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Improving immunization strategies

Lazaros K. Gallos, Fredrik Liljeros, Panos Argyrakis, Armin Bunde, and Shlomo Havlin
Phys. Rev. E 75, 045104(R) – Published 19 April 2007

Abstract

We introduce an immunization method where the percentage of required vaccinations for immunity are close to the optimal value of a targeted immunization scheme of highest degree nodes. Our strategy retains the advantage of being purely local, without the need for knowledge on the global network structure or identification of the highest degree nodes. The method consists of selecting a random node and asking for a neighbor that has more links than himself or more than a given threshold and immunizing him. We compare this method to other efficient strategies on three real social networks and on a scale-free network model and find it to be significantly more effective.

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  • Received 14 February 2006

DOI:https://doi.org/10.1103/PhysRevE.75.045104

©2007 American Physical Society

Authors & Affiliations

Lazaros K. Gallos1, Fredrik Liljeros2, Panos Argyrakis1, Armin Bunde3, and Shlomo Havlin4

  • 1Department of Physics, University of Thessaloniki, 54124 Thessaloniki, Greece
  • 2Department of Sociology, Stockholm University, 106 91 Stockholm, Sweden
  • 3Institut für Theoretische Physik III, Justus-Liebig-Universität Giessen, Heinrich-Buff-Ring 16, 35392 Giessen, Germany
  • 4Minerva Center and Department of Physics, Bar-Ilan University, 52900 Ramat-Gan, Israel

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Issue

Vol. 75, Iss. 4 — April 2007

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