A practical generation interval-based approach to inferring the strength of epidemics from their speed

Sang Woo Park; David Champredon; Joshua S. Weitz; Jonathan Dushoff

2 . CC-BY 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It Figure S1 : We perform the same analysis as we did in Sec. 4.1 assuming gamma distributed incubation and infectious periods. We find that the gamma approximated speed-strength relationship matches the true relationship almost perfectly in this case. Once again, we adjust the standard deviation of the incubation period to match the reported coefficient of variation in serial interval distributions. Rest of the parameters and points as in Fig. 3 3 . CC-BY 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/312397 doi: bioRxiv preprint Figure S2 : Approximating generation-interval distributions with a normal distribution has two problems. First, the distribution extends to negative values, which are biologically impossible. Second, as a consequence, the normal approximation predicts a saturating and eventually a decreasing r−R relationship for large r. Parameters and points as in Fig. 3 .