Predicción con modelo ARIMA en series temporales de Salmonella spp en Chile entre 2014-2022
Resumen
Introducción. Las Enfermedades Transmitidas por Alimentos ( ETA), constituyen un problema de salud pública de relevancia mundial, siendo motivo de vigilancia epidemiológica y son el resultado del consumo de alimentos que contienen toxinas o microorganismos patógenos vivos. El objetivo de este estudio es analizar las series temporales de Salmonella spp. para el periodo 2014-2022 en Chile y desarrollar un modelo predictivo de Media Móvil Autorregresiva (ARIMA). Métodos. Se realizó una descomposición de la serie para estudiar tendencia y estacionalidad. Se utilizó la prueba de Dickey-Fuller para estacionalidad y Kruskall-Wallis para comparación de grupos. Se aplicó el modelo ARIMA para realizar una predicción de casos en un año adelante. Resultados. La serie de estudio para Salmonella spp. tuvo un comportamiento estacional sin diferencias significativas entre grupos (periodos). El modelo ARIMA tuvo un buen desempeño para predecir casos en una serie continua. Conclusiones. El análisis de series temporales en epidemiología es una herramienta valiosa para prever futuros brotes o epidemias en el territorio nacional. El modelo ARIMA tiene un buen desempeño en la serie estacional analizada para Salmonella spp en muestras de deposición.
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Derechos de autor 2023 Nicolas Ayala-Aldana;Antonio Monleon-Getino;Jaume Canela-Soler;Erika Retamal-Contreras
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
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