Finding a Better Immunization Strategy

2008/07/31 by Yiping Chen, Gerald Paul, Shlomo Havlin +2 · 309 citations
Physics and Astronomy · Biochemistry, Genetics and Molecular Biology · Social Sciences · Medicine · Mathematics · #Complex Network Analysis Techniques #Bioinformatics and Genomic Networks #Misinformation and Its Impacts #Immunization #Computer science #Graph #Population #Mathematical optimization #Theoretical computer science #Medicine #Immunology #Mathematics

paper · doi:10.1103/physrevlett.101.058701

published in Physical Review Letters 101(5), 058701 (American Physical Society)

openalex publication_date 2008/07/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/11

Abstract

The problem of finding the best strategy to immunize a population or a computer network with a minimal number of immunization doses is of current interest. It has been accepted that the targeted strategies on most central nodes are most efficient for model and real networks. We present a newly developed graph-partitioning strategy which requires 5% to 50% fewer immunization doses compared to the targeted strategy and achieves the same degree of immunization of the network. We explicitly demonstrate the effectiveness of our proposed strategy on several model networks and also on real networks.

Citations

• Random Graphs
• Percolation theory applied to measures of fragmentation in social networks
• Spread of epidemic disease on networks
• Efficient Immunization Strategies for Computer Networks and Populations
• Immunization of complex networks
• A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
• Efficient local strategies for vaccination and network attack
• Statistical mechanics of complex networks
• A contribution to the mathematical theory of epidemics
• On random graphs. I.

Cited by

• Effective vaccination strategy using graph neural network ansatz
• Graph partition [wikipedia]