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A novel coronavirus (SARS-CoV-2) emerged as a global threat in December 2019. As the epidemic progresses, disease modellers continue to focus 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 modelling approaches and resulting estimates of R 0 during the beginning of the outbreak vary widely, despite relying on similar data sources. Here, we present a 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, the mean generation interval and the generation-interval dispersion. We apply our framework to early estimates of R 0 for the SARS-CoV-2 outbreak, showing that many 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.