Article(id=1321169542798234368, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, articleNumber=null, orderNo=null, doi=10.11847/zgggws1147588, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1743436800000, receivedDateStr=2025-04-01, revisedDate=1751299200000, revisedDateStr=2025-07-01, acceptedDate=1754064000000, acceptedDateStr=2025-08-02, onlineDate=1792920965146, onlineDateStr=2026-10-25, pubDate=1762704000000, pubDateStr=2025-11-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792920965146, onlineIssueDateStr=2026-10-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792920965146, creator=13701087609, updateTime=1792920965146, updator=13701087609, issue=Issue{id=1321169495406785472, tenantId=1146029695717560320, journalId=1319373219989389464, year='2025', volume='41', issue='11', pageStart='1281', pageEnd='1408', issueExtLink='null', onlineDate='null', pubDate='1762704000000', pubDateStr='2025-11-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792920953847, creator='13701087609', updateTime=1793011176900, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321547918390178721, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321547918390178722, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1396, endPage=1402, ext={EN=ArticleExt(id=1321169543083447041, articleId=1321169542798234368, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Visual analysis of studies of field epidemiology in China from 2014 to 2024 based on CiteSpace, columnId=1320427686514770171, journalTitle=Chinese Journal of Public Health, columnName=Survey and Report, runingTitle=null, highlight=null, articleAbstract=
Objective To conduct a visual analysis of the research dynamics, hotspots, and frontiers in field epidemiology in China from 2014 to 2024, providing a reference for research planning in this domain.
Methods The literature on field epidemiology in China that was published in Chinese and English between January 1, 2014 and December 31, 2024 was retrieved from the China National Knowledge Infrastructure (CNKI), SinoMed, Web of Science Core Collection, and PubMed. CiteSpace 6.3.R1 was employed to visualize the annual publication trend, author and institution collaboration networks, and keywords. Research hotspots and frontiers were systematically reviewed.
Results A total of 8 475 articles (7 845 in Chinese and 630 in English) were included. The annual number of publications in Chinese and English increased from 638 and 25 in 2014 to 728 and 66 in 2024, respectively. From 2014 to 2024, the annual number of publications in English that were published by Chinese authors showed an overall upward trend (β = 6.000, t = 4.861, P < 0.001), while that in Chinese rose with large fluctuations (β = 14.564, t = 1.456, P = 0.179). The most frequent category was infectious diseases (4 013 articles). Academic journals were the primary publication format (6 891 articles). Regarding methodological applications, descriptive studies (3 260 articles) were mainly used for spatiotemporal distribution analysis of infectious diseases and characterization of chemical poisoning incidents. Case-control studies (2 481 articles) were primarily applied in tracing foodborne illnesses and analyzing occupational exposure associations. Cohort studies (1 160 articles) were commonly conducted to investigate the impact of vaccination history on disease incidence. Cross-sectional surveys (398 articles) were frequently employed in nutritional status censuses. Molecular source-tracing techniques (127 articles) were predominantly utilized in studies of foodborne pathogens. In author and institution collaboration networks, high-yield authors of publications in Chinese were Wang H, Ye Y, Huang X, etc., and those in English were Zhang Y, Wang L, Wang Y, etc. The Chinese Center for Disease Control and Prevention occupied a central position in both Chinese and English publication networks. Keyword co-occurrence analysis revealed large nodes for "epidemiological characteristics," "outbreak," and "food poisoning" in Chinese publications and for "disease outbreaks," "public health surveillance," "risk factors," etc. in English publications. Keyword clustering analysis showed that in Chinese publications, Clusters #11 (outbreak), #14 (outbreak epidemic), and #5 (investigation analysis) formed a methodological loop from event identification to field response and source attribution. Clusters #10 (clustering) and #9 (family clusters) highlighted households and communities as key transmission settings. Co-occurrence of #6 (tuberculosis) and #3 (pulmonary tuberculosis) indicated continued focus on classical respiratory diseases, emphasizing pathogen control. In English publications, Clusters #1 (betacoronavirus), #4 (communicable diseases), and #8 (pulmonary tuberculosis) formed a triangular co-occurrence cluster. Clusters #3 (disease outbreaks), #6 (disease outbreaks), #0 (case control studies), and #2 (risk factors) systematically mapped the emergency response pathway from outbreak detection and case-control studies to risk factor identification, reflecting the systematization of public health emergency response. Clusters #12 (occupational disease) and #10 (noise) indicated occupational noise exposure as a current research focus. Keyword burst detection identified COVID-19, mpox, and mpox virus as emerging hotspots in Chinese publications, and spatio-temporal analysis and disease outbreaks in English publications.
Conclusions The studies of field epidemiology in China exhibits an upward trend and is gradually extending towards practical applications.
, authors=Qian LIU, Youmin ZHAO, Hongxin WANG, Qi WANG, authorsList=Qian LIU, Youmin ZHAO, Hongxin WANG, Qi WANG, authorCompany=null, correspAuthors=Qi WANG, authorNote=null, correspAuthorsNote=
, copyrightStatement=Copyright © 2025 Chinese Journal of Public Health. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321169544673088270, articleId=1321169542798234368, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=2014—2024年中国现场流行病学研究CiteSpace可视化分析, columnId=1320427686770622717, journalTitle=中国公共卫生, columnName=调查报告与分析, runingTitle=null, highlight=null, articleAbstract=
目的 对2014—2024年中国现场流行病学领域的研究动态、热点内容和前沿趋势进行可视化分析，为该领域的研究布局提供参考依据。
方法 检索中国知识资源总库（CNKI）、中国生物医学文献服务系统（SinoMed）、Web of Science核心合集和PubMed 数据库2014年1月1日—2024年12月31日公开发表的关于中国现场流行病学领域相关中、英文文献，应用CiteSpace 6.3.R1软件对该领域2014—2024年的年度发文量变化趋势以及研究作者、研究机构合作网络和关键词进行可视化分析，并对研究热点和前沿方向进行系统梳理。
结果 最终纳入8475篇文献（中文文献7845篇、英文文献630篇），中文和英文发文量分别从2014年的638和25篇上升至2024年的728和66篇，中国2014—2024现场流行病学领域英文文献发文量总体呈上升趋势（β=6.000，t=4.861，P<0.001），而中文文献发文量虽有所增多但因年度间波动较大，上升趋势差异无统计学意义（β=14.564，t=1.456，P=0.179）；纳入文献数量最多的类别为传染病类（4013篇），学术期刊是该领域文献发表的主要出版形式（6891篇）；在文献方法学应用类别分析中，描述性研究（3 260篇）主要用于传染病时空分布分析及化学中毒事件现场描述；病例对照研究（2 481篇）主要应用于食源性疾病溯源及职业暴露关联分析；队列研究（1 160篇）多见于疫苗接种史对患病影响的研究；横断面调查（398篇）常见于居民营养状况普查；分子溯源技术（127篇）多见于分析食源性致病菌研究。在作者和机构合作网络中，2014—2024年现场流行病学领域中文和英文文献的高产作者分别为王海峰、叶莹、黄学勇等和Zhang Y、Wang L、Wang Y等，中国疾病预防控制中心处于中文和英文文献的核心位置。关键词共现分析结果显示，“流行特征”“暴发”“食物中毒”在中文文献中占据较大的节点，“disease outbreaks”“public health surveillance” “risk factors”等关键词在英文文献中占据较大的节点。关键词聚类分析结果显示，在中文文献中，#11（暴发）、#14（暴发疫情）与#5（调查分析），形成事件识别到现场处置再到溯源归因的方法闭环；而#10（聚集性）和#9（家庭聚集）等模块揭示了家庭与社区为疫情关键传播场景，#6（结核）与#3（肺结核）经典呼吸道疾病共现，疾病防控聚焦于病原体控制。在英文文献中，#1（betacoronavirus）、#4（communicable diseases）和#8（pulmonary tuberculosis）构成三角共现簇，#3（disease outbreaks）、#6（disease outbreaks）、#0（case control studies）与#2（risk factors）等聚类完整构建了从暴发识别、病例对照到风险因素溯源的应急响应方法，体现了公共卫生应急处置的系统化发展；#12（occupational disease）与#10（noise）模块揭示职业性噪声暴露是目前职业病研究的焦点。关键词突现分析结果显示，新型冠状病毒感染、猴痘、猴痘病毒和spatio-temporal analysis、disease outbreaks分别成为中文和英文文献新的研究热点。
结论 中国现场流行病学研究呈上升趋势，且逐步向实际应用拓展。
, authors=刘倩, 赵幼敏, 王洪欣, 王齐
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