Fig. 1: Impact of shedding differences on wastewater-based incidence and Re estimates, and variant-relative selection advantage.
A Two variants (Delta, blue, and Omicron, red) are shed in different amounts. The incidence of SARS-CoV-2 and its variants in the population (barplots on the right) is quantified from clinical samples (top path) and from wastewater samples (bottom path) using PCR-based and NGS methods. The difference in shedding can lead to differences in incidence estimates. Created in BioRender. Dreifuss, D. (2025) https:// BioRender.com/5azzvou. B Simulated time series: the dominant strain (Delta, blue) has a stable \({R}_{e}\) of 0.6, and the incidence is steadily declining. A new variant (Omicron, red) with a selection advantage over Delta resulting in an \({R}_{e}\) of 2.2, is introduced and increases in absolute prevalence. We have assumed here that the new variant is shed 50% less, which decouples the historic relationship between community prevalence (solid line) and concentration in wastewater (dashed line), leading to underestimation of its incidence from wastewater-derived data. This in turn also leads to underestimating the total incidence of the virus (blue). C The differential shedding results in a time-delay of 2 days in the growth and decay curves of relative abundance of the variants, but does not alter the growth or decay rates. The estimates of the selection advantage of the variant are not affected. D The differential shedding results in a transient bias in the estimated \({R}_{e}\). The Re = 1.0 threshold is estimated to be crossed 2 days later than without undershedding. The variant-specific \({R}_{e}\) for both variants do not suffer any bias.
