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Aims: This study investigates enteric viruses in wastewater during an outbreak of acute hepatitis caused by hepatitis A virus (HAV) in a large metropolitan area. Emphasis is given to caliciviruses and HAV. Methods and Results: Metagenomic analysis was performed to characterize enteric viruses excreted by the population of Detroit MI, during a hepatitis A outbreak that occurred in 2017 and 2018. Additionally, HAV, norovirus GII, and sapovirus were quantified, using qPCR, in 54 untreated wastewater samples collected over the course of 4 months. Correlation analysis was performed to identify associations between the number of disease cases and HAV concentrations in wastewater. HAV obtained the highest relative abundance among other enteric viruses detected in wastewater metagenomes. Metagenomic analysis also detected several other enteric viruses including astrovirus, enterovirus and hepatitis E virus. Average sapovirus concentrations of 1Á36 9 10 6 gc l À1 were significantly greater than norovirus GII concentrations (2Á94 9 10 4 gc l À1 ). Additionally, norovirus GI and GII along with sapovirus GI.1 were detected using metagenomics. HAV loads in wastewater were significantly correlated with the number of disease cases reported 1 week after wastewater sampling. Conclusions: Surveying untreated wastewater is a promising method for detecting early signs of hepatitis A outbreaks and for routine environmental monitoring of enteric viruses circulating in the environment. Significance and Impact of the Study: Authors demonstrate the usefulness of metagenomics for genogrouping and enteric viral surveillance.

Wastewater-based epidemiology has played a significant role in monitoring the COVID-19 pandemic, yet little is known about degradation of SARS-CoV-2 in sewer networks. Here, we used advanced sewershed modeling software...

There is no standard approach to interoperate the multiple SARS-CoV-2 wastewater surveillance data sets generated during the pandemic. We tested several data processing approaches on wastewater surveillance data sets generated from 19 sewersheds across four major metropolitan areas in the United States from May 2020 through October 2021. First, we explored the effect of different data processing techniques on the correlation between SARS-CoV-2 wastewater RNA load and clinical case counts and found that locally weighted smoothing (LOESS) smoothing applied to multivariate imputation by chain equations (MICE)-imputed wastewater viral load led to the strongest correlations in 16 out of 19 sewersheds (84%). Next, we calculated the rate of change (RC) in wastewater viral load and in clinical cases and found that imputing missing viral load data on a 28-day window produced the strongest correlation (Spearman's ρ = 0.63). Furthermore, we determined an average sensitivity threshold of 2.4 new COVID-19 cases per day resulted in a significant RC in wastewater, but sensitivity varied with the laboratory method used. Our retrospective analysis using RC highlighted certain methodological insights, reduced site-specific impacts, and estimated a wastewater sensitivity threshold�supporting the use of relative, rather than absolute, measures of SARS-CoV-2 wastewater data for more interoperable data sets.

Viruses of concern for quantitative wastewater monitoring are usually selected as a result of an outbreak and subsequent detection in wastewater. However, targeted metagenomics could proactively identify viruses of concern when used as an initial screening tool. To evaluate the utility of targeted metagenomics for wastewater screening, we used ViroCap, a panel of probes designed to target all known vertebrate viruses. Untreated wastewater was collected from wastewater treatment plants (WWTPs) and building-level manholes associated with vulnerable populations in Houston, TX. We evaluated differences in vertebrate virus detection between WWTP and building-level samples, classified human viruses in wastewater, and performed phylogenetic analysis on astrovirus sequencing reads to evaluate targeted metagenomics for subspecies level classification. Vertebrate viruses varied widely across building-level samples. Rarely detected and abundant viruses were identified in WWTP and building-level samples, including enteric, respiratory, and bloodborne viruses. Furthermore, full length genomes were assembled from astrovirus reads and two human astrovirus serotypes were classified in wastewater samples. This study demonstrates the utility of targeted metagenomics as an initial screening step for public health surveillance.