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Table 2 Fitting results on the relation between daily increase rate and cumulative cases using the nonlinear Eq. 4

From: Modeling analysis reveals the transmission trend of COVID-19 and control efficiency of human intervention

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%)

  1. 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)