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Main Authors: Tesfay, Almaz, Saeed, Tareq, Zeb, Anwar, Tesfay, Daniel, Khalaf, Anas, Brannan, James
Format: Preprint
Published: 2020
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Online Access:https://arxiv.org/abs/2011.06280
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author Tesfay, Almaz
Saeed, Tareq
Zeb, Anwar
Tesfay, Daniel
Khalaf, Anas
Brannan, James
author_facet Tesfay, Almaz
Saeed, Tareq
Zeb, Anwar
Tesfay, Daniel
Khalaf, Anas
Brannan, James
contents For a stochastic COVID-19 model with jump-diffusion, we prove the existence and uniqueness of the global positive solution. We also investigate some conditions for the extinction and persistence of the disease. We calculate the threshold of the stochastic epidemic system which determines the extinction or permanence of the disease at different intensities of the stochastic noises. This threshold is denoted by $ξ$ which depends on the white and jump noises. The effects of these noises on the dynamics of the model are studied. The numerical experiments show that the random perturbation introduced in the stochastic model suppresses disease outbreaks as compared to its deterministic counterpart. In other words, the impact of the noises on the extinction and persistence is high. When the noise is large or small, our numerical findings show that the COVID-19 vanishes from the population if $ξ<1;$ whereas the epidemic can't go out of control if $ξ>1.$ From this, we observe that white noise and jump noise have a significant effect on the spread of COVID-19 infection, i.e., we can conclude that the stochastic model is more realistic than the deterministic one. Finally, to illustrate this phenomenon, we put some numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2011_06280
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Dynamics of a Stochastic COVID-19 Epidemic Model with Jump-Diffusion
Tesfay, Almaz
Saeed, Tareq
Zeb, Anwar
Tesfay, Daniel
Khalaf, Anas
Brannan, James
Populations and Evolution
Dynamical Systems
Physics and Society
39A50, 45K05, 65N22
For a stochastic COVID-19 model with jump-diffusion, we prove the existence and uniqueness of the global positive solution. We also investigate some conditions for the extinction and persistence of the disease. We calculate the threshold of the stochastic epidemic system which determines the extinction or permanence of the disease at different intensities of the stochastic noises. This threshold is denoted by $ξ$ which depends on the white and jump noises. The effects of these noises on the dynamics of the model are studied. The numerical experiments show that the random perturbation introduced in the stochastic model suppresses disease outbreaks as compared to its deterministic counterpart. In other words, the impact of the noises on the extinction and persistence is high. When the noise is large or small, our numerical findings show that the COVID-19 vanishes from the population if $ξ<1;$ whereas the epidemic can't go out of control if $ξ>1.$ From this, we observe that white noise and jump noise have a significant effect on the spread of COVID-19 infection, i.e., we can conclude that the stochastic model is more realistic than the deterministic one. Finally, to illustrate this phenomenon, we put some numerical simulations.
title Dynamics of a Stochastic COVID-19 Epidemic Model with Jump-Diffusion
topic Populations and Evolution
Dynamical Systems
Physics and Society
39A50, 45K05, 65N22
url https://arxiv.org/abs/2011.06280