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感染症拡大リスクの地理的分布の評価に関する研究 —新型コロナウィルス感染症の感染データの利用—
http://hdl.handle.net/10458/00010282
http://hdl.handle.net/10458/00010282fa122ed0-f9e7-45d6-be0d-8be084f22282
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
本文 (2.1 MB)
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| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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| 公開日 | 2021-11-02 | |||||
| タイトル | ||||||
| タイトル | 感染症拡大リスクの地理的分布の評価に関する研究 —新型コロナウィルス感染症の感染データの利用— | |||||
| 言語 | ja | |||||
| タイトル | ||||||
| タイトル | Study on Eavalulation of the Geographical Distribution of Infectious Disease Spreading Risk —Usage of Infection Data of Covid-19— | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Keeling model | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | COVID-19 | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Potential infection risk index | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | SIR model | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | departmental bulletin paper | |||||
| 著者 |
古井田, 健太郎
× 古井田, 健太郎× 小酒井, 雄也× 高塚, 佳代子× 岡崎, 直宣× 山場, 久昭× 油田, 健太郎× Koida, Kentaro× Kozakai, Yuya |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | As epidemic prevention management for new coronavirus infection (COVID-19) infection, it is necessary to indicate the area where the infection is currently susceptible. However, it is difficult to quantitatively show the geographical distribution of potential infection risk and infectious disease spread risk. There is a foot-and-mouth disease infection simulation model“Keeling model”as a method that enables macro risk analysis of the spatial transmission process. The Keeling model models the probability of foot-and-mouth disease infection on each farm during the period of infection, and its population parameter λ is highly versatile in quantifying the susceptibility of each farm based on the infection status of surrounding farms. It is an expression. Therefore, in this study, we devised a method to index the susceptibility to human infectious diseases for each unit region, referring to the concept of indexing by the population parameter λ of the Keeling model. He also applied the proposed method to COVID-19 infection data and demonstrated its validity. The method of calculating the potential infection risk index newly proposed in this indexing is a value calculated only from the location and human factors of the unit area without using any individual infection data. Therefore, similar utilization effects are expected in the future outbreak of new infectious diseases. In addition, methods based on infection data developed to improve the accuracy of the potential infection risk index can also be fully applied. There is expected. | |||||
| 言語 | en | |||||
| 書誌情報 |
ja : 宮崎大学工学部紀要 en : Memoirs of Faculty of Engineering, University of Miyazaki 巻 50, p. 143-147, 発行日 2021-09-28 |
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| 出版者 | ||||||
| 出版者 | 宮崎大学工学部 | |||||
| 言語 | ja | |||||
| 出版者 | ||||||
| 出版者 | Faculty of Engineering, University of Miyazaki | |||||
| 言語 | en | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 05404924 | |||||
| 書誌レコードID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AA00732558 | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
