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Simulation of COVID-19 epidemic spread using Stochastic Differential Equations with Jump diffusion for SIR Model

机译:利用SIR模型跳跃扩散的随机微分方程模拟Covid-19流行病

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Mathematical epidemiology is one of the most important research areas, it has contributed to understanding the behavior and the impact also the prediction of infectious disease. One of the fundamental methods intended to see the behavior of the pandemic is the susceptible–infectious–recovered epidemic model. However, the deterministic approach of this model has some limitations in mathematical modeling, for that we propose to add a stochastic variation in SIR equations. In this paper we present a stochastic differential equation with jump-diffusion formula for COVID-19, then we estimate the parameters of our stochastic susceptible–infected–recovered model. Finally, we compare our result with real covid19 spread in Morocco.
机译:数学流行病学是最重要的研究领域之一,它有助于了解行为和影响也对传染病的预测。 旨在看到大流行行为的基本方法之一是敏感传染性恢复的流行病模型。 然而,该模型的确定性方法在数学建模中具有一些局限性,因为我们建议在SIR方程中添加随机变化。 本文介绍了一种随机微分方程,具有Covid-19的跳跃扩散公式,然后估计了我们随机敏感感染恢复模型的参数。 最后,我们将结果与真正的Covid19在摩洛哥传播。

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