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Table 3 SIR parameters (β∗, μ∗), the initial value \({I}_0^{\ast }\), and the shift time point J∗

From: Socio-economic analysis of short-term trends of COVID-19: modeling and data analytics

Country

β*

μ*

R0

I0*

RGFA iterat.a

J*b

PWP iterat.c

‘China’

0,042

2,09E-05

2009,569

4

10

100

75

‘Morocco’

0,0962

6,19E-04

155,412

5

11

33

8

‘Algeria’

0,0974

8,38E-04

116,229

5

13

35

10

‘Japan’

0,0721

8,14E-04

88,575

2

8

84

59

‘Indonesia’

0,0272

3,32E-04

81,928

63

17

111

86

‘India’

0,0466

6,81E-04

68,429

345

9

71

46

‘Costa Rica’

0,0548

1,32E-03

41,515

6

13

33

8

‘Poland’

0,0905

2,39E-03

37,866

26

12

33

8

‘Chile’

0,1404

3,75E-03

37,440

3

10

35

10

‘Ukraine’

0,0741

2,17E-03

34,147

27

11

42

17

‘Slovakia’

0,0477

1,86E-03

25,645

7

14

47

22

‘Egypt’

0,041

1,70E-03

24,118

25

10

105

80

‘New Zealand’

0,1378

5,75E-03

23,965

3

11

27

2

‘Pakistan’

0,0419

2,01E-03

20,846

60

9

113

88

‘Greece’

0,0455

2,22E-03

20,495

14

17

45

20

‘Australia’

0,0923

4,99E-03

18,492

3

11

67

8

‘Bulgaria’

0,0302

1,67E-03

18,084

8

12

67

42

‘Croatia’

0,0978

5,48E-03

17,847

3

6

36

11

‘Tunisia’

0,0617

4,46E-03

13,834

2

10

113

88

‘Colombia’

0,0392

3,44E-03

11,395

48

15

103

78

‘Turkey’

0,107

1,12E-02

9,554

270

15

27

2

‘Romania’

0,0486

5,19E-03

9,364

37

11

55

30

‘Denmark’

0,0699

8,08E-03

8,651

27

18

39

14

‘Norway’

0,0852

9,92E-03

8,589

31

11

29

4

‘Netherlands’

0,1171

1,51E-02

7,755

45

17

29

4

‘Malta’

0,0635

8,30E-03

7,651

3

16

36

11

‘Serbia’

0,0824

1,09E-02

7,560

22

17

38

13

‘Philippines’

0,027

3,78E-03

7,143

22

16

204

179

‘Sweden’

0,0698

1,03E-02

6,777

34

10

44

19

‘United Kingdom’

0,0996

1,67E-02

5,964

70

13

45

20

‘Israel’

0,1164

2,10E-02

5,543

15

16

35

10

‘Russia’

0,0671

1,23E-02

5,455

18

12

98

73

‘Portugal’

0,1183

2,32E-02

5,099

30

7

30

5

‘Italy’

0,106

2,27E-02

4,670

78

13

43

18

‘Canada’

0,0505

1,09E-02

4,633

127

12

59

34

‘Belgium’

0,1385

3,08E-02

4,497

33

16

29

4

‘Germany’

0,0849

1,96E-02

4,332

31

8

66

41

‘Argentina’

0,0363

8,62E-03

4,211

35

10

132

107

‘USA’

0,0974

2,78E-02

3,504

542

8

30

5

‘Finland’

0,0224

6,42E-03

3,489

26

11

79

54

‘Switzerland’

0,1375

4,06E-02

3,387

41

16

26

1

‘Austria’

0,0932

2,80E-02

3,329

40

7

35

10

‘South Africa’

0,0463

1,56E-02

2,968

38

11

127

102

‘Sri Lanka’

0,0157

5,64E-03

2,784

6

9

314

289

‘Albania’

0,0184

7,01E-03

2,625

7

8

178

153

‘Estonia’

0,0224

9,80E-03

2,286

11

9

59

34

‘Uruguay’

0,0378

1,72E-02

2,198

4

7

146

121

‘Kazakhstan’

0,0474

2,26E-02

2,097

11

13

116

91

‘France’

0,0681

4,43E-02

1,537

344

17

55

30

‘Georgia’

0,0623

4,16E-02

1,498

7

12

92

67

‘Brazil’

0,028

3,06E-02

0,915

1285

20

133

108

‘Panama’

0,022

3,86E-02

0,570

65

11

141

116

‘Czechia’

0,0421

2,01E-01

0,209

14

8

171

146

  1. aNumber of iteration of RGFA computed at the convergence of the algorithm
  2. bThe initial value of J∗ was set to 25 days
  3. cEqual to the number of loops of PWP procedure