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【精选】光电子技术专业英语光电子技术专业英语
Epidemic Dynamics with Feedback Mechanism in
Exponential Networks ∗
),YAN Jia-Ren(
) † ,ZHANG Jian-Guo( ),WANG Li( )
LIU Zi-Ran(
Department of physics,Hunan Normal University,Changsha 410081
Abstract
In this letter, we introduce a feedback mechanism to study the spreading of
epidemic by analytical methods and large scale simulations in exponential networks.
We find that the introducing of the feedback mechanism can reduce the density of
infected individuals. Furthermore, it doesn’t change the epidemic threshold (critical
point) λc . These results can help us understand epidemic spreading phenomena on
social networks more practically and design appropriate strategies to control social
infections.
PACS: 89.75.Fb, 87.23.Ge, 64.60.Ht
Recently, there has been a burst of activities in the study of complex networks, and a
lot of significant work has been done.[1−3] One of the principle practical applications of the
work has been in modeling the spread of epidemic disease.[4−9] A detailed understanding
of the structure of these networks and dynamics of disease upon them is crucial to the
development of strategies for disease controlling.[10−12] Much completed work is based on
the unchangeable structures of models.[4−12] However, while there is a disease spreading
in the community, being afraid of infected, people will reduce the frequency of going out
to public places consciously. The larger value of density of infected individuals and the
more lethal of the disease will result in less communications. The structures of networks
will be changed according to the feedback information.[13] So we introduce a feedback
mechanism[14] to study epidemic dynamics in expon
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