Previti Annalisa, Biondi Vito, Bruno Federica, Castelli Germano, Pugliese Michela, Vitale Fabrizio, Padalino Barbara, Passantino Annamaria
Department of Veterinary Sciences, University of Messina - Via Umberto Palatucci, 98168, Messina, Italy.
Experimental Zooprophylactic Institutes of Sicily (IZS Sicilia), Via Gino Marinuzzi, 3, 90129, Palermo, Italy.
BMC Vet Res. 2025 Mar 31;21(1):225. doi: 10.1186/s12917-025-04544-y.
Antimicrobial use (AMU) and antibiotic resistance (AR) in aquaculture present growing concerns for public health. Furthermore, there exists a correlation between fishes' welfare and AMU. This systematic review aims to analyze the scientific literature on fishes' welfare and AMU/AR over the last 32 years, identifing the main research topics, and the fields where investigation has been imitated. A comprehensive search was conducted using Scopus, employing specific keywords related to AMU/AR and welfare and preselected filters. The study employed a systematic approach following the PRISMA guidelines, and machine learning techniques were used. From 2,019 records retrieved, only those focused-on fishes welfare and AMU/AR were retained. Ultimately, 185 records showing a connection between these topics were included in the qualitative analysis. Text mining analysis revealed terms with the highest weighted frequency in the data corpus, while topic analysis identified the top five core areas: Topic 1 (Antibiotic resistance and strain genetic isolation), Topic 2 (Aquaculture and Human Health, environment, and food), Topic 3 (Fish response to stress and indicators), Topic 4 (Control of water and fish growth), and Topic 5 (Aquaculture research and current farming methods). The results indicate a growing interest in fish welfare and AMU/AR, while also highlighting areas that require further investigation, such as the link between these research fields. Improving fish welfare can reduce AR, aligning with the One Health policy.
水产养殖中的抗菌药物使用（AMU）和抗生素耐药性（AR）引发了越来越多的公共卫生问题。此外，鱼类福利与抗菌药物使用之间存在关联。本系统综述旨在分析过去32年中关于鱼类福利以及抗菌药物使用/抗生素耐药性的科学文献，确定主要研究主题以及研究较少的领域。使用Scopus进行了全面搜索，采用了与抗菌药物使用/抗生素耐药性和福利相关的特定关键词以及预先选定的筛选条件。该研究遵循PRISMA指南采用了系统方法，并使用了机器学习技术。从检索到的2019条记录中，仅保留了那些关注鱼类福利以及抗菌药物使用/抗生素耐药性的记录。最终，185条显示这些主题之间存在联系的记录被纳入定性分析。文本挖掘分析揭示了数据语料库中加权频率最高的术语，而主题分析确定了前五个核心领域：主题1（抗生素耐药性与菌株遗传分离）、主题2（水产养殖与人类健康、环境和食物）、主题3（鱼类对压力的反应及指标）、主题4（水质控制与鱼类生长）以及主题5（水产养殖研究与当前养殖方法）。结果表明人们对鱼类福利以及抗菌药物使用/抗生素耐药性的兴趣日益浓厚，同时也突出了需要进一步研究的领域，例如这些研究领域之间的联系。改善鱼类福利可以降低抗生素耐药性，这与“同一健康”政策相一致。
