Bita Shams Mohammad Khansari University of Tehran, Faculty of New Science and Technology, Amir Abad, North Kargar Street 14395-1374, Tehran, Iran Network Biology ISSN 2220-8879 http://www.iaees.org/publications/journals/nb/online-version.asp 2014 4 3 74 94 International Academy of Ecology and Environmental Sciences Hong Kong 14 April 2014 17 May 2014 1 September 2014 targeted immunization epidemic spreading network properties centrality measures complex networks Immunization of complex network with minimal or limited budget is a challenging issue for research community. In spite of much literature in network immunization, no comprehensive research has been conducted for evaluation and comparison of immunization algorithms. In this paper, we propose an evaluation framework for immunization algorithms regarding available amount of vaccination resources, goal of immunization program, and time complexity. The evaluation framework is designed based on network topological metrics which is extensible to all epidemic spreading model. Exploiting evaluation framework on well-known targeted immunization algorithms shows that in general, immunization based on PageRank centrality outperforms other targeting strategies in various types of networks, whereas, closeness and eigenvector centrality exhibit the worst case performance. DOI 10.0000/issn-2220-8879-networkbiology-2014-v4-0007 http://www.iaees.org/publications/journals/nb/articles/2014-4(3)/network-properties-to-evaluate-targeted-immunization-algorithms.pdf