Bibliometric Analysis of Publications on the Omicron Variant from 2020 to 2022 in the Scopus Database Using R and VOSviewer

Hasan Ejaz (), Hafiz Muhammad Zeeshan, Fahad Ahmad, Syed Nasir Abbas Bukhari, Naeem Anwar, Awadh Alanazi, Ashina Sadiq, Kashaf Junaid, Muhammad Atif, Khalid Omer Abdalla Abosalif, Abid Iqbal, Manhal Ahmed Hamza and Sonia Younas
Additional contact information
Hasan Ejaz: Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
Hafiz Muhammad Zeeshan: Department of Computer Sciences, National College of Business Administration and Economics, Lahore 54700, Punjab, Pakistan
Fahad Ahmad: Department of Basic Sciences, Deanship of Common First Year, Jouf University, Sakaka 72388, Saudi Arabia
Syed Nasir Abbas Bukhari: Department of Pharmaceutical Chemistry, College of Pharmacy, Jouf University, Sakaka 72388, Saudi Arabia
Naeem Anwar: Allied Health Department, College of Health and Sport Sciences, University of Bahrain, Zallaq 32038, Bahrain
Awadh Alanazi: Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
Ashina Sadiq: Department of Computer Science, Lahore Leads University, Lahore 54000, Punjab, Pakistan
Kashaf Junaid: School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK
Muhammad Atif: Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
Khalid Omer Abdalla Abosalif: Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
Abid Iqbal: Prince Sultan University, Riyadh 11586, Saudi Arabia
Manhal Ahmed Hamza: Department of Medical Microbiology, Faculty of Medical Laboratory Sciences, Omdurman Islamic University, Omdurman 14415, Sudan
Sonia Younas: HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China

IJERPH, 2022, vol. 19, issue 19, 1-25

Abstract: Human respiratory infections caused by coronaviruses can range from mild to deadly. Although there are numerous studies on coronavirus disease 2019 (COVID-19), few have been published on its Omicron variant. In order to remedy this deficiency, this study undertook a bibliometric analysis of the publishing patterns of studies on the Omicron variant and identified hotspots. Automated transportation, environmental protection, improved healthcare, innovation in banking, and smart homes are just a few areas where machine learning has found use in tackling complicated problems. The sophisticated Scopus database was queried for papers with the term “Omicron” in the title published between January 2020 and June 2022. Microsoft Excel 365, VOSviewer, Bibliometrix, and Biblioshiny from R were used for a statistical analysis of the publications. Over the study period, 1917 relevant publications were found in the Scopus database. Viruses was the most popular in publications for Omicron variant research, with 150 papers published, while Cell was the most cited source. The bibliometric analysis determined the most productive nations, with USA leading the list with the highest number of publications (344) and the highest level of international collaboration on the Omicron variant. This study highlights scientific advances and scholarly collaboration trends and serves as a model for demonstrating global trends in Omicron variant research. It can aid policymakers and medical researchers to fully grasp the current status of research on the Omicron variant. It also provides normative data on the Omicron variant for visualization, study, and application.

Keywords: bibliometrics; Omicron variant; Scopus; Biblioshiny application; Bibliometrix package; R; VOSviewer (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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