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Heterosexuals have become the most prevalent group of HIV-1 in Kunming, Yunnan Province. Utilizing the principle of genetic similarity between their gene sequences, we built a molecular transmission network by gathering data from earlier molecular epidemiological studies. This allowed us to analyze the epidemiological features of this group and offer fresh concepts and approaches for the prevention and management of HIV-1 epidemics. Cytoscope was used to visualize and characterize the network following the processing of the sample gene sequences by BioEdit and HyPhy. The number of possible links and the size of the clusters were investigated as influencing factors using a zero-inflated Poisson model and a logistic regression model, respectively. A scikit-learn-based prediction model was developed to account for the dynamic changes in the HIV-1 molecular network. Six noteworthy modular clusters with network scores ranging from 4 to 9 were found from 150 clusters using Molecular Complex Detection analysis at a standard genetic distance threshold of 0.01. The size of the number of possible links and the network's clustering rate were significantly impacted by sampling time, marital status, and CD4+ T lymphocytes (all p < 0.05). The gradient boosting machine (GBM) model had the highest area under the curve value, 0.884 ± 0.051, according to scikit-learn. Though not all cluster subtypes grew equally, the network clusters were relatively specific and aggregated. The largest local transmission-risk group for HIV-1CRF08_BC is now the heterosexual transmission population. The most suitable model for constructing the HIV-1 molecular network dynamics prediction model was found to be the GBM model. [ABSTRACT FROM AUTHOR]

Background In 2016, China has implemented the World Health Organization's "treat all" policy. We aimed to assess the impact of significant improvements in the 95-95-95 targets on population-level human immunodeficiency virus (HIV) transmission dynamics and incidence. Methods We focused on 3 steps of the HIV care continuum: diagnosed, on antiretroviral therapy, and achieving viral suppression. The molecular transmission clusters were inferred using HIV-TRACE. New HIV infections were estimated using the incidence method in the European Centre for Disease Prevention and Control HIV Modelling Tool. Results Between 2004 and 2023, the national HIV epidemiology database recorded 2.99 billion person-times of HIV tests and identified 1 976 878 new diagnoses. We noted a roughly "inverted-V" curve in the clustering frequency, with the peak recorded in 2014 (67.1% [95% confidence interval, 63.7%–70.5%]), concurrent with a significant improvement in the 95-95-95 targets from 10-13-<71 in 2005 to 84-93-97 in 2022. Furthermore, we observed a parabolic curve for a new infection with the vertex occurring in 2010. Conclusions In general, it was suggested that the improvements in the 95-95-95 targets were accompanied by a reduction in both the population-level HIV transmission rate and incidence. Thus, China should allocate more effort to the first "95" target to achieve a balanced 95-95-95 target. [ABSTRACT FROM AUTHOR]

Background: As the social economy has developed and population mobility has increased, differences in the Human immunodeficiency virus type 1 (HIV‐1) genotype distribution among men who have sex with men (MSM) have become apparent in the provinces and cities across China. The high variability and drug resistance characteristics of HIV‐1 can lead to the widespread spread of resistant strains, which may also result in antiretroviral therapy failure and an increase in the mortality rate. Objective: The genotypic drug resistance characteristics and HIV‐1 transmission risks among HIV‐1‐infected MSM in Guiyang, Guizhou Province were analyzed in the current study. The aim of the study was to provide a scientific basis for preventing the spread of HIV‐1 strains among MSM and develop intervention measures. Method: A cross‐sectional study was conducted at the Guiyang Public Health Clinical Center. A total of 181 HIV‐1‐infected MSM who not received treatment at the center between 1 January 2020 and 31 December 2022 were selected. The HIV‐1 pol region gene fragment, including the protease and reverse transcriptase regions, was amplified by nested PCR and RT‐PCR. The maximum likelihood method was used to construct a phylogenetic tree for analyzing the HIV‐1 genotypes in MSM. HIV‐1 genotypic resistance was evaluated using the Stanford University HIV drug resistance database. A molecular transmission network of HIV was constructed and the risk of HIV‐1 transmission was determined. Results: We successfully amplified 173 pol gene sequences from blood samples obtained from 181 patients. The main subtype was CRF07_BC (60.69% [105/173]), followed by CRF01_AE (26.59% [46/173]), CRF08_BC (4.05% [7/173]), CRF55_01B (4.62% [8/173]), B (3.47% [6/173]), and C (0.58% [1/173]). The distribution of HIV‐1 genotypes in MSM showed that there was a significant difference in the genotype composition of HIV‐1‐infected MSM according to registered residences and ages (p <.05). The CRF55_01B subtype accounted for the lowest proportion in Guiyang City and individuals >30 years of age. Multivariate logistic regression analysis of risk factors for drug resistance in HIV‐1‐infected MSM showed that the overall prevalence of pretreatment drug‐resistant species was 12.72% (22/173), and age >30 years, CRF55_01B subtype, and CD4+ T lymphocyte count >350 cells/mm3 were risk factors for drug resistance in MSM HIV‐1 strains. Among the pretreatment drug‐resistant species, non‐nucleoside reverse transcriptase inhibitors with ≥1 drug resistant‐species accounted for 9.25% (16/173), followed by protease inhibitors at 4.05% (7/173) and nucleoside reverse transcriptase inhibitors at 1.73% (3/173). Non‐nucleoside reverse transcriptase inhibitors resistant to the CRF07_BC and CRF01_AE genotypes were predominant. The CRF55_01B genotype was shown to be most likely to carry the V179E mutation. The molecular network included CRF07_BC and B genotypes. The results of multi‐factor logistic regression analysis on the factors affecting the rate of joining the network showed that individuals >30 years of age were less likely to join the network compared to those individuals <30 years of age. Conclusion: The distribution of HIV‐1 genotypes among MSM in Guiyang is diverse and complex. The main genotypes were shown to be CRF07_BC and CRF01_AE. The drug resistance mutation rate is high and pretreatment drug‐resistant species is at a moderate level of prevalence, with NNRTIs being the most common site for drug resistance mutations. The CRF07_BC subtype and patients <30 years of age were identified as the key intervention targets in Guiyang based on the molecular transmission network. Patients should routinely undergo drug resistance testing before starting antiretroviral therapy to avoid virologic treatment failure and prevent the spread of HIV‐1‐resistant strains in MSM. [ABSTRACT FROM AUTHOR]

The number of newly reported HIV-1 infections among older individuals (≥50 years of age) has increased rapidly in Hangzhou, a central city in the Yangtze River Delta region of China. To provide a scientific basis for prevention and intervention strategies targeted at older individuals in Hangzhou, an epidemiological survey combined with molecular transmission network analysis was conducted. A total of 2,899 individuals with newly confirmed HIV-1 infections, including 635 older individuals and 2,264 younger individuals (<50 years of age), were enrolled in this study. Among older individuals, heterosexual contact was the predominant mode of HIV-1 transmission. In addition, it was observed that older individuals with lower levels of education exhibited a higher susceptibility to HIV-1 infection. The analysis of transmission network, which was inferred using HIV-TRACE algorithm, revealed that the newly diagnosed HIV-1 infections among older individuals in Hangzhou exhibited a pattern of scattered transmission, with key clusters primarily located in non-main urban areas. The predominant mode of transmission in these areas was nonmarital and noncommercial or nonmarital and commercial heterosexual transmission. Notably, the study highlighted a significant proportion of older individuals (73.3%, 11/15) within B subtype. Multivariate logistic regression analysis further revealed that the subtype B was a significant factor associated with older individuals having ≥3 node degrees in the network, occurring 5.55 times more frequent than subtype CRF07_BC (95% confidence intervals = 1.17–26.22, p = .031). Furthermore, the lower CD4 levels observed among older individuals underscored the challenge of late diagnosis in Hangzhou. Taken together, it is imperative to test and intervene for high-risk older individuals. To tackle this issue effectively, it is essential to enhance the detection of the B subtype and implement targeted interventions in key clusters within non-main urban areas. In addition, proactive measures should be implemented to address the challenge of late diagnosis in Hangzhou by promoting widespread testing among the older individuals, particularly in priority areas. [ABSTRACT FROM AUTHOR]

Abstract Objective The objective of this study was to conduct a comprehensive analysis of the molecular transmission networks and transmitted drug resistance (TDR) patterns among individuals newly diagnosed with HIV-1 in Nanjing. Methods Plasma samples were collected from newly diagnosed HIV patients in Nanjing between 2019 and 2021. The HIV pol gene was amplified, and the resulting sequences were utilized for determining TDR, identifying viral subtypes, and constructing molecular transmission network. Logistic regression analyses were employed to investigate the epidemiological characteristics associated with molecular transmission clusters. Results A total of 1161 HIV pol sequences were successfully extracted from newly diagnosed individuals, each accompanied by reliable epidemiologic information. The analysis revealed the presence of multiple HIV-1 subtypes, with CRF 07_BC (40.57%) and CRF01_AE (38.42%) being the most prevalent. Additionally, six other subtypes and unique recombinant forms (URFs) were identified. The prevalence of TDR among the newly diagnosed cases was 7.84% during the study period. Employing a genetic distance threshold of 1.50%, the construction of the molecular transmission network resulted in the identification of 137 clusters, encompassing 613 nodes, which accounted for approximately 52.80% of the cases. Multivariate analysis indicated that individuals within these clusters were more likely to be aged ≥ 60, unemployed, baseline CD4 cell count ≥ 200 cells/mm3, and infected with the CRF119_0107 (P

This study aimed to investigate the molecular transmission network and drug resistance in treatment-naive HIV-1-infected patients in the Liangshan District, China. The research subjects for this study were HIV-1-infected patients who did not receive any antiretroviral therapy (ART) in the Liangshan District between January 2022 and July 2023. Peripheral venous whole-blood samples were collected from the research subjects. Two milliliters of blood was used for CD4+ T lymphocyte counting detection. Ten milliliters of blood was centrifuged to separate the plasma and blood cells for quantitative detection of HIV-1 RNA and DNA and drug resistance testing of HIV-1. A total of 156 participants were included in this study (88 males and 68 females). The median age of the participants was 37 years. The findings revealed a positive correlation between the HIV-1 DNA and the HIV-1 RNA levels (r = 0.478, p < 0.001). However, a negative correlation was observed between the HIV-1 DNA levels and CD4+ T lymphocyte counts (r = −0.186, p = 0.020). Of the 156 participants, 145 were successfully tested for drug resistance of HIV-1 RNA and HIV-1 DNA simultaneously. Four cases failed the HIV-1 RNA drug resistance testing, and another two failed the HIV-1 DNA drug resistance testing. The most common HIV-1 subtype was the CRF07_BC recombinant. In this study, the overall incidence of transmitted drug resistance (TDR) was 8.33%. The resistance rates of non-nucleoside reverse transcriptase inhibitor (NNRTI) and protease inhibitor (PI) were 7.69% and 0.64%, respectively. In addition, 32 participants were found to have drug-resistant mutations. The primary drug-resistant mutations were K103N, V179D, E157Q, and A128T, mainly against efavirenz (EFV) and nevirapine (NVP) resistance. The drug resistance of HIV-1-infected ART-naive patients in the Liangshan District cannot be ignored. HIV-1 drug resistance testing is recommended before initiating ART. [ABSTRACT FROM AUTHOR]

Abstract Background Hepatitis C virus (HCV) infection poses a major public health challenge globally, especially among injecting drug users. China has the world’s largest burden of HCV infections. However, little is known about the characteristics of transmission networks among drug user populations. This study aims to investigate the molecular epidemiology and transmission characteristics of HCV infections among drug users in Zhuhai, a bustling port city connecting Mainland China and its Special Administrative Regions. Methods Participants enrolled in this study were drug users incarcerated at Zhuhai’s drug rehabilitation center in 2015. Their sociodemographic and behavioral information, including gender, promiscuity, drug use method, and so forth, was collected using a standardized questionnaire. Plasmas separated from venous blood were analyzed for HCV infection through ELISA and RT-PCR methods to detect anti-HCV antibodies and HCV RNA. The 5’UTR fragment of the HCV genome was amplified and further sequenced for subtype identifications and phylogenetic analysis. The phylogenetic tree was inferred using the Maximum Likelihood method based on the Tamura-Nei model, and the transmission cluster network was constructed using Cytoscape3.8.0 software with a threshold of 0.015. Binary logistic regression models were employed to assess the factors associated with HCV infection. Results The overall prevalence of HCV infection among drug users was 44.37%, with approximately 19.69% appearing to clear the HCV virus successfully. Binary logistic regression analysis revealed that those aged over 40, engaging in injecting drug use, and being native residents were at heightened risk for HCV infection among drug user cohorts. The predominant HCV subtypes circulating among those drug users were 6a (60.26%), followed by 3b (16.7%), 3a (12.8%), 1b (6.41%) and 1a (3.85%), respectively. Molecular transmission network analysis unveiled the presence of six transmission clusters, with the largest propagation cluster consisting of 41 individuals infected with HCV subtype 6a. Furthermore, distinct transmission clusters involved eight individuals infected with subtype 3b and seven with subtype 3a were also observed. Conclusion The genetic transmission networks revealed a complex transmission pattern among drug users in Zhuhai, emphasizing the imperative for a targeted and effective intervention strategy to mitigate HCV dissemination. These insights are pivotal for shaping future national policies on HCV screening, treatment, and prevention in port cities.

HIV-1CRF08_BC is the most prevalent epidemic subtype among heterosexual (HET) and intravenous drug users (IDUs) in Kunming, Yunnan. Using the pol region of gene sequences derived from molecular epidemiological surveys, we developed a molecular transmission network for the purpose of analyzing its epidemiological characteristics, assessing its epidemiological trends, identifying its potential transmission relationships, and developing targeted interventions. HyPhy 2.2.4 was used to calculate pairwise genetic distances between sequences; GraphPad-Prism 8.0 was employed to determine the standard genetic distance; and Cytoscope 3.7.2 was applied to visualize the network. We used the network analysis tools to investigate network characteristics and the Molecular Complex Detection (MCODE) tool to observe the growth of the network. We utilized a logistic regression model to examine the factors influencing clustering and a zero-inflated Poisson model to investigate the factors influencing potential transmission links. At the standard genetic distance threshold of 0.008, 406 out of 858 study participants were clustered in 132 dissemination networks with a total network linkage of 868, and the number of links per sequence ranged from 1 to 19. The MCODE analysis identified three significant modular clusters in the networks, with network scores ranging from 4.9 to 7. In models of logistic regression, HET, middle-aged and elderly individuals, and residents of northern and southeastern Kunming were more likely to enter the transmission network. According to the zero-inflated Poisson model, age, transmission category, sampling year, marital status, and CD4+ T level had a significant effect on the size of links. The molecular clusters in Kunming's molecular transmission network are specific and aggregate to a certain extent. HIV-1 molecular network analysis provided information on local transmission characteristics, and these findings helped to determine the priority of transmission-reduction interventions. [ABSTRACT FROM AUTHOR]

Background: Hepatitis C virus (HCV) infection poses a major public health challenge globally, especially among injecting drug users. China has the world's largest burden of HCV infections. However, little is known about the characteristics of transmission networks among drug user populations. This study aims to investigate the molecular epidemiology and transmission characteristics of HCV infections among drug users in Zhuhai, a bustling port city connecting Mainland China and its Special Administrative Regions. Methods: Participants enrolled in this study were drug users incarcerated at Zhuhai's drug rehabilitation center in 2015. Their sociodemographic and behavioral information, including gender, promiscuity, drug use method, and so forth, was collected using a standardized questionnaire. Plasmas separated from venous blood were analyzed for HCV infection through ELISA and RT-PCR methods to detect anti-HCV antibodies and HCV RNA. The 5'UTR fragment of the HCV genome was amplified and further sequenced for subtype identifications and phylogenetic analysis. The phylogenetic tree was inferred using the Maximum Likelihood method based on the Tamura-Nei model, and the transmission cluster network was constructed using Cytoscape3.8.0 software with a threshold of 0.015. Binary logistic regression models were employed to assess the factors associated with HCV infection. Results: The overall prevalence of HCV infection among drug users was 44.37%, with approximately 19.69% appearing to clear the HCV virus successfully. Binary logistic regression analysis revealed that those aged over 40, engaging in injecting drug use, and being native residents were at heightened risk for HCV infection among drug user cohorts. The predominant HCV subtypes circulating among those drug users were 6a (60.26%), followed by 3b (16.7%), 3a (12.8%), 1b (6.41%) and 1a (3.85%), respectively. Molecular transmission network analysis unveiled the presence of six transmission clusters, with the largest propagation cluster consisting of 41 individuals infected with HCV subtype 6a. Furthermore, distinct transmission clusters involved eight individuals infected with subtype 3b and seven with subtype 3a were also observed. Conclusion: The genetic transmission networks revealed a complex transmission pattern among drug users in Zhuhai, emphasizing the imperative for a targeted and effective intervention strategy to mitigate HCV dissemination. These insights are pivotal for shaping future national policies on HCV screening, treatment, and prevention in port cities. [ABSTRACT FROM AUTHOR]

Objective: To elucidate the epidemiological features of HIV-2 in Hunan Province, China, utilizing sequence analysis. Methods: Thirteen individuals diagnosed with HIV-2 infection in Hunan Province, China, from 2017 to 2023 were included in this study. Amplification of HIV-2 env and pol regions was conducted, followed by Sanger sequencing. Phylogenetic and molecular transmission network analyses were performed to delineate molecular features and transmission dynamics. Results: All 14 individuals contracted HIV-2 through heterosexual intercourse, comprising 7 males and 7 females, with a median age of 58 years. Among them, three couples (HN001 and HN013, HN010 and HN011, HN008 and HN009) were identified, along with commercial sexual activity engagement reported for subject HN004. Notably, subjects HN001, HN003, HN008, and HN010 engaged in commercial sexual activities at the same location as subject HN004. Phylogenetic analysis of the pol gene revealed close proximity of sequences from all subjects to reference sequences from Gambia (Sub-type A). Employing a genetic distance threshold of 1.5 %, eight out of the 14 subjects formed a molecular transmission network, with HN002 and HN004 identified as central nodes. Conclusion: From 2017 to 2023, all HIV-2-infected individuals in Hunan Province, China, acquired the virus through identifiable routes, indicating transmission of similar HIV-2 strains among them.

HIV-related spatial analysis studies in China are relatively few, and Jiangsu Province has not reported the relevant data in recent years. To describe the spatial distribution and molecular linkage characteristics of HIV-infected patients, this article combined descriptive epidemiology, spatial analysis, and molecular epidemiology methods to analyze patient reporting, patient mobility information, and HIV sequence information simultaneously. The results showed that HIV reporting profiles differed among Jiangsu cities, with the reporting rate in southern Jiangsu being above average. There was a spatial autocorrelation (Global Moran I = 0.5426, p < 0.05), with Chang Zhou showing a High–High aggregation pattern. Chang Zhou and Wu Xi were identified as hotspots for HIV reporting and access to molecular transmission networks. Some infected individuals still showed cross-city or even cross-province mobility after diagnosis, and three were linked with individuals in the destination cities within the largest molecular transmission cluster, involving 196 patients. The cross-city or cross-province mobility of patients may result in a potential HIV transmission risk, suggesting that combining timely social network surveys, building an extensive transmission network across cities and provinces, and taking critical regions and key populations as entry points could contribute to improved prevention and control efficiency and promote achievement of the 95-95-95 target and cascade. [ABSTRACT FROM AUTHOR]

The HIV‐1 pandemic has persisted for four decades, and poses a major challenge to global public health. Shenzhen, a city with large number of migrant populations in China, is suffering HIV‐1 epidemic. It is necessary to continuously conduct the molecular surveillance among newly diagnosed HIV‐1 patients in these migrant population. In this study, plasma samples of newly diagnosed and ART‐naive HIV‐1 infections were collected from Shenzhen city in China. The partial genes of HIV‐1 gag and pol were amplified and sequenced for the analysis of genotype, drug resistance, and molecular transmission network. Ninety‐one sequences of pol gene were obtained from newly diagnosed HIV‐1 infections in Shenzhen, and seven HIV‐1 subtypes were revealed in this investigation. Among them, the circulating recombinant form (CRF) 07_BC was the mostly frequent subtype (53.8%, 49/91), followed by CRF01_AE (20.9%, 19/91), CRF55_01B (9.9%, 9/91), unique recombinant forms (URFs) (8.8%, 8/91), B (3.3%, 3/91), CRF59_01B (2.2%, 2/91), and CRF08_BC (1.1%, 1/91). The overall prevalence of pretreatment drug resistance (PDR) was 23.1% (21/91), and 52.38% (11/21) of the PDR was specific for the nonnucleotide reverse transcriptase inhibitors (NNRTIs). Furthermore, a total of 3091 pol gene sequences were used to generate 19 molecular transmission clusters, and then one growing cluster, a new cluster, and a cluster with growth reactivation were identified. The result revealed that more sexual partner, CRF_07BC subtype, and seven amino acid deletions in gag p6 region might be the influencing factors associated with the high risk of transmission behavior. Compared with CRF01_AE subtype, CRF07_BC subtype strains were more likely to form clusters in molecular transmission network. This suggests that long‐term surveillance of the HIV‐1 molecular transmission should be a critical measure to achieve a precise intervention for controlling the spread of HIV‐1 in China. [ABSTRACT FROM AUTHOR]

IntroductionHIV-1 subtype B, as once one of the earliest strains introduced into mainland China rapidly spread in commercial plasma donors and heterosexuals in 1990s. Here, we aim to investigate the origin and evolutionary history of HIV-1 subtype B in Fuyang city, China.MethodsWe collected sequences tested from Fuyang in the east of China where higher prevalence of HIV-1 among commercial plasma donors and heterosexuals to construct a phylogenetic tree using the Markov chain Monte Carlo (MCMC) algorithm, infer molecular transmission network using TN93 model and visualize it with Cytoscape software.Results and discussionOur results showed that >99% of subtype B sequences belonged to Thai B. The sequences from Fuyang often cluster closer to those from other its adjacent cities, which clustered together and formed a monophyletic cluster. HIV-1 B circulating in Fuyang dates back to approximately 1990. Among the 1,437 sequences, 166 clustered at a genetic distance of ≤1.2%, resulting in 73 clusters. The degree of clustering with at least one other person was 11.55%. Among the transmission clusters, 50 (80.65%) comprised two individuals. Most clusters consisted of both heterosexual transmission routes and men who have sex with men. Phylogenetic and molecular network analyses revealed a common origin with neighboring regions in mainland China, local onwards transmission after its introduction, and a limited clustering degree. However, at least two co-existing transmission routes in most transmission clusters imply a greater challenge in controlling the spread of HIV-1. Our findings highlight the value on tailoring prevention interventions by combination of molecular surveillance and epidemiology.

ObjectivesWe investigated the prevalence of pretreatment drug resistance (PDR), the molecular transmission network among HIV-positive individuals, and the impact of virological failure on those who received antiretroviral therapy (ART) in China.MethodsBased on the World Health Organization (WHO) surveillance guidelines for PDR, a baseline survey and follow-up were conducted in 2018 and 2021, respectively. Demographic information and plasma samples were obtained from all participants. HIV pol gene region sequences were used to analyze the PDR and molecular transmission networks using the Stanford HIV database algorithm and HIV-TRACE, respectively. This study assessed the odds ratios (OR) of PDR to virological failure (viral load ≥ 50 copies/mL) after 3 years of ART using multivariable logistic regression.ResultsOf the 4,084 individuals, 370 (9.1%) had PDR. The prevalence of PDR to non-nucleoside reverse transcriptase inhibitors (5.2%) was notably higher than that to nucleoside reverse transcriptase inhibitors (0.7%, p < 0.001), protease inhibitors (3.0%, p < 0.001), and multidrug resistance (0.3%, p < 0.001). A total of 1,339 (32.8%) individuals from 361 clusters were enrolled in the molecular transmission network. Of the 361 clusters, 22 included two or more individuals with PDR. The prevalence of virological failure among HIV-positive individuals after 3 years of ART without PDR, those with PDR to Chinese listed drugs, and those with PDR to other drugs was 7.9, 14.3, and 12.6%, respectively. Compared with that in HIV-positive individuals without PDR, virological failure after 3 years of ART was significantly higher (OR: 2.02, 95% confidence interval (CI): 1.25–3.27) and not significantly different (OR: 1.72, 95% CI: 0.87–3.43) in individuals with PDR to Chinese listed drugs and those with PDR to other drugs, respectively. Missed doses in the past month were significantly associated with virological failure (OR, 2.82; 95% CI: 4.08–5.89).ConclusionThe overall prevalence of PDR was close to a high level and had an impact on virological failure after 3 years of ART. Moreover, HIV drug-resistant strains were transmitted in the molecular transmission network. These results illustrate the importance of monitoring PDR and ensuring virological suppression through drug adherence.

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&#95;AE and CRF07&#95;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., (©Yan He, Ying Tang, Qun Hua, Xin Li, You Ge, Yangyang Liu, Rong Tang, Ye Tian, Wei Li. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 29.05.2024.)

Background: Emerging HIV drug resistance caused by increased usage of antiretroviral drugs (ARV) could jeopardize the success of standardized HIV management protocols in resource-limited settings., Objective: We aimed to characterize pretreatment HIV drug resistance (PDR) among HIV-positive individuals and risk factors in China in 2022., Methods: This cross-sectional study was conducted using 2-stage systematic sampling according to the World Health Organization's surveillance guidelines in 8 provincial-level administrative divisions in 2022. Demographic information and plasma samples were obtained from study participants. PDR was analyzed using the Stanford HIV drug resistance database, and the Tamura-Nei 93 model in HIV-TRACE was used to calculate pairwise matches with a genetic distance of 0.01 substitutions per site. Logistic regression was used to identify and estimate factors associated with PDR., Results: PDR testing was conducted on 2568 participants in 2022. Of the participants, 34.8% (n=893) were aged 30-49 years, 81.4% (n=2091) were male, and 3.2% (n=81) had prior ARV exposure. The prevalence of PDR to protease and reverse transcriptase regions, nonnucleoside reverse transcriptase inhibitors, nucleoside reverse transcriptase inhibitors, and protease inhibitors were 7.4% (n=190), 6.3% (n=163), 1.2% (n=32), and 0.2% (n=5), respectively. Yunnan, Jilin, and Zhejiang had much higher PDR incidence than did Sichuan. The prevalence of nonnucleoside reverse transcriptase inhibitor-related drug resistance was 6.1% (n=157) for efavirenz and 6.3% (n=163) for nevirapine. Multivariable logistic regression models indicated that participants who had prior ARV exposure (odds ratio [OR] 7.45, 95% CI 4.50-12.34) and the CRF55&#95;01B HIV subtype (OR 2.61, 95% CI 1.41-4.83) were significantly associated with PDR. Among 618 (24.2%) sequences (nodes) associated with 253 molecular transmission clusters (size range 2-13), drug resistance mutation sites included K103, E138, V179, P225, V106, V108, L210, T215, P225, K238, and A98., Conclusions: The overall prevalence of PDR in China in 2022 was modest. Targeted genotypic PDR testing and medication compliance interventions must be urgently expanded to address PDR among newly diagnosed people living with HIV in China., (©Hongli Chen, Jingjing Hao, Jing Hu, Chang Song, Yesheng Zhou, Miaomiao Li, Jin Chen, Xiu Liu, Dong Wang, Xiaoshan Xu, Peixian Xin, Jiaxin Zhang, Lingjie Liao, Yi Feng, Dan Li, Stephen W Pan, Yiming Shao, Yuhua Ruan, Hui Xing. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 17.11.2023.)