One Health prevalence of non-typhoidal Salmonella in humans, animals, food, and the environment across Asia, Europe, and Africa (2016–2025): a systematic review and meta-analysis with subgroup analyses

This project presents a prospectively registered systematic review and meta-analysis conducted within a One Health framework to estimate the prevalence of non-typhoidal Salmonella (NTS) across humans, animals, food, and environmental sources in Asia, Europe, and Africa from 2016 to 2025. Non-typhoidal Salmonella remains a leading zoonotic and foodborne pathogen globally, with transmission occurring through interconnected human–animal–food–environment pathways. Fragmentation of existing evidence by sector and region has limited comprehensive understanding of cross-sector transmission dynamics and antimicrobial resistance patterns. This review aims to (i) estimate pooled prevalence of NTS across One Health sources, and (ii) explore heterogeneity by continent, source type, serovar, diagnostic method, and antimicrobial resistance status using subgroup analyses and meta-regression. Eligible studies include observational prevalence data from cross-sectional studies, surveillance systems, and baseline cohort data, with no language restrictions. A comprehensive and reproducible search strategy will be implemented across major bibliographic databases (PubMed, Scopus, Web of Science, ScienceDirect, Google Scholar, and regional databases). Study selection, data extraction, and risk of bias assessment will be performed independently by two reviewers, with methodological quality assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. Meta-analyses will be conducted using random-effects models in R, with appropriate transformations for proportion data, heterogeneity assessment, prediction intervals, sensitivity analyses, and evaluation of small-study effects. All protocol versions, search strategies, data extraction templates, analytical code, and protocol amendments will be version-controlled and archived on the Open Science Framework to ensure transparency, reproducibility, and long-term accessibility.