Estimation of Reproduction Number (Ro) and Early Prediction of 2019 Novel Coronavirus Disease (COVID-19) Outbreak in India Using 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 importanc...
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Published in | Epidemiology and health pp. e2020028 - 5 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
한국역학회
09.05.2020
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Subjects | |
Online Access | Get full text |
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Summary: | 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. KCI Citation Count: 0 |
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Bibliography: | https://www.e-epih.org/upload/pdf/epih-42-e2020028.pdf |
ISSN: | 2092-7193 2092-7193 |
DOI: | 10.4178/epih.e2020028 |