ACS ES&T Water

Coagulation, flocculation, and sedimentation (CFS) is widely applied as a combined unit process in the treatment of drinking water, wastewater, and recycled water; however, virus reduction through CFS has not been sufficiently characterized to assign pathogen log reduction value (LRV) credits. This study collected data through a systematic review that yielded over 1000 LRVs from 43 manuscripts covering 46 viruses to characterize virus reduction through CFS. The results demonstrate that CFS is effective at reducing viruses, with 68% of virus LRVs greater than 1. A mixed-effects model was used to identify potential mechanisms of virus reduction with ferric and aluminum coagulants, as well as factors associated with variability in performance. Key insights from the model show that virus reduction is: (1) improved at lower pH, similar to natural organic matter (NOM) reduction, (2) lower in secondary effluent than surface water for drinking water treatment, (3) virus-dependent, and (4) dependent on virus enumeration methods, with lower LRVs observed for molecular techniques. These findings demonstrate the potential for CFS to provide consistent and explainable virus reduction, potentially establishing a foundation for regulatory crediting in potable reuse applications. Future crediting frameworks will need to account for the factors impacting performance to accurately quantify and assign credit for virus reduction.

Throughout the COVID-19 pandemic, wastewater surveillance has been used worldwide to provide valuable public health data. RT-qPCR is frequently used as a quantitative methodology for wastewater surveillance but is susceptible to mutations in target regions. These mutations may lead to misinterpretation of surveillance data; a drop in signal could be concluded to be a result of lower viral load, when in fact it is caused by reduced detection efficiency. We describe a novel approach to mitigating the impacts of such mutations: monitoring the cumulative signal from two targets (N1 and N2) via independent amplification reactions using identically labeled probes; a "single-channel multiplex" approach. Using the IDEXX Water SARS-CoV-2 RT-qPCR test, we demonstrate equivalent intra-assay repeatability and quantitative results from the combined N1N2 test when compared to individual N1 and N2 assays. Furthermore, we show that while mutations in B.1.1.529, BA.5.2, and BA.5.2.1 significantly impact the performance of the N1 assay, the impact on the N1N2 assay was negligible, and nearly within acceptable margin of error for technical replicates. These findings demonstrate that a single-channel multiplex approach can be used to improve the robustness of wastewater surveillance and minimize the risk of future mutations leading to unreliable public health data.

Traditional methods for monitoring the microbiological quality of water focus on the detection of fecal indicator bacteria such as Escherichia coli, often tested as a weekly grab sample. To understand the stability of E.coli concentrations over time, we evaluated three approaches to measuring E. coli levels in water: microbial culture using Colilert, quantitative PCR for uidA and next-generation sequencing of the 16S rRNA gene. Two watersheds, one impacted by agricultural and the other by urban activities, were repeatedly sampled over a simultaneous ten-hour period during each of the four seasons. Based on 16S rRNA gene deep sequencing, each watershed showed different microbial community profiles. The bacterial microbiomes varied with season, but less so within each 10-hour sampling period. Enterobacteriaceae comprised only a small fraction (<1%) of the total community. The qPCR assay detected significantly higher quantities of E. coli compared to the Colilert assay and there was also variability in the Colilert measurements compared to Health Canadas recommendations for recreational water quality. From the 16S data, other bacteria such as Prevotella and Bacteroides showed promise as alternative indicators of fecal contamination. A better understanding of temporal changes in watershed microbiomes will be important in assessing the utility of current biomarkers of fecal contamination, determining the best timing for sample collection, as well as searching for additional microbial indicators of the health of a watershed.

Sewage contamination of freshwater occurs in the form of raw waste or as effluent (at varying levels of treatment) from wastewater treatment plants. Global management of this contamination has focused on detection of live sewage-indicating bacteria in freshwater, drinking water, and irrigation systems. While raw waste (animal and human) and underfunctioning WWTPs can introduce live enteric bacteria to freshwater systems, most WWTPs, even when operating correctly, do not remove bacterial genetic material from treated waste, resulting in the addition of concentrated enteric bacterial DNA (molecular contamination), including antibiotic resistance genes, into water columns and sediment of freshwater systems. In freshwater systems with both raw and treated waste inputs, then, there will be increased interaction between live sewage-associated bacteria (untreated sewage) and molecular contamination (from both untreated and treated wastewater effluent), with the potential of increasing antibiotic resistance in the live bacterial populations. To evaluate this understudied interaction between molecular and bacterial contamination in the freshwater environment, we conducted a three-month field-based study of sewage-associated bacteria and genetic material in water and sediment in a freshwater tributary of the Hudson River (NY, USA) that supplies drinking water and receives treated and untreated wastewater discharges from several municipalities. Using both molecular and culture-based bacterial analyses, we demonstrate both treated and untreated sewage influences on water and sediment bacterial communities in this tributary, and water-sediment exchanges of enteric bacteria and associated genetic material with rain events. Furthermore, treated sewage effluent on this waterway serves as a concentrated source of int1 (antibiotic resistance) genes, which appear to collect in the sediments below the outfall along with fecal indicating bacteria, serving as a possible genetic exchange substrate and a source for future molecular and bacterial water contamination. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/530486v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1abdb61org.highwire.dtl.DTLVardef@1cfc550org.highwire.dtl.DTLVardef@1a33647org.highwire.dtl.DTLVardef@40829e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIn a model freshwater system used both as drinking water and wastewater disposal, C_LIO_LIBacterial and genetic material differ between water and sediment compartments C_LIO_LILive bacteria C_LI

Wastewater and environmental monitoring (WEM) was a critical public health surveillance tool for SARS-CoV-2 surveillance during the COVID-19 Pandemic. However, substantial methodological heterogeneity across laboratories continues to challenge the interpretation and thus compromise the actionability of resulting WEM measurements. This study quantifies interlaboratory concordance in SARS-CoV-2 WEM measurements using influent wastewater samples collected between September 2021 and January 2024 at a single wastewater treatment facility within the Ontario Wastewater Surveillance Initiative, analyzed independently by 12 laboratories using their routine methods. In the absence of a known true viral concentration, interlaboratory WEM measurements were evaluated against a facility-specific longitudinal benchmark derived from routine surveillance at the source facility and correlated to clinical surveillance metrics. Concordance was assessed across four WEM measurement units commonly used in practice: SARS-CoV-2 copies/mL, SARS-CoV-2 copies/copies of PMMoV, and their standardized counterpart wastewater viral activity level (WVAL) units of WVAL-standardized SARS-CoV-2 copies/mL and WVAL-standardized SARS-CoV-2 copies/copies of PMMoV. Measurements in each unit were analyzed using complementary analytical frameworks, including categorical concordance metrics, principal component analysis, and linear mixed-effects modelling. Across the study period, interlaboratory measurements consistently captured benchmark temporal dynamics, including major peaks and periods of low activity, but showed substantial variation in magnitude and public-health interpretation across laboratory methods. Concordance was strongest during epidemiological extremes and deteriorated during transitional periods, increasing the risk of misclassification with potentially implications for public health decision-making. To explore potential laboratory methodological drivers of agreement, associations between the benchmark concordance and the laboratory-specific concentration, extraction, and RT-qPCR analytical steps were assessed using Fishers exact tests, alongside extracted-mass threshold analyses. No single methodological factor showed a statistically significant association with benchmark concordance in this study; however, several parameters, including RNA template volume, total RT-qPCR reaction volume, and extracted mass of analyzed settled solids, may warrant further investigation in future studies.

Enteric viruses are a leading cause of waterborne illness worldwide and surveillance studies lack standardization in method selection. The most common and cost-effective approach to concentrating viruses from water samples involves virus adsorption and elution (VIRADEL) procedures, followed by secondary concentration. There is a lack of consistency in how secondary concentration methods are practiced and some methods may have better recovery for particular groups of viruses. Secondary concentration methods typically involve precipitation and the most common methods employ organic flocculation (OF) by acidification at a pH of 3.5, or precipitation by polyethylene glycol (PEG) in combination with the addition of NaCl. In this study, the recovery of coliphage MS2 using the plaque assay and human adenovirus strain 41 (HAdV41) using cell-culture and qPCR assays were evaluated by OF and PEG secondary concentration of spiked samples of wastewater, surface water, and groundwater. The recovery of MS2 and HAdV41 by PEG precipitation was significantly higher than that by OF (p<0.0001) when viruses were detected by culture based methods and marginally better when HAdV41 was enumerated by qPCR (p<0.019). The recovery of HAdV41 by qPCR ranged from 75.3% to 94.4% (n=36). The mean recovery of MS2 by OF was 4.4% (0.9%-7.7%; n=14) and ranged from 57.1% to 87.9% (n=28) for the PEG methods. The poor recovery of MS2 by OF was attributed to inactivation or poor stability at acidic conditions as MS2 were not recovered in the supernatant following OF and centrifugation. The inconsistency and lack of justification for method selection in many studies calls for a systematic study to inform guidance and standardization with respect to the application of concentration methods for various water types and viral pathogens. IMPORTANCEMS2 should not be used as a process control for methods involving acidification and culture-based detection. The dense floc produced by the PEG method may have contributed to higher recoveries as the pellet was more compact and stable than the loose pellet formed by OF. Standard methods for the detection of enteric viruses and surrogates that involve acidification could be modified with PEG precipitation to uphold virus recovery and minimize inactivation.

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has proven a practical complement to clinical data for assessing community-scale infection trends. Clinical assays, such as the CDC-promulgated N1, N2, and N3 have been used to detect and quantify viral RNA in wastewater but, to date, have not included estimates of reliability of true positive or true negative. Bayes Theorem was applied to estimate Type I and Type II error rates for detections of the virus in wastewater. Conditional probabilities of true positive or true negative were investigated when one assay was used, or multiple assays were run concurrently. Cumulative probability analysis was used to assess the likelihood of true SARS-CoV-2 detection using multiple samples. Results demonstrate highly reliable positive (>0.86 for priors >0.25) and negative (>0.80 for priors = 0.50) results using a single assay. Using N1 and N2 concurrently caused greater reliability (>0.99 for priors <0.05) when results concurred but generated potentially counterintuitive interpretations when results were discordant. Regional wastewater surveillance data was investigated as a means of setting prior probabilities. Probability of true detection with a single marker was investigated using cumulative probability across all combinations of positive and negative results for a set of three samples. Findings using a low (0.11) and uniformed (0.50) initial prior resulted in high probabilities of detection (>0.95) even when a set of samples included one or two negative results, demonstrating the influence of high sensitivity and specificity values. Analyses presented here provide a practical framework for understanding analytical results generated by wastewater surveillance programs.

Moore swabs have been used extensively for passive sampling in wastewater surveillance, typically yielding presence/absence information for targets of interest. Quantitative analysis of Moore swab data is only possible if target uptake is well characterized, specifically the relationship between quantity of the target in the liquid sample matrix and the quantity of target sorbing to the Moore swab as a function of time. The mechanism of Moore swab absorption remains unclear and is important to understand toward using them more quantitatively. We conducted viral adsorption and desorption experiments using nonpathogenic SARS-CoV-2 surrogates: {Phi}6, MHV, and BCoV as well as heat-inactivated Zika virus (ZIKV). We fit empirical adsorption data from batch experiments to Langmuir, Freundlich and Redlich-Peterson isotherm models. We observed the adsorption behavior of viral targets onto Moore swabs is best characterized by the Redlich-Peterson isotherm model. Moore swabs retained the highest viral RNA concentrations after exposure durations between 9-12 hours in the presence of target microbes during kinetic viral adsorption experiments. The results inform current and future use of Moore swabs to produce quantitative data during wastewater surveillance, especially in settings where composite sampling remains infeasible. ImportanceThis paper describes the adsorption behavior of viruses and bacteriophages to Moore swabs. Passive sampling via Moore swabs is among the most scalable form of passive wastewater sampling, considered critical to advance wastewater surveillance globally. But key unknowns constrain the utility of Moore swabs and all passive sampling approaches, including the quantitative relationship between targets in wastewater and recovery via Moore swabs. Practical questions such as how long they should be deployed and whether they can be interpreted quantitatively really depend on a characterization of viral target loading behaviors on Moore swab material as a function of time and concentration in the wastewater. Here, we use an approach that is seldom applied to microbial targets to examine adsorption behavior of viruses to Moore swabs, deriving isotherms that describe the relationships between concentration of the viral targets in wastewater and time on attachment to swab material. This is a critical step in advancing the application of Moore swab passive sampling for wastewater surveillance, with potential relevance to other microbial targets of interest.

Nanobubble (NB) technology has been hailed as a novel way to disinfect water. Previous studies suggested that when NBs collapse, they create shock waves that result in OH- free radicals, which can damage cells, including bacteria. In this study, we investigated, through a series of 11 experiments, the potential use of air nanobubbles (128 {+/-} 44 nm, mean {+/-} SD) to reduce the concentration of various pathogenic bacteria including Aeromonas hydrophila, A. veronii, Vibrio parahaemolyticus, and Streptococcus agalactiae under controlled, tank-based laboratory conditions. Despite the high number of nanobubbles continuously added to a relatively small volume of water in experimental tanks (50-100 L), we did not observe a consistent or significant decrease in bacteria that would control disease outbreaks. Although most of the experiments were conducted in fresh water on A. hydrophila, results were consistent across fresh and brackish water experiments, Gram-negative and Gram-positive bacteria, and a range of nanobubble concentrations. This study suggests air nanobubbles on their own are inadequate to significantly reduce high levels of pathogenic bacteria in water. We propose to explore other gases for improving the disinfection properties of this technology. SIGNIFICANCE STATEMENTAir nanobubbles did not sufficiently reduce the level of bacteria in laboratory experiments.

Surveillance of rotavirus infections remains critical because vaccines are underutilized in the USA. Using wastewater solids measurements of rotavirus RNA collected over one year from 185 wastewater treatment plants (WWTPs) in the USA, we inferred spatiotemporal occurrence patterns of rotavirus infections and compared occurrence patterns to clinical metrics of infections and markers of vaccination coverage. We also estimated infection prevalence from wastewater measurements using available data on rotavirus RNA shedding in feces. Nationally, wastewater measurements of rotavirus RNA were correlated with clinical metrics of infection and exhibited elevated winter-spring concentrations beginning in the South. WWTP service areas characterized by markers of high vaccination coverage generally experienced a shorter duration of elevated rotavirus concentrations compared to areas characterized by markers of low vaccination coverage. Rotavirus infection prevalence estimates were highly uncertain and sensitive to shedding parameters. Wastewater monitoring of vaccine-preventable diseases is valuable for informing where vaccination campaigns should be targeted.

BackgroundMetagenomic sequencing of wastewater (W-MGS) can in principle detect any known or novel pathogen in a population. We quantify the sensitivity and cost of W-MGS for viral pathogen detection by jointly analysing W-MGS and epidemiological data for a range of human-infecting viruses. MethodsSequencing data from four studies were analysed to estimate the relative abundance (RA) of 11 human-infecting viruses. Corresponding prevalence and incidence estimates were obtained or calculated from academic and public-health reports. These estimates were combined using a hierarchical Bayesian model to predict RA at set prevalence or incidence values, allowing comparison across studies and viruses. These predictions were then used to estimate the sequencing depth and concomitant cost required for pathogen detection using W-MGS with or without use of a hybridization-capture enrichment panel. FindingsAfter controlling for variation in local infection rates, relative abundance varied by orders of magnitude across studies for a given virus. For instance, a local SARS-CoV-2 weekly incidence of 1% corresponds to predicted SARS-CoV-2 relative abundance ranging from 3.8 x 10-10 to 2.4 x 10-7 across studies, translating to orders-of-magnitude variation in the cost of operating a system able to detect a SARS-CoV-2-like pathogen at a given sensitivity. Use of a respiratory virus enrichment panel in two studies dramatically increased predicted relative abundance of SARS-CoV-2, lowering yearly costs by 24-to 29-fold for a system able to detect a SARS-CoV-2-like pathogen before reaching 0.01% cumulative incidence. InterpretationThe large variation in viral relative abundance after controlling for epidemiological factors indicates that other sources of inter-study variation, such as differences in sewershed hydrology and lab protocols, have a substantial impact on the sensitivity and cost of W-MGS. Well-chosen hybridization capture panels can dramatically increase sensitivity and reduce cost for viruses in the panel, but may reduce sensitivity to unknown or unexpected pathogens. FundingWellcome Trust; Open Philanthropy; Musk Foundation Research In ContextO_ST_ABSEvidence before this studyC_ST_ABSNumerous other studies have performed wastewater metagenomic sequencing (W-MGS), with a range of objectives. However, few have explicitly examined the performance of W-MGS as a monitoring tool. We searched PubMed between database inception and September 2024, using the search terms "MGS OR Metagenomic sequencing OR Metagenomics OR Shotgun sequencing" AND "Performance OR Precision OR Sensitivity OR Cost-effectiveness OR Effectiveness" AND "Virus OR Viral OR Virome" AND "Wastewater OR Sewage". Among the 88 resulting studies, 17 focused specifically on viruses in wastewater. A 2023 UK study by Child and colleagues assessed hybridization-capture and untargeted sequencing of wastewater for genomic epidemiology, concluding that the former but not the latter provided sufficient coverage for effective variant tracking. However, they did find untargeted sequencing sufficient for presence/absence calls of human pathogens in wastewater, a finding supported by numerous other W-MGS studies. While several studies examined the effect of different W-MGS protocols on viral abundance and composition, none accounted for epidemiological or study effects, and none explicitly quantified the sensitivity and cost of W-MGS for viral detection. Added value of this studyTo our knowledge, this study provides the first quantitative assessment of the sensitivity and cost of untargeted and hybridization-capture W-MGS for pathogen surveillance. Linking a large corpus of public wastewater metagenomic sequencing with epidemiological data in a Bayesian model, we predict pathogen relative abundance in W-MGS data at set infection prevalence or incidence, and estimate concomitant read-depth and cost requirements for effective detection across different studies and viruses. Our flexible modelling framework provides a valuable tool for evaluation of sequencing-based surveillance in other contexts. Implications of all the available evidenceThe sensitivity of untargeted W-MGS varies greatly with pathogen and study design, and large gaps in our understanding remain for pathogens not present in our data. As untargeted W-MGS protocols undergo further improvements, our Bayesian modelling framework is an effective tool for evaluating the sensitivity of new protocols under different epidemiological conditions. While less pathogen-agnostic, hybridization capture can dramatically increase the sensitivity of W-MGS-based pathogen monitoring, and our findings support piloting it as a tool for biosurveillance of known viruses.

Wastewater-based surveillance (WBS) is widely used to monitor respiratory viruses, yet uncertainties remain regarding how viral RNA concentrations in wastewater reflect infection dynamics. Specifically, diurnal variation in shedding and RNA losses during in-sewer transport can impact measured signals. We conducted a field study in a 5-km trunk sewer (travel time of one hour). Wastewater was sampled at the sewer inlet and outlet using autosamplers collecting time-proportional one-hour composite samples over 24 hours. The one-hour composite samples were analyzed for assessing intra-daily fluctuations, and 24-hour composites for signal change. Biofilms from the sewer-pipe walls were collected at three locations. Nucleic acids were extracted, and SARS-CoV-2, Influenza A/B, and Respiratory Syncytial Virus (RSV) RNA were quantified using a multiplex digital PCR assay. All viruses showed pronounced diurnal variation, with consistent morning load peaks. Viral RNA in the bulk liquid decreased during in-sewer transport, with modelled changes ranging from 15% to 72% across pathogens. Biofilms served as minor reservoirs of viral RNA; for SARS-CoV-2, sequencing revealed similarity between biofilm and bulk liquid RNA. Our study provides a full-scale assessment of in-sewer transport effects on viral RNA and highlights the need to account for complex in-sewer dynamics when interpreting WBS data.

Quantitative polymerase chain reaction (qPCR) offers a rapid, automated, and potentially on-site method for quantifying L. pneumophila in building potable water systems, complementing and potentially replacing traditional culture-based techniques. However, the application of qPCR in assessing human health risks is complicated by its tendency to overestimate such risks due to the detection of genomic copies that do not correspond to viable, infectious bacteria. This study examines the relationship between L. pneumophila measurements obtained via qPCR and culture-based methods, aiming to understand and establish qPCR-to-culture concentration ratios needed to inform associated health risks. We developed a Poisson lognormal ratio model and a random-effects meta-analysis to analyze variations in qPCR-to-culture ratios within and across sites. Our findings indicate these ratios typically vary from 1:1 to 100:1, with ratios close to 1:1 predicted at all sites. Consequently, adopting a default 1:1 conversion factor appears necessary as a cautious approach to convert qPCR concentrations to culturable concentrations for use in models of associated health risks, for example, through quantitative microbial risk assessment (QMRA) frameworks. Where this approach may be too conservative, targeted sampling and the applications of viability-qPCR could improve the accuracy of qPCR-based QMRA. Standardizing qPCR and culture-based methods and reporting site-specific environmental factors that affect the culturability of L. pneumophila would improve the understanding of the relationship between the two methods. The ratio model introduced here shifts us beyond simple correlation analyses, facilitating investigations of temporal and spatial heterogeneities in the relationship. This analysis is a step forward in the integration of QMRA and molecular biology, as the framework demonstrated here for L. pneumphila is applicable to other pathogens monitored in the environment.

Wastewater monitoring for infectious disease targets is increasingly used to better understand circulation of diseases. The present study validated hydrolysis-probe digital droplet (reverse-transcriptase (RT))-PCR assays for important enteric viruses (rotavirus, adenovirus group F, norovirus GI and GII, and enteroviruses), outbreak or emerging viruses (hepatitis A and West Nile virus), and an emerging drug resistant fungal pathogen (Candida auris). We used the assays to retrospectively measure concentrations of the targets in wastewater solids. Viral and fungal nucleic-acid concentrations were measured in two wastewater solids samples per week at two wastewater treatment plants in the San Francisco Bay Area of California, USA for 26 months. We detected all targets in wastewater solids with the exception of West Nile virus. At both wastewater treatment plants, human adenovirus group F was detected at the highest concentrations, followed by norovirus GII, enteroviruses, norovirus GI, and rotavirus at the lowest concentrations. Hepatitis A and C. auris were detected less consistently than the aforementioned viruses. Enterovirus D68 was detected in a limited time frame during fall 2022 at both sites. The measurements reported herein, and in some cases their seasonal trends, are consistent with previous reports of these targets in wastewater. These measurements represent some of the first quantitative measurements of these infectious disease targets in the solid fraction of wastewater. This study lays a foundation for the use of wastewater solids for the detection of specific infectious disease targets in wastewater monitoring programs aimed to better understand the spread of these diseases.

Despite the wide adoption of wastewater surveillance, more research is needed to understand the fate and transport of viral genetic markers in wastewater. This information is essential for the interpretation of wastewater surveillance data and the development of mechanistic models that link wastewater measurements to the number of individuals shedding virus. In this study, we examined the solid-liquid partitioning behavior of four viruses in wastewater: SARS-CoV-2, respiratory syncytial virus (RSV), rhinovirus (RV), and F+ coliphage/MS2. We used two approaches to achieve this: we (1) conducted laboratory partitioning experiments using lab-grown viruses and (2) examined the distribution of endogenous viruses in wastewater. Partition experiments were conducted at 4{degrees}C and 22{degrees}C; wastewater samples were spiked with varying concentrations of each virus and stored for three hours to allow the system to equilibrate. Solids and liquids were separated via centrifugation and viral RNA concentrations were quantified using reverse-transcription-digital droplet PCR (RT-ddPCR). For the distribution experiment, wastewater samples were collected from six wastewater treatment plants and processed without spiking exogenous viruses; viral RNA concentrations were measured in wastewater solids and liquid. Overall, RNA concentrations were higher in solids than the liquid fraction of wastewater by approximately 3-4 orders of magnitude. Partition coefficients (KF) from laboratory experiments were determined using the Freundlich model and ranged from 2,000-270,000 ml{middle dot}g-1 across viruses and temperature conditions. Distribution coefficients (Kd) determined from endogenous wastewater viruses were consistent with results from laboratory experiments.Further research is needed to understand how virus and wastewater characteristics might influence the partition of viral genetic markers in wastewater. SynopsisWe examined the solid-liquid partitioning behavior of SARS-CoV-2, RSV, RV, and F+coliphage/MS2 RNA in wastewater influent. Overall, partition/distribution coefficients were similar across viruses and temperature conditions.

Microbial contamination of surface waters remains a significant public health concern, particularly in low- and middle-income countries (LMICs) and urban settings affected by combined sewer overflows (CSOs). Standard culture-based methods for monitoring fecal indicator bacteria (FIB)-- including membrane filtration (MF) and most probable number (MPN) assays--typically require laboratory infrastructure, do not provide same-day results, and systematically underestimate total FIB loads due to their inability to accurately quantify aggregate-bound bacteria. This study evaluates ALERT, an automated rapid method for culturable FIB quantification, as a viable field-deployable alternative to conventional laboratory techniques. ALERT employs a whole-sample approach that comprehensively captures both planktonic and aggregate-bound E. coli, thereby addressing critical limitations of traditional methods. Three instrument variants were assessed: the in-situ ALERT System V2, the portable ALERT LAB, and the handheld ALERT One, designed for single-sample analysis in resource-limited environments. Comparative field and laboratory trials conducted in Germany, France, and the UK demonstrate that ALERT delivers accuracy and precision equivalent to MPN methods, while providing faster results directly in the field and enabling high-frequency sampling. Use cases included storm event monitoring, CSO impact evaluation, and on-site validation and optimization of point-of-use water potabilization treatments. ALERT One was also successfully used by citizen scientist volunteers, highlighting its suitability for decentralized community-based monitoring. By enabling rapid, accurate, and comprehensive microbial water quality assessments, ALERT qualifies as a robust field alternative to laboratory testing. It supports enhanced water safety, empowers community-based surveillance and public engagement, and facilitates data-driven decision-making in both LMICs and high-income countries.

The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires a significant, coordinated public health response. Assessing case density and spread of infection is critical and relies largely on clinical testing data. However, clinical testing suffers from known limitations, including test availability and a bias towards enumerating only symptomatic individuals. Wastewater-based epidemiology (WBE) has gained widespread support as a potential complement to clinical testing for assessing COVID-19 infections at the community scale. The efficacy of WBE hinges on the ability to accurately characterize SARS-CoV-2 RNA concentrations in wastewater. To date, a variety of sampling schemes have been used without consensus around the appropriateness of grab or composite sampling. Here we address a key WBE knowledge gap by examining the variability of SARS-CoV-2 RNA concentrations in wastewater grab samples collected every 2 hours for 72 hours compared with three corresponding 24-hour flow-weighted composite samples collected over the same period. Results show relatively low variability (respective means for N1, N2, N3 assays = 608, 847.9, 768.4 copies 100 mL-1, standard deviations = 501.4, 500.3, 505.8 copies 100 mL-1) for grab sample concentrations, and good agreement between most grab samples and their respective composite (mean deviation from composite = 159 copies 100 mL-1). When SARS-CoV-2 RNA concentrations are used to calculate viral load (RNA concentration * total influent flow the sample day), the discrepancy between grabs (log10 range for all grabs = 11.9) or a grab and its associated 24-hour composite (log10 difference = 11.6) are amplified. A similar effect is seen when estimating carrier prevalence in a catchment population with median estimates based on grabs ranging 63-1885 carriers. Findings suggest that grab samples may be sufficient to characterize SARS-CoV-2 RNA concentrations, but additional calculations using these data may be sensitive to grab sample variability and warrant the use of flow-weighted composite sampling. These data inform future WBE work by helping determine the most appropriate sampling scheme and facilitate sharing of datasets between studies via consistent methodology.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/608195v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@abf38dorg.highwire.dtl.DTLVardef@102d02dorg.highwire.dtl.DTLVardef@1b14e5dorg.highwire.dtl.DTLVardef@18fd10d_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic AbstractC_FLOATNO C_FIG Granular activated carbon (GAC) treatment followed by chlorination (GAC/Cl2) and chlorination followed by chloramination (Cl2/NH2Cl) are two methods utilized by drinking water treatment facilities to mitigate the formation of disinfection byproducts (DBPs) in treated water. However, the effectiveness of these methods in reducing the overall toxicity of drinking water, driven by DBPs, remains largely unknown. In this study, we evaluate the total toxicity of water samples from a pilot-scale GAC system with post-chlorination (GAC/Cl2), and occasionally pre-chlorination upstream of GAC (Cl2/GAC/Cl2), compared to water treated by chlorination followed by chloramination (Cl2/NH2Cl). The research was conducted at various bromide and iodide levels and across three GAC bed volumes. To assess DNA stress and oxidative stress in water extracts, we employed the yeast toxicogenomic assay and human cell RT-qPCR assay, along with the DBP analysis from our previous study. Our results indicated that under environmental halogen conditions, GAC/Cl2 typically reduces both genotoxicity and oxidative stress in treated water more effectively than Cl2/NH2Cl and Cl2 treatment. However, Cl2/GAC/Cl2 does not consistently lower toxicity compared to GAC/Cl2. Notably, under high halogen conditions, Cl2/GAC/Cl2 fails to reduce genotoxicity and oxidative stress compared to samples without GAC treatment. Correlation analysis suggested that iodinated DBPs (I-DBPs) and nitrogenous DBPs (N-DBPs) were particularly associated with increased DNA stress and oxidative stress, indicating these classes of DBPs as significant contributors to the observed toxicity. While neither of these two categories of DBPs are regulated by the EPA, it appears that unregulated and unidentified DBPs significantly contribute to the genotoxicity and oxidative stress in drinking water. This research highlights the complex dynamics of water treatment processes and underscores the critical impact of unregulated DBPs on water toxicity.

Wastewater-based epidemiology (WBE) is a valuable tool for surveillance of infectious diseases like COVID-19, yet balancing prediction accuracy with practical deployment remains challenging, particularly in low- resource, low-prevalence, and early warning contexts. We analyzed a two-and-a-half-year dataset from Athens-Clarke County, Georgia (USA) to compare approaches for predicting COVID-19 cases from SARS-CoV-2 wastewater data. We evaluated the effects of extraction replicates and use of quantitative versus detection frequency data on model performance using random forest and linear models. Results show that two extraction replicates generally suffice for reliable prediction, supporting efficient resource use. Combined viral load and detection frequency produced the strongest models, but detection frequency alone predicted new COVID-19 cases more accurately than viral load alone and was less sensitive to RT-qPCR instrumentation changes, making it a practical alternative when quantification is unreliable/infeasible. Linear models predicted new cases more accurately than random forest models, offering a resource-efficient option for monitoring wastewater trends. Following declines in clinical testing in spring 2022, wastewater- based models estimated substantially higher case counts than were reported, underscoring WBEs role for ongoing surveillance of COVID-19 and other infectious diseases. These findings provide practical guidance for optimizing WBE implementation, particularly where early warning and resource constraints are significant factors. HIGHLIGHTSO_LIAnalysis of SARS-CoV-2 in wastewater revealed that presence/absence rates in wastewater predicted new COVID-19 cases better than viral quantity alone C_LIO_LITwo extraction replicates was sufficient for acceptable prediction accuracy C_LIO_LILinear regression models more accurately predicted new cases than random forest C_LIO_LIAfter clinical testing efforts diminished, wastewater models predicted higher case counts than were reported C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC="FIGDIR/small/25330828v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@189e7b8org.highwire.dtl.DTLVardef@cc1102org.highwire.dtl.DTLVardef@1709ed1org.highwire.dtl.DTLVardef@cab23b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Harmful cyanobacterial blooms present persistent risks to both drinking water security and wastewater reuse, driving the need for advanced treatment strategies. Treatment barrier(s) need to be capable of simultaneously controlling cyanobacteria, cyanotoxins, and co-occurring contaminants like bloom-associated antimicrobial resistance genes (ARGs) particularly in the case of recycling treated wastewater. Ozone nanobubble technology has emerged as a promising innovation, offering extended oxidative stability and enhanced interfacial reactivity compared to conventional ozonation. Hence this research objectives were to (a) assess the removal performance of ozone nanobubbles in eliminating cyanobacteria and their co-occurring contaminants in comparison to conventional ozone systems, and (b) investigate the repeatability of the results in varying background water qualities, ozone decay and the potential for by-products formation Ozonation using nanobubbles enhanced oxidation performance by 19%-34% in the drinking water reservoir compared to conventional ozonation while keeping the ozone concentration below 2mg/l. Lower oxidation efficiencies were observed in treated wastewater compared to drinking water sources, reflecting the higher content of organic matter and suspended solids, and oxidant demand characteristic of recycled water systems. Despite these challenges, ozone nanobubbles consistently outperformed conventional ozonation in reducing both cyanobacterial biomass and cell viability, underscoring their potential as an advanced "polishing" step for algal management in wastewater reuse applications. By exploring fate of ARGs alongside cyanobacteria and toxin removal, this work extends beyond traditional ozonation trials. It provides valuable field-based evidence that bridges the divide between laboratory efficacy and full-scale operational performance. Future studies should build on this by exploring combined or sequential treatment barriers that enhance DNA degradation, thereby addressing both cellular and genetic risks in water supply and reuse systems. Observing the action of nanobubbles under dynamic, real-world water quality conditions is currently challenging; however, this studys novel field trials demonstrate potential nanobubble applications and provide valuable insights to guide future investigations. The results reinforce the broader applicability of ozone nanobubble technology for multi-target contaminant control in water reservoirs.