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KOBAYASHI GENYA
Department Undergraduate School , School of Commerce Position Professor |
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| Language | English |
| Publication Date | 2020 |
| Type | Academic Journal |
| Peer Review | Peer reviewed |
| Title | Predicting intervention effect for COVID-19 in Japan: state space modeling approach |
| Contribution Type | Co-authored (first author) |
| Journal | BioScience Trends |
| Journal Type | Another Country |
| Publisher | International Research and Cooperation Association for Bio & Socio-Sciences Advancement (IRCA-BSSA) |
| Volume, Issue, Page | 14(3),pp.174-181 |
| Author and coauthor | Genya Kobayashi, Shonosuke Sugasawa, Hiromasa Tamae, Takayuki Ozu |
| Details | Japan has observed a surge in the number of confirmed cases of the coronavirus disease (COVID-19) that has caused a serious impact on the society especially after the declaration of the state of emergency on April 7, 2020. This study analyzes the real time data from March 1 to April 22, 2020 by adopting a sophisticated statistical modeling based on the state space model combined with the well-known susceptible-infected-recovered (SIR) model. The model estimation and forecasting are conducted using the Bayesian methodology. The present study provides the parameter estimates of the unknown parameters that critically determine the epidemic process derived from the SIR model and prediction of the future transition of the infectious proportion including the size and timing of the epidemic peak with the prediction intervals that naturally accounts for the uncertainty. |
| DOI | 10.5582/bst.2020.03133 |
| ISSN | 1881-7815 |
| PermalinkURL | https://www.jstage.jst.go.jp/article/bst/advpub/0/advpub_2020.03133/_pdf |