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PubMed2026

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans↗

PubMed2026

Assessing the potential of wastewater-based epidemiology to evaluate the impact of COVID-19 policy changes on stimulant use across 17 countries.

BACKGROUND AND AIMS: A limited number of studies have employed wastewater-based epidemiology (WBE) to assess the impact of specific COVID-19 public health directives on stimulant consumption. This study investigates the potential of WBE as a complementary information source to support decision-making, by examining drug use changes during the pandemic. METHODS: WBE data on stimulant use from 2019 through 2022 was obtained from 17 countries covering a total of 47 wastewater treatment plants worldwide. The Oxford Coronavirus Government Response Tracker stringency index was used to standardize the severity of the COVID-19 interventions across different countries. A multiple linear regression model was fitted for the population-normalized mass loads of amphetamine, cocaine (through its metabolite benzoylecgonine), MDMA, and methamphetamine to investigate whether changes in COVID-19 restrictions influenced stimulant use, controlling for possible week-weekend and spatial effects. RESULTS: In most locations, WBE suggests that stimulant use was not significantly affected by the COVID-19 interventions, or even increased under the stricter measures. Methamphetamine use showed the largest decrease with increasing policy stringency, with a negative linear relationship found in 19% of cities, followed by MDMA (18%), cocaine (15%) and amphetamine (6%). Social gathering restrictions mainly impacted cocaine and MDMA use, while methamphetamine consumption declined most under stringent travel restrictions. CONCLUSIONS: This study highlights the heterogeneous effects of the COVID-19 policy changes on stimulant use, even within countries. The ability of WBE to compile consecutive daily estimates proves to be particularly useful to assess the direct effect of specific policy changes on the consumption of different stimulants.

COVID-19 interventions↗

PubMed2026

Microfiltration (MF) and Ultrafiltration (UF) for Sewage and Surface Water Concentration for SARS-CoV-2 and Other Enveloped Viruses' Detection in Wastewater-Based Epidemiology (WBE).

This study objective was to evaluate hollow fiber membranes for concentration of enveloped enteric viruses in sewage and surface water samples. Microfiltration (MF, 0.2 µm nominal pore size) and ultrafiltration (UF, 100 kDa molecular weight cut-off) hollow fiber membranes were compared for the concentration of the bovine respiratory syncytial virus, and the influence of initial sample volumes (1, 1.5, and 2 L), permeate recovery rates (60%, 70% and 80% of the initial volume collected as permeate, equivalent to volumetric concentration factors of 2.5, 3.3 and 5), and backwashing was assessed. Polyethylene glycol precipitation followed by centrifugation (PEG-C) was evaluated both as a stand-alone method and as a secondary step applied to the membrane concentrate. MF and UF membranes had a similar capacity to retain pollutants and to concentrate organic matter in most parameters and conditions (p > 0.05). In sewage, increasing the initial volume from 1 to 2 L raised recovery from 20.7 ± 0.1% to 30.0 ± 0.1% with MF and from 20.8 ± 0.1% to 25.3 ± 0.1% with UF (p < 0.05), whereas changes in the permeate recovery rate produced no significant differences (p > 0.05). In surface water recovery did not exceed 5.5%, and every increment in the permeate recovery rate produced a significant increase (p < 0.05). Backwashing had a stronger effect on RNA recovery than pore size or the remaining operational parameters, reaching 29.3 ± 9.3% with MF and 33.8 ± 13.7% with UF in sewage and nearly doubling recovery in surface water. In sewage, PEG-C alone (14.1%) was statistically similar to membrane filtration alone (12.1% to 12.3%, p > 0.05), while combining both techniques raised recovery to 23.0% to 25.5%. In surface water, membranes alone recovered 0.8% against 2.4% for PEG-C (p < 0.05), and the combination of UF with PEG-C reached 5.7%, making it a valid alternative, albeit more time consuming and requiring additional equipment. Recoveries are expressed as the ratio between the genome copy concentration in the concentrate and in the spiked sample; on a total genome copy basis they correspond to 4% to 9% in sewage and to about 1% in surface water.

tangential filtration↗

PubMed2026

Whole-genome sequencing of adenovirus 41 directly from wastewater using nested overlapping PCR and MinION.

Human adenovirus F41 (HAdV-F41) is one of the leading causes of children's acute gastroenteritis and was recently linked to an outbreak of severe acute hepatitis of unknown etiology among children during 2021 to 2022. While most evidence is based on clinical data, wastewater-based epidemiology offers a community-level approach to monitoring circulating strains and enhancing outbreak preparedness. In this study, we developed an overlapping amplicon-based whole-genome sequencing approach to directly detect HAdV-F41 from archived wastewater samples, using nested PCR with 13 primer sets. Archived wastewater samples were collected between 2021 and 2022 from three treatment plants in Seattle, USA. The viral load ranged from 1.2 × 103 to 8.4 × 103 genome copies per liter. The Oxford Nanopore platform was used for whole-genome sequencing. Complete or partial (>84%) HAdV-F41 genomes were recovered from wastewater samples, with mean coverage depths ranging from 10³ to 10⁵. The consensus sequences showed more than 99% similarity to reference genomes in the NCBI database. The phylogenetic analysis revealed that 2 sequences clustered within lineage 2a and 11 within lineage 2b, reflecting that at least two sub-lineages were circulating in the community at that time. Our results demonstrate that the overlapping amplicon-based whole-genome sequencing approach using the Oxford Nanopore platform reliably recovers HAdV-F41 genomes from wastewater. This method offers high-resolution genomic surveillance of circulating, clinically relevant HAdV-F41, supporting wastewater-based epidemiology as a valuable tool for detecting emerging variants and strengthening the early warning system for future disease outbreaks.IMPORTANCEHuman adenovirus F41 is a primary cause of childhood gastroenteritis and has been linked to recent outbreaks of severe acute hepatitis in children, yet community-level genomic surveillance of this virus remains limited. This study shows that wastewater can be used to recover nearly complete HAdV-F41 genomes through a targeted overlapping-amplicon sequencing strategy on the Oxford Nanopore platform. By applying this method to archived wastewater samples, we detected the simultaneous circulation of multiple viral lineages in a large city. These findings extend wastewater-based epidemiology beyond SARS-CoV-2 and emphasize its importance for monitoring clinically significant enteric viruses. The method described here offers a scalable tool for tracking viral evolution in communities and enhancing early warning systems for future outbreaks.

Wastewater↗

PubMed2026

Mapping Wastewater Pathogens and Their Associated Environmental and Public Health Risk Factors: A Systematic Review and Meta-Analysis.

BACKGROUND: Wastewater-based epidemiology (WBE) has emerged as a critical tool for public health surveillance, yet its application across diverse pathogens and geographical settings remains inconsistent. This systematic review synthesizes global evidence on wastewater surveillance to identify associated risk factors. METHODS: Following PRISMA 2020 guidelines (PROSPERO: CRD420261297382), a systematic search was conducted across PubMed, Scopus, Google Scholar, and Web of Science for studies published between 2000 and 2025. RESULTS: Thirty-nine peer-reviewed studies were included. The evidence base is geographically skewed toward the European Region (48.7%) and the Americas (23.1%), with significant underrepresentation in LMICs. Viruses were the primary biological target (89.7%), followed by bacteria (7.7%) and parasites (2.6%). A proportion meta-analysis of 31 eligible studies demonstrated a pooled wastewater pathogen detection prevalence of 62% (95% CI: 47.5-74.6%), with the European Region yielding the highest regional estimate (73%) and the African Region the lowest (8.3%). Conventional PCR and sequencing methods showed higher pooled detection rates (92.4% and 90.1%, respectively) than RT-qPCR (47.9%). CONCLUSION: WBE provides a robust early-warning system indicating a need for broader pathogen diversity, incorporating bacterial and parasitic surveillance and expansion into rural and resource-limited regions.

Contamination↗

PubMed2020

The wastewater microbiome: A novel insight for COVID-19 surveillance.

Wastewater-Based Epidemiology is a tool to face and mitigate COVID-19 outbreaks by evaluating conditions in a specific community. This study aimed to analyze the microbiome profiles using nanopore technology for full-length 16S rRNA sequencing in wastewater samples collected from a penitentiary (P), a residential care home (RCH), and a quarantine or health care facilities (HCF). During the study, the wastewater samples from the RCH and the P were negative for SARS-CoV-2 based on qPCRs, except during the fourth week when was detected. Unexpectedly, the wastewater microbiome from RCH and P prior to week four was correlated with the samples collected from the HCF, suggesting a core bacterial community is expelled from the digest tract of individuals infected with SARS-CoV-2. The microbiota of wastewater sample positives for SARS-CoV-2 was strongly associated with enteric bacteria previously reported in patients with risk factors for COVID-19. We provide novel evidence that the wastewater microbiome associated with gastrointestinal manifestations appears to precede the SARS-CoV-2 detection in sewage. This finding suggests that the wastewaters microbiome can be applied as an indicator of community-wide SARS-CoV-2 surveillance.

COVID-19↗

PubMed2025

Inclusion of Physical-Chemical Water Quality Measurements Can Improve Associations between SARS-CoV-2 RNA Levels in Wastewater and COVID-19 Cases within Smaller Sewersheds.

Measurements of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater can be used to understand the prevalence of COVID-19 cases within a community. Environmental conditions inclusive of physical-chemical water quality characteristics are known to impact wastewater SARS-CoV-2 signals, but they are rarely measured within the sewer infrastructure in areas upstream of wastewater treatment plants (WWTPs). The objectives of this study were to report on measurements of environmental parameters [flow and physical-chemical water quality (water temperature, pH, specific conductivity, dissolved oxygen, and turbidity)] upstream of a WWTP and to evaluate whether the inclusion of these environmental parameters improves correlations between SARS-CoV-2 RNA levels in wastewater, and COVID-19 prevalence in the sewershed community. Measurements of environmental parameters and SARS-CoV-2 RNA in wastewater spanned different time scales (minutes, hours and weeks) and population scales (building, campus, community). For short time scales, water quality parameters did not improve correlations between SARS-CoV-2 in wastewater and COVID-19 prevalence due to high variability of water quality and flows within the sewer system. When averaging data over weekly time scales, regressions showed that inclusion of pH improved correlations between RNA and COVID-19 prevalence. At the cluster scale, for the entire data set, the root mean square error decreased from 6.9 cases per week to 6.5 cases per week. At the community scale benefits were observed only for the delta wave with a decrease in root mean square error from 539 cases per week to 430 cases per week. The inclusion of pH improved correlations between wastewater SARS-CoV-2 and COVID-19 prevalence more frequently when evaluating the cluster sewershed scale (populations of a few thousand) in comparison to the community scale (populations of several 100,000). Given the simplicity of measuring pH and other physical-chemical water quality parameters, their inclusion should be considered as part of wastewater-based epidemiology programs.

COVID-19↗

PubMed2025

Drug resistant Klebsiella pneumoniae from patients and hospital effluent: a correlation?

BACKGROUND: The application of wastewater-based epidemiology has gained traction as a cost effective tool in antimicrobial resistance (AMR) surveillance with studies showing a correlation between the presence of resistant bacteria from hospital sewage and patients. This study compared Klebsiella pneumoniae from patients and hospital effluent in terms of antibiotic resistance patterns, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs) and phylogenomic relationships. RESULTS: Pooled effluent samples were collected from the final effluent point of a regional hospital and K. pneumoniae isolates were identified on selective media. Clinical isolates were also collected from the same hospital. Antimicrobial susceptibility testing (AST) was performed using the VITEK® 2 system. DNA was extracted prior to whole genome sequencing (WGS). The resistome, mobilome, and phylogenetic lineages of sequenced isolates were assessed using bioinformatics analysis. A total of 10 randomly selected presumptive and 10 clinical K. pneumoniae constituted the sample and were subjected to AST. Total resistance was observed in the clinical samples to cefuroxime, cefotaxime, piperacillin/tazobactam, gentamicin, tobramycin and trimethoprim/sulfamethoxazole. The effluent isolates exhibited total susceptibility to most antibiotics but showed resistance to amoxicillin/clavulanic acid and piperacillin/tazobactam (100%), and tigecycline (10%). The effluent isolates did not exhibit a diverse resistome, while the clinical isolates harboured genes conferring resistance to aminoglycoside (aph(6)-Id, aph(3'')-Ib, aac(6')-Ib-cr, aadA16), ß-lactam (blaSVH group, blaOXA group, blaTEM group), and fluoroquinolone (oqxA, oqxB) antibiotics. Only class 1 integrons were identified. Phylogenetic analysis revealed that effluent isolates from this study were not closely related to the clinical isolates. CONCLUSION: This study showed no correlation between the resistance profiles of the clinical and effluent isolates. The relationship between AMR in hospital effluent and clinical resistance may depend on the antimicrobial agents and bacterial species studied.

Klebsiella pneumoniae↗

PubMed2025

Wastewater Sequencing Reveals Persistent Circulation and Rising Prevalence of Several Oncogenic Viruses Across Texas.

BACKGROUND: Oncogenic viruses cause high-risk cancers in humans and are responsible for nearly 20% of all cancer cases worldwide. Currently, very limited data exists in the realm of wastewater-based viral epidemiology (WBE) of cancer-causing viruses, with existing studies using targeted approaches (i.e PCR-based approaches) which lack scalability. Our study aims to carry out WBE with hybrid-capture probes to detect and track multiple oncogenic viruses simultaneously in wastewater across Texas, USA, overcoming the drawbacks associated with targeted approaches. METHODS: Here, we used a hybrid-capture approach to detect, filter and sequence oncogenic virus signals from wastewater samples collected over a duration of three years, from May 2022 to May 2025. Once viral reads were sequenced, we utilized established computational tools to characterize reads into their respective virus of origin. Next, viral abundances of each characterized oncogenic virus were tracked over time and read coverage across their genomes was measured using read mapping techniques. FINDINGS: We detected six known oncogenic viruses, along with three suspected oncogenic viruses across all sampling locations within Texas. Over three years, viral abundance gradually increased, with distinct peaks and dips over the summer and winter months. The prevalence of high-risk viruses such as HPV and EBV rose sharply, with increases in abundance observed post-2024. We also obtained nearly 100% genome coverage with viral reads captured using a hybrid-capture technique for almost all oncogenic viruses and their types. INTERPRETATIONS: Our study shows that a hybrid-capture method can efficiently overcome the challenges faced with using targeted approaches for WBE. Using this method, we get broader read coverage, coupled with concurrent and consistent real-time tracking dynamics of multiple oncogenic viruses. Our findings also emphasize the persistent circulation and rising prevalence of high-risk cancer-causing viruses, underscoring the need for sustained public health interventions to protect communities and assess viral prevalence in high-risk populations. FUNDING: This work was supported by S.B. 1780, 87th Legislature, 2021 Reg. Sess. (Texas 2021), the Baylor College of Medicine and the Alkek Foundation Seed Funds.

Journal Article↗

PubMed2026

Population-level genomic surveillance of human norovirus using wastewater-based whole-genome sequencing.

Wastewater-based surveillance has garnered increasing attention as a valuable approach for capturing community-level infection dynamics that are often difficult to detect through clinical reporting systems alone. In this study, we analyzed human norovirus genotype distributions and whole-genome-level variations in wastewater samples collected in Gwangju, Korea. These results were interpreted in conjunction with a documented foodborne outbreak to evaluate the epidemiological relevance of wastewater-based monitoring. Human norovirus concentrations were quantified using TaqMan Array Card-based RT-qPCR, and whole-genome next-generation sequencing (NGS) was performed to obtain viral read counts and reads per kilobase per million filtered reads values. Overall, strong correlations were observed between RT-qPCR-based concentrations and NGS-derived metrics. Genotype dynamics varied among wastewater treatment plants, reflecting differences in catchment size and local population characteristics. In particular, the relative abundance of GII.17[P17] increased during epidemiological week 50, temporally coinciding with a documented local foodborne outbreak. Variant analysis revealed that wastewater samples exhibited mixed nucleotide patterns, with multiple alleles coexisting at varying relative frequencies rather than fixed substitutions. Notably, some nonsynonymous variants detected in clinical samples were also observed in wastewater samples collected surrounding the outbreak period. Together, these findings demonstrate that wastewater-based whole-genome surveillance can capture both genotype-level shifts and nucleotide-level dynamics at the population scale, highlighting its potential as a complementary tool for monitoring community-level norovirus circulation and outbreak-associated genotype dynamics.IMPORTANCEWastewater-based surveillance is increasingly recognized as a promising approach for capturing community-level infection dynamics that are often missed by clinical surveillance. In this study, we applied whole-genome sequencing to wastewater samples collected in Gwangju, South Korea, to comprehensively characterize human norovirus genotype distributions and genetic variation. Distinct genotype patterns were observed across wastewater treatment plants, reflecting differences in catchment population size and local characteristics. Notably, an increase in the GII.17[P17] genotype detected in wastewater coincided with a foodborne outbreak investigated in Gwangju, demonstrating the potential of wastewater surveillance to reflect ongoing community transmission and emerging outbreak-associated genotypes. In addition, wastewater samples contained diverse and coexisting genetic variants, capturing population-level viral diversity and evolutionary dynamics that are not readily detected through clinical surveillance alone. These findings highlight the value of wastewater-based whole-genome surveillance for monitoring community-level viral circulation and support its integration as a complementary strategy to existing clinical surveillance systems.

genotype dynamics↗

PubMed2026

Wastewater-based sequencing of respiratory syncytial virus to investigate lineage dynamics and antigenic site mutations: a retrospective genomic epidemiology study.

BACKGROUND: Respiratory syncytial virus (RSV) infections pose a substantial health burden, particularly for clinically vulnerable populations such as infants and older adults. Although novel immunoprophylactic interventions show promise in providing protection, many countries may not have robust surveillance systems to monitor circulating RSV lineages and detect mutations that might reduce the effectiveness of these new interventions. We aimed to assess the diversity and temporal dynamics of circulating RSV lineages in urban populations through amplicon-based sequencing and analysis of wastewater extracts. METHODS: In this prospective observational wastewater-based genomic surveillance study, 32 raw influent 24-h composite samples were collected during the 2022-23 and 2023-24 RSV seasons from both Zurich and Geneva, Switzerland. We applied an RSV subtype-specific amplicon-based sequencing approach to obtain RSV-A and RSV-B sequences from all 64 samples. Mutations relative to reference genomes were identified at positions with read depth above 30. Relative abundances of RSV lineages were estimated from frequencies of lineage-signature mutations, present in greater than 90% of publicly available sequences of that lineage. FINDINGS: Relative abundances of RSV-B (2022-23) and RSV-A (2023-24) lineages were estimated over the two RSV seasons. During the 2022-23 season, the RSV-B B.D.E.1 lineage prevailed in both cities. In the 2023-24 season, multiple RSV-A lineages cocirculated, including A.D.1, A.D.3, A.D.5, and their sub-lineages. Identification and frequency estimation of mutations showed low-frequency, non-synonymous mutations in antigenic sites on the fusion gene of both RSV-A and RSV-B, some of which have not been reported in clinical sequences. The primary outcome was identification and relative abundance of RSV lineages in wastewater samples. INTERPRETATION: These findings show the potential of wastewater-based genomic surveillance to identify and track circulating RSV lineages and clinically relevant mutations. As novel RSV immunoprophylaxis measures are introduced in upcoming RSV seasons, wastewater-derived genomic RSV data provide a valuable baseline for understanding RSV diversity and future viral evolution under increased immunological pressure. FUNDING: This study was funded by the Swiss National Science Foundation and in part by the National Institute Of Allergy And Infectious Diseases of the National Institutes of Health. Funding for sample collection and processing was provided by the Swiss Federal Office of Public Health.

Humans↗