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

摘要

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 (Rsub0/sub). This work is focused on predicting the COVID-19 outbreak in its early stage in India based on an estimation of Rsub0/sub. 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 Rsub0/sub using the earlyR package. The maximum-likelihood approach was used to analyze the distribution of Rsub0/sub values, and the bootstrap strategy was applied for resampling to identify the most likely Rsub0/sub value. We estimated the median value of Rsub0/sub 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.