Immunization Strategies Based on the Overlapping Nodes in Networks with Community Structure

TL;DR

This paper investigates how overlapping community structures in networks influence epidemic spread and evaluates immunization strategies targeting overlapping nodes using real-world data.

Contribution

It provides an empirical analysis of immunization strategies based on overlapping nodes, highlighting their importance in epidemic control within community-structured networks.

Findings

Overlapping nodes significantly impact epidemic spread.

Immunization based on overlapping membership reduces epidemic size.

Overlapping community structures require targeted immunization strategies.

Abstract

Understanding how the network topology affects the spread of an epidemic is a main concern in order to develop efficient immunization strategies. While there is a great deal of work dealing with the macroscopic topological properties of the networks, few studies have been devoted to the influence of the community structure. Furthermore, while in many real-world networks communities may overlap, in these studies non-overlapping community structures are considered. In order to gain insight about the influence of the overlapping nodes in the epidemic process we conduct an empirical evaluation of basic deterministic immunization strategies based on the overlapping nodes. Using the classical SIR model on a real-world network with ground truth overlapping community structure we analyse how immunization based on the membership number of overlapping nodes (which is the number of communities the node belongs to) affect the largest connected component size. Comparison with random immunization strategies designed for networks with non-overlapping community structure show that overlapping nodes play a major role in the epidemic process.