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Article(id=1324077475592012173, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077443828560770, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509087, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1757260800000, receivedDateStr=2025-09-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614270350, onlineDateStr=2026-11-02, pubDate=1775750400000, pubDateStr=2026-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614270350, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614270350, creator=13701087609, updateTime=1793614270350, updator=13701087609, issue=Issue{id=1324077443828560770, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='7', pageStart='1153', pageEnd='1344', issueExtLink='null', onlineDate='null', pubDate='1775750400000', pubDateStr='2026-04-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614262778, creator='13701087609', updateTime=1793614352085, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324077818509918661, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077443828560770, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324077818509918662, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077443828560770, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1186, endPage=1194, ext={EN=ArticleExt(id=1324077475843670414, articleId=1324077475592012173, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Epidemiological characteristics and spatiotemporal clustering analysis of sexually transmitted infections in China from 2010 to 2020, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the epidemiological characteristics and spatiotemporal distribution of sexually transmitted infections (STIs) including HIV/AIDS, gonorrhea and syphilis in China from 2010 to 2020, providing scientific evidence for optimizing STIs prevention and control strategies.

Methods

Case data on STIs (HIV/AIDS, gonorrhea, syphilis) from 2010 to 2020 were extracted from the Public Health Data Center. Descriptive epidemiology, standard deviation ellipse, center of gravity migration modeling, and spatial autocorrelation analysis were employed to analyze epidemiological characteristics and spatial evolution patterns.

Results

From 2010 to 2020, a cumulative total of 6 558 885 HIV/AIDS, gonorrhea and syphilis cases were reported across 31 provinces nationwide, with an average annual incidence rate of 43.55 per 100 000 population. Syphilis accounted for the highest proportion (73.68%), followed by gonorrhea (18.31%) and AIDS (8.01%). The incidence of AIDS continued to rise (1.20 → 4.43 per 100 000), syphilis fluctuated upward (26.86 → 33.08 per 100 000), while gonorrhea slightly decreased (7.91 → 7.49 per 100 000). Gonorrhea exhibited seasonal peaks in summer and autumn (July-October), whereas other STIs showed no distinct seasonal patterns. The primary high-risk group for AIDS was individuals aged 20 and above, while gonorrhea predominantly affected those aged 15-25. The high-risk group for syphilis shifted from infants and young children to individuals aged 85 and above. HIV/AIDS clustered in the southwest region and spread toward the northwest. Gonorrhea was prevalent in eastern regions (Zhejiang, Fujian) and southern China (Guangdong, Hainan). Syphilis originated in southern China (Guangdong, Guangxi Zhuang Autonomous Region) and spread toward the northwest (Qinghai, Xinjiang Uygur Autonomous Region). Global spatial autocorrelation analysis revealed significant positive spatial correlations between HIV/AIDS (except in 2010) and gonorrhea incidence, with increasing clustering intensity annually (Moran's I values: 0.08-0.36, P<0.05). Syphilis incidence primarily exhibited random distribution patterns (Moran's I values: 0.06-0.34, P>0.05). Standard deviation ellipses and center of gravity migration models revealed that the epidemic center was located at the junction of Sichuan, Chongqing, and Hunan provinces. From 2010 to 2020, the center first shifted northward and then southward, with the greatest displacement occurring in 2012 and 2019—2020.

Conclusion

STIs in China from 2010 to 2020 exhibited distinct spatio-temporal clustering. Given the substantial burden of sexually transmitted infections in China and the persistent southward shift of hotspots, differentiated interventions should be implemented in high-incidence areas and key populations across Southwest and South China. Strengthening cross-regional joint prevention and control mechanisms is imperative.

, authors=Yu-peng LIU1, Ming-hui SHA2, Hai-hao JIN2, authorsList=Yu-peng LIU, Ming-hui SHA, Hai-hao JIN, authorCompany=null, correspAuthors=Hai-hao JIN, 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=1324077478683214233, articleId=1324077475592012173, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=2010—2020年中国主要性传播疾病的流行病学特征及时空聚集性分析, 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

分析2010—2020年中国艾滋病、淋病、梅毒3种性传播疾病（sexually transmitted infections，STIs）的流行病特征和时空分布，为优化性传播传染病的防控策略提供科学依据。

方法

从公共卫生数据中心提取2010—2020年STIs（艾滋病、淋病、梅毒）的病例资料，运用描述性流行病学、标准差椭圆及重心迁移模型方法和空间自相关分析方法分析其流行病学特征及空间演变规律。

结果

2010—2020年，累积全国31个省份报告艾滋病、淋病、梅毒共6 558 885例，年均发病率为43.55/10万，其中梅毒占比最高，为73.68%，其次为淋病的18.31%和艾滋病的8.01%。2010—2020年艾滋病发病率持续上升（1.20/10万→4.43/10万），梅毒波动上升（26.86/10万→33.08/10万），淋病略有下降（7.91/10万→7.49/10万）；淋病夏季和秋季高发（7—10月），其余病种无明显季节性规律。艾滋病高发人群以20岁以上为主，淋病高发人群集中于15~25岁，梅毒高发人群从婴幼儿转变为85岁以上人群。艾滋病聚集于西南地区并向西北地区扩散；淋病高发于东部地区（浙江、福建）及华南地区（广东、海南）；梅毒始于华南地区（广东、广西壮族自治区）并向西北地区（青海、新疆维吾尔自治区）蔓延。全局空间自相关结果显示，艾滋病（除2010年）和淋病发病呈现显著空间正相关性且聚集性逐年增强（Moran I值为0.08~0.36，P<0.05），梅毒主要呈现随机分布特征（Moran I值为0.06~0.34，P>0.05）。标准差椭圆及重心迁移模型显示，发病重心位于川渝湘交界带，2010—2020年整体呈“先北后南”迁移，2012年与2019—2020年移动距离最大。

结论

2010—2020年中国STIs具有明显的时空聚集性。中国性传播传染病负担沉重，热点区域持续南移，应针对西南地区和华南地区的高发区及重点人群实施差异化干预，强化跨地区联防联控机制。

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刘雨朋（2001—），男，硕士在读，研究方向：流行病学与统计学

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金海浩，E-mail：
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BMC Public Health, 2025, 25(1): 1928., articleTitle=Global and regional disease burden of HIV/AIDS from 1990 to 2021 and projections to 2030, refAbstract=null), Reference(id=1324077488590160348, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, doi=null, pmid=null, pmcid=null, year=2024, volume=43, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[18], rfOrder=17, authorNames=Zhang C, Fu XH, Liu YQ, journalName=Lancet Reg Health West Pac, refType=null, unstructuredReference=Zhang C, Fu XH, Liu YQ, et al. Burden of infectious diseases and bacterial antimicrobial resistance in China: a systematic analysis for the global burden of disease study 2019[J]. Lancet Reg Health West Pac, 2024, 43: 100972., articleTitle=Burden of infectious diseases and bacterial antimicrobial resistance in China: a systematic analysis for the global burden of disease study 2019, refAbstract=null), Reference(id=1324077488653074909, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, doi=null, pmid=null, pmcid=null, year=2021, volume=224, issue=12, pageStart=S103, pageEnd=S112, url=null, language=null, rfNumber=[19], rfOrder=18, authorNames=Kreisel KM, Llata E, Haderxhanaj L, journalName=The Journal of Infectious Diseases, refType=null, unstructuredReference=Kreisel KM, Llata E, Haderxhanaj L, et al. The burden of and trends in pelvic inflammatory disease in the United States, 2006-2016[J]. The Journal of Infectious Diseases, 2021, 224(12): S103-S112., articleTitle=The burden of and trends in pelvic inflammatory disease in the United States, 2006-2016, refAbstract=null), Reference(id=1324077488736960990, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, doi=null, pmid=null, pmcid=null, year=2023, volume=34, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[20], rfOrder=19, authorNames=Kenyon C, Herrmann B, Hughes G, journalName=Lancet Reg Health Eur, refType=null, unstructuredReference=Kenyon C, Herrmann B, Hughes G, et al. Management of asymptomatic sexually transmitted infections in Europe: towards a differentiated, evidence-based approach[J]. Lancet Reg Health Eur, 2023, 34: 100743., articleTitle=Management of asymptomatic sexually transmitted infections in Europe: towards a differentiated, evidence-based approach, refAbstract=null), Reference(id=1324077488850207199, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, doi=null, pmid=null, pmcid=null, year=2024, volume=22, issue=1, pageStart=296, pageEnd=null, url=null, language=null, rfNumber=[21], rfOrder=20, authorNames=Soe NN, Yu Z, Latt PM, journalName=BMC Medicine, refType=null, unstructuredReference=Soe NN, Yu Z, Latt PM, et al. Evaluation of artificial intelligence-powered screening for sexually transmitted infections-related skin lesions using clinical images and metadata[J]. BMC Medicine, 2024, 22(1): 296., articleTitle=Evaluation of artificial intelligence-powered screening for sexually transmitted infections-related skin lesions using clinical images and metadata, refAbstract=null)], funds=[Fund(id=1324077487046656458, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, awardId=MS2023145, language=CN, fundingSource=2023年度江苏省中医药科技发展计划项目(MS2023145), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324077478918095258, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, xref=1., ext=[AuthorCompanyExt(id=1324077478926483867, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, companyId=1324077478918095258, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, North China University of Science and Technology, Tangshan, Hebei 063210, China), AuthorCompanyExt(id=1324077478939066780, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, companyId=1324077478918095258, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.华北理工大学公共卫生学院，河北　唐山　063210)]), AuthorCompany(id=1324077479031341469, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, xref=2., ext=[AuthorCompanyExt(id=1324077479035535774, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, companyId=1324077479031341469, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.镇江市第三人民医院，江苏　镇江　212000)])], figs=[ArticleFig(id=1324077482831380920, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Figure 1, caption=Monthly incidence trends of major sexually transmitted infections in China, 2010—2020, figureFileSmall=OmWkES4+oCop+hS3Acsaiw==, figureFileBig=IRw9VuoyZm2KqQCmwL0ZgA==, tableContent=null), ArticleFig(id=1324077483108204985, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=图1, caption=2010—2020年中国STIs月发病率变化趋势, figureFileSmall=OmWkES4+oCop+hS3Acsaiw==, figureFileBig=IRw9VuoyZm2KqQCmwL0ZgA==, tableContent=null), ArticleFig(id=1324077483322114490, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Figure 2, caption=Age distribution of cases for major sexually transmitted infections in China, 2010 and 2020, figureFileSmall=1icDf0RZp8dFu8hQuKaO6Q==, figureFileBig=wYnudGUkFDbeL5RBmtU93w==, tableContent=null), ArticleFig(id=1324077483389223355, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=图2, caption=2010与2020年中国STIs发病人群分布

注：A为2010年与2020年艾滋病不同年龄段的发病率；B为2010年与2020年淋病不同年龄段的发病率；C为2010年与2020年梅毒不同年龄段的发病率。

, figureFileSmall=1icDf0RZp8dFu8hQuKaO6Q==, figureFileBig=wYnudGUkFDbeL5RBmtU93w==, tableContent=null), ArticleFig(id=1324077483590549948, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Figure 3, caption=Geographical distribution of incidence rate for major sexually transmitted infections in China, 2010 and 2020, figureFileSmall=QEkp/2mxEs+ltxOBWH/00g==, figureFileBig=vRcYLemYjAA3Yx2gg6tW4A==, tableContent=null), ArticleFig(id=1324077483674436029, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=图3, caption=2010和2020年中国STIs发病率的地区分布

注：图A、B为2010和2020年艾滋病发病地区分布；图C、D为2010和2020年淋病发病地区分布；图E、F为2010和2020年梅毒发病地区分布；审图号：GS（2024）0650号。

, figureFileSmall=QEkp/2mxEs+ltxOBWH/00g==, figureFileBig=vRcYLemYjAA3Yx2gg6tW4A==, tableContent=null), ArticleFig(id=1324077483754127806, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Figure 4, caption=Local indicators of spatial association (LISA) cluster maps for major sexually transmitted infections in China, 2010 and 2020, figureFileSmall=mIFNJn5W7bayj0ai2gBLWQ==, figureFileBig=py2QsihmmIRteDiTsbJl+w==, tableContent=null), ArticleFig(id=1324077483833819583, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=图4, caption=2010—2020年我国STIs局部自相关分析分布图

注：图A、B为2010和2020年中国艾滋病局部自相关分析鸟瞰图；图C、D为2010和2020年中国淋病局部自相关分析鸟瞰图；图E、F为2010和2020年中国梅毒局部自相关分析鸟瞰图；审图号为GS（2024）0650号。

, figureFileSmall=mIFNJn5W7bayj0ai2gBLWQ==, figureFileBig=py2QsihmmIRteDiTsbJl+w==, tableContent=null), ArticleFig(id=1324077483896734144, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Figure 5, caption=Migration trajectory of the incidence gravity center of sexually transmitted infections (HIV/AIDS, gonorrhea, and syphilis) in China, 2010—2020, figureFileSmall=Evy9TmeVWkLxnpJ+y+Y+rQ==, figureFileBig=VENELv3gytXkvRHlIkNFzg==, tableContent=null), ArticleFig(id=1324077484030951873, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=图5, caption=2010—2020年我国STIs（艾滋病、淋病、梅毒）发病率重心迁移轨迹, figureFileSmall=Evy9TmeVWkLxnpJ+y+Y+rQ==, figureFileBig=VENELv3gytXkvRHlIkNFzg==, tableContent=null), ArticleFig(id=1324077484114837954, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Table 1, caption=

Epidemiological overview of STIs in China, 2010—2020

, figureFileSmall=null, figureFileBig=null, tableContent=
时间（年）艾滋病淋病梅毒总病发数发病率（1/10万）
发病数发病率（1/10万）发病数发病率（1/10万）发病数发病率（1/10万）
201015 9821.20105 5447.91358 53426.86480 06035.97
201120 4501.5397 9547.31395 18229.47513 58638.30
201241 9293.1191 8536.82410 07430.44543 85640.36
201342 2863.1299 6597.36406 77230.04548 71740.52
201445 1453.3395 4737.05419 09130.93559 70941.30
201550 3303.69100 2457.36433 97431.85584 54942.90
201654 3603.97115 0248.39438 19931.97607 58344.32
201757 1944.14138 85510.06475 86034.49671 90948.69
201864 1704.62133 1569.59494 86735.63692 19349.83
201971 2045.10117 9388.45535 81938.37724 96151.91
202062 1674.43105 1607.49464 43533.08631 76245.00
), ArticleFig(id=1324077484358107587, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=表1, caption=

2010—2020年中国STIs流行概况

, figureFileSmall=null, figureFileBig=null, tableContent=
时间（年）艾滋病淋病梅毒总病发数发病率（1/10万）
发病数发病率（1/10万）发病数发病率（1/10万）发病数发病率（1/10万）
201015 9821.20105 5447.91358 53426.86480 06035.97
201120 4501.5397 9547.31395 18229.47513 58638.30
201241 9293.1191 8536.82410 07430.44543 85640.36
201342 2863.1299 6597.36406 77230.04548 71740.52
201445 1453.3395 4737.05419 09130.93559 70941.30
201550 3303.69100 2457.36433 97431.85584 54942.90
201654 3603.97115 0248.39438 19931.97607 58344.32
201757 1944.14138 85510.06475 86034.49671 90948.69
201864 1704.62133 1569.59494 86735.63692 19349.83
201971 2045.10117 9388.45535 81938.37724 96151.91
202062 1674.43105 1607.49464 43533.08631 76245.00
), ArticleFig(id=1324077484450382276, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Table 2, caption=

Gender composition of cases for major sexually transmitted infections in China, 2010—2020

, figureFileSmall=null, figureFileBig=null, tableContent=
疾病男性病例数（%）女性病例数（%）性别比（男∶女）主要趋势
艾滋病78.5021.503.6∶1男性占比持续增加
淋病73.8026.202.8∶1比例相对稳定
梅毒54.5045.501.2∶1比例相对稳定
), ArticleFig(id=1324077484769149381, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=表2, caption=

2010—2020年中国主要STIs发病人群性别占比

, figureFileSmall=null, figureFileBig=null, tableContent=
疾病男性病例数（%）女性病例数（%）性别比（男∶女）主要趋势
艾滋病78.5021.503.6∶1男性占比持续增加
淋病73.8026.202.8∶1比例相对稳定
梅毒54.5045.501.2∶1比例相对稳定
), ArticleFig(id=1324077484857229766, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Table 3, caption=

Global spatial autocorrelation analysis of incidence rate for sexually transmitted infections in China, 2010—2020

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）艾滋病淋病梅毒
Moran I值Z值P值Moran I值Z值P值Moran I值Z值P值
20100.081.8210.0690.203.4230.0010.132.3590.018
20110.092.0660.0390.243.934<0.010.101.8090.070
20120.132.4400.0150.253.983<0.010.091.7470.081
20130.172.9690.0030.274.351<0.010.061.2500.211
20140.193.2310.0010.253.992<0.010.081.5550.120
20150.233.677<0.010.254.055<0.010.122.2120.027
20160.274.174<0.010.284.436<0.010.162.6260.009
20170.284.363<0.010.294.617<0.010.172.7710.006
20180.284.291<0.010.314.830<0.010.223.535<0.01
20190.284.500<0.010.334.972<0.010.334.8540.001
20200.324.891<0.010.365.346<0.010.345.000<0.01
), ArticleFig(id=1324077484962087367, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=表3, caption=

2010—2020年中国STIs发病率全局空间自相关分析

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）艾滋病淋病梅毒
Moran I值Z值P值Moran I值Z值P值Moran I值Z值P值
20100.081.8210.0690.203.4230.0010.132.3590.018
20110.092.0660.0390.243.934<0.010.101.8090.070
20120.132.4400.0150.253.983<0.010.091.7470.081
20130.172.9690.0030.274.351<0.010.061.2500.211
20140.193.2310.0010.253.992<0.010.081.5550.120
20150.233.677<0.010.254.055<0.010.122.2120.027
20160.274.174<0.010.284.436<0.010.162.6260.009
20170.284.363<0.010.294.617<0.010.172.7710.006
20180.284.291<0.010.314.830<0.010.223.535<0.01
20190.284.500<0.010.334.972<0.010.334.8540.001
20200.324.891<0.010.365.346<0.010.345.000<0.01
), ArticleFig(id=1324077485251494344, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=EN, label=Table 4, caption=

Calculation table of the migration trajectory of the incidence rate gravity center of sexually transmitted infections (HIV/AIDS, gonorrhea, and syphilis) in China, 2010—2020

, figureFileSmall=null, figureFileBig=null, tableContent=
经度纬度移动方向及角度距离/m
108.9630.11——
108.9630.16东南0.898 25 627.06
107.2530.81东南64.621 5177 627.99
108.1330.92东北7.242 384 294.37
108.4531.13东北37.785 137 698.43
108.4731.37东北83.835 826 791.62
108.4531.46东南12.385 411 042.03
108.4031.52东南35.623 17 822.44
108.0631.69东南57.466 736 691.27
108.0831.40西北1.869 532 776.66
108.3830.86西北23.491 066 925.83
), ArticleFig(id=1324077486920827337, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077475592012173, language=CN, label=表4, caption=

2010—2020年我国STIs（艾滋病、淋病、梅毒）发病率重心迁移轨迹计算表

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经度纬度移动方向及角度距离/m
108.9630.11——
108.9630.16东南0.898 25 627.06
107.2530.81东南64.621 5177 627.99
108.1330.92东北7.242 384 294.37
108.4531.13东北37.785 137 698.43
108.4731.37东北83.835 826 791.62
108.4531.46东南12.385 411 042.03
108.4031.52东南35.623 17 822.44
108.0631.69东南57.466 736 691.27
108.0831.40西北1.869 532 776.66
108.3830.86西北23.491 066 925.83
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2010—2020年中国主要性传播疾病的流行病学特征及时空聚集性分析
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刘雨朋 1 , 沙明慧 2 , 金海浩 2
现代预防医学 | 流行病与统计方法 2026,53(7): 1186-1194
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现代预防医学 |流行病与统计方法 2026 , 53 (7) : 1186 -1194
2010—2020年中国主要性传播疾病的流行病学特征及时空聚集性分析
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刘雨朋（2001—），男，硕士在读，研究方向：流行病学与统计学

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刘雨朋1, 沙明慧2, 金海浩2
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，江苏　镇江　212000
通讯作者:
金海浩，E-mail：
作者简介:

刘雨朋（2001—），男，硕士在读，研究方向：流行病学与统计学

Epidemiological characteristics and spatiotemporal clustering analysis of sexually transmitted infections in China from 2010 to 2020
Yu-peng LIU1, Ming-hui SHA2, Hai-hao JIN2
Affiliations
  • School of Public Health, North China University of Science and Technology, Tangshan, Hebei 063210, China
出版时间: 2026-04-10 doi: 10.20043/j.cnki.MPM.202509087
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摘要
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目的

分析2010—2020年中国艾滋病、淋病、梅毒3种性传播疾病（sexually transmitted infections，STIs）的流行病特征和时空分布，为优化性传播传染病的防控策略提供科学依据。

方法

从公共卫生数据中心提取2010—2020年STIs（艾滋病、淋病、梅毒）的病例资料，运用描述性流行病学、标准差椭圆及重心迁移模型方法和空间自相关分析方法分析其流行病学特征及空间演变规律。

结果

2010—2020年，累积全国31个省份报告艾滋病、淋病、梅毒共6 558 885例，年均发病率为43.55/10万，其中梅毒占比最高，为73.68%，其次为淋病的18.31%和艾滋病的8.01%。2010—2020年艾滋病发病率持续上升（1.20/10万→4.43/10万），梅毒波动上升（26.86/10万→33.08/10万），淋病略有下降（7.91/10万→7.49/10万）；淋病夏季和秋季高发（7—10月），其余病种无明显季节性规律。艾滋病高发人群以20岁以上为主，淋病高发人群集中于15~25岁，梅毒高发人群从婴幼儿转变为85岁以上人群。艾滋病聚集于西南地区并向西北地区扩散；淋病高发于东部地区（浙江、福建）及华南地区（广东、海南）；梅毒始于华南地区（广东、广西壮族自治区）并向西北地区（青海、新疆维吾尔自治区）蔓延。全局空间自相关结果显示，艾滋病（除2010年）和淋病发病呈现显著空间正相关性且聚集性逐年增强（Moran I值为0.08~0.36，P<0.05），梅毒主要呈现随机分布特征（Moran I值为0.06~0.34，P>0.05）。标准差椭圆及重心迁移模型显示，发病重心位于川渝湘交界带，2010—2020年整体呈“先北后南”迁移，2012年与2019—2020年移动距离最大。

结论

2010—2020年中国STIs具有明显的时空聚集性。中国性传播传染病负担沉重，热点区域持续南移，应针对西南地区和华南地区的高发区及重点人群实施差异化干预，强化跨地区联防联控机制。

性传播传染病  /  艾滋病  /  淋病  /  梅毒  /  时空流行病学
Objective

To analyze the epidemiological characteristics and spatiotemporal distribution of sexually transmitted infections (STIs) including HIV/AIDS, gonorrhea and syphilis in China from 2010 to 2020, providing scientific evidence for optimizing STIs prevention and control strategies.

Methods

Case data on STIs (HIV/AIDS, gonorrhea, syphilis) from 2010 to 2020 were extracted from the Public Health Data Center. Descriptive epidemiology, standard deviation ellipse, center of gravity migration modeling, and spatial autocorrelation analysis were employed to analyze epidemiological characteristics and spatial evolution patterns.

Results

From 2010 to 2020, a cumulative total of 6 558 885 HIV/AIDS, gonorrhea and syphilis cases were reported across 31 provinces nationwide, with an average annual incidence rate of 43.55 per 100 000 population. Syphilis accounted for the highest proportion (73.68%), followed by gonorrhea (18.31%) and AIDS (8.01%). The incidence of AIDS continued to rise (1.20 → 4.43 per 100 000), syphilis fluctuated upward (26.86 → 33.08 per 100 000), while gonorrhea slightly decreased (7.91 → 7.49 per 100 000). Gonorrhea exhibited seasonal peaks in summer and autumn (July-October), whereas other STIs showed no distinct seasonal patterns. The primary high-risk group for AIDS was individuals aged 20 and above, while gonorrhea predominantly affected those aged 15-25. The high-risk group for syphilis shifted from infants and young children to individuals aged 85 and above. HIV/AIDS clustered in the southwest region and spread toward the northwest. Gonorrhea was prevalent in eastern regions (Zhejiang, Fujian) and southern China (Guangdong, Hainan). Syphilis originated in southern China (Guangdong, Guangxi Zhuang Autonomous Region) and spread toward the northwest (Qinghai, Xinjiang Uygur Autonomous Region). Global spatial autocorrelation analysis revealed significant positive spatial correlations between HIV/AIDS (except in 2010) and gonorrhea incidence, with increasing clustering intensity annually (Moran's I values: 0.08-0.36, P<0.05). Syphilis incidence primarily exhibited random distribution patterns (Moran's I values: 0.06-0.34, P>0.05). Standard deviation ellipses and center of gravity migration models revealed that the epidemic center was located at the junction of Sichuan, Chongqing, and Hunan provinces. From 2010 to 2020, the center first shifted northward and then southward, with the greatest displacement occurring in 2012 and 2019—2020.

Conclusion

STIs in China from 2010 to 2020 exhibited distinct spatio-temporal clustering. Given the substantial burden of sexually transmitted infections in China and the persistent southward shift of hotspots, differentiated interventions should be implemented in high-incidence areas and key populations across Southwest and South China. Strengthening cross-regional joint prevention and control mechanisms is imperative.

Sexually transmitted infectious diseases  /  HIV/AIDS  /  Gonorrhea  /  Syphilis  /  Spatiotemporal epidemiology
刘雨朋, 沙明慧, 金海浩. 2010—2020年中国主要性传播疾病的流行病学特征及时空聚集性分析. 现代预防医学, 2026 , 53 (7) : 1186 -1194 . DOI: 10.20043/j.cnki.MPM.202509087
Yu-peng LIU, Ming-hui SHA, Hai-hao JIN. Epidemiological characteristics and spatiotemporal clustering analysis of sexually transmitted infections in China from 2010 to 2020[J]. Modern Preventive Medicine, 2026 , 53 (7) : 1186 -1194 . DOI: 10.20043/j.cnki.MPM.202509087
正文
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性传播疾病（sexually transmitted infections，STIs）是全球重大的公共卫生问题，其流行不仅威胁个体健康，更对社会经济发展和人口质量构成长期挑战[1-3]。世界卫生组织2020年估计，全球每年新增3.74亿例可治愈的性病病例，其中梅毒、淋病和艾滋病是三大法定报告病种。近年来，随着社会流动性增强、行为方式多元化以及检测技术的进步，中国STIs的流行特征呈现新的变化趋势。根据中国疾病预防控制中心数据，梅毒、淋病和艾滋病占全国法定报告性病病例的95%以上。2010—2020年是中国公共卫生体系快速发展的关键十年，也是艾滋病、梅毒等重大STIs防控策略持续优化的重要阶段[4]。因此，系统分析中国STIs发病的时空分布规律、动态演变特征及影响因素，对优化区域化防控资源配置、实现精准干预具有重要意义[5-6]。
空间流行病学作为一门融合地理学与流行病学的交叉学科，为在宏观尺度上可视化并量化疾病负担的空间异质性提供了强大工具。然而，现有研究多聚焦于单一病种（如HIV/AIDS）或局部区域的流行病学分析，缺乏对中国主要STIs发病模式的多病种、长时序、大尺度的整合研究[7-8]。此外，现有文献较少结合社会行为因素（如人口流动、网络交友模式普及）和环境变量（如城镇化率、医疗可及性）探讨其对STIs传播的空间驱动机制[9-10]。因此，本研究整合全国31个省份2010—2020年的法定报告数据，系统分析艾滋病、淋病、梅毒的流行病学特征及时空演变规律，量化社会生态因子对发病风险的贡献度，进而为构建“区域-人群-病种”三位一体的精准防控体系提供科学依据。
1　资料与方法
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1.1　资料来源
收集公共卫生科学数据中心2010—2020年全国艾滋病、淋病、梅毒的相关数据，包括中国大陆31个省份（直辖市、自治区）各年度STIs发病率数据。同期人口数据来源于《中国统计年鉴》，通过国家基础地理信息中心获取全国行政区矢量地图及经纬度坐标。本研究计算的发病率为粗发病率，即利用报告病例数除以当年《中国统计年鉴》公布的全国或各省份年中总人口数得出。
1.2　研究方法
1.2.1　空间自相关分析
空间自相关分析包括全局和局部空间自相关分析。全局空间自相关通过计算Moran I指数进行评估，该统计量用于量化整体上的空间依赖程度。其值为正提示空间正相关及聚集性，负值代表空间离散，而零值则表明随机分布。统计显著性通过Z检验判定（P<0.05）。局部空间自相关可识别出四种空间关联模式：热点区域（“高-高”聚集）、冷点区域（“低-低”聚集）、异常区域（“高-低”和“低-高”聚集）。
1.2.2　标准偏差椭圆分析及重心迁移
以各省会城市坐标为几何中心，计算其年度发病率的加权重心坐标，并构建标准差椭圆，以可视化空间扩散方向与范围。重心迁移轨迹通过逐年连接重心点获得，结合迁移距离和迁移角度定量描述2010—2020年中国STIs重心的时空演变规律。
1.3　统计学方法
采用Excel 2019和R 4.3.1对2010 —2020年中国STIs原始发病资料进行整理与描述性统计分析。运用ChiPlot软件绘制年龄分布哑铃图。使用ArcGIS 10.8软件开展空间自相关分析，结合SaTScan 10.1.2软件进行时空扫描分析。检验水准α=0.05。
2　结果
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2.1　STIs流行概况
2010—2020年全国累积报告STIs病例6 558 885例，其中艾滋病525 217例（8.01%）、淋病1 200 861例（18.31%）、梅毒4 832 807（73.68%）。STIs年均发病率为43.55/10万。见表1。
2.2　STIs三间分布特征
2.2.1　时间分布
艾滋病发病率由2010年的1.20/10万升至2020年的4.43/10万，淋病发病率由2010年的7.91/10万降至2020年的7.49/10万，梅毒发病率由2010年的26.86/10万升至2020年的33.08/10万。2010—2020年全国每月均有STIs病例出现。艾滋病发病无明显的季节性，发病率逐年增长，最高为2018年12月的0.57/10万，后逐渐趋于平缓。淋病发病高峰为每年的夏季和秋季（7—10月），其中2017年8月淋病发病率最高，为0.98/10万。梅毒发病无明显的季节性，其中2019年7月梅毒发病率最高，为3.58/10万。见图1。
2.2.2　人群分布
2010—2020年STIs各年龄均有发病，艾滋病以20岁以上年龄组为主，淋病以15~25岁以上年龄组为主，梅毒高发年龄变化较大。其中梅毒高发年龄组从0~1岁转变成85岁以上人群。见图2。
在性别分布方面，2010—2020年，三种STIs均表现出显著的性别差异。艾滋病病例以男性为主，男女性别比高达3.6∶1，且这一比例随时间推移进一步扩大。淋病病例同样主要为男性，性别比维持在2.8∶1左右。梅毒的性别分布最为均衡，但男性病例数仍略高于女性，性别比约为1.2∶1。见表2。
基于省级数据的相关分析显示，STIs的发病率与地区经济发展水平存在显著关联。淋病发病率与人均GDP呈显著正相关（rs=0.45，P<0.05），提示其在经济较发达省份的负担更重。与之相反，艾滋病发病率与人均GDP呈负相关趋势（rs=-0.32，P=0.08），虽未达到统计学显著性，但仍表明其负担可能向经济欠发达地区倾斜。梅毒发病率与人均GDP未发现显著相关性（rs=0.12，P>0.05）。
2.2.3　地区分布
2010—2020年艾滋病的空间分布显示出在西南省份[如广西壮族自治区（简称广西）、云南、贵州、四川]高度集中，并呈现出向西北地区[如新疆维吾尔自治区（简称新疆）]蔓延的趋势。具体而言，2010年高发区集中于云南、广西；至2015年，四川、重庆的聚集性显著增强，并出现向青海、新疆扩散的苗头；到2020年，形成了以川渝黔滇为核心的稳固热点区，并向西北延伸。华北地区[河北、山西、内蒙古自治区（简称内蒙古）]的发病率始终维持在较低水平。淋病2010—2020年高发地区为东部地区的浙江和福建，华南地区的广东和海南，并逐渐向西南地区（贵州、海南）扩散，2015年其东部（浙江、福建）和华南（广东、海南）的热点已非常清晰，构成了此后扩散的基础。中部地区（吉林，黑龙江）等地处于低流行水平。梅毒在2010年主要集中在华南地区（广东、广西），2015年可见明显的“西进”和“北上”趋势，热点区扩展至湖南、江西等地，并初步波及西北；至2020年，已逐渐向西北地区（青海、新疆等）扩散，华北地区（山东、河北等）处于低流行水平。见图3。
2.3　空间分析
2.3.1　全局空间自相关分析
除2010年HIV发病率外，艾滋病、淋病在2010—2020年中国历年发病率均呈现空间正相关（Moran I值为0.08~0.36，P<0.05），即艾滋病和淋病存在空间聚集性。淋病的Moran I值除2014和2015年在0.25左右波动，艾滋病和淋病Moran I值均呈现逐年上升趋势，表明2010—2020年艾滋病及淋病发病的空间聚集性逐渐增强。梅毒发病率主要呈随机分布（Moran I值为0.06~0.34，P<0.05）。见表3。
2.3.2　局部空间自相关分析
中国STIs在2010—2020年局部热点区域多集中艾滋病我国南部地区。2020年局部空间自相关结果显示，艾滋病高-高区域为四川、贵州、云南、湖南、重庆和广西；淋病高-高区域为江西、福建、广东、海南；梅毒高-高区域为广东、西藏自治区（简称西藏）；艾滋病、淋病和梅毒低-低区域均为吉林、辽宁、北京、河北、内蒙古；淋病和梅毒低-高区域分别为湖南和广西。见图4。
2.4　标准偏差椭圆分析及重心迁移轨迹计算
2010—2020年我国主要STIs的发病重心高度集中于四川、重庆、湖南和湖北四省交界地带，这一重心位置与全国的几何重心（大致在甘肃境内）乃至各省的几何重心（省会城市）均不重合，从宏观尺度上直观地印证了我国STIs发病率存在显著的空间异质性，呈现非均衡的增长模式。从移动轨迹看，重心在2010—2020年存在阶段性波动，移动距离最为显著的时期是2010—2012年、2012—2013年以及2019—2020年；整体上呈现出“先北移后南返”的迁移趋势，但其活动范围始终未脱离上述核心热点区域。见表4、图5。
3　讨论
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本研究从2010—2020年中国大陆31个省份艾滋病、淋病与梅毒三种STIs的三间分布、时空变化规律与演化轨迹，发现2010—2020年中国STIs中梅毒发病率最高，艾滋病发病率持续快速上升，淋病略有下降，三者呈现显著的人群、季节和空间分布差异。三种疾病空间分布模式各异，全国发病重心动态迁移，凸显了精准化、差异化防控的迫切需求。
2010—2020年，梅毒年均发病率由26.86/10万上升至33.08/10万，占全部STIs病例的73.68%，提示国家梅毒防控规划虽已实施十余年，但距离“先天梅毒≤15/10万活产”目标仍有显著差距。艾滋病发病率则由1.20/10万持续上升至4.43/10万，年均增长率达11.4%，表明国家“十二五”“十三五”行动计划取得阶段性成效。淋病发病率整体下降，但夏季与秋季（7 —10月）出现明显峰值，其传播与季节性有关联，需开展时点性干预。
艾滋病以20岁以上成年人为主，淋病集中于15~25岁人群，而梅毒高发年龄则从婴幼儿后移至85岁以上老年人群。该变化趋势可能与以下因素有关：母婴阻断策略的强化使得婴幼儿梅毒发病率显著下降[11-12]；老年人群性行为活跃、防护意识薄弱、空巢老人缺少陪伴以及合并慢性病等因素，导致其成为新的高风险人群；青年群体中淋病高发与避孕方式转变（如口服避孕药替代安全套）有关[13-14]。因此，未来防控策略应根据年龄结构变化，完善检测系统，针对高危人群的识别，更加精准制定防控措施，尤其应加强对老年群体的性健康教育及筛查覆盖[15]。
本研究补充的性别与社会经济维度分析，为精准防控提供了更清晰的画像。艾滋病和淋病在男性中的高负担，可能与男性更广泛的性网络、更高的商业性行为比例以及男男性行为人群中疫情的快速上升有关。梅毒性别分布相对均衡，但需关注孕产妇梅毒筛查对女性病例发现率的提升作用。从社会经济角度看，淋病在经济发达地区的聚集，或与人口流动性大、娱乐服务业密集等因素相关；而艾滋病向经济欠发达地区的扩散趋势，则警示我们需关注这些地区在健康教育、检测资源和治疗可及性方面的短板。这凸显了防控策略需结合地区发展不平衡的国情，在经济发达地区加强行为干预和规范性病诊疗市场，在欠发达地区则需强化基础防控体系建设和财政支持。
2010—2020年，艾滋病与淋病的全局Moran I值分别由2010年的0.08、0.20上升至2020年的0.32、0.36，发病呈现空间正相关性。艾滋病局部热点区域集中于四川、云南、贵州、广西、广东等地，发病率呈现“高-高”聚集的分布趋势。进一步分析得出“热点”主要聚集在我国大陆西南地区，“冷点”主要聚集在东部地区。其西南地区的高聚集性主要与以下因素密切相关：（1）边境流动性：云南、广西毗邻“金三角”毒品走廊，跨境毒品与性交易网络增加了传播，有着特殊的信仰文化背景，多个性伴侣的情况比例较高，增加了患病的风险[16-17]；（2）经济梯度：西南地区人均GDP较低，贫困人口数量较大、经济欠发达地区医疗资源匮乏，导致病例发现与报告滞后[18-19]；（3）文化脆弱性：教育水平较低，性健康教育覆盖不足，缺乏性相关的预防知识，从而增加了患病风险。梅毒发病率最高，其发病率主要呈随机分布[20-21]。局部空间自相关分析研究表明，一些梅毒高危人群存在于欠发达地区和内陆地区，包括新疆、西藏等。重心迁移轨迹显示，2010—2020年中国STIs发病重心整体呈现“先北后南”的迁移趋势，尤其2012年与2019 —2020年移动距离最大，疫情存在阶段性扩散与回流现象。
本研究的主要优势在于运用地理信息系统技术对全国2010—2020年艾滋病、淋病、梅毒从年龄、时间、地区等方面进行分析，为未来STIs预防工作有一定的借鉴意义。但此研究也存在一定的局限性。首先，本研究的病例资料来源于公共卫生科学数据中心，其公布的最新数据截至2020年，未能涵盖最近几年的流行态势，未来研究需纳入更新数据以验证趋势的持续性。其次，本研究分析只精确到省级的发病率信息，故研究得到的结论可能不够精准。在今后的研究中，可以评估地方级发病的时间趋势和地理分布，以更详细地识别我国STIs的多样性，未来有待进一步开展研究。此外，本研究使用粗发病率进行时空比较。粗发病率未对地区间和不同时期的人口年龄、性别结构差异进行标准化，因此，观察到的部分差异可能受到人口结构因素的影响。例如，梅毒在高龄人群中的发病率上升，可能与我国人口老龄化趋势有关。未来研究若能从数据源获取更详细的分年龄、性别人口学数据，采用年龄标准化发病率进行分析，将能更精确地揭示疾病负担的真实变化趋势和地区差异。最后，本研究中使用省级人均GDP作为收入水平的代理指标，未能反映个体层面的社会经济状况，未来研究若能获取个体层面的数据，如职业、教育、医保类型等，将能更精确地揭示社会经济因素对STIs风险的影响。
基金
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  • 2023年度江苏省中医药科技发展计划项目(MS2023145)
文献
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2026年第53卷第7期
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doi: 10.20043/j.cnki.MPM.202509087
  • 接收时间：2025-09-08
  • 首发时间：2026-11-02
  • 出版时间：2026-04-10
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  • 收稿日期：2025-09-08
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2023年度江苏省中医药科技发展计划项目(MS2023145)
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    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，江苏　镇江　212000

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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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