A different choice of serial interval distribution would affect the estimated time varying Rš‘’š‘“š‘“. This sensitivity is explored in detail in Flaxman et al., 2020, though we provide a brief description of the impact here. For the same daily case data, a longer average serial interval would correspond to an increased estimate of Rš‘’š‘“š‘“ when Rš‘’š‘“š‘“>1, and a decreased estimate when Rš‘’š‘“š‘“<1. This effect can be understood intuitively by considering the epidemic dynamics in these two situations. When Rš‘’š‘“š‘“>1 , daily case counts are increasing on average. The weighted average case counts (weighted by the serial interval distribution), decrease as the mean of the serial interval increases (i.e., as the support is shifted to older/lower daily case data). In order to generate the same number of observed cases in the present, Rš‘’š‘“š‘“ must increase. A similar observation can be made for Rš‘’š‘“š‘“<1.