{"paper_id":"1006c143-dfc1-4f78-bafa-4f90a7ae4aae","body_text":"Genetic Diversity, Drug Resistance, and Molecular Transmission Networks of HIV-1 in Zunyi: Implications for Precision Prevention | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic Diversity, Drug Resistance, and Molecular Transmission Networks of HIV-1 in Zunyi: Implications for Precision Prevention Yinyin Wang, Yunli Ma, Miao He, Yonghu Wan, Yuxia Liu, Lu Ma, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8526252/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Background HIV-1 genetic diversity and the spread of pretreatment drug resistance (PDR) complicate epidemic control. Southwestern China has a heterogeneous HIV epidemic, but molecular transmission dynamics in many prefecture-level settings remain poorly described. Methods We analyzed HIV-1 pol sequences from 208 newly diagnosed individuals in Zunyi, Guizhou Province. Genotypes were assigned by reference-based phylogenetic analysis; PDR was interpreted using the Stanford HIV Drug Resistance Database. Molecular transmission networks were inferred from pairwise genetic distances calculated with the TN93 model, and factors associated with PDR and clustering were evaluated using logistic regression. Results CRF07_BC (56.3%) and CRF01_AE (29.3%) were the predominant genotypes. PDR was detected in 21.2% of participants and varied significantly across genotypes, with higher prevalence observed in CRF08_BC and other recombinant forms. Molecular network analysis identified 31 transmission clusters involving 36.1% of sequences, with cluster sizes ranging from 2 to 6 nodes. Most clusters were small, and both densely connected subgraphs and simple linear chains were observed, indicating heterogeneous transmission patterns. Clustered cases were largely heterosexual and included a high proportion of individuals aged ≥ 50 years. CRF07_BC formed more tightly connected clusters, whereas CRF01_AE exhibited greater structural diversity. Multivariate analysis showed that divorced or widowed individuals were less likely to be included in transmission clusters. Conclusions The HIV epidemic in Zunyi is characterized by high genetic diversity, fragmented molecular transmission networks, and genotype-specific clustering patterns. Integrating molecular network analysis with routine drug resistance surveillance can improve understanding of local transmission dynamics and support precision HIV prevention strategies in southwestern China. HIV-1 molecular transmission network pol gene pretreatment drug resistance phylogenetic analysis China Figures Figure 1 Figure 2 Background Human immunodeficiency virus (HIV) is a retrovirus characterized by exceptionally high genetic variability. This diversity is largely driven by the low fidelity and lack of proofreading capacity of reverse transcriptase, which enables rapid mutation and frequent recombination during viral replication. Since the first AIDS case was reported in China in 1987, the number of people living with HIV/AIDS has continued to rise[ 1 ]. By the end of 2023, approximately 39.9 million people were living with HIV worldwide, reflecting both the expanding scale of infection and the increasing complexity of circulating viral variants[ 2 ]. Globally, HIV-1 group M remains the predominant cause of the epidemic and encompasses multiple subtypes and circulating recombinant forms (CRFs), many of which exhibit clear geographic clustering. In East Asia, the proportion of CRF infections exceeds 80%, underscoring both the persistent recombination pressure and the dynamic evolution of regional epidemics[ 3 ]. The widespread implementation of antiretroviral therapy (ART) has markedly reduced viral replication and improved patient prognosis, yet the emergence and onward transmission of drug-resistant HIV-1 strains have become a growing public health concern[ 4 ]. At the same time, rapid population movement and the proliferation of online social platforms have expanded the reach of HIV transmission, making transmission patterns increasingly concealed and complex[ 5 ]. Novel recombinant strains continue to emerge, and traditional epidemiological investigations—which depend heavily on self-reported behavioral histories—face inherent limitations in accurately reconstructing transmission pathways[ 6 , 7 ]. Advances in molecular biology and bioinformatics have facilitated the development of HIV-1 molecular transmission network analysis, a powerful tool for precision HIV prevention[ 6 ]. By comparing pol-gene sequences and estimating pairwise genetic distances, molecular networks can infer potential transmission linkages, identify active transmission clusters, and detect high-risk transmitters who may be driving local spread[ 9 ]. Studies conducted in Sichuan, Shenzhen, Ningxia, and other regions of China have demonstrated that this approach can effectively reveal geographic patterns of viral flow[ 10 – 12 ], subtype-specific clustering characteristics, and the role of key populations in sustaining transmission. Southwestern China remains one of the regions most heavily affected by HIV, and Guizhou Province represents a particularly complex epidemic setting characterized by substantial viral diversity, frequent recombination, and heterogeneous transmission modes. Zunyi, a major city in northern Guizhou and an important regional transportation hub, exhibits considerable population mobility and continues to report a high burden of new HIV infections. Despite this, systematic investigations of HIV-1 genotype distribution and molecular transmission network structure in Zunyi are scarce, limiting current understanding of local transmission dynamics. Therefore, we characterized HIV-1 genotypes and constructed a molecular transmission network based on pol sequences from newly diagnosed cases in Zunyi. We further examined demographic and epidemiological factors associated with pretreatment drug resistance and network clustering to inform precision prevention efforts in Guizhou Province. Methods Sample Collection and Processing Whole blood samples were obtained from newly reported HIV/AIDS patients at the time of confirmatory diagnosis. Samples were centrifuged at 3,000 r/min for 15 minutes at 4°C, and plasma was separated and stored at − 80°C until further analysis. Viral RNA was extracted using the MagMAX™ Viral RNA Isolation Kit (Thermo Fisher Scientific) on the automated nucleic acid workstation PAN9600S, following the manufacturer’s instructions. The HIV-1 pol gene region was amplified via RT-PCR for subsequent sequencing analysis.Amplified HIV segements were sent to sequence determination by 3730xl (Abi).The study protocol was approved by the Ethics Committee of Guizhou Center for Disease Control and Prevention (No. W2022-08). The study was conducted in accordance with the 1964 «Helsinki Declaration». Genotype and phylogenetic analysis We used MEGA 7.0 ( http://www.megasoftware.net ) to align the sequences and build the phylogenetic tree using the neighbor-joining method under Kimura's two parameter correction (1000 replicates). The HIV reference sequence were obtained from the Los Alamos database ( http://www.hiv.anl.gov ) as the following (Genbank Accession Number): CRF07BC: AF503396, JF906666, HQ215583, AF286226, HG421616, J0901027, EF122515; CRF01AE: GU564223, JX112798, AY008714, U51189, JF906597; CRF08BC: AF286229, AY008717; Subtype B: K03455, U71182, AY173951,AY33195; CRF5501B: X574662,X574663, JX574661, KF857447. Drug Resistance Analysis Assembled pol sequences were uploaded to the Stanford University HIV Drug Resistance Database ( https://hivdb.stanford.edu ) to identify drug-resistance–associated mutations, resistance profiles, and inferred levels of susceptibility to antiretroviral drugs. Genetic Distance Calculation and Molecular Network Construction Pairwise genetic distances among all pol sequences were calculated using the Tamura–Nei 93 (TN93) model by HyPhy2.2.4 software[ 13 ]. Molecular transmission networks were constructed in Cytoscape version 3.9.1. Genetic distance thresholds from 0.1% to 1.5% were evaluated sequentially[ 14 ], The optimal threshold of 1.0% was selected because it yielded the maximum number of clusters while minimizing artificial cluster inflation. Statistical Analysis All statistical analyses were performed using SPSS software version 26.0. Categorical variables were expressed as frequencies and percentages. The χ² test or Fisher’s exact test was used to compare proportions between groups. Variables with P < 0.10 in univariate logistic regression analysis were included in multivariate logistic regression models to identify independent factors associated with PDR and molecular network clustering. A two-sided P < 0.05 was considered statistically significant. Results Baseline characteristics of participants A total of 208 individuals with successfully amplified pol sequences were included in the analysis.Among them, 153 (73.6%) were male, and 121 (58.2%) were aged ≥ 50 years. Most participants reported heterosexual transmission (167, 80.3%), while 41 (19.7%) reported homosexual transmission. Regarding marital status, 100(48.1%) were married and 65(31.2%) were divorced or widowed. Demographic and clinical characteristics stratified by genotype are presented in Table 1 . Phylogenetic analysis of HIV-1 pol sequences Phylogenetic analysis of the 208 HIV-1 pol gene sequences revealed clear clustering corresponding to major circulating genotypes (Fig. 1 ). Four major genotype categories among the 208 sequences: CRF07_BC (117, 56.3%), CRF01_AE (61, 29.3%), CRF08_BC (15, 7.2%), and other recombinant forms (15, 7.2%). Among these, CRF07_BC and CRF01_AE formed the largest clades, indicating their predominance in the study population. CRF08_BC and subtype B were represented by smaller, well-defined clusters, while a limited number of sequences grouped into other recombinant or B-related lineages.The phylogenetic tree demonstrated strong genotype-specific aggregation, with minimal intermixing between major clades. Sequences classified as the same genotype clustered tightly together, supporting the reliability of genotype assignment. Overall structure of the molecular transmission network Using a 1.0% genetic distance threshold, molecular network analysis identified 31 transmission clusters among 208 HIV-1 sequences, with 75 sequences (36.1%) clustered and 133 (63.9%) remaining unclustered. Cluster sizes ranged from 2 to 6 nodes, with small clusters predominating. Both densely connected clusters including fully interconnected structures of 3–5 individuals and simple dyadic or linear chains were observed, indicating heterogeneous transmission patterns.Most clustered cases were male, predominantly aged above 50 years, and largely associated with heterosexual transmission, while homosexual transmission contributed only a small proportion. CRF07_BC and CRF01_AE were the major genotypes involved in clustering; CRF07_BC tended to form more tightly connected structures, whereas CRF01_AE exhibited greater network structural diversity. In contrast, CRF08_BC and other recombinant forms were involved in only a few small clusters(Fig. 2 ). Pretreatment drug resistance and Cluster characteristics by demographic factors Pretreatment drug resistance (PDR) was detected in 21.2% (44/208) of participants. The prevalence of PDR varied significantly across genotypes (χ²=28.76, P < 0.001), with the highest proportions observed in CRF08_BC (7/15, 46.7%) and other genotypes (10/15, 66.7%). The odds ratios (OR) for these genotypes were 6.34 (95% CI: 1.792–22.437) and 14.258 (95% CI: 3.727–54.544) times that of the reference group, respectively. In univariate analysis, genotype was strongly associated with PDR, and multivariate logistic regression confirmed its independent association. In univariate analysis, marital status, transmission route, age group, education level, and genotype were associated with cluster membership. Multivariate logistic regression indicated that divorced or widowed individuals were significantly less likely to be clustered (OR = 0.284, 95% CI: 0.134–0.600). Genotype was not statistically significant in the adjusted model, though CRF01_AE showed a trend toward higher clustering probability compared with CRF07_BC. (Table 2 ) Discussion In this study, we characterized the HIV-1 genotype distribution and molecular transmission network among newly reported HIV infections in Zunyi, Guizhou Province. By integrating phylogenetic analysis, drug resistance surveillance, and molecular network construction, our findings provide a comprehensive view of the local transmission dynamics in a region with high viral diversity and complex epidemic patterns. Consistent with reports from other provinces in China, CRF07_BC and CRF01_AE were the predominant genotypes, together accounting for more than 80% of all sequences[ 15 , 16 ]. The clear genotype-specific clustering observed in the phylogenetic tree supports the stability and ongoing circulation of these major lineages in the region. The relatively high proportion of CRF07_BC aligns with its known dominance among heterosexual transmission networks in western China[ 17 ], while the substantial presence of CRF01_AE reflects its continued expansion beyond traditionally defined risk groups. Molecular network analysis revealed that only approximately one-third of sequences were included in transmission clusters, suggesting that most infections were not linked to detectable recent transmission chains at the selected genetic distance threshold. This finding indicates a transmission pattern dominated by dispersed or sporadic spread, rather than large, rapidly expanding outbreaks. The predominance of small clusters and simple dyadic links further supports the notion of fragmented transmission networks in Zunyi, which may be influenced by population mobility, delayed diagnosis, and incomplete sampling of transmission partners. Notably, CRF07_BC and CRF01_AE contributed most to network clustering, yet their structural characteristics differed. CRF07_BC tended to form more tightly connected clusters, which may reflect relatively stable transmission networks or repeated transmission within closely linked social or sexual contacts. In contrast, CRF01_AE exhibited greater structural diversity, including both compact clusters and linear chains, suggesting more heterogeneous transmission pathways. These genotype-specific network patterns underscore the importance of considering viral lineage when interpreting molecular transmission dynamics. In univariate analysis, marital status, transmission route, age, education level, and genotype were associated with clustering. After adjustment, only marital status remained independently associated with clustering, suggesting confounding among correlated sociodemographic variables. Notably, individuals aged ≥ 50 years constituted a substantial proportion of clustered cases, but the age–clustering association was attenuated in multivariate analysis, indicating that older populations may represent an underrecognized prevention priority rather than an independent driver of clustering. In this region, heterosexual transmission constituted the majority of clustered cases, while homosexual transmission accounted for only a small proportion of clustered nodes. This may reflect differences in network structure, testing coverage, or partner turnover rates between the transmission routes in this area. Interestingly, individuals aged ≥ 50 years accounted for a substantial proportion of clustered cases (57/75, 76.0%), and age was associated with clustering in univariate analysis; however, this association was attenuated and no longer statistically significant after adjustment, suggesting confounding by correlated sociodemographic factors.But the growing importance of older populations in the local HIV transmission network—a group that may be underrecognized in prevention programs [ 18 , 19 ]. Pretreatment drug resistance was detected in over one-fifth of participants, with marked variation across genotypes. The particularly high prevalence of PDR among CRF08_BC and other recombinant forms, despite their limited clustering in the molecular network, suggests that drug resistance may circulate through pathways not captured by recent transmission clusters, such as historical transmission events or treatment-experienced sources[ 20 ]. This finding emphasizes the need for continued resistance surveillance alongside molecular network analysis[ 21 ]. Several limitations should be acknowledged. First, the cross-sectional design and incomplete sampling of transmission partners may have led to underestimation of clustering and network connectivity. Second, reliance on self-reported transmission routes may introduce misclassification bias. Third, the use of a single genetic distance threshold, while methodologically justified, cannot fully capture the dynamic nature of HIV transmission over time. From a public health perspective, the identification of small but active transmission clusters suggests that timely diagnosis and rapid linkage to care may effectively interrupt ongoing transmission. Older individuals and those involved in heterosexual transmission networks should be considered priority populations for targeted interventions. Conclusions Our study demonstrates that the HIV epidemic in Zunyi is characterized by high genetic diversity, fragmented molecular transmission networks, and genotype-specific clustering patterns. CRF07_BC and CRF01_AE remain central to local transmission, but differ in their network structures, while older age groups and heterosexual transmission play a substantial role in ongoing spread. These findings highlight the value of integrating molecular network analysis into routine HIV surveillance and support the development of targeted, precision prevention strategies tailored to local transmission dynamics in Guizhou Province. Abbreviations HIV Human Immunodeficiency Virus CRF circulating recombinant form PDR pretreatment drug resistance ART antiretroviral therapy Declarations Ethics approval and consent to participate The study protocol was approved by the Ethics Committee of Guizhou Center for Disease Control and Prevention (No. W2022-08). The study was conducted in accordance with the 1964 «Helsinki Declaration». All information about participants was reported to the CDC by doctors after obtaining informed consent from patients. Consent for publication Not applicable. Availability of data and materials Data can be requested from the corresponding author. Competing interests The authors declare no conflict of interest. Funding This research was funded by the following grants: 1. Science and Technology Fund Project of Guizhou Provincial Health Commission (Grant No. gzwkj2023-506). 2. Regional Innovation Cooperation Project of the Sichuan Science and Technology Program (Grant No. 2025YFHZ0296). Authors' contributions Xinhui Zhang,Yunli Ma and Yinyin Wang designed and conceived this research, and wrote the manuscript. Yonghu Wan, Yuxia Liu, Lu Ma, Yu Zhang, Min Zheng, and Zhi Yuan conducted the epidemiological investigation,sample collection,data collection and management and provided laboratory support. Zhan Gao and Miao He analyzed the data, and prepared the figures and tables. Acknowledgements We thank the health workers in Center for Disease Control and Prevention in Guiyang ,Zunyi and Honghuagang District for their hard work in carrying out the surveys and data collection. We would also like to thank the study participants for their involvement and voluntary cooperation in this study. Corresponding Authors Xinhui Zhang Guizhou Provincial Center for Disease Control and Prevention, Guiyang, China Email: [email protected] Zhan Gao Institute of Blood Transfusion, Chinese Academy of Medical Sciences, Chengdu, China Email: [email protected] References Yan Y, Wu S, Chen L, Yan P, Qiu Y, Xie M, et al. Shift in HIV/AIDS Epidemic in Southeastern China: A Longitudinal Study from 1987 to 2015. Int J Environ Res Public Health. 2016;13:794. https://doi.org/10.3390/ijerph13080794 . Global HIV. & AIDS statistics. Fact sheet. 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Tables Table 1 Demographic and clinical characteristics of participants stratified by HIV-1 genotype Characteristic Total (n = 208) CRF07_BC (n = 117) CRF01_AE (n = 61) CRF08_BC (n = 15) Other (n = 15) χ 2 P Gender 4.226 0.238 Male 153(73.6) 90(76.9) 39(63.9) 12(80) 12(80) Female 55(26.4) 27(23.1) 22(36.1) 3(20) 3(20) Marital Status 12.204 0.058 Married 100(48.1) 52(44.4) 35(57.4) 8(53.3) 6(40) Divorced or Widowed 65(31.2) 34(29.1) 20(32.8) 7(46.7) 6(40) Single 43(20.7) 31(26.5) 6(9.8) 0 3(20) Transmission Route 20.333 0.000 Heterosexual transmission 167(80.3) 85(72.6) 58(95.1) 15(100) 9(60) Homosexual transmission 41(19.7) 32(27.4) 3(4.9) 0 6(40) Age 15.194 0.019 ≤ 25 19(9.1) 14(12) 2(3.3) 3(20) 26–49 68(32.7) 40(34.2) 17(27.9) 3(20) 8(53.3) ≥ 50 121(58.2) 63(53.8) 42(68.9) 12(80) 4(26.7) Education Level 8.766 0.459 Primary School or Below 85(40.9) 48(41) 28(45.9) 7(46.7) 2(13.3) Junior High School 65(31.2) 36(30.8) 20(32.8) 3(20) 6(40) High School/Vocational School 23(11.1) 11(9.4) 7(11.5) 2(13.3) 3(20) College or Above 35(16.8) 22(18.8) 6(9.8) 3(20) 4(26.7) Occupation 16.222 0.181 At Home 118(56.7) 60(51.3) 40(65.6) 8(53.3) 10(66.7) Agriculture/Forestry/Fishing 59(28.4) 37(31.6) 16(26.2) 5(33.3) 1(6.7) Other 20(9.6) 14(10.3) 3(4.9) 1(6.7) 2(13.3) Commerce/Service Industry 8(3.8) 6(5.1) 1(1.6) 0 1(6.7) Worker 2(1) 0 1(1.6) 1(6.7) 0 Drug resistance 28.762 0.000 NO 164(78.8) 101(86.3) 50(82) 8(53.3) 5(33.3) YES 44(21.2) 16(13.7) 11(18) 7(46.7) 10(66.7) CD4 Level 5.873 0.753 < 200 82(39.4) 42(35.9) 27(44.2) 7(46.7) 6(40) 200-<350 75(36.1) 45(38.5) 21(34.4) 6(40) 3(20) 350-<500 37(17.8) 22(18.8) 9(14.8) 1(6.7) 5(33.3) ≥ 500 14(6.7) 8(6.8) 4(6.6) 1(6.7) 1(6.7) Viral load 1.026 0.795 ≥ 1000 189(90.9) 108(92.3) 54(88.5) 14(93.3) 13(86.7) < 1000 19(9.1) 9(7.7) 7(11.5) 1(6.7) 2(13.3) Table 2 Characteristics associated with pretreatment drug resistance and molecular clustering Characteristic PDR (44) non-PDR (164) Univariate Analysis OR(95%CI) P Multivariate Analysis OR(95%CI) P Clustering (n = 75) non- Clustering (n = 133) Univariate Analysis OR(95%CI) P Multivariate Analysis OR(95%CI) P Gender 0.599 0.935 0.045 0.839 Male 31(70.5) 122(74.4) 1 1 49(65.3) 104(78.2) 1 1 Female 13(29.5) 42(25.6) 1.218(0.583 ~ 2.544) 0.961(0.379 ~ 2.437) 26(34.7) 29(21.8) 1.903(1.015 ~ 3.569) 1.085(0.493 ~ 2.389) Marital Status 0.527 0.205 < 0.001 0.001 Married 19(43.2) 81(49.4) 1 1 53(70.7) 47(35.3) 1 1 Divorced or Widowed 15(34.1) 50(30.5) 1.292(0.543 ~ 3.072) 1.314(0.539 ~ 3.2) 18(24) 47(35.3) 0.34(0.174 ~ 0.664) 0.284(0.134 ~ 0.6) Single 10(22.7) 33(20.1) 1.279(0.596 ~ 2.744) 4.71(0.861 ~ 25.771) 4(5.3) 39(29.3) 0.091(0.03 ~ 0.274) 0.168(0.028 ~ 1.016) Transmission Route 0.477 0.13 < 0.001 0.263 Heterosexual transmission 37(84.1) 130(79.3) 1 1 71(94.7) 96(72.2) 1 1 Homosexual transmission 7(15.9) 34(20.7) 0.723(0.297 ~ 1.765) 0.278(0.051 ~ 1.527) 4(5.3) 37(27.8) 0.146(0.05 ~ 0.429) 0.417(0.087 ~ 1.994) Age 0.318 0.237 0.009 0.309 ≤ 25 5(11.4) 14(8.5) 1 1 2(2.7) 17(12.8) 1 1 26–49 28(63.6) 93(56.7) 0.54(0.161 ~ 1.809) 0.486(0.079 ~ 2.996) 16(21.3) 52(39.1) 2.615(0.545 ~ 12.555) 0.825(0.089 ~ 7.626) ≥ 50 11(25) 57(34.8) 0.843(0.279 ~ 2.546) 1.158(0.15 ~ 8.948) 57(76) 64(48.1) 7.571(1.676 ~ 34.203) 1.564(0.149 ~ 16.421) Education Level 0.5 0.585 0.01 0.77 Primary School or Below 17(38.6) 68(41.5) 1 1 39(52) 46(34.6) 1 1 Junior High School 16(36.4) 49(29.9) 1.306(0.602 ~ 2.836) 1.223(0.487 ~ 3.071) 22(29.3) 43(32.3) 0.603(0.309 ~ 1.177) 0.832(0.373 ~ 1.856) High School/Vocational School 4(9.1) 19(11.6) 1(0.374 ~ 2.675) 0.759(0.176 ~ 3.265) 7(9.3) 16(12) 0.516(0.193 ~ 1.382) 1.427(0.38 ~ 5.359) College or Above 7(15.9) 28(17.1) 0.842(0.253 ~ 2.802) 0.426(0.08 ~ 2.269) 7(9.3) 28(21.1) 0.295(0.116 ~ 0.749) 1.513(0.388 ~ 5.901) Occupation 0.518 0.64 0.201 0.349 At Home 27(61.4) 91(55.5) 1 1 43(57.3) 75(56.4) 1 1 Agriculture/Forestry/Fishing 11(25) 48(29.3) 0.772(0.353 ~ 1.691) 0.68(0.258 ~ 1.793) 27(36) 32(24.1) 1.471(0.78 ~ 2.776) 1.217(0.551 ~ 2.689) Commerce/Service Industry 3(6.8) 6(3.7) 1.123(0.214 ~ 5.89) 1.364(0.188 ~ 9.877) 1(1.3) 7(5.3) 0.249(0.03 ~ 2.093) 0.193(0.018 ~ 2.037) Worker 0(0) 2(1.2) 0 0 2(1.4) 0 0 Other 3(6.8) 17(10.3) 0.674(0.182 ~ 2.503) 0.569(0.124 ~ 2.612) 4(5.3) 17(12.8) 0.498(0.154 ~ 1.61) 0.48(0.116 ~ 1.982) CD4 Level 0.469 0.769 0.114 0.265 < 200 18(40.9) 64(39) 1 1 34(45.3) 48(36.1) 1 1 200-<350 13(29.5) 62(37.8) 0.746(0.337 ~ 1.65) 0.821(0.324 ~ 2.079) 22(29.3) 53(39.8) 0.586(0.302 ~ 1.138) 0.528(0.241 ~ 1.154) 350-<500 9(20.5) 28(17.1) 1.143(0.458 ~ 2.854) 1.039(0.342 ~ 3.156) 14(18.7) 23(17.3) 0.859(0.387 ~ 1.906) 1.269(0.474 ~ 3.398) ≥ 500 4(9.1) 10(6.1) 1.422(0.399 ~ 5.074) 1.894(0.446 ~ 8.039) 5(6.7) 9(6.8) 0.784(0.241 ~ 2.548) 0.618(0.151 ~ 2.522) Viral load 0.907 0.906 0.44 0.723 ≥ 1000 40(90.9) 149(90.9) 1 1 66(88) 123(92.5) 1 1 < 1000 4(9.1) 14(8.5) 1.072(0.334 ~ 3.435) 0.922(0.241 ~ 3.532) 9(12) 10(7.5) 1.469(0.553 ~ 3.898) 1.226(0.397 ~ 3.786) Genotype < 0.001 < 0.001 0.017 0.113 CRF07_BC 16(36.4) 101(61.6) 1 1 36(48) 81(60.9) 1 1 CRF01_AE 11(25) 50(30.5) 1.389(0.6 ~ 3.214) 1.188(0.482 ~ 2.928) 30(40) 31(23.3) 2.177(1.151 ~ 4.118) 1.611(0.777 ~ 3.341) CRF08_BC 7(15.9) 8(4.9) 5.524(1.761 ~ 17.329) 6.34(1.792 ~ 22.437) 3(4) 9(6.8) 0.562(0.15 ~ 2.116) 0.366(0.084 ~ 1.591) Other 10(22.7) 5(3) 12.626(3.818 ~ 41.757) 14.258(3.727 ~ 54.544) 6(8) 12(9) 1.5(0.497 ~ 4.529) 2.385(0.539 ~ 10.543) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 16 Feb, 2026 Reviews received at journal 12 Feb, 2026 Reviews received at journal 06 Feb, 2026 Reviewers agreed at journal 22 Jan, 2026 Reviewers agreed at journal 22 Jan, 2026 Reviewers invited by journal 20 Jan, 2026 Editor assigned by journal 07 Jan, 2026 Submission checks completed at journal 07 Jan, 2026 First submitted to journal 05 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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07:07:58\",\"extension\":\"xml\",\"order_by\":27,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":180741,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"ce49d1b08c6c4f50875f15c6c35f937e1structuring.xml\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8526252/v1/453be23709416654fbcde394.xml\"},{\"id\":100950145,\"identity\":\"6bf64d9b-dc65-47bc-b1c5-73f9e48b58f4\",\"added_by\":\"auto\",\"created_at\":\"2026-01-23 07:06:59\",\"extension\":\"html\",\"order_by\":28,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":195634,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"earlyproof.html\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8526252/v1/c36c7242dd369eb582faa038.html\"},{\"id\":100949658,\"identity\":\"4107700e-50db-447d-bfad-20e660efe40a\",\"added_by\":\"auto\",\"created_at\":\"2026-01-23 07:04:55\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2337144,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePhylogenetic analysis of HIV-1 pol sequences\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8526252/v1/ef811f9c78a1a2d48ad4b913.jpg\"},{\"id\":100950529,\"identity\":\"4d8b81b4-b715-4679-a6e6-604286a33321\",\"added_by\":\"auto\",\"created_at\":\"2026-01-23 07:08:32\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":288360,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eMolecular transmission networks of HIV-1\\u003c/p\\u003e\\n\\u003cp\\u003e(A)Transmission network colored by transmission route, marital status, and age.(B) Transmission network colored by subtype, gender, and education level.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8526252/v1/beaef5ce4f27a5b8dba16115.png\"},{\"id\":100952825,\"identity\":\"7e0b893b-88c0-4b9a-a87d-9a4808c27503\",\"added_by\":\"auto\",\"created_at\":\"2026-01-23 07:18:19\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":3843255,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8526252/v1/bffb7c2c-8e82-4659-83de-2fd1e185d74f.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Genetic Diversity, Drug Resistance, and Molecular Transmission Networks of HIV-1 in Zunyi: Implications for Precision Prevention\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eHuman immunodeficiency virus (HIV) is a retrovirus characterized by exceptionally high genetic variability. This diversity is largely driven by the low fidelity and lack of proofreading capacity of reverse transcriptase, which enables rapid mutation and frequent recombination during viral replication. Since the first AIDS case was reported in China in 1987, the number of people living with HIV/AIDS has continued to rise[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. By the end of 2023, approximately 39.9\\u0026nbsp;million people were living with HIV worldwide, reflecting both the expanding scale of infection and the increasing complexity of circulating viral variants[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Globally, HIV-1 group M remains the predominant cause of the epidemic and encompasses multiple subtypes and circulating recombinant forms (CRFs), many of which exhibit clear geographic clustering. In East Asia, the proportion of CRF infections exceeds 80%, underscoring both the persistent recombination pressure and the dynamic evolution of regional epidemics[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe widespread implementation of antiretroviral therapy (ART) has markedly reduced viral replication and improved patient prognosis, yet the emergence and onward transmission of drug-resistant HIV-1 strains have become a growing public health concern[\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. At the same time, rapid population movement and the proliferation of online social platforms have expanded the reach of HIV transmission, making transmission patterns increasingly concealed and complex[\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Novel recombinant strains continue to emerge, and traditional epidemiological investigations\\u0026mdash;which depend heavily on self-reported behavioral histories\\u0026mdash;face inherent limitations in accurately reconstructing transmission pathways[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAdvances in molecular biology and bioinformatics have facilitated the development of HIV-1 molecular transmission network analysis, a powerful tool for precision HIV prevention[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. By comparing pol-gene sequences and estimating pairwise genetic distances, molecular networks can infer potential transmission linkages, identify active transmission clusters, and detect high-risk transmitters who may be driving local spread[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. Studies conducted in Sichuan, Shenzhen, Ningxia, and other regions of China have demonstrated that this approach can effectively reveal geographic patterns of viral flow[\\u003cspan additionalcitationids=\\\"CR11\\\" citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e], subtype-specific clustering characteristics, and the role of key populations in sustaining transmission.\\u003c/p\\u003e \\u003cp\\u003eSouthwestern China remains one of the regions most heavily affected by HIV, and Guizhou Province represents a particularly complex epidemic setting characterized by substantial viral diversity, frequent recombination, and heterogeneous transmission modes. Zunyi, a major city in northern Guizhou and an important regional transportation hub, exhibits considerable population mobility and continues to report a high burden of new HIV infections. Despite this, systematic investigations of HIV-1 genotype distribution and molecular transmission network structure in Zunyi are scarce, limiting current understanding of local transmission dynamics.\\u003c/p\\u003e \\u003cp\\u003eTherefore, we characterized HIV-1 genotypes and constructed a molecular transmission network based on pol sequences from newly diagnosed cases in Zunyi. We further examined demographic and epidemiological factors associated with pretreatment drug resistance and network clustering to inform precision prevention efforts in Guizhou Province.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSample Collection and Processing\\u003c/h2\\u003e \\u003cp\\u003eWhole blood samples were obtained from newly reported HIV/AIDS patients at the time of confirmatory diagnosis. Samples were centrifuged at 3,000 r/min for 15 minutes at 4\\u0026deg;C, and plasma was separated and stored at \\u0026minus;\\u0026thinsp;80\\u0026deg;C until further analysis. Viral RNA was extracted using the MagMAX\\u0026trade; Viral RNA Isolation Kit (Thermo Fisher Scientific) on the automated nucleic acid workstation PAN9600S, following the manufacturer\\u0026rsquo;s instructions. The HIV-1 pol gene region was amplified via RT-PCR for subsequent sequencing analysis.Amplified HIV segements were sent to sequence determination by 3730xl (Abi).The study protocol was approved by the Ethics Committee of Guizhou Center for Disease Control and Prevention (No. W2022-08). The study was conducted in accordance with the 1964 \\u0026laquo;Helsinki Declaration\\u0026raquo;.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eGenotype and phylogenetic analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eWe used MEGA 7.0 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.megasoftware.net\\u003c/span\\u003e\\u003cspan address=\\\"http://www.megasoftware.net\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) to align the sequences and build the phylogenetic tree using the neighbor-joining method under Kimura's two parameter correction (1000 replicates). The HIV reference sequence were obtained from the Los Alamos database (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.hiv.anl.gov\\u003c/span\\u003e\\u003cspan address=\\\"http://www.hiv.anl.gov\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) as the following (Genbank Accession Number): CRF07BC: AF503396, JF906666, HQ215583, AF286226, HG421616, J0901027, EF122515; CRF01AE: GU564223, JX112798, AY008714, U51189, JF906597; CRF08BC: AF286229, AY008717; Subtype B: K03455, U71182, AY173951,AY33195; CRF5501B: X574662,X574663, JX574661, KF857447.\\u003c/p\\u003e\\n\\u003ch3\\u003eDrug Resistance Analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eAssembled \\u003cem\\u003epol\\u003c/em\\u003e sequences were uploaded to the Stanford University HIV Drug Resistance Database (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://hivdb.stanford.edu\\u003c/span\\u003e\\u003cspan address=\\\"https://hivdb.stanford.edu\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) to identify drug-resistance\\u0026ndash;associated mutations, resistance profiles, and inferred levels of susceptibility to antiretroviral drugs.\\u003c/p\\u003e\\n\\u003ch3\\u003eGenetic Distance Calculation and Molecular Network Construction\\u003c/h3\\u003e\\n\\u003cp\\u003ePairwise genetic distances among all \\u003cem\\u003epol\\u003c/em\\u003e sequences were calculated using the Tamura\\u0026ndash;Nei 93 (TN93) model by HyPhy2.2.4 software[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Molecular transmission networks were constructed in Cytoscape version 3.9.1. Genetic distance thresholds from 0.1% to 1.5% were evaluated sequentially[\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e], The optimal threshold of 1.0% was selected because it yielded the maximum number of clusters while minimizing artificial cluster inflation.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical Analysis\\u003c/h2\\u003e \\u003cp\\u003eAll statistical analyses were performed using SPSS software version 26.0. Categorical variables were expressed as frequencies and percentages. The χ\\u0026sup2; test or Fisher\\u0026rsquo;s exact test was used to compare proportions between groups. Variables with \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.10 in univariate logistic regression analysis were included in multivariate logistic regression models to identify independent factors associated with PDR and molecular network clustering. A two-sided \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 was considered statistically significant.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eBaseline characteristics of participants\\u003c/h2\\u003e \\u003cp\\u003eA total of 208 individuals with successfully amplified pol sequences were included in the analysis.Among them, 153 (73.6%) were male, and 121 (58.2%) were aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;50 years. Most participants reported heterosexual transmission (167, 80.3%), while 41 (19.7%) reported homosexual transmission. Regarding marital status, 100(48.1%) were married and 65(31.2%) were divorced or widowed. Demographic and clinical characteristics stratified by genotype are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003ePhylogenetic analysis of HIV-1 pol sequences\\u003c/h3\\u003e\\n\\u003cp\\u003ePhylogenetic analysis of the 208 HIV-1 pol gene sequences revealed clear clustering corresponding to major circulating genotypes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Four major genotype categories among the 208 sequences: CRF07_BC (117, 56.3%), CRF01_AE (61, 29.3%), CRF08_BC (15, 7.2%), and other recombinant forms (15, 7.2%). Among these, CRF07_BC and CRF01_AE formed the largest clades, indicating their predominance in the study population. CRF08_BC and subtype B were represented by smaller, well-defined clusters, while a limited number of sequences grouped into other recombinant or B-related lineages.The phylogenetic tree demonstrated strong genotype-specific aggregation, with minimal intermixing between major clades. Sequences classified as the same genotype clustered tightly together, supporting the reliability of genotype assignment.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eOverall structure of the molecular transmission network\\u003c/h2\\u003e \\u003cp\\u003eUsing a 1.0% genetic distance threshold, molecular network analysis identified 31 transmission clusters among 208 HIV-1 sequences, with 75 sequences (36.1%) clustered and 133 (63.9%) remaining unclustered. Cluster sizes ranged from 2 to 6 nodes, with small clusters predominating. Both densely connected clusters including fully interconnected structures of 3\\u0026ndash;5 individuals and simple dyadic or linear chains were observed, indicating heterogeneous transmission patterns.Most clustered cases were male, predominantly aged above 50 years, and largely associated with heterosexual transmission, while homosexual transmission contributed only a small proportion. CRF07_BC and CRF01_AE were the major genotypes involved in clustering; CRF07_BC tended to form more tightly connected structures, whereas CRF01_AE exhibited greater network structural diversity. In contrast, CRF08_BC and other recombinant forms were involved in only a few small clusters(Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePretreatment drug resistance and Cluster characteristics by demographic factors\\u003c/h2\\u003e \\u003cp\\u003ePretreatment drug resistance (PDR) was detected in 21.2% (44/208) of participants. The prevalence of PDR varied significantly across genotypes (χ\\u0026sup2;=28.76, P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), with the highest proportions observed in CRF08_BC (7/15, 46.7%) and other genotypes (10/15, 66.7%). The odds ratios (OR) for these genotypes were 6.34 (95% CI: 1.792\\u0026ndash;22.437) and 14.258 (95% CI: 3.727\\u0026ndash;54.544) times that of the reference group, respectively. In univariate analysis, genotype was strongly associated with PDR, and multivariate logistic regression confirmed its independent association. In univariate analysis, marital status, transmission route, age group, education level, and genotype were associated with cluster membership. Multivariate logistic regression indicated that divorced or widowed individuals were significantly less likely to be clustered (OR\\u0026thinsp;=\\u0026thinsp;0.284, 95% CI: 0.134\\u0026ndash;0.600). Genotype was not statistically significant in the adjusted model, though CRF01_AE showed a trend toward higher clustering probability compared with CRF07_BC. (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eIn this study, we characterized the HIV-1 genotype distribution and molecular transmission network among newly reported HIV infections in Zunyi, Guizhou Province. By integrating phylogenetic analysis, drug resistance surveillance, and molecular network construction, our findings provide a comprehensive view of the local transmission dynamics in a region with high viral diversity and complex epidemic patterns.\\u003c/p\\u003e \\u003cp\\u003eConsistent with reports from other provinces in China, CRF07_BC and CRF01_AE were the predominant genotypes, together accounting for more than 80% of all sequences[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. The clear genotype-specific clustering observed in the phylogenetic tree supports the stability and ongoing circulation of these major lineages in the region. The relatively high proportion of CRF07_BC aligns with its known dominance among heterosexual transmission networks in western China[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], while the substantial presence of CRF01_AE reflects its continued expansion beyond traditionally defined risk groups.\\u003c/p\\u003e \\u003cp\\u003eMolecular network analysis revealed that only approximately one-third of sequences were included in transmission clusters, suggesting that most infections were not linked to detectable recent transmission chains at the selected genetic distance threshold. This finding indicates a transmission pattern dominated by dispersed or sporadic spread, rather than large, rapidly expanding outbreaks. The predominance of small clusters and simple dyadic links further supports the notion of fragmented transmission networks in Zunyi, which may be influenced by population mobility, delayed diagnosis, and incomplete sampling of transmission partners.\\u003c/p\\u003e \\u003cp\\u003eNotably, CRF07_BC and CRF01_AE contributed most to network clustering, yet their structural characteristics differed. CRF07_BC tended to form more tightly connected clusters, which may reflect relatively stable transmission networks or repeated transmission within closely linked social or sexual contacts. In contrast, CRF01_AE exhibited greater structural diversity, including both compact clusters and linear chains, suggesting more heterogeneous transmission pathways. These genotype-specific network patterns underscore the importance of considering viral lineage when interpreting molecular transmission dynamics.\\u003c/p\\u003e \\u003cp\\u003eIn univariate analysis, marital status, transmission route, age, education level, and genotype were associated with clustering. After adjustment, only marital status remained independently associated with clustering, suggesting confounding among correlated sociodemographic variables. Notably, individuals aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;50 years constituted a substantial proportion of clustered cases, but the age\\u0026ndash;clustering association was attenuated in multivariate analysis, indicating that older populations may represent an underrecognized prevention priority rather than an independent driver of clustering. In this region, heterosexual transmission constituted the majority of clustered cases, while homosexual transmission accounted for only a small proportion of clustered nodes. This may reflect differences in network structure, testing coverage, or partner turnover rates between the transmission routes in this area. Interestingly, individuals aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;50 years accounted for a substantial proportion of clustered cases (57/75, 76.0%), and age was associated with clustering in univariate analysis; however, this association was attenuated and no longer statistically significant after adjustment, suggesting confounding by correlated sociodemographic factors.But the growing importance of older populations in the local HIV transmission network\\u0026mdash;a group that may be underrecognized in prevention programs [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003ePretreatment drug resistance was detected in over one-fifth of participants, with marked variation across genotypes. The particularly high prevalence of PDR among CRF08_BC and other recombinant forms, despite their limited clustering in the molecular network, suggests that drug resistance may circulate through pathways not captured by recent transmission clusters, such as historical transmission events or treatment-experienced sources[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. This finding emphasizes the need for continued resistance surveillance alongside molecular network analysis[\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSeveral limitations should be acknowledged. First, the cross-sectional design and incomplete sampling of transmission partners may have led to underestimation of clustering and network connectivity. Second, reliance on self-reported transmission routes may introduce misclassification bias. Third, the use of a single genetic distance threshold, while methodologically justified, cannot fully capture the dynamic nature of HIV transmission over time.\\u003c/p\\u003e \\u003cp\\u003eFrom a public health perspective, the identification of small but active transmission clusters suggests that timely diagnosis and rapid linkage to care may effectively interrupt ongoing transmission. Older individuals and those involved in heterosexual transmission networks should be considered priority populations for targeted interventions.\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eOur study demonstrates that the HIV epidemic in Zunyi is characterized by high genetic diversity, fragmented molecular transmission networks, and genotype-specific clustering patterns. CRF07_BC and CRF01_AE remain central to local transmission, but differ in their network structures, while older age groups and heterosexual transmission play a substantial role in ongoing spread. These findings highlight the value of integrating molecular network analysis into routine HIV surveillance and support the development of targeted, precision prevention strategies tailored to local transmission dynamics in Guizhou Province.\\u003c/p\\u003e \"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eHIV Human Immunodeficiency Virus\\u003c/p\\u003e \\u003cp\\u003eCRF circulating recombinant form\\u003c/p\\u003e \\u003cp\\u003ePDR pretreatment drug resistance\\u003c/p\\u003e \\u003cp\\u003eART antiretroviral therapy\\u003c/p\\u003e \"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study protocol was approved by the Ethics Committee of Guizhou Center for Disease Control and Prevention (No. W2022-08). The study was conducted in accordance with the 1964 \\u0026laquo;Helsinki Declaration\\u0026raquo;. All information about participants was reported to the CDC by doctors after obtaining informed consent from patients.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eData can be requested from the corresponding author.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no conflict of interest.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research was funded by the following grants:\\u003c/p\\u003e\\n\\u003cp\\u003e1. Science and Technology Fund Project of Guizhou Provincial Health Commission (Grant No. gzwkj2023-506).\\u003c/p\\u003e\\n\\u003cp\\u003e2. Regional Innovation Cooperation Project of the Sichuan Science and Technology Program (Grant No. 2025YFHZ0296).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eXinhui Zhang,Yunli Ma and Yinyin Wang designed and conceived this research, and wrote the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003eYonghu Wan, Yuxia Liu, Lu Ma, Yu Zhang, Min Zheng, and Zhi Yuan conducted the epidemiological investigation,sample collection,data collection and management and provided laboratory support.\\u003c/p\\u003e\\n\\u003cp\\u003eZhan Gao and Miao He analyzed the data, and prepared the figures and tables.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe thank the health workers in Center for Disease Control and Prevention in Guiyang ,Zunyi and Honghuagang District for their hard work in carrying out the surveys and data collection. We would also like to thank the study participants for their involvement and voluntary cooperation in this study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCorresponding Authors\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eXinhui Zhang\\u003c/p\\u003e\\n\\u003cp\\u003eGuizhou Provincial Center for Disease Control and Prevention, Guiyang, China\\u003c/p\\u003e\\n\\u003cp\\u003eEmail: 410228757@qq.com\\u003c/p\\u003e\\n\\u003cp\\u003eZhan Gao\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eInstitute of Blood Transfusion, Chinese Academy of Medical Sciences, Chengdu, China\\u003c/p\\u003e\\n\\u003cp\\u003eEmail:241734355@qq.com\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eYan Y, Wu S, Chen L, Yan P, Qiu Y, Xie M, et al. Shift in HIV/AIDS Epidemic in Southeastern China: A Longitudinal Study from 1987 to 2015. 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Viruses. 2024;16. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/v16071174\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/v16071174\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eDemographic and clinical characteristics of participants stratified by HIV-1 genotype\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCharacteristic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" 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\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGender\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e4.226\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.238\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e153(73.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e90(76.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e39(63.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e12(80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e12(80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e55(26.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e27(23.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e22(36.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMarital Status\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e12.204\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.058\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMarried\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e100(48.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e52(44.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e35(57.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e8(53.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e6(40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDivorced or Widowed\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e65(31.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e34(29.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e20(32.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7(46.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e6(40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSingle\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e43(20.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e31(26.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6(9.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTransmission Route\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e20.333\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHeterosexual transmission\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e167(80.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e85(72.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e58(95.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e15(100)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e9(60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHomosexual \\u003c/p\\u003e \\u003cp\\u003etransmission\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e41(19.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e32(27.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3(4.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e6(40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e15.194\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.019\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19(9.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14(12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2(3.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e26\\u0026ndash;49\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e68(32.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e40(34.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17(27.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e8(53.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e121(58.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e63(53.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e42(68.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e12(80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4(26.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEducation Level\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e8.766\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.459\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrimary School or Below\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e85(40.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e48(41)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e28(45.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7(46.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2(13.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eJunior High School\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e65(31.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e36(30.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e20(32.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e6(40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh School/Vocational School\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e23(11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11(9.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7(11.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2(13.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCollege or Above\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e35(16.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22(18.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6(9.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3(20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4(26.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOccupation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e16.222\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.181\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAt Home\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e118(56.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e 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colname=\\\"c4\\\"\\u003e \\u003cp\\u003e16(26.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5(33.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20(9.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14(10.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3(4.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2(13.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCommerce/Service Industry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8(3.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6(5.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(1.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWorker\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2(1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(1.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDrug resistance\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e28.762\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e 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align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e44(21.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e16(13.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11(18)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7(46.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e10(66.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCD4 Level\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e5.873\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.753\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;200\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e82(39.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42(35.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e27(44.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7(46.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e6(40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e200-\\u0026lt;350\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e75(36.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e45(38.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e21(34.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" 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colname=\\\"c6\\\"\\u003e \\u003cp\\u003e5(33.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;500\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8(6.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4(6.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eViral load\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e1.026\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.795\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;1000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e189(90.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e108(92.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e54(88.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e14(93.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e13(86.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;1000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19(9.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e9(7.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7(11.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2(13.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eCharacteristics associated with pretreatment drug resistance and molecular clustering\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"13\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCharacteristic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePDR\\u003c/p\\u003e \\u003cp\\u003e(44)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003enon-PDR\\u003c/p\\u003e \\u003cp\\u003e(164)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003eUnivariate Analysis\\u003c/p\\u003e \\u003cp\\u003e\\u003c/p\\u003e \\u003cp\\u003eOR(95%CI) P\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003eMultivariate Analysis\\u003c/p\\u003e \\u003cp\\u003e\\u003c/p\\u003e \\u003cp\\u003eOR(95%CI) P\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eClustering\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;75)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003enon-\\u003c/p\\u003e \\u003cp\\u003eClustering\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;133)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c11\\\" namest=\\\"c10\\\"\\u003e \\u003cp\\u003eUnivariate Analysis\\u003c/p\\u003e \\u003cp\\u003e\\u003c/p\\u003e \\u003cp\\u003eOR(95%CI) P\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c13\\\" namest=\\\"c12\\\"\\u003e \\u003cp\\u003eMultivariate Analysis\\u003c/p\\u003e \\u003cp\\u003e\\u003c/p\\u003e \\u003cp\\u003eOR(95%CI) P\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGender\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.599\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.935\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.045\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.839\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e31(70.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e122(74.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e49(65.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e104(78.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e13(29.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42(25.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.218(0.583\\u0026thinsp;~\\u0026thinsp;2.544)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.961(0.379\\u0026thinsp;~\\u0026thinsp;2.437)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e26(34.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e29(21.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1.903(1.015\\u0026thinsp;~\\u0026thinsp;3.569)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1.085(0.493\\u0026thinsp;~\\u0026thinsp;2.389)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eMarital Status\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.527\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.205\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMarried\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19(43.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e81(49.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e53(70.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e47(35.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDivorced or Widowed\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15(34.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e50(30.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.292(0.543\\u0026thinsp;~\\u0026thinsp;3.072)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.314(0.539\\u0026thinsp;~\\u0026thinsp;3.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e18(24)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e47(35.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.34(0.174\\u0026thinsp;~\\u0026thinsp;0.664)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.284(0.134\\u0026thinsp;~\\u0026thinsp;0.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSingle\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10(22.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e33(20.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.279(0.596\\u0026thinsp;~\\u0026thinsp;2.744)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4.71(0.861\\u0026thinsp;~\\u0026thinsp;25.771)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4(5.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e39(29.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.091(0.03\\u0026thinsp;~\\u0026thinsp;0.274)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.168(0.028\\u0026thinsp;~\\u0026thinsp;1.016)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eTransmission Route\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.477\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.263\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHeterosexual transmission\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e37(84.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e130(79.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e71(94.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e96(72.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHomosexual \\u003c/p\\u003e \\u003cp\\u003etransmission\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7(15.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e34(20.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.723(0.297\\u0026thinsp;~\\u0026thinsp;1.765)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.278(0.051\\u0026thinsp;~\\u0026thinsp;1.527)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e4(5.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e37(27.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.146(0.05\\u0026thinsp;~\\u0026thinsp;0.429)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.417(0.087\\u0026thinsp;~\\u0026thinsp;1.994)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eAge\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.318\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.237\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.009\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.309\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5(11.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14(8.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e2(2.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e17(12.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e26\\u0026ndash;49\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e28(63.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e93(56.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.54(0.161\\u0026thinsp;~\\u0026thinsp;1.809)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.486(0.079\\u0026thinsp;~\\u0026thinsp;2.996)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e16(21.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e52(39.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e2.615(0.545\\u0026thinsp;~\\u0026thinsp;12.555)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.825(0.089\\u0026thinsp;~\\u0026thinsp;7.626)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e11(25)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e57(34.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.843(0.279\\u0026thinsp;~\\u0026thinsp;2.546)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.158(0.15\\u0026thinsp;~\\u0026thinsp;8.948)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e57(76)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e64(48.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e7.571(1.676\\u0026thinsp;~\\u0026thinsp;34.203)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1.564(0.149\\u0026thinsp;~\\u0026thinsp;16.421)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eEducation Level\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.585\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrimary School or 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align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eJunior High School\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e16(36.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e49(29.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.306(0.602\\u0026thinsp;~\\u0026thinsp;2.836)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.223(0.487\\u0026thinsp;~\\u0026thinsp;3.071)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e22(29.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e43(32.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.603(0.309\\u0026thinsp;~\\u0026thinsp;1.177)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.832(0.373\\u0026thinsp;~\\u0026thinsp;1.856)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh School/Vocational School\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4(9.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e19(11.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(0.374\\u0026thinsp;~\\u0026thinsp;2.675)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.759(0.176\\u0026thinsp;~\\u0026thinsp;3.265)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e7(9.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e16(12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.516(0.193\\u0026thinsp;~\\u0026thinsp;1.382)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1.427(0.38\\u0026thinsp;~\\u0026thinsp;5.359)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCollege or Above\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7(15.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e28(17.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.842(0.253\\u0026thinsp;~\\u0026thinsp;2.802)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.426(0.08\\u0026thinsp;~\\u0026thinsp;2.269)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e7(9.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e28(21.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.295(0.116\\u0026thinsp;~\\u0026thinsp;0.749)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1.513(0.388\\u0026thinsp;~\\u0026thinsp;5.901)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eOccupation\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.518\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.64\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.201\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.349\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAt Home\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e27(61.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e91(55.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e43(57.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e75(56.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgriculture/Forestry/Fishing\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e11(25)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e48(29.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.772(0.353\\u0026thinsp;~\\u0026thinsp;1.691)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.68(0.258\\u0026thinsp;~\\u0026thinsp;1.793)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e27(36)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e32(24.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1.471(0.78\\u0026thinsp;~\\u0026thinsp;2.776)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1.217(0.551\\u0026thinsp;~\\u0026thinsp;2.689)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCommerce/Service Industry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3(6.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6(3.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.123(0.214\\u0026thinsp;~\\u0026thinsp;5.89)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" 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colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4(9.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10(6.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1.422(0.399\\u0026thinsp;~\\u0026thinsp;5.074)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.894(0.446\\u0026thinsp;~\\u0026thinsp;8.039)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5(6.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e9(6.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e 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align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.906\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.44\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.723\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;1000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e40(90.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e149(90.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e66(88)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e123(92.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e 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colname=\\\"c11\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e2.385(0.539\\u0026thinsp;~\\u0026thinsp;10.543)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"HIV-1, molecular transmission network, pol gene, pretreatment drug resistance, phylogenetic analysis, China\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-8526252/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-8526252/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eHIV-1 genetic diversity and the spread of pretreatment drug resistance (PDR) complicate epidemic control. Southwestern China has a heterogeneous HIV epidemic, but molecular transmission dynamics in many prefecture-level settings remain poorly described.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eWe analyzed HIV-1 pol sequences from 208 newly diagnosed individuals in Zunyi, Guizhou Province. Genotypes were assigned by reference-based phylogenetic analysis; PDR was interpreted using the Stanford HIV Drug Resistance Database. Molecular transmission networks were inferred from pairwise genetic distances calculated with the TN93 model, and factors associated with PDR and clustering were evaluated using logistic regression.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eCRF07_BC (56.3%) and CRF01_AE (29.3%) were the predominant genotypes. PDR was detected in 21.2% of participants and varied significantly across genotypes, with higher prevalence observed in CRF08_BC and other recombinant forms. Molecular network analysis identified 31 transmission clusters involving 36.1% of sequences, with cluster sizes ranging from 2 to 6 nodes. Most clusters were small, and both densely connected subgraphs and simple linear chains were observed, indicating heterogeneous transmission patterns. Clustered cases were largely heterosexual and included a high proportion of individuals aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;50 years. CRF07_BC formed more tightly connected clusters, whereas CRF01_AE exhibited greater structural diversity. Multivariate analysis showed that divorced or widowed individuals were less likely to be included in transmission clusters.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eThe HIV epidemic in Zunyi is characterized by high genetic diversity, fragmented molecular transmission networks, and genotype-specific clustering patterns. Integrating molecular network analysis with routine drug resistance surveillance can improve understanding of local transmission dynamics and support precision HIV prevention strategies in southwestern China.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Genetic Diversity, Drug Resistance, and Molecular Transmission Networks of HIV-1 in Zunyi: Implications for Precision Prevention\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-01-22 11:42:57\",\"doi\":\"10.21203/rs.3.rs-8526252/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2026-02-16T06:37:47+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-02-12T20:45:49+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-02-06T14:53:06+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"303936002838168415059851256530566409530\",\"date\":\"2026-01-22T14:36:37+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"140124343048168885641123258914171135421\",\"date\":\"2026-01-22T11:28:36+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-01-21T03:58:40+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2026-01-07T08:45:48+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2026-01-07T08:44:05+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Infectious Diseases\",\"date\":\"2026-01-06T03:24:24+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"a6cc72d9-9231-49ad-9511-8062cd778a6d\",\"owner\":[],\"postedDate\":\"January 22nd, 2026\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"in-revision\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-05-15T05:54:48+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-01-22 11:42:57\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-8526252\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-8526252\",\"identity\":\"rs-8526252\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}