Abstract

A model for the transmission dynamics of Ebola virus in a multipatch network setting is studied. The model considers the contribution to the dynamics by people who are susceptible, infectious, isolated, deceased but still infectious and not yet buried, as well as the dynamics of the pathogen at interacting nodes or patches. Humans can move between patches carrying the disease to any patch in a region of n communities (patches). Both direct and indirect transmission are accounted for in this model. Matrix and graph-theoretic methods and some combinatorial identities are used to construct appropriate Lyapunov functions to establish global stability results for both the disease-free and the endemic equilibrium of the model. While the model is focused on Ebola, it can be adapted to the study of other disease epidemics, including COVID-19, currently affecting all countries in the world.

Department(s)

Mathematics

Document Type

Article

DOI

https://doi.org/10.1515/msds-2020-0129

Rights Information

© 2021 the author; published by De Gruyter. This work is licensed under the Creative Commons Attribution alone 4.0 License.

Keywords

Ebola virus, global stability, Lyapunov functions, viral infections

Publication Date

1-1-2021

Journal Title

Nonautonomous Dynamical Systems

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