论文标题
具有无症状载体的时间网络上的广义SIS流行模型，并评论衰减比
A Generalized SIS Epidemic Model on Temporal Networks with Asymptomatic Carriers and Comments on Decay Ratio
论文作者
论文摘要
我们研究了SIS流行在时间网络上的类别，并提出了一种新的活动驱动和适应性流行病模型，该模型捕获了网络中无症状和传染性个体的影响。在提议的模型中，称为A-SIYS流行病，每个节点都可以在三种可能的状态中：易感性，无症状或无症状的感染，并感染症状或症状。无症状和有症状的个体都是传染性的。我们表明，拟议的A-SIYS流行病捕获了几种良好的流行病模型作为特殊情况，并获得了足够的条件，在这些情况下，通过诉诸于平均场近似值来消除该疾病。 此外，我们强调了在活动驱动的自适应SIS（A-SIS）模型（Oguraet。Al。，2019年）中的衰减比的推导中的潜在不准确性，并呈现其结果的更一般版本。我们从数值上说明了A-SIS流行模型中感染节点的比例的演变，并表明（Ogura等人，2019年）中的结合通常无法捕获流行病的行为与我们的结果相反。
We study the class of SIS epidemics on temporal networks and propose a new activity-driven and adaptive epidemic model that captures the impact of asymptomatic and infectious individuals in the network. In the proposed model, referred to as the A-SIYS epidemic, each node can be in three possible states: susceptible, infected without symptoms or asymptomatic and infected with symptoms or symptomatic. Both asymptomatic and symptomatic individuals are infectious. We show that the proposed A-SIYS epidemic captures several well-established epidemic models as special cases and obtain sufficient conditions under which the disease gets eradicated by resorting to mean-field approximations. In addition, we highlight a potential inaccuracy in the derivation of the upper bound on the decay ratio in the activity-driven adaptive SIS (A-SIS) model in (Ogura et. al., 2019) and present a more general version of their result. We numerically illustrate the evolution of the fraction of infected nodes in the A-SIS epidemic model and show that the bound in (Ogura et. al., 2019) often fails to capture the behavior of the epidemic in contrast with our results.
