In Response to COVID-19: Configuration Model of the Epidemic Spreading

TL;DR

This paper introduces a configuration model based on scale-free networks to analyze COVID-19 epidemic spread, providing analytical solutions for different dynamic regimes and demonstrating its predictive capabilities.

Contribution

It presents a novel configuration model for epidemic spreading on scale-free networks with analytical solutions and applies it specifically to COVID-19.

Findings

Identifies unstable and stable epidemic regimes

Demonstrates regime interchangeability during outbreaks

Shows predictive accuracy for COVID-19 spread

Abstract

A configuration model for epidemic spread, based on a scale-free network, is introduced. We obtain the analytical solutions describing both unstable and stable dynamics of the epidemic spreading, and demonstrate how these regimes can interchange during the epidemic. We apply the model to the COVID-19 case and demonstrate the predictive features of our model.