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このアイテムのファイル:
| ファイル | 記述 | サイズ | フォーマット | |
|---|---|---|---|---|
| 2186-11.pdf | 7.14 MB | Adobe PDF | 見る/開く |
| タイトル: | COVID-19 in Japan: What could happen in the future? (Recent developments on inverse problems for partial differential equations and their applications) |
| 著者: | Shao, Nian Xuan, Yan Pan, Hanshuang Wang, Shufen Li, Weijia Yan, Yue Li, Xingjie Shen, Christopher Y. Chen, Xu Luo, Xinyue Chen, Yu Xu, Boxi Liu, Keji Zhong, Min Xu, Xiang Jiang, Yu Lu, Shuai Ding, Guanghong Cheng, Jin Chen, Wenbin |
| 発行日: | Jun-2021 |
| 出版者: | 京都大学数理解析研究所 |
| 誌名: | 数理解析研究所講究録 |
| 巻: | 2186 |
| 開始ページ: | 87 |
| 終了ページ: | 105 |
| 抄録: | COVID-19 has been impacting on the whole world critically and constantly Since December 2019. We have independently developed a novel statistical time delay dynamic model on the basis of the distribution models from CCDC. Based only on the numbers of confirmed cases in different regions in China, the model can clearly reveal that the containment of the epidemic highly depends on early and effective isolation. We apply the model on the epidemic in Japan and conclude that there could be a rapid outbreak in Japan if no effective quarantine measures are carried out immediately. |
| 記述: | This paper was finished in February, 2020 and posted in MedRxiv on Feb. 28th, 2020. |
| URI: | http://hdl.handle.net/2433/265585 |
| 関連リンク: | https://doi.org/10.1101/2020.02.21.20026070 |
| 出現コレクション: | 2186 偏微分方程式における逆問題とその応用のさらなる展開 |
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