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Title System Dynamics of a Refined Epidemic Model for Infection Propagation over Complex Networks
Journal Name IEEE Systems Journal
First Author Aresh Dadlani
Coauthor Muthukrishnan Senthil Kumar, Suvi Murugan, Kiseon Kim
Publication Date 2014.05.08 Link Link icon
Impact Factor (%) 1.746 Date 2014-05-22 14:02
The ability to predict future epidemic threats, both in real as well as digital worlds, and to develop effective containment strategies heavily leans on the availability of reliable infection spreading models. The stochastic behavior of such processes make them even more demanding to scrutinize over structured networks. This paper concerns the dynamics of a new susceptible-infected-susceptible (SIS) epidemic model incorporated with multi-stage infection (infection delay) and an infective medium (propagation vector) over complex networks. In particular, we investigate the critical epidemic thresholds and the infection spreading pattern using mean-field approximation and results obtained through extensive numerical simulations. We further generalize the model for any arbitrary number of infective media to mimic existing scenarios in biological and social networks. Our analysis and simulation results reveal that the inclusion of multiple infective medium and multiple stages of infection significantly alleviates the epidemic threshold and thus, accelerates the process of infection spreading in the population.
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