Suppressing epidemics with a limited amount of immunization units.
The way diseases spread through schools, epidemics through countries, and viruses through the internet is crucial in determining their risk. Although each of these threats has its own characteristics, its underlying network determines the spreading. To restrain the spreading, a widely used approach is the fragmentation of these networks through immunization, so that epidemics cannot spread. Here we develop an immunization approach based on optimizing the susceptible size, which outperforms the best known strategy based on immunizing the highest-betweenness links or nodes. We find that the network's vulnerability can be significantly reduced, demonstrating this on three different real networks: the global flight network, a school friendship network, and the internet. In all cases, we find that not only is the average infection probability significantly suppressed, but also for the most relevant case of a small and limited number of immunization units the infection probability can be reduced by up to 55%.
Computational Physics, IfB, ETH Zurich, Schafmattstrasse 6, CH-8093 Zurich, Switzerland. schnechr@ethz.ch
Christian M
CM
Schneider
Tamara
T
Mihaljev
Shlomo
S
Havlin
Hans J
HJ
Herrmann
D058872:Epidemics / Q000517:prevention & control*; D006801:Humans; D007114:Immunization / Q000379:methods*; D008962:Models, Theoretical