Abstract
王瑶瑶,霍大柱,李中杰,叶楚楚,郝莉鹏,杨维中.基于德尔菲法的急性呼吸道传染病监测数据源指标体系构建[J].Chinese journal of Epidemiology,2024,45(11):1605-1610
基于德尔菲法的急性呼吸道传染病监测数据源指标体系构建
Construction of data source indicator system for acute respiratory infectious disease surveillance based on the Delphi method
Received:June 25, 2024  
DOI:10.3760/cma.j.cn112338-20240625-00372
KeyWord: 德尔菲法  急性呼吸道传染病  监测数据源  指标体系
English Key Word: Delphi method  Acute respiratory infectious disease  Surveillance data source  Indicator system
FundProject:国家重点研发计划(2023YFC2308701);中国医学科学院医学与健康科技创新工程(2021-I2M-1-044,2023-I2M-3-011);上海市加强公共卫生体系建设三年行动计划(GWVI-11.1-02-传染病学)
Author NameAffiliationE-mail
Wang Yaoyao Department of Acute Infectious Disease Control and Prevention, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai 200136, China  
Huo Dazhu School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China  
Li Zhongjie School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China  
Ye Chuchu Department of Acute Infectious Disease Control and Prevention, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai 200136, China  
Hao Lipeng Department of Acute Infectious Disease Control and Prevention, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai 200136, China lphao@pdcdc.sh.cn 
Yang Weizhong School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China yangweizhong@cams.cn 
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Abstract:
      目的 建立急性呼吸道传染病监测数据源指标体系,为急性呼吸道传染病监测预警提供理论基础。方法 通过文献综述初步拟定急性呼吸道传染病监测数据源指标,在此基础上运用德尔菲专家咨询法对22人进行2轮专家咨询,进一步确定指标内容。结果 2轮专家咨询的问卷回收率分别为100.00%和86.36%,专家的权威系数均为0.83,第二轮德尔菲专家咨询的Kendall's W值为0.32,各指标变异系数均<0.25。最终构建成的急性呼吸道传染病监测数据源指标体系包括4项一级指标、10项二级指标和26项三级指标。结论 本研究构建的急性呼吸道传染病监测数据源指标体系具有较好的科学性和可靠性,能为急性呼吸道传染病的监测预警和政策制定提供参考依据。
English Abstract:
      Objective To establish an indicator system for surveillance of data sources to provide a theoretical basis for respiratory infectious disease surveillance and early warning. Methods Indicators for data sources in the surveillance of acute respiratory infectious diseases were initially compiled through a literature search. Subsequently, two rounds of expert consultations were conducted with 22 experts using the Delphi method to refine the indicators. Results The questionnaire recovery rates for the two rounds of expert consultation were 100.00% and 86.36%, respectively. The authority coefficient of the experts was 0.83. The coordination coefficient of the second round of Delphi expert consultation was 0.32, and the coefficient of variation of each indicator was less than 0.25. Finally, the indicators system of data source for the surveillance of acute respiratory infectious diseases includes 4 first-level indicators, 10 second-level indicators, and 26 third-level indicators. Conclusion The indicator system of data sources for the surveillance of acute respiratory infectious diseases constructed in this study is reasonable and reliable, providing a valuable reference for surveillance, early warning and policy formulation of acute respiratory infectious diseases.
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