Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India

Abstract

Objectives: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building health-care capacity.

Methods: This effect is studied using the Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. We estimate the infection rate using a least square method with Poisson noise and calculate the reproduction number.

Results: The infection rate is estimated to be 0.270 and the reproduction number to be 2.70. The approximate peak of the epidemic will be August 9, 2020. A 25% drop in infection rate will delay the peak by 11 d for a 1-mo intervention period. The total infected individuals in India will be 9% of the total population.

Conclusions: The predictions are sensitive to changes in the behavior of people and their practice of social distancing.

Keywords: COVID-19; India; SEIR compartmental model; infection rate; intervention; peak prediction.

FIGURE 1

Daily Increase in Confirmed Cases of COVID-19 in India. Note: Day 0 is January 25, 2020, and day 92 is April 26, 2020. Data are taken from Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU).⁴

FIGURE 2

Cumulative Confirmed Cases of COVID-19 in India. Note: Day 0 is January 25, 2020, and day 92 is April 26, 2020. Data are taken from Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU).⁴

FIGURE 3

Comparison of Daily Confirmed Cases and Y in India From t = 0 to t = 92.

FIGURE 4

Infected Individuals for Time t, 0 ≤ t ≤ 550 for p = 0.1.

FIGURE 5

Infected Individuals for Time t, 0 ≤ t ≤ 550 for p = 0.01.

FIGURE 6

Variation in Y (t) for Tme t, 0 ≤ t ≤ 550 With no Intervention, 1 mo of Intervention, and 6 mo of Intervention With Assumption of β ^j = 0.95 × β. (β = 0.270).

FIGURE 7

Variation in Y (t) for Time t, 0 ≤ t ≤ 550 With no Intervention, 1 mo of Intervention, and 6 mo of Intervention With Assumption of β ^j = 0.75 × β. (β = 0.270).

FIGURE 8

Variation in Y (t) for Time t, 0 ≤ t ≤ 550 With no Intervention, 1 mo of Intervention and 6 mo of Intervention With Assumption of β ^j = 0.50 × β. (β = 0.270).

FIGURE 9

Variation in Y (t) for Time t, 0 ≤ t ≤ 550 With 1 mo of Intervention and With Assumption of β ^j = 0.50 × β, β ^j = 0.75 × β, β ^j = 0.95 × β. (β = 0.270).

FIGURE 10

Variation in Y (t) for Time t, 0 ≤ t ≤ 550 With 6 mo of Intervention and With Assumption of β ^j = 0.50 × β, β ^j = 0.75 × β, β ^j = 0.95 × β. (β = 0.270).

FIGURE 11

Infected Individuals Requiring Hospitalization or Intensive Care and Health-Care Capacities in India.