Predicción de infectados por Covid-19 en el Perú por el modelo de media móvil integrada autorregresiva

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Alex Youn Aro Huanacuni

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Durante el brote del virus Covid-19, varios investigadores han estudiado diversos modelos matemáticos de pronóstico de infecciones y muertes; así como, la tasa de contagio del virus. En la actualidad sigue vigente el virus con algunas variantes y conocer su comportamiento es de mucha importancia para desarrollar acciones efectivas en el control de la situación actual y futura de la epidemia. El objetivo fue predecir la cantidad de infectados acumulados por Covid-19, de 38 días, a partir de 23 de diciembre del 2021, utilizando los datos registrados en la Organización Mundial de la Salud (OMS), del caso Perú, y realizando entrenamientos del modelo de media móvil integrada autorregresiva (ARIMA) en el software Python 3. Los modelos más óptimos obtenidos con datos reales de número de casos infectados y muertes diarias por Covid-19, según los parámetros estadísticos EMPA y R2 fueron ARIMA(3,0,1) en la predicción de casos diarios con EMPA=0,178 y R2=0,804 y ARIMA(3,1,1), con EMPA= 0,243 y R2=0,579, en la predicción de muertes diarias. En los cinco modelos aplicados en el periodo de predicción, se estimó un promedio de 53518 personas infectadas por Covid-19.

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Aro Huanacuni, A. Y. (2022). Predicción de infectados por Covid-19 en el Perú por el modelo de media móvil integrada autorregresiva. Ciencia & Desarrollo, 22(1), 1–9. https://doi.org/10.33326/26176033.2022.1.1237
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