The limitations of testing and reporting for SARS-CoV-2 have led to rapid advancements in the field of wastewater-based surveillance. While wastewater may offer reduced sampling biases compared to direct testing and disease reporting, the contributions that dispersed populations throughout the sewershed make to wastewater influent samples are not well characterized. In this work, we leverage temporally resolved concentrations of human fecal marker concentrations (crAssphage crAv056), flow, and physico-chemical data measured at 7 wastewater treatment plants in southern Ohio to characterize contributions from spatially distributed populations. We model the sum of exponentially decaying diluted crAssphage contributions from U.S. census populations using a maximum likelihood approach to statistically estimate a parameter, α90 𝛼90 , representing a travel time influence range or the estimated travel time at which we would expect to see a 90% reduction in concentrations from the sewershed due to degradation, decay and dilution processes. Lastly, we explore models where α90 𝛼90 may be modified by physico-chemical factors or zoning coverage (i.e., residential, commercial, and industry). Our preliminary estimates of α90 𝛼90 suggests that populations nearer versus farther from wastewater treatment plants contribute more highly to the detected concentrations of crAssphage. This implies that sewershed populations are not equally represented in composite influent samples. Furthermore, we find that the α90 𝛼90 decreases as a function of temperature or seasonal effects, providing insight into seasonal variability. Differences in α90 𝛼90 across different markers (e.g., N2 for SARS-CoV-2 and crAv056) would imply that the markers capture different populations contributing to wastewater treatment plant influent. Differences in α90 𝛼90 present one explanation for why normalizing by fecal indicators does not universally help to relate SARS-CoV-2 cases to wastewater data, warranting further investigation of α90 𝛼90 estimates across different markers. Alternatively, a stable marker like crAssphage may also be used to inform future models of more temporally variable molecular targets, such as SARS-CoV-2.
Click here to watch recorded presentation on YouTube.