Practical Applications and New Development of the Control Strategy of Infectious Diseases based on the Stochastic Approach
| Project/Area Number |
16K06416
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Control engineering/System engineering
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| Research Institution | Yamaguchi University |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | 感染症モデル / 確率システム / 安定性解析 / 最適制御 / 時間遅れ / リアプノフ指数 / ワクチン接種 / シミュレーション / 安定性 / 確率最大原理 / 平衡解 / 確率リヤプノフ定理 / リヤプノフ指数 / Disease-free平衡解 / シミュレーション解析 / 制御工学 / シミュレーション工学 / 応用数学 / 確率過程論 / 機械力学・制御 |
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| Outline of Final Research Achievements |
In this research, we have established the feasible control strategy for the infectious disease based on the stochastic system theory. First, we have formulated the infectious model as the simultaneous time delayed stochastic differential equations by considering the random fluctuation in the infection and recovery rates. Secondly, by using the stochastic Lyapunov theorem, we have shown the sufficient condition for the disease-free steady state to be stable. It follows from the stability condition that we are able to know the necessary vaccination rate to control the infectious disease spreading. Finally, by calculating the Lyapunov exponent, we have clarified that the random fluctuation in the recovery and the infection rates have played a role to stabilize the disease-free steady state.
Furthermore, we have developed the new infectious model, i.e., the stochastic age-structured model.
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| Academic Significance and Societal Importance of the Research Achievements |
学術的意義：以下の観点から感染症解析に対する工学的アプローチによる先駆的研究として意義がある．(1) 感染症モデルを確率システム理論に基づき構築したこと．(2) 感染症モデルに含まれる不規則外乱の影響を理論的に明らかにしたこと．(3) シミュレーションにより感染症抑制戦戦略の有効性を明らかにしたこと．
社会的意義：高度に医療技術が進歩した現代社会においても感染症の脅威は依然として存在しているが，本研究は感染症流行の抑制に必要なワクチン接種率の推定や感染症流行過程の予測などにも有効であり，本研究成果は安全かつ健全な社会構築に貢献するものである．
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Report
(4 results)
Research Products
(23 results)
