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Gao R, Li W, Xu J, Guo J, Wang R, Zhang S, Zheng X, Wang J. Characteristics of Subtype and Molecular Transmission Networks among Newly Diagnosed HIV-1 Infections in Patients Residing in Taiyuan City, Shanxi Province, China, from 2021 to 2023. Viruses 2024; 16:1174. [PMID: 39066336 PMCID: PMC11281631 DOI: 10.3390/v16071174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Revised: 07/18/2024] [Accepted: 07/19/2024] [Indexed: 07/28/2024] Open
Abstract
The HIV-1 pandemic, spanning four decades, presents a significant challenge to global public health. This study aimed to understand the molecular transmission characteristics of newly reported HIV infections in Taiyuan, Shanxi Province, China, to analyze the characteristics of subtypes and the risk factors of the transmission network, providing a scientific basis for precise prevention and intervention measures. A total of 720 samples were collected from newly diagnosed HIV-1 patients residing in Taiyuan between 2021 and 2023. Sequencing of partial genes of the HIV-1 pol gene resulted in multiple sequence acquisitions and was conducted to analyze their subtypes and molecular transmission networks. Out of the samples, 584 pol sequences were obtained, revealing 17 HIV-1 subtypes, with CRF07_BC (48.29%), CRF01_AE (31.34%), and CRF79_0107 (7.19%) being the dominant subtypes. Using a genetic distance threshold of 1.5%, 49 molecular transmission clusters were generated from the 313 pol gene sequences. Univariate analysis showed significant differences in the HIV transmission molecular network in terms of HIV subtype and household registration (p < 0.05). Multivariate logistic regression analysis showed that CRF79_0107 subtype and its migrants were associated with higher proportions of sequences in the HIV transmission network. These findings provide a scientific foundation for the development of localized HIV-specific intervention strategies.
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Affiliation(s)
- Ruihong Gao
- Academy of Medical Sciences, Shanxi Medical University, 56 Xinjian South Road, Taiyuan 030001, Shanxi, China;
- School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan 030001, Shanxi, China
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
| | - Wentong Li
- Academy of Medical Sciences, Shanxi Medical University, 56 Xinjian South Road, Taiyuan 030001, Shanxi, China;
- School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan 030001, Shanxi, China
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
| | - Jihong Xu
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
| | - Jiane Guo
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
| | - Rui Wang
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
| | - Shuting Zhang
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
| | - Xiaonan Zheng
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
| | - Jitao Wang
- School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan 030001, Shanxi, China
- Taiyuan Center for Disease Control and Prevention, No. 22, Huazhang West Street, Xiaodian District, Taiyuan 030012, Shanxi, China; (J.X.); (J.G.); (R.W.); (S.Z.); (X.Z.)
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Wang Y, Yang C, Jin X, Chen H, Zhu Q, Dai J, Dong L, Yang M, Sun P, Cao R, Jia M, Ma Y, Chen M. HIV-1 Molecular Networks and Pretreatment Drug Resistance at the Frontier of Yunnan Province, China. AIDS Res Hum Retroviruses 2024. [PMID: 38959124 DOI: 10.1089/aid.2023.0124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2024] Open
Abstract
The border areas of Yunnan Province in China are severely affected by human immunodeficiency virus (HIV). To investigate the risk of HIV transmission and assess the prevalence of pretreatment drug resistance (PDR) in the border area, blood samples were collected from individuals with newly reported HIV in 2021 in three border counties (Cangyuan, Gengma, and Zhenkang) in Yunnan Province. Among the 174 samples successfully genotyped, eight circulating recombinant forms (CRFs), two subtypes, and several unique recombinant forms (URFs) were identified. CRF08_BC (56.9%, 99/174), URFs (14.4%, 25/174), CRF01_AE (10.9%, 19/174), and CRF07_BC (8.0%, 14/174) were the main genotypes. CRF08_BC and URFs were detected more frequently in Chinese and Burmese individuals, respectively. CRF07_BC was found more frequently in men who have sex with men. The proportion of individuals detected in HIV-1 networks was only associated with case-reporting counties. When stratified by county, individuals aged ≤40 years in Cangyuan and ≥41 years in Gengma were more likely to be found in these networks. Furthermore, 93.8% (15/16) of the links in Cangyuan and 79.4% (50/63) of those in Gengma were located within their own counties. The prevalence of PDR to any antiretroviral drug, nucleoside reverse transcriptase inhibitors (NRTIs), and non-nucleoside reverse transcriptase inhibitors (NNRTIs) were 10% (17/170), 0.6% (1/170), and 9.4% (16/170), respectively. The most frequent resistance-associated mutations (RAMs) were V179D/VD/E/T (22.9%, 39/170) and E138A/G/K/R (13.5%, 23/170). In the molecular networks, six clusters shared common RAMs. HIV-1 genetics has become more diverse in border areas. HIV-1 molecular network analysis revealed the different characteristics of the HIV-1 epidemic in the border counties. The prevalence of PDR showed an upward trend, and the PDR to NNRTIs was close to the public response threshold. These findings provide information for the development of AIDS prevention and treatment strategies.
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Affiliation(s)
- Yawen Wang
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & School of Public Health, Kunming Medical University, Kunming, China
| | - Cuiyun Yang
- Division for AIDS/STD Control and Prevention, Lincang Center for Disease Control and Prevention, Lincang, China
| | - Xiaomei Jin
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Huichao Chen
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Qiongmei Zhu
- Division for AIDS/STD Control and Prevention, Lincang Center for Disease Control and Prevention, Lincang, China
| | - Jie Dai
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Lijuan Dong
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Min Yang
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Pengyan Sun
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Rui Cao
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & School of Public Health, Kunming Medical University, Kunming, China
| | - Manhong Jia
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Yanling Ma
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Min Chen
- Yunnan Provincial Key Laboratory of Public Health and Biosafety & Health Laboratory Center, Yunnan Center for Disease Control and Prevention, Kunming, China
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Shi H, Li X, Wang S, Dong X, Qiao M, Wu S, Wu R, Yuan X, Wang J, Xu Y, Zhu Z. Molecular transmission network analysis of newly diagnosed HIV-1 infections in Nanjing from 2019 to 2021. BMC Infect Dis 2024; 24:583. [PMID: 38867161 PMCID: PMC11170874 DOI: 10.1186/s12879-024-09337-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 04/21/2024] [Indexed: 06/14/2024] Open
Abstract
OBJECTIVE The objective of this study was to conduct a comprehensive analysis of the molecular transmission networks and transmitted drug resistance (TDR) patterns among individuals newly diagnosed with HIV-1 in Nanjing. METHODS Plasma samples were collected from newly diagnosed HIV patients in Nanjing between 2019 and 2021. The HIV pol gene was amplified, and the resulting sequences were utilized for determining TDR, identifying viral subtypes, and constructing molecular transmission network. Logistic regression analyses were employed to investigate the epidemiological characteristics associated with molecular transmission clusters. RESULTS A total of 1161 HIV pol sequences were successfully extracted from newly diagnosed individuals, each accompanied by reliable epidemiologic information. The analysis revealed the presence of multiple HIV-1 subtypes, with CRF 07_BC (40.57%) and CRF01_AE (38.42%) being the most prevalent. Additionally, six other subtypes and unique recombinant forms (URFs) were identified. The prevalence of TDR among the newly diagnosed cases was 7.84% during the study period. Employing a genetic distance threshold of 1.50%, the construction of the molecular transmission network resulted in the identification of 137 clusters, encompassing 613 nodes, which accounted for approximately 52.80% of the cases. Multivariate analysis indicated that individuals within these clusters were more likely to be aged ≥ 60, unemployed, baseline CD4 cell count ≥ 200 cells/mm3, and infected with the CRF119_0107 (P < 0.05). Furthermore, the analysis of larger clusters revealed that individuals aged ≥ 60, peasants, those without TDR, and individuals infected with the CRF119_0107 were more likely to be part of these clusters. CONCLUSIONS This study revealed the high risk of local HIV transmission and high TDR prevalence in Nanjing, especially the rapid spread of CRF119_0107. It is crucial to implement targeted interventions for the molecular transmission clusters identified in this study to effectively control the HIV epidemic.
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Affiliation(s)
- Hongjie Shi
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Xin Li
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Sainan Wang
- Department of Laboratory Medicine, Jiangning Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Xiaoxiao Dong
- Department of Microbiology Laboratory, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Mengkai Qiao
- Department of Microbiology Laboratory, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Sushu Wu
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Rong Wu
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Xin Yuan
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Jingwen Wang
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China
| | - Yuanyuan Xu
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China.
| | - Zhengping Zhu
- Department of AIDS/STD Control and Prevention, Nanjing Center for Disease Control and Prevention, Nanjing, China.
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He Y, Tang Y, Hua Q, Li X, Ge Y, Liu Y, Tang R, Tian Y, Li W. Exploring Dynamic Changes in HIV-1 Molecular Transmission Networks and Key Influencing Factors: Cross-Sectional Study. JMIR Public Health Surveill 2024; 10:e56593. [PMID: 38810253 PMCID: PMC11170051 DOI: 10.2196/56593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 02/19/2024] [Accepted: 05/05/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND The HIV-1 molecular network is an innovative tool, using gene sequences to understand transmission attributes and complementing social and sexual network studies. While previous research focused on static network characteristics, recent studies' emphasis on dynamic features enhances our understanding of real-time changes, offering insights for targeted interventions and efficient allocation of public health resources. OBJECTIVE This study aims to identify the dynamic changes occurring in HIV-1 molecular transmission networks and analyze the primary influencing factors driving the dynamics of HIV-1 molecular networks. METHODS We analyzed and compared the dynamic changes in the molecular network over a specific time period between the baseline and observed end point. The primary factors influencing the dynamic changes in the HIV-1 molecular network were identified through univariate analysis and multivariate analysis. RESULTS A total of 955 HIV-1 polymerase fragments were successfully amplified from 1013 specimens; CRF01_AE and CRF07_BC were the predominant subtypes, accounting for 40.8% (n=390) and 33.6% (n=321) of the specimens, respectively. Through the analysis and comparison of the basic and terminal molecular networks, it was discovered that 144 sequences constituted static molecular networks, and 487 sequences contributed to the formation of dynamic molecular networks. The findings of the multivariate analysis indicated that the factors occupation as a student, floating population, Han ethnicity, engagement in occasional or multiple sexual partnerships, participation in anal sex, and being single were independent risk factors for the dynamic changes observed in the HIV-1 molecular network, and the odds ratio (OR; 95% CIs) values were 2.63 (1.54-4.47), 1.83 (1.17-2.84), 2.91 (1.09-7.79), 1.75 (1.06-2.90), 4.12 (2.48-6.87), 5.58 (2.43-12.80), and 2.10 (1.25-3.54), respectively. Heterosexuality and homosexuality seem to exhibit protective effects when compared to bisexuality, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. Additionally, the National Eight-Item score and sex education experience were also identified as protective factors against dynamic changes in the HIV-1 molecular network, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. CONCLUSIONS The HIV-1 molecular network analysis showed 144 sequences in static networks and 487 in dynamic networks. Multivariate analysis revealed that occupation as a student, floating population, Han ethnicity, and risky sexual behavior were independent risk factors for dynamic changes, while heterosexuality and homosexuality were protective compared to bisexuality. A higher National Eight-Item score and sex education experience were also protective factors. The identification of HIV dynamic molecular networks has provided valuable insights into the characteristics of individuals undergoing dynamic alterations. These findings contribute to a better understanding of HIV-1 transmission dynamics and could inform targeted prevention strategies.
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Affiliation(s)
- Yan He
- Department of Infection Management, Nanjing Drum Tower Hospital, Nanjing, China
| | - Ying Tang
- Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Qun Hua
- Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Xin Li
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, China
| | - You Ge
- School of Public Health, Southeast University, Nanjing, China
| | - Yangyang Liu
- School of Public Health, Southeast University, Nanjing, China
| | - Rong Tang
- Nanjing Qixia District Center for Disease Control and Prevention, Nanjing, China
| | - Ye Tian
- Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Wei Li
- Children's Hospital of Nanjing Medical University, Nanjing, China
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Hu L, Zhao B, Liu M, Gao Y, Ding H, Hu Q, An M, Shang H, Han X. Optimization of genetic distance threshold for inferring the CRF01_AE molecular network based on next-generation sequencing. Front Cell Infect Microbiol 2024; 14:1388059. [PMID: 38846352 PMCID: PMC11155296 DOI: 10.3389/fcimb.2024.1388059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 03/28/2024] [Indexed: 06/09/2024] Open
Abstract
Introduction HIV molecular network based on genetic distance (GD) has been extensively utilized. However, the GD threshold for the non-B subtype differs from that of subtype B. This study aimed to optimize the GD threshold for inferring the CRF01_AE molecular network. Methods Next-generation sequencing data of partial CRF01_AE pol sequences were obtained for 59 samples from 12 transmission pairs enrolled from a high-risk cohort during 2009 and 2014. The paired GD was calculated using the Tamura-Nei 93 model to infer a GD threshold range for HIV molecular networks. Results 2,019 CRF01_AE pol sequences and information on recent HIV infection (RHI) from newly diagnosed individuals in Shenyang from 2016 to 2019 were collected to construct molecular networks to assess the ability of the inferred GD thresholds to predict recent transmission events. When HIV transmission occurs within a span of 1-4 years, the mean paired GD between the sequences of the donor and recipient within the same transmission pair were as follow: 0.008, 0.011, 0.013, and 0.023 substitutions/site. Using these four GD thresholds, it was found that 98.9%, 96.0%, 88.2%, and 40.4% of all randomly paired GD values from 12 transmission pairs were correctly identified as originating from the same transmission pairs. In the real world, as the GD threshold increased from 0.001 to 0.02 substitutions/site, the proportion of RHI within the molecular network gradually increased from 16.6% to 92.3%. Meanwhile, the proportion of links with RHI gradually decreased from 87.0% to 48.2%. The two curves intersected at a GD of 0.008 substitutions/site. Discussion A suitable range of GD thresholds, 0.008-0.013 substitutions/site, was identified to infer the CRF01_AE molecular transmission network and identify HIV transmission events that occurred within the past three years. This finding provides valuable data for selecting an appropriate GD thresholds in constructing molecular networks for non-B subtypes.
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Affiliation(s)
- Lijuan Hu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Bin Zhao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Mingchen Liu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Yang Gao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Haibo Ding
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Qinghai Hu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Minghui An
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Hong Shang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Xiaoxu Han
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- National Health Commission (NHC) Key Laboratory of AIDS Prevention and Treatment, National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, China Medical University, Shenyang, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
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Cheng P, He BC, Liu JF, Wang JL, Yang CX, Ma S, Zhang M, Dong XQ, Li JJ. Using the Molecular Transmission Networks to Analyze the Epidemic Characteristics of HIV-1 CRF08_BC in Kunming, Yunnan. AIDS Res Hum Retroviruses 2024; 40:353-362. [PMID: 37658836 DOI: 10.1089/aid.2023.0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023] Open
Abstract
HIV-1CRF08_BC is the most prevalent epidemic subtype among heterosexual (HET) and intravenous drug users (IDUs) in Kunming, Yunnan. Using the pol region of gene sequences derived from molecular epidemiological surveys, we developed a molecular transmission network for the purpose of analyzing its epidemiological characteristics, assessing its epidemiological trends, identifying its potential transmission relationships, and developing targeted interventions. HyPhy 2.2.4 was used to calculate pairwise genetic distances between sequences; GraphPad-Prism 8.0 was employed to determine the standard genetic distance; and Cytoscope 3.7.2 was applied to visualize the network. We used the network analysis tools to investigate network characteristics and the Molecular Complex Detection (MCODE) tool to observe the growth of the network. We utilized a logistic regression model to examine the factors influencing clustering and a zero-inflated Poisson model to investigate the factors influencing potential transmission links. At the standard genetic distance threshold of 0.008, 406 out of 858 study participants were clustered in 132 dissemination networks with a total network linkage of 868, and the number of links per sequence ranged from 1 to 19. The MCODE analysis identified three significant modular clusters in the networks, with network scores ranging from 4.9 to 7. In models of logistic regression, HET, middle-aged and elderly individuals, and residents of northern and southeastern Kunming were more likely to enter the transmission network. According to the zero-inflated Poisson model, age, transmission category, sampling year, marital status, and CD4+ T level had a significant effect on the size of links. The molecular clusters in Kunming's molecular transmission network are specific and aggregate to a certain extent. HIV-1 molecular network analysis provided information on local transmission characteristics, and these findings helped to determine the priority of transmission-reduction interventions.
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Affiliation(s)
- Peng Cheng
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
- School of Public Health, Kunming Medical University, Kunming, P.R. China
| | - Bao-Cui He
- School of Public Health, Kunming Medical University, Kunming, P.R. China
| | - Jia-Fa Liu
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Jia-Li Wang
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Cui-Xian Yang
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Sha Ma
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Mi Zhang
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Xing-Qi Dong
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
- School of Public Health, Kunming Medical University, Kunming, P.R. China
| | - Jian-Jian Li
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
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7
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Kemp SA, Kamelian K, Cuadros DF, Cheng MTK, Okango E, Hanekom W, Ndung'u T, Pillay D, Bonsall D, Wong EB, Tanser F, Siedner MJ, Gupta RK. HIV transmission dynamics and population-wide drug resistance in rural South Africa. Nat Commun 2024; 15:3644. [PMID: 38684655 PMCID: PMC11059351 DOI: 10.1038/s41467-024-47254-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 03/20/2024] [Indexed: 05/02/2024] Open
Abstract
Despite expanded antiretroviral therapy (ART) in South Africa, HIV-1 transmission persists. Integrase strand transfer inhibitors (INSTI) and long-acting injectables offer potential for superior viral suppression, but pre-existing drug resistance could threaten their effectiveness. In a community-based study in rural KwaZulu-Natal, prior to widespread INSTI usage, we enroled 18,025 individuals to characterise HIV-1 drug resistance and transmission networks to inform public health strategies. HIV testing and reflex viral load quantification were performed, with deep sequencing (20% variant threshold) used to detect resistance mutations. Phylogenetic and geospatial analyses characterised transmission clusters. One-third of participants were HIV-positive, with 21.7% having detectable viral loads; 62.1% of those with detectable viral loads were ART-naïve. Resistance to older reverse transcriptase (RT)-targeting drugs was found, but INSTI resistance remained low (<1%). Non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance, particularly to rilpivirine (RPV) even in ART-naïve individuals, was concerning. Twenty percent of sequenced individuals belonged to transmission clusters, with geographic analysis highlighting higher clustering in peripheral and rural areas. Our findings suggest promise for INSTI-based strategies in this setting but underscore the need for RPV resistance screening before implementing long-acting cabotegravir (CAB) + RPV. The significant clustering emphasises the importance of geographically targeted interventions to effectively curb HIV-1 transmission.
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Affiliation(s)
- Steven A Kemp
- Department of Medicine, University of Cambridge, Cambridge, UK
- Pandemic Science Institute, Big Data Institute, University of Oxford, Oxford, UK
| | - Kimia Kamelian
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Diego F Cuadros
- Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA
| | - Mark T K Cheng
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Elphas Okango
- Africa Health Research Institute, KwaZulu-Natal, Durban, South Africa
| | - Willem Hanekom
- Africa Health Research Institute, KwaZulu-Natal, Durban, South Africa
- University College London, London, UK
| | - Thumbi Ndung'u
- Africa Health Research Institute, KwaZulu-Natal, Durban, South Africa
- University College London, London, UK
| | | | - David Bonsall
- Pandemic Science Institute, Big Data Institute, University of Oxford, Oxford, UK
| | - Emily B Wong
- Africa Health Research Institute, KwaZulu-Natal, Durban, South Africa
| | - Frank Tanser
- University of Stellenbosch, Cape Town, South Africa
| | - Mark J Siedner
- Africa Health Research Institute, KwaZulu-Natal, Durban, South Africa
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
- University of KwaZulu-Natal, Durban, South Africa
- Harvard University, Cambridge, MA, England
| | - Ravindra K Gupta
- Department of Medicine, University of Cambridge, Cambridge, UK.
- Africa Health Research Institute, KwaZulu-Natal, Durban, South Africa.
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Zhong X, Yuan D, Fan SF, Liu Y, Su L, He SJ, Liang S, Yang Y. Molecular network analysis of 308 newly diagnosed HIV infection and 210 ART failure patients from rural counties in Sichuan. PLoS One 2024; 19:e0298324. [PMID: 38363761 PMCID: PMC10871515 DOI: 10.1371/journal.pone.0298324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 01/18/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Few studies on molecular epidemiology have studied people with newly diagnosed HIV infection and ART Failure Patients at the same time in rural China. With more serious HIV epidemic than in other provinces in China, Sichuan is an area suitable for this study. OBJECTIVE To analyze the characteristics of HIV-1 molecular networks and factors related to network entry among newly diagnosed HIV infection and ART Failure Patients in three county-level cities (A, B, C) in Sichuan Province, to provide scientific basis for accurate prevention and control. METHODS Nested PCR amplification method was used to amplify HIV-1 pol gene region of 530 blood samples, Sequencer 4.9 was used to edit, clean and splice the gene sequence, Bioedit correction, Fastree 2.1.8 and Figtree 1.4.2 to construct evolutionary tree and determine genotype. HyPhy2.2.4 and Cytoscape 3.6.1 software were used to construct molecular network. Logistic regression analysis was applied. RESULTS 523(98.68%) pol sequences were obtained, and a total of 518 valid sequences with basic information came into the final analyses. A total of 6 genotypes were detected, namely CRF01_AE (320,61.78%), CRF07_BC (149,28.76%), B (30,5.79%), CRF08_BC (11, 2.12%), CRF55_01B (6, 1.16%) and C (2, 0.39%). 186 of 518(35.91%) sequences entered the network at a genetic distance of 0.8%, forming 42 propagation clusters. "High-risk transmitters"(connected with two and more) accounted for 21.62%. Logistic regression showed that≥50 years old (OR = 2.474) were more risky than 18-49 years old, CRF07_BC sub-type (OR = 0.174) were less risky than CRF01_AE sub-type, B sub-type (OR = 6.698) is higher risky than CRF01_AE sub-type, and District B (OR = 0.077) less risky than that of A city. CONCLUSION The sources of HIV infection in rural Sichuan are diversified and complicated. The prevention and control of HIV infection in Sichuan Province should focus on strengthening the long-term dynamic detection of elderly population, B strain sub-type, and in City A.
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Affiliation(s)
- Xia Zhong
- School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Dan Yuan
- Institute of HIV/AIDS prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Shuang feng Fan
- Department of HIV/AIDS prevention, Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Yang Liu
- Department of HIV/AIDS prevention, Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Ling Su
- Institute of HIV/AIDS prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Shi Jiao He
- Department of HIV/AIDS prevention, Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Shu Liang
- Institute of HIV/AIDS prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yi Yang
- School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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Zhang F, Yang Y, Liang N, Liang H, Chen Y, Lin Z, Chen T, Tan W, Yang Y, Huang R, Yao L, Chen F, Huang X, Ye L, Liang H, Liang B. Transmission network and phylogenetic analysis reveal older male-centered transmission of CRF01_AE and CRF07_BC in Guangxi, China. Emerg Microbes Infect 2023; 12:2147023. [PMID: 36369697 PMCID: PMC9809400 DOI: 10.1080/22221751.2022.2147023] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
In China, the number of newly reported HIV infections in older people is increasing rapidly. However, clear information on the impact of older people on HIV transmission is limited. This study aims to reveal the local HIV transmission patterns, especially how older people affect virus transmission. Subtype analysis based on available pol sequences obtained from HIV patients revealed that CRF01_AE and CRF08_BC were predominant in patients aged <50 years, whereas CRF01_AE was predominant in older people aged ≥50 years (χ2 = 29.299, P < 0.001). A total of 25 patients (5.2%, 25/484) were identified with recent HIV infection (RHI). Transmission network analysis found 267 genetically linked individuals forming 55 clusters (2-63 individuals), including 5 large transmission clusters and 12 transmission clusters containing RHI. Bayesian phylogenetic analysis suggested that transmission events in CRF01_AE and CRF07_BC were centred on older males, while transmission events in CRF08_BC were centred on younger males. Multivariable logistic regression analysis showed that older people were more likely to cluster within networks (AOR = 2.303, 95% CI: 1.012-5.241) and that RHI was a significant factor associated with high linkage (AOR = 3.468, 95% CI: 1.315-9.146). This study provides molecular evidence that older males play a central role in the local transmission of CRF01_AE and CRF07_BC in Guangxi. Given the current widespread of CRF01_AE and CRF07_BC in Guangxi, there is a need to recommend HIV screening as part of free national medical examinations for older people to improve early detection, timely treatment, and further reduce second-generation transmission.
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Affiliation(s)
- Fei Zhang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, People’s Republic of China,Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Life Science Institute, Guangxi Medical University, Nanning, People’s Republic of China
| | - Yao Yang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, People’s Republic of China
| | - Na Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, People’s Republic of China
| | - Huayue Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, People’s Republic of China
| | - Yongzheng Chen
- Qinzhou Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Zhaosen Lin
- Qinzhou Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Tongbi Chen
- Qinzhou Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Wenling Tan
- Lingshan County Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Yuan Yang
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Life Science Institute, Guangxi Medical University, Nanning, People’s Republic of China
| | - Rongye Huang
- Qinzhou Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Lin Yao
- Lingshan County Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Fuling Chen
- Lingshan County Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Xingzhen Huang
- Lingshan County Center for Disease Control and Prevention, Qinzhou, People’s Republic of China
| | - Li Ye
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, People’s Republic of China,Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Life Science Institute, Guangxi Medical University, Nanning, People’s Republic of China,Li Ye Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Hao Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, People’s Republic of China,Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Life Science Institute, Guangxi Medical University, Nanning, People’s Republic of China,Hao Liang
| | - Bingyu Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, People’s Republic of China,Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Life Science Institute, Guangxi Medical University, Nanning, People’s Republic of China, Bingyu Liang
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10
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Zhou Y, Lu J, Zhang Z, Sun Q, Xu X, Hu H. Characteristics of the different HIV-1 risk populations based on the genetic transmission network of the newly diagnosed HIV cases in Jiangsu, Eastern China. Heliyon 2023; 9:e22927. [PMID: 38125421 PMCID: PMC10730745 DOI: 10.1016/j.heliyon.2023.e22927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 11/18/2023] [Accepted: 11/22/2023] [Indexed: 12/23/2023] Open
Abstract
Introduction The HIV-1 prevalence has been steadily increasing in Jiangsu, China. HIV-1 genetic transmission network can be used to explore the transmission kinetics and precision intervention in high-risk populations. Thus, we generated an HIV-1 genetic transmission network, explored key risk populations based on different risk factors and found out the risk factors for HIV-1 prevention and control among the newly-diagnosed HIV-1 cases from 2017 to 2018. Method We amplified the HIV-1 pol sequences from the plasma samples of the newly-diagnosed HIV-1 cases from 2017 to 2018 and obtained the infection data from The National HIV/AIDS Surveillance System. HIV-Trace and Cytoscape Software were both used to construct the HIV-1 genetic network with a gene distance of <0.005. The R software was used to analyze the risk factors for inclusion into the network. Results We obtained 3362 sequences with the pol gene region, of which 3316 contained detailed individual information. CRF01_AE accounted for 42.3 % of the HIV-1 subtypes in the samples. The median CD4+T lymphocyte count was 329 cells/μL in 2017 and 313 cells/μL in 2018. At the gene distance threshold of 0.005, 481 sequences were incorporated into the HIV-1 gene network, constructing 202 clusters. Age over 60 years old, heterosexual transmission route, subtype (CRF105_0107, CRF55_01 B, and CRF67_01 B) and CD4+T lymphocyte count (>200) were the risk factors influencing inclusion into the HIV-1 gene network. Moreover, south Jiangsu cities had higher inclusion in the network. Thus, key risk populations in the clusters with different transmission routes, new emerging subtypes, drug resistance nodes, and individuals above 60 years of age in the network represented the critical risk populations that should be focused more on for intervention. Conclusion The HIV-1 genetic transmission network is adept at discovering undiagnosed HIV-infected cases and linking all diagnosed cases for determination of risk infections. Therefore we should pay more attention to these risk infections with further investigation and intervention, helping to achieve the goal of 95 % use combination prevention from the World Health Organization, and push to end AIDS epidemic.
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Affiliation(s)
- Ying Zhou
- Institute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Jing Lu
- Institute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Zhi Zhang
- Institute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Qi Sun
- Institute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Xiaoqin Xu
- Institute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Haiyang Hu
- Institute of AIDS/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
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Gupta R, Kemp S, Kamelian K, Cuadros D, Gupta R, Cheng M, Okango E, Hanekom W, Ndung'u T, Pillay D, Bonsall D, Wong E, Tanser F, Siedner M. HIV transmission dynamics and population-wide drug resistance in rural South Africa. RESEARCH SQUARE 2023:rs.3.rs-3640717. [PMID: 38076835 PMCID: PMC10705695 DOI: 10.21203/rs.3.rs-3640717/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Despite the scale-up of antiretroviral therapy (ART) in South Africa, HIV-1 incidence remains high. The anticipated use of potent integrase strand transfer inhibitors and long-acting injectables aims to enhance viral suppression at the population level and diminish transmission. Nevertheless, pre-existing drug resistance could impede the efficacy of long-acting injectable ART combinations, such as rilpivirine (an NNRTI) and cabotegravir (an INSTI). Consequently, a thorough understanding of transmission networks and geospatial distributions is vital for tailored interventions, including pre-exposure prophylaxis with long-acting injectables. However, empirical data on background resistance and transmission networks remain limited. In a community-based study in rural KwaZulu-Natal (2018-2019), prior to the widespread use of integrase inhibitor-based first-line ART, we performed HIV testing with reflex HIV-1 RNA viral load quantification on 18,025 participants. From this cohort, 6,096 (33.9%) tested positive for HIV via ELISA, with 1,323 (21.7%) exhibiting detectable viral loads (> 40 copies/mL). Of those with detectable viral loads, 62.1% were ART-naïve, and the majority of the treated were on an efavirenz + cytosine analogue + tenofovir regimen. Deep sequencing analysis, with a variant abundance threshold of 20%, revealed NRTI resistance mutations such as M184V in 2% of ART-naïve and 32% of treated individuals. Tenofovir resistance mutations K65R and K70E were found in 12% and 5% of ART-experienced individuals, respectively, and in less than 1% of ART-naïve individuals. Integrase inhibitor resistance mutations were notably infrequent (< 1%). Prevalence of pre-treatment drug resistance to NNRTIs was 10%, predominantly consisting of the K103N mutation. Among those with viraemic ART, NNRTI resistance was 50%, with rilpivirine-associated mutations observed in 9% of treated and 6% of untreated individuals. Cluster analysis revealed that 20% (205/1,050) of those sequenced were part of a cluster. We identified 171 groups with at least two linked participants; three quarters of clusters had only two individuals, and a quarter had 3-6 individuals. Integrating phylogenetic with geospatial analyses, we revealed a complex transmission network with significant clustering in specific regions, notably peripheral and rural areas. These findings derived from population scale genomic analyses are encouraging in terms of the limited resistance to DTG, but indicate that transitioning to long-acting cabotegravir + rilpivirine for transmission reduction should be accompanied by prior screening for rilpivirine resistance. Whole HIV-1 genome sequencing allowed identification of significant proportions of clusters with multiple individuals, and geospatial analyses suggesting decentralised networks can inform targeting public health interventions to effectively curb HIV-1 transmission.
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12
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Wang Z, Wang D, Lin L, Qiu Y, Zhang C, Xie M, Lu X, Lian Q, Yan P, Chen L, Feng Y, Xing H, Wang W, Wu S. Epidemiological characteristics of HIV transmission in southeastern China from 2015 to 2020 based on HIV molecular network. Front Public Health 2023; 11:1225883. [PMID: 37942240 PMCID: PMC10629674 DOI: 10.3389/fpubh.2023.1225883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 10/04/2023] [Indexed: 11/10/2023] Open
Abstract
Objective HIV/AIDS remains a global public health problem, and understanding the structure of social networks of people living with HIV/AIDS is of great importance to unravel HIV transmission, propose precision control and reduce new infections. This study aimed to investigate the epidemiological characteristics of HIV transmission in Fujian province, southeastern China from 2015 to 2020 based on HIV molecular network. Methods Newly diagnosed, treatment-naive HIV/AIDS patients were randomly sampled from Fujian province in 2015 and 2020. Plasma was sampled for in-house genotyping resistance test, and HIV molecular network was created using the HIV-TRACE tool. Factors affecting the inclusion of variables in the HIV molecular network were identified using univariate and multivariate logistic regression analyses. Results A total of 1,714 eligible cases were finally recruited, including 806 cases in 2015 and 908 cases in 2020. The dominant HIV subtypes were CRF01_AE (41.7%) and CRF07_BC (38.3%) in 2015 and CRF07_BC (53. 3%) and CRF01_AE (29.1%) in 2020, and the prevalence of HIV drug resistance was 4.2% in 2015 and 5.3% in 2020. Sequences of CRF07_BC formed the largest HIV-1 transmission cluster at a genetic distance threshold of both 1.5 and 0.5%. Univariate and multivariate logistic regression analyses showed that ages of under 20 years and over 60 years, CRF07_BC subtype, Han ethnicity, sampling in 2015, absence of HIV drug resistance, married with spouse, sampling from three cities of Jinjiang, Nanping and Quanzhou resulted in higher proportions of sequences included in the HIV transmission molecular network at a genetic distance threshold of 1.5% (p < 0.05). Conclusion Our findings unravel the HIV molecular transmission network of newly diagnosed HIV/AIDS patients in Fujian province, southeastern China, which facilitates the understanding of HIV transmission patterns in the province.
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Affiliation(s)
- Zhenghua Wang
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Dong Wang
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liying Lin
- Fuzhou Institute for Disease Control and Prevention of China Railway Nanchang Bureau Group Co., Ltd., Fuzhou, China
| | - Yuefeng Qiu
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Chunyan Zhang
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Meirong Xie
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Xiaoli Lu
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Qiaolin Lian
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Pingping Yan
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Liang Chen
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
| | - Yi Feng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hui Xing
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wei Wang
- National Health Commission Key Laboratory for Parasitic Disease Prevention and Control, Jiangsu Provincial Key Laboratory for Parasites and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China
| | - Shouli Wu
- Fujian Provincial Center for Disease Control and Prevention, Fujian Provincial Key Laboratory of Zoonosis Research, Fuzhou, China
- School of Public Health, Fujian Medical University, Fuzhou, China
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Hong H, Tang C, Liu Y, Jiang H, Fang T, Xu G. HIV-1 drug resistance and genetic transmission network among newly diagnosed people living with HIV/AIDS in Ningbo, China between 2018 and 2021. Virol J 2023; 20:233. [PMID: 37833806 PMCID: PMC10576354 DOI: 10.1186/s12985-023-02193-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND As the HIV epidemic continues to grow, transmitted drug resistance(TDR) and determining relationship of HIV transmission are major barriers to reduce the risk of HIV transmissions.This study aimed to examine the molecular epidemiology and TDR and evaluated the transmission pattern among newly diagnosed people living with HIV/AIDS(PLWHA) in Ningbo city, which could contribute to the development of targeted precision interventions. METHODS Consecutive cross-sectional surveys were conducted in Ningbo City between January 2018 and December 2021. The HIV-1 pol gene region was amplified and sequenced for drug resistance and genetic transmission network analysis. TDR was determined using the Stanford University HIV Drug Resistance Database. Genetic transmission network was visualized using Cytoscape with the genetic distance threshold of 0.013. RESULTS A total of 1006 sequences were sequenced successfully, of which 61 (6.1%) showed evidence of TDR. The most common mutations were K103N (2.3%), E138A/G/Q (1.7%) and V179D/E (1.2%). 12 HIV-1 genotypes were identified, with CRF07_BC being the major genotype (43.3%, 332/767), followed by CRF01_AE (33.7%, 339/1006). 444 (44.1%) pol sequences formed 856 links within 120 transmission clusters in the network. An increasing trend in clustering rate between 2018 and 2021(χ2 = 9.546, P = 0.023) was observed. The odds of older age (≥ 60 years:OR = 2.038, 95%CI = 1.072 ~ 3.872, compared to < 25 years), HIV-1 genotypes (CRF07_BC: OR = 2.147, 95%CI = 1.582 ~ 2.914; CRF55_01B:OR = 2.217, 95%CI = 1.201 ~ 4.091, compared to CRF01_AE) were significantly related to clustering. Compared with CRF01_AE, CRF07_BC were prone to form larger clusters. The largest cluster with CRF07_BC was increased from 15 cases in 2018 to 83 cases in 2021. CONCLUSIONS This study revealed distribution of HIV-1 genotypes, and genetic transmission network were diverse and complex in Ningbo city. The prevalence of TDR was moderate, and NVP and EFV were high-level NNRTI resistance. Individuals aged ≥ 60 years old were more easily detected in the networks and CRF07_BC were prone to form rapid growth and larger clusters. These date suggested that surveillance and comprehensive intervention should be designed for key rapid growth clusters to reduce the potential risk factors of HIV-1 transmission.
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Affiliation(s)
- Hang Hong
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China
| | - Chunlan Tang
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China
| | - Yuhui Liu
- Ningbo Center for Disease Control and Prevention, Ningbo, Zhengjiang, 315010, China
| | - Haibo Jiang
- Ningbo Center for Disease Control and Prevention, Ningbo, Zhengjiang, 315010, China
| | - Ting Fang
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China
| | - Guozhang Xu
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China.
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Cao R, Lei S, Chen H, Ma Y, Dai J, Dong L, Jin X, Yang M, Sun P, Wang Y, Zhang Y, Jia M, Chen M. Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China. Epidemiol Infect 2023; 151:e124. [PMID: 37462024 PMCID: PMC10540185 DOI: 10.1017/s0950268823001140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/26/2023] [Accepted: 07/07/2023] [Indexed: 08/05/2023] Open
Abstract
HIV-1 molecular surveillance provides a new approach to explore transmission risks and targeted interventions. From January to June 2021, 663 newly reported HIV-1 cases were recruited in Zhaotong City, Yunnan Province, China. The distribution characteristics of HIV-1 subtypes and HIV-1 molecular network were analysed. Of 542 successfully subtyped samples, 12 HIV-1 strains were identified. The main strains were CRF08_BC (47.0%, 255/542), CRF01_AE (17.0%, 92/542), CRF07_BC (17.0%, 92/542), URFs (8.7%, 47/542), and CRF85_BC (6.5%, 35/542). CRF08_BC was commonly detected among Zhaotong natives, illiterates, and non-farmers and was mostly detected in Zhaoyang County. CRF01_AE was frequently detected among married and homosexual individuals and mostly detected in Weixin and Zhenxiong counties. Among the 516 pol sequences, 187 (36.2%) were clustered. Zhaotong natives, individuals aged ≥60 years, and illiterate individuals were more likely to be found in the network. Assortativity analysis showed that individuals were more likely to be genetically associated when stratified by age, education level, occupation, and reporting area. The genetic diversity of HIV-1 reflects the complexity of local HIV epidemics. Molecular network analyses revealed the subpopulations to focus on and the characteristics of the risk networks. The results will help optimise local prevention and control strategies.
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Affiliation(s)
- Rui Cao
- School of Public Health, Kunming Medical University, Kunming, China
| | - Shouxiong Lei
- Division for AIDS/STD Control and Prevention, Zhaotong Center for Disease Control and Prevention, Zhaotong, China
| | - Huichao Chen
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Yanling Ma
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Jie Dai
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Lijuan Dong
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Xiaomei Jin
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Min Yang
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Pengyan Sun
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Yawen Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Yuying Zhang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Manhong Jia
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Min Chen
- Health Laboratory Center, Yunnan Center for Disease Control and Prevention, Kunming, China
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Zhang J, Xu K, Jiang J, Fan Q, Ding X, Zhong P, Xing H, Chai C, Pan X. Combining molecular network analysis and field epidemiology to quantify local HIV transmission and highlight ongoing epidemics. Int J Infect Dis 2023; 128:187-193. [PMID: 36587840 DOI: 10.1016/j.ijid.2022.12.033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/06/2022] [Accepted: 12/25/2022] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVES This study aimed to establish a collaborative approach to quantify local HIV transmission, which is an issue of great concern to public health. METHODS We linked HIV-1 pol gene sequences to demographic information and epidemiological investigations in Hangzhou (a central city in East China). We estimated local acquisition rates from a collaboration of molecular network analysis (with a distance-based approach) and epidemiological investigations. RESULTS Among 1064 newly diagnosed patients with HIV, 857 pol sequences were acquired and subsequently analyzed. Multiple subtypes were identified, with circulating recombinant form (CRF)07_BC (42.5%) and CRF01_AE (39.2%) predominating, followed by 13 other subtypes and 26 unique recombinant forms. By integrating the molecular network analysis and epidemiological investigations, we estimated that the proportion of local infection was 63.2%. The multivariable analyses revealed that individuals in clusters were more likely to be local residents, be aged 50 years or older, work as farmers, and have a higher first cluster of differentiation 4 count level (P <0.05). The proportions of local acquisitions over 70% were observed in local residents (79.9%, 242/303), individuals aged 50 years or older (73.6%, 181/246), and farmers (75.6%, 99/131). CONCLUSION The molecular network analysis can augment traditional HIV epidemic surveillance. This study establishes a paradigm for quantifying local HIV transmission for generalization in other areas.
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Affiliation(s)
- Jiafeng Zhang
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Ke Xu
- Department of HIV/AIDS Control and Prevention, Hangzhou Municipal Center for Disease Control and Prevention, Hangzhou, China
| | - Jun Jiang
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Qin Fan
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xiaobei Ding
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Ping Zhong
- Shanghai Municipal Center for Diseases Control and Prevention, Shanghai, China
| | - Hui Xing
- Division of Virology and Immunology, National Center for AIDS/STD Control and Prevention (NCAIDS), Beijing, China
| | - Chengliang Chai
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
| | - Xiaohong Pan
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
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Garcia M, Devlin S, Kerman J, Fujimoto K, Hirschhorn LR, Phillips II G, Schneider J, McNulty MC. Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3269. [PMID: 36833963 PMCID: PMC9964218 DOI: 10.3390/ijerph20043269] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/08/2023] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
The rapid implementation of molecular HIV surveillance (MHS) has resulted in significant challenges for local health departments to develop real-time cluster detection and response (CDR) interventions for priority populations impacted by HIV. This study is among the first to explore professionals' strategies to implement MHS and develop CDR interventions in real-world public health settings. Methods: Semi-structured qualitative interviews were completed by 21 public health stakeholders in the United States' southern and midwestern regions throughout 2020-2022 to identify themes related to the implementation and development of MHS and CDR. Results for the thematic analysis revealed (1) strengths and limitations in utilizing HIV surveillance data for real-time CDR; (2) limitations of MHS data due to medical provider and staff concerns related to CDR; (3) divergent perspectives on the effectiveness of partner services; (4) optimism, but reluctance about the social network strategy; and (5) enhanced partnerships with community stakeholders to address MHS-related concerns. Conclusions: Enhancing MHS and CDR efforts requires a centralized system for staff to access public health data from multiple databases to develop CDR interventions; designating staff dedicated to CDR interventions; and establishing equitable meaningful partnerships with local community stakeholders to address MHS concerns and develop culturally informed CDR interventions.
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Affiliation(s)
- Moctezuma Garcia
- Department of Social Work, College of Health & Sciences, San José State University, San Jose, CA 95112, USA
| | - Samantha Devlin
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
| | - Jared Kerman
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
| | - Kayo Fujimoto
- Department of Health Promotion & Behavioral Sciences, University of Texas Health Sciences Center, Houston, TX 77030, USA
| | - Lisa R. Hirschhorn
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Gregory Phillips II
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - John Schneider
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Moira C. McNulty
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
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17
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Yuan D, Zhong X, Li Y, He Q, Li N, Li H, Liu Y, Li L, Zhang L, Yang Y, Liang S. Molecular Transmission Network of Newly Reported HIV Infections in Pengzhou, Sichuan Province: A Study Based on Genomics and Spatial Epidemiology. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2523. [PMID: 36767889 PMCID: PMC9915990 DOI: 10.3390/ijerph20032523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 01/15/2023] [Accepted: 01/28/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVE The objective of this study was to understand the molecular transmission characteristics of newly reported HIV infections in the city of Pengzhou, Sichuan Province, to analyze the risk factors of transmission network and spatial clustering and the transmission characteristics, and to provide a scientific basis for precision prevention and intervention. METHODS Anticoagulated whole blood was collected from newly reported HIV infections in Pengzhou from March 2019 to August 2021. After the plasma was isolated, the HIV-1 pol gene was amplified and sequenced by reverse transcriptase polymerase chain reaction (PCR). The obtained gene sequences were used to construct a maximum likelihood phylogenetic tree for the analysis of virus subtypes, and a molecular transmission network was constructed using the genetic distance method to evaluate the transmission pattern of people living with HIV/AIDS in Pengzhou. A logistic regression model was used to find out the potential risk factors for entering the molecular transmission network with the number of nodes ≥ 2. Spatial analysis is used to show the geographical pattern of the proportion of newly reported HIV infections entering the molecular transmission network, and a flow map is used to show the intensity of transmission within and between townships. RESULTS A total of 463 newly reported HIV-infection sequences were obtained in this study, including 237 cases (51.19%) of CRF01_ AE, 159 cases (34.34%) of CRF07_BC, 45 cases (9.72%) of B, 15 cases (3.24%) of CRF08_BC and 7 cases (1.5%) of others. The number of clusters was the highest when the gene distance was 0.009, with a total of 246 sequences entering the network, forming 54 clusters, and the network entry rate was 55.36%. There were 170 sequences with more than two nodes in the network sequence. The logistic regression showed that compared with age < 50 years old, age ≥ 50 years old has a higher risk of transmission (OR = 3.43, 95% CI = 2.06-5.71); compared with farmers, the risk of transmission within industry is lower (OR = 0.046, 95% CI = 0.25-0.87); and compared with CRF07_BC, CRF01_AE (OR = 6.09, 95% CI = 3.60-10.30) and B (OR = 20.31, 95% CI = 8.94-46.13) had a higher risk of transmission. Men aged ≥ 50 years are mainly clustered with women between 50 and 70 years of age. In addition to being clustered with gay men, there are nine (50%) and three (16.7%) chains of transmission between gay men and heterosexual men and women, respectively. In the geographical space, there is no hot spot clustering of the molecular propagation network. The subtype B was mainly distributed in the town of Tianpeng and formed transmission networks in eastern Pengzhou;0020CRF01_AE is mainly distributed in the town of Lichun and formed transmission networks in the west and north of Pengzhou. CONCLUSION This study reveals the characteristics and influencing factors of molecular network transmission in the region, as well as the spatial transmission characteristics of newly reported HIV infections in recent years, and reveals the geographical differences in HIV-1 transmission. The results provide a scientific basis for the development of local AIDS-specific intervention measures.
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Affiliation(s)
- Dan Yuan
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu 610044, China
| | - Xia Zhong
- School of Management, Chengdu University of Traditional Chinese Medicine/Healthy Sichuan Research Institute, Chengdu 611137, China
| | - Yiping Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu 610044, China
| | - Qinying He
- Center for AIDS/STD Control and Prevention, Chengdu Center for Disease Control and Prevention, Chengdu 610047, China
| | - Na Li
- Center for AIDS/STD Control and Prevention, Pengzhou Center for Disease Control and Prevention, Chengdu 611930, China
| | - Hanqi Li
- Department of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Yang Liu
- Center for AIDS/STD Control and Prevention, Chengdu Center for Disease Control and Prevention, Chengdu 610047, China
| | - Ling Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu 610044, China
| | - Linglin Zhang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu 610044, China
| | - Yi Yang
- School of Management, Chengdu University of Traditional Chinese Medicine/Healthy Sichuan Research Institute, Chengdu 611137, China
| | - Shu Liang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu 610044, China
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18
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Cholette F, Lazarus L, Macharia P, Thompson LH, Githaiga S, Mathenge J, Walimbwa J, Kuria I, Okoth S, Wambua S, Albert H, Mwangi P, Adhiambo J, Kasiba R, Juma E, Battacharjee P, Kimani J, Sandstrom P, Meyers AFA, Joy JB, Thomann M, McLaren PJ, Shaw S, Mishra S, Becker ML, McKinnon L, Lorway R. Community Insights in Phylogenetic HIV Research: The CIPHR Project Protocol. Glob Public Health 2023; 18:2269435. [PMID: 37851872 DOI: 10.1080/17441692.2023.2269435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 10/04/2023] [Indexed: 10/20/2023]
Abstract
Inferring HIV transmission networks from HIV sequences is gaining popularity in the field of HIV molecular epidemiology. However, HIV sequences are often analyzed at distance from those affected by HIV epidemics, namely without the involvement of communities most affected by HIV. These remote analyses often mean that knowledge is generated in absence of lived experiences and socio-economic realities that could inform the ethical application of network-derived information in 'real world' programmes. Procedures to engage communities are noticeably absent from the HIV molecular epidemiology literature. Here we present our team's protocol for engaging community activists living in Nairobi, Kenya in a knowledge exchange process - The CIPHR Project (Community Insights in Phylogenetic HIV Research). Drawing upon a community-based participatory approach, our team will (1) explore the possibilities and limitations of HIV molecular epidemiology for key population programmes, (2) pilot a community-based HIV molecular study, and (3) co-develop policy guidelines on conducting ethically safe HIV molecular epidemiology. Critical dialogue with activist communities will offer insight into the potential uses and abuses of using such information to sharpen HIV prevention programmes. The outcome of this process holds importance to the development of policy frameworks that will guide the next generation of the global response.
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Affiliation(s)
- François Cholette
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Lisa Lazarus
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Pascal Macharia
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - Laura H Thompson
- Sexually Transmitted and Blood-Borne Infections Surveillance Division, Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada, Ottawa, Canada
| | - Samuel Githaiga
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - John Mathenge
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | | | - Irene Kuria
- Key Population Consortium of Kenya, Nairobi, Kenya
| | - Silvia Okoth
- Bar Hostess Empowerment and Support Programme, Nairobi, Kenya
| | | | - Harrison Albert
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - Peninah Mwangi
- Bar Hostess Empowerment and Support Programme, Nairobi, Kenya
| | - Joyce Adhiambo
- Partners for Health Development in Africa (PHDA), Nairobi, Kenya
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
| | | | - Esther Juma
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
| | | | - Joshua Kimani
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
| | - Paul Sandstrom
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Adrienne F A Meyers
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Jeffrey B Joy
- British Columbia Centre for Excellence in HIV/AIDS (BCCfE), St. Paul's Hospital, Vancouver, Canada
- Division of Infectious Diseases, Department of Medicine, University of British Columbia, Vancouver, Canada
- Bioinformatics Programme, University of British Columbia, Vancouver, Canada
| | - Matthew Thomann
- Department of Anthropology, University of Maryland, College Park, MD, USA
| | - Paul J McLaren
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Souradet Shaw
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Sharmistha Mishra
- MAP Centre for Urban Health Solutions, St. Michael's Hospital, Toronto, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Marissa L Becker
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Lyle McKinnon
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
- Centre for the AIDS Programme of Research in South Africa, Durban, South Africa
| | - Robert Lorway
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
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Fan Q, Zhang J, Luo M, Feng Y, Ge R, Yan Y, Zhong P, Ding X, Xia Y, Guo Z, Pan X, Chai C. Molecular Genetics and Epidemiological Characteristics of HIV-1 Epidemic Strains in Various Sexual Risk Behaviour Groups in Developed Eastern China, 2017-2020. Emerg Microbes Infect 2022; 11:2326-2339. [PMID: 36032035 PMCID: PMC9542350 DOI: 10.1080/22221751.2022.2119167] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Qin Fan
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Jiafeng Zhang
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Mingyu Luo
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Yi Feng
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People’s Republic of China
| | - Rui Ge
- Division of AIDS/TB Prevention and Control, Jiaxing Municipal Center for Disease Control and Prevention, Jiaxing 314050, People’s Republic of China
| | - Yong Yan
- Division of AIDS/TB Prevention and Control, Jiaxing Municipal Center for Disease Control and Prevention, Jiaxing 314050, People’s Republic of China
| | - Ping Zhong
- Department of AIDS and STD, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200051, People’s Republic of China
| | - Xiaobei Ding
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Yan Xia
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Zhihong Guo
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Xiaohong Pan
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Chengliang Chai
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
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Zhuoma L, Zhang Y, Yan T, Kang F, Hou X, Chen J, Huang M, Zeng Y, Wang Q, Zhou C, Liang S, Su L. Non-disclosed men who have sex with men within local MSM HIV-1 genetic transmission networks in Guangyuan, China. Front Public Health 2022; 10:956217. [PMID: 36117593 PMCID: PMC9472546 DOI: 10.3389/fpubh.2022.956217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 07/18/2022] [Indexed: 01/24/2023] Open
Abstract
Background Most men who have sex with men (MSM), especially those with HIV infection, do not disclose their same-sex behaviors in China due to Chinese family values and fear of stigmatization, rejection, or prejudice. However, disclosure of same-sex behaviors to healthcare providers (HCPs) can be beneficial for reducing viral transmission and promoting their physical and mental health. In this study, by combining phylogenetic analysis with traditional epidemiological approaches, we tried to identify the MSM who do not disclose to HCPs in transmission networks and explored the factors related to the non-disclosed behaviors. Method Phylogenetic analysis was conducted using HIV pol sequences obtained from the drug-resistant surveillance program, which was collected as part of routine clinical care since 2012. Sequences were linked to the demographic data collected in the Chinese HIV/AIDS Comprehensive Response Information Management System (CRIMS). First, male patients in whom genetic sequences were within the molecular transmission clusters involving self-reported MSM were identified as potential MSM (pMSM). Then, a cross-sectional survey was conducted to supplement behavioral information and attitudes toward MSM. Results Our sample consisted of 190 pMSM patients. In total, 43.16% of the patients were likely to conceal same-sex behaviors during the first-self-report, and 14.73% of patients might continue to conceal a history of same-sex behaviors even after receiving medical care. The pMSM who concealed their same-sex behaviors were reluctant to accept medical services such as Voluntary Counseling and Testing (VCT) and had a lower likelihood of condom use. In addition, the related factors for non-disclosed behavior were associated with current address, income before diagnosis, and attitudes toward MSM. Conclusion Non-disclosure of same-sex behaviors to HCPs may be a major obstacle for certain medical services for MSM who exhibit risky sexual behaviors. The pMSM from developing areas, with high monthly income, and with neutral or un-supportive attitudes toward MSM may represent non-disclosure of their same-sex behaviors. Thus, policies facilitating MSM to disclose their same-sex behaviors are recommended, such as legislations protecting homosexual rights on employment, education, marriage, and so on.
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Affiliation(s)
- Lacuo Zhuoma
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yan Zhang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Tu Yan
- Guangyuan Center for Disease Control and Prevention, Guangyuan, China
| | - Fayang Kang
- Guangyuan Center for Disease Control and Prevention, Guangyuan, China
| | - Xueqin Hou
- Guangyuan Center for Disease Control and Prevention, Guangyuan, China
| | - Jianguo Chen
- Guangyuan Center for Disease Control and Prevention, Guangyuan, China
| | - Min Huang
- Lizhou District Center for Disease Control and Prevention, Guangyuan, China
| | - Yali Zeng
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Qiushi Wang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Chang Zhou
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Shu Liang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Ling Su
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China,*Correspondence: Ling Su
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21
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Jiang H, Lan G, Zhu Q, Liang S, Li J, Feng Y, Lin M, Xing H, Shao Y. Non-student young men put students at high risk of human immunodeficiency virus acquisition in Guangxi, China: a phylogenetic analysis of surveillance data. Open Forum Infect Dis 2022; 9:ofac042. [PMID: 35198650 PMCID: PMC8860155 DOI: 10.1093/ofid/ofac042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 01/24/2022] [Indexed: 11/27/2022] Open
Abstract
Background We sought to identify students and their sexual partners in a molecular transmission network. Methods We obtained 5996 HIV protease and reverse transcriptase gene sequences in Guangxi (165 from students and 5831 from the general populations) and the relevant demographic data. We constructed a molecular transmission network and introduced a permutation test to assess the robust genetic linkages. We calculated the centrality measures to describe the transmission patterns in clusters. Results At the network level, 68 (41.2%) students fell within the network across 43 (8.1%) clusters. Of 141 genetic linkages between students and their partners, only 25 (17.7%) occurred within students. Students were more likely than random permutations to link to other students (odds ratio [OR], 7.2; P < .001), private company employees aged 16–24 years (OR, 3.3; P = .01), private company or government employees aged 25–49 years (OR, 1.7; P = .03), and freelancers or unemployed individuals aged 16–24 years (OR, 5.0; P < .001). At the cluster level, the median age of nonstudents directly linked to students (interquartile range) was 25 (22–30) years, and 80.3% of them had a high school or higher education background. Compared with students, they showed a significantly higher median degree (4.0 vs 2.0; P < .001) but an equivalent median Eigenvector Centrality (0.83 vs 0.81; P = .60). Conclusions The tendency of genetic linkage between students and nonstudent young men and their important position in the HIV transmission network emphasizes the urgent need for 2-pronged public health interventions based on both school and society.
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Affiliation(s)
- He Jiang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Shujia Liang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Jianjun Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Yi Feng
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mei Lin
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Hui Xing
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yiming Shao
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
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22
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Fujimoto K, Paraskevis D, Kuo JC, Hallmark CJ, Zhao J, Hochi A, Kuhns LM, Hwang LY, Hatzakis A, Schneider JA. Integrated molecular and affiliation network analysis: Core-periphery social clustering is associated with HIV transmission patterns. SOCIAL NETWORKS 2022; 68:107-117. [PMID: 34262236 PMCID: PMC8274587 DOI: 10.1016/j.socnet.2021.05.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
This study investigates the two-mode core-periphery structures of venue affiliation networks of younger Black men who have sex with men (YBMSM). We examined the association between these structures and HIV phylogenetic clusters, defined as members who share highly similar HIV strains that are regarded as a proxy for sexual affiliation networks. Using data from 114 YBMSM who are living with HIV in two large U.S. cities, we found that HIV phylogenetic clustering patterns were associated with social clustering patterns whose members share affiliation with core venues that overlap with those of YBMSM. Distinct HIV transmission patterns were found in each city, a finding that can help to inform tailored venue-based and network intervention strategies.
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Affiliation(s)
- Kayo Fujimoto
- Department of Health Promotion, The University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX 77030
| | - Dimitrios Paraskevis
- Department of Hygiene, Epidemiology, and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Jacky C. Kuo
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Houston, TX 77030
| | | | - Jing Zhao
- Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030
| | - Andre Hochi
- Department of Health Promotion, The University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX 77030
| | - Lisa M Kuhns
- Division of Adolescent Medicine, Ann & Robert H. Lurie Children’s Hospital, and Northwestern University, Feinberg School of Medicine, Department of Pediatrics, 225 E. Chicago Avenue, #161, Chicago, IL 60611
| | - Lu-Yu Hwang
- Department of Epidemiology, Human Genetics, and Environmental Science, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Houston, TX 77030
| | - Angelos Hatzakis
- Department of Hygiene, Epidemiology, and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - John A. Schneider
- Department of Medicine and Public Health Sciences and the Chicago Center for HIV Elimination, University of Chicago, 5837 South Maryland Avenue MC 5065, Chicago, IL 60637
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23
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van Zyl GU. New Technological Developments in Identification and Monitoring of New and Emerging Infections. ENCYCLOPEDIA OF INFECTION AND IMMUNITY 2022. [PMCID: PMC8291697 DOI: 10.1016/b978-0-12-818731-9.00094-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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24
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Zheng S, Wu J, Hu Z, Gan M, Liu L, Song C, Lei Y, Wang H, Liao L, Feng Y, Shao Y, Ruan Y, Xing H. Epidemiology and Molecular Transmission Characteristics of HIV in the Capital City of Anhui Province in China. Pathogens 2021; 10:pathogens10121554. [PMID: 34959509 PMCID: PMC8708547 DOI: 10.3390/pathogens10121554] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 11/19/2021] [Accepted: 11/25/2021] [Indexed: 01/29/2023] Open
Abstract
Hefei, Anhui province, is one of the cities in the Yangtze River Delta, where many people migrate to Jiangsu, Zhejiang and Shanghai. High migration also contributes to the HIV epidemic. This study explored the HIV prevalence in Hefei to provide a reference for other provinces and assist in the prevention and control of HIV in China. A total of 816 newly reported people with HIV in Hefei from 2017 to 2020 were recruited as subjects. HIV subtypes were identified by a phylogenetic tree. The most prevalent subtypes were CRF07_BC (41.4%), CRF01_AE (38.1%) and CRF55_01B (6.3%). Molecular networks were inferred using HIV-TRACE. The largest and most active transmission cluster was CRF55_01B in Hefei’s network. A Chinese national database (50,798 sequences) was also subjected to molecular network analysis to study the relationship between patients in Hefei and other provinces. CRF55_01B and CRF07_BC-N had higher clustered and interprovincial transmission rates in the national molecular network. People with HIV in Hefei mainly transmitted the disease within the province. Finally, we displayed the epidemic trend of HIV in Hefei in recent years with the dynamic change of effective reproductive number (Re). The weighted overall Re increased rapidly from 2012 to 2015, with a peak value of 3.20 (95% BCI, 2.18–3.85). After 2015, Re began to decline and remained stable at around 1.80. In addition, the Re of CRF55_01B was calculated to be between 2.0 and 4.0 in 2018 and 2019. More attention needs to be paid to the rapid spread of CRF55_01B and CRF07_BC-N strains among people with HIV and the high Re in Hefei. These data provide necessary support to guide the targeted prevention and control of HIV.
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Affiliation(s)
- Shan Zheng
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Jianjun Wu
- Anhui Provincial Center for Disease Control and Prevention, Hefei 230601, China;
| | - Zhongwang Hu
- Hefei Center for Disease Control and Prevention, Hefei 230061, China; (Z.H.); (Y.L.); (H.W.)
| | - Mengze Gan
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Lei Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Chang Song
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yanhua Lei
- Hefei Center for Disease Control and Prevention, Hefei 230061, China; (Z.H.); (Y.L.); (H.W.)
| | - Hai Wang
- Hefei Center for Disease Control and Prevention, Hefei 230061, China; (Z.H.); (Y.L.); (H.W.)
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yi Feng
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
- Correspondence:
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25
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Ge Z, Feng Y, Zhang H, Rashid A, Zaongo SD, Li K, Yu Y, Lv B, Sun J, Liang Y, Xing H, Sönnerborg A, Ma P, Shao Y. HIV-1 CRF07_BC transmission dynamics in China: two decades of national molecular surveillance. Emerg Microbes Infect 2021; 10:1919-1930. [PMID: 34498547 PMCID: PMC8477959 DOI: 10.1080/22221751.2021.1978822] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
By analyzing an unprecedentedly large, longitudinal HIV-1 CRF07_BC sequence dataset collected from China in the past two decades, we sought to build CRF07_BC lengthwise transmission networks, and understand its transmission dynamics. We divided CRF07_BC into two clusters based on phylogenetic analysis and an estimation of the pairwise genetic distance at 0.7%. Of 6213 sequences, 3607 (58.1%) linked to ≥1 other sequence. CRF07_BC was divided into two clusters: 07BC_O and 07BC_N. The 07BC_O is the original CRF07_BC, circulating in people who inject drugs (PWID) and heterosexuals, predominantly in southwestern and northwestern provinces of China. The 07BC_N is a new cluster, identified mostly in men having sex with men (MSM) in the northern provinces of China. Bayesian analysis indicates that CRF07_BC has experienced two phases of exponential growth, which was first driven by 07BC_O then 07BC_N. Compared to 07BC_O, the proportion of the parameter of population transmission risk (TR) of 07BC_N has risen constantly. The power-law function analyses reveal that 07BC_N has increased over years with higher degree. In 07BC_N, only 13.16% of MSM were linked to other risk groups, but these links represent 41.45%, 54.25%, and 55.07% of links among heterosexual females, heterosexual males, and male PWID respectively. This study indicates that CRF07_BC has evolved into two clusters in China, and their distributions are distinct across risk groups and geographical regions. 07BC_N shows a greater risk of transmission, and has gradually replaced 07BC_O. Furthermore, the results show that strengthening the MSM interventions could lower the rapidity of 07BC_N transmission in all risk groups.
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Affiliation(s)
- Zhangwen Ge
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.,Department of Laboratory Medicine, Guizhou Provincial People's Hospital, Affiliated Hospital of Guizhou University, Guiyang, People's Republic of China.,School of Medicine, Nankai University, Tianjin, People's Republic of China
| | - Yi Feng
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Hua Zhang
- Department of Laboratory Medicine, Guizhou Provincial People's Hospital, Affiliated Hospital of Guizhou University, Guiyang, People's Republic of China
| | - Abdur Rashid
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.,School of Medicine, Nankai University, Tianjin, People's Republic of China
| | - Silvere D Zaongo
- Department of Infectious Diseases, Nankai University Second People's Hospital, Tianjin Second People's Hospital, Tianjin, People's Republic of China
| | - Kang Li
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Yueyang Yu
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.,School of Medicine, Nankai University, Tianjin, People's Republic of China
| | - Bowen Lv
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Jia Sun
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.,State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - Yanling Liang
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Hui Xing
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Anders Sönnerborg
- Division of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ping Ma
- Department of Infectious Diseases, Nankai University Second People's Hospital, Tianjin Second People's Hospital, Tianjin, People's Republic of China
| | - Yiming Shao
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.,School of Medicine, Nankai University, Tianjin, People's Republic of China.,State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
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26
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Fan Q, Zhang J, Luo M, Yao J, Ge R, Yan Y, Ding X, Chen W, Pan X. Analysis of the Driving Factors of Active and Rapid Growth Clusters Among CRF07_BC-Infected Patients in a Developed Area in Eastern China. Open Forum Infect Dis 2021; 8:ofab051. [PMID: 33728360 PMCID: PMC7944347 DOI: 10.1093/ofid/ofab051] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 01/29/2021] [Indexed: 11/22/2022] Open
Abstract
Background The purpose of this study was to research the molecular transmission and genetic evolutionary characteristics among CRF07_BC-infected patients in a developed area in Eastern China. Methods Plasma samples from newly diagnosed HIV-1-positive patients from 2015–2018 and basic demographic and epidemiological information were obtained. Pol sequences from CRF07_BC-infected patients were selected for phylogenetic, molecular transmission network, and Bayesian evolutionary analyses. Results Pol sequences were successfully obtained from 258 samples of CRF07_BC. Phylogenetic analysis revealed 2 distinct lineages: lineage 1 (66.3%, 171/258), primarily from men who have sex with men (MSM) and some heterosexual individuals, and lineage 2 (33.7%, 87/258), primarily from heterosexual individuals. Under an optimal genetic distance of 0.01 substitutions/site, 163 individuals (63.2%, 163/258) formed 23 groups comprising 6 clusters and 17 dyads in the networks. A distinctly large and rapidly growing cluster (C1) containing 105 individuals was identified, in which MSM with ≥4 links had quite a high transmission risk (low educational background, active sexual behavior, low sexual protection awareness, etc.). According to Bayesian analyses, most C1 clades formed from 2005 to 2009, most of which were closely geographically related to CRF07_BC epidemic strains from Anhui province. Conclusions Here, we elucidated the local transmission characteristics and epidemic pattern of HIV-1 CRF07_BC, revealing that MSM (especially with ≥4 links) may be a significant driver in the formation of active and rapid growth networks in regional CRF07_BC epidemics. Thus, unique region– and risk group–specific transmission network analysis based on a molecular approach can provide critical and insightful information for more effective intervention strategies to limit future HIV-1 transmission.
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Affiliation(s)
- Qin Fan
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Jiafeng Zhang
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Mingyu Luo
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Jiaming Yao
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Rui Ge
- Division of AIDS/TB Prevention and Control, Jiaxing Municipal Center for Disease Control and Prevention, Jiaxing, China
| | - Yong Yan
- Division of AIDS/TB Prevention and Control, Jiaxing Municipal Center for Disease Control and Prevention, Jiaxing, China
| | - Xiaobei Ding
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Wanjun Chen
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xiaohong Pan
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
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27
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Dong ZL, Gao GF, Lyu F. Advances in research of HIV transmission networks. Chin Med J (Engl) 2020; 133:2850-2858. [PMID: 33273335 PMCID: PMC10631577 DOI: 10.1097/cm9.0000000000001155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Indexed: 11/26/2022] Open
Abstract
Transmission network analysis is a crucial evaluation tool aiming to explore the characteristics of the human immunodeficiency virus epidemic, develop evidence-based prevention strategies, and contribute to various areas of human immunodeficiency virus/acquired immunodeficiency syndrome prevention and control. Over recent decades, transmission networks have made tremendous strides in terms of modes, methods, applications, and various other aspects. Transmission network methods, including social, sexual, and molecular transmission networks, have played a pivotal role. Each transmission network research method has its advantages, as well as its limitations. In this study, we established a systematic review of these aforementioned transmission networks with respect to their definitions, applications, limitations, recent progress, and synthetic applications.
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Affiliation(s)
- Zhi-Long Dong
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - George Fu Gao
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Fan Lyu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
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28
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Liu M, Han X, Zhao B, An M, He W, Wang Z, Qiu Y, Ding H, Shang H. Dynamics of HIV-1 Molecular Networks Reveal Effective Control of Large Transmission Clusters in an Area Affected by an Epidemic of Multiple HIV Subtypes. Front Microbiol 2020; 11:604993. [PMID: 33281803 PMCID: PMC7691493 DOI: 10.3389/fmicb.2020.604993] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 10/27/2020] [Indexed: 01/20/2023] Open
Abstract
This study reconstructed molecular networks of human immunodeficiency virus (HIV) transmission history in an area affected by an epidemic of multiple HIV-1 subtypes and assessed the efficacy of strengthened early antiretroviral therapy (ART) and regular interventions in preventing HIV spread. We collected demographic and clinical data of 2221 treatment-naïve HIV-1–infected patients in a long-term cohort in Shenyang, Northeast China, between 2008 and 2016. HIV pol gene sequencing was performed and molecular networks of CRF01_AE, CRF07_BC, and subtype B were inferred using HIV-TRACE with separate optimized genetic distance threshold. We identified 168 clusters containing ≥ 2 cases among CRF01_AE-, CRF07_BC-, and subtype B-infected cases, including 13 large clusters (≥ 10 cases). Individuals in large clusters were characterized by younger age, homosexual behavior, more recent infection, higher CD4 counts, and delayed/no ART (P < 0.001). The dynamics of large clusters were estimated by proportional detection rate (PDR), cluster growth predictor, and effective reproductive number (Re). Most large clusters showed decreased or stable during the study period, indicating that expansion was slowing. The proportion of newly diagnosed cases in large clusters declined from 30 to 8% between 2008 and 2016, coinciding with an increase in early ART within 6 months after diagnosis from 24 to 79%, supporting the effectiveness of strengthened early ART and continuous regular interventions. In conclusion, molecular network analyses can thus be useful for evaluating the efficacy of interventions in epidemics with a complex HIV profile.
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Affiliation(s)
- Mingchen Liu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Xiaoxu Han
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Bin Zhao
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Minghui An
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Wei He
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Zhen Wang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Yu Qiu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Haibo Ding
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Hong Shang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
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