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Novel SIVR epidemic spreading model with virus variation in complex networks

机译:复杂网络中带有病毒变异的新型SIVR流行传播模型

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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.
机译:最近的研究发现,病毒变异与流行之间有着紧密的联系。生物进化,生态环境和医疗资源将导致传播过程中的流行病变异。复杂的网络描绘了传染病在社会中传播的多种相互作用。为了研究带有病毒变异的流行传播的动力学,提出了一种新的流行传播SIVR模型(易感-感染-变异-恢复)。该模型在考虑流行病传播过程中两种不同病毒的变异影响的基础上,扩展了经典的易感传染病(SIR)流行病传播模型。通过描述复杂网络中可变病毒的动力学行为,推导了SIVR模型的均场方程。然后对该模型进行稳态分析,以研究在不同传播率,恢复率,变异率和平均网络度下的流行传播过程。同时,针对同质网络中的免疫阈值,讨论了不同的流行病免疫策略。进行了数值模拟,以说明流行病传播因素之间的关系。结果在预防和控制可变病毒的传播中起着重要作用。

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