Anchoring the mean generation time in the SEIR to mitigate biases in ℜ0 estimates due to uncertainty in the distribution of the epidemiological delays

The basic reproduction number,<0, is of paramount importancein the study of infectious disease dynamics. Primarily,<0servesas an indicator of the transmission potential of an emerginginfectious disease and the effort required to control theinvading pathogen. However, its estimates from compartmentalmodels are strongly conditioned by assumptions in the modelstructure, such as the distributions of the latent and infectiousperiods (epidemiological delays). To further complicate matters,models with dissimilar delay structures produce equivalentincidence dynamics. Following a simulation study, we revealthat the nature of such equivalency stems from a linearrelationship between<0and the mean generation time, alongwith adjustments to other parameters in the model. Leveragingthis knowledge, we propose and successfully test an alternativeparametrization of the SEIR model that produces accurate