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

Spatio-temporal evolution mechanism and dynamic simulation of nitrogen and phosphorus pollution of the Yangtze River economic Belt in China

Excess nitrogen and phosphorus inputs are the main causes of aquatic environmental deterioration. Accurately quantifying and dynamically assessing the regional nitrogen and phosphorus pollution emission (NPPE) loads and influencing factors is crucial for local authorities to implement and formulate refined pollution reduction management strategies. In this study, we constructed a methodological framework for evaluating the spatio-temporal evolution mechanism and dynamic simulation of NPPE. We investigated the spatio-temporal evolution mechanism and influencing factors of NPPE in the Yangtze River Economic Belt (YREB) of China through the pollution load accounting model, spatial correlation analysis model, geographical detector model, back propagation neural network model, and trend analysis model. The results show that the NPPE inputs in the YREB exhibit a general trend of first rising and then falling, with uneven development among various cities in each province. Nonpoint sources are the largest source of land-based NPPE. Overall, positive spatial clustering of NPPE is observed in the cities of the YREB, and there is a certain enhancement in clustering. The GDP of the primary industry and cultivated area are important human activity factors affecting the spatial distribution of NPPE, with economic factors exerting the greatest influence on the NPPE. In the future, the change in NPPE in the YREB at the provincial level is slight, while the nitrogen pollution emissions at the municipal level will develop towards a polarization trend. Most cities in the middle and lower reaches of the YREB in 2035 will exhibit medium to high emissions. This study provides a scientific basis for the control of regional NPPE, and it is necessary to strengthen cooperation and coordination among cities in the future, jointly improve the nitrogen and phosphorus pollution tracing and control management system, and achieve regional sustainable development.

Integrating the exposome and one health approach to national health surveillance: an opportunity for Latin American countries in health preventive management

The exposome approach, emphasizing lifelong environmental exposures, is a holistic framework exploring the intricate interplay between genetics and the environment in shaping health outcomes. Complementing this, the one health approach recognizes the interconnectedness of human and ecological health within a shared ecosystem, extending to planetary health, which encompasses the entire planet. Integrating Disease Surveillance Systems with exposome, one health, and planetary health signifies a paradigm shift in health management, fostering a comprehensive public health framework. This publication advocates for combining traditional health surveillance with exposome and one health/planetary health approach, proposing a three-step approach: ecological analysis, territorial intervention in identified issues, and an analytical phase for assessing interventions. Particularly relevant for Latin American countries facing a double burden of diseases, integrating the exposome into traditional health surveillance proves cost-effective by leveraging existing data and environmental measurements. In conclusion, the integration of exposome and one health approaches into traditional health surveillance presents a robust framework for monitoring population health, especially in regions like Latin America with complex health challenges. This innovative approach enables tailored interventions, disease outbreak predictions, and a holistic understanding of the intricate links between human health and the environment, offering substantial benefits for public health and disease prevention despite existing challenges.

Intersecting planetary health: Exploring the impacts of environmental stressors on wildlife and human health

This comprehensive review articulates critical insights into the nexus of environmental stressors and their health impacts across diverse species, underscoring significant findings that reveal profound effects on both wildlife and human health systems. Central to our examination is the role of pollutants, climate variables, and pathogens in contributing to complex disease dynamics and physiological disruptions, with particular emphasis on immune and endocrine functions. This research brings to light emerging evidence on the severe implications of environmental pressures on a variety of taxa, including predatory mammals, raptorial birds, seabirds, fish, and humans, which are pivotal as indicators of broader ecosystem health and stability. We delve into the nuanced interplay between environmental degradation and zoonotic diseases, highlighting novel intersections that pose significant risks to biodiversity and human populations. The review critically evaluates current methodologies and advances in understanding the morphological, histopathological, and biochemical responses of these organisms to environmental stressors. We discuss the implications of our findings for conservation strategies, advocating for a more integrated approach that incorporates the dynamics of zoonoses and pollution control. This synthesis not only contributes to the academic discourse but also aims to influence policy by aligning with the Global Goals for Sustainable Development. It underscores the urgent need for sustainable interactions between humans and their environments, which are critical for preserving biodiversity and ensuring global health security. By presenting a detailed analysis of the interdependencies between environmental stressors and biological health, this review highlights significant gaps in current research and provides a foundation for future studies aimed at mitigating these pressing issues. Our study is significant as it proposes integrative and actionable strategies to address the challenges at the intersection of environmental change and public health, marking a crucial step forward in planetary health science.

Adjusting for dilution in wastewater using biomarkers: A practical approach

We developed a biomarker-based approach to quantify in-sewer dilution by measuring wastewater quality parameters (ammoniacal-N, orthophosphate, crAssphage). This approach can enhance the environmental management of wastewater treatment works (WWTW) by optimising their operation and providing cost-effective information on the health and behaviour of populations and their interactions with the environment through wastewater-based epidemiology (WBE). Our method relies on site specific baselines calculated for each biomarker. These baselines reflect the sewer conditions without the influence of rainfall-derived inflow and infiltration (RDII). Ammoniacal-N was the best candidate to use as proxy for dilution. We demonstrated that the dilution calculated using biomarkers correlates well with the dilution indicated by measured flow. In some instances, the biomarkers showed much higher dilution than measured flows. These differences were attributed to the loss of flow volume at wastewater treatment works due to the activation of combined sewer overflows (CSOs) and/or storm tanks. Using flow measured directly at the WWTW could therefore result in underestimation of target analyte loads.

Examining the stability of viral RNA and DNA in wastewater: Effects of storage time, temperature, and freeze-thaw cycles

Wastewater-based epidemiology (WBE) has been demonstrably successful as a relatively unbiased tool for monitoring levels of SARS-CoV-2 virus circulating in communities during the COVID-19 pandemic. Accumulated biobanks of wastewater samples allow retrospective exploration of spatial and temporal trends for public health indicators such as chemicals, viruses, antimicrobial resistance genes, and the possible emergence of novel human or zoonotic pathogens. We investigated virus resilience to time, temperature, and freeze-thaw cycles, plus the optimal storage conditions to maintain the stability of genetic material (RNA/DNA) of viral +ssRNA (Envelope - E, Nucleocapsid - N and Spike protein - S genes of SARS-CoV-2), dsRNA (Phi6 phage) and circular dsDNA (crAssphage) in wastewater. Samples consisted of (i) processed and extracted wastewater samples, (ii) processed and extracted distilled water samples, and (iii) raw, unprocessed wastewater samples. Samples were stored at -80 °C, -20 °C, 4 °C, or 20 °C for 10 days, going through up to 10 freeze-thaw cycles (once per day). Sample stability was measured using reverse transcription quantitative PCR, quantitative PCR, automated electrophoresis, and short-read whole genome sequencing. Exploring different areas of the SARS-CoV-2 genome demonstrated that the S gene in processed and extracted samples showed greater sensitivity to freeze-thaw cycles than the E or N genes. Investigating surrogate and normalisation viruses showed that Phi6 remains a stable comparison for SARS-CoV-2 in a laboratory setting and crAssphage was relatively resilient to temperature variation. Recovery of SARS-CoV-2 in raw unprocessed samples was significantly greater when stored at 4 °C, which was supported by the sequencing data for all viruses - both time and freeze-thaw cycles negatively impacted sequencing metrics. Historical extracts stored at -80 °C that were re-quantified 12, 14 and 16 months after original quantification showed no major changes. This study highlights the importance of the fast processing and extraction of wastewater samples, following which viruses are relatively robust to storage at a range of temperatures.

Wastewater surveillance for viral pathogens: A tool for public health

A focus on water quality has intensified globally, considering its critical role in sustaining life and ecosystems. Wastewater, reflecting societal development, profoundly impacts public health. Wastewater-based epidemiology (WBE) has emerged as a surveillance tool for detecting outbreaks early, monitoring infectious disease trends, and providing real-time insights, particularly in vulnerable communities. WBE aids in tracking pathogens, including viruses, in sewage, offering a comprehensive understanding of community health and lifestyle habits. With the rise in global COVID-19 cases, WBE has gained prominence, aiding in monitoring SARS-CoV-2 levels worldwide. Despite advancements in water treatment, poorly treated wastewater discharge remains a threat, amplifying the spread of water-, sanitation-, and hygiene (WaSH)-related diseases. WBE, serving as complementary surveillance, is pivotal for monitoring community-level viral infections. However, there is untapped potential for WBE to expand its role in public health surveillance. This review emphasizes the importance of WBE in understanding the link between viral surveillance in wastewater and public health, highlighting the need for its further integration into public health management.

Repurposing Sewage and Toilet Systems: Environmental, Public Health, and Person-Centered Healthcare Applications

Global terrestrial water supplies are rapidly depleting due to the consequences of climate change. Water scarcity results in an inevitable compromise of safe hygiene and sanitation practices, leading to the transmission of water-borne infectious diseases, and the preventable deaths of over 800.000 people each year. Moreover, almost 500 million people lack access to toilets and sanitation systems. Ecosystems are estimated to be contaminated by 6.2 million tons of nitrogenous products from human wastewater management practices. It is therefore imperative to transform toilet and sewage systems to promote equitable access to water and sanitation, improve public health, conserve water, and protect ecosystems. Here, the integration of emerging technologies in toilet and sewage networks to repurpose toilet and wastewater systems is reviewed. Potential applications of these systems to develop sustainable solutions to environmental challenges, promote public health, and advance person-centered healthcare are discussed.

Combining wastewater surveillance and case data in estimating the time-varying effective reproduction number

Wastewater surveillance has been increasingly acknowledged as a useful tool for monitoring transmission dynamics of infections of public health concern, including the coronavirus disease (COVID-19). While a range of models have been proposed to estimate the time-varying effective reproduction number (Rt) utilizing clinical data, few have harnessed the viral concentration in wastewater samples to do so, leaving uncertainties about the potential precision gains with its use. In this study, we developed a Bayesian hierarchical model which simultaneously reconstructed the latent infection trajectory and estimated Rt. Focusing on the 2022 and early 2023 COVID-19 transmission trends in Singapore, where mass community wastewater surveillance has become routine, we performed estimations using a spectrum of data sources, including reported case counts, hospital admissions, deaths, and wastewater viral loads. We further explored the performance of our wastewater model across various scenarios with different sampling strategies. The results showed consistent estimates derived from models employing diverse data streams, while models incorporating more wastewater samples exhibited greater uncertainty and variation in the inferred Rts. Additionally, our analysis revealed prominent day-of-the-week effect in reported case counts and substantial temporal variations in ascertainment rates. In response to these findings, we advocate for a hybrid approach leveraging both clinical and wastewater surveillance data to account for changes in case-ascertainment rates. Furthermore, our study demonstrates the possibility of reducing sampling frequency or sample size without compromising estimation accuracy for Rt, highlighting the potential for optimizing resource allocation in surveillance efforts while maintaining robust insights into the transmission dynamics of infectious diseases.

Monitoring of over-the-counter (OTC) and COVID-19 treatment drugs complement wastewater surveillance of SARS-CoV-2

BACKGROUND

The application of wastewater-based epidemiology to track the outbreak and prevalence of coronavirus disease (COVID-19) in communities has been tested and validated by several researchers across the globe. However, the RNA-based surveillance has its inherent limitations and uncertainties.

OBJECTIVE

This study aims to complement the ongoing wastewater surveillance efforts by analyzing other chemical biomarkers in wastewater to help assess community response (hospitalization and treatment) during the pandemic (2020-2021).

METHODS

Wastewater samples (n = 183) were collected from the largest wastewater treatment facility in Suffolk County, NY, USA and analyzed for COVID-19 treatment drugs (remdesivir, chloroquine, and hydroxychloroquine (HCQ)) and their human metabolites. We additionally monitored 26 pharmaceuticals including common over-the-counter (OTC) drugs. Lastly, we developed a Bayesian model that uses viral RNA, COVID-19 treatment drugs, and pharmaceuticals data to predict the confirmed COVID-19 cases within the catchment area.

RESULTS

The viral RNA levels in wastewater tracked the actual COVID-19 case numbers well as expected. COVID-19 treatment drugs were detected with varying frequency (9-100%) partly due to their instability in wastewater. We observed a significant correlation (R = 0.30, p < 0.01) between the SARS-CoV-2 genes and desethylhydroxychloroquine (DHCQ, metabolite of HCQ). Remdesivir levels peaked immediately after the Emergency Use Authorization approved by the FDA. Although, 13 out of 26 pharmaceuticals assessed were consistently detected (DF = 100%, n = 111), only acetaminophen was significantly correlated with viral loads, especially when the Omicron variant was dominant. The Bayesian models were capable of reproducing the temporal trend of the confirmed cases.

IMPACT

In this study, for the first time, we measured COVID-19 treatment and pharmaceutical drugs and their metabolites in wastewater to complement ongoing COVID-19 viral RNA surveillance efforts. Our results highlighted that, although the COVID-19 treatment drugs were not very stable in wastewater, their detection matched with usage trends in the community. Acetaminophen, an OTC drug, was significantly correlated with viral loads and confirmed cases, especially when the Omicron variant was dominant. A Bayesian model was developed which could predict COVID-19 cases more accurately when incorporating other drugs data along with viral RNA levels in wastewater.

Assessment of sewer connectivity in the United States and its implications for equity in wastewater-based epidemiology

Wastewater-based epidemiology is a promising public health tool that can yield a more representative view of the population than case reporting. However, only about 80% of the U.S. population is connected to public sewers, and the characteristics of populations missed by wastewater-based epidemiology are unclear. To address this gap, we used publicly available datasets to assess sewer connectivity in the U.S. by location, demographic groups, and economic groups. Data from the U.S. Census' American Housing Survey revealed that sewer connectivity was lower than average when the head of household was American Indian and Alaskan Native, White, non-Hispanic, older, and for larger households and those with higher income, but smaller geographic scales revealed local variations from this national connectivity pattern. For example, data from the U.S. Environmental Protection Agency showed that sewer connectivity was positively correlated with income in Minnesota, Florida, and California. Data from the U.S. Census' American Community Survey and Environmental Protection Agency also revealed geographic areas with low sewer connectivity, such as Alaska, the Navajo Nation, Minnesota, Michigan, and Florida. However, with the exception of the U.S. Census data, there were inconsistencies across datasets. Using mathematical modeling to assess the impact of wastewater sampling inequities on inferences about epidemic trajectory at a local scale, we found that in some situations, even weak connections between communities may allow wastewater monitoring in one community to serve as a reliable proxy for an interacting community with no wastewater monitoring, when cases are widespread. A systematic, rigorous assessment of sewer connectivity will be important for ensuring an equitable and informed implementation of wastewater-based epidemiology as a public health monitoring system.

Emerging biotechnological applications of anaerobic ammonium oxidation

Anaerobic ammonium oxidation (anammox) is an energy-efficient method for nitrogen removal that opens the possibility for energy-neutral wastewater treatment. Research on anammox over the past decade has primarily focused on its implementation in domestic wastewater treatment. However, emerging studies are now expanding its use to novel biotechnological applications and wastewater treatment processes. This review highlights recent advances in the anammox field that aim to overcome conventional bottlenecks, and explores novel and niche-specific applications of the anammox process. Despite the promising results and potential of these advances, challenges persist for their real-world implementation. This underscores the need for a transition from laboratory achievements to practical, scalable solutions for wastewater treatment which mark the next crucial phase in the evolution of anammox research.

Is the reliability of wastewater-based epidemiology affected by season? Comparative analysis with pharmaceuticals prescriptions

Wastewater-based epidemiology (WBE) has been already proposed by several authors for estimating the consumption of drugs, mainly the illicit ones. However, not much information is available about the actual reliability of this tool given the absence of comparison with the actual consumption. This work aims to evaluate the reliability of the WBE as a tool for estimating the consumption of pharmaceuticals in urban area. Measured consumption back-calculated with a WBE approach was compared with prescription of pharmaceutical products as "control." Moreover, seasonal influence on (i) pharmaceutical consumption, (ii) load of pharmaceutical products in the sewer system, and (iii) reliability of WBE was evaluated. Ciprofloxacin, sulfamethoxazole, metoprolol, carbamazepine, and citalopram were estimated by WBE with a difference respect to the "control" value lower than 0.2 order of magnitude while only trimethoprim and sotalol exceeded the 0.5 order of magnitude of difference but below the 1 order of magnitude. Sedatives were the best represented by WBE (on average 0.15 order of magnitude of difference compared to prescription data). However, further studies are suggested to fully estimate the influence of the type of APs on the reliability of the WBE. Seasonal patterns were found for the load of ciprofloxacin in the sewer and for the consumption of sulfamethoxazole and trimethoprim by population but seasonal changes did not have a significant impact (p > 0.05) on the reliability of WBE. Despite some gaps remained to optimize the reliability of the tool, WBE can be considered a valid method to estimate the consumption of prescribed drugs from the analysis of the sewer system.

Emerging trends in wastewater treatment: Addressing microorganic pollutants and environmental impacts

This review focuses on the challenges and advances associated with the treatment and management of microorganic pollutants, encompassing pesticides, industrial chemicals, and persistent organic pollutants (POPs) in the environment. The translocation of these contaminants across multiple media, particularly through atmospheric transport, emphasizes their pervasive nature and the subsequent ecological risks. The urgency to develop cost-effective remediation strategies for emerging organic contaminants is paramount. As such, wastewater-based epidemiology and the increasing concern over estrogenicity are explored. By incorporating conventional and innovative wastewater treatment techniques, this article highlights the integration of environmental management strategies, analytical methodologies, and the importance of renewable energy in waste treatment. The primary objective is to provide a comprehensive perspective on the current scenario, imminent threats, and future directions in mitigating the effects of these pollutants on the environment. Furthermore, the review underscores the need for international collaboration in developing standardized guidelines and policies for monitoring and controlling these microorganic pollutants. It advocates for increased investment in research and development of advanced materials and technologies that can efficiently remove or neutralize these contaminants, thereby safeguarding environmental health and promoting sustainable practice.

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid β, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

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.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Air travel monitoring does not accelerate outbreak detection in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Dynamic nonlinear effects of urbanization on wastewater discharge based on inertial characteristics of wastewater discharge

This study examines the impact of urbanization on wastewater discharge (WD) in 30 provinces in mainland China, considering the inertia characteristics of WD. Various models, including the Tapio decoupling model, dynamic curve relationship model, dynamic threshold effect model, and dynamic quantile model, are employed to analyze the decoupling relationship, curve relationship, threshold relationship, and quantile relationship, respectively. The research findings indicate a shift in the relationship between urbanization and total wastewater discharge (TWD) from expansionary negative decoupling to strong decoupling. Regarding household wastewater discharge (HWD), the relationship is primarily characterized by expansionary negative decoupling and weak decoupling, while industrial wastewater discharge (IWD) is mainly associated with strong decoupling. Urbanization does not exhibit an (inverted) N-shaped relationship with TWD, IWD, and HWD, but it does show an inverted U-shaped relationship with TWD and HWD. The study also reveals that urbanization has a dynamic threshold effect and regional heterogeneity on HWD, but not on TWD and IWD. As the quantile increases, the positive impact of urbanization on TWD and HWD decreases, while the negative impact on IWD increases.

Wastewater analysis of Mpox virus in a city with low prevalence of Mpox disease: an environmental surveillance study

Background

Tracking infectious diseases at the community level is challenging due to asymptomatic infections and the logistical complexities of mass surveillance. Wastewater surveillance has emerged as a valuable tool for monitoring infectious disease agents including SARS-CoV-2 and Mpox virus. However, detecting the Mpox virus in wastewater is particularly challenging due to its relatively low prevalence in the community. In this study, we aim to characterize three molecular assays for detecting and tracking the Mpox virus in wastewater from El Paso, Texas, during February and March 2023.

Methods

In this study, a combined approach utilizing three real-time PCR assays targeting the C22L, F3L, and F8L genes and sequencing was employed to detect and track the Mpox virus in wastewater samples. The samples were collected from four sewersheds in the City of El Paso, Texas, during February and March 2023. Wastewater data was compared with reported clinical case data in the city.

Findings

Mpox virus DNA was detected in wastewater from all the four sewersheds, whereas only one Mpox case was reported during the sampling period. Positive signals were still observed in multiple sewersheds after the Mpox case was identified. Higher viral concentrations were found in the pellet than in the supernatant of wastewater. Notably, an increasing trend in viral concentration was observed approximately 1-2 weeks before the reporting of the Mpox case. Further sequencing and epidemiological analysis provided supporting evidence for unreported Mpox infections in the city.

Interpretation

Our analysis suggests that the Mpox cases in the community is underestimated. The findings emphasize the value of wastewater surveillance as a public health tool for monitoring infectious diseases even in low-prevalence areas, and the need for heightened vigilance to mitigate the spread of Mpox disease for safeguarding global health.

Funding

Center of Infectious Diseases at UTHealth, the University of Texas System, and the Texas Epidemic Public Health Institute. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of these funding organizations.

The Emergence and Widespread Circulation of Enteric Viruses Throughout the COVID-19 Pandemic: A Wastewater-Based Evidence

Growing evidence shed light on the importance of wastewater-based epidemiology (WBE) during the pandemic, when the patients rarely visited the clinics despite the fact that the infections were still prevalent in the community as before. The abundance of infections in the community poses a constant threat of the emergence of new epidemic strains. Herein, we investigated enteric viruses in raw sewage water (SW) from Japan's Tohoku region and compared them to those from the Kansai region to better understand the circulating strains and their distribution across communities during the COVID-19 pandemic. Raw SW was collected between 2019 and 2022, concentrated by polyethylene-glycol-precipitation method, and investigated for major AGE viruses by RT-PCR. Sequence-based analyses were used to assess genotypes and evolutionary relationships. The most commonly detected enteric virus was rotavirus A (RVA) at 63.8%, followed by astrovirus (AstV) at 61.1%, norovirus (NoV) GII and adenovirus (AdV) at 33.3%, sapovirus (SV) at 25.0%, enterovirus (EV) at 19.4%, and NoV GI at 13.9%. The highest prevalence (46.0%) was found in the spring. Importantly, enteric viruses did not decline during the pandemic. Rather, several strains like NoV GII.2, DS-1-like human G3 (equine) RVA, MLB1 AstV, and different F41 HAdV emerged throughout the pandemic and spread widely over the Tohoku and Kansai regions. Tohoku's detection rate remained lower than that of the Kansai area (36 vs 58%). This study provides evidence for the emergence and spread of enteric viruses during the pandemic.

Pencil Graphite Electrocatalytic Sensors Modified by Pyrene Coated Reduced Graphene Oxide Decorated with Molybdenum Disulfide Nanoroses for Hydrazine and 4-Nitrophenol Detection in Real Water Samples

Novel nanostructured platforms based on Pencil Graphite Electrodes (PGEs), modified with pyrene carboxylic acid (PCA) functionalized Reduced Graphene Oxide (rGO), and then decorated by chronoamperometry electrodeposition of MoS2 nanoroses (NRs) (MoS2NRs/PCA-rGO/PGEs) were manufactured for the electrocatalytic detection of hydrazine (N2H4) and 4-nitrophenol, pollutants highly hazardous for environment and human health. The surface morphology and chemistry of the MoS2NRs/PCA-rGO/PGEs were characterized by scanning electron microscopy (SEM), Raman, and X-ray photoelectron spectroscopy (XPS), assessing the coating of the PCA-rGO/PGEs by dense multilayers of NRs. N2H4 and 4-nitrophenol have been monitored by Differential Pulse Voltammetry (DPV), and the MoS2NRs/PCA-rGO/PGEs electroanalytical properties have been compared to the PGEs, as neat and modified by PCA-rGO. The MoS2NRs/PCA-rGO/PGEs demonstrated a higher electrochemical and electrocatalytic activity, due to their high surface area and conductivity, and very fast heterogeneous electron transfer kinetics at the interphase with the electrolyte. LODs lower than the U.S. EPA recommended concentration values in drinking water, namely 9.3 nM and 13.3 nM, were estimated for N2H4 and 4-nitrophenol, respectively and the MoS2NRs/PCA-rGO/PGEs showed good repeatability, reproducibility, storage stability, and selectivity. The effectiveness of the nanoplatforms for monitoring N2H4 and 4-nitrophenol in tap, river, and wastewater was addressed.

Wastewater surveillance facilitates climate change-resilient pathogen monitoring

Traditional disease surveillance systems are ill-equipped to handle climate change-driven shifts in pathogen dynamics. If paired with wastewater surveillance, a cost-effective and scalable approach for generating high-resolution health data, such next-generation systems can enable effective resource allocation and delivery of targeted interventions.

Making waves: Establishing a modeling framework to evaluate novel targets for wastewater-based surveillance

Wastewater-based surveillance (WBS) monitoring of pathogens circulating within a community provides an improved understanding of the occurrence and spread of infectious diseases. However, the potential suitability of WBS for novel disease targets is unclear, including many emerging and neglected diseases. The current ad hoc approach of conducting wastewater detection experiments on novel disease targets to determine their suitability for WBS monitoring is resource intensive and may stall investment in this promising technology. In addition, detections, or non-detections, without the context of disease prevalence and shedding by infected individuals are difficult to interpret upon initial WBS target development. In this paper, we present a WBS feasibility analysis framework to identify which diseases are theoretically appropriate for WBS applications and to improve the initial interpretation of target detections. We then discuss five primary factors that influence the probability of detection in WBS monitoring - genome shedding rate, infection rate, per capita wastewater usage, process limit of detection (PLOD), and the number of PCR replicates. Clarifying the relationships between these factors and the likelihood of detection enhances quantitative insights into applying WBS, guiding researchers and stakeholders into mitigating inherent uncertainties of wastewater monitoring and subsequent improvements in WBS outcomes, thereby supporting future investment and expansion of WBS research, especially in novel disease targets.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Comparison of Cefotaxime-Resistant Escherichia coli and sul1 and intI1 by qPCR for Monitoring of Antibiotic Resistance of Wastewater, Surface Water, and Recycled Water

Awareness of the need for surveillance of antimicrobial resistance (AMR) in water environments is growing, but there is uncertainty regarding appropriate monitoring targets. Adapting culture-based fecal indicator monitoring to include antibiotics in the media provides a potentially low-tech and accessible option, while quantitative polymerase chain reaction (qPCR) targeting key genes of interest provides a broad, quantitative measure across the microbial community. The purpose of this study was to compare findings obtained from the culture of cefotaxime-resistant (cefR) Escherichia coli with two qPCR methods for quantification of antibiotic resistance genes across wastewater, recycled water, and surface waters. The culture method was a modification of US EPA Method 1603 for E. coli, in which cefotaxime is included in the medium to capture cefR strains, while qPCR methods quantified sul1 and intI1. A common standard operating procedure for each target was applied to samples collected by six water utilities across the United States and processed by two laboratories. The methods performed consistently, and all three measures reflected the same overarching trends across water types. The qPCR detection of sul1 yielded the widest dynamic range of measurement as an AMR indicator (7-log versus 3.5-log for cefR E. coli), while intI1 was the most frequently detected target (99% versus 96.5% and 50.8% for sul1 and cefR E. coli, respectively). All methods produced comparable measurements between labs (p < 0.05, Kruskal-Wallis). Further study is needed to consider how relevant each measure is to capturing hot spots for the evolution and dissemination of AMR in the environment and as indicators of AMR-associated human health risk.

M. AH, Fernandez S, Huang AT, Vatanaprasan P, Jay DJ, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Sano D, Furukawa T, Sei K, Leelahavanichkul A, Kanjanabuch T, Hirankarn N, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, McLellan AD, Ishikawa H. COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities

Equitable SARS-CoV-2 surveillance in low-resource communities lacking centralized sewers is critical as wastewater-based epidemiology (WBE) progresses. However, large-scale studies on SARS-CoV-2 detection in wastewater from low-and middle-income countries is limited because of economic and technical reasons. In this study, wastewater samples were collected twice a month from 186 urban and rural subdistricts in nine provinces of Thailand mostly having decentralized and non-sewered sanitation infrastructure and analyzed for SARS-CoV-2 RNA variants using allele-specific RT-qPCR. Wastewater SARS-CoV-2 RNA concentration was used to estimate the real-time incidence and time-varying effective reproduction number (Re). Results showed an increase in SARS-CoV-2 RNA concentrations in wastewater from urban and rural areas 14-20 days earlier than infected individuals were officially reported. It also showed that community/food markets were "hot spots" for infected people. This approach offers an opportunity for early detection of transmission surges, allowing preparedness and potentially mitigating significant outbreaks at both spatial and temporal scales.

Evaluation of low-cost SARS-CoV-2 RNA purification methods for viral quantification by RT-qPCR and next-generation sequencing analysis: Implications for wider wastewater-based epidemiology adoption

Based Epidemiology (WBE) consists of quantifying biomarkers in sewerage systems to derive real-time information on the health and/or lifestyle of the contributing population. WBE usefulness was vastly demonstrated in the context of the COVID-19 pandemic. Many methods for SARS-CoV-2 RNA determination in wastewater were devised, which vary in cost, infrastructure requirements and sensitivity. For most developing countries, implementing WBE for viral outbreaks, such as that of SARS-CoV-2, proved challenging due to budget, reagent availability and infrastructure constraints. In this study, we assessed low-cost methods for SARS-CoV-2 RNA quantification by RT-qPCR, and performed variant identification by NGS in wastewater samples. Results showed that the effect of adjusting pH to 4 and/or adding MgCl₂ (25 mM) was negligible when using the adsorption-elution method, as well as basal physicochemical parameters in the sample. In addition, results supported the standardized use of linear rather than plasmid DNA for a more accurate viral RT-qPCR estimation. The modified TRIzol-based purification method in this study yielded comparable RT-qPCR estimation to a column-based approach, but provided better NGS results, suggesting that column-based purification for viral analysis should be revised. Overall, this work provides evaluation of a robust, sensitive and cost-effective method for SARS-CoV-2 RNA analysis that could be implemented for other viruses, for a wider WEB adoption.

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.

Indian sewage microbiome has unique community characteristics and potential for population-level disease predictions

Sewage wastewater pollutes water and poses a public health issue but it could also prove useful in certain research domains. Sewage is a complex niche relevant for research concerning 'one-health', human health, pollution and antibiotic resistance. Indian gut microbiome is also understudied due to sampling constraints and sewage could be used to explore it. Ostensibly, Indian sewage needs to be studied and here, we performed a cross-sectional pan-India sewage sampling to generate the first comprehensive Indian sewage microbiome. Indian sewage showed predominance of Burkholderiaceae, Rhodocyclaceae, Veillonellaceae, Prevotellaceae, etc. and has high representation of gut microbes. The identified gut microbes have overrepresentation of Veillonellaceae, Rikenellaceae, Streptococcaceae, and Bacillaceae. Imputed metagenomics of sewage microbiome indicated dominance of transport, motility, peptidases, amino acid metabolism, and antibiotic resistance genes. Microbiome-disease associations drawn using simple decision tree and random forest analysis identified specific microbes as potential predictors of diabetes and obesity in a city. Altogether, we generated the first Indian sewage microbiome and our non-invasive, high-throughput workflow could be emulated for future research, wastewater-based epidemiology and designing policies concerning public health.

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

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

Evaluation of population estimation methods for wastewater-based epidemiology in a metropolitan city

This study evaluated the effect of population estimation on the calculation of drug biomarker consumption using wastewater-based epidemiology. Population estimates using mobile phone data, census data, and wastewater quality parameters, such as biological oxygen demand (BOD), total nitrogen (TN), and total phosphorus (TP), were evaluated in six different wastewater treatment plant catchment areas of Busan Metropolitan City, South Korea. The population based on mobile phone data was affected by the patterns of non-resident population movements in each area. The population-normalized daily loads (PNDLs) of methamphetamine were compared according to the different population results. The PNDLs using the population based on mobile phone data (PNDL_Mobile) was 5.87-27.0 mg/d/1000 people. The PNDL_Mobile values were notably different from the PNDLs using wastewater quality parameters (PNDL_Wastewater) (PNDL_Wastewater/PNDL_Mobile: 51-148 %, mean 93 %, relative standard deviation (RSD) 36 %), indicating the unsuitability of population estimation using BOD, TN, and TP. In areas with a large concentration of workplaces, the PNDLs using census data (PNDL_Census) differed from the PNDL_Mobile values (PNDL_Census/PNDL_Mobile: 57-124 %, mean 94 %, RSD 27 %), whereas other areas showed similar values for PNDL_Census and PNDL_Mobile (PNDL_Census/PNDL_Mobile: 95-108 %, mean 102 %, RSD 4.2 %). In particular, the total population estimates of the six survey areas using census data were approximately the same as those based on mobile phone data (RSD: 0.8 %), indicating a decrease in the influence of the non-residential active population in the entire metropolitan city.

Monkeypox outbreak: Wastewater and environmental surveillance perspective

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

A Framework for Public Health Authorities to Evaluate Health Determinants for Wastewater-Based Epidemiology

BACKGROUND

Wastewater-based epidemiology (WBE) is rapidly developing as a powerful public health tool. It can provide information about a wide range of health determinants (HDs), including community exposure to environmental hazards, trends in consumption of licit and illicit substances, spread of infectious diseases, and general community health. As such, the list of possible candidate HDs for WBE is almost limitless. Consequently, a means to evaluate and prioritize suitable candidates for WBE is useful, particularly for public health authorities, who often face resource constraints.

OBJECTIVES

We have developed a framework to assist public health authorities to decide what HDs may be appropriate for WBE and what biomarkers could be used. This commentary reflects the experience of the authors, who work at the interface of research and public health implementation.

DISCUSSION

To be suitable for WBE, a candidate HD should address a public health or scientific issue that would benefit from better understanding at the population level. For HDs where information on individual exposures or stratification by population subgroups is required, WBE is less suitable. Where other methodologies are already used to monitor the candidate HD, consideration must be given to whether WBE could provide better or complementary information to the current approach. An essential requirement of WBE is a biomarker specific for the candidate HD. A biomarker in this context refers to any human-excreted chemical or biological that could act as an indicator of consumption or exposure to an environmental hazard or of the human health state. Suitable biomarkers should meet several criteria outlined in this commentary, which requires background knowledge for both the biomarker and the HD. An evaluation tree summarizing key considerations for public health authorities when assessing the suitability of candidate HDs for WBE and an example evaluation are presented. https://doi.org/10.1289/EHP11115.

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.

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

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