论文标题
延迟的Seirds流行病模型的数学分析：确定性和随机方法
Mathematical analysis of a delayed SEIRDS epidemics models: deterministic and stochastic approach
论文作者
论文摘要
这项研究的主要目的是研究延迟对易感暴露感染的死亡和易感（SEIRD）模型的动态的影响，我们为此添加了一个随机项以说明COVID-19参数估计中的不确定性。我们运行了两个模型，一种确定性和一个随机性，并表明它们的解决方案存在并且是独特的。我们还在数字上研究了免疫丧失对新波的新兴时间的影响，以及疾病灭绝和持久性的必要条件。
The primary goal of this research is to investigate the impact of delay on the dynamics of the Susceptible-Exposed-Infected-Recovered-Death and Susceptible (SEIRDS) model, to which we add a stochastic term to account for uncertainty in COVID-19 parameter estimations. We run two models, one deterministic and one stochastic, and show that their solutions exist and are unique. We also numerically investigate the impact of immunity loss on the emerging time of a new wave, as well as the necessary condition for the extinction and persistence of the disease.
