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10.1016/j.apm.2020.08.057 http://scihub22266oqcxt.onion/10.1016/j.apm.2020.08.057 33012957!7521893!33012957     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Appl+Math+Model 2021 ; 90 (ä): 466-473 Nephropedia Template TP {{tp|p=33012957|t=2021. Analytical features of the SIR model and their applications to COVID-19 |pdf=|usr=}}{{33012957}} gab.com Text Analytical features of the SIR model and their applications to COVID-19 JO: Appl Math Model http://www.kidney.de/pget.php?&tw=1&pmid=33012957 #FOAvip 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 alpha/beta, where alpha is the contact rate in the community and beta 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. Twit Text FOAVip Analytical features of the SIR model and their applications to COVID-19 ????Appl Math Model http://www.kidney.de/pget.php?&tw=1&pmid=33012957 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33012957 #FOAvip English Wikipedia <ref>{{Cite pmid|33012957}}</ref> Analytical features of the SIR model and their applications to COVID-19 #MMPMID33012957 Kudryashov NA; Chmykhov MA; Vigdorowitsch M Appl Math Model 2021[Feb]; 90 (ä): 466-473 PMID33012957show ga 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 alpha/beta, where alpha is the contact rate in the community and beta 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. äAnalytical features of the SIR model and their applications to COVID-1(epmc).pdf DeepDyve Pubget Overpricing