Competitive epidemic networks with multiple survival-of-the-fittest outcomes

We use a deterministic model to study two competing viruses spreading over a two-layer network in the Susceptible--Infected--Susceptible (SIS) framework, and address a central problem of identifying the winning virus in a "survival-of-the-fittest" battle. Existing sufficient conditions ensure that the same virus always wins regardless of initial states. For networks with an arbitrary but finite number of nodes, there exists a necessary and sufficient condition that guarantees local exponential stability of the two equilibria corresponding to each virus winning the battle, meaning that either of the viruses can win, depending on the initial states. However, establishing existence and finding examples of networks with more than three nodes that satisfy such a condition has remained unaddressed. In this paper, we prove that, for any arbitrary number of nodes, such networks exist. We do this by proving that given almost any network layer of one virus, there exists a network layer for the other virus such that the resulting two-layer network satisfies the aforementioned condition. To operationalize our findings, a four-step procedure is developed to reliably and consistently design one of the network layers, when given the other layer. Conclusions from numerical case studies, including a real-world mobility network that captures the commuting patterns for people between $107$ provinces in Italy, extend on the theoretical result and its consequences..

Medienart:

Preprint

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

arXiv.org - (2021) vom: 11. Nov. Zur Gesamtaufnahme - year:2021

Sprache:

Englisch

Beteiligte Personen:

Ye, Mengbin [VerfasserIn]
Anderson, Brian D. O. [VerfasserIn]
Janson, Axel [VerfasserIn]
Gracy, Sebin [VerfasserIn]
Johansson, Karl H. [VerfasserIn]

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Themen:

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510
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Computer Science - Systems and Control
Electrical Engineering and Systems Science - Systems and Control
Mathematics - Dynamical Systems

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XAR033011524