A Convex Framework for Optimal Investment on Disease Awareness in Social Networks

TL;DR

This paper introduces a convex optimization framework to determine the most cost-effective way to invest in disease awareness in social networks, aiming to control epidemic spread effectively.

Contribution

It models epidemic control via awareness using an extended SAIS model and develops a convex method for optimal resource allocation based on network eigenvalues.

Findings

Convex framework effectively finds optimal awareness investment.

Numerical validation on real social network data.

Control conditions derived from eigenvalue analysis.

Abstract

We consider the problem of controlling the propagation of an epidemic outbreak in an arbitrary network of contacts by investing on disease awareness throughout the network. We model the effect of agent awareness on the dynamics of an epidemic using the SAIS epidemic model, an extension of the SIS epidemic model that includes a state of "awareness". This model allows to derive a condition to control the spread of an epidemic outbreak in terms of the eigenvalues of a matrix that depends on the network structure and the parameters of the model. We study the problem of finding the cost-optimal investment on disease awareness throughout the network when the cost function presents some realistic properties. We propose a convex framework to find cost-optimal allocation of resources. We validate our results with numerical simulations in a real online social network.