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Estimation of the reproduction number and early prediction of the COVID-19 outbreak in India using a statistical computing approach
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Karthick Kanagarathinam, Kavaskar Sekar
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Epidemiol Health. 2020;42:e2020028. Published online May 9, 2020
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DOI: https://doi.org/10.4178/epih.e2020028
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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 (R<sub>0</sub>). This work is focused on predicting the COVID-19 outbreak in its early stage in India based on an estimation of R<sub>0</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 R<sub>0</sub> using the earlyR package. The maximum-likelihood approach was used to analyze the distribution of R<sub>0</sub> values, and the bootstrap strategy was applied for resampling to identify the most likely R<sub>0</sub> value. We estimated the median value of R<sub>0</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.
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