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Suppressing the endemic equilibrium in SIS epidemics: A state dependent approach

机译:抑制SIS流行病的流行均衡:状态依赖性方法

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This paper considers the susceptible-infected-susceptible (SIS) epidemic model with an underlying network structure and focuses on the effect of social distancing to regulate the epidemic level. We demonstrate that if each subpopulation is informed of its infection rate and reduces interactions accordingly, the fraction of the subpopulation infected stays below half for all time instants. To this end, we first modify the basic SIS model by introducing a state dependent parameter representing the frequency of interactions between subpopulations. Thereafter, we show that for this modified SIS model, the spectral radius of a suitably-defined matrix being not greater than one causes all the agents, regardless of their initial sickness levels, to converge to the healthy state; assuming non-trivial disease spread, the spectral radius being greater than one leads to the existence of a unique endemic equilibrium, which is also asymptotically stable. Finally, by leveraging the aforementioned results, we show that the fraction of (sub)populations infected never exceeds half.
机译:本文考虑了具有潜在网络结构的敏感感染易感(SIS)疫情模型,并专注于社会远程对流行水平的影响。我们证明,如果每个亚贫困人员被告知其感染率并相应地减少相互作用,则感染的亚群的分数低于一半的时间,以进行所有时间瞬间。为此,我们首先通过引入表示子步骤之间的交互频率的状态相关参数来修改基本SIS模型。此后,我们表明,对于该修改的SIS模型,适当定义的矩阵的光谱半径不大于一个,导致所有药剂,无论其初始疾病水平如何,都会收敛到健康状态;假设非琐碎的疾病扩散,光谱半径大于一个,导致存在独特的流体平衡,这也是渐近稳定的。最后,通过利用上述结果,我们表明感染的(子)种群的一部分从未超过一半。

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