一类随机SIR流行病模型的渐近行为研究

考虑了一类恢复率受到噪声影响的随机SIR流行病模型.首先证明了模型非负解的全局存在惟一性;其次证明了当基本再生数R₀≤1时无病平衡点随机渐近稳定,当R₀>1时随机模型的解围绕确定性模型地方病平衡点震荡.最后通过数值仿真验证了所得结论的正确性.     

具有脉冲出生和脉冲接种的SIR传染病模型

考虑了脉冲出生、脉冲接种、垂直传染、因病死亡等因素,建立了脉冲出生和脉冲接种同时进行的SIR传染病模型,通过分析无病周期解的存在性以及稳定性,得出疾病灭绝的条件.     

一类具有垂直传染和预防接种的传染病模型的稳定性

考虑了垂直传染和预防接种因素对传染病流行影响的SEIRS模型,主要研究了系统的平衡点及其稳定性,得出当预防接种水平超过某一个阈值时疾病可以根除,若接种水平低于阈值时疾病将流行.     

一类疫苗预防接种具有效期性的SIRS模型稳定性分析

研究了一类预防接种下疫苗具有有效期的SIRS传染病模型,得到了决定疾病绝灭与否的闽值,给出了无病平衡点和地方病平衡点的全局稳定性的充分条件,最后借助Matlab软件进行了数值模拟．     

Optimal Vaccination in a Stochastic Epidemic Model of Two Non-Interacting Populations

Developing robust, quantitative methods to optimize resource allocations in response to epidemics has the potential to save lives and minimize health care costs. In this paper, we develop and apply a computationally efficient algorithm that enables us to calculate the complete probability distribution for the final epidemic size in a stochastic Susceptible-Infected-Recovered (SIR) model. Based on these results, we determine the optimal allocations of a limited quantity of vaccine between two non-interacting populations. We compare the stochastic solution to results obtained for the traditional, deterministic SIR model. For intermediate quantities of vaccine, the deterministic model is a poor estimate of the optimal strategy for the more realistic, stochastic case.     

Bimodal Epidemic Size Distributions for Near-Critical SIR with Vaccination

We introduce a recursive algorithm which enables the computation of the distribution of epidemic size in a stochastic SIR model for very large population sizes. In the important parameter region where the model is just slightly supercritical, the distribution of epidemic size is decidedly bimodal. We find close agreement between the distribution for large populations and the limiting case where the distribution is that of the time a Brownian motion hits a quadratic curve. The model includes the possibility of vaccination during the epidemic. The effects of the parameters, including vaccination level, on the form of the epidemic size distribution are explored.     

Optimal Vaccination Policies for an SIR Model with Limited Resources

The purpose of the paper is to use analytical method and optimization tool to suggest a vaccination program intensity for a basic SIR epidemic model with limited resources for vaccination. We show that there are two different scenarios for optimal vaccination strategies, and obtain analytical solutions for the optimal control problem that minimizes the total cost of disease under the assumption of daily vaccine supply being limited. These solutions and their corresponding optimal control policies are derived explicitly in terms of initial conditions, model parameters and resources for vaccination. With sufficient resources, the optimal control strategy is the normal Bang–Bang control. However, with limited resources, the optimal control strategy requires to switch to time-variant vaccination.     

一类具有非线性发生率的带时滞的SIR传染病模型的局部渐近稳定性

基于传统的SIR传染病模型,本文提出了一类具有非线性发生率的带时滞的传染病模型,得出了当S0〈T= μ2＋λ/β,对任意的时间滞后^,无病平衡点岛是局部渐近稳定的;当S0〉 μ2＋λ/β,无病平衡点E0是不稳定的,此时,正平衡点E＋是局部渐近稳定的．     

具有年龄结构的接种流行病模型正平衡解的全局稳定性

研究一个具有年龄结构的接种SIS流行病模型正平衡解的稳定性,先利用等价积分方程给出了正平衡解存在的充分条件,再利用迭代方法及函数的单调性,得到了零平衡解与正平衡解全局稳定的充分条件。     

SIR型传染病的模糊控制

针对SIR型传染病数学模型,将疾病的发展程度这一影响传染病传播的主要因素模糊化,利用条件S0〈P和S0〉p对疫情的影响,建立了一种模糊控制模型,使之在疫情发展的不同阶段对应不同控制措施。     

时滞传染病模型的指数稳定性

利用分析技巧研究了一类SEIRS传染病模型的动力学行为.结论表明如果再生数小于1,则带变时滞的传染病模型的无病平衡点是全局指数渐近稳定的,如果再生数大于1,得到传染病平衡点局部指数稳定的充分条件,同时给出了例子说明结论的有效性.     

具有周期传染率的SIR传染病模型的周期解

考虑了具有周期传染率的SIR流行病模型,定义了基本再生数^-R0=β／（μ＋γ）,分析了该模型的动力学性态,证明了当^-R0〈1时无病平衡点是全局稳定的;^-R0〉1时,无病平衡点是不稳定的,模型至少存在一个周期解。对小振幅的周期传染率模型,给出了模型周期解的近似表达式,证明了该周期解的稳定性,最后做了数值模拟,结果显示周期解可能是全局稳定的。     

SIR传染病模型的混沌跟踪控制

研究了一类疾病传染率受季节因素影响的SIR传染病模型的混沌运动,并采用轨迹跟踪控制方法对传染病模型中的混沌运动进行控制,设计状态反馈控制器,控制系统输出跟踪某一理想状态,使染病者数量渐近趋于零,从而,达到消除疾病的目的．仿真结果表明该方法的有效性．     

Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model

Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling) of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs.     

具有种群Logistic增长的SIR模型的稳定性和Hopf分支

基于种群Logistic增长假设,本文构建了一个三维非线性发生率的SIR模型.首先探讨了该模型平衡点的稳定性,然后应用中心流形投影法得到了系统在非平凡平衡点附近产生超临界分支,并给出了数值模拟.     

一类具有饱和发生率的SEIS模型的全局稳定性

建立并分析了一类具有饱和发生率、在潜伏期具有传染性的SEIS模型.得到了模型的基本再生数R_0和无病平衡点与地方病平衡点全局渐近稳定的充分条件.