# Directionality reduces the impact of epidemics in multilayer networks

**Authors:** Xiangrong Wang, Alberto Aleta, Dan Lu, and Yamir Moreno

arXiv: 1904.06959 · 2019-04-16

## TL;DR

This paper investigates how directionality in multilayer networks influences epidemic spreading, revealing that link directionality significantly affects the epidemic threshold across various degree distributions.

## Contribution

It introduces the study of directed multilayer networks in epidemiology, highlighting the impact of link directionality on disease spread thresholds, a previously overlooked aspect.

## Key findings

- Directionality significantly affects epidemic thresholds.
- The main determinant of thresholds is link directionality.
- Results are applicable to social and transportation systems.

## Abstract

The study of how diseases spread has greatly benefited from advances in network modeling. Recently, a class of networks known as multilayer graphs has been shown to describe more accurately many real systems, making it possible to address more complex scenarios in epidemiology such as the interaction between different pathogens or multiple strains of the same disease. In this work, we study in depth a class of networks that have gone unnoticed up to now, despite of its relevance for spreading dynamics. Specifically, we focus on directed multilayer networks, characterized by the existence of directed links, either within the layers or across layers. Using the generating function approach and numerical simulations of a stochastic susceptible-infected-susceptible (SIS) model, we calculate the epidemic threshold for these networks for different degree distributions of the networks. Our results show that the main feature that determines the value of the epidemic threshold is the directionality of the links connecting different layers, regardless of the degree distribution chosen. Our findings are of utmost interest given the ubiquitous presence of directed multilayer networks and the widespread use of disease-like spreading processes in a broad range of phenomena such as diffusion processes in social and transportation systems.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1904.06959/full.md

## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/1904.06959/full.md

## References

26 references — full list in the complete paper: https://tomesphere.com/paper/1904.06959/full.md

---
Source: https://tomesphere.com/paper/1904.06959