Different Epidemic Models on Complex Networks

Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals＇ relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each ease. Finally, we present numerical simulations for each case to verify our results.     

Effects of superspreaders in spread of epidemic

Within the standard SIR model with spatial structure, we propose two models for the superspreader. In one model, superspreaders have intrinsically strong infectiousness. In other model, they have many social connections. By Monte Carlo simulation, we obtain the percolation probability, the propagation speed, the epidemic curve, the distribution of secondary infected and the propagation path as functions of population and the density of superspreaders. By comparing the results with the data of SARS in Singapore 2003, we conclude that the latter model can explain the observation.     

A fractional order epidemic model for the simulation of outbreaks of influenza A(H1N1)

In this paper, we propose a nonlinear fractional order model in order to explain and understand the outbreaks of influenza A(H1N1). In the fractional model, the next state depends not only upon its current state but also upon all of its historical states. Thus, the fractional model is more general than the classical epidemic models. In order to deal with the fractional derivatives of the model, we rely on the Caputo operator and on the Grünwald–Letnikov method to numerically approximate the fractional derivatives. We conclude that the nonlinear fractional order epidemic model is well suited to provide numerical results that agree very well with real data of influenza A(H1N1) at the level population. In addition, the proposed model can provide useful information for the understanding, prediction, and control of the transmission of different epidemics worldwide. Copyright © 2013 John Wiley & Sons, Ltd.     

The fractional-order SIS epidemic model with variable population size

In this work, we deal with the fractional-order SIS epidemic model with constant recruitment rate, mass action incidence and variable population size. The stability of equilibrium points is studied. Numerical solutions of this model are given. Numerical simulations have been used to verify the theoretical analysis.     

ANALYSIS OF AN SI EPIDEMIC MODEL WITH NONLINEAR TRANSMISSION AND STAGE STRUCTURE

A disease transmission model of SI type with stage structure is formulated. The stability of disease free equilibrium, the existence and uniqueness of an endemic equilibrium, the existence of a global attractor are investigated.     

Olive-Derived Triterpenes Suppress SARS COV-2 Main Protease: A Promising Scaffold for Future Therapeutics

SARS CoV-2 pandemic is still considered a global health disaster, and newly emerged variants keep growing. A number of promising vaccines have been recently developed as a protective measure; however, cost-effective treatments are also of great importance to support this critical situation. Previously, betulinic acid has shown promising antiviral activity against SARS CoV via targeting its main protease. Herein, we investigated the inhibitory potential of this compound together with three other triterpene congeners (i.e., ursolic acid, maslinic acid, and betulin) derived from olive leaves against the viral main protease (M^pro) of the currently widespread SARS CoV-2. Interestingly, betulinic, ursolic, and maslinic acids showed significant inhibitory activity (IC₅₀ = 3.22–14.55 µM), while betulin was far less active (IC₅₀ = 89.67 µM). A comprehensive in-silico analysis (i.e., ensemble docking, molecular dynamic simulation, and binding-free energy calculation) was then performed to describe the binding mode of these compounds with the enzyme catalytic active site and determine the main essential structural features required for their inhibitory activity. Results presented in this communication indicated that this class of compounds could be considered as a promising lead scaffold for developing cost-effective anti-SARS CoV-2 therapeutics.     

SARS CoV内对照RNA病毒样颗粒的构建和表达

在SARS-CoV的核酸检测方法中,由于普遍缺乏安全、稳定、特异的内对照,而不能对样品处理、反转录、扩增以及定量检测实施全程监控。构建的病毒样核蛋白颗粒内对照,能够对SARS-CoV临床检测实施监控。本文通过克隆1.7Kb大肠杆菌噬菌体MS2的装配蛋白和壳蛋白基因以及SARS冠状病毒经过突变产生的270bp内对照片断,并将这些基因连接到载体pTrc99a上表达,进行纯化、定量分析、RT-PCR检测和稳定性试验。获得SARS内对照病毒样核蛋白颗粒,在人血清和SM缓冲液中37℃稳定性可达到30天,能抵抗核糖核酸酶降解。将内对照颗粒加入临床样本中一同检测,能够对检测的全过程(样品处理、反转录和PCR)有效进行监控,与SARS-CoV没有交叉反应。研究表明制备的该病毒样核蛋白颗粒稳定、安全、可靠,可作为SARS冠状病毒RT-PCR检测、定量分析的有效内对照参考品。     

考虑意识对带媒介的SIS模型中疾病传播过程的影响

在无标度网络上,研究意识对带媒介的SIS模型中疾病传播过程的影响.最后的结果表明接触意识与局部意识能增加流行病阈值,而全局意识与媒介意识不能.     

北京市SARS疫情统计分析

本文对严重急性呼吸道综合症 SA RS疾病进行了统计分析 .文章首先以北京市海淀区 SARS确诊病例和疑似病例为研究对象 ,分别按照地区、人口进行了统计分析 ,得出海淀区不同小区疫情发展的显著程度 .然后利用正交试验设计 ,分别就年龄、性别、职业等因素对海淀区 SARS确诊病人和疑似病人影响程度进行了统计分析 ,得出 2 1岁到 50岁的学生和干部得病率最高的统计结果 ,这完全符合海淀区的疫情事实 .这个统计结果已经被海淀区政府“海淀区政府应急管理信息系统 ( H EMIS)”[6]采用 . H EMIS系统作为中国第一个政府应急系统在海淀区 SARS防治中起到了一定作用 [1 ] .文章最后研究了北京市每天新增的确诊病例和每天疑似病例转为确诊病例之间的相关系数 ,从它们的相关性分析可以反映出防治 SARS疫情措施的有效性 .     

具有染病年龄结构的SEIR流行病模型的稳定性

建立和研究了一类具有染病年龄结构的SEIR流行病模型.得到了该模型的基本再生数R0的表达式.证明了当R0<1时,无病平衡点E0不仅局部渐近稳定,而且全局吸引;当R0>1时,无病平衡点E0不稳定,此时存在稳定的地方病平衡点.