Epidemiol Health.  2020;42:e2020028. 10.4178/epih.e2020028.

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

• Kanagarathinam K
• Sekar K

• KMID: 2504672
• DOI: http://doi.org/10.4178/epih.e2020028

Abstract

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 (R₀). This work is focused on predicting the COVID-19 outbreak in its early stage in India based on an estimation of R₀. 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 R₀ using the earlyR package. The maximum-likelihood approach was used to analyze the distribution of R₀ values, and the bootstrap strategy was applied for resampling to identify the most likely R₀ value. We estimated the median value of R₀ 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.

Keyword

Basic reproduction number, COVID-19, Forecasting, Statistical computing