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Xie Z, Chen B, Duan Z. Spatiotemporal Analysis of HIV/AIDS Incidence in China From 2009 to 2019 and Its Association With Socioeconomic Factors: Geospatial Study. JMIR Public Health Surveill 2024; 10:e56229. [PMID: 38848123 PMCID: PMC11193075 DOI: 10.2196/56229] [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: 01/10/2024] [Revised: 03/20/2024] [Accepted: 05/08/2024] [Indexed: 06/09/2024] Open
Abstract
BACKGROUND The Joint United Nations Program on HIV/AIDS (UNAIDS) has set the "95-95-95" targets to ensure that 95% of all people living with HIV will know their HIV status, 95% of all people living with HIV will receive sustained antiretroviral therapy (ART), and 95% of all people receiving ART will achieve viral suppression (<1000 copies/mL). However, few countries have currently achieved these targets, posing challenges to the realization of the UNAIDS goal to eliminate the global HIV/AIDS epidemic by 2030. The Chinese government has implemented corresponding policies for HIV/AIDS prevention and control; however, it still faces the challenge of a large number of HIV/AIDS cases. Existing research predominantly focuses on the study of a particular region or population in China, and there is relatively limited research on the macro-level analysis of the spatiotemporal distribution of HIV/AIDS across China and its association with socioeconomic factors. OBJECTIVE This study seeks to identify the impact of these factors on the spatiotemporal distribution of HIV/AIDS incidence in China, aiming to provide scientific recommendations for future policy development. METHODS This study employed ArcGIS 10.2 (Esri) for spatial analysis, encompassing measures such as the imbalance index, geographical concentration index, spatial autocorrelation analysis (Moran I), and hot spot analysis (Getis-Ord Gi*). These methods were used to unveil the spatiotemporal distribution characteristics of HIV/AIDS incidence in 31 provinces of China from 2009 to 2019. Geographical Detector was used for ecological detection, risk area detection, factor detection, and interaction detection. The analysis focused on 9 selected socioeconomic indicators to further investigate the influence of socioeconomic factors on HIV/AIDS incidence in China. RESULTS The spatiotemporal distribution analysis of HIV/AIDS incidence in China from 2009 to 2019 revealed distinct patterns. The spatial distribution type of HIV/AIDS incidence in China was random in 2009-2010. However, from 2011 to 2019, the distribution pattern evolved toward a clustered arrangement, with the degree of clustering increasing each year. Notably, from 2012 onwards, there was a significant and rapid growth in the aggregation of cold and hot spot clusters of HIV/AIDS incidence in China, stabilizing only by the year 2016. An analysis of the impact of socioeconomic factors on HIV/AIDS incidence in China highlighted the "urbanization rate" and "urban basic medical insurance fund expenditure" as the primary factors influencing the spatial distribution of HIV/AIDS incidence. Additionally, among social factors, indicators related to medical resources exerted a crucial influence on HIV/AIDS incidence. CONCLUSIONS From 2009 to 2019, HIV/AIDS incidence in China was influenced by various socioeconomic factors. In the future, it is imperative to optimize the combination of different socioeconomic indicators based on regional incidence patterns. This optimization will facilitate the formulation of corresponding policies to address the challenges posed by the HIV/AIDS epidemic.
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Affiliation(s)
- Ziyi Xie
- Faculty of Humanities and Social Science, Macao Polytechnic University, Macao, China
| | - Bowen Chen
- Faculty of Humanities and Social Science, Macao Polytechnic University, Macao, China
| | - Zhizhuang Duan
- Xingzhi College, Zhejiang Normal University, Jinhua, 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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3
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Yang S, Feng C, Fei T, Wu D, Feng L, Yuan F, Fu Y, Ma H, Yu B, Liu L, Li Y, Li Y, Huang Y, Su L, Pei X, Yang W, Yang Y, Zeng Y, Ye L, Yang H, Gong Y, Zhang L, Yuan D, Liang S, Jia P. Mortality risk of people living with HIV under hypothetical intervention scenarios of PM2.5 and HIV severity: a prospective cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 916:169938. [PMID: 38199346 DOI: 10.1016/j.scitotenv.2024.169938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 12/30/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
This study estimated and compared mortality risks among people living with HIV (PLWH) under the real-world and hypothetical scenarios of PM2.5 concentrations and HIV severity. An open cohort from all PLWH receiving antiretroviral therapy in Sichuan during 2010-2019 was constructed, resulting in 541,515 person-years. Annual mean concentrations of PM2.5 were estimated and linked to PLWH by their residential address. The parametric g-formula were used to assess 3- and 5-year mortality risks under the real-world and hypothetical scenarios of PM2.5 (10-35, 35-50, 50-75 μg/m3) and CD4 concentrations (0-200, 200-500, 500-800, 800-1100 counts/μl). The estimated 3- and 5-year mortality risks among the PLWH were 14.43 % and 19.38 %, respectively, which would decrease substantially when annual PM2.5 concentration were reduced to between 10 and 35 μg/m3 (risk difference [RD] = -3.23 % and - 4.06 %) and would increase when PM2.5 concentration were elevated to between 50 and 75 μg/m3 (RD = 3.59 % and 5.04 %). The mortality risk would increase when CD4 concentration were reduced to <200 counts/μl (RD = 15.90 % and 20.27 %) and would decrease when CD4 concentration were ≥ 200 counts/μl, especially to between 800 and 1100 counts/μl (RD = -9.01 % and - 11.75 %). The elevated concentration of PM2.5 may disproportionately affect individuals with immune deficiency, especially those with more severity. The findings would serve as justifications for future intervention design and policy making to alleviate air pollution and improve environmental justice and health equity.
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Affiliation(s)
- Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Chuanteng Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China
| | - Teng Fei
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Dan Wu
- London School of Hygiene and Tropical Medicine, London, UK
| | - Liao Feng
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Fengshun Yuan
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yao Fu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Hua Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Bin Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Li Liu
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yizhuo Li
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Yiping Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yuling Huang
- 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
| | - Xiaodi Pei
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Wei Yang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yihui Yang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yali Zeng
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Li Ye
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Hong Yang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yi Gong
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Linglin Zhang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Dan Yuan
- 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.
| | - Peng Jia
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China; School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; Hubei Luojia Laboratory, Wuhan, Hubei, China; School of Public Health, Wuhan University, Wuhan, China.
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4
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Yang H, Chen M, Hu Y, Xu M, Li Y, Liu L, Yuan D, Yuan F, Li L, Ye L, Zhou C, Zhang Y, Liang S, Su L. An Assessment of Trends in HIV-1 Prevalence and Incidence and Spatio-Temporal Analyses of HIV-1 Recent Infection Among MSM During the Surveillance Period Between 2018 and 2022 in Sichuan, China. HIV AIDS (Auckl) 2024; 16:83-93. [PMID: 38464995 PMCID: PMC10924877 DOI: 10.2147/hiv.s448096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 02/24/2024] [Indexed: 03/12/2024] Open
Abstract
Background Men who have sex with men (MSM) is one main type of high-risk activities facilitating HIV-1 transmission in Sichuan province. Previous works on HIV-1 incidence and prevalence among MSM only concentrated before 2018, the situation after that is unknown. In addition, the distribution of hot-spots related to current HIV-1 epidemic is also rarely known among MSM in Sichuan. Objective To update trends of HIV-1 prevalence and incidence and to visualize hot-spots of ongoing transmission in Sichuan province during surveillance period among MSM between 2018 and 2022. Methods Limiting Antigen Avidity assay was performed to detect recent infection within new HIV-1 diagnoses founded during surveillance period among MSM. The HIV-1 prevalence and incidence were calculated according to an extrapolation method proposed by publications and guidelines. Trend tests were performed using χ2 tests with linear-by-linear association. The spatial analysis was conducted with ArcGIS 10.7 to figure hot-spots of HIV-1 recent infections among MSM. Results Between 2018 and 2022, 16,697 individuals participated in HIV-1 MSM sentinel surveillance program, of which 449 samples (98.25%) were tested with LAg-Avidity EIA, and 230 samples were classified as recent infection. Respectively, the overall prevalence and incidence were 2.74% and 3.69% (95% CI: 3.21, 4.16) and both had significant declining trends (p < 0.001). Luzhou city had a highest HIV-1 incidence (10.74%, 95% CI: 8.39, 13.10) over the study period and was recognized as a hot-spot for recent HIV-1 infection among MSM. Conclusion During the surveillance period, both HIV-1 prevalence and incidence were declining. However, Luzhou city had an unusually high HIV-1 incidence and became an emerging hot-spot of recent HIV-1 infection among MSM. This finding suggested focused attention, cross-regional intervention strategies, and prevention programs are urgently required to curb the spread of ongoing transmission.
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Affiliation(s)
- Hong Yang
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Maogang Chen
- Department of Microbiology, Liangshan Yi Autonomous Prefecture Center for Disease Control and Prevention, Xichang, People’s Republic of China
| | - Ying Hu
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Mengjiao Xu
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Yiping Li
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Lunhao Liu
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Dan Yuan
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Fengshun Yuan
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Ling Li
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Li Ye
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Chang Zhou
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Yan Zhang
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Shu Liang
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Ling Su
- Department of AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
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5
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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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Yang H, Li Y, Xu M, Hu Y, Yuan F, Liu L, Li L, Yuan D, Ye L, Zhou C, Zhang Y, Su L, Liang S. The Update of HIV-1 Prevalence and Incidence and Spatio-Temporal Analyses of HIV Recent Infection Among Four Sub-Groups in Sichuan, China During Surveillance Period Between 2016 and 2022. Infect Drug Resist 2023; 16:6535-6548. [PMID: 37814665 PMCID: PMC10560476 DOI: 10.2147/idr.s428744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 09/27/2023] [Indexed: 10/11/2023] Open
Abstract
Background Sichuan Province has gradually become a hot-spot for HIV/AIDS. Little is known about the HIV-1 incidence and prevalence among four sub-groups since 2015. Meanwhile, the distributions of hot-spot areas related to recent infection cases that indicate current transmission among the four subgroups are also rare. Objective The main purpose of this study was to assess the HIV-1 prevalence and incidence and to visualize the distributions of hot-spot areas of current transmission among four subgroups (people who inject drugs, male STD clinic attendees, female sex workers and men who had sex with men) during the surveillance period in Sichuan province between 2016 and 2022. Results Of the 267,617 individuals, 2158 HIV-positive samples were tested with Lag-Avidity EIA, among which 493 samples were identified as recent infections. Among people who inject drugs (PWID), both HIV-1 prevalence (from 1.41% to 0.34%) and incidence (from 0.03% to 0.140%) showed a significant decreasing trend. Among men who had sex with men (MSM), female sex workers (FSWs), and male STD clinic attendees, HIV-1 prevalence indicated significant decreasing trends, whereas HIV-1 incidence showed no significant changes. Spatial analysis demonstrated the formation of hot-spots and clusters of current transmissions sharing regional differences, mainly concentrated in the southeast, and most of these were consecutive hot-spots. Conclusion The prevention and control were efficacious and persistent. However, among the other three subgroups, there is a need for a regional cooperative in prevention and control approaches and collaborative research in many aspects.
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Affiliation(s)
- Hong Yang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Yiping Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Mengjiao Xu
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Ying Hu
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Fengshun Yuan
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Lunhao Liu
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Ling Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Dan Yuan
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Li Ye
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Chang Zhou
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Yan Zhang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Ling Su
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Shu Liang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
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7
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Zhou Y, Cui M, Hong Z, Huang S, Zhou S, Lyu H, Li J, Lin Y, Huang H, Tang W, Sun C, Huang W. High Genetic Diversity of HIV-1 and Active Transmission Clusters among Male-to-Male Sexual Contacts (MMSCs) in Zhuhai, China. Viruses 2023; 15:1947. [PMID: 37766353 PMCID: PMC10535991 DOI: 10.3390/v15091947] [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: 08/03/2023] [Revised: 09/15/2023] [Accepted: 09/16/2023] [Indexed: 09/29/2023] Open
Abstract
Monitoring genetic diversity and recent HIV infections (RHIs) is critical for understanding HIV epidemiology. Here, we report HIV-1 genetic diversity and RHIs in blood samples from 190 HIV-positive MMSCs in Zhuhai, China. MMSCs with newly reported HIV were enrolled from January 2020 to June 2022. A nested PCR was performed to amplify the HIV polymerase gene fragments at HXB2 positions 2604-3606. We constructed genetic transmission network at both 0.5% and 1.5% distance thresholds using the Tamura-Nei93 model. RHIs were identified using a recent infection testing algorithm (RITA) combining limiting antigen avidity enzyme immunoassay (LAg-EIA) assay with clinical data. The results revealed that 19.5% (37/190) were RHIs and 48.4% (92/190) were CRF07_BC. Two clusters were identified at a 0.5% distance threshold. Among them, one was infected with CRF07_BC for the long term, and the other was infected with CRF55_01B recently. We identified a total of 15 clusters at a 1.5% distance threshold. Among them, nine were infected with CRF07_BC subtype, and RHIs were found in 38.8% (19/49) distributed in eight genetic clusters. We identified a large active transmission cluster (n = 10) infected with a genetic variant, CRF79_0107. The multivariable logistic regression model showed that clusters were more likely to be RHIs (adjusted OR: 3.64, 95% CI: 1.51~9.01). The RHI algorithm can help to identify recent or ongoing transmission clusters where the prevention tools are mostly needed. Prompt public health measures are needed to contain the further spread of active transmission clusters.
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Affiliation(s)
- Yi Zhou
- Faculty of Medicine, Macau University of Science and Technology, Macau SAR, China;
- Department of HIV Prevention, Zhuhai Center for Disease Control and Prevention, Zhuhai 519060, China; (H.L.); (H.H.)
| | - Mingting Cui
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China;
| | - Zhongsi Hong
- Department of Infectious Diseases, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519001, China
| | - Shaoli Huang
- School of Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China
| | - Shuntai Zhou
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hang Lyu
- Department of HIV Prevention, Zhuhai Center for Disease Control and Prevention, Zhuhai 519060, China; (H.L.); (H.H.)
| | - Jiarun Li
- Department of HIV Prevention, Zhuhai Center for Disease Control and Prevention, Zhuhai 519060, China; (H.L.); (H.H.)
| | - Yixiong Lin
- Department of HIV Prevention, Zhuhai Center for Disease Control and Prevention, Zhuhai 519060, China; (H.L.); (H.H.)
| | - Huitao Huang
- Department of HIV Prevention, Zhuhai Center for Disease Control and Prevention, Zhuhai 519060, China; (H.L.); (H.H.)
| | - Weiming Tang
- Dermatology Hospital of Southern Medical University, Guangzhou 510315, China
- Southern Medical University Institute for Global Health and Sexually Transmitted Diseases, Guangzhou 510315, China
- University of North Carolina Project-China, Guangzhou 510315, China
| | - Caijun Sun
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China;
- Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou 510080, China
| | - Wenyan Huang
- Department of HIV Prevention, Zhuhai Center for Disease Control and Prevention, Zhuhai 519060, China; (H.L.); (H.H.)
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Yuan D, Zhang Y, Li Y, Li L, Yang H, Yang W, Yu H, Feng L, Liang S. CD4(+) T Cell Count Progress and Influencing Factors of Recovery in AIDS Patients with Virological Failure in Sichuan Province: A Retrospective Cohort Study. Infect Drug Resist 2022; 15:6985-6999. [DOI: 10.2147/idr.s378799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 10/13/2022] [Indexed: 12/05/2022] Open
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Chen J, Chen H, Li J, Luo L, Kang R, Liang S, Zhu Q, Lu H, Zhu J, Shen Z, Feng Y, Liao L, Xing H, Shao Y, Ruan Y, Lan G. Genetic network analysis of human immunodeficiency virus sexual transmission in rural Southwest China after the expansion of antiretroviral therapy: A population-based study. Front Microbiol 2022; 13:962477. [PMID: 36060743 PMCID: PMC9434148 DOI: 10.3389/fmicb.2022.962477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 07/26/2022] [Indexed: 11/28/2022] Open
Abstract
Background This study is used to analyze the genetic network of HIV sexual transmission in rural areas of Southwest China after expanding antiretroviral therapy (ART) and to investigate the factors associated with HIV sexual transmission through the genetic network. Materials and methods This was a longitudinal genetic network study in Guangxi, China. The baseline survey and follow-up study were conducted among patients with HIV in 2015, and among those newly diagnosed from 2016 to 2018, respectively. A generalized estimating equation model was employed to explore the factors associated with HIV transmission through the genetic linkage between newly diagnosed patients with HIV (2016-2018) and those at baseline (2015-2017), respectively. Results Of 3,259 identified HIV patient sequences, 2,714 patients were at baseline, and 545 were newly diagnosed patients with HIV at follow-up. A total of 8,691 baseline objectives were observed by repeated measurement analysis. The prevention efficacy in HIV transmission for treated HIV patients was 33% [adjusted odds ratio (AOR): 0.67, 95% confidence interval (CI): 0.48-0.93]. Stratified analyses indicated the prevention efficacy in HIV transmission for treated HIV patients with a viral load (VL) of <50 copies/ml and those treated for 4 years with a VL of <50 copies/ml to be 41 [AOR: 0.59, 95% CI: 0.43-0.82] and 65% [AOR: 0.35, 95% CI: 0.24-0.50], respectively. No significant reduction in HIV transmission occurred among treated HIV patients with VL missing or treated HIV patients on dropout. Some factors were associated with HIV transmission, including over 50 years old, men, Zhuang and other nationalities, with less than secondary schooling, working as a farmer, and heterosexual transmission. Conclusion This study reveals the role of ART in reducing HIV transmission, and those older male farmers with less than secondary schooling are at high risk of HIV infection at a population level. Improvements to ART efficacy for patients with HIV and precision intervention on high-risk individuals during the expansion of ART are urgently required.
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Affiliation(s)
- Jin Chen
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 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
| | - Liuhong Luo
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Ruihua Kang
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 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
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Huaxiang Lu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Jinhui Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Zhiyong Shen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Yi Feng
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (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 Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (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 Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (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 Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 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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