Table 1. Best-fit model estimates for key epidemiological parameters.

Parameter	10 January–23 January	24 Jan–2 Feb	3 Feb– 12 Feb	13 Feb–22 Feb	23 Feb–15 Mar
Transmission Rate βT (Reported)	0.05 (0.03,0.08)	0.02 (0.01,0.03)	0.02 (0.02,0.05)	0.02 (0.01,0.03)	0.01 (0.01,0.02)
Transmission Rate βNT (Unreported)	0.25 (0.24,0.25)	0.24 (0.23,0.24)	0.24 (0.23,0.28)	0.24 (0.23,0.26)	0.24 (0.23,0.24)
Mobility Probability	0.1 (0.09,0.12)	0.92 (0.9,0.94)	0.73 (0.41,0.91)	0.69 (0.25,0.9)	0.49 (0.06,0.92)
Latent Period	4.57 (4.48,4.65)	4.67 (4.57,4.74)	4.41 (2.46,4.7)	3.7 (2.32,4.66)	3.79 (3.03,4.41)
Testing Rate	0.11 (0.1,0.13)	0.24 (0.13,0.68)	0.86 (0.24,0.94)	0.92 (0.12,0.95)	0.94 (0.86,0.95)
Infection Period (Reported)	1.82 (1.43,2.24)	1.42 (1.14,2.3)	1.53 (1.13,2.44)	1.31 (1.1,2.05)	1.09 (1.06,1.55)
Infection Period (Unreported)	3.4 (3.27,3.68)	3.32 (3.2,3.63)	3.44 (3.22,4.03)	3.32 (3.2,3.6)	3.3 (3.22,3.76)
Relative testing rate (Wuhan)	0.01 (0.01,0.01)	0.01 (0,0.04)	0.07 (0.01,0.09)	0.53 (0.05,0.68)	0.83 (0.56,0.87)

Notes: This table shows best-fit model posterior estimates of the median and 95% confidence intervals for key epidemiological parameters derived from 200 simulation of the model. To simulate the sharp increase in cities in Hubei, we assume a testing rate of cities in Hubei equal to 1 on February 13, so the testing rate in Hubei in February 13 is not estimated.