Dynamical behavior of a stochastic SIQS epidemic model on scale-free networks

Author(s):  
Rundong Zhao ◽  
Qiming Liu ◽  
Meici Sun
2017 ◽  
Vol 381 (47) ◽  
pp. 3945-3951 ◽  
Author(s):  
Huiyan Kang ◽  
Kaihui Liu ◽  
Xinchu Fu

OALib ◽  
2017 ◽  
Vol 04 (05) ◽  
pp. 1-9
Author(s):  
Xiongding Liu ◽  
Tao Li ◽  
Yuanmei Wang ◽  
Chen Wan ◽  
Jing Dong

2021 ◽  
Vol 152 ◽  
pp. 111420
Author(s):  
Changchun Lv ◽  
Ziwei Yuan ◽  
Shubin Si ◽  
Dongli Duan

2017 ◽  
Vol 31 (16) ◽  
pp. 1750131 ◽  
Author(s):  
Fuzhong Nian ◽  
Shuanglong Yao

Based on the stress responses of individuals, the susceptible-infected-susceptible epidemic model was improved on the small-world networks and BA scale-free networks and the simulations were implemented and analyzed. Results indicate that the behaviors of individual’s stress responses could induce the epidemic spreading resistance and adaptation at the network level. This phenomenon showed that networks were learning how to adapt to the disease and the evolution process could improve their immunization to future infectious diseases and would effectively prevent the spreading of infectious diseases.


2008 ◽  
Vol 50 (1) ◽  
pp. 120-124
Author(s):  
Yang Qiu-Ying ◽  
Zhang Gui-Qing ◽  
Zhang Ying-Yue ◽  
Chen Tian-Lun

2011 ◽  
Vol 204-210 ◽  
pp. 354-358 ◽  
Author(s):  
Guang Wu Gong ◽  
Da Min Zhang

A new susceptible-infected-susceptible model with feedback mechanism is proposed. The dynamic behavior of the epidemic model with feedback mechanism in scale-free networks is researched by theoretical analysis and computer simulation. The results show that feedback mechanism can reduce the stable infective ratio of system; however, it can not influence the epidemic threshold of system. The results can help us to understand rightly epidemic spreading process in reality networks and guide people to design effective epidemic preventive and controlling measures when epidemic outbreaks.


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