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Another look at a good approximation of data for the distribution of COVID-19 in Cuba


 
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Revista Habanera de Ciencias Médicas

 ISSN 1729-519X

KYURKCHIEV, Nikolay; ILIEV, Anton; RAHNEV, Asen    TERZIEVA, Todorka. Another look at a good approximation of data for the distribution of COVID-19 in Cuba. []. , 19, 3   10--2020. ISSN 1729-519X.

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In the article “Adjustment of population growth curve applied to Covid-19 in Cuba”, the authors propose six types of models to approximate data from the distribution of COVID-19 in Cuba, while giving a clear answer to the possible advantages of some considerations. In this paper, we study intrinsic properties of some models of growth with polynomial variable transfer that give a very good approximation of the specific data on the pandemics in Cuba by June 5, 2020. The models have the right to exist in the treatment of issues from different fields of scientific knowledge. Numerical examples are presented using CAS MATHEMATICA.

^len^a

En el artículo “Ajuste de curvas de crecimiento poblacional aplicadas a la COVID-19 en Cuba”, los autores proponen y seriamente analizan seis tipos de modelos (logísticos y otros modelos de crecimiento) para aproximar los datos sobre la distribución de la COVID-19 en Cuba mientras plantean una clara respuesta a las posibles ventajas de algunas consideraciones. En este trabajo estudiamos las propiedades intrínsecas de algunos modelos de creciemiento con transferencia de variables polinómicas que proporcionan una muy buena aproximación de los datos específicos sobre la pandemia en Cuba antes del 5 de junio de 2020. Los modelos tienen el derecho a existir en el tratamiento de cuestiones de diferentes campos del conocimiento científico. Los ejemplos numéricos se presentan utilizando un modelo matemático para calcular los casos.

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