Application of the Integrated Autoregressive Method of Moving Averages for the analysis of series of cases of COVID-19 in Peru

Aplicación del Método Autorregresivo Integrado de Medias Móviles para el análisis de series de casos de COVID-19 en el Perú

Authors

DOI:

https://doi.org/10.25176/RFMH.v21i1.3307

Keywords:

Forecasting, Pandemics, Coronavirus

Abstract

Objective: To estimate an Integrated Autoregressive Moving Average model (ARIMA) for the analysis of series of COVID-19 cases, in Peru. Methods: The present study was based on a univariate time series analysis; The data used refer to the number of new accumulated cases of COVID-19 from March 6 to June 11, 2020. For the analysis of the fit of the model, the autocorrelation coefficients (ACF), the unit root test of Augmented Dickey-Fuller (ADF), the Normalized Bayesian Information Criterion (Normalized BIC), the absolute mean percentage error (MAPE) and the Box-Ljung test. Results: The prognosis for COVID-19 cases, between June 12 and July 11, 2020 ranges from 220 596 to 429 790. Conclusions: The results obtained with the ARIMA model, compared with the observed data, show an adequate adjustment of the values; And although this model, easy to apply and interpret, does not simulate the exact behavior over time, it can be considered a simple and immediate tool to approximate the number of cases.

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Published

2020-12-16

How to Cite

Cordova Sotomayor, D. A., & Santa Maria Carlos, F. B. (2020). Application of the Integrated Autoregressive Method of Moving Averages for the analysis of series of cases of COVID-19 in Peru: Aplicación del Método Autorregresivo Integrado de Medias Móviles para el análisis de series de casos de COVID-19 en el Perú. Revista De La Facultad De Medicina Humana, 21(1). https://doi.org/10.25176/RFMH.v21i1.3307