Threshold behaviour of a SI epidemiological model with two structuring variables

In this article, we study a SI epidemic model describing the spread of a disease in a perfectly mixed managed population, representing an animal herd in a fattening farm. The epidemic process is characterized by a non-neglectable and variable incubation period, during which individuals are infectious but cannot be easily detected. The susceptible and infected populations are structured according to age and, for infected, to time remaining before the end of the incubation, where they show detectable clinical signs. We study the well posedness and the asymptotic behaviour of the problem and show that in some cases, even if the farm is fed with healthy animals, disease persistence can occur. We give an explicit formula for the basic reproduction number \({\mathcal{R}_0}\) and the biological interpretation of this threshold on a specific example. We finally illustrate the asymptotic behaviour of the model by numerical simulations.     

Random Sums of Independent Indicators and Generalized Reduced Processes

We consider a random sum of independent and identically distributed Bernoulli random variables. We prove several limit theorems for this sum under some natural assumptions. Using these limit theorems a generalized version of the reduced critical Galton-Watson process will be studied. In particular we find limit distributions for the number of individuals in a given generation the number of whose descendants after some generations exceeds a fixed or increasing level. An application to study of the number of “big” trees in a forest containing a random number of trees will also be discussed.     

Transmission dynamics of a two-strain pairwise model with infection age

We present and study a two-strain pairwise epidemic model with non-Markovian recovery process in which the recovery rate depends on infection age. The novel model is a hyperbolic system which can be transformed into a system of integro-differential equations by using the method of characteristics. For the two-strain pairwise model, the reproduction number with arbitrary recovery time distributions is obtained. We carry out rigorous analysis and obtain upper and lower estimates for the final epidemic size. Finally, the effects of three commonly used recovery time distributions on the reproduction number are compared by numerical simulations. We further present how the mean length of the infectious period affects the final epidemic size, the peak time and the duration of an epidemic.     

SIS reaction–diffusion model with risk-induced dispersal under free boundary

A spatial susceptible–infected–susceptible epidemic model with a free boundary, where infected individuals disperse non-uniformly, is investigated in this study. Spatial heterogeneity and movement of individuals are essential factors that affect pandemics and the eradication of infectious diseases. Our goal is to investigate the effect of a dispersal strategy for infected individuals, known as risk-induced dispersal (RID), which represents the motility of infected individuals induced by risk depending on whether they are in a high- or a low-risk region. We first construct the basic reproduction number and then understand the manner in which a nonuniform movement of infected individuals affects the spreading–vanishing dichotomy of a disease in a one-dimensional domain. We conclude that even though the infected individuals reside in a high-risk initial domain, the disease can be eradicated from the region if the infected individuals move with a high sensitivity of RID as they disperse. Finally, we demonstrate our results via simulations for a one-dimensional case.     

A fixed-point algorithm to estimate the Yule-Simon distribution parameter

The Yule-Simon distribution is a discrete probability distribution related to preferential attachment processes such as the growth in the number of species per genus in some higher taxon of biotic organisms, the distribution of the sizes of cities, the wealth distribution among individuals, the number of links to pages in the World Wide Web, among others. In this paper we present an algorithm to, given a set of observations stemmed from a Yule process, obtain the parameter of the Yule-Simon distribution with maximum likelihood. In order to test our algorithm, we use a modified Polya urn process simulation to generate some data that was used as input to our algorithm. We make a comparison of our algorithm with other methods and also we show an application to some empirical data.     

A nonparametric estimation of the infection curve

Predicting the future course of an epidemic depends on being able to estimate the current numbers of infected individuals.However,while back-projection techniques allow reliable estimation of the numbers of infected individuals in the more distant past,they are less reliable in the recent past.We propose two new nonparametric methods to estimate the unobserved numbers of infected individuals in the recent past in an epidemic.The proposed methods are noniterative,easily computed and asymptotically normal wit...     

Mathematical Analysis of SIR Epidemic Model with Piecewise Infection Rate and Control Strategies

The limitation of contact between susceptible and infected individuals plays an important role in decreasing the transmission of infectious diseases. Prevention and control strategies contribute to minimizing the transmission rate. In this paper, we propose SIR epidemic model with delayed control strategies, in which delay describes the response and effect time. We study the dynamic properties of the epidemic model from three aspects: steady states, stability and bifurcation. By eliminating the existence of limit cycles, we establish the global stability of the endemic equilibrium, when the delay is ignored. Further, we find that the delayed effect on the infection rate does not affect the stability of the disease-free equilibrium, but it can destabilize the endemic equilibrium and bring Hopf bifurcation. Theoretical results show that the prevention and control strategies can effectively reduce the final number of infected individuals in the population. Numerical results corroborate the theoretical ones.     

Monte Carlo simulation and analytic approximation of epidemic processes on large networks

Low dimensional ODE approximations that capture the main characteristics of SIS-type epidemic propagation along a cycle graph are derived. Three different methods are shown that can accurately predict the expected number of infected nodes in the graph. The first method is based on the derivation of a master equation for the number of infected nodes. This uses the average number of SI edges for a given number of the infected nodes. The second approach is based on the observation that the epidemic spreads along the cycle graph as a front. We introduce a continuous time Markov chain describing the evolution of the front. The third method we apply is the subsystem approximation using the edges as subsystems. Finally, we compare the steady state value of the number of infected nodes obtained in different ways.     

离散的SI和SIS传染病模型的研究

为了描述个体的死亡、染病者的恢复以及疾病的传染,引入了相应的概率.基于总种群中个体数量为常数的假设,根据染病者能否恢复分别建立了具有生命动力学的离散SI和SIS传染病模型.所得到的结果显示:它们具有与相应连续模型相同的动力学性态,并确定了各自的阈值.在它们的阈值之下,传染病最终将灭绝;在它们的阈值之上,传染病将会发展成为地方病,染病者的数量将趋向于一确定的正常数.     

Bifurcation analysis of an SIRS epidemic model with standard incidence rate and saturated treatment function

An epidemic model with standard incidence rate and saturated treatment function of infectious individuals is proposed to understand the effect of the capacity for treatment of infective individuals on the disease spread. The treatment function in this paper is a continuous and differential function which exhibits the effect of delayed treatment when the rate of treatment is lower and the number of infected individuals is getting larger. It is proved that the existence and stability of the disease-free and endemic equilibria for the model are not only related to the basic reproduction number but also to the capacity for treatment of infective individuals. And a backward bifurcation is found when the capacity is not enough. By computing the first Lyapunov coefficient, we can determine the type of Hopf bifurcation, i.e., subcritical Hopf bifurcation or supercritical Hopf bifurcation. We also show that under some conditions the model undergoes Bogdanov-Takens bifurcation. Finally, numerical simulations are given to support some of the theoretical results.     

一类带有非线性传染率的SEIR传染病模型的全局分析

通过假设被传染的易感者一部分经过一段潜伏期后才具有传染性,而另一部分被感染的易感者直接成为传染者,建立了一类带有非线性传染率的SEIR传染病模型,得到了确定疾病是否成为地方病的基本再生数以及无病平衡点和地方病平衡点的全局稳定性.     

ANALYSIS OF A SUSCEPTIBLE-EXPOSED-INFECTED EPIDEMIC MODEL WITH RANDOM PERTURBATION AND VARYING POPULATION SIZE

In this paper, we study a type of susceptible-exposed-infected (SEI) epidemic model with varying population size and introduce the random perturbation of the constant contact rate into the SEI epidemic model due to the universal existence of fluctuations. Under some moderate conditions, the density of the exposed and the infected individuals exponentially approaches zero almost surely are derived. Furthermore, the stochastic SEI epidemic model admits a stationary distribution around the endemic equilibrium, and the solution is ergodic. Some numerical simulations are carried out to demonstrate the efficiency of the main results.     

SIR epidemics on random graphs with a fixed degree sequence

Let Δ > 1 be a fixed positive integer. For \begin{align*}{\textbf{ {z}}} \in \mathbb{R}_+^\Delta\end{align*} let G_z be chosen uniformly at random from the collection of graphs on ∥z∥₁n vertices that have z_in vertices of degree i for i = 1,…,Δ. We determine the likely evolution in continuous time of the SIR model for the spread of an infectious disease on G_z, starting from a single infected node. Either the disease halts after infecting only a small number of nodes, or an epidemic spreads to infect a linear number of nodes. Conditioning on the event that more than a small number of nodes are infected, the epidemic is likely to follow a trajectory given by the solution of an associated system of ordinary differential equations. These results also give the likely number of nodes infected during the course of the epidemic and the likely length in time of the epidemic. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012     

一类带有一般出生率的SIS传染病模型的全局分析

将一般出生率系数引入S IS传染病模型,得到了种群灭绝和疾病灭绝的阈值条件.分别借助S tokes定理和D u lac函数对染病者的数量模型和染病者在种群中所占比例的模型进行了讨论,得到了相应模型的全局动力学行为.     

Impacts of TV and radio advertisements on the dynamics of an infectious disease: A modeling study

TV and radio advertisements are widely acknowledged as important interventions in raising issues of public health care and play promising role to control the infection through propagating awareness among the individuals. In this paper, a nonlinear susceptible‐infected‐susceptible (SIS) model is proposed and analyzed to see the impacts of TV and radio advertisements on the spread of influenza epidemic. In the model formulation, it is assumed that the susceptible individuals contract infection through the direct contact with infected individuals. The information regarding the protection against the disease is propagated via TV and radio advertisements, and their growth rates are assumed to be proportional to the fraction of infected individuals. However, the growth rate of TV advertisements decreases with the increase in number of aware individuals. The information broadcasted through TV and radio advertisements induces behavioral changes among the susceptible individuals, and they form an isolated aware class. The epidemiological feasible equilibria, their stability properties, and direction of bifurcation are discussed. The expression for modified basic reproduction number is obtained. The model analysis shows that the dissemination rate of awareness among susceptible individuals due to TV and radio advertisements and baseline number of TV and radio advertisements have potential to reduce the epidemic peak and, thus, control the spread of infection. Further, the analytical findings are well supported through numerical simulation.     

一类具有阶段结构和接种的SIR传染病模型

根据不同程度的感染者有不同的传染率,建立了一个具有阶段结构和双线性传染率的S IR流行病模型,得到了模型的阈值参数R0,证明了模型平衡点的全局性态完全由R0的值确定.并进行了数值模拟.     

带有脉冲免疫和传染年龄的传染病模型的全局吸引性

讨论了带有脉冲免疫和传染年龄的传染病模型.传染类的恢复率是传染年龄的函数,当染病再生数小于1时,文章得到无病周期解是全局吸引的.如果总人口规模变化,也可得到类似的结论.最后,提出了带有脉冲免疫和传染年龄传染病模型待解决的问题.     

一类拟平稳序列极值的极限律

Ｋ．Ｆ．Ｔｕｒｋｍａｎ讨论了一类拟平稳序列最大值的渐近分布。本文利用点过程收全党一理得到水平超出点过程的收敛定理和第ｒ个最大值的渐近分布及前ｒ个最大值的联合渐近分布。     

Dynamic Cost-Benefit Analysis of Drug Substitution Programs

This paper studies optimal spending for drug substitution programs in the context of a dynamic epidemic model of both drug use and drug use-related infections. Two types of costs are considered in addition to control costs: social costs resulting from individuals being dependent on drugs; additional costs due to drug users being vulnerable to infections like hepatitis C or HIV. Analysis of the model demonstrates that the long-run equilibrium is not necessarily unique. Instead, there may be multiple equilibria. Which of these equilibria is optimal depends on the initial conditions for the number of drug addicts and the number of those who are infected. So, for a given set of epidemic parameters, it may be optimal to spend a lot on substitution programs that reduce the number of drug addicts or to spend little and to accept a high level of drug use.