Article(id=1240977215924531977, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240977214964036360, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202412304, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734451200000, receivedDateStr=2024-12-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773801624518, onlineDateStr=2026-03-18, pubDate=1748102400000, pubDateStr=2025-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773801624518, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773801624518, creator=13701087609, updateTime=1773801624518, updator=13701087609, issue=Issue{id=1240977214964036360, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='10', pageStart='1729', pageEnd='1920', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773801624289, creator=13701087609, updateTime=1773825591019, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241077738770068227, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240977214964036360, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241077738770068228, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240977214964036360, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1843, endPage=1848, ext={EN=ArticleExt(id=1240977216629175058, articleId=1240977215924531977, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Construction of the indicator system for evaluating the emergency response capability of county-level centers for disease control and prevention, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To develop an evaluation index system for public health emergency response capacity of county-level centers for Disease control and Prevention (CDC) to promote the construction of public health emergency response system and improve the emergency response capacity of county-level CDC in China.

Methods

The index system framework was developed based on a literature review and group discussions. The Delphi method was applied to select the evaluation indicators through two rounds of expert consultation involving 26 experts, and the weights of the indicators were determined using the Analytic Hierarchy Process (AHP).

Results

The system included 6 primary indicators, 21 secondary indicators, and 69 tertiary indicators. The weights of each indicator were calculated using the Analytic Hierarchy Process (AHP). The weight of first-level indicators from high to low were emergency response capacity (0.212), emergency system construction (0.199), emergency support capacity (0.175), monitoring and early warning capacity (0.170), emergency team (0.161), information communication and departmental collaboration (0.083). Among the second-level indicators, the weights of training exercise (0.490), early warning and prediction (0.490), and emergency fund guarantee (0.490) were in the top three. The consistency ratio (CR) values for the first-level, second-level, and third-level indicators were all below 0.1, which met the standard requirements of consistency test, and the weight division of indicators was reasonable.

Conclusion

This study provides indicator guidance for improving the emergency response capacity of county CDC, and promote the construction of public health emergency response system in China and the improvement of emergency response capacity of county CDC.

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目的

构建县级疾病预防控制中心突发公共卫生事件应急能力评价指标体系,推动我国公共卫生应急体系的建设和县级CDC应急能力的提升。

方法

通过文献研究和小组讨论构建指标体系框架,采用德尔菲法对26位专家进行两轮咨询确定评价指标,并运用层次分析法(AHP)计算了各指标的权重。

结果

通过两轮专家咨询,构建了一个包含6项一级指标、21项二级指标和69项三级指标的县级CDC应急能力评价指标体系。一级指标权重从大到小分别是应急处置能力(0.212)、应急体系建设(0.199)、应急保障能力(0.175)、监测预警能力(0.170)、应急队伍(0.161)、信息沟通与部门协作(0.083)。二级指标中,培训演练(0.490)、预警预测(0.490)、应急资金保障(0.490)权重位于前三。一级指标、二级指标和三级指标的一致性比率(CR)均小于0.1,符合一致性检验的标准要求,表明指标权重分配合理。

结论

该研究为提升县级CDC突发公共卫生事件应急能力提供了指标指引,有助于我国公共卫生应急体系的建设和县级CDC应急能力的提升。

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赵莉,E-mail:
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马思思(2001—),女,硕士在读,研究方向:卫生政策与管理

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Evaluation based on expert judgment

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判断依据影响程度
实践经验0.300.40.5
理论分析0.100.20.3
参考文献0.050.10.1
直觉0.050.10.1
向同行了解0.050.10.1
), ArticleFig(id=1240996915723162198, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=CN, label=表1, caption=

专家判断依据评定

, figureFileSmall=null, figureFileBig=null, tableContent=
判断依据影响程度
实践经验0.300.40.5
理论分析0.100.20.3
参考文献0.050.10.1
直觉0.050.10.1
向同行了解0.050.10.1
), ArticleFig(id=1240996915869962849, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=EN, label=Table 2, caption=

Basic information of experts

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项目内容频数
n
构成比
%
性别1976.0
624.0
年龄(岁)
≤3000.0
>30~40416.0
>40~501144.0
>501040.0
受教育程度
本科及以下1352.0
硕士研究生832.0
博士研究生416.0
工作单位性质
卫生健康主管部门832.0
卫生事业单位1456.0
科研院校312.0
从事专业领域
卫生行政管理832.0
疾病预防与控制1456.0
公共卫生312.0
工作年限(年)
≤500.0
>5~1014.0
>10~20728.0
>20~301040.0
>30728.0
职称初级00.0
中级312.0
副高级1872.0
正高级416.0
), ArticleFig(id=1240996915979014764, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=CN, label=表2, caption=

专家基本情况

, figureFileSmall=null, figureFileBig=null, tableContent=
项目内容频数
n
构成比
%
性别1976.0
624.0
年龄(岁)
≤3000.0
>30~40416.0
>40~501144.0
>501040.0
受教育程度
本科及以下1352.0
硕士研究生832.0
博士研究生416.0
工作单位性质
卫生健康主管部门832.0
卫生事业单位1456.0
科研院校312.0
从事专业领域
卫生行政管理832.0
疾病预防与控制1456.0
公共卫生312.0
工作年限(年)
≤500.0
>5~1014.0
>10~20728.0
>20~301040.0
>30728.0
职称初级00.0
中级312.0
副高级1872.0
正高级416.0
), ArticleFig(id=1240996916062900852, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=EN, label=Table 3, caption=

Degree of expert authority

, figureFileSmall=null, figureFileBig=null, tableContent=
熟悉程度
Cs
专家判断系数
Ca
权威系数
Cr
第一轮0.930.980.95
第二轮0.900.980.94
), ArticleFig(id=1240996916222284412, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=CN, label=表3, caption=

专家权威程度

, figureFileSmall=null, figureFileBig=null, tableContent=
熟悉程度
Cs
专家判断系数
Ca
权威系数
Cr
第一轮0.930.980.95
第二轮0.900.980.94
), ArticleFig(id=1240996916348113542, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=EN, label=Table 4, caption=

Kendall coordination coefficients of indicators at all levels in two rounds of expert consultation

, figureFileSmall=null, figureFileBig=null, tableContent=
指标肯德尔协调系数(Wχ2P
第一轮
一级指标0.51577.271<0.001
二级指标0.251137.881<0.001
三级指标0.184359.280<0.001
总体指标0.219575.620<0.001
第二轮
一级指标0.54167.637<0.010
二级指标0.250124.911<0.010
三级指标0.214401.207<0.010
总体指标0.236600.823<0.010
), ArticleFig(id=1240996916478136974, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=CN, label=表4, caption=

两轮专家咨询各级指标肯德尔协调系数

, figureFileSmall=null, figureFileBig=null, tableContent=
指标肯德尔协调系数(Wχ2P
第一轮
一级指标0.51577.271<0.001
二级指标0.251137.881<0.001
三级指标0.184359.280<0.001
总体指标0.219575.620<0.001
第二轮
一级指标0.54167.637<0.010
二级指标0.250124.911<0.010
三级指标0.214401.207<0.010
总体指标0.236600.823<0.010
), ArticleFig(id=1240996916582994583, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=EN, label=Table 5, caption=

Intra-group correlation coefficients of indicators at all levels in two rounds of expert consultation

, figureFileSmall=null, figureFileBig=null, tableContent=
指标组内相关系数
ICC,95%CI
P
第一轮
一级指标0.755(0.546~0.881)<0.001
二级指标0.936(0.893~0.967)<0.001
三级指标0.980(0.967~0.990)<0.001
总体指标0.985(0.975~0.992)<0.001
第二轮
一级指标0.887(0.797~0.944)<0.001
二级指标0.937(0.895~0.968)<0.001
三级指标0.984(0.974~0.992)<0.001
总体指标0.987(0.978~0.993)<0.001
), ArticleFig(id=1240996916679463582, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=CN, label=表5, caption=

两轮专家咨询各级指标组内相关系数

, figureFileSmall=null, figureFileBig=null, tableContent=
指标组内相关系数
ICC,95%CI
P
第一轮
一级指标0.755(0.546~0.881)<0.001
二级指标0.936(0.893~0.967)<0.001
三级指标0.980(0.967~0.990)<0.001
总体指标0.985(0.975~0.992)<0.001
第二轮
一级指标0.887(0.797~0.944)<0.001
二级指标0.937(0.895~0.968)<0.001
三级指标0.984(0.974~0.992)<0.001
总体指标0.987(0.978~0.993)<0.001
), ArticleFig(id=1240996916788515495, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=EN, label=Table 6, caption=

Evaluation index system of public health emergency response capacity of county-level CDCS

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标权重二级指标权重三级指标权重合成权重
A1应急体系建设0.199 B1-1应急组织机构0.387 C1-1-1设立应急管理机构0.333 0.026
C1-1-2应急管理人员配置情况0.667 0.003
B1-2应急制度0.275 C1-2-1制定应急管理相关制度0.333 0.018
C1-2-2应急管理科室职责明确情况0.667 0.667
B1-3应急管理机制建设0.198 C1-3-1应急组织指挥体系完善情况0.178 0.007
C1-3-2现场处置机制0.221 0.009
C1-3-3监测预警机制0.247 0.010
C1-3-4保障机制0.142 0.006
C1-3-5联防联控机制0.126 0.005
C1-3-6群防群控机制0.087 0.003
B1-4应急预案制定0.140 C1-4-1应急预案、技术方案完整性和完善情况0.312 0.009
C1-4-2应急预案、技术方案的可操作性0.490 0.014
C1-4-3应急预案、技术方案的知晓和熟练掌握情况0.198 0.006
A2应急队伍建设0.161 B2-1专家库0.198 C2-1-1设立应急专家库情况0.142 0.005
C2-1-2专家专业构成情况0.200 0.006
C2-1-3建立专家库管理制度0.329 0.011
C2-1-4上级指导专家设置情况0.329 0.011
B2-2应急队伍0.312 C2-2-1建立应急队伍管理制度0.242 0.012
C2-2-2应急队伍联动机制0.320 0.016
C2-2-3应急队伍数量和构成情况0.187 0.009
C2-2-4应急队伍参加训练情况0.143 0.007
C2-2-5应急队伍装备配置情况0.108 0.005
B2-3培训演练0.490 C2-3-1培训演练的频次和覆盖率0.198 0.016
C2-3-2培训演练的方式开展情况0.312 0.025
C2-3-3培训演练的效果评估与考核0.490 0.039
A3监测预警能力0.170 B3-1监测分析0.312 C3-1-1信息收集来源0.246 0.013
C3-1-2事件报告完整率和及时率0.190 0.010
C3-1-3事件判定流程和工作规范情况0.171 0.009
C3-1-4建立应急信息报告制度及执行情况0.288 0.015
C3-1-5监测系统使用情况0.105 0.006
B3-2风险评估0.198 C3-2-1风险评估工作开展情况0.490 0.017
C3-2-2风险评估机制建立情况0.198 0.007
C3-2-3风险评估结果运用情况0.312 0.011
B3-3预警预测0.490 C3-3-1预警信息通报机制建立情况0.6670.055
C3-3-2监测信息分析预测情况0.3330.028
A4应急处置能力0.212 B4-1应急指挥协调0.264 C4-1-1应急领导小组组织和分工情况0.5000.028
C4-1-2启动应急响应情况0.5000.028
B4-2现场调查0.419 C4-2-1应急事件规范处置率情况0.272 0.024
C4-2-2应急事件原因查明率情况0.125 0.011
C4-2-3应急事件处置及时率情况0.416 0.037
C4-2-4应急事件处置上报及时率情况0.187 0.017
B4-3实验室检测0.140 C4-3-1可开展检测项目情况0.103 0.003
C4-3-2人员配置及专业情况0.077 0.002
C4-3-3仪器设备配置及使用情况0.092 0.003
C4-3-4应急样本采集、保留、运输和检测情况0.133 0.004
C4-3-5实验室生物安全防护等级0.122 0.004
C4-3-6质量管理规范建设情况0.134 0.004
C4-3-7实验室开展计量认证/认可通过率0.138 0.004
C4-3-8实验室外部质控考核合格率0.201 0.006
B4-4总结评估0.177 C4-4-1应急事件处置后开展总结评估0.6670.025
C4-4-2应急事件处置效果总结评估0.3330.012
A5应急保障能力0.175 B5-1应急资金保障0.490 C5-1-1应急专项经费满足全年工作需要情况0.6670.057
C5-1-2应急时财政追加经费情况0.3330.029
B5-2应急物资管理及储备0.312 C5-2-1制订应急物资管理及调用制度0.329 0.018
C5-2-2建立应急物资储备目录和计划0.329 0.018
C5-2-3应急物资管理和获得渠道建立0.200 0.011
C5-2-4中心现有应急物资储备情况0.142 0.008
B5-3应急人员保障0.198 C5-3-1应急人员人身安全保障0.6670.023
C5-3-2应急人员物资供应情况0.3330.012
A6信息沟通与部门协作0.083B6-1应急宣传教育0.198 C6-1-1宣传教育频率及覆盖率情况0.198 0.003
C6-1-2宣传教育途径0.312 0.005
C6-1-3宣传教育效果情况0.490 0.008
B6-2风险沟通0.275 C6-2-1风险沟通机制建设情况0.490 0.011
C6-2-2与媒体沟通及报道情况0.312 0.007
C6-2-3开展风险沟通技巧培训情况0.198 0.005
B6-3区域或部门协作0.387 C6-3-1与横向纵向部门配合情况0.6670.021
C6-3-2与毗邻地区地市疾控中心的联动情况0.3330.011
B6-4社会支持0.140 C6-4-1社会支持资源参与情况0.333 0.004
C6-4-2社会公众参与配合情况0.667 0.008
), ArticleFig(id=1240996916935316147, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977215924531977, language=CN, label=表6, caption=

县级CDC突发公共卫生事件应急能力评价指标体系

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一级指标权重二级指标权重三级指标权重合成权重
A1应急体系建设0.199 B1-1应急组织机构0.387 C1-1-1设立应急管理机构0.333 0.026
C1-1-2应急管理人员配置情况0.667 0.003
B1-2应急制度0.275 C1-2-1制定应急管理相关制度0.333 0.018
C1-2-2应急管理科室职责明确情况0.667 0.667
B1-3应急管理机制建设0.198 C1-3-1应急组织指挥体系完善情况0.178 0.007
C1-3-2现场处置机制0.221 0.009
C1-3-3监测预警机制0.247 0.010
C1-3-4保障机制0.142 0.006
C1-3-5联防联控机制0.126 0.005
C1-3-6群防群控机制0.087 0.003
B1-4应急预案制定0.140 C1-4-1应急预案、技术方案完整性和完善情况0.312 0.009
C1-4-2应急预案、技术方案的可操作性0.490 0.014
C1-4-3应急预案、技术方案的知晓和熟练掌握情况0.198 0.006
A2应急队伍建设0.161 B2-1专家库0.198 C2-1-1设立应急专家库情况0.142 0.005
C2-1-2专家专业构成情况0.200 0.006
C2-1-3建立专家库管理制度0.329 0.011
C2-1-4上级指导专家设置情况0.329 0.011
B2-2应急队伍0.312 C2-2-1建立应急队伍管理制度0.242 0.012
C2-2-2应急队伍联动机制0.320 0.016
C2-2-3应急队伍数量和构成情况0.187 0.009
C2-2-4应急队伍参加训练情况0.143 0.007
C2-2-5应急队伍装备配置情况0.108 0.005
B2-3培训演练0.490 C2-3-1培训演练的频次和覆盖率0.198 0.016
C2-3-2培训演练的方式开展情况0.312 0.025
C2-3-3培训演练的效果评估与考核0.490 0.039
A3监测预警能力0.170 B3-1监测分析0.312 C3-1-1信息收集来源0.246 0.013
C3-1-2事件报告完整率和及时率0.190 0.010
C3-1-3事件判定流程和工作规范情况0.171 0.009
C3-1-4建立应急信息报告制度及执行情况0.288 0.015
C3-1-5监测系统使用情况0.105 0.006
B3-2风险评估0.198 C3-2-1风险评估工作开展情况0.490 0.017
C3-2-2风险评估机制建立情况0.198 0.007
C3-2-3风险评估结果运用情况0.312 0.011
B3-3预警预测0.490 C3-3-1预警信息通报机制建立情况0.6670.055
C3-3-2监测信息分析预测情况0.3330.028
A4应急处置能力0.212 B4-1应急指挥协调0.264 C4-1-1应急领导小组组织和分工情况0.5000.028
C4-1-2启动应急响应情况0.5000.028
B4-2现场调查0.419 C4-2-1应急事件规范处置率情况0.272 0.024
C4-2-2应急事件原因查明率情况0.125 0.011
C4-2-3应急事件处置及时率情况0.416 0.037
C4-2-4应急事件处置上报及时率情况0.187 0.017
B4-3实验室检测0.140 C4-3-1可开展检测项目情况0.103 0.003
C4-3-2人员配置及专业情况0.077 0.002
C4-3-3仪器设备配置及使用情况0.092 0.003
C4-3-4应急样本采集、保留、运输和检测情况0.133 0.004
C4-3-5实验室生物安全防护等级0.122 0.004
C4-3-6质量管理规范建设情况0.134 0.004
C4-3-7实验室开展计量认证/认可通过率0.138 0.004
C4-3-8实验室外部质控考核合格率0.201 0.006
B4-4总结评估0.177 C4-4-1应急事件处置后开展总结评估0.6670.025
C4-4-2应急事件处置效果总结评估0.3330.012
A5应急保障能力0.175 B5-1应急资金保障0.490 C5-1-1应急专项经费满足全年工作需要情况0.6670.057
C5-1-2应急时财政追加经费情况0.3330.029
B5-2应急物资管理及储备0.312 C5-2-1制订应急物资管理及调用制度0.329 0.018
C5-2-2建立应急物资储备目录和计划0.329 0.018
C5-2-3应急物资管理和获得渠道建立0.200 0.011
C5-2-4中心现有应急物资储备情况0.142 0.008
B5-3应急人员保障0.198 C5-3-1应急人员人身安全保障0.6670.023
C5-3-2应急人员物资供应情况0.3330.012
A6信息沟通与部门协作0.083B6-1应急宣传教育0.198 C6-1-1宣传教育频率及覆盖率情况0.198 0.003
C6-1-2宣传教育途径0.312 0.005
C6-1-3宣传教育效果情况0.490 0.008
B6-2风险沟通0.275 C6-2-1风险沟通机制建设情况0.490 0.011
C6-2-2与媒体沟通及报道情况0.312 0.007
C6-2-3开展风险沟通技巧培训情况0.198 0.005
B6-3区域或部门协作0.387 C6-3-1与横向纵向部门配合情况0.6670.021
C6-3-2与毗邻地区地市疾控中心的联动情况0.3330.011
B6-4社会支持0.140 C6-4-1社会支持资源参与情况0.333 0.004
C6-4-2社会公众参与配合情况0.667 0.008
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县级疾控中心突发公共卫生事件应急能力评价指标体系构建
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马思思 1 , 李祥 2 , 范琳林 1 , 陈冬琼 1 , 陈颖 1 , 范泽炜 1 , 蒋莉华 1, 3 , 杜宇 4, 5 , 赵莉 1, 4
现代预防医学 | 卫生政策与管理 2025,52(10): 1843-1848
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现代预防医学 | 卫生政策与管理 2025, 52(10): 1843-1848
县级疾控中心突发公共卫生事件应急能力评价指标体系构建
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马思思1, 李祥2, 范琳林1, 陈冬琼1, 陈颖1, 范泽炜1, 蒋莉华1, 3, 杜宇4, 5, 赵莉1, 4
作者信息
  • 1.四川大学华西公共卫生学院/四川大学华西第四医院 卫生政策与管理学系,四川 成都 610041
  • 2.富顺县卫生健康局/富顺县中医药管理局
  • 3.四川大学华西临床医学院/四川大学华西医院
  • 4.四川大学华西-协和陈志潜卫生健康研究院卫生应急管理研究中心
  • 5.四川大学华西公共卫生学院/四川大学华西第四医院 急诊与重症医学科
  • 马思思(2001—),女,硕士在读,研究方向:卫生政策与管理

通讯作者:

赵莉,E-mail:
Construction of the indicator system for evaluating the emergency response capability of county-level centers for disease control and prevention
Si-si MA1, Xiang LI2, Lin-lin FAN1, Dong-qiong CHEN1, Ying CHEN1, Ze-wei FAN1, Li-hua JIANG1, 3, Yu DU4, 5, Li ZHAO1, 4
Affiliations
  • Department of Health Policy and Management, West China School of Public Health/The Fourth West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2025-05-25 doi: 10.20043/j.cnki.MPM.202412304
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目的

构建县级疾病预防控制中心突发公共卫生事件应急能力评价指标体系,推动我国公共卫生应急体系的建设和县级CDC应急能力的提升。

方法

通过文献研究和小组讨论构建指标体系框架,采用德尔菲法对26位专家进行两轮咨询确定评价指标,并运用层次分析法(AHP)计算了各指标的权重。

结果

通过两轮专家咨询,构建了一个包含6项一级指标、21项二级指标和69项三级指标的县级CDC应急能力评价指标体系。一级指标权重从大到小分别是应急处置能力(0.212)、应急体系建设(0.199)、应急保障能力(0.175)、监测预警能力(0.170)、应急队伍(0.161)、信息沟通与部门协作(0.083)。二级指标中,培训演练(0.490)、预警预测(0.490)、应急资金保障(0.490)权重位于前三。一级指标、二级指标和三级指标的一致性比率(CR)均小于0.1,符合一致性检验的标准要求,表明指标权重分配合理。

结论

该研究为提升县级CDC突发公共卫生事件应急能力提供了指标指引,有助于我国公共卫生应急体系的建设和县级CDC应急能力的提升。

县级疾病预防控制中心  /  应急能力  /  指标体系  /  德尔菲法  /  层次分析法
Objective

To develop an evaluation index system for public health emergency response capacity of county-level centers for Disease control and Prevention (CDC) to promote the construction of public health emergency response system and improve the emergency response capacity of county-level CDC in China.

Methods

The index system framework was developed based on a literature review and group discussions. The Delphi method was applied to select the evaluation indicators through two rounds of expert consultation involving 26 experts, and the weights of the indicators were determined using the Analytic Hierarchy Process (AHP).

Results

The system included 6 primary indicators, 21 secondary indicators, and 69 tertiary indicators. The weights of each indicator were calculated using the Analytic Hierarchy Process (AHP). The weight of first-level indicators from high to low were emergency response capacity (0.212), emergency system construction (0.199), emergency support capacity (0.175), monitoring and early warning capacity (0.170), emergency team (0.161), information communication and departmental collaboration (0.083). Among the second-level indicators, the weights of training exercise (0.490), early warning and prediction (0.490), and emergency fund guarantee (0.490) were in the top three. The consistency ratio (CR) values for the first-level, second-level, and third-level indicators were all below 0.1, which met the standard requirements of consistency test, and the weight division of indicators was reasonable.

Conclusion

This study provides indicator guidance for improving the emergency response capacity of county CDC, and promote the construction of public health emergency response system in China and the improvement of emergency response capacity of county CDC.

County-level centers for disease control and prevention  /  Emergency response capacity  /  Indicator system  /  Delphi method  /  Analytic hierarchy process
马思思, 李祥, 范琳林, 陈冬琼, 陈颖, 范泽炜, 蒋莉华, 杜宇, 赵莉. 县级疾控中心突发公共卫生事件应急能力评价指标体系构建. 现代预防医学, 2025 , 52 (10) : 1843 -1848 . DOI: 10.20043/j.cnki.MPM.202412304
Si-si MA, Xiang LI, Lin-lin FAN, Dong-qiong CHEN, Ying CHEN, Ze-wei FAN, Li-hua JIANG, Yu DU, Li ZHAO. Construction of the indicator system for evaluating the emergency response capability of county-level centers for disease control and prevention[J]. Modern Preventive Medicine, 2025 , 52 (10) : 1843 -1848 . DOI: 10.20043/j.cnki.MPM.202412304
突发公共卫生事件的特点包括传播速度快、影响范围广和不确定性高,对人民的生命安全构成威胁并引发财产损失,对社会和经济发展造成不利影响[1]。在21世纪的前20年里,全球范围内突发公共卫生事件的发生率持续攀升,人类共面临了5起由重大传染病引发的严重突发公共卫生危机[2]
自SARS疫情以来,我国对突发公共卫生事件的应急工作予以了高度关注,国家有关部门相继出台了一系列政策[3-7]。公共卫生系统的完整性显著提高,特别是省级和市级疾病预防控制中心(Center for Disease Control and Prevention,CDC)对突发公共卫生事件的管理(提高到近90%),建立更优的资源配置和服务提供的CDC体系,该体系帮助我国从仓促应对SARS转变为2013年有组织应对H7N9禽流感提供了坚实的基础,包括更优的教育结构、财政支持和监测和预警能力[8-9],被世界卫生组织确定为值得推荐的应对模式。
CDC作为应对突发公共卫生事件的主力力量,其应急能力的强弱影响着应急体系的完善[3]。而县级CDC是“国家—省—市—县”四级疾控体系依托网底,在我国疾控工作的落实中起到关键作用[4-5]。当前,县级疾控体系虽已形成基础能力框架,但面对新发传染病、复合型灾害等复杂挑战,传统指标在风险预警灵敏度、多部门协同效能、智慧化技术应用等维度存在滞后性[10]。此前关于疾控中心突发公共卫生事件应急能力评价指标体系构建研究已存在,本研究强调针对县级疾控中心的特殊需求,结合实际情况的评价体系。因此,建立一个统一标准或具有实际参考价值的县级疾病预防控制中心突发公共卫生事件应急能力评价指标体系,既能服务于日常风险评估与预案演练的质量控制,又能为突发事件的快速分级响应提供决策依据,最终实现从被动应对向主动防控的战略转型,切实筑牢基层公共卫生安全屏障。
以各种相关词汇“县级疾病预防控制中心”“突发公共卫生事件”“应急能力”等在知网、PubMed、万方等数据库进行检索,并访问国家卫生健康委员会、国家疾病预防控制局等官方网站收集整理相关指标并对指标进行初步筛选,形成指标体系初步框架。经过研究小组讨论拟定出初步的指标体系,其中包括7个一级指标、23个二级指标和79个三级指标。
根据既往相关研究,咨询专家人数确定在20人左右较为合适[11],基于此,本研究邀请各研究领域专家26名,包括公共卫生管理、卫生行政管理和传染病预防与控制,专家工作单位包括卫生行政部门、高校公共卫生学院和疾病预防控制中心。专家纳入标准需满足两项条件:(1)从事CDC应急管理工作不少于5年;(2)具有中级及以上职称的卫生行政部门主管和应急研究方向的高校专家。
本研究依据确定的指标体系设计了咨询问卷,内容包括专家咨询的目的、专家基本信息、指标的重要性评定、熟悉程度以及判断系数四个部分。该问卷通过向专家发送邮件的方式进行问卷回收。本研究运用李克特5级评分法进行打分,指标重要程度分为1~5分,评定数值越大指标越重要[12]
专家的积极性用问卷有效率来表示。当问卷有效回收率超过70%时,说明专家的参与度较高[13],其研究结果具有较高的可信度。
专家的权威系数(Cr)是通过判断系数(Ca)和熟悉程度(Cs)的算术平均值来计算。当专家咨询的权威系数(Cr)超过0.70时,认为专家的意见是可信的[13-14]Cs分为5个等级,包括非常不熟悉、不太熟悉、一般熟悉、比较熟悉和很熟悉来表示程度,分别赋值为0.2,0.4,0.6,0.8,1;判断依据包含5个方面的内容,具体判断依据和赋值见表1
专家协调程度采用变异系数(CV[15]、肯德尔协调系数(W[16]和组内相关系数(Intraclass Correlation Coefficient,ICC[17]来表示。肯德尔协调系数(W)反映各专家意见的一致程度。该系数的取值范围是0至1,越接近1,表明专家一致程度越高。组内相关系数(ICC)可用于定量和定类数据,反映各专家对指标的一致性,ICC取值范围在0~1之间,大于0.75表示专家一致性很好[18],本研究采用双向/随机绝对一致性且平均度量计算ICC值。用χ2检验来检验肯德尔协调系数(W)的显著性,95%置信区间(Confidence Interval,CI)来检验ICC的显著性,P<0.05表示专家意见具有良好的协调性,结果可靠[19]
指标重要性可以通过专家集中程度来表示,通过算数平均数、均方差和CV来表示。高平均值和低CV表明指标重要性高。当指标重要性算数平均数值大于3.5,CV低于0.25,且满分比大于等于25%时该指标被纳入[20]
经过两轮专家咨询,通过专家积极性、权威性、协调程度和集中程度来评估指标的合理性和可靠性。根据专家的意见对指标进行删除、新增和修改,最终确定评价体系。
在SPSSAU在线数据平台中AHP权重计算板块通过设置计算方法和判断矩阵阶数后输入数据,SPSSAU会自动构建出相对重要性判断矩阵,默认输出计算权重和一致性检验结果。在既往研究中,多运用1~9标度法构建指标判断矩阵,TL Saaty通过试验研究得出,1~9标度的标度值便于打分,容易操作,可以量化分析评价专家的主观判断,计算指标权重。
德尔菲法共纳入26名咨询专家,专家基本情况见表2
第一轮咨询共邀请26位咨询专家,收回25份有效咨询专家问卷,咨询问卷有效率为96.15%;第二轮有26位专家受邀进行咨询,收到了25份有效的咨询问卷,有效率为96.15%。
两轮专家权威程度见表3
第一轮德尔菲法咨询肯德尔协调系数(W)范围为0.184~0.515(P<0.001),第二轮的范围为0.214~0.541(P<0.010)。两轮专家咨询的协调系数检验结果表明,专家意见在两轮中具有一致性(见表4)。第一轮德尔菲法专家咨询的组内相关系数(ICC)为0.755~0.985(P<0.001),第二轮为0.887~0.987(P<0.001),两轮组内相关系数提示专家对各级指标评分一致性很好(见表5)。
通过专家提出意见、纳入标准要求及讨论后,对指标进行了调整。经过整理编码,第一轮的指标体系框架由6个一级指标、21个二级指标和76个三级指标组成。经过第二轮专家咨询,最终确定的指标体系框架包括6个一级指标、21个二级指标和69个三级指标。
采用层次分析法计算各指标的权重,结果显示一级、二级和三级指标的一致性比率(CR)均低于0.1,符合一致性检验的要求,指标权重划分是合理的。各指标权重计算结果见表6
本研究共邀请了26位专家参与两轮德尔菲法咨询,两轮专家积极系数均为96.15%,表明专家们在指标体系构建过程中积极参与;同时,两轮的专家权威系数分别为0.95和0.94,表明参与的专家具有较高的权威性,研究结果的可靠性较强。
两轮专家咨询中,总体指标的肯德尔协调系数分别为0.219和0.236,且均具有统计学意义(P<0.01),表明专家的意见具有较高的一致性;同时,两轮专家咨询总体指标组内相关系数分别为0.985和0.987,且均具有统计学意义(P<0.001),说明专家们的意见趋于一致,指标体系构建结果具有很好的可靠性。
本研究结果显示,一级指标权重从大到小分别是应急处置能力(0.212)、应急体系建设(0.199)、应急保障能力(0.175)、监测预警能力(0.170)、应急队伍(0.161)、信息沟通与部门协作(0.083),说明良好的应急处置能力是县级疾病预防控制中心应对突发公共卫生事件的基石,本研究结果与周亚霖等[21]研究结果一致。成立区(县)级的应急专家库,能够增强县级疾病预防控制中心应急队伍在处理突发公共卫生事件时的能力,同时也是有效应对突发公共卫生事件的一种重要手段[22]。二级指标中,培训演练(0.490)、预警预测(0.490)、应急资金保障(0.490)权重位于前三,提示县(区)疾病预防控制中心通过应急模拟演练使工作人员熟知突发公共卫生事件应对流程是必要的。陈蓉等[23]研究认为,通过应急模拟演练可以有效反映出应急响应流程和预案不一致、流程不清晰等问题。汪丹丹等[24]研究中指出的应尽早采取有效响应、处置措施将影响控制在最小范围内,因此需要充足的应急资金,建立监测预警机制,从而确保其及时、规范及准确地应对事件。
本研究尚存在一定局限性:一是最终确立的指标体系尚未实际在县级疾病预防控制中心进行信度、效度检验;二是最终确立的指标体系缺乏具体的参考标准评定其应急能力的强弱,仅能通过得分的高低从一定程度上判定其应急能力强弱,在查阅相关文献和政策时也未发现针对县级CDC应急能力评价的等级标准,在后续的研究中可进一步完善。
  • 突发公共卫生事件应急管理学科建设(H200940)
  • 自贡市公共卫生应急管理体系、机制及核心能力指标研究(2020CDZG-22)
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2025年第52卷第10期
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doi: 10.20043/j.cnki.MPM.202412304
  • 接收时间:2024-12-18
  • 首发时间:2026-03-18
  • 出版时间:2025-05-25
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  • 收稿日期:2024-12-18
基金
突发公共卫生事件应急管理学科建设(H200940)
自贡市公共卫生应急管理体系、机制及核心能力指标研究(2020CDZG-22)
作者信息
    1.四川大学华西公共卫生学院/四川大学华西第四医院 卫生政策与管理学系,四川 成都 610041
    2.富顺县卫生健康局/富顺县中医药管理局
    3.四川大学华西临床医学院/四川大学华西医院
    4.四川大学华西-协和陈志潜卫生健康研究院卫生应急管理研究中心
    5.四川大学华西公共卫生学院/四川大学华西第四医院 急诊与重症医学科

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2种不同金属材料的力学参数

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Number of
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种数
Number of
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占总种数比例
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种数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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