Open Access

ARTICLE

Nonlinear Time Series Analysis of Pathogenesis of COVID-19 Pandemic Spread in Saudi Arabia

Sunil Kumar Sharma¹, Shivam Bhardwaj^2,*, Rashmi Bhardwaj³, Majed Alowaidi¹

1 College of Computer and Information Sciences, Majmaah University, Majmaah, 11952, Saudi Arabia
2 Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, Delhi, 110086, India
3 Non-Linear Dynamics Research Laboratory, GGS Indraprastha University, Delhi, 110078, India

* Corresponding Author: Shivam Bhardwaj. Email:

(This article belongs to the Special Issue: Artificial Intelligence and Information Technologies for COVID-19)

Computers, Materials & Continua 2021, 66(1), 805-825. https://doi.org/10.32604/cmc.2020.011937

Received 06 June 2020; Accepted 11 July 2020; Issue published 30 October 2020

Abstract

This article discusses short–term forecasting of the novel Corona Virus (COVID-19) data for infected and recovered cases using the ARIMA method for Saudi Arabia. The COVID-19 data was obtained from the Worldometer and MOH (Ministry of Health, Saudi Arabia). The data was analyzed for the period from March 2, 2020 (the first case reported) to June 15, 2020. Using ARIMA (2, 1, 0), we obtained the short forecast up to July 02, 2020. Several statistical parameters were tested for the goodness of fit to evaluate the forecasting methods. The results show that ARIMA (2, 1, 0) gave a better forecast for the data system. COVID 19 data followed quadratic behavior, and in the long run, it spreads with a high peak. It is concluded that COVID-19 will follow secondary shock waves, and it is strongly advisable to maintain social distancing with all safety measures as the pandemic situation is not in control.

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