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.

Urban sanitation infrastructure is inadequate in many low-income countries, leading to the presence of highly concentrated, uncontained fecal waste streams in densely populated areas. Combined with mechanisms of aerosolization, airborne transport of enteric microbes and their genetic material is possible in such settings but remains poorly characterized. We detected and quantified enteric pathogen-associated gene targets in aerosol samples near open wastewater canals (OWCs) or impacted (receiving sewage or wastewater) surface waters and control sites in La Paz, Bolivia; Kanpur, India; and Atlanta, USA, via multiplex reverse-transcription qPCR (37 targets) and ddPCR (13 targets). We detected a wide range of enteric targets, some not previously reported in extramural urban aerosols, with more frequent detections of all enteric targets at higher densities in La Paz and Kanpur near OWCs. We report density estimates ranging up to 4.7 × 102 gc per mair 3 across all targets including heat-stable enterotoxigenic Escherichia coli, Campylobacter jejuni, enteroinvasive E. coli/Shigella spp., Salmonella spp., norovirus, and Cryptosporidium spp. Estimated 25, 76, and 0% of samples containing positive pathogen detects were accompanied by culturable E. coli in La Paz, Kanpur, and Atlanta, respectively, suggesting potential for viability of enteric microbes at the point of sampling. Airborne transmission of enteric pathogens merits further investigation in cities with poor sanitation.

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 transcriptionquantitative 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 k and 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 k may be insufficient for modeling virus inactivation in surface waters.

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The Sustainable Development Goals require that 100 mL water samples contain no culturable E. coli to classify a water supply as "safely managed" from a microbial perspective. But small volume sampling is often insufficient for detecting microbial risks. We used culture-based measures of total coliforms and E. coli along with dead-end ultrafiltration (DEUF) and droplet digital PCR (ddPCR) to assess the microbial water quality of an urban water supply in Jaipur, India. Despite the absence of culturable E. coli in 90% of the 100 mL grab samples (n = 20) during the 10-day sampling period, we detected genes associated with protozoan and bacterial pathogens (Giardia, Cryptosporidium, and enterotoxigenic E. coli) in 3 DEUF samples of groundwater (n = 9; volume 59 to 122.4 liters). Of the three groundwater samples positive for waterborne pathogens, two were associated with 100 mL grab samples that were negative for culturable E. coli. Methods with improved analytical sensitivity, such as DEUF and ddPCR, can detect evidence of pathogens in drinking water supplies and supplement conventional culture-based methods to better inform pathogenspecific risk assessment and management.