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Article(id=1324044540667113896, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324044540067328424, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509105, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1757001600000, receivedDateStr=2025-09-05, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793606418053, onlineDateStr=2026-11-02, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793606418053, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793606418053, creator=13701087609, updateTime=1793606418053, updator=13701087609, issue=Issue{id=1324044540067328424, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='8', pageStart='1345', pageEnd='1536', issueExtLink='null', onlineDate='null', pubDate='1777046400000', pubDateStr='2026-04-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793606417910, creator='13701087609', updateTime=1793670137580, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324311799788602160, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324044540067328424, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324311799788602161, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324044540067328424, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1358, endPage=1364, ext={EN=ArticleExt(id=1324044540901994921, articleId=1324044540667113896, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Spatio-temporal cluster analysis of five category B respiratory infectious diseases, China, 2004-2020, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To systematically analyze the spatial and temporal evolution patterns of five Category B respiratory infectious diseases (pulmonary tuberculosis (PTB), scarlet fever, measles, meningococcal meningitis (MM) and pertussis) in China (2004-2020) to guide regional prevention strategies.

Methods

Based on the National Notifiable Disease Reporting System (NNDRS) data, we integrated spatial autocorrelation analysis, center of gravity migration model and standard deviation ellipse method for multi-dimensional spatio-temporal modelling to reveal the migration paths and clustering characteristics of the morbidity hotspots.

Results

The incidence rates of PTB and MM continued to decline, which measles showed a fluctuating decline. scarlet fever and pertussis rose significantly after 2016, with a tendency to make a comeback. The high-high clustering areas of PTB and measles migrated to the northwest. Scarlet fever showed a northward return, with the high-high clustering stable and locked in Inner Mongolia after 2018 (Moran I=0.354, P<0.01). Pertussis hotspot area shifted southward, and the high-high clustering area focused on Xiang-qian junction in 2020. The incidence of MM continued to be low and spatial aggregation disappeared.

Conclusion

These diseases exhibit westward migration and northward return, necessitating targeted control systems in northwestern China, optimized mobile population monitoring and vaccine persistence strategies.

, authors=Yun YU1, Sheng-qiang ZOU2, Qiang WANG3, Deng-bo DONG1, Feng Lin1, Ya-ji YAO4, authorsList=Yun YU, Sheng-qiang ZOU, Qiang WANG, Deng-bo DONG, Feng Lin, Ya-ji YAO, authorCompany=null, correspAuthors=Sheng-qiang ZOU, 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=1324044542873317810, articleId=1324044540667113896, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=2004—2020年中国五种乙类呼吸道传染病的时空聚集性分析, 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

系统分析2004—2020年中国五种具有代表性的乙类呼吸道传染病（肺结核、猩红热、麻疹、流行性脑脊髓膜炎、百日咳）的时空演化规律，为制定差异化区域防控策略提供科学依据。

方法

基于国家传染病报告系统数据，整合空间自相关分析（全局和局部Moran I）、重心迁移模型和标准差椭圆方法，运用ArcGIS 10.8和GeoDa 1.18.0进行多维度时空建模，揭示发病热点的迁移路径与聚集特征。

结果

肺结核、流行性脑脊髓膜炎发病率持续下降，麻疹呈波动下降；猩红热和百日咳2016年后显著上升。肺结核与麻疹高-高聚类区向西北迁移，形成青藏高原-甘青新交界热点带。猩红热呈现北归，2018年后高-高聚类稳定锁定内蒙古地区（Moran I=0.354，P<0.01）。百日咳热点区南移，2020年高聚集区聚焦湘黔交界（湖南省与贵州省交界处）。流脑发病率持续走低，空间聚集性消失。

结论

中国五种呼吸道传染病呈现西迁北归的格局，需建立西北地区靶向防控体系，优化流动人口监测与疫苗持久性策略。

, authors=于芸1, 邹圣强2, 王强3, 董邓波1, 林枫1, 姚雅极4, authorsList=于芸, 邹圣强, 王强, 董邓波, 林枫, 姚雅极, authorCompany=null, correspAuthors=邹圣强, authorNote=

于芸（2001—），女，硕士在读，研究方向：流行病与卫生统计学

, correspAuthorsNote=
邹圣强，E-mail：
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=o8O+N6RMIHLwetDWSW2Qxw==, magXml=bxUTURqCyx50kqdeIPLR4w==, pdfUrl=null, pdf=RfEjuWIPWh8B3avnTOOEvQ==, pdfFileSize=2207299, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=VbP0TKyIsUzXpxon9c4bSQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=DvuClzN0GbCLZ7fUg7piFA==, mapNumber=null, fund=null)}, authors=[Author(id=1324044545083716029, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044540667113896, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1324044545222128063, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044540667113896, authorId=1324044545083716029, language=EN, stringName=Yun YU, firstName=Yun, middleName=null, lastName=YU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=School of Public Health, North China University of Science and Technology, Tangshan, HeBei 063210, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1324044545322791360, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044540667113896, authorId=1324044545083716029, language=CN, stringName=于芸, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1.华北理工大学公共卫生学院，河北　唐山　063210, bio={"content":"

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注：A为肺结核；B为猩红热；C为麻疹；D为流脑；E为百日咳。

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注：A为肺结核；B为猩红热；C为麻疹；D为流脑；E为百日咳。

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Results of a global spatial autocorrelation test for the incidence of PTB and scarlet fever in China from 2004 to 2020

, figureFileSmall=null, figureFileBig=null, tableContent=
年份肺结核猩红热
Moran IZ值P值Moran IZ值P值
2004—20050.2352.5880.0100.3313.5160.010
2006—20070.2642.9040.0100.4383.9600.010
2008—20090.2873.1490.0100.4904.4390.010
2010—20110.4113.7550.0100.4433.8660.010
2012—20130.4544.2730.0100.3903.8720.010
2014—20150.4464.2610.0100.4113.8890.020
2016—20170.4824.8070.0100.3763.6370.020
2018—20190.4524.9800.0100.3543.4160.010
20200.5215.1240.0100.0701.0230.160
), ArticleFig(id=1324044550544699886, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044540667113896, language=CN, label=表1, caption=

2004—2020年中国肺结核和猩红热发病率全局空间自相分析

, figureFileSmall=null, figureFileBig=null, tableContent=
年份肺结核猩红热
Moran IZ值P值Moran IZ值P值
2004—20050.2352.5880.0100.3313.5160.010
2006—20070.2642.9040.0100.4383.9600.010
2008—20090.2873.1490.0100.4904.4390.010
2010—20110.4113.7550.0100.4433.8660.010
2012—20130.4544.2730.0100.3903.8720.010
2014—20150.4464.2610.0100.4113.8890.020
2016—20170.4824.8070.0100.3763.6370.020
2018—20190.4524.9800.0100.3543.4160.010
20200.5215.1240.0100.0701.0230.160
), ArticleFig(id=1324044550645363183, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044540667113896, language=EN, label=Table 2, caption=

Results of a global spatial autocorrelation test for the incidence of measles, MM and pertussis in China from 2004 to 2020

, figureFileSmall=null, figureFileBig=null, tableContent=
年份麻疹流行性脑脊髓膜炎百日咳
Moran IZ值P值Moran IZ值P值Moran IZ值P值
2004—20050.1892.4400.0300.1671.7860.0500.1131.5340.090
2006—20070.0701.0820.1800.0641.1490.1300.0361.2690.130
2008—2009-0.0330.0180.470-0.0010.4070.2300.0230.5650.290
2010—20110.3553.2040.0100.0280.6400.230-0.0180.0550.390
2012—20130.0720.9100.1700.0472.1300.040-0.048-0.2980.490
2014—20150.2993.2630.0200.0353.1140.010-0.040-0.0480.480
2016—20170.5075.7520.010-0.0210.5310.330-0.0040.3630.310
2018—20190.0070.3370.350-0.0070.3870.3400.0860.9360.150
20200.0370.6800.260-0.131-0.9340.1800.2482.6230.040
), ArticleFig(id=1324044550725054960, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044540667113896, language=CN, label=表2, caption=

2004—2020年中国麻疹、流行性脑脊髓膜炎和百日咳发病率全局空间自相分析

, figureFileSmall=null, figureFileBig=null, tableContent=
年份麻疹流行性脑脊髓膜炎百日咳
Moran IZ值P值Moran IZ值P值Moran IZ值P值
2004—20050.1892.4400.0300.1671.7860.0500.1131.5340.090
2006—20070.0701.0820.1800.0641.1490.1300.0361.2690.130
2008—2009-0.0330.0180.470-0.0010.4070.2300.0230.5650.290
2010—20110.3553.2040.0100.0280.6400.230-0.0180.0550.390
2012—20130.0720.9100.1700.0472.1300.040-0.048-0.2980.490
2014—20150.2993.2630.0200.0353.1140.010-0.040-0.0480.480
2016—20170.5075.7520.010-0.0210.5310.330-0.0040.3630.310
2018—20190.0070.3370.350-0.0070.3870.3400.0860.9360.150
20200.0370.6800.260-0.131-0.9340.1800.2482.6230.040
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2004—2020年中国五种乙类呼吸道传染病的时空聚集性分析
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于芸 1 , 邹圣强 2 , 王强 3 , 董邓波 1 , 林枫 1 , 姚雅极 4
现代预防医学 | 流行病与统计方法 2026,53(8): 1358-1364
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现代预防医学 |流行病与统计方法 2026 , 53 (8) : 1358 -1364
2004—2020年中国五种乙类呼吸道传染病的时空聚集性分析
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于芸1, 邹圣强2 , 王强3, 董邓波1, 林枫1, 姚雅极4
作者信息
  • 1.华北理工大学公共卫生学院，河北　唐山　063210
  • 2.镇江市第三人民医院
  • 3.江苏大学医学院
  • 4.南京中医药大学镇江附属医院
通讯作者:
邹圣强，E-mail：
作者简介:

于芸（2001—），女，硕士在读，研究方向：流行病与卫生统计学

Spatio-temporal cluster analysis of five category B respiratory infectious diseases, China, 2004-2020
Yun YU1, Sheng-qiang ZOU2 , Qiang WANG3, Deng-bo DONG1, Feng Lin1, Ya-ji YAO4
Affiliations
  • School of Public Health, North China University of Science and Technology, Tangshan, HeBei 063210, China
出版时间: 2026-04-25 doi: 10.20043/j.cnki.MPM.202509105
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摘要
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目的

系统分析2004—2020年中国五种具有代表性的乙类呼吸道传染病（肺结核、猩红热、麻疹、流行性脑脊髓膜炎、百日咳）的时空演化规律，为制定差异化区域防控策略提供科学依据。

方法

基于国家传染病报告系统数据，整合空间自相关分析（全局和局部Moran I）、重心迁移模型和标准差椭圆方法，运用ArcGIS 10.8和GeoDa 1.18.0进行多维度时空建模，揭示发病热点的迁移路径与聚集特征。

结果

肺结核、流行性脑脊髓膜炎发病率持续下降，麻疹呈波动下降；猩红热和百日咳2016年后显著上升。肺结核与麻疹高-高聚类区向西北迁移，形成青藏高原-甘青新交界热点带。猩红热呈现北归，2018年后高-高聚类稳定锁定内蒙古地区（Moran I=0.354，P<0.01）。百日咳热点区南移，2020年高聚集区聚焦湘黔交界（湖南省与贵州省交界处）。流脑发病率持续走低，空间聚集性消失。

结论

中国五种呼吸道传染病呈现西迁北归的格局，需建立西北地区靶向防控体系，优化流动人口监测与疫苗持久性策略。

中国  /  呼吸道传染病  /  发病率  /  时空分布  /  空间自相关
Objective

To systematically analyze the spatial and temporal evolution patterns of five Category B respiratory infectious diseases (pulmonary tuberculosis (PTB), scarlet fever, measles, meningococcal meningitis (MM) and pertussis) in China (2004-2020) to guide regional prevention strategies.

Methods

Based on the National Notifiable Disease Reporting System (NNDRS) data, we integrated spatial autocorrelation analysis, center of gravity migration model and standard deviation ellipse method for multi-dimensional spatio-temporal modelling to reveal the migration paths and clustering characteristics of the morbidity hotspots.

Results

The incidence rates of PTB and MM continued to decline, which measles showed a fluctuating decline. scarlet fever and pertussis rose significantly after 2016, with a tendency to make a comeback. The high-high clustering areas of PTB and measles migrated to the northwest. Scarlet fever showed a northward return, with the high-high clustering stable and locked in Inner Mongolia after 2018 (Moran I=0.354, P<0.01). Pertussis hotspot area shifted southward, and the high-high clustering area focused on Xiang-qian junction in 2020. The incidence of MM continued to be low and spatial aggregation disappeared.

Conclusion

These diseases exhibit westward migration and northward return, necessitating targeted control systems in northwestern China, optimized mobile population monitoring and vaccine persistence strategies.

China  /  Respiratory infectious diseases  /  Morbidity  /  Spatial and temporal distribution  /  Spatial auto-correlation
于芸, 邹圣强, 王强, 董邓波, 林枫, 姚雅极. 2004—2020年中国五种乙类呼吸道传染病的时空聚集性分析. 现代预防医学, 2026 , 53 (8) : 1358 -1364 . DOI: 10.20043/j.cnki.MPM.202509105
Yun YU, Sheng-qiang ZOU, Qiang WANG, Deng-bo DONG, Feng Lin, Ya-ji YAO. Spatio-temporal cluster analysis of five category B respiratory infectious diseases, China, 2004-2020[J]. Modern Preventive Medicine, 2026 , 53 (8) : 1358 -1364 . DOI: 10.20043/j.cnki.MPM.202509105
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呼吸道传染病（respiratory infectious diseases，RIDs）具有传播途径易实现、人群普遍易感、传播速度快、范围广和传染性强等特点，极易造成暴发和流行且难以控制，威胁个人与群体健康，给全球疾病防治带来巨大压力[1-2]。世界卫生组织估计，COVID-19大流行已导致全球确诊病例超过7.6亿例，死亡人数约为600万[3]。尽管全球努力暂时缓解了COVID-19的传播，但RIDs继续对人类健康构成重大风险[4]。目前的研究表明，RIDs可能会使全球预期寿命平均缩短1.29年[5]。中国自2004年完善法定传染病报告系统以来，已将肺结核、猩红热、麻疹、流脑和百日咳等疾病纳入重点监测范畴。这些疾病具有高发病率、季节性流行和区域聚集性特征，对公共卫生体系构成持续挑战[6]。例如，麻疹虽通过疫苗接种计划得到控制，但2013年后出现反弹，提示需更精准的时空防控策略[7]。
2004—2020年涵盖了中国免疫规划扩大、COVID-19防控等关键节点，构成了一个动态变化的防控政策背景。然而，现有研究多聚焦于单一病种或短期态势，缺乏在长时期内，对主要RIDs进行系统性、对比性的时空格局分析。因此，本文旨在通过时空分布分析等方法，全面阐明RIDs的时间、季节性和空间分布特征对于制定有效的干预措施以减少其传播至关重要[2]。
1　研究方法
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1.1　数据来源
2004年至2020年中国31个省（自治区、直辖市）五种RIDs的数据来源于公共卫生科学数据中心中国疾病预防控制中心。国家传染病报告系统是一个基于互联网的实时疾病报告系统，涵盖了中国大陆各种医疗机构，覆盖了31个省级行政区划的55 077个卫生机构[8-9]。中国标准底图[GS（2024）0650]来源于中华人民共和国自然资源部下属的标准地图服务（http://bzdt.ch.mnr.gov.cn/，2025年4月7日访问）。
1.2　空间相关性
将各省的五个RIDs数据与中国地图相关联。使用ArcGIS的制图功能，创建了五种RIDs发病率地图。全局空间自相关分析检查研究区域是否存在空间自相关。Moran I范围为-1到1，在α=0.05的显著性水平下，接近1的值表示正空间自相关，接近-1的值表示负空间自相关，0表示随机性[10]。本研究使用局部Moran I来分析空间单位级别的空间自相关模式，并进行LISA来识别聚类区域。确定了四种聚类模式：高-高（HH）、高-低（HL）、低-低（LL）和低-高（LH）[11]。
1.3　重力重心迁移和标准差椭圆
采用标准差椭圆法分析数据的方向和分布。椭圆大小反映了发病率在空间尺度上的集中程度。长轴长度表示数据分布的方向，短轴长度表示数据分布的范围。长轴和短轴的长度差异越大，数据的方向性就越明显。相反，如果长轴和短轴的长度更接近，则表示方向性不太明显[12]。
1.4　统计方法
使用Excel 2019对数据进行汇总。R 4.3.2软件用于整合五种RIDs的数据集。Origin 2021用于绘制折线图及以月发病率雷达图，分别呈现疾病的长期趋势和季节性特征。GeoDa 1.18.0软件生成空间邻接权重矩阵，进行空间探索性分析，包括全局空间自相关分析。ArcGIS 10.8软件用于实现地图可视化、绘制LISA聚类地图，并采用重力重心迁移轨迹和标准差椭圆分析法，从空间动力学视角揭示疾病分布格局的演变特征。
2　结果
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2.1　五种主要呼吸道传染病发病率的时空分布
2004—2020年期间，中国共报告肺结核16 262 631例、猩红热753 697例、麻疹801 663例、流脑11 151例和百日咳108 751例。图1显示了这五种主要RIDs的空间分布。新疆维吾尔自治区肺结核发病率（184.541/10万）、流脑发病率（0.300/10万）和百日咳发病率（1.871/10万）明显高于其他省份；而猩红热发病率（13.598/10万）主要聚集在北京；麻疹发病率主要分布在西藏（13.820/10万）、新疆（11.827/10万）等西部地区。总体上，肺结核和流脑的发病率分别呈现下降趋势；猩红热和百日咳在一定程度上波动上升；麻疹先波动升高再下降；季节分布上，肺结核各月发病率均匀，无显著季节性。猩红热季节性明显，冬季（12月—次年2月）为发病高峰。麻疹流行季节为春季（3月—5月）。流脑的发病率在春季（2月—4月）达到高峰。百日咳发病率夏季（7月—8月）最高。（见图1、图2）。
2.2　全局空间自相关性分析
肺结核全局Moran I均大于0，从2004年至2005年从0.235逐渐上升到2018年至2019年的0.452，表明其聚集性逐渐增强。P<0.01具有统计学意义，且Z值均大于2.58，表明肺结核在中国的发病率存在显著的空间正相关性；猩红热全局Moran I均大于0，2004—2019年P<0.05具有统计学意义，且Z值在2004—2019年均大于2.58，表明猩红热这一时期在中国的发病率存在显著的空间正相关性，2020年正相关性下降；麻疹全局Moran I在2008—2009年为负值，其余时期均大于0。2004—2005年期间P<0.05且Z>1.96，表明这一时期麻疹呈空间正相关，2010—2011年和2014—2017年这两个时间段P<0.05且Z>2.58，表明这两个时期麻疹在中国的发病率存在显著的空间正相关性；而流脑和百日咳的全局Moran I正负交替出现，Z值相对较小，P值多数大于0.05，说明空间呈现离散趋势或未形成持续的空间聚集性。见表1、表2。
2.3　局部空间自相关分析
2004—2020年肺结核发病热点逐渐扩散，2004—2005年暂未出现发病热点，2006—2007年位于湖南省，2008年后主要向西部地区扩散。猩红热高高聚集性自2006—2017年在内蒙古自治区和吉林省交替或同时出现，2018—2019年出现在河北省和北京市，2020年出现在甘肃省。麻疹高高聚集在中西部地区，青海地区尤其严重。流脑高高聚集性范围较小，2004—2005年出现在西藏自治区，2014—2015年出现在青海省后消失。百日咳高高聚集性自2004—2009年主要出现在中西部地区，随后逐渐消失，2020年又在南部少数地区出现（图3）。
2.4　重力重心迁移和标准差椭圆
肺结核发病重心主要集中在陕西省和甘肃省，重心逐渐向西南方向迁移。自2004—2018年椭圆逐渐增大，表明肺结核的分布范围较广且离散程度较高。2019—2020年椭圆明显缩小，肺结核的分布范围逐渐集中。
猩红热发病重心早期位于华北地区，2011年向西南方向迁移至陕西省一带，2014年后回迁至华北山西省附近。标准差椭圆早期范围较广覆盖华北、华东多个省份，发病分散性高；中期椭圆范围逐渐缩小聚集华中局部地区；近年椭圆范围继续缩小，集中在华北局部。
麻疹发病重心2004由甘肃省向东北部转移，2010年后逐渐开始向西部转移，最终又回到陕西省附近。标准差椭圆早期覆盖范围较广，发病分散性高；中期椭圆聚集于华中地区；近年来收缩至西北局部地区。
流脑发病重心早期主要集中在宁夏回族自治区和陕西省周围，后逐渐向西北部迁移，2016年后向东南部迁移至重庆市附近。标准差椭圆早期范围较小且集中在华东地区，随后广泛覆盖大半个中国，后期范围缩小稳定在中西部地区。
百日咳发病重心早期向西北部迁移，2015年后向东南部迁移至湖北省附近。标准差椭圆早期覆盖华东、华北广泛地区，发病较为分散。中期覆盖至华中及西北部分地区，后期聚焦于华中及南部地区（图4）。
3　讨论
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时空分析技术通过测量疾病在时间和空间上的相关性，有效揭示RIDs高发地区和潜在风险地区[13]。本研究通过探讨中国五种RIDs，系统分析了2004—2020年间的时空分布格局和迁移路线，强调了时空分布在RIDs防疫工作中的重要作用。同时揭示了两大核心趋势：一方面，在长期防控政策作用下，肺结核、流脑和麻疹的发病率呈持续或波动下降态势，且空间聚集性呈现不同的演变路径；另一方面，2020年COVID-19防控措施的实施，对所有疾病产生了抑制效应，但其抑制程度在不同疾病间存在差异。从而引出了两个问题：第一，理解不同疾病其长期时空格局演变的异同。第二，它们对同一种非药物干预措施（NPIs）是否会表现出差异化的响应。
2020年观察到五种RIDs的发病率普遍骤降，为评估NPIs对呼吸道病原体传播的广谱性与差异性效果提供了独一无二的自然实验证据[14]。全民佩戴口罩、保持社交距离、限制大型集会乃至局部封锁等严格的NPIs措施直接减少了人际接触频率和飞沫传播机会，切断了RIDs的共同传播途径。如图2，将2004—2019年的长期趋势与2020年的数据点进行对比，可以观察到一次断崖式下降，这表明了突发公共卫生事件作为短期强力干扰因素的特征。长期趋势反映了防控政策的累积效果，而2020年的骤降则直观展示了NPIs在短期内压制传播的强大能力。进一步分析发现，NPIs的抑制效果在不同疾病间存在差异，这反衬出各类病原体传播动力学的不同。猩红热与百日咳的降幅尤为剧烈，这可能源于二者缺乏高效疫苗（猩红热）或疫苗免疫力可能随时间衰减（百日咳），其传播更依赖于频繁的易感人群接触，因此对NPIs的阻断作用更为敏感。已通过疫苗建立牢固免疫屏障的麻疹和流脑，其本身发病率已处于极低水平，NPIs的叠加效应更多是巩固了既有成果。而肺结核对NPIs的反应模式与急性传染病存在差异。尽管NPIs通过减少人群接触，在2020年对肺结核的传播产生了一定的抑制效应，但其发病率的下降幅度远不如猩红热、百日咳等急性传染病。表明对于肺结核这类慢性传染病，NPIs这种普适性的公共卫生干预对其防控效果相对有限。2020年数据的下滑可能更应被理解为长期下降趋势中的一次小幅波动，而非流行规律的根本性扭转。这一差异化提示，在制定未来应对新发RIDs策略时，应充分考虑目标病原体的传播动力学特征和现有免疫背景。
深入分析五种疾病的时空格局，发现其演变规律并非杂乱无章，而是反映了不同类型RIDs在干预策略、传播动力学和社会自然因素等共同作用下的差异化响应。首先，疫苗可预防疾病的命运引人深思。流脑空间聚集性的消失，印证了高水平免疫规划在构建群体免疫屏障[15]、阻断传播链方面的作用，可视为公共卫生干预的成功典范[16]。然而，同为疫苗可预防的麻疹和百日咳，空间聚集性出现动态变化，则揭示了免疫策略面临的持久性挑战，这可能与细胞疫苗保护效力随时间的衰减密切相关[17]，提示需要对免疫程序的持久保护效果给予持续关注。建议在此区域重点开展青少年及成人疫苗加强接种的宣传教育与试点项目，同时利用大数据技术优化流动儿童的预防接种信息跨区域管理，确保免疫服务的可及性与连续性。
与上述疾病形成对比的是无疫苗可用的猩红热。其北归并稳定聚集于内蒙古等地的时空特征，可能将病因指向了自然与社会因素。这种格局很可能与北方地区冬季寒冷漫长、室内活动频繁[18]有关。同时，牧区医疗点稀疏[19]，儿童症状识别和转诊效率低[20]。建议针对性地强化学校晨检机制，并在冬季开展RIDs防控宣传周，推广室内通风和佩戴口罩措施，提高基层医疗机构工作人员的配置水平。
值得关注的是肺结核，其热点持续向西部地区迁移，提示贫困、营养不良、医疗资源可及性差等社会决定因素是其难以根除的原因[21]。此外，高原缺氧环境可能削弱局部免疫力，进一步加剧疾病负担[22]。因此，建议在热点带推行综合性干预。将结核防控与乡村振兴政策绑定，提供诊断补贴；加强基层医疗设施建设，推广移动诊疗车覆盖偏远地区。
综上所述，本研究发现中国五种RIDs的时空格局演变受到三类力量的共同塑造：一是疫苗等特异性干预措施，它决定了疾病的基本流行态势；二是社会经济与环境因素，它解释了疾病为何在某些地区表现出顽固的空间韧性；三是NPIs的短期影响，其效果强弱揭示了疾病传播链的脆弱环节。因此，未来的防控策略需具备分层和精准思维：对疫苗可预防疾病，重点是查漏补缺；对猩红热等，需强化监测预警；而对肺结核，则需推行融入扶贫、教育等的综合干预模式。
但本研究的局限性不容忽视。首先，本研究虽系统揭示了中国五种RIDs时空演变规律，但是主要依赖国家传染病报告系统数据，研究表明2023年我国肺结核患者仅有76%被发现并报告[23]。因此，本研究可能低估了西部、农村等薄弱地区的真实疾病发病率。导致对五种疾病具体时空分布情况的描述不够全面。后续工作需通过多种渠道进一步核实并补充数据。另一方面，17年间传染病诊断技术和报告标准的演进，也可能对发病率的长期趋势比较和不同年份间的横向对比带来潜在影响。其次，数据库中不同年龄猩红热发病率缺失，而年龄是传染病重要的混杂因素之一。因此，在后续研究中应广泛收集年龄信息，分析不同疾病发病人群的年龄结构及不同年龄对发病率的影响。最后，数据库信息仅更新至2020年，尚未纳入2021至2025年的数据，导致无法评估重大公共卫生事件对这些疾病发病率的影响。且现有分析尚未整合经济水平、环境暴露及医疗资源配置等关键协变量，而这些因素之间相互关联，共同构成疾病的风险背景，可能会对针对性防控策略制定产生影响。未来的研究应将医院信息系统、人口普查、环境监测等多源大数据整合，构建包含上述关键协变量的多层次模型，将能更清晰地揭示驱动疾病时空演变的根本动力，从而为制定更具针对性和根因性的防控策略提供科学依据。
4　结论
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本研究系统揭示了五种RIDs的时空演化规律，追踪了发病热点的变化趋势、发病重心与发病范围的动态演变特征。不仅观察到了空间异质性还发现了一定的共性，为制定精准防控策略提供了科学依据。从时间上讲，肺结核发病率呈现下降趋势，猩红热发病率呈波动上升趋势，麻疹发病率出现波动下降趋势，流脑发病率持续下降，百日咳发病率呈现缓慢上升的趋势。从空间上看，肺结核发病热点地区主要在西部地区。猩红热高高聚集区主要位于内蒙古地区。麻疹发病主要聚集在青海等西部地区。流脑发病率低，发病热点少有出现。百日咳的发病热点早期主要出现在青海和甘肃地区，后聚集于南部少数地区。中国五种RIDs防控格局呈现西迁与北归态势：一方面，公共卫生政策推动肺结核、麻疹等疾病重心向西部资源薄弱区迁移，形成以青藏高原—甘青新交界（青海省、甘肃省以及新疆维吾尔自治区这一相互毗连的省份）为核心的持续高聚集区。另一方面，猩红热向华北—东北转移。且五种疾病的发病重心都在山西、宁夏、陕西等西北部地区徘徊。因此，更应该加强对西部地区的精准防控和北部地区的重点监测，加大中国西北部地区防控资源的投入，完善西部地区的RIDs监测体系，优化医疗资源配置，提升全国对于RIDs的防控能力。
基金
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  • 江苏省中医药学会雏鹰腾飞项目(CYTF2024077)
  • 镇江市科技智库“青年人才”项目(ZKQN-2024-004)
  • 镇江市社科应用研究“学习贯彻党的二十届三中全会精神”专项课题(2024SZ017)
  • 上海市卫生健康委员会科研项目(202340019)
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2026年第53卷第8期
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doi: 10.20043/j.cnki.MPM.202509105
  • 接收时间：2025-09-05
  • 首发时间：2026-11-02
  • 出版时间：2026-04-25
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  • 收稿日期：2025-09-05
基金
江苏省中医药学会雏鹰腾飞项目(CYTF2024077)
镇江市科技智库“青年人才”项目(ZKQN-2024-004)
镇江市社科应用研究“学习贯彻党的二十届三中全会精神”专项课题(2024SZ017)
上海市卫生健康委员会科研项目(202340019)
作者信息
    1.华北理工大学公共卫生学院，河北　唐山　063210
    2.镇江市第三人民医院
    3.江苏大学医学院
    4.南京中医药大学镇江附属医院

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邹圣强，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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