Mathematical modeling and multi-agents approach for the evolution of the Coronavirus pandemic

Rajaa Aboulaich, K. Bensaid, S. Chabbar, Jaafar El Karkri
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Abstract

The objective of this work is to simulate the growth of the novel corona virus disease in some cities in Morocco. We study the impact of the barrier and health measures to be taken to reduce the spread and contain the epidemic. In order to define the optimal measures to take to curb the spread of the pandemic, our goal is to use adequate mathematical modeling tools and adapt agent-based models to simulate the evolution of the pandemic and its spread in Morocco. An analysis of the disease spread based on compartmental modeling leads to an ordinary differential equation governing the system. In addition, the agent-based approach uses artificial intelligence and makes it possible to deal with complexity, also permits to consider different scenarios. The obtained numerical simulations give a clear idea of the spread of a party’s disease and for each of the measures that are taken into account during containment or during de-containment. These simulations are decision support efficient tools rendered on powerful modeling tools. The two approaches are complementary and give rise to successful models.
冠状病毒大流行演变的数学建模和多agent方法
这项工作的目的是模拟摩洛哥一些城市新型冠状病毒病的发展。我们研究了屏障的影响以及为减少传播和控制疫情而应采取的卫生措施。为了确定遏制该流行病蔓延的最佳措施,我们的目标是使用适当的数学建模工具并调整基于主体的模型,以模拟该流行病的演变及其在摩洛哥的蔓延。基于区室模型的疾病传播分析导致控制系统的常微分方程。此外,基于代理的方法使用人工智能,使得处理复杂性成为可能,也允许考虑不同的场景。所获得的数值模拟可以清楚地了解缔约方疾病的传播情况,以及在控制或去控制期间所考虑的每一项措施。这些模拟是在强大的建模工具上呈现的决策支持有效工具。这两种方法是互补的,并产生成功的模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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