A Comparative Study between ARIMA Model, Holt-Winters – No Seasonal and Fuzzy Time Series for New Cases of COVID-19 in Algeria

Abdelmounaim Hadjira^1, , Hicham Salhi² and Fadoua El Hafa³

¹Department of Economics, Mohamed Boudiaf University, M’sila, Algeria

²Laboratory of Applied Research in Hydraulics, University of Mustapha Ben Boulaid-Batna 2, Algeria

³Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China

Cite this paper:
Abdelmounaim Hadjira, Hicham Salhi and Fadoua El Hafa. A Comparative Study between ARIMA Model, Holt-Winters – No Seasonal and Fuzzy Time Series for New Cases of COVID-19 in Algeria. American Journal of Public Health Research. 2021; 9(6):248-256. doi: 10.12691/ajphr-9-6-4

Abstract

Background: Coronavirus disease has become a worldwide threat affecting almost every country in the world. The spread of the virus is likely to continue unabated. The aim of this study is to compare between Autoregressive Integrated Moving Average (ARIMA) model, Fuzzy time series and Holt-Winters – No seasonal for forecasting the COVID-19 new cases in Algeria. Methods: Three different models to predict the number of Covid-19 new cases in Algeria were used. The number of new cases of COVID-19 in Algeria during the period from 24^th February 2020 to 31th July 2021 was modeled according to ARIMA(4,1,2) model, Five based Fuzzy time series models including the Chen model, Heuristic Huareng model, Singh model, Abbasov-Manedova model and NFTS model, and Holt-Winters – No seasonal. Results: The predictive values were obtained from the 1^st August 2021 to 31th December 2021. According to a set of criteria (ME, MAE, MSE, RMSE, U), we found that the FTNS model is the most accurate and best generating model for the values of the number of new cases of Covid-19. Conclusion: To the best of our knowledge, this is the first comparative study of three models of forecasting of Covid-19 new cases in Algeria. This study shows that ARIMA models with optimally selected covariates are useful tools for monitoring and predicting trends of COVID-19 cases in Algeria. Moreover, this forecast will help the Health authorities to be better prepared to fight the epidemic by engaging their healthcare facilities.

Keywords:
Covid-19 ARIMA fuzzy time series model Holt-Winter-non-seasonal Algeria

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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