Message-passing theory for cooperative epidemics

TL;DR

This paper develops a message-passing framework to analyze the complex dynamics of cooperative epidemics on networks, accurately predicting phase transitions, hysteresis, and optimal seeding strategies for outbreaks.

Contribution

It introduces a novel message-passing method to model two interacting pathogens on networks, capturing complex epidemic phenomena and guiding intervention strategies.

Findings

Accurate predictions of epidemic phase transitions and hysteresis.

Validation of the model through simulations on synthetic networks.

Identification of optimal nodes for infection seeding.

Abstract

The interaction among spreading processes on a complex network is a nontrivial phenomenon of great importance. It has recently been realized that cooperative effects among infective diseases can give rise to qualitative changes in the phenomenology of epidemic spreading, leading for instance to abrupt transitions and hysteresis. Here we consider a simple model for two interacting pathogens on a network and we study it by using the message-passing approach. In this way we are able to provide detailed predictions for the behavior of the model in the whole phase-diagram for any given network structure. Numerical simulations on synthetic networks (both homogeneous and heterogeneous) confirm the great accuracy of the theoretical results. We finally consider the issue of identifying the nodes where it is better to seed the infection in order to maximize the probability of observing an extensive outbreak. The message-passing approach provides an accurate solution also for this problem.