论文标题
SIR模型与广义逻辑分布与SARS的应用与Covid-19之间的关系
A Relationship Between SIR Model and Generalized Logistic Distribution with Applications to SARS and COVID-19
论文作者
论文摘要
本文表明，广义逻辑分布模型来自众所周知的隔室模型，这些模型由易感，感染和回收的隔室组成，在某些条件下缩写为SIR模型。在SIR模型中，预测感染人群数量和传染性参数的最终值存在不确定性。但是，通过利用从广义逻辑分布模型获得的信息，我们可以更稳定，更准确地执行SIR数值计算。还介绍了使用这种组合方法的严重急性呼吸综合征（SARS）和冠状病毒疾病（COVID-19）的应用。
This paper shows that the generalized logistic distribution model is derived from the well-known compartment model, consisting of susceptible, infected and recovered compartments, abbreviated as the SIR model, under certain conditions. In the SIR model, there are uncertainties in predicting the final values for the number of infected population and the infectious parameter. However, by utilizing the information obtained from the generalized logistic distribution model, we can perform the SIR numerical computation more stably and more accurately. Applications to severe acute respiratory syndrome (SARS) and Coronavirus disease 2019 (COVID-19) using this combined method are also introduced.
