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时间:2021-10-19 16:43:29 来源:3044am永利集团欢迎您 作者: 阅读:

报告题目Optimal control applied to mosquito-borne diseases: Malaria and WNV

报告人: 丁婉菂  教授

报告时间:20211030(周六) 10:0011:30

报告地点:腾讯会议:613 952 676

报告摘要We present some optimal control work on mosquito-borne diseases: Malaria and West Nile Virus. First, a malaria transmission model with SEIR (susceptible-exposed-infected-recovered) classes for the human population, SEI (susceptible-exposed-infected) classes for the wild mosquitoes and an additional class for sterile mosquitoes is formulated. We derive the basic reproduction number of the infection. We formulate an optimal control problem in which the goal is to minimize both the infected human populations and the cost to implement two control strategies: the release of sterile mosquitoes and the usage of insecticide-treated nets to reduce the malaria transmission. Adjoint equations are derived and the characterization of the optimal controls are established. Finally, we quantify the effectiveness of the two interventions aimed at limiting the spread of Malaria. A combination of both strategies leads to a more rapid elimination of the wild mosquito population that can suppress Malaria transmission.

Secondly, we consider a West-Nile Virus transmission model that describes the interaction between bird and mosquito populations (eggs, larvae, adults) and the dynamics for larvicide and adulticide, with impulse controls. We derive the basic reproduction number of the infection. We reformulate the impulse control problems as nonlinear optimization problems to derive adjoint equations and establish optimality conditions. We formulate three optimal control problems which seek to balance the cost of insecticide applications (both the timing and application level) with (1) the benefit of reducing the number of mosquitoes, (2) the benefit of reducing the disease burden, or (3) the benefit of preserving the healthy bird population. Numerical simulations are provided to illustrate the results of both models.
报告人简介: 丁婉菂,美国中田纳西州立大学数学科学系和计算与数据科学中心教授。主要研究领域是生物数学,计算生物学与最优控制。主要应用常微分方程,偏微分方程,差分方程,agent/individual-based modeling 和混合动力系统来研究人口动态,疾病建模和控制,自然资源管理,以及系统生物学。先后主持过2项美国国家自然科学基金项目以及若干其他基金项目,发表SCI文章20余篇。担任7Society for Mathematical Biology Digest 的编辑以及其他杂志编辑,为30余杂志审稿( SIAM Journal on Applied Mathematics,  Journal of Mathematical Analysis and Applications,  Optimal Control Applications and Methods, Journal of Theoretical Biology);分别担任过Phi Kappa Phi 中田纳西州立大学分会的秘书、副会长和会长。丁婉菂教授也是美国SIMIODE: Systemic Initiative for Modeling Investigations and Opportunities with Differential Equations的顾问董事会委员,以及技术,工程及数学(STEM)中心的董事成员。

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