@article{oai:miyazaki-u.repo.nii.ac.jp:00006423,
 author = {古井田, 健太郎 and 小酒井, 雄也 and 高塚, 佳代子 and Takatsuka, Kayoko and Okazaki, Naonobu and 岡崎, 直宣 and Yamaba, Hisaaki and 山場, 久昭 and Aburada, Kentaro and 油田, 健太郎 and Koida, Kentaro and Kozakai, Yuya},
 journal = {宮崎大学工学部紀要, Memoirs of Faculty of Engineering, University of Miyazaki},
 month = {Sep},
 note = {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.},
 pages = {143--147},
 title = {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—},
 volume = {50},
 year = {2021},
 yomi = {コイダ, ケンタロウ and コザカイ, ユウナ and タカツカ, カヨコ and オカザキ, ナオノブ and ヤマバ, ヒサアキ and アブラダ, ケンタロウ}
}