Human exposure to pathogenic viruses in environmental waters results in a significant global disease burden. Current microbial water quality monitoring approaches, mainly based on fecal indicator bacteria, insufficiently capture human health impacts posed by pathogenic viruses in water. The emergence of the 'microbiome era' and high-throughput metagenome sequencing has led to the discovery of novel human-associated viruses, including both pathogenic and commensal viruses in the human microbiome. The discovery of novel human-associated viruses is often followed by their detection in wastewater, highlighting the great diversity of human-associated viruses potentially present in the water environment. Novel human-associated viruses provide a rich reservoir to develop viral water quality management tools with diverse applications, such as regulating wastewater reuse and monitoring agricultural and recreational waters. Here, we review the pathway from viral discovery to water quality monitoring tool, and highlight select human-associated viruses identified by metagenomics and subsequently detected in the water environment (namely Bocavirus, Cosavirus, CrAssphage, Klassevirus, and Pepper Mild Mottle Virus). We also discuss research needs to enable the application of recently discovered human-associated viruses in water quality monitoring, including investigating the geographic distribution, environmental fate, and viability of potential indicator viruses. Examples suggest that recently discovered human pathogens are likely to be less abundant in sewage, while other human-associated viruses (e.g., bacteriophages or viruses from food) are more abundant but less human-specific. The improved resolution of human-associated viral diversity enabled by metagenomic tools provides a significant opportunity for improved viral water quality management tools.

A portion of those infected with SARS-CoV-2 shed the virus and its genetic material in respiratory fluids, saliva, urine, and stool, thus giving the potential to monitor for infections via wastewater. Wastewater surveillance efforts to date have largely assumed that stool shedding has been the primary source of SARS-CoV-2 RNA signal; however, there are increasing questions about the possible contribution of other shedding routes, with implications for wastewater surveillance design and feasibility. In this study we used clinical SARS-CoV-2 RNA shedding data and a Monte Carlo framework to assess the relative contribution of various shedding routes on SARS-CoV-2 RNA loads in wastewater. Stool shedding dominated total SARS-CoV-2 RNA load for community-level surveillance, with mean contributions more than two orders of magnitude greater than other shedding routes. However, RNA loads were more nuanced when considering building-level monitoring efforts designed to identify a single infected individual, where any shedding route could plausibly contribute a detectable signal. The greatest source of model variability was viral load in excreta, suggesting that future modeling efforts may be improved by incorporating specific modeling scenarios with precise SARS-CoV-2 shedding data, and beyond that wastewater surveillance must continue to account for large variability during data analysis and reporting. Importantly, the findings imply that wastewater surveillance at finer spatial scales is not entirely dependent on shedding via feces for sensitive detection of infections thus enlarging the potential use cases of wastewater as a non-intrusive surveillance methodology.

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Fecal indicator bacteria currently employed for microbial water quality management are poor representatives of viruses. Viral water quality indicators have recently been proposed based on the human gut bacteriophage crAssphage and the food virus pepper mild mottle virus (PMMoV) due to their high abundance in sewage and association to human waste. Here, we develop a model relating crAssphage and PMMoV abundance to the risk of swimmer illness in a recreational water contaminated with fresh, untreated domestic sewage. This model, entitled QMRAswim, is available via a Web-based user interface and is generalizable to any indicator or pathogen. The majority of predicted illnesses from exposure to untreated domestic sewagecontaminated water were attributable to viruses, primarily norovirus. The mean crAssphage and PMMoV concentrations correlating with 30 illnesses per 1000 bathers were 4648 GC/100 mL and 5054 GC/100 mL, respectively, approximately 50 times their standard detection limit. This study reaffirms the importance of monitoring viral water quality to adequately protect public health, suggests the high potential of both crAssphage and PMMoV for this application, and establishes a basis to relate viral indicator abundance with probability of illness due to viral pathogens.

Environments that receive fecal pollution are reservoirs of antibiotic resistance. Recent metagenomic observations suggest that the fecal pollution indicator crAssphage correlates with the occurrence of antibiotic resistance genes (ARGs) in the environment. Expanding the utility of crAssphage to represent the environmental occurrence of ARGs would potentially facilitate ARG management in environments contaminated with fecal pollution. In this study, we analyzed a suite of molecular indicators for ARGs and crAssphage over a 30 day sampling period in an urban stream that receives combined sewer overflows. The sampled stream showed high levels of ARGs and crAssphage with statistically significantly elevated levels during wet weather events. The observed correlation between crAssphage and ARG molecular detection was high when all were measured using digital droplet polymerase chain reaction (PCR). Quantitative PCR and digital droplet PCR quantifications of crAssphage showed only moderate agreement, emphasizing the importance of detection technology when making quantitative comparisons. Overall, this study demonstrates the potential of a crAssphage fecal indicator to correlate with ARG occurrence when employing a "toolbox" approach to fecal pollution management.

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Candida auris is an opportunistic fungal pathogen and an emerging global public health threat, given its high mortality among infected individuals, antifungal resistance, and persistence in healthcare environments. This study explored the applicability of wastewater surveillance for C. auris in a metropolitan area with reported outbreaks across multiple healthcare facilities. Influent or primary effluent samples were collected over 10 weeks from seven sewersheds in Southern Nevada. Pelleted solids were analyzed using an adapted quantitative polymerase chain reaction (qPCR) assay targeting the ITS2 region of the C. auris genome. Positive detection was observed in 72 of 91 samples (79%), with higher detection frequencies in sewersheds serving healthcare facilities involved in the outbreak (94 vs 20% sample positivity). Influent wastewater concentrations ranged from 2.8 to 5.7 log 10 gene copies per liter (gc/L), and primary clarification achieved an average log reduction value (LRV) of 1.24 ± 0.34. Presumptive negative surface water and wastewater controls were non-detect. These results demonstrate that wastewater surveillance may assist in tracking the spread of C. auris and serve as an early warning tool for public health action. These findings provide the foundation for future application of wastewater-based epidemiology (WBE) to community-or facility-level surveillance of C. auris and other high consequence, healthcare-associated infectious agents.

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