An immunization based on node activity

Fuzhong Nian, Chasheng Hu, Shuanglong Yao, Longjing Wang and Xingyuan Wang

Chaos, Solitons & Fractals, 2018, vol. 107, issue C, 228-233

Abstract: In this paper, a standard susceptible-infected-recovered-susceptible (SIRS) epidemic model based on the dynamic network model is established. The dynamic network based on the Barabasi–Albert (BA) scale-free network model is constructed, keeping the same total number of edges, adding and deleting edges are operated according to the corresponding node activity level. These operations also can change the node activity. At the same time, a new immunization scheme - “immunization based on node activity” is proposed, in which the nodes with most active be immunized firstly. The propagation situations of random immunization, immunization based on node activity and high-risk immunization are investigated, the influence of some parameters on the density of infected individuals is also analyzed in detail. When the number of immunization nodes is the same, the results show that the effect of immunization based on node activity is the best. Therefore, immunization based on node activity is effective, and it is more feasible in dynamic network.

Keywords: Epidemic; Dynamic network; Immunization; Node activity; SIRS (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077918300134
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:107:y:2018:i:c:p:228-233

DOI: 10.1016/j.chaos.2018.01.013

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. ().