无标度网络中最大传染能力限定的病毒传播问题研究

传统的病毒传播模型在无限大无标度网络上不存在病毒传播阈值,即无论病毒的传播速率多么低,病毒始终能够在网络中传播.但研究发现,这个结论是在网络中存在超级传染者的假设下得到的,然而许多真实的无标度网络中并不存在超级传染者.因此,文章提出了一个最大传染能力限定的病毒传播模型,并从理论上证明了在最大传染能力限定的无限大无标度网络上,病毒传播阈值是存在的;同时,也分析了最大传染能力限定下非零传播阈值与有限规模网络下非零传播阈值的本质区别,并解释了为什么人们总是认为传统病毒传播模型对许多真实网络病毒感染程度估计过高的关键词：无标度网络最大传染能力传播阈值感染程度     

Kinetics of Infection-Driven Growth Model with Birth and Death

We propose a two-species infection model, in which an infected aggregate can gain one monomer from a healthy one due to infection when they meet together. Moreover, both the healthy and infected aggregates may lose one monomer because of self-death, but a healthy aggregate can spontaneously yield a new monomer. Consider a simple system in which the birth/death rates are directly proportional to the aggregate size, namely, the birth and death rates of the healthy aggregate of size k are J1 k and J2k while the self-death rate of the infected aggregate of size k is J3k. We then investigate the kinetics of such a system by means of rate equation approach. For the J1 〉 J2 case, the aggregate size distribution of either species approaches the generalized scaling form and the typical size of either species increases wavily at large times. For the J1 = J2 case, the size distribution of healthy aggregates approaches the generalized scaling form while that of infected aggregates satisfies the modified scaling form. For the J1 〈 J2 case, the size distribution of healthy aggregates satisfies the modified scaling form, but that of infected aggregates does not scale.     

Global dynamics of a mathematical model for HTLV-I infection of CD4 T-cells

In this paper, a mathematical model for HILV-I infection of CD4⁺ T-cells is investigated. The force of infection is assumed be of a function in general form, and the resulting incidence term contains, as special cases, the bilinear and the saturation incidences. The model can be seen as an extension of the model [Wang et al. Mathematical analysis of the global dynamics of a model for HTLV-I infection and ATL progression, Math. Biosci. 179 (2002) 207-217; Song, Li, Global stability and periodic solution of a model for HTLV-I infection and ATL progression, Appl. Math. Comput. 180(1) (2006) 401-410]. Mathematical analysis establishes that the global dynamics of T-cells infection is completely determined by a basic reproduction number _R0${\mathfrak{R}}_0$. If _R0?1${\mathfrak{R}}_0?1$, the infection-free equilibrium is globally stable; if _R0>1${\mathfrak{R}}_0>1$, the unique infected equilibrium is globally stable in the interior of the feasible region.     

早期日本血吸虫感染长爪沙鼠动物模型的建立

实验应用双抗体夹心免疫吸附试验（Double Antibodies—ELISA ELISA）检测获得感染鼠血清的循环抗体,所用抗原由日本血吸虫成虫和虫卵抗原免疫长爪沙鼠而获得．实验结果证明,用该试验检测长爪沙鼠感染日本血吸虫后6周内各期的抗体有高度的特异性,可为日本血吸虫感染模型的建立和考核疗效提供参考．     

具有周期传染率和垂直传染的SIR传染病模型的周期解

考虑具有周期传染率和垂直传染的S IR流行病模型,分析了该模型的动力学性态.对小振幅的周期垂直传染率模型,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,并做了数值模拟,显示出周期解可能是全局稳定的.     

Modeling the dynamical behavior of the interaction of T-cells and human immunodeficiency virus with saturated incidence

In the last forty years, the rise of HIV has undoubtedly become a major concern in the field of public health, imposing significant economic burdens on affected regions. Consequently, it becomes imperative to undertake comprehensive investigations into the mechanisms governing the dissemination of HIV within the human body. In this work, we have devised a mathematical model that elucidates the intricate interplay between CD4⁺T-cells and viruses of HIV,employing the principles of fractional calculus. The production rate of CD4⁺T-cells, like other immune cells depends on certain factors such as age, health status, and the presence of infections or diseases. Therefore, we incorporate a variable source term in the dynamics of HIV infection with a saturated incidence rate to enhance the precision of our findings. We introduce the fundamental concepts of fractional operators as a means of scrutinizing the proposed HIV model.To facilitate a deeper understanding of our system, we present an iterative scheme that elucidates the trajectories of the solution pathways of the system. We show the time series analysis of our model through numerical findings to conceptualize and understand the key factors of the system.In addition to this, we present the phase portrait and the oscillatory behavior of the system with the variation of different input parameters. This information can be utilized to predict the long-term behavior of the system, including whether it will converge to a steady state or exhibit periodic or chaotic oscillations.