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Analytical features of the SIR model and their applications to COVID-19

机译:SIR模型的分析特征及其在Covid-19的应用程序

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A classic two-parameter epidemiological SIR-model of the coronavirus propagation is considered. The first integrals of the system of non-linear equations are obtained. The Painleve test shows that the system of equations is not integrable in the general case. However, the general solution is obtained in quadrature as an inverse time-function. Using the first integrals of the system of equations, analytical dependencies for the number of infected patients I(t) and that of recovered patients R(t) on the number of susceptible to infection S(t) are obtained. A particular attention is paid to interrelation of I(t) and R(t) both depending on α/β, where α is the contact rate in the community and β is the intensity of recovery/decease of patients. It is demonstrated that the data on particular morbidity waves in Hubei (China), Italy, Austria, South Korea, Moscow (Russia) as well some Australian territories are satisfactorily described by the expressions obtained for I(R). The variability of parameter N having been traditionally considered as a static population size is discussed.
机译:考虑了冠状病毒传播的经典双参数流行病学SIR模型。获得非线性方程系统的第一积分。止痛试验表明,方程式在一般情况下不可列于。然而,将通用解决方案以正交获得为逆时间函数。使用方程式系统的第一积分,获得感染患者数量的分析依赖性,并且获得易受感染易感染患者的恢复患者R(T)的患者R(t)的数量。特别注意,根据α/β,对I(t)和R(t)的相互关注,其中α是群落中的接触率,β是患者的回收率/可失性的强度。据证明,湖北(中国),意大利,奥地利,韩国,莫斯科(俄罗斯)的关于一些澳大利亚领土的数据令人满意地描述了对i(r)的表达方式。讨论了传统上被认为是静态群体大小的参数n的可变性。

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