GLOBAL STABILITY OF SIRS EPIDEMIC MODELS WITH A CLASS OF NONLINEAR INCIDENCE RATES AND DISTRIBUTED DELAYS

In this article, we establish the global asymptotic stability of a disease-free equilibrium and an endemic equilibrium of an SIRS epidemic model with a class of nonlin- ear incidence rates and distributed delays. By using strict monotonicity of the incidence function and constructing a Lyapunov functional, we obtain sufficient conditions under which the endemic equilibrium is globally asymptotically stable. When the nonlinear inci- dence rate is a saturated incidence rate, our result provides a new global stability condition for a small rate of immunity loss.

GLOBAL STABILITY OF AN SIRS EPIDEMIC MODEL WITH DELAYS

In this article, an SIRS epidemic model spread by vectors （mosquitoes） which have an incubation time to become infectious is formulated. It is shown that a disease-free equilibrium point is globally stable if no endemic equilibrium point exists. Further, the endemic equilibrium point （if it exists） is globally stable with a respect ＂weak delay＂. Some known results are generalized.

GLOBAL STABILITY OF EXTENDED MULTI-GROUP SIR EPIDEMIC MODELS WITH PATCHES THROUGH MIGRATION AND CROSS PATCH INFECTION

In this article, we establish the global stability of an endemic equilibrium of multi-group SIR epidemic models, which have not only an exchange of individuals between patches through migration but also cross patch infection between different groups. As a result, we partially generalize the recent result in the article [16].

Steady State Solution and Stability of an Age-Structured MSIQR Epidemic Model

The importance of epidemiology in our life has stimulated researchers to extend the classic Susceptibles-Infectives-Removed (SIR) model to sophisticated models by including more factors in order to give detailed transmission dynamics of epidemic diseases. However, the integration of the quarantine policy and age-structure is less addressed. In this work we propose an age-structured MSIQR (temporarily immune-susceptibles-infectives-quarantined-removed) model to study the impact of quarantine policies on the spread of epidemic diseases. Specifically, we investigate the existence of steady state solutions and stability property of the proposed model. The derived explicit expression of the basic reproductive number shows that the disease-free equilibrium is globally asymptotically stable if, and that the unique endemic equilibrium exists if. In addition, the stability conditions of the endemic equilibrium are derived.

The Effect of State-Dependent Control for an SIRS Epidemic Model with Varying Total Population

Based on the mechanism of prevention and control of infectious disease, we propose, in this paper, an SIRS epidemic model with varying total population size and state-dependent control, where the fraction of susceptible individuals in population is as the detection threshold value. By the Poincaré map, theory of differential inequalities and differential equation geometry, the existence and orbital stability of the disease-free periodic solution are discussed. Theoretical results show that by state-dependent pulse vaccination we can make the proportion of infected individuals tend to zero, and control the transmission of disease in population.

Stability of a Delayed Stochastic Epidemic COVID-19 Model with Vaccination and with Differential Susceptibility

In this paper, we treat the spread of COVID-19 using a delayed stochastic SVIRS (Susceptible, Infected, Recovered, Susceptible) epidemic model with a general incidence rate and differential susceptibility. We start with a deterministic model, then add random perturbations on the contact rate using white noise to obtain a stochastic model. We first show that the delayed stochastic differential equation that describes the model has a unique global positive solution for any positive initial value. Under the condition R0 ≤ 1, we prove the almost sure asymptotic stability of the disease-free equilibrium of the model.

Epidemic Propagation: An Automaton Model as the Continuous SIR Model

The use of the SIR model to predict the time evolution of an epidemic is very frequent and has spatial information about its propagation which may be very useful to contrast its spread. In this paper we take a particular cellular automaton model that well reproduces the time evolution of the disease given by the SIR model;setting the automaton is generally an annoying problem because we need to run a lot of simulations, compare them to the solution of the SIR model and, finally, decide the parameters to use. In order to make this procedure easier, we will show a fast method that, in input, requires the parameters of the SIR continuous model that we want to reproduce, whereas, in output, it yields the parameters to use in the cellular automaton model. The problem of computing the most suitable parameters for the reticular model is reduced to the problem of finding the roots of a polynomial Equation.

Study on the Dynamics of an SIR Epidemic Model with Saturated Growth Rate

In this paper, we investigate the dynamic properties of an SIR epidemic model with saturated growth rate. Under the conditions of an arbitrary initial value, we prove that the system exists unique positive solution, and give the sufficient conditions caused by random environmental factors leading to the extinction of infectious diseases. Moreover, we verify the conditions for the persistence of infectious diseases in the mean sense. Finally, we provide the biology interpretation and some strategies to control the infectious diseases.

Extinction and Stationary Distribution of a Stochastic SIR Epidemic Model with Jumps

A stochastic susceptible-infective-recovered(SIR)epidemic model with jumps was considered.The contributions of this paper are as follows.(1) The stochastic differential equation(SDE)associated with the model has a unique global positive solution;(2) the results reveal that the solution of this epidemic model will be stochastically ultimately bounded,and the non-linear SDE admits a unique stationary distribution under certain parametric conditions;(3) the coefficients play an important role in the extinction of the diseases.

Stability Analysis of an SIR Epidemic Model with Non-Linear Incidence Rate and Treatment

We consider a SIR epidemic model with saturated incidence rate and treatment. We show that if the basic reproduction number, R0 is less than unity and the disease free equilibrium is locally asymptotically stable. Moreover, we show that if R0 > 1, the endemic equilibrium is locally asymptotically stable. In the end, we give some numerical results to compare our model with existing model and to show the effect of the treatment term on the model.

A cellular automata model of epidemics of a heterogeneous susceptibility

In this paper we present a model with spatial heterogeneity based on cellular automata （CA）. In the model we consider the relevant heterogeneity of host （susceptible） mixing and the natural birth rate. We divide the susceptible population into three groups according to the immunity of each individual based on the classical susceptible-infectedremoved （SIR） epidemic models, and consider the spread of an infectious disease transmitted by direct contact among humans and vectors that have not an incubation period to become infectious. We test the local stability and instability of the disease-free equilibrium by the spectrum radii of Jacobian. The simulation shows that the structure of the nearest neighbour size of the cell （or the degree of the scale-free networks） plays a very important role in the spread properties of infectious disease. The positive equilibrium of the infections versus the neighbour size follows the third power law if an endemic equilibrium point exists. Finally, we analyse the feature of the infection waves for the homogeneity and heterogeneous cases respectively.

Asymptotic Behavior of a Stochastic SIRS Model with Non-linear Incidence and Levy Jumps

A stochastic susceptible-infective-recovered-susceptible( SIRS) model with non-linear incidence and Levy jumps was considered. Under certain conditions, the SIRS had a global positive solution. The stochastically ultimate boundedness of the solution of the model was obtained by using the method of Lyapunov function and the generalized Ito's formula. At last,asymptotic behaviors of the solution were discussed according to the value of R0. If R0< 1,the solution of the model oscillates around a steady state, which is the diseases free equilibrium of the corresponding deterministic model,and if R0> 1,it fluctuates around the endemic equilibrium of the deterministic model.

具有Logistic增长和心理作用的随机SIRS传染病模型定性分析

基于流行病受环境噪声和心理作用的影响,建立了一类具有Logistic增长和心理作用的随机SIRS传染病模型,目的在于讨论Logistic增长和心理作用对模型全局动力学的影响。首先,通过构造Lyapunov函数并利用Itˆo公式,证明了该模型全局正解的存在唯一性;然后,在适当的条件下,利用随机Lyapunov函数方法,应用LaSalle不变性原理得到该模型正解存在遍历平稳分布的充分条件。结果表明:环境和心理变化在一定条件下会对疾病起抑制作用。最后,通过数值模拟验证了理论结果的正确性。

一类时间周期SIRS扩散传染病模型的渐近传播速度

利用渐近传播速度理论,研究了一类模拟时间周期变化传播环境中疾病传播的SIRS反应扩散传染病模型的渐近传播性质。区别于已有针对SI二维系统的传播速度的结果,该模型中R仓室无法解耦于整个系统,为此需要克服高维和非自治性耦合带来的困难,以证明高维系统渐近传播速度的存在性。首先,借助单调系统渐近传播速度的抽象理论和比较原理证明了染病者I仓室在疾病未入侵区域的传播性质,以此结论为基础,利用整体解结合最大值原理进一步验证了恢复者R仓室在未入侵区域具有类似的传播性质。其次,分别对I和R方程运用比较原理结合一致持久思想和最大值原理分析了其在疾病已入侵区域的一致持久性。由此,得到了划分这两个变化区域的渐近传播速度阈值,即证明了整个系统渐近传播速度的存在性。最后,利用数值方法进一步模拟了时间周期传播环境下疾病已入侵区域更具体的传播动态。

Simulation of Spread of Infectious Diseases and Population Mobility in a Deterministic Epidemic Patch Model

Computer simulation models are widely applied in various areas of the health care sector, including the spread of infectious diseases. Patch models involve explicit movements of people between distinct locations. The aim of the present work has been designed and explored a patch model with population mobility between different patches and between each patch and an external population. The authors considered a SIR （susceptible-infected-recovered） scheme. The model was explored by computer simulations. The results show how endemic levels are reached in all patches of the system. Furthermore, the performed explorations suggest that the people mobility between patches, the immigration from outside the system and the infection rate in each patch, are factors that may influence the dynamics of epidemics and should be considered in health policy planning.

Analytic algorithms for Some Models of Nonlinear Age–Structured Population Dynamics and Epidemiology

Three analytic algorithms based on Adomian decomposition, homotopy perturbation and homotopy analysis methods are proposed to solve some models of nonlinear age-structured population dynamics and epidemiology. Truncating the resulting convergent infinite series, we obtain numerical solutions of high accuracy for these models. Three numerical examples are given to illustrate the simplicity and accuracy of the methods.

SIRS epidemic modeling using fractional-ordered differential equations:Role of fear effect

In this paper,an SIRS epidemic model using Grunwald-Letnikov fractional-order derivative is formulated with the help of a nonlinear system of fractional differential equations to analyze the effects of fear in the population during the outbreak of deadly infectious diseases.The criteria for the spread or extinction of the disease are derived and discussed on the basis of the basic reproduction number.The condition for the existence of Hopf bifurcation is discussed considering fractional order as a bifurcation parameter.Additionally,using the Grunwald-Letnikov approximation,the simulation is carried out to confirm the validity of analytic results graphically.Using the real data of COVID-19 in India recorded during the second wave from 15 May 2021 to 15 December 2021,we estimate the model parameters and find that the fractional-order model gives the closer forecast of the disease than the classical one.Both the analytical results and numerical simulations presented in this study suggest different policies for controlling or eradicating many infectious diseases.

复杂网络上带有直接免疫的SIRS类传染模型研究

在SIRS(susceptible-infected-removed-susceptible)模型基础上,提出一个带有直接免疫的SIRS类传染模型.利用平均场理论,分析得到该传播模型的传染临界阈值主要与网络拓扑结构、直接免疫速率和免疫丧失速率有关.理论分析和数值仿真表明,直接免疫作用可以增大复杂网络上疾病传播的临界阈值、降低传染性疾病的传播范围,从而有效控制疾病在复杂网络上传播.

现实复杂情形下的SIRS型传染病模型及其控制策略

研究现实复杂情形下(包含非线性传染率、有隔离措施、群外个体迁入、生育与死亡以及疾病可水平和垂直传播等)的SIRS型传染病模型。首先证明该传染病模型的无病平衡点与地方病平衡点的唯一存在性及渐近稳定性;然后从基本再生数以及折衷考虑人道主义、救治代价与疾病控制效果的原则,针对流行于人类的传染病,提出"优先隔离染病个体、提高疾病治愈率以及控制传染病垂直传播"的传染病综合控制策略;最后,数值仿真验证了模型的稳态特性以及综合控制策略的有效性。

具有Logistic增长和治疗的SIRS传染病模型的后向分支

利用传染病动力学理论,建立一类具有Logistic增长和治疗的SIRS传染病模型,并假设模型中总人口增长满足Logistic方程,考虑治疗项为非线性的可微函数,以描述有限的医疗资源对延迟患者治疗的影响.综合运用微分方程稳定性理论中的Routh-Hurwitz判据、LaSalle不变集原理并构造适当的Lyapunov函数方法,获得了该模型的无病平衡点和地方病平衡点全局渐近稳定的代数判据及后项分支存在条件.结果表明,当延迟患者治疗的影响较严重时,该模型会出现后向分支现象,基本再生数已不再是疾病是否消亡的阀值,需要加强医疗资源建设,通过提供及时优质的医疗服务,才能有效控制或根除疾病.