Open Access

ARTICLE

Classification and Categorization of COVID-19 Outbreak in Pakistan

Amber Ayoub¹, Kainaat Mahboob¹, Abdul Rehman Javed², Muhammad Rizwan¹, Thippa Reddy Gadekallu², Mustufa Haider Abidi^3,*, Mohammed Alkahtani^4,5

1 Department of Computer Science, Kinnaird College for Women, Lahore, 54000, Pakistan
2 Department of Cyber Security, Air University, Islamabad, Pakistan
3 School of Information Technology and Engineering, Vellore Institute of Technology, Tamil Nadu, India
4 Raytheon Chair for Systems Engineering, Advanced Manufacturing Institute, King Saud University, Riyadh, 11421, Saudi Arabia
5 Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia

* Corresponding Author: Mustufa Haider Abidi. Email:

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

Computers, Materials & Continua 2021, 69(1), 1253-1269. https://doi.org/10.32604/cmc.2021.015655

Received 01 December 2020; Accepted 05 February 2021; Issue published 04 June 2021

Abstract

Coronavirus is a potentially fatal disease that normally occurs in mammals and birds. Generally, in humans, the virus spreads through aerial droplets of any type of fluid secreted from the body of an infected person. Coronavirus is a family of viruses that is more lethal than other unpremeditated viruses. In December 2019, a new variant, i.e., a novel coronavirus (COVID-19) developed in Wuhan province, China. Since January 23, 2020, the number of infected individuals has increased rapidly, affecting the health and economies of many countries, including Pakistan. The objective of this research is to provide a system to classify and categorize the COVID-19 outbreak in Pakistan based on the data collected every day from different regions of Pakistan. This research also compares the performance of machine learning classifiers (i.e., Decision Tree (DT), Naive Bayes (NB), Support Vector Machine, and Logistic Regression) on the COVID-19 dataset collected in Pakistan. According to the experimental results, DT and NB classifiers outperformed the other classifiers. In addition, the classified data is categorized by implementing a Bayesian Regularization Artificial Neural Network (BRANN) classifier. The results demonstrate that the BRANN classifier outperforms state-of-the-art classifiers.

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Citations