DocumentCode
724528
Title
Novel SIVR epidemic spreading model with virus variation in complex networks
Author
Degang Xu ; Xiyang Xu ; Zhifang Su
Author_Institution
Coll. of Inf. Sci. & Eng., Central South Univ., Changsha, China
fYear
2015
fDate
23-25 May 2015
Firstpage
5164
Lastpage
5169
Abstract
Recent researches find that there are tight relations between virus variation and epidemic. Creature evolution, ecological environment and medical sources will lead to epidemic variation in the spreading process. Complex networks portray a multitude of interactions through which infectious diseases propagate in a society. In order to study the dynamics of epidemic spreading with virus variation, a new epidemic spreading SIVR model (Susceptible-Infective-Variant-Recovery) is proposed. This model extends the classical Susceptible-Infectious-Recovery (SIR) epidemic spreading model with considering variation affection of two different virus in the process of epidemic spreading. Mean-field equations of SIVR model are derived by describing the dynamics behaviors of the variable virus in complex networks. Then steady-state analysis for this model is conducted to investigate the process of epidemic spreading under different spreading rate, recovery rate, variant rate, and the average degree of networks. Meanwhile, different epidemic immunization strategies are discussed for the immunization threshold in homogeneous networks. Numerical simulations are conducted to illustrate the relationship between the factors of the epidemic spreading. The results play an important role in preventing and controlling the spreading of variable virus.
Keywords
complex networks; diseases; epidemics; network theory (graphs); SIR; SIVR epidemic spreading model; complex networks; creature evolution; ecological environment; epidemic immunization strategies; infectious diseases; medical sources; recovery rate; spreading process; spreading rate; susceptible-infectious-recovery epidemic spreading model; susceptible-infective-variant-recovery; variable virus; variant rate; virus variation; Biological system modeling; Complex networks; Electronic mail; Immune system; Mathematical model; Numerical models; Steady-state; Epidemic spreading; Immunization strategy; SIVR model; Variant rate; virus variation;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7162845
Filename
7162845
Link To Document