Efficient Immunization Strategies for Computer Networks and Populations

TL;DR

This paper introduces an acquaintance immunization strategy that effectively reduces the threshold for immunization in networks, especially scale-free ones, without requiring global network knowledge.

Contribution

The paper proposes a novel immunization method based on random acquaintances, which is simpler and more practical than targeted strategies, and demonstrates its effectiveness analytically.

Findings

Immunization threshold is significantly lowered using the proposed strategy.

The strategy is effective across various network types, including scale-free networks.

No global network knowledge is needed for implementation.

Abstract

We present an effective immunization strategy for computer networks and populations with broad and, in particular, scale-free degree distributions. The proposed strategy, acquaintance immunization, calls for the immunization of random acquaintances of random nodes (individuals). The strategy requires no knowledge of the node degrees or any other global knowledge, as do targeted immunization strategies. We study analytically the critical threshold for complete immunization. We also study the strategy with respect to the susceptible-infected-removed epidemiological model. We show that the immunization threshold is dramatically reduced with the suggested strategy, for all studied cases.