Immunization Dynamics on a 2-layer Network Model

TL;DR

This paper presents a two-layer network model to study epidemic immunization dynamics, revealing how prevention strategies can reduce outbreaks or, unexpectedly, aid disease survival due to complex interactions.

Contribution

It introduces a novel two-layer network framework combining small-world and scale-free networks to analyze immunization effects in epidemics.

Findings

Prevention can turn large epidemic waves into small fluctuations.

In some cases, prevention may inadvertently support disease persistence.

Two distinct time scales influence the immunization dynamics.

Abstract

We introduce a 2-layer network model for the study of the immunization dynamics in epidemics. Spreading of an epidemic is modeled as an excitatory process in a small-world network (body layer) while immunization by prevention for the disease as a dynamic process in a scale-free network (head layer). It is shown that prevention indeed turns periodic rages of an epidemic into small fluctuation. The study also reveals that, in a certain situation, prevention actually plays an adverse role and helps the disease survive. We argue that the presence of two different characteristic time scales contributes to the immunization dynamics observed.