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[论文解读] Bifurcation Thresholds and Optimal Control in Transmission Dynamics of Arboviral Diseases

Hamadjam Abboubakar, Jean Claude Kamgang|arXiv (Cornell University)|Jan 11, 2016
Mathematical and Theoretical Epidemiology and Ecology Models参考文献 104被引用 55
一句话总结

本研究构建了一个包含不完美疫苗和多种控制策略的虫媒病毒病传播分 compartment 模型,分析了分岔动力学并利用庞特里亚金最大值原理优化控制。研究结果表明,只有在存在疾病致死率的情况下,才会出现疾病消除需满足 R₀ < 1 且需额外控制的后向分岔现象;同时表明,联合使用疫苗接种、治疗、媒介控制和个人防护可显著降低传播成本。

ABSTRACT

In this paper, we derive and analyse a model for the control of arboviral diseases which takes into account an imperfect vaccine combined with some other mechanisms of control already studied in the literature. We begin by analyse the basic model without controls. We prove the existence of two disease-free equilibrium points and the possible existence of up to two endemic equilibrium points (where the disease persists in the population). We show the existence of a transcritical bifurcation and a possible saddle-node bifurcation and explicitly derive threshold conditions for both, including defining the basic reproduction number, R 0 , which determines whether the disease can persist in the population or not. The epidemiological consequence of saddle-node bifurcation (backward bifurcation) is that the classical requirement of having the reproduction number less than unity, while necessary, is no longer sufficient for disease elimination from the population. It is further shown that in the absence of disease--induced death, the model does not exhibit this phenomenon. We perform the sensitivity analysis to determine the model robustness to parameter values. That is to help us to know the parameters that are most influential in determining disease dynamics. The model is extended by reformulating the model as an optimal control problem, with the use of five time dependent controls, to assess the impact of vaccination combined with treatment, individual protection and vector control strategies (killing adult vectors, reduction of eggs and larvae). By using optimal control theory, we establish optimal conditions under which the disease can be eradicated and we examine the impact of a possible combined control tools on the disease transmission. The Pontryagin's maximum principle is used to characterize the optimal control. Numerical simulations, efficiency analysis and cost effectiveness analysis show that, vaccination combined with other control mechanisms, would reduce the spread of the disease appreciably, and this at low cost.

研究动机与目标

  • 研究不完美疫苗及多种控制策略对虫媒病毒病传播动力学的影响。
  • 确定后向分岔(鞍结分岔)发生的条件,该现象会复杂化疾病消除过程。
  • 评估疾病致死率在促成或阻止后向分岔中的作用。
  • 制定并求解最优控制问题,以最小化疾病负担与干预成本。
  • 通过数值模拟评估联合控制策略的成本效益与效率。

提出的方法

  • 为人类与蚊子种群构建一个确定性 SEIR-SVEI 分 compartment 模型,包含五种时间依赖的控制变量:疫苗接种、治疗、个人防护、成蚊灭杀与幼虫灭杀。
  • 分析无控制的基本模型,以识别无病平衡点(DFE)与地方性平衡点,证明最多存在两个地方性状态。
  • 推导基本再生数 R₀,并通过横截性与鞍结分岔分析建立疾病持续或消退的阈值条件。
  • 应用庞特里亚金最大值原理,刻画最小化包含疾病负担与干预成本的代价函数的最优控制策略。
  • 进行敏感性分析,以评估参数对 R₀ 与疾病动态的影响程度。
  • 通过数值模拟开展效率与成本效益分析,比较不同干预组合的效果。

实验结果

研究问题

  • RQ1在何种条件下模型会出现后向分岔?其流行病学意义为何?
  • RQ2在缺乏完美疫苗的情况下,疾病致死率如何影响后向分岔的发生?
  • RQ3为根除虫媒病毒病,疫苗接种、治疗、个人防护与媒介控制的最优组合为何?
  • RQ4敏感性分析如何对关键参数影响疾病传播与 R₀ 的程度进行排序?
  • RQ5与单一干预措施相比,联合控制策略的成本效益如何?

主要发现

  • 当存在疾病致死率时,才会出现后向分岔,即 R₀ < 1 仅为必要条件,而非充分条件,无法保证疾病消除。
  • 若无疾病致死率,当 R₀ ≤ 1 时,无病平衡点全局渐近稳定,后向分岔不会发生。
  • 基本再生数 R₀ 作为阈值参数,决定疾病是否持续或消退。
  • 敏感性分析表明,传播率(β_hv, β_vh)、恢复率(γ_h, γ_v)及媒介繁殖率对 R₀ 的影响最为显著。
  • 数值模拟显示,联合使用疫苗接种、治疗、个人防护及媒介控制(尤其是幼虫灭杀与成蚊灭杀)比单一干预措施更有效地降低疾病负担。
  • 成本效益与效率分析确认,联合控制策略可在低投入下实现显著的疾病减少效果,最优控制策略显示感染者数量迅速下降。

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