EPIDEMIC SPREADING AND GLOBAL STABILITY OF A NEW SIS MODEL WITH DELAY ON HETEROGENEOUS NETWORKS

2015 ◽  
Vol 23 (04) ◽  
pp. 1550029 ◽  
Author(s):  
HUIYAN KANG ◽  
YIJUN LOU ◽  
GUANRONG CHEN ◽  
SEN CHU ◽  
XINCHU FU

In this paper, we study a susceptible-infected-susceptible (SIS) model with time delay on complex heterogeneous networks. Here, the delay describes the incubation period in the vector population. We calculate the epidemic threshold by using a Lyapunov functional and some analytical methods, and find that adding delay increases the epidemic threshold. Then, we prove the global stability of disease-free and endemic equilibria by using the theory of functional differential equations. Furthermore, we show numerically that the epidemic threshold of the new model may change along with other factors, such as the infectivity function, the heterogeneity of the network, and the degrees of nodes. Finally, we find numerically that the delay can affect the convergence speed at which the disease reaches equilibria.

2015 ◽  
Vol 08 (01) ◽  
pp. 1550007 ◽  
Author(s):  
Jiancheng Zhang ◽  
Jitao Sun

In this paper, we investigate a new model with a generalized feedback mechanism in weighted networks. Compare to previous models, we consider the initiative response of people and the important impact of nodes with different edges on transmission rate as epidemics prevail. Furthermore, by constructing Lyapunov function, we prove that the disease-free equilibrium E0 is globally asymptotically stable as the epidemic threshold R* < 1. When R* > 1, we obtain the permanence of epidemic and the local stability of endemic equilibrium E*. Finally, one can find a good agreement between numerical simulations and our analytical results.


2016 ◽  
Vol 27 (08) ◽  
pp. 1650090 ◽  
Author(s):  
Yijiang Zou ◽  
Weibing Deng ◽  
Wei Li ◽  
Xu Cai

The epidemic spreading was explored on activity-driven networks (ADNs), accounting for the study of dynamics both on and of the ADN. By employing the susceptible-infected-susceptible (SIS) model, two aspects were considered: (1) the infection rate of susceptible agent (depending on the number of its infected neighbors) evolves due to the temporal structure of ADN, rather than being a constant number; (2) the susceptible and infected agents generate unequal links while being activated, namely, the susceptible agent gets few contacts with others in order to protect itself. Results show that, in both cases, the larger epidemic threshold and smaller outbreak size were obtained.


Filomat ◽  
2017 ◽  
Vol 31 (2) ◽  
pp. 347-361 ◽  
Author(s):  
Yang Li ◽  
Wanbiao Ma ◽  
Liming Xiao ◽  
Weitao Yang

In this paper, based on some biological meaning, triple-negative T cells (TN) and the immature single-positive T cells (CD3-4+8- and CD3-4-8+) have been introduced into well known Mehr?s nonlinear dynamic model which is used to describe proliferation, differentiation and death of T cells in the thymus (Modeling positive and negative selection and differentiation processes in the thymus, Journal of Theoretical Biology, 175 (1995) 103-126), and a class of improved nonlinear dynamic model with seven state variables and time delays has been proposed. Then, by using quasi-steady-state approximation and some classical analysis techniques of functional differential equations, the local and global stability of the equilibrium of the model have been analysed. Finally, some numerical simulations are given to summarize the applications of the theoretical results.


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