Epidemic paradox induced by awareness driven network dynamics

TL;DR

This paper investigates how awareness-driven behaviors in network models can paradoxically reduce epidemic sizes, revealing that fewer aware nodes can sometimes be more effective in controlling outbreaks.

Contribution

It introduces a novel epidemic model incorporating awareness dynamics and demonstrates the paradoxical effect where fewer aware nodes lead to smaller epidemics.

Findings

Epidemic size scales linearly with network size in susceptible-aware and all-aware models.

Epidemic size scales sublinearly in infected-aware models.

Influential nodes and disassortativity enhance epidemic awareness.

Abstract

We study stationary epidemic processes in scale-free networks with local awareness behavior adopted by only susceptible, only infected, or all nodes. We find that while the epidemic size in the susceptible-aware and the all-aware models scales linearly with the network size, the scaling becomes sublinear in the infected-aware model. Hence, fewer aware nodes may reduce the epidemic size more effectively; a phenomenon reminiscent of Braess's paradox. We present numerical and theoretical analysis, and highlight the role of influential nodes and their disassortativity to raise epidemic awareness.