An efficient immunization strategy based on transmission limit in weighted complex networks

Dongqin Shen and Shanshan Cao

Chaos, Solitons & Fractals, 2018, vol. 114, issue C, 1-7

Abstract: The immunization strategy against the epidemic spreading in real world has attracted widespread attention of scientists from many different fields. However, the traditional immune behavior is achieved by deleting the edges in the network, which can lead to variations in the network structure and consequently serious damage to the efficiency of networks. In this paper, we studied a new type of immune strategy applied to weighted networks, which is to maintain the necessary network efficiency by limit the transmission(reduce the weight of edges) to suppress the spread of epidemic. It is similar to the inflammation around the infected parts of our body, which not only prevent epidemic from further spreading but also do no harm to the function of the body. We first set the rate of transmission be proportional to the edge weight according to the S–I epidemic spreading model. Then, we propose the specific dynamic evolution model for infected nodes that boosts efficient epidemic control. Theoretical analysis and simulation results indicate that the immunization strategy can efficaciously prevent the spread of the epidemic, while maintaining the high efficiency of the network.

Keywords: Weighted network; S–I model; Epidemic controlling; Immunization strategy; Transmission limit (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077918303953
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:114:y:2018:i:c:p:1-7

DOI: 10.1016/j.chaos.2018.06.014

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().