The Cost of Uncertainty in Curing Epidemics
The Cost of Uncertainty in Curing Epidemics
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DOI：
10.1145/3219617.3219622
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发表时间：
2017-11
期刊：
影响因子：
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通讯作者：
Jessica Hoffmann;C. Caramanis
中科院分区：
文献类型：
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作者：
Jessica Hoffmann;C. Caramanis
流行病模型被用于生物和社会科学，工程和计算机科学，并在人类疾病和计算机病毒的动态研究中产生了重要影响，而且还对谣言，病毒视频以及最近社交网络上假新闻的传播产生了重要影响。在本文中，我们专注于在图上传播的流行病，正如开创性论文[5]所介绍的那样。特别是，我们考虑所谓的SI模型（见下文的精确定义），其中受感染的节点只能将感染传播到其未受感染的邻居，而不是早期文献中考虑的完全混合模型。这种基于图的方法提供了一个更真实的模型，其中流行病的传播由图的连通性决定，因此某些节点可能在感染传播中发挥比其他节点更大的作用。
Epidemic models are used across biological and social sciences, engineering, and computer science, and have had important impact in the study of the dynamics of human disease and computer viruses, but also trends rumors, viral videos, and most recently the spread of fake news on social networks. In this paper, we focus on epidemics propagating on a graph, as introduced by the seminal paper [5]. In particular, we consider so-called SI models (see below for a precise definition) where an infected node can only propagate the infection to its non-infected neighbor, as opposed to the fully mixed models considered in the early literature. This graph-based approach provides a more realistic model, in which the spread of the epidemic is determined by the connectivity of the graph, and accordingly some nodes may play a larger role than others in the spread of the infection.