A An Application of Bradford’s Law for the Covid-19 Research Output Indexed in Web of Science during 2020 – 2025
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2026.17.4.02Keywords:
COVID-19;Bibliometrics; Scientometrics; Bradford’s Law; Mathematical model; Theoretical mode; Leimkuhler logarithmic model; Egghe’s theoretical formulationDimensions Badge
Issue
Section
License
Copyright (c) 2026 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The COVID-19 pandemic triggered an unprecedented surge in scientific publications across diverse disciplines, including medicine, virology, public health, and biomedical sciences. Understanding the distribution of this rapidly expanding body of literature is essential for identifying key sources of scholarly communication. This study applies Bradford’s Law of Journal Scattering to examine the distribution and concentration of COVID-19 research articles indexed in the Web of Science (WoS) database during the period 2020–2025. The primary objective is to identify the core (nucleus) journals contributing to the field and to verify the applicability of Bradford’s Law using established mathematical models. Bibliographic data were retrieved using the keyword “COVID-19,” yielding a total of 21,762 publications distributed across 3,733 journals. The analysis categorizes journals into Bradford zones to determine the concentration of research output and to assess the conformity of the observed distribution with theoretical expectations. The findings of this study provide valuable insights for researchers, librarians, and policymakers in identifying influential journals and understanding publication patterns in pandemic-related research. The collected data were categorized by document type, and only journal articles were selected for analysis, resulting in a dataset of 20,935 articles published across 3,294 journals. This study aims to identify the core journals and assess the applicability of Bradford’s Law using established mathematical and theoretical models.Abstract
Bradford’s zoning technique was applied to classify journals into three distinct zones, each contributing approximately one-third of the total number of articles. The distribution was further validated using the Leimkuhler logarithmic model, resulting in the construction of a Bradford–Leimkuhler curve. In addition, Egghe’s theoretical formulation was employed to interpret the characteristics of the three Bradford zones. The study also analyzed key bibliometric indicators of the most productive journals, including impact factor, h-index, publication origin, and the countries of publication.
The results demonstrate a strong conformity of COVID-19 research publications to Bradford’s Law, revealing a highly concentrated core (nucleus) of journals, followed by two successive zones characterized by exponentially increasing numbers of journals with decreasing productivity. Verification through the Leimkuhler model confirmed a logarithmic growth pattern, thereby supporting the applicability of Bradford’s Law. Egghe’s model further elucidated deviations observed in the peripheral zones as a natural outcome of inequalities in journal productivity. Overall, this bibliometric investigation provides valuable insights for researchers, librarians, and policymakers in identifying influential and essential journals within the domain of COVID-19 research.
How to Cite
Downloads
Similar Articles
- P. Nagajothi, M. V. Srinath, Ensemble and Multimodal Approaches for Analyzing Student Engagement and Flexibility in Online Learning: A Review , The Scientific Temper: Vol. 17 No. 03 (2026): The Scientific Temper
- V. Manikandabalaji, R. Sivakumar, V. Maniraj, A novel approach using type-II fuzzy differential evolution is proposed for identifying and diagnosis of diabetes using semantic ontology , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- J. Fathima Fouzia, M. Mohamed Surputheen, M. Rajakumar, Hybrid pigeon optimization-based feature selection and modified multi-class semantic segmentation for skin cancer detection (HPO-MMSS) , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- Hardik N Talsania, Kirit Modi, Interpretable Cardiovascular Diagnosis using Multi-dimensional Feature Fusion and Deep Learning , The Scientific Temper: Vol. 17 No. 02 (2026): The Scientific Temper
- Pritesh C. Panchal, Dhaval A. Zala, Assessing Profitability, financial efficiency and Solvency: Financial Statement Analysis with special reference to ONGC , The Scientific Temper: Vol. 17 No. 03 (2026): The Scientific Temper
- Punithavathy E, N. Priya, A resilience framework for fault-tolerance in cloud-based microservice applications , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Ruchi Tiwari, Vipinchandra Tiwari, Vinitkumar Jagdishprasad Varma, Human Rights Disclosure in the Indian Banking Sector , The Scientific Temper: Vol. 17 No. 03 (2026): The Scientific Temper
- Hemang Shah, Archana Gadekar, Artificial intelligence and intellectual property rights with special reference to patent and copyright , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
- Habtamu Rufe Gurmu, M. Krishna Naidu, Garedo Tesfa, Assessment of Factors Influencing Use of Insecticide among Smallholders Farmers in Dale Sadi District of Kellem Wallega Zone, Ethiopia , The Scientific Temper: Vol. 17 No. 02 (2026): The Scientific Temper
- Binay Kumar Mahto, Rakesh Patel, Rajendra Bapna, Ajay Kumar Shukla, Development and Standardization of a Poly Herbal Formulation , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
<< < 10 11 12 13 14 15 16 17 18 19 > >>
You may also start an advanced similarity search for this article.

