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Shen M, Xiao Y, Rong L, Zhuang G, Song C, Zhao Q, Huang J, Zhu Q, Liang S, Chen H, Li J, Liao L, Shao Y, Xing H, Ruan Y, Lan G. The impact of attrition on the transmission of HIV and drug resistance. AIDS 2023; 37:1137-1145. [PMID: 36927994 DOI: 10.1097/qad.0000000000003528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
BACKGROUND Attrition due to loss to follow-up or termination of antiretroviral therapy (ART) among HIV-infected patients in care may increase the risk of emergence and transmission of drug resistance (TDR), diminish benefit of treatment, and increase morbidity and mortality. Understanding the impact of attrition on the epidemic is essential to provide interventions for improving retention in care. METHODS We developed a comprehensive HIV transmission dynamics model by considering CD4 + cell count dependent diagnosis, treatment, and attrition involving TDR and acquired drug resistance. The model was calibrated by 11 groups HIV/AIDS surveillance data during 2008-2018 from Guangxi, China, and validated by the prevalence of TDR among diagnosed treatment-naive individuals. We aimed to investigate how attrition would affect the transmission of HIV and drug-resistance when expanding ART. RESULTS In the base case with CD4 + cell count dependent per capita attrition rates 0.025∼0.15 and treatment rates 0.23∼0.42, we projected cumulative total new infections, new drug-resistant infections, and HIV-related deaths over 2022-2030 would be 145 391, 7637, and 51 965, respectively. Increasing treatment rates by 0.1∼0.2 can decrease the above total new infections (deaths) by 1.63∼2.93% (3.52∼6.16%). However, even 0.0114∼0.0220 (0.0352∼0.0695) increase in attrition rates would offset this benefit of decreasing infections (deaths). Increasing treatment rates (attrition rates) by 0.05∼0.1 would increase the above drug-resistant infections by 0.16∼0.30% (22.18∼41.15%). CONCLUSION A minor increase in attrition can offset the benefit of treatment expansion and increase the transmission of HIV drug resistance. Reducing attrition rates for patients already in treatment may be as important as expanding treatment for untreated patients.
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Affiliation(s)
- Mingwang Shen
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi
| | - Yanni Xiao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Libin Rong
- Department of Mathematics, University of Florida, Gainesville, Florida, USA
| | - Guihua Zhuang
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi
| | - Chang Song
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
| | - Quanbi Zhao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
| | - Jinghua Huang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Shujia Liang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Huanhuan Chen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Jianjun Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
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2
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Hou Z, Jiang Y, Zhang L, Tu A, Liu T, Du X, Dai C, Xu Y, Qiao R, Tan J. Characterization and Recombinant Genotypes of HIV-1 in Gansu Province, China. AIDS Res Hum Retroviruses 2021; 37:946-953. [PMID: 34107769 DOI: 10.1089/aid.2021.0008] [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: 11/12/2022] Open
Abstract
It is important to monitor the diversity and evolution of HIV-1 genotypes, especially in some remote and undeveloped regions in China where the diversity and distribution of HIV-1 genotypes are not fully clear. To investigate the genotypes and distribution of HIV-1 in far Northwestern Gansu Province of China, we selected 220 HIV-1-positive plasma samples from the Center for Disease Control and Prevention (CDC) in Gansu from January 2016 to December 2018. The viral load of inclusion samples were over 1,000 copies per milliliter. The gag, pol, and env gene of HIV-1 were amplified by nested reverse transcription-polymerase chain reaction kit, sequenced, and then identified genotypes using HIV-BLAST tool and the neighbor-joining method. One hundred fifty of 220 inclusion samples were successfully determined HIV-1 genotypes. Our results show that circulating recombinant forms (CRF) 07_BC and CRF01_AE are predominant and accounted for 46.7% and 28.0%, respectively. Other HIV-1 subtypes and genotypes included B/B' (6.0%), CRF08_BC (4.0%), and C (1.3%). In addition, we reported CRF65_cpx and CRF55_01B subtypes in Gansu for the first time. Phylogenetic tree analysis showed that the sequences of different samples are scattered in different genotype groups, and no obvious aggregation occurs. Our results indicate the genetic variety and complexity of HIV-1 and provide critical information for HIV/AIDS control and prevention in Gansu Province.
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Affiliation(s)
- Zongjie Hou
- Gansu Provincial Key Laboratory of Evidence Based Medicine and Clinical Translation and Department of Immunology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Yu Jiang
- Gansu Provincial Key Laboratory of Evidence Based Medicine and Clinical Translation and Department of Immunology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Lincai Zhang
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | - Aixia Tu
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | - Ting Liu
- Gansu Provincial Key Laboratory of Evidence Based Medicine and Clinical Translation and Department of Immunology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- Department of Geriatrics, the First School of Clinical Medicine, Lanzhou University, Lanzhou, China
| | - Xiufen Du
- Gansu Provincial Key Laboratory of Evidence Based Medicine and Clinical Translation and Department of Immunology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Chen Dai
- Gansu Provincial Key Laboratory of Evidence Based Medicine and Clinical Translation and Department of Immunology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Yaning Xu
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | - Ruijuan Qiao
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | - Jiying Tan
- Gansu Provincial Key Laboratory of Evidence Based Medicine and Clinical Translation and Department of Immunology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
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Zhang F, Liang B, Liang X, Lin Z, Yang Y, Liang N, Yang Y, Liang H, Jiang J, Huang J, Huang R, Zhong S, Qin C, Jiang J, Ye L, Liang H. Using Molecular Transmission Networks to Reveal the Epidemic of Pretreatment HIV-1 Drug Resistance in Guangxi, China. Front Genet 2021; 12:688292. [PMID: 34567064 PMCID: PMC8460771 DOI: 10.3389/fgene.2021.688292] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 06/29/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction Pretreatment drug resistance (PDR) is becoming an obstacle to the success of ART. This study investigated the prevalence of PDR and the transmission clusters (TCs) of drug resistance mutations (DRMs) in two cities where drug abuse used to be high to describe the local HIV-1 transmission dynamics. Methods Plasma samples were obtained from 1,027 ART-naïve patients in Guangxi. Viral subtypes and DRMs were identified. Transmission network and related factors were also determined. Results A total of 1,025 eligible sequences were obtained from Qinzhou (65.8%) and Baise (34.2%) cities. The predominant HIV-1 genotype was CRF08_BC (45.0%), followed by CRF01_AE (40.9%). The overall prevalence of PDR was 8.3%, and resistance to NNRTI was the most common. Putative links with at least one other sequence were found in 543/1,025 (53.0%) sequences, forming 111 clusters (2–143 individuals). The most prevalent shared DRMs included V106I (45.35%), V179D (15.1%), and V179E (15.1%). Clusters related to shared DRMs were more frequent and larger in CRF08_BC. The prevalence of shared DRMs increased with time, while the proportion of PDR gradually decreased. Age > 50 years was associated with clustering. Subtype CRF08_BC was more likely to have DRMs, PDR propagation, and DRM sharing. Conclusion PDR prevalence is moderate in this region. The association between PDR and subtype CRF08_BC suggested that DRMs spreading from injection drug users (IDUs) to heterosexuals (HETs) might be the major source of PDR in this region. Our findings highlight the significance of continuous surveillance of PDR.
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Affiliation(s)
- Fei Zhang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Bingyu Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Science Institute, Guangxi Medical University, Nanning, China
| | - Xu Liang
- Baise Center for Disease Control and Prevention, Baise, China
| | - Zhaosen Lin
- Qinzhou Center for Disease Control and Prevention, Qinzhou, China
| | - Yuan Yang
- Guangxi Collaborative Innovation Center for Biomedicine, Life Science Institute, Guangxi Medical University, Nanning, China
| | - Na Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Yao Yang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Huayue Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Jiaxiao Jiang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Jiegang Huang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Rongye Huang
- Qinzhou Center for Disease Control and Prevention, Qinzhou, China
| | - Shanmei Zhong
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Cai Qin
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China
| | - Junjun Jiang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Science Institute, Guangxi Medical University, Nanning, China
| | - Li Ye
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Science Institute, Guangxi Medical University, Nanning, China
| | - Hao Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Science Institute, Guangxi Medical University, Nanning, China
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4
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Pang X, Tang K, He Q, Huang J, Fang N, Zhou X, Zhu Q, Wu X, Shen Z, Liang S. HIV drug resistance and HIV transmission risk factors among newly diagnosed individuals in Southwest China. BMC Infect Dis 2021; 21:160. [PMID: 33557775 PMCID: PMC7871613 DOI: 10.1186/s12879-021-05854-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 01/28/2021] [Indexed: 12/20/2022] Open
Abstract
Background The widespread use of antiretroviral therapy (ART) has resulted in the development of transmitted drug resistance (TDR), which reduces ART efficacy. We explored TDR prevalence and its associated risk factors in newly diagnosed individuals in Guangxi. Methods We enrolled 1324 participants who were newly diagnosed with HIV-1 and had not received ART at voluntary counselling and testing centres (VCT) in Guangxi, China, who had not received ART. Phylogenetic relationship, transmission cluster, and genotypic drug resistance analyses were performed using HIV-1 pol sequences. We analysed the association of demographic and virological factors with TDR. Results In total, 1151 sequences were sequenced successfully, of which 83 (7.21%) showed evidence of TDR. Multivariate logistic regression analysis revealed that there was significant difference between the prevalence of TDR and unmarried status (adjusted odds ratio (aOR) = 2.41, 95% CI: 1.23–4.71), and CRF08_BC subtype (aOR = 2.03, 95% CI: 1.13–3.64). Most cases of TDR were related to resistance to non-nucleoside reverse transcriptase inhibitors (4.87%) and V179E was the most common mutation detected. We identified a total of 119 HIV transmission clusters (n = 585, 50.8%), of which 18 (15.1%) clusters showed evidence of TDR (36, 41.86%). Three clusters were identified that included drug-resistant individuals having a transmission relationship with each other. The following parameters were associated with TDR transmission risk: Unmarried status, educational level of junior high school or below, and CRF08_BC subtype may be a risk of the transmission of TDR. Conclusions Our findings indicated that moderate TDR prevalence and highlighted the importance of continuous TDR monitoring and designing of strategies for TDR mitigation.
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Affiliation(s)
- Xianwu Pang
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China.,Guangxi Collaborative Innovation Center for Biomedicine, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Kailing Tang
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China
| | - Qin He
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China
| | - Jinghua Huang
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China
| | - Ningye Fang
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China
| | - Xinjuan Zhou
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China
| | - Qiuying Zhu
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China
| | - Xiuling Wu
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China
| | - Zhiyong Shen
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China.
| | - Shujia Liang
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, 530028, Guangxi, China.
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5
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Patterns and risk of HIV-1 transmission network among men who have sex with men in Guangxi, China. Sci Rep 2021; 11:513. [PMID: 33436843 PMCID: PMC7803972 DOI: 10.1038/s41598-020-79951-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 12/14/2020] [Indexed: 11/08/2022] Open
Abstract
The prevalence of HIV-1 in Guangxi is very high, and the rate of HIV-1 infection among men who have sex with men (MSM) has been increasing. Therefore, it is necessary to explore the patterns and risk factors of HIV transmission in Guangxi. For this purpose, individuals diagnosed with HIV-1 during 2013-2018 in Guangxi were recruited. Phylogenetic relationship, transmission clusters, and genotypic drug resistance analyses were performed based on HIV-1 pol sequences. Related factors were analysed to assess for their association with HIV-1 transmission. CRF07_BC (50.4%) and CRF01_AE (33.4%) were found to be the predominant subtypes. The analysed 1633 sequences (50.15%, Guangxi; 49.85%, other provinces) were segregated into 80 clusters (size per cluster, 2-704). We found that 75.3% of the individuals were in three clusters (size ˃ 100), and 73.8% were high-risk spreaders (links ≥ 4). Infection time, marital status, and subtype were significantly associated with HIV-1 transmission. Additionally, 80.2% of recent infections were linked to long-term infections, and 46.2% were linked to other provinces. A low level of transmitted drug resistance was detected (4.8%). Our findings indicated superclusters and high-risk HIV-1 spreaders among the MSM in Guangxi. Effective strategies blocking the route of transmission should be developed.
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Cao Z, Li J, Chen H, Song C, Shen Z, Zhou X, Lan G, Zhu Q, Liang S, Xing H, Liao L, Feng Y, Shao Y, Ruan Y. Effects of HIV-1 genotype on baseline CD4+ cell count and mortality before and after antiretroviral therapy. Sci Rep 2020; 10:15875. [PMID: 32985559 PMCID: PMC7522205 DOI: 10.1038/s41598-020-72701-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 09/04/2020] [Indexed: 02/07/2023] Open
Abstract
To assess whether human immunodeficiency virus type 1 (HIV-1) genotype influences baseline CD4+ T lymphocyte (CD4+) cell count and mortality of patients. The study was conducted from 2014 to 2019 in Guangxi, China, and included 2845 newly diagnosed HIV patients. We used a median regression model to compare CD4+ cell counts in patients newly diagnosed with different HIV-1 genotypes, and a Cox regression model to analyze the associations between HIV-1 genotypes and mortality before and after antiretroviral treatment (ART). In newly diagnosed HIV patients, the baseline CD4+ cell counts of patients with CRF01_AE were significantly lower than those of patients with CRF07_BC, CRF08_BC, and other genotypes. Compared with CRF01_AE, patients infected with CRF07_BC (hazard ratio, 0.55; 95% CI 0.36–0.85), CRF08_BC (hazard ratio, 0.67; 95% CI 0.52–0.85), or other genotypes (hazard ratio, 0.52; 95% CI 0.29–0.94) had significantly lower mortality rates before ART. There were no significant associations between different HIV-1 genotypes and mortality after ART. HIV-1 genotype significantly influences baseline CD4+ cell count and mortality before ART in newly diagnosed HIV patients. We find no significant difference in the outcome of death after ART in patients with different HIV-1 genotypes.
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Affiliation(s)
- Zhiqiang Cao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Jianjun Li
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, China
| | - Huanhuan Chen
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, China
| | - Chang Song
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Zhiyong Shen
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, China
| | - Xinjuan Zhou
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, China
| | - Guanghua Lan
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, China
| | - Qiuying Zhu
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, China
| | - Shujia Liang
- Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control, Nanning, China
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yi Feng
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China.
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7
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Chen H, Luo L, Pan SW, Lan G, Zhu Q, Li J, Zhu J, Chen Y, Shen Z, Ge X, Tang Z, Xing H, Shao Y, Ruan Y, Yang W. HIV Epidemiology and Prevention in Southwestern China: Trends from 1996-2017. Curr HIV Res 2020; 17:85-93. [PMID: 31269884 PMCID: PMC6806534 DOI: 10.2174/1570162x17666190703163838] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 05/29/2019] [Accepted: 06/27/2019] [Indexed: 12/17/2022]
Abstract
The aim of this review is to describe long-term HIV epidemiology and prevention trends in Guangxi, a provincial-level region located along a major drug trafficking corridor in southwestern China. Between 1996 and 2006, HIV transmission in Guangxi was primarily fueled by Injection Drug Use (IDU). Since 2006, heterosexual sex has become the dominant mode of HIV transmission, followed by drug injection. Moreover, older, heterosexual adults appear to be at increased risk for HIV. The vast majority of new HIV cases are attributed to local HIV subtypes already circulating within Guangxi (93%), though imported subtypes are associated with younger age groups. Since 2011, HIV incidence in Guangxi has stabilized, due in part to HIV prevention efforts that include expanded HIV testing, antiretroviral treatment, and other intervention measures. Between 1996 and 2017, Guangxi, China experienced dramatic changes in the primary HIV transmission mode and at-risk age group. Due in part to local and National AIDS control and prevention campaigns, HIV incidence trends in Guangxi no longer appear to be increasing.
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Affiliation(s)
- Huanhuan Chen
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Liuhong Luo
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Stephen W Pan
- Department of Health and Environmental Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China
| | - Guanghua Lan
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Qiuying Zhu
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Jianjun Li
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Jinhui Zhu
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Yi Chen
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Zhiyong Shen
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Xianming Ge
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Zhenzhu Tang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yiming Shao
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.,State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yuhua Ruan
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.,State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Wenmin Yang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
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8
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Chen R, Liang B, Wen B, Huang G, Ning C, Lao C, Jiang J, Liu J, Zhou B, Huang J, Chen J, Zang N, Liao Y, Mo D, Ye L, Liang H. No Difference in Prevalence of Transmitted Drug Resistance between Injection Drug Users and Non-Injection Drug Users: A Cross-Sectional Study among Antiretroviral Treatment-Naïve HIV Patients. Intervirology 2019; 61:281-291. [PMID: 31018203 DOI: 10.1159/000499367] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Accepted: 02/17/2019] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES The epidemiological evidence is inconsistent about whether HIV-positive injection drug users (IDUs) are at higher risk of developing antiretroviral resistance than any other HIV-positive populations. This study aims to investigate and compare transmitted drug resistance (TDR) between IDUs and non-IDUs in Lingshan County, an HIV-hit region in Guangxi, China, where IDU and heterosexual transmission were the two dominant transmission routes and roughly equally contributed to the local HIV transmission. METHODS A cross-sectional study was conducted among newly diagnosed and antiretroviral-treatment (ART)-naïve HIV-1 patients from Lingshan County. The pol gene of HIV-1 from the individuals was sequenced followed by genotyping and TDR analysis. RESULTS Two dominant transmission routes, heterosexual contact and IDU, accounted for 49.2 and 45.9% of 183 HIV-1 infection cases, respectively. Three genotypes, including CRF08_BC (70.6%), CRF01_AE (24.4%), and CRF07_BC (5.0%), and three unique recombinant forms (1.6%), were identified. There was a significant difference in genotype distribution among the different transmission routes (F = 21.814, p < 0.001). The overall TDR prevalence was 5.5%. There were no significant differences in TDR prevalence among the different transmission routes (F = 1.420, p = 0.439). CONCLUSIONS Injection drug use has little impact on TDR prevalence compared with other routes of transmission.
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Affiliation(s)
- Rongfeng Chen
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Bingyu Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Binbin Wen
- School of Nursing, Guangxi University of Chinese Medicine, Nanning, China
| | - Guanghua Huang
- Department of AIDS Prevention, Lingshan Center for Disease Control and Prevention, Lingshan, China
| | - Chuanyi Ning
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Chengyong Lao
- Department of AIDS Prevention, Lingshan Center for Disease Control and Prevention, Lingshan, China
| | - Junjun Jiang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Jie Liu
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Bo Zhou
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Jiegang Huang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Jinmei Chen
- Department of AIDS Prevention, Lingshan Center for Disease Control and Prevention, Lingshan, China
| | - Ning Zang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Yanyan Liao
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Dongsong Mo
- Department of AIDS Prevention, Lingshan Center for Disease Control and Prevention, Lingshan, China
| | - Li Ye
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China
| | - Hao Liang
- Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China, .,Guangxi Collaborative Innovation Center for Biomedicine, Life Sciences Institute, Guangxi Medical University, Nanning, China,
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9
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Li J, Feng Y, Shen Z, Li Y, Tang Z, Xiong R, Zhang H, Wei J, Zhou X, Deng Y, Fang N, Lan G, Liang S, Zhu Q, Xing H, Ruan Y, Shao Y. HIV-1 Transmissions Among Recently Infected Individuals in Southwest China are Predominantly Derived from Circulating Local Strains. Sci Rep 2018; 8:12831. [PMID: 30150680 PMCID: PMC6110827 DOI: 10.1038/s41598-018-29201-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 06/13/2018] [Indexed: 11/09/2022] Open
Abstract
Although the Guangxi region accounts for 10% of all HIV-1 cases new reported in 2011 in China, the sources of the transmitted HIV-1 strains are virtually unknown. To determine the extent to which recent HIV infections were derived from already circulating local strains as opposed to recently introduced strains, we performed a cross-sectional molecular epidemiological investigation of recent infections across Guangxi during 2012-2013. HIV-1 nucleotide sequences were amplified and sequenced. Phylogenetic analyses of pol gene regions were used to determine HIV-1 transmission source strains. Based on 229 sequences generated, the subtype/CRF distribution was as follows: CRF01_AE (61.1%), CRF07_BC (18.8%), CRF08_BC (16.6%), CRF55_01B (3.1%), and subtype B' (0.4%). In total, 213 of 229 (93.0%) sequenced transmission strains were derived from already-circulating local strains. Multivariate logistic regression analysis showed that only an age of 18-25 years was significantly associated with transmission from outside Guangxi (compared to >25 years, AOR: 5.15, 95% CI: 1.18-22.48, p < 0.01). This is the first study to use a Bayesian discrete phylogeographic approach to analyze transmission source strains in China. Our results provide useful data for designing evidence-based prevention strategies and methods for combating the rapid spread of sexually transmitted HIV in Guangxi.
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Affiliation(s)
- Jianjun Li
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Yi Feng
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control (NCAIDS) and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Zhiyong Shen
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Yingxin Li
- College of Pharmacy, Guangxi Medical University, Nanning, China
| | - Zhenzhu Tang
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China.
| | - Runsong Xiong
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Hongman Zhang
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Jing Wei
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control (NCAIDS) and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Xinjuan Zhou
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Yueqin Deng
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Ningye Fang
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Guanghua Lan
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Shujia Liang
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Qiuying Zhu
- Institute of HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, China
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control (NCAIDS) and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control (NCAIDS) and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control (NCAIDS) and Prevention, Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
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10
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Epidemiological surveillance of HIV-1 transmitted drug resistance among newly diagnosed individuals in Shijiazhuang, northern China, 2014-2015. PLoS One 2018; 13:e0198005. [PMID: 29870534 PMCID: PMC5988301 DOI: 10.1371/journal.pone.0198005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 05/12/2018] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The widespread use of antiretroviral therapy (ART) has led to considerable concerns about the prevalence of transmitted drug resistance (TDR). Sexual contact, particularly men who have sex with men (MSM) was the most prevalent form of HIV transmission in Shijiazhuang. Hence, we conducted an epidemiological surveillance study on TDR among newly diagnosed individuals who infected-HIV through sexual contact in from 2014-2015. METHODS Genotypic resistance mutations were defined using the WHO-2009 surveillance list. Potential impact on antiretroviral drug was predicted according to the Stanford HIV db program version 7.0. The role of transmission clusters in drug resistant strains was evaluated by phylogenetic and network analyses. RESULTS In this study, 589 individuals were recruited and 542 samples were amplified and sequenced successfully. The over prevalence of TDR was 6.1%: 1.8% to nucleoside reverse transcriptase inhibitors (NRTIs), 2.0% to non- NRTIs (NNRTIs) and 2.4% to protease inhibitors (PIs), respectively. We did not find significant differences in the TDR prevalence by demographic and clinical characteristics (p > 0.05). Using network and phylogenetic analysis, almost 60.0% sequences were clustered together. Of these clusters, 2 included at least two individuals carrying the same resistance mutation, accounting for 21.2% (7/33) individuals with TDR. No significant difference was observed in the clustering rate between the individuals with and without TDR. CONCLUSIONS We obtained a moderate level TDR rate in studied region. These findings enhance our understanding of HIV-1 drug resistance prevalence in Shijiazhuang, and may be helpful for the comprehensive prevention and control of HIV-1.
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11
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Chen L, His JH, Wu X, Shen Z, Lu H, Chen H, Huang H, Zhang H, Ruan Y, Shao Y, Tang Z. Disparities in HIV and syphilis prevalence and risk factors between older male clients with and without steady sex partners in southwestern rural China. BMC Infect Dis 2017; 17:269. [PMID: 28403825 PMCID: PMC5389008 DOI: 10.1186/s12879-017-2367-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Accepted: 03/29/2017] [Indexed: 01/11/2023] Open
Abstract
Background Heterosexual intercourse accounted for 93% of reported HIV cases in Guangxi, and Guangxi had 10% of China’s total number of reported HIV cases. Older men are particularly vulnerable to STIs, for example, 46% of Guangxi’s HIV cases were men over 50 years of age. As this is an under-studied population in China, effective prevention and control policies have yet to be developed. Thus, the aim of this study was to use a large-scale cross-sectional survey to understand the demographic and behavior factors associated with HIV and syphilis infections among older male clients of female sex workers (FSWs) in a high epidemic area of rural Guangxi, China. Methods A large-scale cross-sectional survey was conducted in 2012 among older male clients of FSWs in low-cost commercial sex venues. Questionnaire interviews were administered to collect sociodemographic and sexual behavior information. Blood samples were collected for HIV and syphilis infection tests. Results Of the 3485 participants, 2509 (72.0%) clients had a steady sex partner and 976 (28.0%) clients had no steady sex partner. The overall prevalence of HIV and syphilis infection were 3.0% and 3.2%, respectively. Compared to those with a steady sex partner, clients with no steady partner had higher odds of HIV infection (AOR: 1.90, 95% CI: 1.27–2.86), syphilis infection (AOR: 1.53, 95% CI: 1.02–2.30), and having factors associated with HIV or syphilis infection, including non-commercial casual sex encounters in last month (AOR: 3.29, 95% CI: 2.42–4.46), >10 years of commercial sex history (AOR: 1.31, 95% CI: 1.12–1.53), >2 incidents of commercial sex in last month (AOR: 1.53, 95% CI: 1.19–1.96), and aphrodisiac use in last month (AOR: 1.40, 95% CI: 1.16–1.70). Clients with no steady partner had lower odds of having heterosexual intercourse (AOR: 0.66, 95% CI: 0.56–0.79), awareness and knowledge of HIV/AIDS (AOR: 0.75, 95% CI: 0.64–0.88), and having had HIV tests (AOR: 0.65, 95% CI: 0.44–0.98). Conclusion Older male clients of low-cost commercial sex venues in rural southwestern China are at high risk for HIV and syphilis infection, especially those with no steady sex partner. Improved interventions are urgently needed for this neglected risk population.
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Affiliation(s)
- Li Chen
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, No.18 Jinzhou Road, Nanning, Guangxi, China
| | - Jenny H His
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Xinghua Wu
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, No.18 Jinzhou Road, Nanning, Guangxi, China
| | - Zhiyong Shen
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, No.18 Jinzhou Road, Nanning, Guangxi, China
| | - Huaxiang Lu
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, No.18 Jinzhou Road, Nanning, Guangxi, China
| | - Huanhuan Chen
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, No.18 Jinzhou Road, Nanning, Guangxi, China
| | - Hui Huang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, No.18 Jinzhou Road, Nanning, Guangxi, China
| | - Heng Zhang
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Zhenzhu Tang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, No.18 Jinzhou Road, Nanning, Guangxi, China.
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12
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Liu P, Feng Y, Wu J, Tian S, Su B, Wang Z, Liao L, Xing H, You Y, Shao Y, Ruan Y. Polymorphisms and Mutational Covariation Associated with Death in a Prospective Cohort of HIV/AIDS Patients Receiving Long-Term ART in China. PLoS One 2017; 12:e0170139. [PMID: 28099515 PMCID: PMC5242503 DOI: 10.1371/journal.pone.0170139] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 12/29/2016] [Indexed: 12/11/2022] Open
Abstract
Background HIV drug resistance is associated with faster clinical progression of AIDS. However, the effect of significant polymorphisms and mutational covariation on mortality among HIV/AIDS patients receiving long-term antiretroviral therapy (ART), have rarely been studied. Methods In this prospective cohort study from December 2003 to December 2014, we present a new computational modelling approach based on bioinformatics-based models and several statistical methods to elucidate the molecular mechanisms involved in the acquisition of polymorphisms and mutations on death in HIV/AIDS patients receiving long-term ART in China. Results This study involved 654 ART-treated patients, who had been followed for 5473.4 person-years, a median of 9.8 years, and 178 died (25.2%, 3.3/100 person-years). The first regimens included AZT/d4T + NVP+ ddI (78.9%) or AZT/d4T + NVP+ 3TC (20.0%). We calculated an individual Ka/Ks value for each specific amino acid mutation. Result showed that 20 polymorphisms (E6D, Q18H, E35D, S37N, T39A, K43E, S68N, L74I, I93L, K103N, V106A, E169D, Y181C, G190A, Q197K, T200V, T200E, T215I, E224D and P225H) were strongly associated with AIDS related deaths. Among them, 7 polymorphisms (L74I, K103N, V106A, Y181C, G190A, T215I and P225H) were known to be drug resistance mutations, 7 polymorphisms (E6D, E35D, S37N, I93L, E169D, T200V and T200E were considered to be potential drug resistance mutations, and 6 polymorphisms (T39A, K43E, S68N, Q197K, T200V and E224D) were newly found to have an association with drug resistance mutations, which formed a complex network of relationships. Conclusions Some polymorphisms and mutational covariation may be the important influencing factors in the failure of treatment. Understanding these mechanisms is essential for the development of new therapies, designing optimal drug combinations, and determining effective clinical management of individual patients.
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Affiliation(s)
- Pengtao 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Jianjun Wu
- Anhui Center for Disease Control and Prevention, Hefei, Anhui Province, China
| | - Suian Tian
- Henan Center for Disease Control and Prevention, Zhengzhou, Henan Province, China
| | - Bin Su
- Anhui Center for Disease Control and Prevention, Hefei, Anhui Province, China
| | - Zhe Wang
- Henan Center for Disease Control and Prevention, Zhengzhou, Henan Province, China
| | - 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yinghui You
- Weifang Medical University, Weifang, Shandong Province, China
| | - 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - 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, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
- * E-mail:
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