For a stochastic COVID-19 model with jump-diffusion, we prove the existence and uniqueness of the global positive solution of the model . We also investigate some conditions for the extinction and persistence of the disease. We calculate the threshold of the  epidemic system which determines the extinction or permanence of the disease at different intensities of the stochastic noises. This threshold is denoted by \xi that depends on the white and jump noises.  When the noise is large or small, our numerical findings show that the COVID-19 vanishes from the people if \xi <1; whereas control the epidemic diseases if \xi >1. From this, we observe that white noise and jump noise have a significant effect on the spread of COVID-19 infection . To illustrate this phenomenon, we put some numerical simulations.
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 \xi 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 \xi <1; whereas the epidemic can't go out of control if \xi >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.
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of the model
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stochastic
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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.
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people
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control the epidemic diseases
the epidemic can't go out of control
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, i.e., we can conclude that the stochastic model is more realistic than the deterministic one. Finally, to