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Enveloped virus fate in the environment is not well understood; there are no quantitative data on sunlight inactivation of enveloped viruses in water. Herein, we measured the sunlight inactivation of two enveloped viruses (Phi6 and murine hepatitis virus, MHV) and a nonenveloped virus (MS2) over time in clear water with simulated sunlight exposure. We attenuated UV sunlight wavelengths using long-pass 50% cutoff filters at 280, 305, and 320 nm. With the lowest UV attenuation tested, all decay rate constants (corrected for UV light screening, k̂) were significantly different from dark controls; the MS2 k̂was equal to 4.5 m2/MJ, compared to 16 m2/MJ for Phi6 and 52 m2/MJ for MHV. With the highest UV attenuation tested, only k̂for MHV (6.1 m2/MJ) was different from the dark control. Results indicate that the two enveloped viruses decay faster than the nonenveloped virus studied, and k̂are significantly impacted by UV attenuation. Differences in k̂may be due to the presence of viral envelopes but may also be related to other differing intrinsic properties of the viruses, including genome length and composition. Reported k̂values can inform strategies to reduce the risk from exposure to enveloped viruses in the environment.

Forecasting environmental hazards is critical in preventing or building resilience to their impacts on human communities and ecosystems. Environmental data science is an emerging field that can be harnessed for forecasting, yet more work is needed to develop methodologies that can leverage increasingly large and complex data sets for decision support. Here, we design a data-driven framework that can, for the first time, forecast bacterial standard exceedances at marine beaches with 3 days lead time. Using historical data sets collected at two California sites, we train nearly 400 forecast models using statistical and machine learning techniques and test forecasts against predictions from both a naive “persistence” model and a baseline nowcast model. Overall, forecast models are found to have similar sensitivities and specificities to the persistence model, but significantly higher areas under the ROC curve (a metric distinguishing a model’s ability to effectively parse classes across decision thresholds), suggesting that forecasts can provide enhanced information beyond past observations alone. Forecast model performance at all lead times was similar to that of nowcast models. Together, results suggest that integrating the forecasting framework developed in this study into beach management programs can enable better public notification and aid in proactive pollution and health risk management.

Despite the widespread 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 optimizing monitoring strategies and interpreting wastewater surveillance data. 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: (1) laboratory partitioning experiments using lab-grown viruses and (2) distribution experiments using endogenous viruses in raw wastewater. Partition experiments were conducted at 4 and 22 °C. Wastewater samples were spiked with varying concentrations of each virus, solids and liquids were separated via centrifugation, and viral RNA concentrations were quantified using reverse-transcription-digital droplet PCR (RT-ddPCR). For the distribution experiments, wastewater samples were collected from six wastewater treatment plants and processed without spiking exogenous viruses; viral RNA concentrations were measured in wastewater solids and liquids. In both experiments, RNA concentrations were higher in the solid fraction than the liquid fraction by approximately 3–4 orders of magnitude. Partition coefficients (KF) ranged from 2000–270,000 mL·g–1across viruses and temperature conditions. Distribution coefficients (Kd) were consistent with results from partitioning experiments. Further research is needed to understand how virus and wastewater characteristics might influence the partitioning of viral genetic markers in wastewater.

Water, sanitation, and hygiene (WASH) improvements are promoted to reduce diarrhoea in low-income countries. However, trials from the past 5 years have found mixed effects of household-level and community-level WASH interventions on child health. Measuring pathogens and host-specific faecal markers in the environment can help investigate causal pathways between WASH and health by quantifying whether and by how much interventions reduce environmental exposure to enteric pathogens and faecal contamination from human and different animal sources. We aimed to assess the effects of WASH interventions on enteropathogens and microbial source tracking (MST) markers in environmental samples.

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

Enveloped viruses are characterized by a lipid-containing envelope that encapsulates the virion, and they have been the cause of major outbreaks and pandemics. Some enveloped viruses are excreted in feces and other bodily fluids of infected people and animals, raising the question of their fate in the aquatic environment. Consequently, we conducted a systematic review and meta-analysis of the decay rate constants (k) of enveloped viruses from 12 families (i.e., Coronaviridae, Cystoviridae(specifically Phi6), Filoviridae, Hepadnaviridae, Herpesviridae, Orthomyxoviridae, Paramyxoviridae, Pneumoviridae, Poxviridae, Retroviridae, Rhabdoviridae, Togaviridae) in environmental waters and wastewater to evaluate their decay kinetics and identify the environmental and virus characteristics that influence k. A total of 812 kthat met inclusion criteria were identified in the literature, with the number of kfor each family ranging from 0 to 560, and the virus family averaged values of kranging from 0.11 d–1and 1.85 d–1. Virus type (i.e., genus, species, subspecies, or subtype), method of virus enumeration (i.e., culture-based or (RT-)QPCR), and experimental water matrix type, temperature and sterility were found to have significant effects on k. Additionally, enveloped viruses were found to have statistically significantly greater kthan nonenveloped viruses. Multiple linear regression models that allow prediction of log10kas a function of virus type, enumeration method, water temperature, and water type are provided for six virus families that had sufficient data available for model fitting (i.e., Coronaviridae, Phi6, Herpesviridae, Orthomyxoviridae, Rhabdoviridae, Togaviridae). Compiled log10kand multiple regression models can be used to inform management of human and animal waste, operation of water and wastewater facilities, and exposure risks to treatment plant workers and communities living in regions that lack treatment facilities. Given limited data available for some enveloped virus families with a potential water-related transmission route, there is need for additional data collection to aid academic researchers, public health agencies, and water and wastewater professionals involved in outbreak response.

Real-time quantitative polymerase chain reaction (qPCR) and digital PCR (dPCR) methods have revolutionized environmental microbiology, yielding quantitative organism-specific data of nucleic acid targets in the environment. Such data are essential for characterizing interactions and processes of microbial communities, assessing microbial contaminants in the environment (water, air, fomites), and developing interventions (water treatment, surface disinfection, air purification) to curb infectious disease transmission. However, our review of recent qPCR and dPCR literature in our field of health-related environmental microbiology showed that many researchers are not reporting necessary and sufficient controls and methods, which would serve to strengthen their study results and conclusions. Here, we describe the application, utility, and interpretation of the suite of controls needed to make high quality qPCR and dPCR measurements of microorganisms in the environment. Our presentation is organized by the discrete steps and operations typical of this measurement process. We propose systematic terminology to minimize ambiguity and aid comparisons among studies. Example schemes for batching and combining controls for efficient work flow are demonstrated. We describe critical reporting elements for enhancing data credibility, and we provide an element checklist in the Supporting Information. Additionally, we present several key principles in metrology as context for laboratories to devise their own quality assurance and quality control reporting framework. Following the EMMI guidelines will improve comparability and reproducibility among qPCR and dPCR studies in environmental microbiology, better inform engineering and public health actions for preventing disease transmission through environmental pathways, and for the most pressing issues in the discipline, focus the weight of evidence in the direction toward solutions.

Human norovirus (hNoV) is an important etiology of gastrointestinal illness and can be transmitted via ingestion of contaminated water. Currently impractical to culture, hNoV detection is reliant on real-time polymerase chain reaction (RT-PCR)-based methods. This approach cannot distinguish between infective and inactivated viruses because intact regions of the RNA genome can amplify even if the damage is present in other regions of the genome or because intact genetic material is not contained within an infectious virion. Herein, we employ a multiple long-amplicon RT-qPCR extrapolation approach to assay genome-wide damage and an enzymatic pretreatment to study the impact of simulated sunlight on the infectivity of hNoV in clear, sensitizer-free water. Using MS2 coliphage as an internal control, the genome-wide damage extrapolation approach, previously successfully applied for UV-254 inactivation, vastly overestimated sunlight inactivation, suggesting key differences in photoinactivation under different spectral conditions. hNoV genomic RNA was more susceptible to simulated sunlight degradation per base compared to MS2 genomic RNA, while enzymatic pretreatment indicated that hNoV experienced more capsid damage than MS2. This work provides practical and mechanistic insight into the endogenous sunlight inactivation of single-stranded RNA bacteriophage MS2, a widely used surrogate, and hNoV GII.4 Sydney, an important health-relevant virus, in clear sensitizer-free water.

During the COVID-19 pandemic, many countries and regions investigated the potential use of wastewater-based disease surveillance as an early warning system. Initially, methods were created to detect the presence of SARS-CoV-2 RNA in wastewater. Investigators have since conducted extensive studies to examine the link between viral concentration in wastewater and COVID-19 cases in areas served by sewage treatment plants over time. However, only a few reports have attempted to create predictive models for hospitalizations at a county-level based on SARS-CoV-2 RNA concentrations in wastewater. This study implemented a linear mixed-effects model that evaluates the association between levels of virus in wastewater and county-level hospitalizations. The model was then utilized to predict short-term county-level hospitalization trends in 21 counties in California based on data from March 21, 2022, to May 21, 2023. The modeling framework proposed here permits repeated measurements, as well as fixed and random effects. The model that incorporated wastewater data as an input variable rather than cases or test positivity rate exhibited robust performance and effectively captured discernible trends in hospitalizations. Additionally, the model allows for the prediction of SARS CoV-2 hospitalizations two weeks ahead. Forecasts of COVID-19 hospitalizations could provide crucial information for hospitals to better allocate resources and prepare for potential surges in patient numbers.

To reduce the incidence of recreational waterborne illness, fecal indicator bacteria (FIB) are measured to assess water quality and inform beach management. Recently, predictive FIB models have been used to aid managers in making beach posting and closure decisions. However, those predictive models must be trained using rich historical data sets consisting of FIB and environmental data that span years, and many beaches lack such data sets. Here, we investigate whether water quality data collected during discrete short duration, high-frequency beach sampling events (e.g., samples collected at sub-hourly intervals for 24–48 h) are sufficient to train predictive models that can be used for beach management. We use data collected during six high-frequency sampling events at three California marine beaches and train a total of 126 models using common data-driven techniques. Tide, solar irradiation, water temperature, significant wave height, and offshore wind speed were found to be the most important environmental variables in the models. We validate the predictive performance of models using withheld data. Random forests are consistently the top performing model type. Overall, we find that data-driven models trained using high-frequency FIB and environmental data perform well at predicting water quality and can be used to inform public health decisions at beaches.

Wastewater-based epidemiology may be useful for informing public health response to viral diseases like COVID-19 caused by SARS-CoV-2. We quantified SARS-CoV-2 RNA in wastewater influent and primary settled solids in two wastewater treatment plants to inform the preanalytical and analytical approaches and to assess whether influent or solids harbored more viral targets. The primary settled solids samples resulted in higher SARS-CoV-2 detection frequencies than the corresponding influent samples. Likewise, SARS-CoV-2 RNA was more readily detected in solids using one-step digital droplet (dd)RT-PCR than with two-step RT-QPCR and two-step ddRT-PCR, likely owing to reduced inhibition with the one-step ddRT-PCR assay. We subsequently analyzed a longitudinal time series of 89 settled solids samples from a single plant for SARS-CoV-2 RNA as well as coronavirus recovery (bovine coronavirus) and fecal strength (pepper mild mottle virus) controls. SARS-CoV-2 RNA targets N1 and N2 concentrations correlated positively and significantly with COVID-19 clinically confirmed case counts in the sewershed. Together, the results demonstrate that measuring SARS-CoV-2 RNA concentrations in settled solids may be a more sensitive approach than measuring SARS-CoV-2 in influent.

SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of meta-information to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what meta-information should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting.

Information about microbial water quality is critical for managing water safety and protecting public health. In low-income countries, monitoring all drinking water supplies is impractical because financial resources and capacity are insufficient. Data sets derived from satellite imagery, census, and hydrological models provide an opportunity to examine relationships between a suite of environmental risk factors and microbial water quality over large geographical scales. We investigated the relationships between groundwater fecal contamination and different environmental parameters in Uganda and Bangladesh. In Uganda, groundwater contamination was associated with high population density (p< 0.001; OR = 1.27), high cropland coverage (p< 0.001; OR = 1.47), high average monthly precipitation (p< 0.001; OR = 1.14), and high surface runoff (p< 0.001; OR = 1.37), while low groundwater contamination was more likely in areas further from cities (p< 0.001; OR = 0.66) and with higher forest coverage (p< 0.001; OR = 0.70). In Bangladesh, contamination was associated with higher weekly precipitation (p< 0.001; OR = 1.44) and higher livestock density (p = 0.05; OR = 1.11), while low contamination was associated with low forest coverage (p< 0.001; OR = 1.23) and high cropland coverage (p< 0.001; OR = 0.80). We developed a groundwater contamination index for each country to help decision-makers identify areas where groundwater is most prone to fecal contamination and prioritize monitoring activities. Our approach demonstrates how to harness satellite-derived data to guide water safety management.

Fecal pollution at beaches can pose a health risk to recreators. Quantitative microbial risk assessment (QMRA) is a tool to evaluate the use of candidate fecal indicators to signify a health risk from enteric pathogens in sewage-impacted waters. We extend the QMRA approach to model mixtures of sewage at different ages using genetic marker concentrations for human-associated crAssphage, Bacteroidesspp., and polyomavirus in sewage samples from 49 wastewater facilities across the contiguous United States. Risk-based threshold (RBT) estimates varied across different mixture and sewage age scenarios. Fresh sewage RBT estimates were not always protective when aged sewage was present, and aged sewage RBT estimates often fell below the marker lower limit of quantification. Conservative RBT estimates of 9.3 × 102and 9.1 × 103(copies/100 mL) for HF183/BacR287 and CPQ_056, respectively, were predicted when fresh sewage was greater (by volume) than aged at the time of measurement. Conversely, genetic markers may not be effective indicators when aged sewage contributes the majority of pathogens, relative to fresh contamination, but minimal marker levels. Results highlight the utility of QMRA that incorporates pollutant age and mixture scenarios, the potential advantages of a crAssphage fecal indicator, and the potential influence of site-specific factors on estimating RBT values.

Stormwater biofilters are being implemented widely in urban environments to provide green space, alleviate flooding, and improve stormwater quality. However, biofilters with conventional media (sand, soil, and/or mulch or compost) do not reliably remove contaminants from stormwater. Research suggests addition of biochar to the biofilter media can improve the pollutant removal capacity of biofilters. In the current work, we present a systematic review of laboratory and mesocosm studies of biochar-augmented biofilters and an assessment of watershed-scale implementation of biofilters on local water quality. A full text review of 84 papers was conducted; of these, data were extracted from the 14 that met our inclusion criteria. log10removal of microbial pollutants and trace organic contaminants (TOrCs) by biochar-augmented media is generally greater than those of the controls containing just sand, soil, and/or compost. log10removal of nitrogen, phosphorous, total organic carbon, and total suspended solids in biochar-augmented biofilters is not clearly higher than those of control experiments. A supplemental analysis of four studies reporting longer-term breakthrough data revealed that TOrC removal effectiveness varies substantially among high temperature wood-based biochars, and that operational lifetimes of full-scale systems constrained by TOrC sorption capacity could range from five months to over seven years depending on the selected biochar. At the watershed-scale, biochar-augmented biofilters can provide enhanced treatment of runoff, resulting in the need for fewer treatment units or a smaller volume of watershed runoff treated to meet water quality criteria compared to their conventional counterparts. While their installation can reduce the load of pollutants to receiving waters, achieving concentration-based water quality targets may prove difficult even when pollutant removal capacity is high. This work highlights the importance of a systems approach to studying how biofilter installation affects water quality within a watershed. We identify several topical areas where further research is needed, especially as installation of biofilters and other stormwater control measures gain popularity in highly urbanized watersheds.

Fecal indicator organisms are measured to indicate the presence of fecal pollution, yet the association between indicators and pathogens varies by context. The goal of this study was to empirically evaluate the relationships between indicator Escherichia coli, microbial source tracking markers, select enteric pathogen genes, and potential sources of enteric pathogens in 600 rural Bangladeshi households. We measured indicators and pathogen genes in stored drinking water, soil, and on mother and child hands. Additionally, survey and observational data on sanitation and domestic hygiene practices were collected. Log10concentrations of indicator E. coliwere positively associated with the prevalence of pathogenic E. coligenes in all sample types. Given the current need to rely on indicators to assess fecal contamination in the field, it is significant that in this study context indicator E. coliconcentrations, measured by IDEXX Colilert-18, provided quantitative information on the presence of pathogenic E. coliin different sample types. There were no significant associations between the human fecal marker (HumM2) and human-specific pathogens in any environmental sample type. There was an increase in the prevalence of Giardia lambliagenes, any E. colivirulence gene, and the specific E. colivirulence genes stx1/2with every log10increase in the concentration of the animal fecal marker (BacCow) on mothers’ hands. Thus, domestic animals were important contributors to enteric pathogens in these households.

This study investigated the risk of gastrointestinal illness associated with swimming in surface waters with aged sewage contamination. First, a systematic review compiled 333 first order decay rate constants (k) for human norovirus and its surrogates feline calicivirus and murine norovirus, Salmonella, Campylobacter, Escherichia coliO157:H7, Giardia, and Cryptosporidium, and human-associated indicators in surface water. A meta-analysis investigated effects of sunlight, temperature, and water matrix on k. There was a relatively large number of kfor bacterial pathogens and some human-associated indicators (n> 40), fewer for protozoans (n= 14–22), and few for human norovirus and its Caliciviridaesurrogates (n= 2–4). Average kranked: Campylobacter> human-associated markers > Salmonella> E. coliO157:H7 > norovirus and its surrogates > Giardia> Cryptosporidium. Compiled kvalues were used in a quantitative microbial risk assessment (QMRA) to simulate gastrointestinal illness risk associated with swimming in water with aged sewage contamination. The QMRA used human-associated fecal indicator HF183 as an index for the amount of sewage present and thereby provided insight into how risk relates to HF183 concentrations in surface water. Because exposure to norovirus contributed the majority of risk, and HF183 kis greater than norovirus k, the risk associated with exposure to a fixed HF183 concentration increases with the age of contamination. Swimmer exposure to sewage after it has aged ∼3 days results in median risks less than 30/1000. A risk-based water quality threshold for HF183 in surface waters that takes into account uncertainty in contamination age is derived to be 4100 copies/100 mL.

Stormwater best management practices (BMPs) are implemented to reduce microbial pollution in runoff, but their removal efficiencies differ. Enhanced BMPs, such as those with media amendments, can increase removal of fecal indicator bacteria (FIB) in runoff from 0.25-log10to above 3-log10; however, their implications for watershed-scale management are poorly understood. In this work, a computational model was developed to simulate watershed-scale bacteria loading and BMP performance using the Ballona Creek Watershed (Los Angeles County, CA) as a case study. Over 1400 scenarios with varying BMP performance, percent watershed area treated, BMP treatment volume, and infiltrative capabilities were simulated. Incremental improvement of BMP performance by 0.25-log10, while keeping other scenario variables constant, reduces annual bacterial load at the outlet by a range of 0–29%. In addition, various simulated scenarios provide the same FIB load reduction; for example, 75% load reduction is achieved by diverting runoff from either 95% of the watershed area to 25 000 infiltrating BMPs with 0.5-log10removal or 75% of the watershed area to 75 000 infiltrating BMPs with 1.5-log10removal. Lastly, simulated infiltrating BMPs provide greater FIB reduction than noninfiltrating BMPs at the watershed scale. Results provide new insight on the trade-offs between BMP treatment volume, performance, and distribution.

Stormwater biofilters are distributed stormwater control measures for managing urban runoff. Recent work has shown that adding biochar to biofilters can reduce stormwater contaminant concentrations, including fecal indicator bacteria (FIB). However, the potential of biochar-augmented biofilters to remove human pathogens from stormwater has not been investigated. In this study, we investigated the removal of bacterial pathogens Salmonella entericaserovar Typhimurium and Staphylococcus aureus, as well as bacterial and viral indicators Escherichia coliand MS2 coliphage in laboratory-scale biochar-amended biofilters. Biochar-amended biofilters performed better than sand biofilters in removing the microorganisms from stormwater and removal of pathogenic bacteria was greater than that of FIB. Biochar-augmented biofilters provided up to 3.9, 1.9, and 1.8 log10removal for pathogenic bacteria, E. coli, and MS2, respectively. We utilized colloid filtration theory to elucidate potential microbial removal mechanisms. In biochar-amended biofilters, electrostatic interactions between the virus and collector surfaces likely controlled bacteriophage removal whereas the electrostatic interactions likely played a minor role in bacterial removal. Bacterial removal in biochar-augmented biofilters was likely controlled by straining and hydrophobic interactions. The findings of this study inform the design of geomedia-amended biofilters to reduce stormwater-derived microbial contamination in receiving waters.

Solar energy is readily available in most climates and can be used for water purification. However, solar disinfection of drinking water mostly relies on ultraviolet light, which represents only 4% of the total solar energy, and this leads to a slow treatment speed. Therefore, the development of new materials that can harvest visible light for water disinfection, and so speed up solar water purification, is highly desirable. Here we show that few-layered vertically aligned MoS2(FLV-MoS2) films can be used to harvest the whole spectrum of visible light (∼50% of solar energy) and achieve highly efficient water disinfection. The bandgap of MoS2was increased from 1.3 to 1.55 eV by decreasing the domain size, which allowed the FLV-MoS2to generate reactive oxygen species (ROS) for bacterial inactivation in the water. The FLV-MoS2showed a ∼15 times better log inactivation efficiency of the indicator bacteria compared with that of bulk MoS2, and a much faster inactivation of bacteria under both visible light and sunlight illumination compared with the widely used TiO2. Moreover, by using a 5 nm copper film on top of the FLV-MoS2as a catalyst to facilitate electron–hole pair separation and promote the generation of ROS, the disinfection rate was increased a further sixfold. With our approach, we achieved water disinfection of >99.999% inactivation of bacteria in 20 min with a small amount of material (1.6 mg l–1) under simulated visible light.

Human norovirus (HuNoV) is an important cause of acute gastroenteritis and can be transmitted by water exposures, but its persistence in water is not well understood. Loss of HuNoV infectivity in surface water was compared with persistence of intact HuNoV capsids and genome segments. Surface water from a freshwater creek was filter-sterilized, inoculated with HuNoV (GII.4) purified from stool, and incubated at 15 or 20 °C. We measured HuNoV infectivity via the human intestinal enteroid system and HuNoV persistence via reverse transcription-quantitative polymerase chain reaction assays without (genome segment persistence) or with (intact viral capsid persistence) enzymatic pretreatment to digest naked RNA. For infectious HuNoV, results ranged from no significant decay to a decay rate constant (“k”) of 2.2 day–1. In one creek water sample, genome damage was likely a dominant inactivation mechanism. In other samples from the same creek, loss of HuNoV infectivity could not be attributed to genome damage or capsid cleavage. The range in kand the difference in the inactivation mechanism observed in water from the same site could not be explained, but variable constituents in the environmental matrix could have contributed. Thus, a single kmay be insufficient for modeling virus inactivation in surface waters.

Influenza A virus (IAV) causes significant morbidity and mortality in the United States and has pandemic potential. Identifying IAV epidemic patterns is essential to inform the timing of vaccinations and nonpharmaceutical interventions. In a prospective, longitudinal study design, we measured IAV RNA in wastewater settled solids at 163 wastewater treatment plants across 33 states to characterize the 2022–2023 influenza season at the state, health and human services (HHS) regional, and national scales. Influenza season onset, offset, duration, peak, and intensity using IAV RNA in wastewater were compared with those determined using laboratory-confirmed influenza hospitalization rates and outpatient visits for influenza-like illness (ILI). The onset for HHS regions as determined by IAV RNA in wastewater roughly corresponded with those determined using ILI when the annual geometric mean of IAV RNA concentration was used as a baseline (i.e., the threshold that triggers onset), although offsets between the two differed. IAV RNA in wastewater provided early warning of onset, compared to the ILI estimate, when the baseline was set at twice the limit of IAV RNA detection in wastewater. Peak when determined by IAV RNA in wastewater generally preceded peak determined by IAV hospitalization rate by 2 weeks or less. IAV RNA in wastewater settled solids is an IAV-specific indicator that can be used to augment clinical surveillance for seasonal influenza epidemic timing and intensity.

We evaluated the magnitude and composition (in terms of salinity, 223Ra and 224Ra activity, and nutrient concentrations) of submarine groundwater discharge (SGD) fluxes at 11 sites on the Kona coast of Hawaii. Discharging groundwater was typically brackish to saline and had high Ra activity relative to ocean water and fresher, inland groundwater. Brackish SGD fluxes, estimated using a mass‐balance approach based on excess coastal ocean 224Ra activity, ranged from 3 to 1300 L m−1of coastline min−1. Fluxes of the freshwater component of SGD, calculated based on salinity, ranged from 2 to 310 L m−1min−1. Nutrient fluxes into coastal waters from SGD varied by up to three orders of magnitude among sites. Nitrate + nitrite (N + N), phosphate, and silica concentrations showed strong, inverse linear correlations with salinity in coastal seawater and groundwater. These correlations were consistent with previous work that documented conservative mixing between fresh, high‐nutrient groundwater and saline, low‐nutrient seawater at a few coastal ocean sites. We extend this conservative relationship to more coastal ocean sites and to groundwater in the coastal aquifer. N + N concentrations in the fresh component of discharging groundwater were higher at sites near golf courses and those with a greater percentage of bare land within a 5‐km radius, and silica concentrations in the fresh component of discharging groundwater were higher at sites with more bare land and lower population densities. However, neither urbanization nor agriculture was significantly correlated with groundwater nutrient concentrations on this relatively undeveloped coast.

Environmental Context.Pathogenic bacteria and viruses are sometimes detected in coastal waters, high levels of which correlate with occurrence of acute gastrointestinal illness in recreational beach users. The source of the bacterial and viral contamination to the beach is not always easy to decipher, and therefore efforts to prevent these occurrences are limited by lack of full understanding of their cause. Abstract.Beach water contamination by pathogenic agents is monitored by Fecal Indicator Bacteria (FIB) levels. A source of these agents may be submarine groundwater discharge. At Huntington Beach, California high FIB levels in the surf zone are shown to be associated with high 224Ra and 223Ra activities, indicators of groundwater discharge.