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Article

Bibliometric Analysis of Highly Pathogenic Avian Influenza Research Globally from 2003 to 2023

by
Clement Meseko
1,
Uwem Okon Edet
1,2,*,
Okoroiwu Henshaw
3,
Nicodemus Mkpuma
,
Kayode Abraham Olawuyi
1 and
Charles Archibong
2
1
Regional Laboratory for Animal Influenza & Transboundary Animal Diseases, National Veterinary Research Institute (NVRI), Vom 930101, Plateau State, Nigeria
2
Department of Biological Science (Microbiology Unit), Arthur Jarvis University, Dan Archibong Drive, Akpabuyo, Cross River State, Nigeria
3
Medical Laboratory Science Department, David Umahi Federal University of Health Sciences, Uburu, Ohaozara LGA, Ebonyi State, Nigeria
*
Author to whom correspondence should be addressed.
GERMS 2025, 15(1), 11-25; https://doi.org/10.18683/germs.2025.1451
Submission received: 20 August 2024 / Revised: 23 January 2025 / Accepted: 1 March 2025 / Published: 31 March 2025

Abstract

Introduction: Despite decades of research on highly pathogenic avian influenza, especially H5N1, an understanding of the impact of research outputs on policy, the impact of funding and policies, collaboration between authors, and other bibliometric measurable indices is elusive. Methods: H5N1 research data were retrieved from the PubMed database using “H5N1”, “highly pathogenic”, and “influenza” as keywords, and combined with the Boolean operator, “OR”. The evaluated growth pattern of H5N1 research was analysed using Microsoft Excel, while the VOS viewer window version 1.6.15 was utilized in analyzing the keywords, authors’ inputs, and collaborations amongst research institutes/universities involved in H5N1 research. Results: A total of 8411 articles published within 2003 and 2023 were retrieved. The trend of the published articles indicates that 2003 to 2004 had the lowest number of articles, while the highest were observed for 2009 and 2010. Since then, there has been a gradual decline. The most dominant article type was original research article (89.80%), followed by reviews with 7.54%. The most productive countries were Japan, the United States of America, China, and Egypt in Africa. The top 15 authors accounted for 12.40% of the total published data. Keywords analysis revealed the emergence of newer keywords such as H5N8, wild birds, mammals, and Nigeria; however, as expected, influenza virus avian H5N1 subtype was the dominant keyword. Research institutes with backgrounds in agriculture and veterinary medicine dominated the top 15 organizations involved in H5N1 research. Conclusions: Our findings suggest that research aimed at developing therapeutics and vaccines, as well as continuous surveillance in high-risk areas is urgently needed. Furthermore, the findings provide baseline data for all the stakeholders involved in H5N1 research, which could inform future research, funding, and policies.
Keywords: H5N1; research output; policies; evolution; highly pathogenic avian influenza H5N1; research output; policies; evolution; highly pathogenic avian influenza

Share and Cite

MDPI and ACS Style

Meseko, C.; Edet, U.O.; Henshaw, O.; Mkpuma, N.; Olawuyi, K.A.; Archibong, C. Bibliometric Analysis of Highly Pathogenic Avian Influenza Research Globally from 2003 to 2023. GERMS 2025, 15, 11-25. https://doi.org/10.18683/germs.2025.1451

AMA Style

Meseko C, Edet UO, Henshaw O, Mkpuma N, Olawuyi KA, Archibong C. Bibliometric Analysis of Highly Pathogenic Avian Influenza Research Globally from 2003 to 2023. GERMS. 2025; 15(1):11-25. https://doi.org/10.18683/germs.2025.1451

Chicago/Turabian Style

Meseko, Clement, Uwem Okon Edet, Okoroiwu Henshaw, Nicodemus Mkpuma, Kayode Abraham Olawuyi, and Charles Archibong. 2025. "Bibliometric Analysis of Highly Pathogenic Avian Influenza Research Globally from 2003 to 2023" GERMS 15, no. 1: 11-25. https://doi.org/10.18683/germs.2025.1451

APA Style

Meseko, C., Edet, U. O., Henshaw, O., Mkpuma, N., Olawuyi, K. A., & Archibong, C. (2025). Bibliometric Analysis of Highly Pathogenic Avian Influenza Research Globally from 2003 to 2023. GERMS, 15(1), 11-25. https://doi.org/10.18683/germs.2025.1451

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