Modeling the Dynamics of Infectious Diseases in Different Scale-Free Networks with the Same Degree Distribution

TL;DR

This study investigates how the topological structure of scale-free networks influences infectious disease spread, revealing that different network structures can significantly alter epidemic dynamics despite identical degree distributions.

Contribution

It introduces a comparison of disease dynamics across various scale-free networks generated by different algorithms, highlighting the impact of network topology on epidemic spread.

Findings

Network topology significantly affects disease spread dynamics.

Different algorithms produce networks with similar degree distributions but different epidemic outcomes.

The same degree distribution does not guarantee similar epidemic behavior.

Abstract

The transmission dynamics of some infectious diseases is related to the contact structure between individuals in a network. We used five algorithms to generate contact networks with different topological structure but with the same scale-free degree distribution. We simulated the spread of acute and chronic infectious diseases on these networks, using SI (Susceptible - Infected) and SIS (Susceptible - Infected - Susceptible) epidemic models. In the simulations, our objective was to observe the effects of the topological structure of the networks on the dynamics and prevalence of the simulated diseases. We found that the dynamics of spread of an infectious disease on different networks with the same degree distribution may be considerably different.