Abstract: In this paper, we first analyze different time series CoViD-19 data by exploring confirmed, death and recovered daily reports from January 22, 2020 to May 30, 2021 in the West African Economic and Monetary Union (WAEMU) Area. We then use the Prophet model to forecast the total number of infected cases from May 31, 2021 to July 29, 2021 by providing graphics and by giving tables containing the total number of infected cases from July 25 to 29, 2021 for each country in the zone. |
Keywords and phrases: CoViD-19, time series, forecast, Prophet model, West African Economic and Monetary Union.
Received: June 4, 2021; Revised: July 3, 2021; Accepted: July 5, 2021; Published: July 26, 2021
How to cite this article: Harouna Sangaré and Abdou Fané, Time series analysis and forecasting of Covid-19 data: case of the West African economic and monetary union area, Advances and Applications in Statistics 69(2) (2021), 169-190. DOI: 10.17654/AS069020169
This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License
References:
[1] M. B. Bouraima, B. I. P. Zonon and Y. Qiu, The first 100 days: a review and analysis of the evolution of the Covid-19 pandemic in the West African Economic and Monetary Union (WAEMU), Eurasian Journal of Medical Investigation (EJMI) 4(4) (2020), 405-413. [2] Amit Kumar Gupta, Vijender Singh, Priya Mathur and Carlos M. Travieso-Gonzalez, Prediction of COVID-19 pandemic measuring criteria using support vector machine, Prophet and linear regression models in Indian scenario, Journal of Interdisciplinary Mathematics, 2020. doi:10.1080/09720502.2020.1833458. [3] A. B. Malik, Analysis and Forecast of COVID-19 Pandemic in Pakistan, 2020. doi:https://doi.org/10.1101/2020.06.24.20138800. [4] T. Milind and J. Rajashree, COVID-19 forecast using time series methods, International Journal of Scientific and Technology Research 9(8) (2020), 45-51. [5] B. V. Vishwas and Ashish Patel, Hands-on Time Series Analysis with Python: From Basics to Bleeding Edge Techniques, 2020. https://doi.org/10.1007/978-1-4842-5992-4. [6] M. Ponce and Amit Sandhel, Covid-19.analytics: An R Package to Obtain, Analyze and Visualize Data from the Coronavirus Disease Pandemic, 2021. arXiv:2009.01091v2 [cs.CY].
|