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.
【저자키워드】 COVID-19, India, Intervention, infection rate, peak prediction, SEIR compartmental model, 【초록키워드】 coronavirus disease, social distancing, Reproduction number, compartmental model, infected individual, total population, Poisson, SEIR, the epidemic, health-care, involved, changes in, calculate, 【제목키워드】 prediction, Effect, peak, Total,