Modelos de Series de Tiempo para Predecir el Número de Casos de Variantes Dominantes del SARS-COV-2 Durante las Olas Epidémicas en Chile


Claudia Paz Barría Sandoval

Patricio Andrés Salas Fernández

Guillermo Patricio Ferreira Cabezas

Palabras clave:
COVID-19, SARS-COV-2, Delta, Gamma, Omicron, Time Series Models COVID-19, SARS-COV-2, Delta, Gamma, Omicron, Modelo de Series de Tiempo


El COVID-19 y sus variantes han creado una pandemia a nivel global. En Chile, hasta el 28 de febrero del 2022, ya se han infectado más de 3 millones de personas y han muerto más de 42 mil personas. En este artículo, se realiza un estudio comparativo de diferentes modelos matemáticos utilizados para modelar y predecir el número de casos diarios confirmados de COVID-19 en Chile. Esta investigación considera los registros diarios de casos confirmados desde el inicio de la pandemia y por lo tanto incluye los contagiados por las distintas variantes del virus (Delta, Gamma y Omicron), estas variantes han dominado la evolución de los contagios diarios en Chile, siendo la variante Omicron la que ha demostrado tener una mayor tasa de contagios a nivel nacional. El objetivo de este estudio es brindar información relevante sobre la evolución de la pandemia por COVID-19 en Chile mediante modelos de series de tiempo que han sido validados en distintas investigaciones y evaluar su precisión frente a la variante Omicron del virus SARS-CoV-2.



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