Table 2.

Fitting results on the relation between daily increase rate and cumulative cases using the nonlinear Eq. 4

Countries	Cumulative cases				Time (days)
	a	b	c	r2	a	b	c	r2
China	0.52	− 0.0223	0.2792	0.88 (+ 13%)	0.5263	− 0.0921	0.4786	0.83 (+ 9%)
R. Korea	912.2	− 911.0	0.0002	0.94 (+ 20%)	0.7173	− 0.3019	0.2529	0.87 (+ 45%)
Italy	809.1	− 808.4	0.0001	0.82 (+ 44%)	0.5964	− 0.1969	0.2809	0.87 (+ 18%)
Spain	0.36	− 0.0035	0.3818	0.72 (+ 13%)	0.3368	− 0.0030	1.3051	0.70 (+ 1%)
Germany	0.30	− 0.0014	0.4537	0.40 (+ 7%)	0.2895	− 0.0017	1.3921	0.38 (+ 2%)
France	308.4	− 307.8	0.0002	0.64 (+ 46%)	0.6179	− 0.2482	0.2189	0.70 (+ 20%)
Iran	1657.5	− 1656.5	0.0001	0.86 (+ 116%)	0.6108	− 0.1982	0.3035	0.81 (+ 34%)

a, b and c are the model coefficients defined in Eq. 4. r² represents goodness of the fit. The percentage after r² was the increased percentage of variance explained by the nonlinear model than those using linear model (Table 1)