Global animal melioidosis prevalence: a systematic review and meta-analysis
Year: 2026
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: BACKGROUND: Burkholderia pseudomallei, the causative agent of melioidosis, infects both humans and a broad range of animal species. While human disease has been well characterized, animal data are dispersed across studies and lack a comprehensive global synthesis. This systematic review and meta-analysis estimated the pooled global prevalence of animal melioidosis and examined regional and diagnostic influences. METHODS: Following PRISMA 2020 guidelines, studies reporting B. pseudomallei detection in animals were retrieved from PubMed, Scopus, and Embase up to April 2025. Pooled prevalence was calculated using a random-effects model. Subgroup and meta-regression analyses explored moderators of heterogeneity. RESULTS: Twenty-eight studies from 11 countries, encompassing 98,885 animal samples, were included. The global pooled prevalence was 7.3% (95% CI: 0.039-0.117), with high heterogeneity (I² = 98.8%). Southeast Asia, particularly Thailand, showed consistently higher prevalence across livestock, wildlife, and companion animals. Diagnostic methods and study period contributed to variability but were not statistically significant. CONCLUSIONS: Animal melioidosis is globally distributed, with Thailand serving as a key endemic region and research hub. Strengthening One Health surveillance, standardizing diagnostic tools, and expanding genomic monitoring are essential for improved detection and control of B. pseudomallei across animal populations.
Source: Irish Veterinary Journal
Authors: Jongkonnee Thanasai, Atthaphong Phongphithakchai, Moragot Chatatikun, Sa-ngob Laklaeng, Jitbanjong Tangpong, Pakpoom Wongyikul, Phichayut Phinyo, Supphachoke Khemla, Anchalee Chittamma, Wiyada Kwanhian Klangbud
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,990
Funder: Mahasarakham University
OpenAlex ID: W7140193737