The effect of awareness on networked SIS epidemics
The effect of awareness on networked SIS epidemics
复制标题
意识对网络 SIS 流行病的影响
DOI：
10.1109/cdc.2016.7798394
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
J. Shamma
中科院分区：
文献类型：
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作者：
Keith Paarporn;Ceyhun Eksin;J. Weitz;J. Shamma
我们研究了任意固定网络拓扑上的SIS流行病模型，其中n个代理或网络节点具有关于流行病状态的部分信息。当这些代理人认为疫情目前很流行时，他们的反应是与邻居保持距离。代理的感知是从三个信息来源加权的：他们联系网络中受感染邻居的比例，他们的社交网络，以及整个网络中受感染节点比例的全局广播。用离散时间2n状态马尔可夫链描述了基准(无感知)和感知模型的动态特性。通过耦合技术，我们建立了基准模型和感知模型之间的单调性。特别地，我们证明了对于感知模型，样本路径空间上任何增加的随机变量，例如根除时间或感染总数的期望都较低。此外，我们还从耦合分布的角度给出了这种期望差异的刻画。在模拟中，我们评估不同的信息来源如何影响流行病的传播。
We study an SIS epidemic model over an arbitrary fixed network topology where the n agents, or nodes of the network, have partial information about the epidemic state. The agents react by distancing themselves from their neighbors when they believe the epidemic is currently prevalent. An agent's awareness is weighted from three sources of information: the fraction of infected neighbors in their contact network, their social network, and a global broadcast of the fraction of infected nodes in the entire network. The dynamics of the benchmark (no awareness) and awareness models are described by discrete-time 2n-state Markov chains. Through a coupling technique, we establish monotonicity properties between the benchmark and awareness models. Particularly, we show that the expectation of any increasing random variable on the space of sample paths, e.g. eradication time or total infections, is lower for the awareness model. In addition, we give a characterization for this difference of expectations in terms of the coupling distribution. In simulations, we evaluate how different sources of information affect the spread of an epidemic.