论文标题
流行病的数学建模； COVID-19冠状病毒的案例研究
Mathematical Modeling of Epidemic Diseases; A Case Study of the COVID-19 Coronavirus
论文作者
论文摘要
在这项研究中，我们从数学建模的角度研究了流行病（例如Covid-19冠状病毒）的流行病的传播模式。该研究基于众所周知的易感感染（SIR）隔室模型家族的扩展。它展示了社会措施如何影响模型参数，例如距离，区域锁定，隔离和全球公共卫生警惕性，最终可以随着时间的流逝而改变死亡率和主动污染案件。与所有数学模型一样，该模型的预测能力受到可用数据的准确性以及用于建模问题的所谓\ textit {抽象水平}的限制。为了使更广泛的研究人员更好地了解流行病的传播模式，还提供了对生物系统建模的简短介绍，并在线提供了模拟的MATLAB源代码。
In this research, we study the propagation patterns of epidemic diseases such as the COVID-19 coronavirus, from a mathematical modeling perspective. The study is based on an extensions of the well-known susceptible-infected-recovered (SIR) family of compartmental models. It is shown how social measures such as distancing, regional lockdowns, quarantine and global public health vigilance, influence the model parameters, which can eventually change the mortality rates and active contaminated cases over time, in the real world. As with all mathematical models, the predictive ability of the model is limited by the accuracy of the available data and to the so-called \textit{level of abstraction} used for modeling the problem. In order to provide the broader audience of researchers a better understanding of spreading patterns of epidemic diseases, a short introduction on biological systems modeling is also presented and the Matlab source codes for the simulations are provided online.
