Aplicación de modelos de crecimiento sigmoidal en el pronóstico en tiempo real del brote de la Covid-19 en Villa Clara

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Palabras clave:

Covid-19, modelos de crecimiento sigmoidal, SIR, pronósticos en tiempo real

Resumen

En el presente artículo se estudia la dinámica de transmisión del SARS CoV-2 en Villa Clara utilizando diferentes modelos matemáticos, entre ellos los modelos fenomenológicos de crecimiento sigmoidal y de dinámica de población SIR. A partir del ajuste de los modelos a las series de datos de infectados acumulados, diariamente se evaluaron y estimaron diferentes parámetros asociados a la marcha de la Covid-19 en la provincia, información considerada por las autoridades en la toma de decisiones. Se presenta además, en retrospectiva, la evaluación de los pronósticos realizados en momentos representativos de las tres etapas identificadas, avalándose la intervención oportuna de las autoridades sanitarias para controlar eventos de transmisión local suscitados en el territorio.

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Publicado

2020-12-01

Cómo citar

[1]
Norman Montenegro, O. et al. 2020. Aplicación de modelos de crecimiento sigmoidal en el pronóstico en tiempo real del brote de la Covid-19 en Villa Clara. Ciencias matemáticas. 34, 1 (dic. 2020), 55–65.

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