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Article(id=1324050991196287442, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324050876230415089, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202601190, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1768233600000, receivedDateStr=2026-01-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793607955979, onlineDateStr=2026-11-02, pubDate=1781020800000, pubDateStr=2026-06-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793607955979, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793607955979, creator=13701087609, updateTime=1793607955979, updator=13701087609, issue=Issue{id=1324050876230415089, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='11', pageStart='1921', pageEnd='2112', issueExtLink='null', onlineDate='null', pubDate='1781020800000', pubDateStr='2026-06-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793607928569, creator='13701087609', updateTime=1793670049253, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324311429322507008, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324050876230415089, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324311429322507009, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324050876230415089, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2074, endPage=2080, ext={EN=ArticleExt(id=1324050991443751379, articleId=1324050991196287442, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Molecular transmission network analysis of newly reported HIV-1 cases in Qingbaijiang District, Chengdu, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the characteristics of the molecular transmission network among newly reported human immunodeficiency virus type 1 (HIV-1) cases in Qingbaijiang District of Chengdu from 2022 to 2024, and to provide guidance for local HIV/AIDS prevention and control.

Methods

A total of 283 anticoagulated blood samples and demographic information from newly reported HIV-1 cases in Qingbaijiang District from 2022 to 2024 were collected. The HIV-1 pol region gene sequences were amplified by reverse transcription polymerase chain reaction (PCR) and nested PCR, followed by sequencing. A molecular network was constructed based on a genetic distance threshold of 1.5%. The patterns of the molecular transmission network were analyzed, and binary logistic regression was used to analyze factors influencing entry into the network.

Results

A total of 277 valid sequences were obtained. Nine genetic subtypes were identified, with CRF07_BC (197 cases, 71.11%) and CRF01_AE (63 cases, 22.74%) being predominant. Under a genetic distance threshold of 1.5%, the network entry rate was 50.18% (139/277), forming 33 molecular clusters, with the number of cases in each cluster ranging from 2 to 16. Multivariable logistic regression analysis indicated that individuals aged ≥50 years (OR=44.138, 95% CI: 4.474-435.459), and those infected with CRF01_AE (OR=10.434, 95% CI: 1.981-54.966) or CRF07_BC (OR=10.371, 95% CI: 2.078-51.760) subtypes were more likely to be included in the network (P<0.05). High-risk infected individuals (degree ≥4) exhibited significant differences across various occupations, education levels, genetic subtypes, and current residences (P<0.05), and those residing in FH Town (OR=44.138, 95% CI: 4.474-435.459) had a significantly higher risk.

Conclusion

Among newly reported HIV-1 infections in Qingbaijiang District, the predominant genetic subtypes were CRF07_BC and CRF01_AE. Individuals infected with CRF01_AE or CRF07_BC subtypes and aged ≥50 years were more likely to enter the molecular transmission network. Certain townships showed a higher transmission risk among infected individuals. Therefore, it is recommended to establish a molecular transmission network for long-term surveillance in the region and implement targeted interventions in key towns/streets and among high-risk populations to curb the spread of the HIV/AIDS epidemic.

, authors=Zhan-zhi LIU1, Si-min ZHOU1, Wen-tao CHEN1, Shan-shan LI2, authorsList=Zhan-zhi LIU, Si-min ZHOU, Wen-tao CHEN, Shan-shan LI, authorCompany=null, correspAuthors=Zhan-zhi LIU, 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=1324050992194531798, articleId=1324050991196287442, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=成都市青白江区新报告HIV-1感染者分子传播网络特征分析, columnId=1228016573844226129, journalTitle=现代预防医学, columnName=疾病预防控制, runingTitle=null, highlight=null, articleAbstract=
目的

研究成都市青白江区2022—2024年新报告人类免疫缺陷病毒1型（human immunodeficiency virus type 1，HIV-1）感染者分子传播网络特征，为本地区艾滋病防控提供指导。

方法

收集青白江区2022—2024年283份新报告HIV-1感染者抗凝血样及人口学信息，通过反转录聚合酶链式反应（polymerase chain reaction，PCR）和巢氏PCR扩增HIV-1 pol基因区序列并测序，基于1.5%基因距离阈值构建分子网络，分析该地区的分子传播网络形态，使用二项logistic回归进行入网影响因素分析。

结果

共获取277条有效序列，发现9种基因亚型，以CRF07_BC 197例（71.11%）和CRF01_AE 63例（22.74%）为主。基因距离阈值在1.5%时，入网率为50.18%，形成33个分子簇，簇内病例数在2～16之间。多因素logistic回归显示，≥50岁（OR=44.138，95%CI：4.474～435.459）、CRF01_AE（OR=10.434，95%CI：1.981～54.966）和CRF07_BC（OR=10.371，95%CI：2.078～51.760）亚型的感染者更容易入网（P<0.05）。高风险感染者（度数≥4）在不同职业、文化程度、基因亚型和现住址具有显著性差异（P<0.05），现住址在FH镇（OR=44.138，95%CI：4.474～435.459）的感染者风险更高。

结论

青白江区新报告HIV-1感染者基因亚型以CRF07_BC和CRF01_AE为主，年龄≥50岁且亚型为CRF01_AE或CRF07_BC的感染者更容易进入分子传播网络，部分乡镇的感染者有较大传播风险。应构建分子传播网络对该地区进行长期监测，针对重点镇街和高风险人群，采取精准的干预措施遏制艾滋病疫情传播。

, authors=刘展志1, 周思敏1, 陈文涛1, 李姗珊2, authorsList=刘展志, 周思敏, 陈文涛, 李姗珊, authorCompany=null, correspAuthors=刘展志, authorNote=

刘展志（1995—），男，本科，主管技师，研究方向：疾病预防控制工作

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刘展志，E-mail：
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注：A为 不同基因亚型分子网络；B为 不同性别分子网络；C为 不同接触方式分子网络；D为 不同地区分子网络；圆点大小代表链接边数量。

, figureFileSmall=VpuHSStnrwV3uJV777xLXg==, figureFileBig=yldg+Gdf5v6uXyyDvLWzQQ==, tableContent=null), ArticleFig(id=1324050999933022713, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324050991196287442, language=EN, label=Table1, caption=

Analysis of the molecular networks and risk factors for newly reported HIV-1 cases in Qingbaijiang District from 2022 to 2024

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人数入网人数单因素分析多因素分析
（构成比/%）（占比/%）χ2值P值aOR(95%CI)P值
性别0.0310.860
男216(77.98)109(50.46)
女61(22.02)30(49.18)
年龄（岁）10.2260.001
<5082(29.60)29(35.37)1.000
≥50195(70.40)110(56.41)1.997(1.047～3.810)0.036
民族3.0550.080
汉族274(98.92)139(50.73)
少数民族3(1.08)0(0.00)
职业4.4190.036
农民142(51.26)80(56.34)1.000
其他135(48.74)59(43.70)1.199(0.639～2.251)0.571
婚姻状况1.4240.491
未婚38(13.72)16(42.10)
已婚136(49.10)72(52.94)
离异或丧偶103(37.18)51(49.51)
文化程度11.4150.003
中专/高中及以上34(12.27)10(29.41)1.000
初中79(28.52)34(43.04)1.524(0.572～4.062)0.399
小学及以下164(59.21)95(57.93)1.810(0.658～4.977)0.250
感染途径4.6790.031
异性性传播269(97.11)138(51.30)1.000
同性性传播8(2.89)1(12.50)0.267(0.029～2.502)0.248
基因亚型10.6950.005
CRF01_AE63(22.74)33(52.38)10.434(1.981～54.966)0.006
CRF07_BC197(71.12)104(52.79)10.371(2.078～51.760)0.004
其他亚型17(6.14)2(11.76)1.000
现住址22.6940.002
DW街道72(25.99)34(47.22)1.000
DT街道22(7.94)12(54.55)1.709(0.592～4.930)0.321
CX镇19(6.86)9(47.37)0.795(0.275～2.295)0.672
MM镇12(4.33)8(66.67)1.855(0.483～7.118)0.368
YD镇32(11.56)22(68.75)2.652(0.889～7.908)0.080
QQ镇33(11.91)20(60.61)1.633(0.596～4.476)0.340
FH镇30(10.83)19(63.33)1.612(0.586～4.433)0.355
区外57(20.58)15(26.32)0.399(0.178～0.896)0.026
), ArticleFig(id=1324051000042074618, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324050991196287442, language=CN, label=表1, caption=

青白江区2022—2024年新报告HIV-1感染者分子传播网络入网影响因素分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人数入网人数单因素分析多因素分析
（构成比/%）（占比/%）χ2值P值aOR(95%CI)P值
性别0.0310.860
男216(77.98)109(50.46)
女61(22.02)30(49.18)
年龄（岁）10.2260.001
<5082(29.60)29(35.37)1.000
≥50195(70.40)110(56.41)1.997(1.047～3.810)0.036
民族3.0550.080
汉族274(98.92)139(50.73)
少数民族3(1.08)0(0.00)
职业4.4190.036
农民142(51.26)80(56.34)1.000
其他135(48.74)59(43.70)1.199(0.639～2.251)0.571
婚姻状况1.4240.491
未婚38(13.72)16(42.10)
已婚136(49.10)72(52.94)
离异或丧偶103(37.18)51(49.51)
文化程度11.4150.003
中专/高中及以上34(12.27)10(29.41)1.000
初中79(28.52)34(43.04)1.524(0.572～4.062)0.399
小学及以下164(59.21)95(57.93)1.810(0.658～4.977)0.250
感染途径4.6790.031
异性性传播269(97.11)138(51.30)1.000
同性性传播8(2.89)1(12.50)0.267(0.029～2.502)0.248
基因亚型10.6950.005
CRF01_AE63(22.74)33(52.38)10.434(1.981～54.966)0.006
CRF07_BC197(71.12)104(52.79)10.371(2.078～51.760)0.004
其他亚型17(6.14)2(11.76)1.000
现住址22.6940.002
DW街道72(25.99)34(47.22)1.000
DT街道22(7.94)12(54.55)1.709(0.592～4.930)0.321
CX镇19(6.86)9(47.37)0.795(0.275～2.295)0.672
MM镇12(4.33)8(66.67)1.855(0.483～7.118)0.368
YD镇32(11.56)22(68.75)2.652(0.889～7.908)0.080
QQ镇33(11.91)20(60.61)1.633(0.596～4.476)0.340
FH镇30(10.83)19(63.33)1.612(0.586～4.433)0.355
区外57(20.58)15(26.32)0.399(0.178～0.896)0.026
), ArticleFig(id=1324051000134349307, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324050991196287442, language=EN, label=Table 2, caption=

Characteristics of molecular clusters (≥10 cases) in Qingbaijiang District ［n（%）］

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变量总计（n=39）C1(n=16)C2(n=13)C3(n=10)
性别
男32(82.05)14(87.50)9(69.23)9(90.00)
女7(17.95)2(12.50)4(30.77)1(10.00)
年龄（岁）
<506(15.38)2(12.50)4(30.77)0(0.00)
≥5033(84.62)14(87.50)9(69.23)10(100.00)
职业
农民27(69.23)10(62.50)9(69.23)8(80.00)
其他12(30.77)6(37.50)4(30.77)2(20.00)
婚姻状况
未婚8(20.51)1(6.25)2(15.38)5(50.00)
已婚22(56.41)13(81.25)6(46.16)3(30.00)
离异或丧偶9(23.08)2(12.50)5(38.46)2(20.00)
文化程度
初中6(15.38)1(6.25)4(30.77)1(10.00)
小学及以下33(84.62)15(93.75)9(69.23)9(90.00)
感染途径
异性性传播39(100.00)16(100.00)13(100.00)10(100.00)
基因亚型
CRF01_AE10(25.64)0(0.00)0(0.00)10(100.00)
CRF07_BC29(74.36)16(100.00)13(100.00)0(0.00)
现住址
DW街道1(2.56)0(0.00)1(7.69)0(0.00)
DT街道2(5.13)0(0.00)1(7.69)1(10.00)
CX镇1(2.56)0(0.00)0(0.00)1(10.00)
MM镇3(7.69)0(0.00)3(23.08)0(0.00)
YD镇9(23.08)1(6.25)3(23.08)5(50.00)
QQ镇7(17.95)6(37.50)0(0.00)1(10.00)
FH镇14(35.90)7(43.75)5(38.46)2(20.00)
区外2(5.13)2(12.50)0(0.00)0(0.00)
), ArticleFig(id=1324051000235012604, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324050991196287442, language=CN, label=表2, caption=

青白江区10例及以上病例的分子簇特征分布［n（%）］

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变量总计（n=39）C1(n=16)C2(n=13)C3(n=10)
性别
男32(82.05)14(87.50)9(69.23)9(90.00)
女7(17.95)2(12.50)4(30.77)1(10.00)
年龄（岁）
<506(15.38)2(12.50)4(30.77)0(0.00)
≥5033(84.62)14(87.50)9(69.23)10(100.00)
职业
农民27(69.23)10(62.50)9(69.23)8(80.00)
其他12(30.77)6(37.50)4(30.77)2(20.00)
婚姻状况
未婚8(20.51)1(6.25)2(15.38)5(50.00)
已婚22(56.41)13(81.25)6(46.16)3(30.00)
离异或丧偶9(23.08)2(12.50)5(38.46)2(20.00)
文化程度
初中6(15.38)1(6.25)4(30.77)1(10.00)
小学及以下33(84.62)15(93.75)9(69.23)9(90.00)
感染途径
异性性传播39(100.00)16(100.00)13(100.00)10(100.00)
基因亚型
CRF01_AE10(25.64)0(0.00)0(0.00)10(100.00)
CRF07_BC29(74.36)16(100.00)13(100.00)0(0.00)
现住址
DW街道1(2.56)0(0.00)1(7.69)0(0.00)
DT街道2(5.13)0(0.00)1(7.69)1(10.00)
CX镇1(2.56)0(0.00)0(0.00)1(10.00)
MM镇3(7.69)0(0.00)3(23.08)0(0.00)
YD镇9(23.08)1(6.25)3(23.08)5(50.00)
QQ镇7(17.95)6(37.50)0(0.00)1(10.00)
FH镇14(35.90)7(43.75)5(38.46)2(20.00)
区外2(5.13)2(12.50)0(0.00)0(0.00)
), ArticleFig(id=1324051000318898685, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324050991196287442, language=EN, label=Table 3, caption=

Distribution of newly reported HIV-1 cases with a network degree ≥4 in Qingbaijiang District, 2022—2024

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变量入网人数
(n=139)		度数≥4人数单因素分析多因素分析
占比（%）χ2值P值aOR(95%CI)P值
性别0.0500.824
男10952(47.71)
女3015(50.00)
年龄（岁）2.7620.097
<502910(34.48)
≥5011057(51.82)
职业6.5270.011
农民8046(57.50)1.000
其他5921(35.59)0.738(0.262～2.076)0.565
婚姻状况5.4460.066
未婚1611(68.75)
已婚7237(51.38)
离异或丧偶5119(37.25)
文化程度9.4470.009
中专/高中及以上102(20.00)1.000
初中3411(32.35)1.007(0.151～6.714)0.994
小学及以下9554(56.84)2.110(0.358～12.439)0.409
感染途径0.9370.333
异性性传播13867(48.55)
同性性传播10(0.00)
接触方式
配偶或固定性伴阳性138(61.54)4.2530.235
男男性行为10(0.00)
非婚商业异性性行为8745(51.72)
非婚非商业异性性行为3814(36.84)
基因亚型10.0360.007
CRF01_AE339(27.27)
CRF07_BC10458(55.77)
其他亚型20(0.00)
现住址31.814<0.001
DW街道347(20.59)1.000
DT街道123(25.00)1.514(0.272～8.432)0.636
CX镇94(44.44)3.559(0.622～20.350)0.154
MM镇84(50.00)2.818(0.459～17.309)0.263
YD镇2211(50.00)3.498(0.782～15.641)0.101
QQ镇2013(65.00)3.794(0.870～16.545)0.076
FH镇1918(94.74)44.138(4.474～435.459)0.001
区外157(46.67)2.560(0.635～10.330)0.187
), ArticleFig(id=1324051000419561982, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324050991196287442, language=CN, label=表3, caption=

2022—2024年青白江区新报告HIV-1感染者节点度数≥4的病例分布

, figureFileSmall=null, figureFileBig=null, tableContent=
变量入网人数
(n=139)		度数≥4人数单因素分析多因素分析
占比（%）χ2值P值aOR(95%CI)P值
性别0.0500.824
男10952(47.71)
女3015(50.00)
年龄（岁）2.7620.097
<502910(34.48)
≥5011057(51.82)
职业6.5270.011
农民8046(57.50)1.000
其他5921(35.59)0.738(0.262～2.076)0.565
婚姻状况5.4460.066
未婚1611(68.75)
已婚7237(51.38)
离异或丧偶5119(37.25)
文化程度9.4470.009
中专/高中及以上102(20.00)1.000
初中3411(32.35)1.007(0.151～6.714)0.994
小学及以下9554(56.84)2.110(0.358～12.439)0.409
感染途径0.9370.333
异性性传播13867(48.55)
同性性传播10(0.00)
接触方式
配偶或固定性伴阳性138(61.54)4.2530.235
男男性行为10(0.00)
非婚商业异性性行为8745(51.72)
非婚非商业异性性行为3814(36.84)
基因亚型10.0360.007
CRF01_AE339(27.27)
CRF07_BC10458(55.77)
其他亚型20(0.00)
现住址31.814<0.001
DW街道347(20.59)1.000
DT街道123(25.00)1.514(0.272～8.432)0.636
CX镇94(44.44)3.559(0.622～20.350)0.154
MM镇84(50.00)2.818(0.459～17.309)0.263
YD镇2211(50.00)3.498(0.782～15.641)0.101
QQ镇2013(65.00)3.794(0.870～16.545)0.076
FH镇1918(94.74)44.138(4.474～435.459)0.001
区外157(46.67)2.560(0.635～10.330)0.187
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成都市青白江区新报告HIV-1感染者分子传播网络特征分析
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刘展志 1 , 周思敏 1 , 陈文涛 1 , 李姗珊 2
现代预防医学 | 疾病预防控制 2026,53(11): 2074-2080
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现代预防医学 |疾病预防控制 2026 , 53 (11) : 2074 -2080
成都市青白江区新报告HIV-1感染者分子传播网络特征分析
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刘展志1 , 周思敏1, 陈文涛1, 李姗珊2
作者信息
  • 1.成都市青白江区疾病预防控制中心，四川 成都 610300
  • 2.成都市疾病预防控制中心
通讯作者:
刘展志，E-mail：
作者简介:

刘展志（1995—），男，本科，主管技师，研究方向：疾病预防控制工作

Molecular transmission network analysis of newly reported HIV-1 cases in Qingbaijiang District, Chengdu
Zhan-zhi LIU1 , Si-min ZHOU1, Wen-tao CHEN1, Shan-shan LI2
Affiliations
  • Qingbaijiang District Center for Disease Control and Prevention, Chengdu, Sichuan 610300, China
出版时间: 2026-06-10 doi: 10.20043/j.cnki.MPM.202601190
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摘要
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目的

研究成都市青白江区2022—2024年新报告人类免疫缺陷病毒1型（human immunodeficiency virus type 1，HIV-1）感染者分子传播网络特征，为本地区艾滋病防控提供指导。

方法

收集青白江区2022—2024年283份新报告HIV-1感染者抗凝血样及人口学信息，通过反转录聚合酶链式反应（polymerase chain reaction，PCR）和巢氏PCR扩增HIV-1 pol基因区序列并测序，基于1.5%基因距离阈值构建分子网络，分析该地区的分子传播网络形态，使用二项logistic回归进行入网影响因素分析。

结果

共获取277条有效序列，发现9种基因亚型，以CRF07_BC 197例（71.11%）和CRF01_AE 63例（22.74%）为主。基因距离阈值在1.5%时，入网率为50.18%，形成33个分子簇，簇内病例数在2～16之间。多因素logistic回归显示，≥50岁（OR=44.138，95%CI：4.474～435.459）、CRF01_AE（OR=10.434，95%CI：1.981～54.966）和CRF07_BC（OR=10.371，95%CI：2.078～51.760）亚型的感染者更容易入网（P<0.05）。高风险感染者（度数≥4）在不同职业、文化程度、基因亚型和现住址具有显著性差异（P<0.05），现住址在FH镇（OR=44.138，95%CI：4.474～435.459）的感染者风险更高。

结论

青白江区新报告HIV-1感染者基因亚型以CRF07_BC和CRF01_AE为主，年龄≥50岁且亚型为CRF01_AE或CRF07_BC的感染者更容易进入分子传播网络，部分乡镇的感染者有较大传播风险。应构建分子传播网络对该地区进行长期监测，针对重点镇街和高风险人群，采取精准的干预措施遏制艾滋病疫情传播。

分子传播网络  /  HIV-1  /  分子簇
Objective

To investigate the characteristics of the molecular transmission network among newly reported human immunodeficiency virus type 1 (HIV-1) cases in Qingbaijiang District of Chengdu from 2022 to 2024, and to provide guidance for local HIV/AIDS prevention and control.

Methods

A total of 283 anticoagulated blood samples and demographic information from newly reported HIV-1 cases in Qingbaijiang District from 2022 to 2024 were collected. The HIV-1 pol region gene sequences were amplified by reverse transcription polymerase chain reaction (PCR) and nested PCR, followed by sequencing. A molecular network was constructed based on a genetic distance threshold of 1.5%. The patterns of the molecular transmission network were analyzed, and binary logistic regression was used to analyze factors influencing entry into the network.

Results

A total of 277 valid sequences were obtained. Nine genetic subtypes were identified, with CRF07_BC (197 cases, 71.11%) and CRF01_AE (63 cases, 22.74%) being predominant. Under a genetic distance threshold of 1.5%, the network entry rate was 50.18% (139/277), forming 33 molecular clusters, with the number of cases in each cluster ranging from 2 to 16. Multivariable logistic regression analysis indicated that individuals aged ≥50 years (OR=44.138, 95% CI: 4.474-435.459), and those infected with CRF01_AE (OR=10.434, 95% CI: 1.981-54.966) or CRF07_BC (OR=10.371, 95% CI: 2.078-51.760) subtypes were more likely to be included in the network (P<0.05). High-risk infected individuals (degree ≥4) exhibited significant differences across various occupations, education levels, genetic subtypes, and current residences (P<0.05), and those residing in FH Town (OR=44.138, 95% CI: 4.474-435.459) had a significantly higher risk.

Conclusion

Among newly reported HIV-1 infections in Qingbaijiang District, the predominant genetic subtypes were CRF07_BC and CRF01_AE. Individuals infected with CRF01_AE or CRF07_BC subtypes and aged ≥50 years were more likely to enter the molecular transmission network. Certain townships showed a higher transmission risk among infected individuals. Therefore, it is recommended to establish a molecular transmission network for long-term surveillance in the region and implement targeted interventions in key towns/streets and among high-risk populations to curb the spread of the HIV/AIDS epidemic.

Molecular transmission network  /  HIV-1  /  Molecular cluster
刘展志, 周思敏, 陈文涛, 李姗珊. 成都市青白江区新报告HIV-1感染者分子传播网络特征分析. 现代预防医学, 2026 , 53 (11) : 2074 -2080 . DOI: 10.20043/j.cnki.MPM.202601190
Zhan-zhi LIU, Si-min ZHOU, Wen-tao CHEN, Shan-shan LI. Molecular transmission network analysis of newly reported HIV-1 cases in Qingbaijiang District, Chengdu[J]. Modern Preventive Medicine, 2026 , 53 (11) : 2074 -2080 . DOI: 10.20043/j.cnki.MPM.202601190
正文
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目前，分子生物学技术在我国的发展和应用逐渐成熟，人类免疫缺陷病毒(human immunodeficiency virus，HIV）分子流行病学研究成为了解疫情特征、追踪传播路径和实施精准防控策略的关键技术手段。通过将HIV病毒基因测序数据与现场流行病学调查结果联合分析，可从分子水平构造病毒传播拓扑结构，揭示传播规律，显著提升识别高风险人群的能力，同时克服了社会歧视和伦理限制带来的溯源难题[1]。青白江区位于成都市东北部，与成都市金堂县、德阳市广汉市等四个区县接壤，以现代物流和工业制造为主导产业，人口流动频繁，导致该地区近年来获得性免疫缺陷综合征（简称艾滋病，acquired immunodeficiency syndrome，AIDS）感染者报告数逐年上升，给AIDS防控带来巨大挑战[2]。HIV分子传播网络研究已经广泛应用于全国各地区艾滋防治领域[3-5]，但目前尚未有对青白江区HIV分子传播网络的构建相关研究。本研究选取青白江区2022—2024年新报告且未开展抗病毒治疗的HIV-1感染者，通过基因序列分析，了解该地区流行毒株和分子网络传播结构特征，识别重点区域和高危人群，为支撑该地区AIDS防控策略的科学决策与精准实施提供依据。
1　对象与方法
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1.1　研究对象
选取成都市青白江区疾病预防控制中心HIV确证实验室2022年1月—2024年12月新报告且未接受抗病毒治疗的HIV-1感染者为研究对象。纳入标准：HIV补充试验为阳性者，未接受抗病毒治疗，获得研究对象知情同意。剔除既往感染者、不愿意配合相关调查病例，筛选出HIV-1感染者283例。人口学信息及感染相关数据均来自AIDS防治基本信息系统，包括社会人口学特征（性别、年龄、职业、婚姻状况、现住址、文化程度）及流行病学相关信息（感染途径、接触方式）。本研究获得成都市青白江区疾病预防控制中心伦理委员会批准（批准号：青疾控伦理202601号）。
1.2　研究方法
1.2.1　样本采集与保存
抗凝血样本来源于2022—2024年本机构HIV确证实验室首次开展补充试验留样，样品采集由青白江区各AIDS检测点、筛查实验室完成，严格按照《全国艾滋病检测技术规范（2020年修订版）》，采集5 ml EDTA抗凝全血，1 500～3 000 r/min离心15 min，将血浆置于聚丙烯冻存管中备用，分离后的血浆放置-80℃冰箱保存，定期送四川省疾病预防控制中心或成都市疾病预防控制中心开展测序。
1.2.2　核酸提取、目的片段扩增与测序
采用Roche公司生产的全自动病毒核酸提取仪及其配套试剂盒提取病毒核酸。采用反转录聚合酶链式反应（polymerase chain reaction,PCR）和巢氏PCR扩增方法，对HIV-1病毒pol区域基因序列进行扩增，核酸提取及扩增由四川省疾病预防控制中心或成都市疾病预防控制中心完成。将目的处出现条带的扩增产物送至北京博迈德基因有限公司、北京诺赛基因组研究中心有限公司和北京安普生化科技有限公司开展核酸纯化及基因测序。
1.2.3　序列整理和亚型确定
使用Sequencher 4.9软件对测序结果进行编辑、清理和拼接序列，使用Bioedit 软件对样本序列进行校正与HIV sequence database of the Los Alamos National Laboratories（LANL）参考序列进行比对分析，利用FastTree软件构建系统进化树，确定毒株具体基因亚型。
1.2.4　分子传播网络构建和分析
使用中国艾滋病病毒基因序列数据平台（https://nmdc.cn/hiv）：工具-HIV传播预测预警工具（HIV Trace法）（https://nmdc.cn/hiv/tool/earlywarning）TN93模型计算两条序列间基因距离阈值，在基因距离0.005～0.020内进行阈值敏感性分析，以成簇最高分辨率（最多分子网络数量）的基因距离阈值。根据《HIV传播网络监测和干预技术指南（2025修订版）》，分子簇是根据HIV基因序列遗传相似性将具有传播关系的HIV感染者进行关联所形成的网络拓扑学结构，分子传播网络中的每个节点代表一例感染者，节点数≥10的分子簇为具有高度传播风险的大分子簇，度数（degrees）表示每个节点所连接的边的数目，也称链接数，通常度数越高，表明节点潜在连接关系越多，传播风险越高，度数≥4的应予以重点关注[6]。
1.3　统计分析
采用WPS 2019进行数据预处理，并以SPSS 27.0为平台对整理后的数据进行统计分析。计数资料采用例数和构成比描述，单因素分析采用χ2检验，单因素分析中P<0.05的变量纳入二项logistic回归模型分析，检验水准α=0.05。
2　结果
收起
2.1　基本特征
成功获取目标人群序列277条，共检出9种基因亚型，其中CRF07_BC 197例（71.12%）、CRF01_AE 63例（22.74%）、CRF08_BC 8例（2.90%）、CRF55_01B 2例（0.72%）、CRF85_BC 2例（0.72%）、CRF109_0107 1例（0.36%）、CRF59_01B 1例（0.36%）、CRF64_BC 1例（0.36%）、B 1例（0.36%）、独特重组型（unique recombinant form, URF）1例（0.36%）。277例感染者以男性、≥50岁、汉族、农民、已婚、小学及以下文化程度、异性性传播为主，分别占77.98%、70.40%、98.92%、51.26%、49.10%、59.21%、97.11%；现住址以DW街道为主，占25.99%。
2.2　分子传播网络特征
在1.5%的基因距离阈值下，分子簇总数达到峰值，此时共有139条序列进入分子传播网络中，入网率为50.18%，形成33个分子簇，包含139个节点和340条边，簇内病例数介于2～16之间。其中分子簇C1、C2和C3分别包含16、13和10个节点，是网络中最大的三个分子簇。3种基因亚型进入分子网络，CRF07_BC亚型形成簇最多，共形成23个簇，入网率为53.33%；其次是CRF01_AE亚型，共形成9个簇，入网率为52.38%；而CRF85_BC亚型共形成1个簇，入网率为100%。见图1A。入网感染者以男性、≥50岁异性性传播、小学及以下文化程度、农民、已婚为主，分别占78.42%、79.14%、99.28%、68.35%、57.55%、51.80%。见图1B、C和表1。各簇主要分布于DW街道，占66.67%；其中分子簇C1以FH镇和QQ镇为主，分别占43.75%、37.5%，C2以FH镇为主，占38.46%，C3以YD镇为主，占50%。见图1D。
2.3　入网危险因素分析
单因素分析显示，感染者的入网率在不同年龄、文化程度、职业、基因亚型、感染途径及现住址间存在显著差异（P<0.05）；而性别、民族及婚姻状况的影响无统计学意义（P<0.05）。采用二项logistic回归模型分析显示：年龄、基因亚型和现住址对感染者入网有影响，相比于<50岁，≥50岁（OR=1.997,95%CI：1.047～3.810）的感染者更容易进入网络；相比其他亚型，CRF01_AE（OR=10.434,95%CI:1.981～54.966）和CRF07_BC（OR=10.371,95%CI:2.078～51.760）亚型的感染者更容易进入网络；相比DW街道，青白江区外（OR=0.399,95%CI：0.178～0.896）的感染者更不容易进入网络。见表1。
2.4　重点分子簇分析
网络中大分子簇（节点≥10）有3个，包括C1、C2和C3分子簇，分别包含16、13和10例感染者，占全部入网病例数的28.06%。分子簇C1和C2由CRF07_BC亚型构成，C3由CRF01_AE亚型构成。分子簇C1、C2和C3包含的39例感染者均为异性性传播，文化程度全部为初中及以下。分子簇C1中男性和≥50岁病例均占87.5%，农民占62.50%，现住址主要是FH镇（43.75%）和QQ镇（37.50%）。还有2例感染者现住址为区外，来自与FH镇和QQ镇接壤的JT县，女性占比50%，有商业性行为服务史。分子簇C2中男性、≥50岁、农民均占69.23%，现住址均为本区内，包含FH镇（38.46%）、YD镇（23.08%）和MM镇（23.08%）在内的5个街道/乡镇。分子簇C3中男性占90%，农民占80%，均为本区内的男性病例，包含YD镇（50.00%）、FH镇（20.00%）在内的5个街道/乡镇。见表2。同时还发现分子簇21存在男男性行为感染者与异性性传播的男性感染者相连情况。见图1C。
2.5　传播风险分析
入网的感染者中共有67例度数≥4，占比48.2%，全部为异性性传播，主要分布于FH镇（26.87%）、QQ镇（19.40%）和YD镇（16.42%），67例病例中男性占77.61%，非婚商业性行为占67.16%，包括44例男性和1例女性，男性传播途径为非婚商业性行为占84.62%；女性15例，44.67%的女性为配偶或固定性伴阳性。单因素分析结果显示：不同职业、文化程度、基因亚型和现住址的感染者度数≥4差异具有统计学意义（P<0.05）；采用二项logistic回归模型分析，现住址对度数≥4风险有影响；相比DW街道，FH镇（OR=44.138,95%CI:4.474～435.459）的感染者度数≥4风险更高。见表3。
3　讨论
收起
本研究主要分析了成都市青白江区2022—2024年277例新报告HIV-1感染者的分子网络传播流行情况，共发现9种基因亚型，以CRF07_BC和CRF01_AE亚型为主，与国内部分地区[7-8]的HIV-1基因亚型流行情况相似。有研究表明，CRF07_BC亚型毒株具有较强的传播能力，已经超越CRF01_AE亚型成为我国感染人数最多的毒株[9]，且在跨地区传播中占比很高，分子网络中节点连接复杂[10]。
研究发现年龄、基因亚型和现住址是入网的影响因素，≥50岁感染者更容易入网，这与四川省既往其他研究相同[11]。入网的感染者主要是文化程度低、年龄≥50的男性病例，以异性性传播为主。提示在年龄≥50的人群中，部分人可能仍处于性活跃度高阶段，且存在非婚商业异性性行为，同时由于文化程度较低，缺乏对AIDS的正确认识，性行为自我保护的意识不强，不愿意或很少使用安全套，从而导致AIDS感染风险增加。
分子传播网络显示，青白江区整体入网率为50.18%。该区两个乡镇与周边一县构成最大分子簇（C1），该分子簇包含一名来自该县的女性商业性行为从业者。提示部分男性在面临性需求无法被满足的情况下，可能会在寻求商业性行为服务时为规避风险，通常会采取地理规避策略来选择性交易地点，从而导致了HIV跨区域或跨区县传播。针对该类人群应进一步加强筛查检测、行为干预和溯源分析等精准干预措施，以有效遏制艾滋病传播。研究还发现分子簇21存在男男性行为感染者与异性性传播的男性感染者相连情况，这可能是感染者在调查时未准确告知其接触方式，双性性行为男性更具有隐瞒性从而导致传播链条更为复杂[12]，提示在日常防控工作中应重视双性性行为感染者在传播链中的重要角色。
传播风险分析显示，现住址是度数≥4风险的影响因素，FH镇的病例可能存在较高传播风险。还发现女性病例接触方式以配偶或固定性别阳性为主，与重庆渝北[13]研究结果相似，此发现指向配偶阳性是处于“固定关系”中的女性感染的重要因素之一，提示要做好单阳家庭宣传教育，推广“配偶阳性检测”服务和完善阳性告知支持体系，以保护固定性伴关系中的女性免受艾滋病侵害。
综上所述，2022—2024年青白江区新报告HIV-1感染者基因型以CRF07_BC和CRF01_AE亚型为主，不同的年龄、基因亚型和现住址是入网的影响因素，青白江区内部分乡镇的感染者有较大传播风险，且存在跨区县传播，提示下一步应利用分子传播网络的结果，针对流行的重点区域和重点人群提出精准的干预措施，以遏制疫情的蔓延。
基金
收起
  • 成都市科技局技术创新研发项目
  • 成渝地区MSM艾滋病病毒基因亚型多态性及关联性研究(2024-YF05-00828-SN)
文献
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参考文献 引证文献
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2026年第53卷第11期
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doi: 10.20043/j.cnki.MPM.202601190
  • 接收时间：2026-01-13
  • 首发时间：2026-11-02
  • 出版时间：2026-06-10
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  • 收稿日期：2026-01-13
基金
成都市科技局技术创新研发项目
成渝地区MSM艾滋病病毒基因亚型多态性及关联性研究(2024-YF05-00828-SN)
作者信息
    1.成都市青白江区疾病预防控制中心，四川 成都 610300
    2.成都市疾病预防控制中心

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2种不同金属材料的力学参数
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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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