Abstract

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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