SARIMA model-based forecasting required number of COVID-19 vaccines globally and empirical analysis of peoples’ view towards the vaccines

Amer Malki; El-Sayed Atlam; Aboul Ella Hassanien; Ashraf Ewis; Guesh Dagnew; Ibrahim Gad

Alexandria Engineering Journal (Dec 2022)

SARIMA model-based forecasting required number of COVID-19 vaccines globally and empirical analysis of peoples’ view towards the vaccines

Amer Malki,
El-Sayed Atlam,
Aboul Ella Hassanien,
Ashraf Ewis,
Guesh Dagnew,
Ibrahim Gad

Affiliations

Amer Malki: College of Computer Science and Engineering, Taibah University, Yanbu, Saudi Arabia
El-Sayed Atlam: Department of Computer Science, Tanta University, Tanta, Egypt; College of Computer Science and Engineering, Taibah University, Yanbu, Saudi Arabia; Corresponding author at: Department of Computer Science, Tanta University, Tanta, Egypt.
Aboul Ella Hassanien: Faculty of Computers and Artificial Intelligence, Cairo University, Cairo, Egypt
Ashraf Ewis: Department of Public Health and Occupational Medicine, Faculty of Medicine, Minia University, El-Minia, Egypt; Department of Public Health, Faculty of Health Sciences – AlQunfudah, Umm AlQura University, Meccah, Saudi Arabia
Guesh Dagnew: Department of Computer Science, Institute of Technology, Dire Dawa University, Ethiopia
Ibrahim Gad: Department of Computer Science, Tanta University, Tanta, Egypt

Journal volume & issue: Vol. 61, no. 12
pp. 12091 – 12110

Abstract

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Recent studies regarding COVID-19 show a growing tendency to talk about the COVID-19 Pandemic on online channels. With the recent release of the Pfizer vaccine of COVID-19, people keep posting many rumors regarding the safety concerns of the Vaccine, especially among older people. Due to the rapid spread of the COVID-19 virus and the worldwide Pandemic developed, the rush to develop the COVID-19 Vaccine has become an alarming priority in health care services worldwide. In this research work, we have systematically evaluated people’s views towards the COVID-19 Vaccine, and shreds of evidence are supported empirically. The study mainly focuses on the empirical evidence and intensive discussions on what is currently known about the mechanism of action, efficacy, and toxicity of the most promising vaccines (Moderna), (Pfizer/BioNtech), (Astrazenac/Oxford), and (Sputnik V) against COVID-19. Our study’s primary objective is to provide an analysis of the questionnaire regarding people’s opinions, preferences, and acceptance of the COVID-19 vaccines. We have created an online questionnaire using a google form to collect data from various countries supposed to employ COVID-19 vaccines. The questionnaires were distributed to people in many Arab and foreign countries such as Egypt, Saudi Arabia, India, England, China, and Japan. A total of 516 responses were returned and analyzed using statistical, and Seasonal Autoregressive Integrated Moving Average (SARIMA) approaches. The SARIMA model is used to predict the total number of vaccines in the next few days. To attain the most accurate forecast and prediction, the SARIMA model parameters are investigated with a grid search method. Finally, the combination of the parameters (1,0,1)×(1,0,0,1) is considered to be the best SARIMA model because it has the lowest AIC values of −4100.11 and the best Correlation coefficients of 0.984.

Published in Alexandria Engineering Journal

ISSN: 1110-0168 (Print); 2090-2670 (Online)
Publisher: Elsevier
Country of publisher: Egypt
LCC subjects: Technology: Engineering (General). Civil engineering (General)
Website: http://www.journals.elsevier.com/alexandria-engineering-journal/

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