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A biologically inspired immunization strategy for network epidemiology
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Title: | A biologically inspired immunization strategy for network epidemiology |
Authors: | Liu, Yang Browse this author | Deng, Yong Browse this author | Jusup, Marko Browse this author | Wang, Zhen Browse this author |
Keywords: | Infectious agent | Physarum polycephalum | Heterogeneous topology | Degree centrality | Betweenness centrality | Closeness centrality | SIR model |
Issue Date: | 7-Jul-2016 |
Publisher: | Elsevier |
Journal Title: | Journal of theoretical biology |
Volume: | 400 |
Start Page: | 92 |
End Page: | 102 |
Publisher DOI: | 10.1016/j.jtbi.2016.04.018 |
PMID: | 27113785 |
Abstract: | Well-known immunization strategies, based on degree centrality, betweenness centrality, or closeness centrality, either neglect the structural significance of a node or require global information about the network. We propose a biologically inspired immunization strategy that circumvents both of these problems by considering the number of links of a focal node and the way the neighbors are connected among themselves. The strategy thus measures the dependence of the neighbors on the focal node, identifying the ability of this node to spread the disease. Nodes with the highest ability in the network are the first to be immunized. To test the performance of our method, we conduct numerical simulations on several computer-generated and empirical networks, using the susceptible-infected-recovered (SIR) model. The results show that the proposed strategy largely outperforms the existing well-known strategies. |
Rights: | (C) 2016 Elsevier Ltd. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Type: | article (author version) |
URI: | http://hdl.handle.net/2115/66491 |
Appears in Collections: | 電子科学研究所 (Research Institute for Electronic Science) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: Marko Jusup
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