Global Level Research Output in Monkey Pox: A Scientometric Analysis

S Ravichandran*, P Rajendran

SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamilnadu, India

Refer this article

S Ravichandran, P Rajendran. Global Level Research Output in Monkey Pox: A Scientometric Analysis. November-December 2024, V2 – I6, Pages - 0274 – 0282. Doi: https://doi.org/10.55522/ijti.v2i6.0090.

ABSTRACT

The current study examined the growth of research publications released between 2062 and 2024 using a sample of 203 articles published in the field of Monkey Pox. The biggest number of papers, 121 (59.61%), were published in 2021-2024. During the study period, an article's RGR gradually declined from 0.86 in 1970-1973 to 0.76 in 2021-2024. The doubling time of article publishing gradually increases, from 0.80 in 1970-1973 to 90 in 2021-2024. The most prolific authors in the subject of Monkey Pox, it is found that Marennikova, S.S. has contributed the maximum number of articles i.e., 16 (23.88%) research publications in India. The vast majority of research output is available in the form of Article 121 (59.61%) research publications, and the country-wise distribution of publications shows that India provided the most articles (146), accounting for more than 44 (30.14%) research publications. The institutions with the University of Organisation Mondiale de la Santé published 7 (17.07%) articles, and the journals revealed that Bulletin of the World Health Organization ranked best with 9 (20.45%) publications. The time series analysis statistical application in Monkey Pox research articles is predicted to reach approximately 60 in 2025 and 70 in 2030. So, at the time, rigorous examination confirmed that the number of publications on monkey pox study was increasing. The widely referenced paper is Galdiero S., Falanga A., et al. (2011) Silver nanoparticles as potential antiviral drugs, Molecules, 16(10):8894-8918. The citation count is 778, as is the review's document type.

Keywords:

Scientometric, Tuberculosis, RGR, Time series analysis, Highly cited paper, RCI.