论文标题
随机共互联-19流行病模型的动力学
Dynamics of a Stochastic COVID-19 Epidemic Model with Jump-Diffusion
论文作者
论文摘要
对于带有跳跃的随机Covid-19模型，我们证明了全球积极解决方案的存在和独特性。我们还研究了疾病灭绝和持久性的一些条件。我们计算了随机流行系统的阈值，该系统决定了随机噪声的不同强度下疾病的灭绝或永久性。该阈值用$ξ$表示，该$取决于白色和跳噪声。研究了这些噪声对模型动力学的影响。数值实验表明，与其确定性对应物相比，随机模型中引入的随机扰动抑制了疾病的暴发。换句话说，噪声对灭绝和持久性的影响很高。当噪声大小时，我们的数字发现表明，如果$ξ<1; $; $从人群中消失，而如果$ξ> 1. $ 1. $。从中，我们观察到白噪声和跳跃噪声对COVID-19感染的传播产生了重大影响，即我们可以比以前的模型更为现实。最后，为了说明这一现象，我们放了一些数值模拟。
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.
