COVID-19 Diagnosis: A Review of Rapid Antigen, RT-PCR and Artificial Intelligence Methods

Raphael Taiwo Aruleba; Tayo Alex Adekiya; Nimibofa Ayawei; George Obaido; Kehinde Aruleba; Ibomoiye Domor Mienye; Idowu Aruleba; Blessing Ogbuokiri

doi:10.3390/bioengineering9040153

COVID-19 Diagnosis: A Review of Rapid Antigen, RT-PCR and Artificial Intelligence Methods

Bioengineering (Basel). 2022 Apr 3;9(4):153. doi: 10.3390/bioengineering9040153.

Authors

Raphael Taiwo Aruleba¹, Tayo Alex Adekiya², Nimibofa Ayawei³, George Obaido⁴, Kehinde Aruleba⁵, Ibomoiye Domor Mienye⁶, Idowu Aruleba⁶, Blessing Ogbuokiri⁷

Affiliations

¹ Department of Molecular and Cell Biology, Faculty of Science, University of Cape Town, Cape Town 7701, South Africa.
² Department of Pharmacy and Pharmacology, School of Therapeutic Science, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South Africa.
³ Department of Chemistry, Bayelsa Medical University, Yenagoa PMB 178, Bayelsa State, Nigeria.
⁴ Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0404, USA.
⁵ School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK.
⁶ Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa.
⁷ Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada.

Abstract

As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, and surveillance. Meanwhile, fast and efficient point-of-care (POC) testing and self-testing kits have become necessary in the fight against COVID-19 and to assist healthcare personnel and governments curb the spread of the virus. This paper presents a review of the various types of COVID-19 detection methods, diagnostic technologies, and surveillance approaches that have been used or proposed. The review provided in this article should be beneficial to researchers in this field and health policymakers at large.

Keywords: COVID-19; SARS-CoV-2; artificial intelligence; deep learning; machine learning; molecular diagnosis.

Publication types

Review