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10.1016/j.chaos.2020.110241 http://scihub22266oqcxt.onion/10.1016/j.chaos.2020.110241 32863615!7444956!32863615     free     free     free       Chaos+Solitons+Fractals 2020 ; 140 (ä): 110241 Nephropedia Template TP {{tp|p=32863615|t=2020. Logistic equation and COVID-19 |pdf=|usr=}}{{32863615}} gab.com Text Logistic equation and COVID-19 JO: Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32863615 #FOAvip The generalized logistic equation is used to interpret the COVID-19 epidemic data in several countries: Austria, Switzerland, the Netherlands, Italy, Turkey and South Korea. The model coefficients are calculated: the growth rate and the expected number of infected people, as well as the exponent indexes in the generalized logistic equation. It is shown that the dependence of the number of the infected people on time is well described on average by the logistic curve (within the framework of a simple or generalized logistic equation) with a determination coefficient exceeding 0.8. At the same time, the dependence of the number of the infected people per day on time has a very uneven character and can be described very roughly by the logistic curve. To describe it, it is necessary to take into account the dependence of the model coefficients on time or on the total number of cases. Variations, for example, of the growth rate can reach 60%. The variability spectra of the coefficients have characteristic peaks at periods of several days, which corresponds to the observed serial intervals. The use of the stochastic logistic equation is proposed to estimate the number of probable peaks in the coronavirus incidence. Twit Text FOAVip Logistic equation and COVID-19 ????Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=32863615 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32863615 #FOAvip English Wikipedia <ref>{{Cite pmid|32863615}}</ref> Logistic equation and COVID-19 #MMPMID32863615 Pelinovsky E; Kurkin A; Kurkina O; Kokoulina M; Epifanova A Chaos Solitons Fractals 2020[Nov]; 140 (ä): 110241 PMID32863615show ga The generalized logistic equation is used to interpret the COVID-19 epidemic data in several countries: Austria, Switzerland, the Netherlands, Italy, Turkey and South Korea. The model coefficients are calculated: the growth rate and the expected number of infected people, as well as the exponent indexes in the generalized logistic equation. It is shown that the dependence of the number of the infected people on time is well described on average by the logistic curve (within the framework of a simple or generalized logistic equation) with a determination coefficient exceeding 0.8. At the same time, the dependence of the number of the infected people per day on time has a very uneven character and can be described very roughly by the logistic curve. To describe it, it is necessary to take into account the dependence of the model coefficients on time or on the total number of cases. Variations, for example, of the growth rate can reach 60%. The variability spectra of the coefficients have characteristic peaks at periods of several days, which corresponds to the observed serial intervals. The use of the stochastic logistic equation is proposed to estimate the number of probable peaks in the coronavirus incidence. äLogistic equation and COVID-19 (epmc).pdf DeepDyve Pubget Overpricing