Reconciling early-outbreak preliminary estimates of the basic reproductive number and its uncertainty: a new framework and applications to the novel coronavirus (2019-nCoV) outbreak

ABSTRACT

A novel coronavirus (SARS-CoV-2) has recently emerged as a global threat. As the epidemic progresses, many disease modelers have focused on estimating the basic reproductive number[R] 0- the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modeling approaches and resulting estimates of[R] 0 vary widely, despite relying on similar data sources. Here, we present a novel statistical framework for comparing and combining different estimates of[R] 0 across a wide range of models by decomposing the basic reproductive number into three key quantities the exponential growth rate r, the mean generation interval [Formula], and the generation-interval dispersion{kappa} . We then apply our framework to early estimates of[R] 0 for the SARS-CoV-2 outbreak. We show that many early[R] 0 estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of[R] 0, including the shape of the generation-interval distribution, in efforts to estimate[R] 0 at the outset of an epidemic.