KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
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AbstractWe study a susceptible-infected-susceptible epidemic process over a static contact network where the nodes have partial information about the epidemic state. They react by limiting their interactions with their neighbors when they believe the epidemic is currently prevalent. A node's awareness is weighted by the fraction of infected neighbors in 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 Markov chains, from which mean-field approximations (MFAs) are derived. The states of the MFA are interpreted as the nodes' probabilities of being infected. We show a sufficient condition for the existence of a
CitationPaarporn K, Eksin C, Weitz JS, Shamma JS (2017) Networked SIS Epidemics With Awareness. IEEE Transactions on Computational Social Systems 4: 93–103. Available: http://dx.doi.org/10.1109/tcss.2017.2719585.
SponsorsThis work was supported in part by the Army Research Office under Grant W911NF-14-1-0402, and in part by the King Abdullah University of Science and Technology.