Temporal percolation of a susceptible adaptive network

L.D. Valdez, P.A. Macri and L.A. Braunstein

Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, issue 18, 4172-4180

Abstract: In the past decades, many authors have used the susceptible–infected–recovered model to study the impact of the disease spreading on the evolution of the infected individuals. However, few authors focused on the temporal unfolding of the susceptible individuals. In this paper, we study the dynamic of the susceptible–infected–recovered model in an adaptive network that mimics the transitory deactivation of permanent social contacts, such as friendship and work-ship ties. Using an edge-based compartmental model and percolation theory, we obtain the evolution equations for the fraction susceptible individuals in the susceptible biggest component. In particular, we focus on how the individual’s behavior impacts on the dilution of the susceptible network. We show that, as a consequence, the spreading of the disease slows down, protecting the biggest susceptible cluster by increasing the critical time at which the giant susceptible component is destroyed. Our theoretical results are fully supported by extensive simulations.

Keywords: Epidemic models; Percolation; Adaptive networks (search for similar items in EconPapers)
Date: 2013
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:392:y:2013:i:18:p:4172-4180

DOI: 10.1016/j.physa.2013.05.003

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