Equilibria analysis of a networked bivirus epidemic model using Poincar\'e--Hopf and Manifold Theory
Brian D.O. Anderson, Mengbin Ye

TL;DR
This paper analyzes the complex equilibrium patterns of a two-virus epidemic model on networks, employing advanced topological methods to establish bounds and stability properties of coexistence states.
Contribution
It introduces novel counting and stability results for coexistence equilibria in a bivirus network model using Poincaré-Hopf and Morse theory, addressing gaps in existing research.
Findings
Lower bounds on the number of coexistence equilibria
Properties of local stability and instability of equilibria
Numerical demonstrations of multiple attractors and coexistence states
Abstract
This paper considers a deterministic Susceptible-Infected-Susceptible (SIS) networked bivirus epidemic model (termed the bivirus model for short), in which two competing viruses spread through a set of populations (nodes) connected by two graphs, which may be different if the two viruses have different transmission pathways. The networked dynamics can give rise to complex equilibria patterns, and most current results identify conditions on the model parameters for convergence to the healthy equilibrium (where both viruses are extinct) or a boundary equilibrium (where one virus is endemic and the other is extinct). However, there are only limited results on coexistence equilibria (where both viruses are endemic). This paper establishes a set of ``counting'' results which provide lower bounds on the number of coexistence equilibria, and perhaps more importantly, establish properties on…
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Taxonomy
TopicsMathematical and Theoretical Epidemiology and Ecology Models · Evolution and Genetic Dynamics · COVID-19 epidemiological studies
