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Article(id=1324070896012505355, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202508311, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1755705600000, receivedDateStr=2025-08-21, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793612701657, onlineDateStr=2026-11-02, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793612701657, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793612701657, creator=13701087609, updateTime=1793612701657, updator=13701087609, issue=Issue{id=1324070892967428793, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='24', pageStart='4417', pageEnd='4608', issueExtLink='null', onlineDate='null', pubDate='1766592000000', pubDateStr='2025-12-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793612700931, creator='13701087609', updateTime=1793612772549, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324071193430602023, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324071193430602024, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4417, endPage=4423, ext={EN=ArticleExt(id=1324070896515821836, articleId=1324070896012505355, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Application of the moving epidemic method (MEM) to determine the epidemic threshold and intensity levels of varicella, Sichuan, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To establish the epidemic thresholds and intensity classification criteria for varicella in Sichuan Province by applying the Moving Epidemic Method (MEM), so as to provide a scientific basis for precision prevention and control.

Methods

Based on the weekly incidence data of varicella in Sichuan Province from 2014 to 2024, obtained from the China Information System for Disease Control and Prevention, the MEM model was constructed separately for each epidemic season, accounting for its characteristic bimodal peaks (the spring-summer peak from week 8 to week 34 and the autumn-winter peak from week 35 to week 7 of the following year). The optimal parameter (δ) was determined through cross-validation. Model performance was evaluated using sensitivity, specificity, and the Youden index.

Results

In the autumn-winter model, after excluding data from weeks 35 to 7 of the 2014-2015 season, the model was built based on nine years of historical data (δ=2.9), yielding a sensitivity of 0.837, a specificity of 0.933, and a Youden index of 0.770. In the spring-summer model, after excluding data from weeks 8 to 34 of 2020, the model was constructed using nine years of historical data (δ=2.6), which resulted in a sensitivity of 0.902, a specificity of 0.943, and a Youden index of 0.845.

Conclusion

The seasonal stratification approach combined with the MEM epidemic intensity assessment model enables accurate identification of varicella epidemic periods in Sichuan Province, thereby providing a scientific basis for implementing differentiated prevention and control measures based on epidemic intensity levels.

, authors=Xin HU1, Xiao-yun WU2, Rong-jie WEI1, authorsList=Xin HU, Xiao-yun WU, Rong-jie WEI, authorCompany=null, correspAuthors=Rong-jie WEI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, 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=1324070899309228305, articleId=1324070896012505355, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=移动流行区间法在四川省水痘流行阈值及强度分级中的应用, columnId=1228016567632462653, journalTitle=现代预防医学, columnName=流行病与统计方法, runingTitle=null, highlight=null, articleAbstract=
目的

应用移动流行区间法（moving epidemic method，MEM）建立四川省水痘流行阈值及强度分级标准，为精准防控提供依据。

方法

基于中国疾病预防控制信息系统2014-2024年四川省水痘周发病率数据，针对水痘双峰流行特征（秋冬季第35周-次年7周、春夏季第8-34周），分流行季构建MEM模型。通过交叉验证优化最优参数δ，采用灵敏度、特异度、约登指数评价模型性能。

结果

秋冬流行季模型中，删除2014-2015年第35-7周数据后，基于9年历史数据建模（δ=2.9），灵敏度、特异度及约登指数分别为0.837、0.933和0.770。春夏流行季模型中，删除2020年第8-34周数据后，采用9年历史数据建模（δ=2.6），灵敏度、特异度与约登指数分别为0.902、0.943和0.845。

结论

采用拆分流行季的方法，结合MEM流行强度评估模型，能准确辨识四川省水痘流行期，可依据流行强度分级实施差异化防控，为四川省水痘防控提供参考依据。

, authors=胡新1, 伍霄雲2, 魏荣杰1, authorsList=胡新, 伍霄雲, 魏荣杰, authorCompany=null, correspAuthors=魏荣杰, authorNote=

胡新（1989—），男，本科，副主任医师，研究方向：传染病预防控制

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魏荣杰，E-mail：
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胡新（1989—），男，本科，副主任医师，研究方向：传染病预防控制

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胡新（1989—），男，本科，副主任医师，研究方向：传染病预防控制

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Human Vaccines & Immunotherapeutics, 2018, 14 (10): 2464-2471., articleTitle=Seroepidemiology of varicella in Hangzhou, China in the vaccine era, refAbstract=null), Reference(id=1324070909987926378, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, doi=null, pmid=null, pmcid=null, year=2020, volume=26, issue=3, pageStart=290, pageEnd=292, url=null, language=null, rfNumber=［22］, rfOrder=39, authorNames=徐志荣, 郭鸿平, 周婷, journalName=中国疫苗和免疫, refType=null, unstructuredReference=徐志荣，郭鸿平，周婷, 等. 昆明市官渡区2019年1~14岁健康儿童水痘-带状疱疹病毒抗体水平 [J]. 中国疫苗和免疫, 2020, 26 (3): 290-292., articleTitle=昆明市官渡区2019年1~14岁健康儿童水痘-带状疱疹病毒抗体水平, refAbstract=null), Reference(id=1324070910071812459, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, doi=null, pmid=null, pmcid=null, year=2020, volume=26, issue=3, pageStart=290, pageEnd=292, url=null, language=null, rfNumber=［22］, rfOrder=40, authorNames=Xu ZR, Guo HP, Zhou T, journalName=Chinese Journal of Vaccines and Immunization, refType=null, unstructuredReference=Xu ZR, Guo HP, Zhou T, et al. Antibody levels against varicella-zoster virus among 1-14-year-old healthy children in Guandu district of Kunming city, 2019 [J]. Chinese Journal of Vaccines and Immunization, 2020, 26 (3): 290-292. (In Chinese), articleTitle=Antibody levels against varicella-zoster virus among 1-14-year-old healthy children in Guandu district of Kunming city, 2019, refAbstract=null), Reference(id=1324070910151504236, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, doi=null, pmid=null, pmcid=null, year=2012, volume=25, issue=11, pageStart=1527, pageEnd=1529, 1534, url=null, language=null, rfNumber=［23］, rfOrder=41, authorNames=钱晓华, 谭顺荣, 杨彦基, journalName=中国生物制品学杂志, refType=null, unstructuredReference=钱晓华，谭顺荣，杨彦基, 等. 单剂水痘疫苗接种后人群中暴发水痘疫情的原因分析 [J]. 中国生物制品学杂志, 2012, 25 (11): 1527-1529, 1534., articleTitle=单剂水痘疫苗接种后人群中暴发水痘疫情的原因分析, refAbstract=null), Reference(id=1324070910227001709, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, doi=null, pmid=null, pmcid=null, year=2012, volume=25, issue=11, pageStart=1527, pageEnd=1529, 1534, url=null, language=null, rfNumber=［23］, rfOrder=42, authorNames=Qian XH, Tan SR, Yang YJ, journalName=Chinese Journal of Biologicals, refType=null, unstructuredReference=Qian XH, Tan SR, Yang YJ, et al. Reason for outbreak of varicella in population after immunization with a single dose of varicella vaccine [J]. Chinese Journal of Biologicals, 2012, 25 (11): 1527-1529, 1534. (In Chinese), articleTitle=Reason for outbreak of varicella in population after immunization with a single dose of varicella vaccine, refAbstract=null)], funds=[Fund(id=1324070904740852032, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, awardId=cstc2020jscx-cylhX0003, language=CN, fundingSource=重庆市技术创新与应用发展专项重点项目(cstc2020jscx-cylhX0003), fundOrder=null, country=null), Fund(id=1324070904803766593, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, awardId=5R01AI125842-02, language=CN, fundingSource=NIH过敏与传染病预防控制项目(5R01AI125842-02), fundOrder=null, country=null), Fund(id=1324070904879264066, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, awardId=2022YFS0052, language=CN, fundingSource=四川省科技计划项目(2022YFS0052), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324070899636384018, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, xref=1., ext=[AuthorCompanyExt(id=1324070899644772627, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, companyId=1324070899636384018, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Sichuan Provincial Center for Disease Control and Prevention, Chengdu, Sichuan 610041, China), AuthorCompanyExt(id=1324070899653161236, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, companyId=1324070899636384018, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.四川省疾病预防控制中心，四川　成都　610041)]), AuthorCompany(id=1324070899720270101, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, xref=2., ext=[AuthorCompanyExt(id=1324070899724464406, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, companyId=1324070899720270101, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.眉山市疾病预防控制中心)])], figs=[ArticleFig(id=1324070901553180976, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Fig.1, caption=Distribution of weekly incidence rates of varicella in Sichuan Province, 2014-2024, figureFileSmall=+ppZ4+fPv38OdlLK0QxIdw==, figureFileBig=fuoB8e+1rvnUFh280qRL4A==, tableContent=null), ArticleFig(id=1324070901616095537, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=CN, label=图1, caption=2014—2024年四川省水痘周发病率分布图, figureFileSmall=+ppZ4+fPv38OdlLK0QxIdw==, figureFileBig=fuoB8e+1rvnUFh280qRL4A==, tableContent=null), ArticleFig(id=1324070901892919602, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Fig.2, caption=Distribution of average weekly incidence rate of varicella in Sichuan Province, 2014-2024, figureFileSmall=ePdBUL9+FpQX50v+NoaV/Q==, figureFileBig=Qc2e9FGoVxQNFJtS+dRq2w==, tableContent=null), ArticleFig(id=1324070901972611379, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=CN, label=图2, caption=2014—2024年四川省水痘周平均发病率分布图, figureFileSmall=ePdBUL9+FpQX50v+NoaV/Q==, figureFileBig=Qc2e9FGoVxQNFJtS+dRq2w==, tableContent=null), ArticleFig(id=1324070902048108852, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Table 1, caption=

Selection of the parameter (δ) for the MEM model for varicella during the autumn-winter seasons in Sichuan Province, 2014-2024

, figureFileSmall=null, figureFileBig=null, tableContent=
δ值灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
2.00.8920.7770.9010.7590.6640.669
2.10.8730.8400.9260.7440.6910.714
2.20.8510.8410.9240.7120.6640.692
2.30.8420.8740.9380.7080.6800.716
2.40.8240.8850.9430.6880.6690.710
2.50.8210.8900.9450.6850.6690.711
2.60.7820.9200.9570.6490.6520.702
2.70.7690.9440.9690.6420.6600.713
2.80.7710.9360.9650.6420.6550.707
2.90.7440.9790.9880.6260.6660.723
3.00.6120.9930.9950.5290.5630.605
), ArticleFig(id=1324070903700664629, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=CN, label=表1, caption=

2014—2024年四川省秋冬流行季水痘MEM模型参数δ的筛选

, figureFileSmall=null, figureFileBig=null, tableContent=
δ值灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
2.00.8920.7770.9010.7590.6640.669
2.10.8730.8400.9260.7440.6910.714
2.20.8510.8410.9240.7120.6640.692
2.30.8420.8740.9380.7080.6800.716
2.40.8240.8850.9430.6880.6690.710
2.50.8210.8900.9450.6850.6690.711
2.60.7820.9200.9570.6490.6520.702
2.70.7690.9440.9690.6420.6600.713
2.80.7710.9360.9650.6420.6550.707
2.90.7440.9790.9880.6260.6660.723
3.00.6120.9930.9950.5290.5630.605
), ArticleFig(id=1324070903822299446, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Table 2, caption=

Selection of the parameter (δ) for the MEM model for varicella during the spring-summer seasons in Sichuan Province, 2015-2024

, figureFileSmall=null, figureFileBig=null, tableContent=
δ值灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
2.00.9270.7480.8740.8460.6970.675
2.10.9030.8410.9140.8220.7400.744
2.20.8740.8820.9330.7880.7380.755
2.30.8740.9030.9440.7920.7560.777
2.40.8260.9530.9700.7450.7460.779
2.50.8080.9610.9750.7270.7350.769
2.60.7890.9800.9860.7120.7330.769
2.70.7780.9800.9860.7020.7220.758
2.80.7780.9800.9860.7020.7220.758
2.90.7350.9940.9960.6660.6950.729
3.00.7290.9940.9960.6620.6890.723
), ArticleFig(id=1324070903935545655, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=CN, label=表2, caption=

2015—2024年四川省春夏流行季水痘MEM模型参数δ的筛选

, figureFileSmall=null, figureFileBig=null, tableContent=
δ值灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
2.00.9270.7480.8740.8460.6970.675
2.10.9030.8410.9140.8220.7400.744
2.20.8740.8820.9330.7880.7380.755
2.30.8740.9030.9440.7920.7560.777
2.40.8260.9530.9700.7450.7460.779
2.50.8080.9610.9750.7270.7350.769
2.60.7890.9800.9860.7120.7330.769
2.70.7780.9800.9860.7020.7220.758
2.80.7780.9800.9860.7020.7220.758
2.90.7350.9940.9960.6660.6950.729
3.00.7290.9940.9960.6620.6890.723
), ArticleFig(id=1324070904044597560, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Table 3, caption=

Cross-validation results of the MEM model for varicella during the autumn-winter seasons in Sichuan Province, 2014-2024, before and after the exclusion of surveillance data

, figureFileSmall=null, figureFileBig=null, tableContent=
年份灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后
2014—20150.485-1.000-1.000-0.500-0.492-0.485-
2015—20160.5310.5311.0001.0001.0001.0000.4110.4110.4670.4670.5310.531
2016—20170.6350.6351.0001.0001.0001.0000.5480.5480.5900.590.6350.635
2017—20180.8920.8920.9820.9820.9880.9880.8480.8480.8560.8560.8750.875
2018—20191.0001.0000.9380.8440.9560.8961.0001.0000.9460.8690.9380.844
2019—20200.9890.9890.9640.9640.9790.9790.9810.9810.9570.9570.9530.953
2020—20210.9460.9460.9470.9470.9810.9810.8570.8570.8660.8660.8940.894
2021—20220.6830.7430.9390.9390.9580.9620.5900.6390.5840.640.6220.681
2022—20231.0001.0000.9090.8180.9330.8751.0001.0000.9210.8460.9090.818
2023—20240.8570.9051.0000.9701.0000.9740.8460.8890.8520.8690.8570.874
), ArticleFig(id=1324070904132677945, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=CN, label=表3, caption=

2014—2024年四川省秋冬流行季水痘MEM模型删除前后各年份监测数据交叉验证拟合效果

, figureFileSmall=null, figureFileBig=null, tableContent=
年份灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后
2014—20150.485-1.000-1.000-0.500-0.492-0.485-
2015—20160.5310.5311.0001.0001.0001.0000.4110.4110.4670.4670.5310.531
2016—20170.6350.6351.0001.0001.0001.0000.5480.5480.5900.590.6350.635
2017—20180.8920.8920.9820.9820.9880.9880.8480.8480.8560.8560.8750.875
2018—20191.0001.0000.9380.8440.9560.8961.0001.0000.9460.8690.9380.844
2019—20200.9890.9890.9640.9640.9790.9790.9810.9810.9570.9570.9530.953
2020—20210.9460.9460.9470.9470.9810.9810.8570.8570.8660.8660.8940.894
2021—20220.6830.7430.9390.9390.9580.9620.5900.6390.5840.640.6220.681
2022—20231.0001.0000.9090.8180.9330.8751.0001.0000.9210.8460.9090.818
2023—20240.8570.9051.0000.9701.0000.9740.8460.8890.8520.8690.8570.874
), ArticleFig(id=1324070904220758330, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Table 4, caption=

Cross-validation results of the Moving Epidemic Method (MEM) model for varicella during the spring-summer seasons in Sichuan Province, 2015-2024, before and after exclusion of surveillance data by year

, figureFileSmall=null, figureFileBig=null, tableContent=
年份灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后
20150.7170.7331.0001.0001.0001.0000.6850.7500.7010.7420.7170.733
20160.6050.6061.0001.0001.0001.0000.5510.6180.5770.6120.6050.606
20170.8170.9001.0001.0001.0001.0000.7200.8610.7670.8800.8170.900
20180.9300.9890.9640.9420.9770.9580.8930.9850.8820.9370.8940.931
20190.9691.0000.9120.9520.9550.9710.9391.0000.8870.9610.8810.952
20200.497-1.000-1.000-0.574-0.534-0.497-
20210.9851.0000.8590.7870.9330.8860.9661.0000.8710.8350.8430.787
20220.9841.0000.8730.8960.9290.9310.9701.0000.8780.9130.8570.896
20230.8110.8750.9791.0000.9881.0000.7120.8460.7440.8600.7900.875
20240.9191.0000.9320.9000.9700.9440.8281.0000.8240.9220.8500.900
), ArticleFig(id=1324070904313033019, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=CN, label=表4, caption=

2015—2024年四川省春夏流行季水痘MEM模型删除前后各年份监测数据交叉验证拟合效果

, figureFileSmall=null, figureFileBig=null, tableContent=
年份灵敏度特异度阳性预测值阴性预测值马修相关系数约登指数
删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后删除前删除后
20150.7170.7331.0001.0001.0001.0000.6850.7500.7010.7420.7170.733
20160.6050.6061.0001.0001.0001.0000.5510.6180.5770.6120.6050.606
20170.8170.9001.0001.0001.0001.0000.7200.8610.7670.8800.8170.900
20180.9300.9890.9640.9420.9770.9580.8930.9850.8820.9370.8940.931
20190.9691.0000.9120.9520.9550.9710.9391.0000.8870.9610.8810.952
20200.497-1.000-1.000-0.574-0.534-0.497-
20210.9851.0000.8590.7870.9330.8860.9661.0000.8710.8350.8430.787
20220.9841.0000.8730.8960.9290.9310.9701.0000.8780.9130.8570.896
20230.8110.8750.9791.0000.9881.0000.7120.8460.7440.8600.7900.875
20240.9191.0000.9320.9000.9700.9440.8281.0000.8240.9220.8500.900
), ArticleFig(id=1324070904380141884, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Table 5, caption=

Epidemic Intensity levels of Varicella during the autumn-winter seasons in Sichuan Province, 2015-2024

, figureFileSmall=null, figureFileBig=null, tableContent=
年份发病率峰值
（/10万）		峰值时间
（周次）		流行阈值中等强度阈值高等强度阈值极高强度阈值流行水平
2015—20161.041430.6901.4852.0992.445低
2016—20171.117480.6911.4722.1162.483低
2017—20181.600480.6931.4082.1242.547中
2018—20192.241480.6801.3551.9632.312高
2019—20201.877460.6691.3802.0732.481中
2020—20211.650430.6701.4042.1182.540中
2021—20221.455450.6911.4222.1352.555中
2022—20232.325480.6591.3551.9552.299极高
2023—20241.928460.6651.3732.0472.443中
), ArticleFig(id=1324070904468222269, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=CN, label=表5, caption=

2015—2024年四川省秋冬流行季水痘流行水平

, figureFileSmall=null, figureFileBig=null, tableContent=
年份发病率峰值
（/10万）		峰值时间
（周次）		流行阈值中等强度阈值高等强度阈值极高强度阈值流行水平
2015—20161.041430.6901.4852.0992.445低
2016—20171.117480.6911.4722.1162.483低
2017—20181.600480.6931.4082.1242.547中
2018—20192.241480.6801.3551.9632.312高
2019—20201.877460.6691.3802.0732.481中
2020—20211.650430.6701.4042.1182.540中
2021—20221.455450.6911.4222.1352.555中
2022—20232.325480.6591.3551.9552.299极高
2023—20241.928460.6651.3732.0472.443中
), ArticleFig(id=1324070904547914046, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070896012505355, language=EN, label=Table 6, caption=

Epidemic Intensity levels of Varicella during the spring-summer seasons in Sichuan Province, 2015-2024

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年份发病率峰值
（/10万）		峰值时间
（周次）		流行阈值中等强度阈值高等强度阈值极高强度阈值流行水平
20151.090240.5901.3061.7862.050低
20161.107230.5871.3331.7431.963低
20171.483230.5931.2681.7902.084中
20181.567230.5851.2381.7522.042中
20191.983240.5791.2391.7312.007高
20211.677230.5731.2301.7221.999中
20221.768230.5671.2271.7101.980高
20231.542230.5901.2471.7712.068中
20241.599210.5731.2421.7592.051中
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2015—2024年四川省春夏流行季水痘流行水平

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20151.090240.5901.3061.7862.050低
20161.107230.5871.3331.7431.963低
20171.483230.5931.2681.7902.084中
20181.567230.5851.2381.7522.042中
20191.983240.5791.2391.7312.007高
20211.677230.5731.2301.7221.999中
20221.768230.5671.2271.7101.980高
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移动流行区间法在四川省水痘流行阈值及强度分级中的应用
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胡新 1 , 伍霄雲 2 , 魏荣杰 1
现代预防医学 | 流行病与统计方法 2025,52(24): 4417-4423
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现代预防医学 |流行病与统计方法 2025 , 52 (24) : 4417 -4423
移动流行区间法在四川省水痘流行阈值及强度分级中的应用
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胡新1, 伍霄雲2, 魏荣杰1
作者信息
  • 1.四川省疾病预防控制中心，四川　成都　610041
  • 2.眉山市疾病预防控制中心
通讯作者:
魏荣杰，E-mail：
作者简介:

胡新（1989—），男，本科，副主任医师，研究方向：传染病预防控制

Application of the moving epidemic method (MEM) to determine the epidemic threshold and intensity levels of varicella, Sichuan
Xin HU1, Xiao-yun WU2, Rong-jie WEI1
Affiliations
  • Sichuan Provincial Center for Disease Control and Prevention, Chengdu, Sichuan 610041, China
出版时间: 2025-12-25 doi: 10.20043/j.cnki.MPM.202508311
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摘要
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目的

应用移动流行区间法（moving epidemic method，MEM）建立四川省水痘流行阈值及强度分级标准，为精准防控提供依据。

方法

基于中国疾病预防控制信息系统2014-2024年四川省水痘周发病率数据，针对水痘双峰流行特征（秋冬季第35周-次年7周、春夏季第8-34周），分流行季构建MEM模型。通过交叉验证优化最优参数δ，采用灵敏度、特异度、约登指数评价模型性能。

结果

秋冬流行季模型中，删除2014-2015年第35-7周数据后，基于9年历史数据建模（δ=2.9），灵敏度、特异度及约登指数分别为0.837、0.933和0.770。春夏流行季模型中，删除2020年第8-34周数据后，采用9年历史数据建模（δ=2.6），灵敏度、特异度与约登指数分别为0.902、0.943和0.845。

结论

采用拆分流行季的方法，结合MEM流行强度评估模型，能准确辨识四川省水痘流行期，可依据流行强度分级实施差异化防控，为四川省水痘防控提供参考依据。

水痘  /  移动流行区间法  /  流行阈值  /  流行强度  /  双峰分布
Objective

To establish the epidemic thresholds and intensity classification criteria for varicella in Sichuan Province by applying the Moving Epidemic Method (MEM), so as to provide a scientific basis for precision prevention and control.

Methods

Based on the weekly incidence data of varicella in Sichuan Province from 2014 to 2024, obtained from the China Information System for Disease Control and Prevention, the MEM model was constructed separately for each epidemic season, accounting for its characteristic bimodal peaks (the spring-summer peak from week 8 to week 34 and the autumn-winter peak from week 35 to week 7 of the following year). The optimal parameter (δ) was determined through cross-validation. Model performance was evaluated using sensitivity, specificity, and the Youden index.

Results

In the autumn-winter model, after excluding data from weeks 35 to 7 of the 2014-2015 season, the model was built based on nine years of historical data (δ=2.9), yielding a sensitivity of 0.837, a specificity of 0.933, and a Youden index of 0.770. In the spring-summer model, after excluding data from weeks 8 to 34 of 2020, the model was constructed using nine years of historical data (δ=2.6), which resulted in a sensitivity of 0.902, a specificity of 0.943, and a Youden index of 0.845.

Conclusion

The seasonal stratification approach combined with the MEM epidemic intensity assessment model enables accurate identification of varicella epidemic periods in Sichuan Province, thereby providing a scientific basis for implementing differentiated prevention and control measures based on epidemic intensity levels.

Varicella  /  Moving epidemic method  /  Epidemic intensity  /  Epidemic threshold  /  Bimodal distribution
胡新, 伍霄雲, 魏荣杰. 移动流行区间法在四川省水痘流行阈值及强度分级中的应用. 现代预防医学, 2025 , 52 (24) : 4417 -4423 . DOI: 10.20043/j.cnki.MPM.202508311
Xin HU, Xiao-yun WU, Rong-jie WEI. Application of the moving epidemic method (MEM) to determine the epidemic threshold and intensity levels of varicella, Sichuan[J]. Modern Preventive Medicine, 2025 , 52 (24) : 4417 -4423 . DOI: 10.20043/j.cnki.MPM.202508311
正文
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水痘是由水痘-带状疱疹病毒（varicella-zoster virus，VZV）感染引起的一种急性呼吸道传染病，以全身丘疹、瘙痒性水疱为主要临床表现，人类是该病毒的唯一宿主[1]，常在学校和托幼机构等聚集性场所暴发流行，不仅影响师生健康和教学秩序，还增加了社会经济负担[2]。提前对潜在的流行阶段及强度开展分级评估，及时启动风险预警和防控措施，是有效防控水痘流行的关键措施。移动流行区间法（MEM）是WHO推荐的一种通过动态时间序列建模实现季节性流感流行起始阶段及强度变化特征的精准判定方法[3]，近年来被广泛运用于流感、手足口病等相关研究中[4-6]。监测数据显示，四川水痘流行特征与流感、手足口病相似，符合模型纳入条件。本研究基于四川省2014-2024年水痘发病资料，将MEM模型应用于水痘流行强度阈值监测及高峰预警，计算出各个流行分级阈值，评估流行强度，为四川省水痘防控提供参考依据。
1　材料与方法
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1.1　资料来源
四川省2014年第1周—2024年第52周水痘周发病数来源于中国疾病预防控制信息系统的“传染病报告信息管理系统”，按周汇总。同期人口数据来源于中国疾病预防控制信息系统“基本信息系统”。所有数据均无缺失值。
1.2　四川省水痘流行季节划分
监测数据分析表明，四川省水痘发病率时间分布呈典型双峰特征[7]。为满足移动流行区间法（MEM）对单峰型时序数据结构的要求，本研究将完整年度数据划分为两个独立的单峰流行季。划分流程如下：首先对历年每周水痘发病率数据求取算术平均值。然后基于周平均发病率分布图，识别相邻主峰间的显著低谷点，最后以低谷点所对应的周次为分界点，将全年数据分割为两个独立的单峰流行季，分别计算这两个独立的单峰流行季的强度阈值进而比较分析。
1.3　统计分析
1.3.1　MEM建模分析与评价
本研究构建MEM模型并进行评价的具体步骤如下：
①确定流行季节阶段：基于历史监测数据，应用最大累积和百分比算法进行自适应阈值计算，精确界定每个历史流行季内三个阶段的周次范围，将流行季节划分为流行前期、流行期、流行后期。
②计算流行起始与终止阈值：在所有历史流行季的流行前期数据中，选取发病率最高的n个值（n=30/N，N为纳入建模的流行季总数），计算n个值的算术平均数，并求取其单侧95%置信区间上限，确定为流行起始阈值。采用相同算法，基于所有历史流行季的流行后期数据，选取发病率最高的n个值，计算其算术平均数及其单侧95%置信区间上限，得到流行终止阈值。
③计算流行强度分级阈值：利用所有历史流行季流行期内的发病率数据，选取流行期内发病率最高的n个值（n=30/N，N为流行季数），计算其几何均数，再求取该几何均数的单侧40%、90%、97.5%置信区间的上限，分别作为中、高和极高流行阈值。
④模型评价：采用灵敏度、特异度和约登指数综合评价模型对历史数据的拟合优度。最优模型参数（δ）通过最大化约登指数确定。评价依据的“金标准”由MEM对每个流行季的阶段划分为流行前期、流行期和流行后期。计算公式分别为，灵敏度=（流行期内周报告发病率大于流行阈值的总周数）/（流行期总周数），特异度=（流行前期和流行后期2个时期内周报告发病率小于流行阈值的总周数）/（流行前期和流行后期2个时期的总周数），约登指数=灵敏度+特异度-1。
⑤交叉验证：为评估模型的稳定性和泛化能力，采用留一法交叉验证，依次将每一个历史流行季单独作为“目标季”留出。使用MEM步骤①对该目标季进行流行期划分（作为金标准）；利用剩余的所有流行季数据，执行MEM步骤①（阶段划分）和步骤②（阈值计算），预测该目标季的流行起始与终止阈值；将预测阈值应用于目标季的实际数据，计算该季的灵敏度、特异度和约登指数等评价指标；循环直至所有流行季均被留出一次。设定约登指数<0.5作为模型拟合效果差的标准，该阈值表明模型预测方向接近随机水平。最终建模过程中，将删除所有约登指数低于此阈值的年份数据，以确保模型的准确性和可靠性。
1.3.2　数据分析
利用Excel 2019软件整理原始数据，通过R 4.4.2软件中的“MEM”程序包完成统计分析（包括选择最优参数选择、评价历史数据拟合效果、建模），检验水准α=0.05。
2　结果
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2.1　流行特征分析
2014—2024年期间，四川省水痘发病率最高值在2023年第48周（2.325/10万），最低值在2023年第4周（0.107/10万），呈典型的季节性双峰分布特征，见图1。
2.2　流行季时间范围的确定
对2014—2024年水痘数据进行平滑，其年度分布呈现“双峰相当”模式，见图2。主峰位于第48周（1.432/10万），次峰在第23周（1.296/10万）；2个低谷分别出现在第8周（0.280/10万）和第34周（0.320/10万）。因此以2个低谷所在周为界，将2014年到2024年各年度的第35至次年第7周定义为秋冬季流行季，2015年到2024年各年度的第8~34周定义为春夏季流行季，以此分别建立秋冬季和春夏季MEM模型。
2.3　模型参数δ的选择
基于2014—2024年四川省水痘周发病率数据，设定参数δ的测试范围为2.0至3.0（步长0.1），分别构建秋冬与春夏两个流行季的预警模型。结果显示，当秋冬流行季δ=2.9、春夏流行季δ=2.4时，模型预测精度达到最优状态。不同参数δ取值对应模型的评价结果见表1和表2。此时秋冬季模型的灵敏度、特异度和约登指数分别为0.791，0.966和0.757，春夏季模型的灵敏度、特异度和约登指数分别为0.826，0.953和0.779。
2.4　历史数据拟合效果
通过交叉验证法验证历史数据的模型拟合度时，将拟合效果较差（约登指数<0.5）的年份予以删除。最终，秋冬流行季预警模型的最优δ值为2.9，模型灵敏度、特异度和约登指数分别为0.837、0.933和0.770；春夏流行季预警模型的最优δ值为2.6，模型灵敏度、特异度和约登指数分别为0.902、0.943和0.845，各年份监测数据在删除前后的拟合效果详见表3和表4。
2.5　模型建立
MEM模型显示，秋冬流行季开始阈值为0.7，中等、高等和极高的流行强度阈值分别为1.44、2.13和2.54。春夏流行季开始阈值为0.6，中等、高等和极高的流行强度阈值分别为1.30、1.80和2.08。就各年流行高峰的流行水平而言，2022-2023年秋冬季达到极高流行水平，2019年春夏季、2022年春夏季以及2018-2019年秋冬季达到高流行水平，其余均为中或低流行水平，见表5、表6。
3　讨论
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我国从2005年开始通过传染病信息报告管理系统对水痘病例进行监测报告，并通过突发公共卫生事件报告管理信息系统对水痘暴发疫情进行监测，但目前水痘尚不属于我国法定报告传染病[8]，四川省也未将水痘纳入法定丙类传染病进行报告和管理，仅作为其他传染病进行监测。根据中国疾病预防控制信息系统数据统计，2024年四川省共报告水痘42 193例，报告水痘突发公共卫生事件10起，占同期传染病突发公共卫生事件的14.49%（居第三位），占同期学校传染病突发公共卫生事件的23.81%，表明四川省水痘处于高发状态，水痘已成为引起学校暴发疫情的主要传染病之一。
MEM现已广泛应用于流感、手足口病监测预警[9-10]，但较少用于水痘的监测预警。有研究建议MEM模型的流行季节数目不宜超过10年且最好为单峰流行，效果优于双峰流行，如果流行为双峰型则需进行拆分成为两个单峰进行分析[11]。既往研究[7，12-13]显示，全国水痘发病呈现明显的季节性分布特征，四川与全国水痘发病高峰基本一致，呈典型的季节性双峰分布特征。由于MEM模型要求流行季节呈单峰，因此部分地区在构建模型时，有的地区采用纳入主高峰监测数据建模[6，14]，有的地区采用季节拆分建模[15-16]。针对四川省水痘发病呈现“双峰相当”流行特征，参考广东等地做法[16-17]，将研究数据划分为春夏季（第8-34周）与秋冬季（第35-次年7周）两个独立流行季分别建模。研究发现，秋冬流行季2014—2015年与春夏流行季2020年的模型拟合效果较差，约登指数分别为0.485和0.497。为提高模型稳健性，删除以上年份数据后再次进行交叉验证。其中，秋冬流行季2014—2015年被删除，可能与2013年7月实施的《四川省水痘疫苗使用指导意见（试行）》建议普及2剂次疫苗接种政策有关，通过提高疫苗接种率影响了水痘流行规律，导致该年度流行曲线形态偏离预期模式；而春夏流行季2020年被删除，则可能与新冠疫情防控所采取的干预措施有关，致使流行规律出现异常[18]。在删除拟合不佳的年份后，重新筛选模型的最优δ值。经优化后，四川省水痘秋冬流行季模型的灵敏度、特异度和约登指数分别为0.837、0.933和0.770，春夏流行季模型的灵敏度、特异度和约登指数分别达到0.902、0.943和0.845。与仅选择单峰数据的新疆研究结果（0.73、0.98、0.71）相比[19]，本研究模型效能指标结果更优，显示该方法在双峰分布传染病预警中的良好适应性。从流行季节阈值和持续时间来看，秋冬季均高于春夏季，提示秋冬季为防控关键期，这可能与秋冬季人群室内聚集增加、气候条件利于病毒传播有关。
接种水痘疫苗是预防和控制水痘最主要措施之一，预警结果显示，四川省2022—2023年秋冬季达到极高流行水平，2022年春夏季达到高流行水平，这可能与疫情防控期间适龄儿童水痘疫苗接种率降低有关。据四川省2022年抗体水平调查结果报道[20]，四川省0~11岁健康儿童水痘-带状疱疹病毒IgG抗体总阳性率仅为40.8%，抗体水平总体较低，低于云南省昆明市官渡区（71.1%）[21]和浙江省杭州市（65.6%）[22]，进一步印证了疫苗接种率对流行强度的显著影响。因此，建议适龄儿童接种2剂次水痘疫苗[23]，四川省可综合考虑适时将水痘疫苗纳入省级儿童免疫规划。同时，建议四川省各地要积极开展水痘监测预警，及时准确评估水痘流行的开始时间、高峰时间、结束时间和流行强度等关键指标，可根据疾病高、中、低流行水平，分类开展疫情健康风险提示、警示信息通报及预警决策建议等措施，为优先接种疫苗区域、应急接种人群确定及疫情防控干预措施的强化时机提供决策依据。
综上所述，本研究通过拆分流行季的方法，证实了MEM模型在确定具有双峰流行特征的四川省水痘流行强度阈值方面具有良好的适用性，能够准确识别水痘流行期，为水痘流行病学的深入研究提供了方法学参考。然而，本研究也存在一定局限性：首先，仅纳入周发病率单一指标，评估维度不够全面；其次，现有文献中MEM模型主要应用于流感和手足口病，将其推广应用于水痘等传染病的报道相对较少，其普适性仍需进一步验证。
基金
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  • 重庆市技术创新与应用发展专项重点项目(cstc2020jscx-cylhX0003)
  • NIH过敏与传染病预防控制项目(5R01AI125842-02)
  • 四川省科技计划项目(2022YFS0052)
文献
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2025年第52卷第24期
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doi: 10.20043/j.cnki.MPM.202508311
  • 接收时间：2025-08-21
  • 首发时间：2026-11-02
  • 出版时间：2025-12-25
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  • 收稿日期：2025-08-21
基金
重庆市技术创新与应用发展专项重点项目(cstc2020jscx-cylhX0003)
NIH过敏与传染病预防控制项目(5R01AI125842-02)
四川省科技计划项目(2022YFS0052)
作者信息
    1.四川省疾病预防控制中心，四川　成都　610041
    2.眉山市疾病预防控制中心

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魏荣杰，E-mail：
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
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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