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

Author

Listed:
  • Hasan Ejaz

    (Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
    These authors contributed equally to this work.)

  • Hafiz Muhammad Zeeshan

    (Department of Computer Sciences, National College of Business Administration and Economics, Lahore 54700, Punjab, Pakistan
    These authors contributed equally to this work.)

  • 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)

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.

Suggested Citation

  • 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 & , 2022. "Bibliometric Analysis of Publications on the Omicron Variant from 2020 to 2022 in the Scopus Database Using R and VOSviewer," IJERPH, MDPI, vol. 19(19), pages 1-25, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12407-:d:928988
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    References listed on IDEAS

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    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    3. Malcolm Koo, 2021. "Systemic Lupus Erythematosus Research: A Bibliometric Analysis over a 50-Year Period," IJERPH, MDPI, vol. 18(13), pages 1-14, July.
    4. Wenting Yang & Jiantong Zhang & Ruolin Ma, 2020. "The Prediction of Infectious Diseases: A Bibliometric Analysis," IJERPH, MDPI, vol. 17(17), pages 1-19, August.
    5. Verónica García-Pascual & Elvira García-Beltrán & Begoña Domenech-Amigot, 2022. "Eye-Related COVID-19: A Bibliometric Analysis of the Scientific Production Indexed in Scopus," IJERPH, MDPI, vol. 19(16), pages 1-15, August.
    6. Marium Mehmood & Nasser Alshammari & Saad Awadh Alanazi & Fahad Ahmad & Sampath Pradeep, 2022. "Systematic Framework to Predict Early-Stage Liver Carcinoma Using Hybrid of Feature Selection Techniques and Regression Techniques," Complexity, Hindawi, vol. 2022, pages 1-11, January.
    7. Dungey, Mardi & Doko Tchatoka, Firmin & Yanotti, María B., 2018. "Using multiple correspondence analysis for finance: A tool for assessing financial inclusion," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 212-222.
    8. Luís Farinha & João Renato Sebastião & Carlos Sampaio & João Lopes, 2020. "Social innovation and social entrepreneurship: discovering origins, exploring current and future trends," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 17(1), pages 77-96, March.
    9. Nicole C Nelson & Kelsey Ichikawa & Julie Chung & Momin M Malik, 2021. "Mapping the discursive dimensions of the reproducibility crisis: A mixed methods analysis," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-20, July.
    10. Jiangang Shi & Kaifeng Duan & Guangdong Wu & Rui Zhang & Xiaowei Feng, 2020. "Comprehensive metrological and content analysis of the public–private partnerships (PPPs) research field: a new bibliometric journey," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2145-2184, September.
    11. Paulina Phoobane & Muthoni Masinde & Tafadzwanashe Mabhaudhi, 2022. "Predicting Infectious Diseases: A Bibliometric Review on Africa," IJERPH, MDPI, vol. 19(3), pages 1-20, February.
    12. Dorin Vicentiu Popescu & Adriana Dima & Elena Radu & Ecaterina Milica Dobrota & Victor Marian Dumitrache, 2022. "Bibliometric Analysis of the Green Deal Policies in the Food Chain," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 24(60), pages 410-410, April.
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