Immunization of epidemics in multiplex networks

Dawei Zhao; Lianhai Wang; Shudong Li; Zhen Wang; Lin Wang; Bo Gao

doi:10.1371/journal.pone.0112018

Immunization of epidemics in multiplex networks

PLoS One. 2014 Nov 17;9(11):e112018. doi: 10.1371/journal.pone.0112018. eCollection 2014.

Authors

Dawei Zhao¹, Lianhai Wang¹, Shudong Li², Zhen Wang³, Lin Wang⁴, Bo Gao⁵

Affiliations

¹ Shandong Provincial Key Laboratory of Computer Network, Shandong Computer Science Center (National Supercomputer Center in Jinan), Jinan, China.
² College of Mathematics and Information Science, Shandong Institute of Business and Technology, Shandong, Yantai, China; College of Computer, National University of Defense Technology, Hunan, Changsha, China.
³ Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong; Center for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Center for Nonlinear and Complex systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
⁴ Centre for Chaos and Complex Networks, Department of Electronic Engineering, City University of Hong Kong, Hong Kong.
⁵ School of Computer Information management, Inner Mongolia University of Finance and Economics, Hohhot, China.

Abstract

Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Epidemics*
Humans
Immunization*
Models, Theoretical*

Grants and funding

This paper was supported by the National Natural Science Foundation of China (No. 61202362, 61262057, 61472433; URLs http://www.nsfc.gov.cn/; L. H. W. and S. D. L. received the funding), the Project funded by China Postdoctoral Science Foundation (No. 2013M542560; URLs http://jj.chinapostdoctor.org.cn/V1/Program1/Default.aspx; L. S. D. received the funding), the Natural Science Foundation of Shandong Province (No. ZR2013FM025, ZR2013FQ001, ZR2011FQ030; URLs http://www.sdnsf.gov.cn/portal/; L. H. W. received the funding), and the Shandong Academy of Sciences Youth Fund Project (No. 2013QN007; URLs http://www.sdnsf.gov.cn/portal/; L. H. W. received the funding). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.