Table 1 Simulation result of SEIR model for Case A.

From: Exploring dependence of COVID-19 on environmental factors and spread prediction in India

Date

S[t + 1]

E[t + 1]

I[t + 1]

R[t + 1]

31-Jan

7826

31,030

102

0

08-Feb

4781

15,836

206

0

16-Feb

12,807

31,694

510

0

24-Feb

13,125

40,999

765

0

27-Feb

18,014

65,276

612

0

03-Mar

10,079

32,226

514

0

10-Mar

13,885

42,761

703

4

17-Mar

133,124

478,921

1467

20

24-Mar

105,141

318,371

2497

71

31-Mar

112,752

158,692

2795

208

07-Apr

116,052

76,902

4723

774

14-Apr

114,883

59,122

10,513

1105

21-Apr

91,901

46,800

12,814

1182

28-Apr

88,217

39,422

16,818

1565

05-May

84,676

25,541

20,943

2003

12-May

75,347

20,454

27,447

2546

19-May

60,261

15,649

16,938

3552

26-May

48,192

10,894

12,941

4488

02-Jun

38,539

4895

11,591

5358

09-Jun

35,441

4510

10,791

6168

16-Jun

21,256

4313

10,050

6921

  1. The SEIR model is run by considering full lockdown for Case A in which the peak in number of infected people {I[t]} appears to be on 12 May 2020, followed by drop in number of cases which reduces to 10050 by mid of June. Similarly, number of exposed persons {E[t]}, susceptible people {S[t]} also seem to follow a downward trend after a certain time. While number of Removed persons, which include removal by treatment or death, seems to be increasing given the lag in infection and treatment.