Networked SIS Epidemics With Awareness

Keith Paarporn, Ceyhun Eksin, Joshua S. Weitz, Jeff S. Shamma

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


We 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
Original languageEnglish (US)
Pages (from-to)93-103
Number of pages11
JournalIEEE Transactions on Computational Social Systems
Issue number3
StatePublished - Jul 20 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This 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.


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