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A hybrid model for modeling the spread of epidemics: Theory and simulation

机译:用于建模流行病传播的混合模型:理论与模拟

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The spread of disease is a dynamic and complex phenomenon. In the world, diseases are the effects of misery and poverty. To find how to understand epidemiological systems is essential for governments. So why, modeling is an excellent method because it simplifies the reality. Presently, models of differential equations like SIR and SEIR are the most used, but they are more difficult to apply at the world scale. In this paper we propose a hybrid model, which presents a case of modeling an epidemic spreading to several cities in a SIR compartmental model (Susceptible - Infected - Recovered). This hybrid model certifies that the population mobility, the basic reproduction number, the simulation environment and other factors greatly influence the dynamics of disease. The particular interest of our model is its hybrid nature. We modeled the spread of diseases by coupling the Agent-Based Model (ABM) and differentials equations as well as designing hybrid model by taking the simultaneous advantages of Agent-Based Models and mathematical models (ODE). Our model does not require a lot of parameters nor several hardware resources compared to general Agent-Based Models. Simulations based on 10,000 to 100,000 individuals were performed without problems.
机译:疾病的传播是一种动态而复杂的现象。在世界上,疾病是苦难和贫穷的后果。寻找如何理解流行病学系统对于政府至关重要。因此,为什么建模是一种出色的方法,因为它简化了现实。目前,最常用的是SIR和SEIR之类的微分方程模型,但在世界范围内更难应用。在本文中,我们提出了一种混合模型,该模型以SIR隔间模型(易感性-感染-恢复)为例,模拟了一种流行病扩散到多个城市的情况。该混合模型证明人口流动性,基本繁殖数量,模拟环境和其他因素极大地影响了疾病的动态。我们模型的特别兴趣在于它的混合性质。我们通过结合基于主体的模型(ABM)和微分方程对疾病的传播进行建模,并利用基于主体的模型和数学模型(ODE)的同时优势设计混合模型。与基于代理的通用模型相比,我们的模型不需要大量参数,也不需要几个硬件资源。进行了基于10,000到100,000个人的模拟,没有出现问题。

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