Estimation of the reproduction number and early prediction of the COVID-19 outbreak in India using a statistical computing approach

Coronavirus disease 2019 (COVID-19), which causes severe respiratory illness, has become a pandemic. The World Health Organization has declared it a public health crisis of international concern. We developed a susceptible, exposed, infected, recovered (SEIR) model for COVID-19 to show the importance of estimating the reproduction number (R(0)). This work is focused on predicting the COVID-19 outbreak in its early stage in India based on an estimation of R(0). The developed model will help policymakers to take active measures prior to the further spread of COVID-19. Data on daily newly infected cases in India from March 2, 2020 to April 2, 2020 were to estimate R(0) using the earlyR package. The maximum-likelihood approach was used to analyze the distribution of R(0) values, and the bootstrap strategy was applied for resampling to identify the most likely R(0) value. We estimated the median value of R(0) to be 1.471 (95% confidence interval [CI], 1.351 to 1.592) and predicted that the new case count may reach 39,382 (95% CI, 34,300 to 47,351) in 30 days.