传染病信息

目的 为解析我国传染病监测预警领域的研究动态与知识结构，本研究旨在揭示该领域的研究现状、热点演进及前沿趋势，为优化传染病监测预警体系提供科学支撑。方法 以中国知网和科学引文索引数据库核心合集为数据源，检索建库至2024年传染病监测预警相关中英文文献，最终纳入6 065篇。利用CiteSpace软件构建作者合作网络、关键词共现与聚类图谱，结合突现词检测，分析研究演进路径及热点分布。结果 我国传染病监测预警研究分为萌芽、起步和快速发展3个阶段，核心作者群体初步形成，马家奇、王丽萍等学者在监测系统标准化、流行病学评估等领域贡献突出。关键词分析显示，“传染病”“预警系统”“突发公共卫生事件”为核心研究主题。突现词表明“大数据”“人工智能”成为前沿热点。结论 我国传染病监测预警体系在政策驱动、技术革新及疫情推动下的快速发展，核心作者合作网络与跨学科融合推动研究深化。未来需加强数据标准化建设，促进多源信息整合，优化人工智能预测模型，并拓展国际合作以提升全球公共卫生治理能力。

Objective To elucidate the research dynamics and knowledge structure in the field of infectious disease surveillance and early warning in China, this study aims to reveal the current status, evolution of research hotspots, and frontier trends in this domain, thereby providing a scientific basis for optimizing the infectious disease surveillance and early warning system. Methods The China National Knowledge Infrastructure(CNKI) and the Web of Science(WOS) Core Collection databases were selected as the data sources, and relevant Chinese and English literature on infectious disease surveillance and early warning from the establishment of these databases to 2024 were retrieved. After a rigorous screening process, a total of 6 065 articles were ultimately included. CiteSpace software was employed to construct co-authorship networks, keyword co-occurrence, and clustering maps. In addition, burst detection techniques were applied to systematically analyze the evolution and spatial-temporal distribution patterns of research hotspots. Results The research on infectious disease surveillance and early warning in China has evolved throughthree stages: inception, initiation, and rapid development. A core group of authors has initially formed, with scholars such as Ma Jiaqi and Wang Liping making significant contributions in the areas of surveillance system standardization and epidemiological evaluation. Keyword analysis revealed that "infectious diseases" "early warning systems" and "public health emergencies" are the core research themes. Burst terms indicated that "big data" and "artificial intelligence" have emerged as frontier hotspots. Conclusions This study clearly illustrates the remarkable development of the infectious disease surveillance and early warning system in China, which has been propelled by policy support, technological innovation, and the impetus of epidemic events. The formation of core authorship network and the integration of interdisciplinary knowledge have further facilitatedthe indepth exploration of this field. In the future, efforts should be concentrated on strengthening data standardization, promoting the integration of multi-source information, optimizing artificial intelligence-based predictive models, and expanding international cooperation, all of which are crucial for enhancing global public health governance capacity.