Mapping the Global Landscape of Antibiotic-Resistant Brucellosis Research: An LDA Topic Modeling and Text Analysis

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Introduction Antibiotic-resistant brucellosis poses a growing challenge at the intersection of antibiotic resistance, zoonotic disease control, and public health. To address the lack of a systematic understanding of how research priorities in the field have evolved, this study conducts a large-scale structural and content analysis of the scientific literature to map thematic distributions, temporal trends, and underexplored research areas. Methods Data were extracted from the Scopus database, encompassing 419 scientific articles. After excluding missing data, 360 articles were selected for analysis. The data processing involved text cleansing, lemmatization, and the creation of bigrams and trigrams. The Latent Dirichlet Allocation (LDA) model was utilized to identify themes, and the optimal number of topics was established through the Coherence Score metric. The visualization of results encompassed various methods, including Word Cloud diagrams, topic distribution graphs, and a heatmap illustrating cluster similarities. Results Scientific output on antibiotic-resistant brucellosis began in 1953 and showed a marked increase after 2010, peaking in 2023. LDA topic modeling identified seven thematic clusters, with the highest concentration of publications in genetics-related resistance, treatment strategies, and Brucella strain diversity. The strongest thematic similarity was observed between genetic resistance and strain diversity clusters (similarity score = 0.40), while public health–focused research showed minimal overlap with genetic studies (similarity score = 0.04). Temporal analysis indicated a growing emphasis on genetically oriented research after 2010, whereas public health and zoonotic disease control showed highly scattered and minimal activity. Conclusion The analysis highlights a research landscape, with prevention, vaccination, surveillance, and policy-oriented studies remaining underrepresented, while identifying priority directions for future research, including targeted genomics, novel therapeutic approaches, and One Health–based surveillance.

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