Table 1.

Table of average values of the best-fit parameters and associated standard deviations computed from 30 independent runs of the stochastic differential evolution algorithm [3], as implemented in the Python-Scipy package. The line marked with an asterisk refers to a fit limited to the data up to February 19^th 2020. The best-fit values of the additional parameters fitted for the China outbreak were $I_0=430\pm 20,$$R_0=10\pm 10,$$D_0=15\pm 7$ (full range) and $I_0=999\pm 1,$$R_0=10\pm 10,$$D_0=17\pm 7$ (full range).

Country	r [days${}^{-1}$]		a [days${}^{-1}$]		d [days${}^{-1}$]		S0
Italy	$7.90\times {10}^{-6}\pm 3\times {10}^{-8}$		$2.13\times {10}^{-2}\pm 2\times {10}^{-4}$		$1.63\times {10}^{-2}\pm 2\times {10}^{-4}$		4.13 × 104 ± 2 × 102
China	$3.95\times {10}^{-6}\pm 4\times {10}^{-8}$		$3.53\times {10}^{-2}\pm 1\times {10}^{-4}$		$3.1\times {10}^{-3}\pm 2\times {10}^{-4}$		8.33 × 104 ± 2 × 102
China*	$3.33\times {10}^{-6}\pm 2\times {10}^{-8}$		$1.80\times {10}^{-2}\pm 2\times {10}^{-4}$		$3.0\times {10}^{-3}\pm 2\times {10}^{-4}$		7.92 × 104 ± 4 × 102