of cross-border areas on pathogen dynamics remain complex to disentangle and are often poorly understood. For instance, cross-border areas represent the ideal location for the sharing of viral variants between countries, with international air travel, land travel and waterways playing an important role in the cross-border spread of infectious diseases. Unfortunately, monitoring the point of entry and the evolutionary dynamics of viruses in space and time within local populations remain challenging. Here we tested the efficiency of wastewater-based epidemiology and genotyping in monitoring Covid-19 epidemiology and SARS-CoV-2 variant dynamics in French Guiana, a tropical country located in South America. Our results suggest that wastewater-based epidemiology and genotyping are powerful tools to monitor variant introduction and disease evolution within a tropical country but the inclusion of both clinical and wastewater samples could still improve our understanding of genetic diversity co-circulating. Wastewater sequencing also revealed the cryptic transmission of SARS-CoV-2 variants within the country. Interestingly, we found some amino acid changes specific to the variants co-circulating in French Guiana, suggesting a local evolution of the SARS-CoV-2 variants after their introduction. More importantly, our results showed that the proximity to bordering countries was not the origin of the emergence of the French Guianese B.1.160.25 variant, but rather that this variant emerged from an ancestor B.1.160 variant introduced by European air plane travelers, suggesting thus that air travel remains a significant risk for cross-border spread of infectious diseases. Overall, we suggest that wastewater-based epidemiology and genotyping provides a cost effective and non-invasive approach for pathogen monitoring and an early-warning tool for disease emergence and spread within a tropical country.

Development, confirmation, and application of a seeded Escherichia coli process control organism to validate Salmonella enterica serovar Typhi environmental surveillance methods

Salmonella enterica serovar Typhi (S. Typhi) is the causative agent of Typhoid fever. Blood culture is the gold standard for clinical diagnosis, but this is often difficult to employ in resource limited settings. Environmental surveillance of waste-impacted waters is a promising supplement to clinical surveillance, however validating methods is challenging in regions where S. Typhi concentrations are low. To evaluate existing S. Typhi environmental surveillance methods, a novel process control organism (PCO) was created as a biosafe surrogate. Using a previous described qPCR assay, a modified PCR amplicon for the staG gene was cloned into E. coli. We developed a target region that was recognized by the Typhoid primers in addition to a non-coding internal probe sequence. A multiplex qPCR reaction was developed that differentiates between the typhoid and control targets, with no cross-reactivity or inhibition of the two probes. The PCO was shown to mimic S. Typhi in lab-based experiments with concentration methods using primary wastewater: filter cartridge, recirculating Moore swabs, membrane filtration, and differential centrifugation. Across all methods, the PCO seeded at 10 CFU/mL and 100 CFU/mL was detected in 100% of replicates. The PCO is detected at similar quantification cycle (Cq) values across all methods at 10 CFU/mL (Average = 32.4, STDEV = 1.62). The PCO was also seeded into wastewater at collection sites in Vellore (India) and Blantyre (Malawi) where S. Typhi is endemic. All methods tested in both countries were positive for the seeded PCO. The PCO is an effective way to validate performance of environmental surveillance methods targeting S. Typhi in surface water.

Environmental Surveillance of Poliovirus and Non-polio Enteroviruses in Iran, 2017-2023: First Report of Imported Wild Poliovirus Type 1 Since 2000

In Iran, which is at high risk of the Wild Poliovirus (WPV) and Vaccine-Derived Poliovirus (VDPV) importation due to its neighborhood with two polio endemic countries, Pakistan and Afghanistan, Environmental Surveillance (ES) was established in November 2017. Sistan-Balouchestan province was chosen for the ES due to its vicinity with Pakistan and Afghanistan. Five sewage collection sites in 4 cities (Zahedan, Zabol, Chabahar and Konarak) were selected in the high-risk areas. Since the establishment of ES in November 2017 till the end of 2023, 364 sewage specimens were collected and analyzed. The ES detected polioviruses which have the highest significance for polio eradication program, that is, Wild Poliovirus type 1 (WPV1) and Poliovirus type 2 (PV2). In April and May 2019, three of 364 (0.8%) sewage specimens from Konarak were positive for imported WPV1. According to phylogenetic analysis, they were highly related to WPV1 circulating in Karachi (Sindh province) in Pakistan. PV2 was also detected in 5.7% (21/364) of the sewage specimens, most of which proved to be imported from the neighboring countries. Of 21 isolated PV2s, 7 were VDPV2, of which 5 proved to be imported from the neighboring countries as there was VDPV2 circulating in Pakistan at the time of sampling, and 2 were ambiguous VDPVs (aVDPV) with unknown source. According to the findings of this study, as long as WPV1 and VDPV2 outbreaks are detected in Iran's neighboring countries, there is a definite need for continuation and expansion of the environmental surveillance.

Advances in wastewater analysis revealing the co-circulating viral trends of noroviruses and Omicron subvariants

Co-presence of enveloped and non-enveloped viruses is common both in community circulation and in wastewater. Community surveillance of infections requires robust methods enabling simultaneous quantification of multiple viruses in wastewater. Using enveloped SARS-CoV-2 Omicron subvariants and non-enveloped norovirus (NoV) as examples, this study reports a robust method that integrates electronegative membrane (EM) concentration, viral inactivation, and RNA preservation (VIP) with efficient capture and enrichment of the viral RNA on magnetic (Mag) beads, and direct detection of RNA on the beads. This method provided improved viral recoveries of 80 ± 4 % for SARS-CoV-2 and 72 ± 5 % for Murine NoV. Duplex reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays with newly designed degenerate primer-probe sets offered high PCR efficiencies (90-91 %) for NoV (GI and GII) targets and were able to detect as few as 15 copies of the viral RNA per PCR reaction. This technique, combined with duplex detection of NoV and multiplex detection of Omicron, successfully quantified NoV (GI and GII) and Omicron variants in the same sets of 94 influent wastewater samples collected from two large wastewater systems between July 2022 and June 2023. The wastewater viral RNA results showed temporal changes of both NoV and Omicron variants in the same wastewater systems and revealed an inverse relationship of their emergence. This study demonstrated the importance of a robust analytical platform for simultaneous surveillance of enveloped and non-enveloped viruses in wastewater. The ability to sensitively determine multiple viral pathogens in wastewater will advance applications of wastewater surveillance as a complementary public health tool.

Wastewater-Based Epidemiology for Viral Surveillance from an Endemic Perspective: Evidence and Challenges

Wastewater-based epidemiology (WBE) is currently used to monitor not only the spread of the viral SARS-CoV-2 pandemic but also that of other viruses in endemic conditions, particularly in the absence of syndromic surveillance. The continuous monitoring of sewage requires high expenditure and significant time investments, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Tuscany (Italy) and targeted human adenovirus (HAdV), norovirus genogroup II (NoVggII), enterovirus (EV), and SARS-CoV-2. Samples were collected at the entrances of treatment plants and concentrated using PEG/NaCl precipitation, and viral nucleic acids were extracted and detected through real-time reverse transcription qPCR. NoVggII was the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. Compared with data that were previously collected in the same study area (from February 2021 to September 2021), the results for SARS-CoV-2 revealed a shift from an epidemic to an endemic pattern, at least in the region under investigation, which was likely due to viral mutations that led to the spreading of new variants with increased resistance to summer environmental conditions. In conclusion, using standardized methods and an efficient monitoring strategy, WBE proves valuable for viral surveillance in pandemic and epidemic scenarios, enabling the identification of temporal-local distribution patterns that are useful for making informed public health decisions.

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.

Environmental surveillance reveals co-circulation of distinctive lineages of enteroviruses in southwest China's border cities, 2020-2022

AIMS

Enteroviruses are significant human pathogens associated with a range of mild to severe diseases. This study aims to understand the diversity and genetic characterization of enteroviruses circulated in southwest China's border cities by using environmental surveillance.

METHODS AND RESULTS

A total of 96 sewage samples were collected in three border cities and a port located in Yunnan Province, China from July 2020 to June 2022. After cell culture and VP1 sequencing, a total of 590 enterovirus isolates were identified, belonging to 21 types. All PV strains were Sabin-like with ≤6 nucleotide mutations in the VP1 coding region. Echovirus 6, echovirus 21 (a rare serotype in previous studies), and coxsackievirus B5 were the predominant serotypes, which accounted for 21.19%, 18.31%, and 13.39% of the total isolates, respectively. The prevalence of the common serotypes varied across different border cities and periods. Phylogenetic analysis revealed the presence of multiple evolutionary lineages for E21, E6, and E30, some of which formed distinct branches.

CONCLUSIONS

High diversity of enteroviruses and distinct lineages of predominant serotypes circulated in southwest China's border cities.

Development of a computational model to inform environmental surveillance sampling plans for Salmonella enterica serovar Typhi in wastewater

Typhoid fever-an acute febrile disease caused by infection with the bacterium Salmonella enterica serotype Typhi (S. Typhi)-continues to be a leading cause of global morbidity and mortality, particularly in developing countries with limited access to safe drinking water and adequate sanitation. Environmental surveillance, the process of detecting and enumerating disease-causing agents in wastewater, is a useful tool to monitor the circulation of typhoid fever in endemic regions. The design of environmental surveillance sampling plans and the interpretation of sampling results is complicated by a high degree of uncertainty and variability in factors that affect the final measured pathogens in wastewater samples, such as pathogen travel time through a wastewater network, pathogen dilution, decay and degradation, and laboratory processing methods. Computational models can, to an extent, assist in the design of sampling plans and aid in the evaluation of how different contributing factors affect sampling results. This study presents a computational model combining dynamic and probabilistic modeling techniques to estimate-on a spatial and temporal scale-the approximate probability of detecting S. Typhi within a wastewater system. This model may be utilized to inform environmental surveillance sampling plans and may provide useful insight into selecting appropriate sampling locations and times and interpreting results. A simulated applied modeling scenario is presented to demonstrate the model's functionality for aiding an environmental surveillance study in a typhoid-endemic community.

A scoping review of human pathogens detected in untreated human wastewater and sludge

Wastewater monitoring is an approach to identify the presence or abundance of pathogens within a population. The objective of this scoping review (ScR) was to identify and characterize research on human pathogens and antimicrobial resistance detected in untreated human wastewater and sludge. A search was conducted up to March 2023 and standard ScR methodology was followed. This ScR included 1,722 articles, of which 56.5% were published after the emergence of COVID-19. Viruses and bacteria were commonly investigated, while research on protozoa, helminths, and fungi was infrequent. Articles prior to 2019 were dominated by research on pathogens transmitted through fecal-oral or waterborne pathways, whereas more recent articles have explored the detection of pathogens transmitted through other pathways such as respiratory and vector-borne. There was variation in sampling, samples, and sample processing across studies. The current evidence suggests that wastewater monitoring could be applied to a range of pathogens as a public health tool to detect an emerging pathogen and understand the burden and spread of disease to inform decision-making. Further development and refinement of the methods to identify and interpret wastewater signals for different prioritized pathogens are needed to develop standards on when, why, and how to monitor effectively.

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

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

Targeted community wastewater surveillance for SARS-CoV-2 and Mpox virus during a festival mass-gathering event

Wastewater surveillance has emerged recently as a powerful approach to understanding infectious disease dynamics in densely populated zones. Wastewater surveillance, while promising as a public health tool, is often hampered by slow turn-around times, complex analytical protocols, and resource-intensive techniques. In this study, we evaluated an affinity capture method and microfluidic digital PCR as a rapid approach to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mpox (formerly known as monkeypox) virus, and fecal indicator, pepper mild mottle virus (PMMoV) in wastewater during a mass-gathering event. Wastewater samples (n = 131) were collected from residential and commercial manholes, pump stations, and a city's wastewater treatment plant. The use of Nanotrap® Microbiome Particles and microfluidic digital PCR produced comparable results to other established methodologies, with reduced process complexity and analytical times, providing same day results for public health preparedness and response. Using indigenous SARS-CoV-2 and PMMoV in wastewater, the average viral recovery efficiency was estimated at 10.1 %. Both SARS-CoV-2 N1 and N2 genes were consistently detected throughout the sampling period, with increased RNA concentrations mainly in wastewater samples collected from commercial area after festival mass gatherings. The mpox virus was sporadically detected in wastewater samples during the surveillance period, without distinct temporal trends. SARS-CoV-2 RNA concentrations in the city's wastewater mirrored the city's COVID-19 cases, confirming the predictive properties of wastewater surveillance. Wastewater surveillance continues to be beneficial for tracking diseases that display gastrointestinal symptoms, including SARS-CoV-2, and can be a powerful tool for sentinel surveillance. However, careful site selection and a thorough understanding of community dynamics are necessary when performing targeted surveillance during temporary mass-gathering events as potential confirmation bias may occur.

The detection of Japanese encephalitis virus in municipal wastewater during an acute disease outbreak

AIM

To demonstrate the capability of wastewater-based surveillance (WBS) as a tool for detecting potential cases of Japanese Encephalitis Virus (JEV) infection in the community.

METHODS AND RESULTS

In this study, we explore the potential of WBS to detect cases of JEV infection by leveraging from an established SARS-CoV-2 wastewater surveillance program. We describe the use of two reverse transcriptase quantitative polymerase chain reaction (RTqPCR) assays targeting JEV to screen archived samples from two wastewater treatment plants (WWTPs). JEV was detected in wastewater samples collected during a timeframe coinciding with a cluster of acute human encephalitis cases, alongside concurrent evidence of JEV detection in mosquito surveillance and the sentinel chicken programs within South Australia's Riverland and Murraylands regions.

CONCLUSIONS

Current surveillance measures for JEV encounter multiple constraints, which may miss the early stages of JEV circulation or fail to capture the full extent of transmission. The detection of JEV in wastewater during a disease outbreak highlights the potential WBS has as a complementary layer to existing monitoring efforts forming part of the One Health approach required for optimal disease response and control.

Wastewater surveillance of the most common circulating respiratory viruses in Athens: The impact of COVID-19 on their seasonality

Due to governments' actions to contain the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the activity of common circulating respiratory viruses was significantly disrupted after the COVID-19 pandemic and thorough surveillance of respiratory pathogens was considered essential worldwide. Wastewater-based epidemiology has proven to be a valuable tool, that provides complementary information on disease outbreaks and is increasingly used to study the infection dynamics of other viruses, apart from SARS-CoV-2. The aims of the present study were the detection of four commonly circulating respiratory viruses: SARS-CoV-2, influenza A, B and Human Respiratory Syncytial Virus (RSV), the evaluation of the COVID-19 pandemic impact on their seasonality and the determination of the possible common trends in the viral load of these viruses in the wastewater of the Attica region. A standardized and validated concentration and extraction protocol was used, generic for all four viruses, followed by Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) assays. The study proved that there was a prolonged period when all four viruses circulated in the population and an early outbreak of seasonal influenza and RSV in 2022-2023, compared to data from the pre-COVID-19 period. SARS-CoV-2, influenza A and RSV concentrations showed peak levels during December, followed by a slight decline in influenza A concentrations, followed by steady increase of influenza B concentrations in January 2023. SARS-CoV-2 was the dominant virus throughout the whole study period. This is the first study in Greece that investigated the most common circulating viruses simultaneously and in one of the largest timelines, providing crucial information about their infection dynamics during a period when an outbreak of respiratory diseases was declared by the National Public Health Organization. Presented results highlight the establishment of environmental surveillance as a non-invasive and complementary virus outbreak monitoring tool and the importance of influenza A, B and RSV integration into a wastewater-based surveillance system to help in disease management.

Development and validation of a duplex RT-qPCR assay for norovirus quantification in wastewater samples

Norovirus (NoV) is a highly contagious enteric virus that causes widespread outbreaks and a substantial number of deaths across communities. As clinical surveillance is often insufficient, wastewater-based epidemiology (WBE) may provide novel pathways of tracking outbreaks. To utilise WBE, it is important to use accurate and sensitive methods for viral quantification. In this study, we developed a one-step duplex RT-qPCR assay to simultaneously test the two main human pathogenic NoV genogroups, GI and GII, in wastewater samples. The assay had low limits of detection (LOD), namely 0.52 genome copies (gc)/µl for NoVGI and 1.37 gc/µl for NoVGII. No significant concentration-dependent interactions were noted for both NoVGI and for NoVGII when the two targets were mixed at different concentrations in the samples. When tested on wastewater-derived RNA eluents, no significant difference between duplex and singleplex concentrations were found for either target. Low levels of inhibition (up to 32 %) were noted due to organic matter present in the wastewater extracts. From these results we argue that the duplex RT-qPCR assay developed enables the sensitive detection of both NoVGI and NoVGII in wastewater-derived RNA eluents, in a time and cost-effective way and may be used for surveillance to monitor public and environmental health.

Systematic review and meta-analysis of human health-related protein markers for realizing real-time wastewater-based epidemiology

For effective implementation of the wastewater-based epidemiology (WBE) approach, real-time quantification of markers in wastewater is critical for data acquisition before data interpretation, dissemination, and decision-making. This can be achieved by using biosensor technology, but whether the quantification/detection limits of different types of biosensors comply with the concentration of WBE markers in wastewater is unclear. In the present study, we identified promising protein markers with relatively high concentrations in wastewater samples and analyzed biosensor technologies that are potentially available for real-time WBE. The concentrations of potential protein markers in stool and urine samples were obtained through systematic review and meta-analysis. We examined 231 peer-review papers to collect information regarding potential protein markers that can enable us to achieve real-time monitoring using biosensor technology. Fourteen markers in stool samples were identified at the ng/g level, presumably equivalent to ng/L of wastewater after dilution. Moreover, relatively high average concentrations of fecal inflammatory proteins were observed, e.g., fecal calprotectin, clusterin, and lactoferrin. Fecal calprotectin exhibited the highest average log concentration among the markers identified in stool samples with its mean value being 5.24 [95 % CI: 5.05, 5.42] ng/g. We identified 50 protein markers in urine samples at the ng/mL level. Uromodulin (4.48 [95 % CI: 4.20, 4.76] ng/mL) and plasmin (4.18 [95 % CI: 3.15, 5.21] ng/mL) had the top two highest log concentrations in urine samples. Furthermore, the quantification limit of some electrochemical- and optical-based biosensors was found to be around the femtogram/mL level, which is sufficiently low to detect protein markers in wastewater even after dilution in sewer pipes.

Wastewater surveillance beyond COVID-19: a ranking system for communicable disease testing in the tri-county Detroit area, Michigan, USA

Introduction

Throughout the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has been utilized to monitor the disease in the United States through routine national, statewide, and regional monitoring projects. A significant canon of evidence was produced showing that wastewater surveillance is a credible and effective tool for disease monitoring. Hence, the application of wastewater surveillance can extend beyond monitoring SARS-CoV-2 to encompass a diverse range of emerging diseases. This article proposed a ranking system for prioritizing reportable communicable diseases (CDs) in the Tri-County Detroit Area (TCDA), Michigan, for future wastewater surveillance applications at the Great Lakes Water Authority's Water Reclamation Plant (GLWA's WRP).

Methods

The comprehensive CD wastewater surveillance ranking system (CDWSRank) was developed based on 6 binary and 6 quantitative parameters. The final ranking scores of CDs were computed by summing the multiplication products of weighting factors for each parameter, and then were sorted based on decreasing priority. Disease incidence data from 2014 to 2021 were collected for the TCDA. Disease incidence trends in the TCDA were endowed with higher weights, prioritizing the TCDA over the state of Michigan.

Results

Disparities in incidences of CDs were identified between the TCDA and state of Michigan, indicating epidemiological differences. Among 96 ranked CDs, some top ranked CDs did not present relatively high incidences but were prioritized, suggesting that such CDs require significant attention by wastewater surveillance practitioners, despite their relatively low incidences in the geographic area of interest. Appropriate wastewater sample concentration methods are summarized for the application of wastewater surveillance as per viral, bacterial, parasitic, and fungal pathogens.

Discussion

The CDWSRank system is one of the first of its kind to provide an empirical approach to prioritize CDs for wastewater surveillance, specifically in geographies served by centralized wastewater collection in the area of interest. The CDWSRank system provides a methodological tool and critical information that can help public health officials and policymakers allocate resources. It can be used to prioritize disease surveillance efforts and ensure that public health interventions are targeted at the most potentially urgent threats. The CDWSRank system can be easily adopted to geographical locations beyond the TCDA.

Environmental sampling for disease surveillance: Recent advances and recommendations for best practice

The study of infectious diseases includes both the progression of the disease in its host and how it transmits between hosts. Understanding disease transmission is important for recommending effective interventions, protecting healthcare workers, and informing an effective public health response. Sampling the environment for infectious diseases is critical to public health since it can provide an understanding of the mechanisms of transmission, characterization of contamination in hospitals and other public areas, and the spread of a disease within a community. Measurements of biological aerosols, particularly those that may cause disease, have been an ongoing topic of research for decades, and so a wide variety of technological solutions exist. This wide field of possibilities can create confusion, particularly when different approaches yield different answers. Therefore, guidelines for best practice in this area are important to allow more effective use of this data in public health decisions. This review examines air, surface and water/wastewater sampling methods, with a focus on aerosol sampling, and a goal of recommending approaches to designing and implementing sampling systems that may incorporate multiple strategies. This is accomplished by developing a framework for designing and evaluating a sampling strategy, reviewing current practices and emerging technologies for sampling and analysis, and recommending guidelines for best practice in the area of aerosol sampling for infectious disease.

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

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

Environmental surveillance detects circulating vaccine-derived poliovirus type 2 that was undetected by acute flaccid paralysis surveillance in 2021 in Uganda

The success of the global polio eradication initiative is threatened by the genetic instability of the oral polio vaccine, which can result in the emergence of pathogenic vaccine-derived polioviruses following prolonged replication in the guts of individuals with primary immune deficiencies or in communities with low vaccination coverage. Through environmental surveillance, circulating vaccine-derived poliovirus type 2 was detected in Uganda in the absence of detection by acute flaccid paralysis (AFP) surveillance. This underscores the sensitivity of environmental surveillance and emphasizes its usefulness in supplementing AFP surveillance for poliovirus infections in the race towards global polio eradication.

Pepper Mild Mottle Virus as a Potential Indicator of Fecal Contamination in Influents of Wastewater Treatment Plants in Riyadh, Saudi Arabia

Several indicators of fecal pollution in water resources are continuously monitored for their reliability and, of particular interest, their correlation to human enteric viruses-not justified by traditional bacterial indicators. Pepper mild mottle virus (PMMoV) has recently been proposed as a successful viral surrogate of human waterborne viruses; however, in Saudi Arabia there are no available data in terms of its prevalence and concentration in water bodies. The concentration of PMMoV in three different wastewater treatment plants (King Saud University (KSU), Manfoha (MN), and Embassy (EMB) wastewater treatment plants (WWTP)) was measured using qRT-PCR during a one-year period and compared to the human adenovirus (HAdV), which is highly persistent and considered an indicator for viral-mediated fecal contamination. PMMoV was found in ~94% of the entire wastewater samples (91.6-100%), with concentrations ranging from 62 to 3.5 × 10⁷ genome copies/l (GC/l). However, HAdV was detected in 75% of raw water samples (~67-83%). The HAdV concentration ranged between 1.29 × 10³ GC/L and 1.26 × 10⁷ GC/L. Higher positive correlation between PMMoV and HAdV concentrations was detected at MN-WWTP (r = 0.6148) than at EMB-WWTP (r = 0.207). Despite the lack of PMMoV and HAdV seasonality, a higher positive correlation (r = 0.918) of PMMoV to HAdV was recorded at KSU-WWTP in comparison to EMB-WWTP (r = 0.6401) around the different seasons. Furthermore, meteorological factors showed no significant influence on PMMoV concentrations (p > 0.05), thus supporting the use of PMMoV as a possible fecal indicator of wastewater contamination and associated public health issues, particularly at MN-WWTP. However, a continuous monitoring of the PMMoV distribution pattern and concentration in other aquatic environments, as well as its correlation to other significant human enteric viruses, is essential for ensuring its reliability and reproducibility as a fecal pollution indicator.

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

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

Rapid Reverse Purification DNA Extraction Approaches to Identify Microbial Pathogens in Wastewater

Wastewater monitoring became a promising solution in the early detection of outbreaks. Despite the achievements in the identification of pathogens in wastewater using real-time PCR, there is still a lack of reliable rapid nucleic acid extraction protocols. Therefore, in this study, samples were subjected to alkali, proteinase K and/or bead-beating followed by reverse purification magnetic beads-based separation. Wastewater samples spiked with S. aureus, E. coli and C. parvum were used as examples for Gram-positive and -negative bacteria and protozoa, respectively. All results were compared with a spin column technology as a reference method. Proteinase K with bead beating (vortexing with 0.1 mm glass beads for three minutes) was particularly successful for bacterial DNA extraction (three- to five-fold increase). The most useful extraction protocol for protozoa was pre-treatment with proteinase K (eight-fold increase). The selected methods were sensitive as far as detecting one bacterial cell per reaction for S. aureus, ten bacterial cells for E. coli and two oocysts for C. parvum. The extraction reagents are cold chain independent and no centrifuge or other large laboratory equipment is required to perform DNA extraction. A controlled validation trial is needed to test the effectiveness at field levels.

Sampling Considerations for Wastewater Surveillance of Antibiotic Resistance in Fecal Bacteria

Wastewaters can be analyzed to generate population-level data for public health surveillance, such as antibiotic resistance monitoring. To provide representative data for the contributing population, bacterial isolates collected from wastewater should originate from different individuals and not be distorted by a selection pressure in the wastewater. Here we use Escherichia coli diversity as a proxy for representativeness when comparing grab and composite sampling at a major municipal wastewater treatment plant influent and an untreated hospital effluent in Gothenburg, Sweden. All municipal samples showed high E. coli diversity irrespective of the sampling method. In contrast, a marked increase in diversity was seen for composite compared to grab samples from the hospital effluent. Virtual resampling also showed the value of collecting fewer isolates on multiple occasions rather than many isolates from a single sample. Time-kill tests where individual E. coli strains were exposed to sterile-filtered hospital wastewater showed rapid killing of antibiotic-susceptible strains and significant selection of multi-resistant strains when incubated at 20 °C, an effect which could be avoided at 4 °C. In conclusion, depending on the wastewater collection site, both sampling method and collection/storage temperature could significantly impact the representativeness of the wastewater sample.

When case reporting becomes untenable: Can sewer networks tell us where COVID-19 transmission occurs?

Monitoring SARS-CoV-2 in wastewater is a valuable approach to track COVID-19 transmission. Designing wastewater surveillance (WWS) with representative sampling sites and quantifiable results requires knowledge of the sewerage system and virus fate and transport. We developed a multi-level WWS system to track COVID-19 in Atlanta using an adaptive nested sampling strategy. From March 2021 to April 2022, 868 wastewater samples were collected from influent lines to wastewater treatment facilities and upstream community manholes. Variations in SARS-CoV-2 concentrations in influent line samples preceded similar variations in numbers of reported COVID-19 cases in the corresponding catchment areas. Community sites under nested sampling represented mutually-exclusive catchment areas. Community sites with high SARS-CoV-2 detection rates in wastewater covered high COVID-19 incidence areas, and adaptive sampling enabled identification and tracing of COVID-19 hotspots. This study demonstrates how a well-designed WWS provides actionable information including early warning of surges in cases and identification of disease hotspots.

A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic

The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks. We consider weekly averages of flow-normalised viral concentration, reported as the number of SARS-CoV-2N1 gene copies per litre (gc/L) of wastewater available at 303 STWs over the period between 1 June 2021 and 30 March 2022. We specify a spatially continuous statistical model that quantifies the relationship between weekly viral concentration and a collection of covariates covering socio-demographics, land cover and virus associated genomic characteristics at STW catchment areas while accounting for spatial and temporal correlation. We evaluate the model's predictive performance at the catchment level through 10-fold cross-validation. We predict the weekly viral concentration at the population-weighted centroid of the 32,844 lower super output areas (LSOAs) in England, then aggregate these LSOA predictions to the Lower Tier Local Authority level (LTLA), a geography that is more relevant to public health policy-making. We also use the model outputs to quantify the probability of local changes of direction (increases or decreases) in viral concentration over short periods (e.g. two consecutive weeks). The proposed statistical framework can predict SARS-CoV-2 viral concentration in wastewater at high spatio-temporal resolution across England. Additionally, the probabilistic quantification of local changes can be used as an early warning tool for public health surveillance.

Metagenomic sequencing combined with flow cytometry facilitated a novel microbial risk assessment framework for bacterial pathogens in municipal wastewater without cultivation

A workflow that combined metagenomic sequencing with flow cytometry was developed. The absolute abundance of pathogens was accurately estimated in mock communities and real samples. Metagenome-assembled genomes binned from metagenomic data set is robust in phylogenetic analysis and virulence profiling.

Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

Monitoring of SARS-CoV-2 concentration and circulation of variants of concern in wastewater of Leuven, Belgium

Wastewater surveillance plays an important role in the management of the coronavirus disease 2019 (COVID-19) pandemic all over the world. Using different wastewater collection points in Leuven, we wanted to investigate the use of wastewater surveillance as an early warning system for an uprise of infections and as a tool to follow the circulation of specific variants of concern (VOCs) in particular geographic areas. Wastewater samples were collected from local neighborhood sewers and from a large regional wastewater treatment plant (WWTP) in the area of Leuven, Belgium. After virus concentration, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was quantified by real-time quantitative polymerase chain reaction (RT-qPCR) and normalized with the human fecal indicator pepper mild mottle virus (PMMoV). A combination of multiplex RT-qPCR assays was used to detect signature mutations of circulating VOCs. Fecal virus shedding of SARS-CoV-2 variants was measured in feces samples of hospitalized patients. In two residential sampling sites, a rise in wastewater SARS-CoV-2 concentration preceded peaks in positive cases. In the WWTP, viral load peaks were seen concomitant with the consecutive waves of positive cases caused by the original Wuhan SARS-CoV-2 strain and subsequent VOCs. During the Omicron BA.1 wave, the wastewater viral load increased to a lesser degree, even after normalization of SARS-CoV-2 concentration using PMMoV. This might be attributable to a lower level of fecal excretion of this variant. Circulation of SARS-CoV-2 VOCs Alpha, Delta, Omicron BA1/BA.2, and BA.4/BA.5 could be detected based on the presence of specific key mutations. The shift in variants was noticeable in the wastewater, with key mutations of two different variants being present simultaneously during the transition period. Wastewater-based surveillance is a sensitive tool to monitor SARS-CoV-2 circulation levels and VOCs in larger regions. In times of reduced test capacity, this can prove to be highly valuable. Differences in excretion levels of various SARS-CoV-2 variants should however be taken into account when using wastewater surveillance to monitor SARS-CoV-2 circulation levels in the population.

Long-term SARS-CoV-2 surveillance in the wastewater of Stockholm: What lessons can be learned from the Swedish perspective?

Wastewater-based epidemiology (WBE) can be used to track the spread of SARS-CoV-2 in a population. This study presents the learning outcomes from over two-year long monitoring of SARS-CoV-2 in Stockholm, Sweden. The three main wastewater treatment plants in Stockholm, with a total of six inlets, were monitored from April 2020 until June 2022 (in total 600 samples). This spans five major SARS-CoV-2 waves, where WBE data provided early warning signals for each wave. Further, the measured SARS-CoV-2 content in the wastewater correlated significantly with the level of positive COVID-19 tests (r = 0.86; p << 0.0001) measured by widespread testing of the population. Moreover, as a proof-of-concept, six SARS-CoV-2 variants of concern were monitored using hpPCR assay, demonstrating that variants can be traced through wastewater monitoring. During this long-term surveillance, two sampling protocols, two RNA concentration/extraction methods, two calculation approaches, and normalization to the RNA virus Pepper mild mottle virus (PMMoV) were evaluated. In addition, a study of storage conditions was performed, demonstrating that the decay of viral RNA was significantly reduced upon the addition of glycerol to the wastewater before storage at -80 °C. Our results provide valuable information that can facilitate the incorporation of WBE as a prediction tool for possible future outbreaks of SARS-CoV-2 and preparations for future pandemics.

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.

COVID-19 surveillance in wastewater: An epidemiological tool for the monitoring of SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic has prompted a lot of questions globally regarding the range of information about the virus's possible routes of transmission, diagnostics, and therapeutic tools. Worldwide studies have pointed out the importance of monitoring and early surveillance techniques based on the identification of viral RNA in wastewater. These studies indicated the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in human feces, which is shed via excreta including mucus, feces, saliva, and sputum. Subsequently, they get dumped into wastewater, and their presence in wastewater provides a possibility of using it as a tool to help prevent and eradicate the virus. Its monitoring is still done in many regions worldwide and serves as an early "warning signal"; however, a lot of limitations of wastewater surveillance have also been identified.

Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 10² genomic copies/L to 6.87 × 10³ gc/L and N2 values ranging from 1.91 × 10² gc/L to 6.45 × 10³ gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.

Assessment of a mass balance equation for estimating community-level prevalence of COVID-19 using wastewater-based epidemiology in a mid-sized city

Wastewater-based epidemiology (WBE) has emerged as a valuable epidemiologic tool to detect the presence of pathogens and track disease trends within a community. WBE overcomes some limitations of traditional clinical disease surveillance as it uses pooled samples from the entire community, irrespective of health-seeking behaviors and symptomatic status of infected individuals. WBE has the potential to estimate the number of infections within a community by using a mass balance equation, however, it has yet to be assessed for accuracy. We hypothesized that the mass balance equation-based approach using measured SARS-CoV-2 wastewater concentrations can generate accurate prevalence estimates of COVID-19 within a community. This study encompassed wastewater sampling over a 53-week period during the COVID-19 pandemic in Gainesville, Florida, to assess the ability of the mass balance equation to generate accurate COVID-19 prevalence estimates. The SARS-CoV-2 wastewater concentration showed a significant linear association (Parameter estimate = 39.43, P value < 0.0001) with clinically reported COVID-19 cases. Overall, the mass balance equation produced accurate COVID-19 prevalence estimates with a median absolute error of 1.28%, as compared to the clinical reference group. Therefore, the mass balance equation applied to WBE is an effective tool for generating accurate community-level prevalence estimates of COVID-19 to improve community surveillance.

Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes

Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.

Wastewater research and surveillance: an ethical exploration

The current COVID-19 pandemic has given wastewater research a huge impetus. While wastewater research has some promising applications, there are as yet no well-developed ethical guidelines on how and under what conditions to use wastewater research. The current perspective paper aims to explore the different ethical questions pertaining to wastewater research and surveillance and to provide some tentative guidelines on the desirability of different types of applications. This paper shows that wastewater research offers interesting possibilities, but that legal regulation and ethical guidelines are still lacking, while there are ethical risks involved. The perspective indicates that it is important to look beyond the regulation of data collection and to shift the focus to the question how the analysis and use of wastewater data can be supervised.

Community-Based SARS-CoV-2 Testing Using Saliva or Nasopharyngeal Swabs to Compare the Performance of Weekly COVID-19 Screening to Wastewater SARS-CoV-2 Signals

Multiple studies worldwide have confirmed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be detected in wastewater. However, there is a lack of data directly comparing the wastewater SARS-CoV-2 RNA concentration with the prevalence of coronavirus disease 2019 (COVID-19) in individuals living in sewershed areas. Here, we correlate wastewater SARS-CoV-2 signals with SARS-CoV-2 positivity rates in symptomatic and asymptomatic individuals and compare positivity rates in two underserved communities in Portland, Oregon to those reported in greater Multnomah County. 403 individuals were recruited via two COVID-19 testing sites over a period of 16 weeks. The weekly SARS-CoV-2 positivity rate in our cohort ranged from 0 to 21.7% and trended higher than symptomatic positivity rates reported by Multnomah County (1.9-8.7%). Among the 362 individuals who reported symptom status, 76 were symptomatic and 286 were asymptomatic. COVID-19 was detected in 35 participants: 24 symptomatic, 9 asymptomatic, and 2 of unknown symptomatology. Wastewater testing yielded 0.33-149.9 viral RNA genomic copies/L/person and paralleled community COVID-19 positive test rates. In conclusion, wastewater sampling accurately identified increased SARS-CoV-2 within a community. Importantly, the rate of SARS-CoV-2 positivity in underserved areas is higher than positivity rates within the County as a whole, suggesting a disproportionate burden of SARS-CoV-2 in these communities.

Poliovirus returns to the UK after nearly 40 years: current efforts and future recommendations

On 22 June 2022, the UK Health Security Agency declared a 'rare national incidence' after finding poliovirus in sewage in London for the first time in nearly 40 years. Although no cases of the disease or accompanying paralysis have been documented, the general public's risk is considered minimal. However, public health experts recommend that families are up to date on their polio vaccines to decrease the chance of harm. This article discusses the epidemiology of poliovirus by examining the aetiology of the disease and current mitigation policies implemented to prevent the spread of type 2 vaccine-deceived poliovirus in the UK. Finally, by examining the clinical features of polio, which range from mild gastroenteritis episodes, respiratory sickness, malaise and severe paralysis type, this article offers an advice on particular therapies and tactics to avoid poliovirus outbreaks and other future outbreaks.

Surveillance Program of Clinical Samples for Polio and Non-Polio Enteroviruses in the Slovak Republic during the 1958-2020 Period

Enteroviruses (EVs) are associated with a wide spectrum of diseases involving various organs. Our aim was to give a historical overview of the genesis of clinical sample processing for EVs in the Slovak Republic (SR) during the 1958–2020 period, within the framework of the World Health Organization (WHO) polio program. Further, analyses were made of the data obtained from the archives of processed clinical sample surveillance using statistical methods. We used generalized additive models (GAM) with binomial distribution and logit link functions and an autoregressive moving average (ARMA) to analyze the data obtained during this 63-year period. Our results show trends in the composition of EV strains circulating in the population. Furthermore, statistically significant increasing trends of the non-polio enteroviruses (NPEVs) were observed over the studied time, represented by echoviruses (E) and coxsackieviruses A and B (CVA and CVB), with a cyclical pattern of occurrence. The most prevalent serotype over this period was CVB5, which became significantly more prevalent after 2000. While PVs, CVB1, and CVB3 were present in the second half of the studied period, CVA10, CVA16, E3, E25, and E30 appeared more frequently.

Research needs for optimising wastewater-based epidemiology monitoring for public health protection

Wastewater-based epidemiology (WBE) is an unobtrusive method used to observe patterns in illicit drug use, poliovirus, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The pandemic and need for surveillance measures have led to the rapid acceleration of WBE research and development globally. With the infrastructure available to monitor SARS-CoV-2 from wastewater in 58 countries globally, there is potential to expand targets and applications for public health protection, such as other viral pathogens, antimicrobial resistance (AMR), pharmaceutical consumption, or exposure to chemical pollutants. Some applications have been explored in academic research but are not used to inform public health decision-making. We reflect on the current knowledge of WBE for these applications and identify barriers and opportunities for expanding beyond SARS-CoV-2. This paper critically reviews the applications of WBE for public health and identifies the important research gaps for WBE to be a useful tool in public health. It considers possible uses for pathogenic viruses, AMR, and chemicals. It summarises the current evidence on the following: (1) the presence of markers in stool and urine; (2) environmental factors influencing persistence of markers in wastewater; (3) methods for sample collection and storage; (4) prospective methods for detection and quantification; (5) reducing uncertainties; and (6) further considerations for public health use.

Wastewater surveillance of SARS-CoV-2 in dormitories as a part of comprehensive university campus COVID-19 monitoring

Wastewater-based epidemiology is an effective tool for monitoring infectious disease spread or illicit drug use within communities. At the Ohio State University, we conducted a SARS-CoV-2 wastewater surveillance program in the 2020-2021 academic year and compared results with the university-required weekly COVID-19 saliva testing to monitor COVID-19 infection prevalence in the on-campus residential communities. The objectives of the study were to rapidly track trends in the wastewater SARS-CoV-2 gene concentrations, analyze the relationship between case numbers and wastewater signals when adjusted using human fecal viral indicator concentrations (PMMoV, crAssphage) in wastewater, and investigate the relationship of the SARS-CoV-2 gene concentrations with wastewater parameters. SARS-CoV-2 nucleocapsid and envelope (N1, N2, and E) gene concentrations, determined with reverse transcription droplet digital PCR, were used to track SARS-CoV-2 viral loads in dormitory wastewater once a week at 6 sampling sites across the campus during the fall semester in 2020. During the following spring semester, research was focused on SARS-CoV2 N2 gene concentrations at 5 sites sampled twice a week. Spearman correlations both with and without adjusting using human fecal viral indicators showed a significant correlation (p < 0.05) between human COVID-19 positive case counts and wastewater SARS-CoV-2 gene concentrations. Spearman correlations showed significant relationships between N1 gene concentrations and both TSS and turbidity, and between E gene concentrations and both pH and turbidity. These results suggest that wastewater signal increases with the census of infected individuals, in which the majority are asymptomatic, with a statistically significant (p-value <0.05) temporal correlation. The study design can be utilized as a platform for rapid trend tracking of SARS-CoV-2 variants and other diseases circulating in various communities.

History of the Wastewater Assessment of Polio and Non-Polio Enteroviruses in the Slovak Republic in 1963-2019

We describe the genesis of poliovirus (PV) and non-polio enterovirus (NPEV) surveillance program of sewage wastewaters from its inception to the present in the Slovak Republic (SR). Sampling procedures and evolution of the methodology used in the SR for the detection of PVs and NPEVs are presented chronologically. For statistical data processing, we divided our dataset into two periods, the first period from 1963 to 1998 (35 years), and the second period from 1999 to 2019 (21 years). Generalized additive models were used to assess temporal trends in the probability of occurrence of major EV serotypes during both periods. Canonical correspondence analysis on relative abundance data was used to test temporal changes in the composition of virus assemblages over the second period. The probability of occurrence of major viruses PV, coxsackieviruses (CVA, CVB), and Echoviruses (E)) significantly changed over time. We found that 1015 isolated PVs were of vaccine origin, called "Sabin-like" (isolates PV1, PV2, PV3). The composition of EV assemblages changed significantly during the second period. We conclude that during the whole period, CVB5, CVB4, and E3 were prominent NPEVS in the SR.

Community Wastewater-Based Surveillance Can Be a Cost-Effective Approach to Track COVID-19 Outbreak in Low-Resource Settings: Feasibility Assessment for Ethiopia Context

Wastewater surveillance systems have become an important component of COVID-19 outbreak monitoring in high-income settings. However, its use in most low-income settings has not been well-studied. This study assessed the feasibility and utility of wastewater surveillance system to monitor SARS-CoV-2 RNA in Addis Ababa, Ethiopia. The study was conducted at nine Membrane Bio-reactor (MBR) wastewater processing plants. The samples were collected in two separate time series. Wastewater samples and known leftover RT-PCR tested nasopharyngeal swabs were processed using two extraction protocols with different sample conditions. SARS-CoV-2 wastewater RT-PCR testing was conducted using RIDA GENE SARS-CoV-2 RUO protocol for wastewater SARS-CoV-2 RNA testing. Wastewater SARS-CoV-2 RNA RT-PCR protocol adaptation, optimization, and detection were conducted in an Addis Ababa, Ethiopia context. Samples collected during the first time series, when the national COVID-19 case load was low, were all negative. Conversely, samples collected during the second time series were all positive, coinciding with the highest daily reported new cases of COVID-19 in Ethiopia. The wastewater-based SARS-CoV-2 surveillance approach is feasible for Addis Ababa. The COVID-19 wastewater based epidemiological approach can potentially fill the evidence gap in distribution and dynamics of COVID-19 in Ethiopia and other low-income settings.

CaFÉ: A Sensitive, Low-Cost Filtration Method for Detecting Polioviruses and Other Enteroviruses in Residual Waters

Acute flaccid paralysis (AFP) surveillance has been used to identify polio cases and target vaccination campaigns since the inception of the Global Poliovirus Eradication Initiative (GPEI) in 1988. To date, only Afghanistan and Pakistan have failed to interrupt wild poliovirus transmission. Circulation of vaccine-derived polioviruses (VDPV) continues to be a problem in high-risk areas of the Eastern Mediterranean, African, and Southeast Asian regions. Environmental surveillance (ES) is an important adjunct to AFP surveillance, helping to identify circulating polioviruses in problematic areas. Stools from AFP cases and contacts (>200,000 specimens/year) and ES samples (>642 sites) are referred to 146 laboratories in the Global Polio Laboratory Network (GPLN) for testing. Although most World Health Organization supported laboratories use the two-phase separation method due to its simplicity and effectiveness, alternative simple, widely available, and cost-effective methods are needed. The CAFÉ (Concentration and Filtration Elution) method was developed from existing filtration methods to handle any type of sewage or residual waters. At $10-20 US per sample for consumable materials, CAFÉ is cost effective, and all equipment and reagents are readily available from markets and suppliers globally. The report describes the results from a parallel study of CAFÉ method with the standard two-phase separation method. The study was performed with samples collected from five countries (Guatemala, Haïti, Thailand, Papua New Guinea, and the Philippines), run in three laboratories-(United States, Thailand and in the Philippines) to account for regional and sample-to-sample variability. Samples from each site were divided into two 500 ml aliquots and processed by both methods, with no other additional concentration or manipulation. The results of 338 parallel-tested samples show that the CAFÉ method is more sensitive than the two-phase separation method for detection of non-polio enteroviruses (p-value < 0.0001) and performed as well as the two-phase separation method for polioviruses detection with no significant difference (p-value > 0.05). The CAFÉ method is a robust, sensitive, and cost-effective method for isolating enteroviruses from residual waters.

Detection of multiple human astroviruses in sewage by next generation sequencing

Human astrovirus (HAstV) composes of classic HAstV serotypes 1-8 and recently discovered novel HAstV-MLB and HAstV-VA strains. A number of studies have demonstrated that wastewater analysis is an effective approach to understand the prevalence and diversity of enteric viruses in local population. However, a comprehensive analysis of classic and novel HAstVs in sewage is still lacking. In this study, sewage samples were collected monthly from Jinan, China during 2018-2019. Quantification of HAstV genomes was performed by real-time quantitative PCR. Different from previous studies which focused on partial ORF1b or ORF2 gene, complete ORF2 region of HAstV was amplified from sewage concentrates, and amplicons were subjected to next generation sequencing (NGS) and genetic analysis. This methodology allowed detection of 18 astroviruses, of which 7 (HAstV-1, -2, -4, -5, VA1, VA2, and VA3) were detected in all sewage samples. A new strain VA6 mapped to the HMO clade was identified in 20.8% of samples, with 82.4%-83.3% nucleotide identities to the closest strain VA5. The viral load of classic, MLB and VA clades in sewage samples ranged from 3.7 × 10⁴ to 4.6 × 10⁷, 3.4 × 10⁴ to 3.9 × 10⁶, and 3.3 × 10⁴ to 4.1 × 10⁶ copies per liter, respectively. Phylogenetic analysis based on complete ORF2 region reflected local HAstVs within each genotype constituted multiple co-circulating lineages. Existence of several new lineages composed exclusively or predominantly of Chinese sequences was observed as well. These results demonstrate sewage contains astroviruses with considerable high diversities. NGS based environmental surveillance greatly improves the understanding of HAstV circulation and should be encouraged.

Microbiome Analysis for Wastewater Surveillance during COVID-19

Wastewater surveillance (WS), when coupled with advanced molecular techniques, offers near real-time monitoring of community-wide transmission of SARS-CoV-2 and allows assessing and mitigating COVID-19 outbreaks, by evaluating the total microbial assemblage in a community. Composite wastewater samples (24 h) were collected weekly from a manhole between December 2020 and November 2021 in Maryland, USA. RT-qPCR results showed concentrations of SARS-CoV-2 RNA recovered from wastewater samples reflected incidence of COVID-19 cases. When a drastic increase in COVID-19 was detected in February 2021, samples were selected for microbiome analysis (DNA metagenomics, RNA metatranscriptomics, and targeted SARS-CoV-2 sequencing). Targeted SARS-CoV-2 sequencing allowed for detection of important genetic mutations, such as spike: K417N, D614G, P681H, T716I, S982A, and D1118H, commonly associated with increased cell entry and reinfection. Microbiome analysis (DNA and RNA) provided important insight with respect to human health-related factors, including detection of pathogens and their virulence/antibiotic resistance genes. Specific microbial species comprising the wastewater microbiome correlated with incidence of SARS-CoV-2 RNA, suggesting potential association with SARS-CoV-2 infection. Climatic conditions, namely, temperature, were related to incidence of COVID-19 and detection of SARS-CoV-2 in wastewater, having been monitored as part of an environmental risk score assessment carried out in this study. In summary, the wastewater microbiome provides useful public health information, and hence, a valuable tool to proactively detect and characterize pathogenic agents circulating in a community. In effect, metagenomics of wastewater can serve as an early warning system for communicable diseases, by providing a larger source of information for health departments and public officials. IMPORTANCE Traditionally, testing for COVID-19 is done by detecting SARS-CoV-2 in samples collected from nasal swabs and/or saliva. However, SARS-CoV-2 can also be detected in feces of infected individuals. Therefore, wastewater samples can be used to test all individuals of a community contributing to the sewage collection system, i.e., the infrastructure, such as gravity pipes, manholes, tanks, lift stations, control structures, and force mains, that collects used water from residential and commercial sources and conveys the flow to a wastewater treatment plant. Here, we profile community wastewater collected from a manhole, detect presence of SARS-CoV-2, identify genetic mutations of SARS-CoV-2, and perform COVID-19 risk score assessment of the study area. Using metagenomics analysis, we also detect other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Results show that by analyzing all microorganisms present in wastewater, pathogens circulating in a community can provide an early warning for contagious diseases.

Centralized and decentralized wastewater-based epidemiology to infer COVID-19 transmission - A brief review

Wastewater-based epidemiology has shown to be a promising and innovative approach to measure a wide variety of illicit drugs that are consumed in the communities. In the same way as for illicit drugs, wastewater-based epidemiology is a promising approach to understand the prevalence of viruses in a community-level.

The ongoing coronavirus disease 2019 (COVID-19) pandemic created an unprecedented burden on public health and diagnostic laboratories all over the world because of the need for massive laboratory testing. Many studies have shown the applicability of a centralized wastewater-based epidemiology (WBE) approach, where samples are collected at WWTPs. A more recent concept is a decentralized approach for WBE where samples are collected at different points of the sewer system and at polluted water bodies. The second being particularly important in countries where there are insufficient connections from houses to municipal sewage pipelines and thus untreated wastewater is discharged directly in environmental waters.

A decentralized approach can be used to focus the value of diagnostic tests in what we call targeted-WBE, by monitoring wastewater in parts of the population where an outbreak is likely to happen, such as student dorms, retirement homes and hospitals. A combination of centralized and decentralized WBE should be considered for an affordable, sustainable, and successful WBE implementation in high-, middle- and low-income countries.

Early warning of a COVID-19 surge on a university campus based on wastewater surveillance for SARS-CoV-2 at residence halls

As COVID-19 continues to spread globally, monitoring the disease at different scales is critical to support public health decision making. Surveillance for SARS-CoV-2 RNA in wastewater can supplement surveillance based on diagnostic testing. In this paper, we report the results of wastewater-based COVID-19 surveillance on Emory University campus that included routine sampling of sewage from a hospital building, an isolation/quarantine building, and 21 student residence halls between July 13th, 2020 and March 14th, 2021. We examined the sensitivity of wastewater surveillance for detecting COVID-19 cases at building level and the relation between Ct values from RT-qPCR results of wastewater samples and the number of COVID-19 patients residing in the building. Our results show that weekly wastewater surveillance using Moore swab samples was not sensitive enough (6 of 63 times) to reliably detect one or two sporadic cases in a residence building. The Ct values of the wastewater samples over time from the same sampling location reflected the temporal trend in the number of COVID-19 patients in the isolation/quarantine building and hospital (Pearson's r < -0.8), but there is too much uncertainty to directly estimate the number of COVID-19 cases using Ct values. After students returned for the spring 2021 semester, SARS-CoV-2 RNA was detected in the wastewater samples from most of the student residence hall monitoring sites one to two weeks before COVID-19 cases surged on campus. This finding suggests that wastewater-based surveillance can be used to provide early warning of COVID-19 outbreaks at institutions.