A.2. Influenza. Chowell et al. [51] used four methods to calculate R 0 using data from the 1918 influenza pandemic in California. The four methods involved (1) an early exponential growth rate, (2) In particular, uncertainty during the early part of the epidemic leads to a wide range of estimates for R 0 (0.5-3.5, 95% confidence interval), but uncertainty decreases with more observations. Wallinga and Lipsitch [52] investigated how generation intervals shape the relationship between growth rates and reproductive numbers. For new emerging infectious diseases, the observed exponential epidemic growth rate r can indirectly infer the value of the reproductive number. The existence of a few different equations that relate the reproductive number to the growth rate makes such inference ambiguous. It is unclear which of these equations might apply to new infection. The authors showed that these different equations differ only with respect to their assumed shape of the generation-interval distribution. They found that the shape of the generation-interval distribution determines which equation is appropriate for inferring the reproductive number from the observed growth rate. By assuming all generation intervals to be equal to the mean, they obtained an upper bound on the range of possible values that the reproductive number may attain for a given growth rate. They also showed that it is possible to obtain an empirical estimate of the reproductive number by taking the generation-interval distribution equal to the observed distribution.