Epidemic spreading on weighted networks with adaptive topology based on infective information

Yun Feng, Li Ding, Yun-Han Huang and Li Zhang

Physica A: Statistical Mechanics and its Applications, 2016, vol. 463, issue C, 493-502

Abstract: In this paper, we consider epidemic spreading on a weighted adaptive network in which the network topology varies according to the global and local infective information of individuals. We focus on the relationship between network topology and epidemic spreading. Interacting strength is defined to evaluate the level of how individuals’ infective information taking effects on their connections. The model is analyzed by discrete-time Monte-Carlo simulations with an initial BA scale-free network. It is found that greater interacting strength leads to higher epidemic threshold, lower average disease density of steady-state and shorter epidemic prevalent decay time. Besides, the interaction tends to change the initial BA scale-free network to a fat-tail network while the scaling exponent almost keeps unchanged. In addition, individual who reacts with local infective information will significantly restrain the outbreak of disease comparing to the one with global infective information, and this phenomenon becomes more notable if the interacting strength becomes greater.

Keywords: Epidemic spreading; SIS model; Adaptive topology; Infective information (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:463:y:2016:i:c:p:493-502

DOI: 10.1016/j.physa.2016.07.072

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