论文标题
根据SIR模型的SARS-COV-2大流行的遗传突变和动态传播的研究以及其进化的预测
Study of genetic mutations and dynamic spread of SARS-CoV-2 pandemic and prediction of its evolution according to the SIR model
论文作者
论文摘要
在这项工作中，我们的目的是研究累积数量的SARS-COV-2大流行的动态行为可以提供有关每天分布的整体行为的信息。可以以先前在Euclidean网络上在Euclidean网络上研究的易感性感染的（SIR）模型获得的经验形式合成累积数据。从我们进行的研究中，我们可以得出结论，欧几里得网络上的SIR模型可以从几个国家中重现具有精确度的数据的数据。这可以深入了解影响SARS-COV-2行为的不同药物，尤其是在病毒突变期间。因此，我们试图分析不同国家的遗传突变的效果，以及特定突变如何使病毒更具传染性。
In this work, we aim to study that the dynamics behavior for cumulative number of SARS-CoV-2 pandemic can provide information on the overall behavior of the spread over daily time.The cumulative data can be synthesized in an empirical form obtained from a Susceptible-Infected-Recovered (SIR) model previously studied on a Euclidean network. From the study we carried out, we can conclude that the SIR model on the Euclidean network can reproduce data from several countries with a deviation of precision for given parameter values. This gives an insight into the different agents that influence the behavior of SARS-CoV-2 especially during the virus mutation period. We are thus trying to analyze the effect of genetic mutations in different countries, and how a specific mutation can make the virus more contagious.
