2023 Fiscal Year Final Research Report
Mathematical analysis and epidemiological application of structured epidemic models
| Project/Area Number |
19K14594
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 12040:Applied mathematics and statistics-related
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| Research Institution | Kobe University |
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Principal Investigator |
Kuniya Toshikazu 神戸大学, システム情報学研究科, 准教授 (60713013)
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Keywords | 感染症 / 数理モデル / 基本再生産数 / 異質性 / 年齢構造 / 空間構造 / 流行予測 / 政策効果 |
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| Outline of Final Research Achievements |
In this study, we focused on structured epidemic models, which enable us to consider the heterogeneity such as age, sex, location of individuals in population. We performed mathematical analysis and obtained conditions for the occurrence of the outbreak and the recurrent epidemic waves. Moreover, we applied our models to the data of COVID-19 and gained insights on the epidemic prediction and intervention evaluation.
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| Free Research Field |
数理生物学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で得られた成果は，感染症の流行に伴う被害を効果的に減少させる観点から社会貢献に繋がると考えられる．また，数理モデルには普遍性があるため，COVID-19などの特定の感染症に限定されず，将来の様々な感染症の流行に対応可能な基礎理論の構築に，本研究は貢献したと言える．また，本研究で構築した異質性を含むモデルに関する理論は，現代社会に日々蓄積される大規模かつ多様なデータの有効活用に繋がる点で意義があると考えられる．
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