Characterizing HIV transmission networks across the United States

Interpreting the Epidemiological Characteristics of HIV-1 in Heterosexually Transmitted Population Based on Molecular Transmission Network in Kunming, Yunnan: A Retrospective Cohort Study

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.

Molecular cluster, transmission characteristics, origin and dynamics analysis of HIV-1 CRF59_01B in China: A molecular epidemiology study

PURPOSE

This study investigated for the HIV-1 CRF59_01B epidemic's spatiotemporal dynamics and its transmission networks in China.

METHODS

Between 2007 and 2020, a total of 250 partial pol gene sequences of HIV-1 CRF59_01B were collected from four regions (10 Chinese provinces). Phylogenetic tree construction and cluster identification were then performed. The Bayesian skyline and birth-death susceptible-infected-removed models were employed for the phylodynamic analyses of subtypes and large clusters, respectively. Phylogenetic analyses and trait diffusion of these sequences were performed using Bayesian phylogenetic methods (beast-classic package). Distance-based molecular network analyses were performed to identify putative relationships.

RESULTS

Using a genetic distance threshold of 1.3 %, We identified 45 clusters that included 62.40 % (156/250) of the sequences. Three clusters (6.67 %, 3/45) had 10 or more sequences, and were considered "large clusters". Six clusters (13.33 %) included sequences from different regions (Southeast, Northeast, Southeast, and Central China). Thirteen clusters (28.89 %) included sequences of men who had sex with men only, three clusters (6.67 %) included sequences of heterosexuals only, and 12 clusters (26.67 %) included sequences of both groups. The substitution rate of CRF59_01B was 1.91 × 10-3 substitutions per site per year [95 % highest posterior density (HPD) interval: 1.39 × 10-3-2.49 × 10-3)], the time to the most recent common ancestor of CRF59_01B was to be 1992.83 (95 % HPD: 1977.97-2002.81). A Bayesian skyline plot revealed that the effective population size of CRF59_01B increased from 2000 to 2015 and remained stable after 2015. The large clusters showed continuous growth from 2013 to 2020. Phylogeographic analysis showed that CRF59_01B B most likely originated in Southeast China, with a posterior probability of 97.44 %, and then spread to other regions.

CONCLUSIONS

Our study revealed the temporal and geographical origins of HIV-1 CRF59_01B as well as the process of transmission among various regions and risk groups in China, which can help develop targeted HIV prevention strategies.

HIV-1 Molecular Networks and Pretreatment Drug Resistance at the Frontier of Yunnan Province, China

The border areas of Yunnan Province in China are severely affected by human immunodeficiency virus (HIV). To investigate the risk of HIV transmission and assess the prevalence of pretreatment drug resistance (PDR) in the border area, blood samples were collected from individuals with newly reported HIV in 2021 in three border counties (Cangyuan, Gengma, and Zhenkang) in Yunnan Province. Among the 174 samples successfully genotyped, eight circulating recombinant forms (CRFs), two subtypes, and several unique recombinant forms (URFs) were identified. CRF08_BC (56.9%, 99/174), URFs (14.4%, 25/174), CRF01_AE (10.9%, 19/174), and CRF07_BC (8.0%, 14/174) were the main genotypes. CRF08_BC and URFs were detected more frequently in Chinese and Burmese individuals, respectively. CRF07_BC was found more frequently in men who have sex with men. The proportion of individuals detected in HIV-1 networks was only associated with case-reporting counties. When stratified by county, individuals aged ≤40 years in Cangyuan and ≥41 years in Gengma were more likely to be found in these networks. Furthermore, 93.8% (15/16) of the links in Cangyuan and 79.4% (50/63) of those in Gengma were located within their own counties. The prevalence of PDR to any antiretroviral drug, nucleoside reverse transcriptase inhibitors (NRTIs), and non-nucleoside reverse transcriptase inhibitors (NNRTIs) were 10% (17/170), 0.6% (1/170), and 9.4% (16/170), respectively. The most frequent resistance-associated mutations (RAMs) were V179D/VD/E/T (22.9%, 39/170) and E138A/G/K/R (13.5%, 23/170). In the molecular networks, six clusters shared common RAMs. HIV-1 genetics has become more diverse in border areas. HIV-1 molecular network analysis revealed the different characteristics of the HIV-1 epidemic in the border counties. The prevalence of PDR showed an upward trend, and the PDR to NNRTIs was close to the public response threshold. These findings provide information for the development of AIDS prevention and treatment strategies.

Using the Molecular Transmission Networks to Analyze the Epidemic Characteristics of HIV-1 CRF08_BC in Kunming, Yunnan

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.

Molecular epidemiology to aid virtual elimination of HIV transmission in Australia

The Global UNAIDS 95/95/95 targets aim to increase the percentage of persons who know their HIV status, receive antiretroviral therapy, and have achieved viral suppression. Achieving these targets requires efforts to improve the public health response to increase access to care for those living with HIV, identify those yet undiagnosed with HIV early, and increase access to prevention for those most at risk of HIV acquisition. HIV infections in Australia are among the lowest globally having recorded significant declines in new diagnoses in the last decade. However, the HIV epidemic has changed with an increasing proportion of newly diagnosed infections among those born outside Australia observed in the last five years. Thus, the current prevention efforts are not enough to achieve the UNAIDS targets and virtual elimination across all population groups. We believe both are possible by including molecular epidemiology in the public health response. Molecular epidemiology methods have been crucial in the field of HIV prevention, particularly in demonstrating the efficacy of treatment as prevention. Cluster detection using molecular epidemiology can provide opportunities for the real-time detection of new outbreaks before they grow, and cluster detection programs are now part of the public health response in the USA and Canada. Here, we review what molecular epidemiology has taught us about HIV evolution and spread. We summarize how we can use this knowledge to improve public health measures by presenting case studies from the USA and Canada. We discuss the successes and challenges of current public health programs in Australia, and how we could use cluster detection as an add-on to identify gaps in current prevention measures easier and respond quicker to growing clusters. Lastly, we raise important ethical and legal challenges that need to be addressed when HIV genotypic data is used in combination with personal data.

Modeling homophily in dynamic networks with application to HIV molecular surveillance

BACKGROUND

Efforts to control the HIV epidemic can benefit from knowledge of the relationships between the characteristics of people who have transmitted HIV and those who became infected by them. Investigation of this relationship is facilitated by the use of HIV genetic linkage analyses, which allows inference about possible transmission events among people with HIV infection. Two persons with HIV (PWH) are considered linked if the genetic distance between their HIV sequences is less than a given threshold, which implies proximity in a transmission network. The tendency of pairs of nodes (in our case PWH) that share (or differ in) certain attributes to be linked is denoted homophily. Below, we describe a novel approach to modeling homophily with application to analyses of HIV viral genetic sequences from clinical series of participants followed in San Diego. Over the 22-year period of follow-up, increases in cluster size results from HIV transmissions to new people from those already in the cluster-either directly or through intermediaries.

METHODS

Our analytical approach makes use of a logistic model to describe homophily with regard to demographic, clinical, and behavioral characteristics-that is we investigate whether similarities (or differences) between PWH in these characteristics are associated with their sequences being linked. To investigate the performance of our methods, we conducted on a simulation study for which data sets were generated in a way that reproduced the structure of the observed database.

RESULTS

Our results demonstrated strong positive homophily associated with hispanic ethnicity, and strong negative homophily, with birth year difference. The second result implies that the larger the difference between the age of a newly-infected PWH and the average age for an available cluster, the lower the odds of a newly infected person joining that cluster. We did not observe homophily associated with prior diagnosis of sexually transmitted diseases. Our simulation studies demonstrated the validity of our approach for modeling homophily, by showing that the estimates it produced matched the specified values of the statistical network generating model.

CONCLUSIONS

Our novel methods provide a simple and flexible statistical network-based approach for modeling the growth of viral (or other microbial) genetic clusters from linkage to new infections based on genetic distance.

Molecular networks reveal complex interactions with MSM in heterosexual women living with HIV-1 who play peripheral roles in Guangzhou, China

BACKGROUND

With the number of newly diagnosed HIV-positive heterosexual women increasing yearly, it is urgent to understand HIV-1 transmission among heterosexual women in Guangzhou, China.

METHODS

HIV-1 pol sequences were obtained from people living with HIV-1 during 2008 to 2017 in Guangzhou, China. A molecular network was constructed using HIV-1 TRAnsmission Cluster Engine with 1.5% genetic distance. Potential linkage and centrality metric were measured with Cytoscape. Transmission pathways between heterosexual women and men who have sex with men (MSM) were determined using Bayesian phylogenetic analysis.

RESULTS

In the network, 1799 (62.6%) MSM, 692 (24.1%) heterosexual men and 141 (4.9%) heterosexual women formed 259 clusters. Molecular clusters including MSM and heterosexuals were more likely to form larger networks (P<0.001). Nearly half of the heterosexual women (45.4%) were linked to heterosexual men and 17.7% to MSM, but only 0.9% of MSM were linked to heterosexual women. Thirty-three (23.4%) heterosexual women linked to at least one MSM node and were in peripheral role. Compared to general heterosexual women, the proportion of heterosexual women linked to MSM infected with CRF55_01B (P<0.001) and CRF07_BC (P<0.001) was higher than that of other subtypes, and the proportion diagnosed between 2012-2017 (P=0.001) was higher than that in 2008-2012. In MCC trees, 63.6% (21/33) of the heterosexual women differentiated from the heterosexual evolutionary branch, while 36.4% (12/33) differentiated from the MSM evolutionary branch.

CONCLUSION

Heterosexual women living with HIV-1 were mainly linked to heterosexual men and were in peripheral positions in the molecular network. The role of heterosexual women in HIV-1 transmission was limited, but the interaction between MSM and heterosexual women were complex. Awareness of the HIV-1 infection status of sexual partners and active HIV-1 detection are needed for women.

From components to communities: bringing network science to clustering for molecular epidemiology

Defining clusters of epidemiologically related infections is a common problem in the surveillance of infectious disease. A popular method for generating clusters is pairwise distance clustering, which assigns pairs of sequences to the same cluster if their genetic distance falls below some threshold. The result is often represented as a network or graph of nodes. A connected component is a set of interconnected nodes in a graph that are not connected to any other node. The prevailing approach to pairwise clustering is to map clusters to the connected components of the graph on a one-to-one basis. We propose that this definition of clusters is unnecessarily rigid. For instance, the connected components can collapse into one cluster by the addition of a single sequence that bridges nodes in the respective components. Moreover, the distance thresholds typically used for viruses like HIV-1 tend to exclude a large proportion of new sequences, making it difficult to train models for predicting cluster growth. These issues may be resolved by revisiting how we define clusters from genetic distances. Community detection is a promising class of clustering methods from the field of network science. A community is a set of nodes that are more densely inter-connected relative to the number of their connections to external nodes. Thus, a connected component may be partitioned into two or more communities. Here we describe community detection methods in the context of genetic clustering for epidemiology, demonstrate how a popular method (Markov clustering) enables us to resolve variation in transmission rates within a giant connected component of HIV-1 sequences, and identify current challenges and directions for further work.

The characteristics of HIV-1 subtype B on phylogenetic dynamic and molecular transmission network in Fuyang City, China, 2011 to 2019

Introduction

HIV-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.

Methods

We 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 discussion

Our 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.

Beyond HIV outbreaks: protocol, rationale and implementation of a prospective study quantifying the benefit of incorporating viral sequence clustering analysis into routine public health interventions

INTRODUCTION

HIV continues to have great impact on millions of lives. Novel methods are needed to disrupt HIV transmission networks. In the USA, public health departments routinely conduct contact tracing and partner services and interview newly HIV-diagnosed index cases to obtain information on social networks and guide prevention interventions. Sequence clustering methods able to infer HIV networks have been used to investigate and halt outbreaks. Incorporation of such methods into routine, not only outbreak-driven, contact tracing and partner services holds promise for further disruption of HIV transmissions.

METHODS AND ANALYSIS

Building on a strong academic-public health collaboration in Rhode Island, we designed and have implemented a state-wide prospective study to evaluate an intervention that incorporates real-time HIV molecular clustering information with routine contact tracing and partner services. We present the rationale and study design of our approach to integrate sequence clustering methods into routine public health interventions as well as related important ethical considerations. This prospective study addresses key questions about the benefit of incorporating a clustering analysis triggered intervention into the routine workflow of public health departments, going beyond outbreak-only circumstances. By developing an intervention triggered by, and incorporating information from, viral sequence clustering analysis, and evaluating it with a novel design that avoids randomisation while allowing for methods comparison, we are confident that this study will inform how viral sequence clustering analysis can be routinely integrated into public health to support the ending of the HIV pandemic in the USA and beyond.

ETHICS AND DISSEMINATION

The study was approved by both the Lifespan and Rhode Island Department of Health Human Subjects Research Institutional Review Boards and study results will be published in peer-reviewed journals.

Molecular Epidemiology and Transmission Dynamics of the HIV-1 Epidemic in Ethiopia: Epidemic Decline Coincided With Behavioral Interventions Before ART Scale-Up

Background

Ethiopia is one of the sub-Saharan countries hit hard by the HIV epidemic. Previous studies have shown that subtype C dominates the Ethiopian HIV-1 epidemic, but the evolutionary and temporal dynamics of HIV-1 in Ethiopia have not been closely scrutinized. Understanding the evolutionary and epidemiological pattern of HIV is vital to monitor the spread, evaluate and implement HIV prevention strategies.

Methods

We analyzed 1,276 Ethiopian HIV-1 subtype C polymerase (pol sequences), including 144 newly generated sequences, collected from different parts of the country from 1986 to 2017. We employed state-of-art maximum likelihood and Bayesian phylodynamic analyses to comprehensively describe the evolutionary dynamics of the HIV-1 epidemic in Ethiopia. We used Bayesian phylodynamic models to estimate the dynamics of the effective population size (Ne) and reproductive numbers (Re) through time for the HIV epidemic in Ethiopia.

Results

Our analysis revealed that the Ethiopian HIV-1 epidemic originated from two independent introductions at the beginning of the 1970s and 1980s from eastern and southern African countries, respectively, followed by epidemic growth reaching its maximum in the early 1990s. We identified three large clusters with a majority of Ethiopian sequences. Phylodynamic analyses revealed that all three clusters were characterized by high transmission rates during the early epidemic, followed by a decline in HIV-1 transmissions after 1990. Re was high (4–6) during the earlier time of the epidemic but dropped significantly and remained low (Re &lt; 1) after the mid-1990. Similarly, with an expected shift in time, the effective population size (Ne) steadily increased until the beginning of 2000, followed by a decline and stabilization until recent years. The phylodynamic analyses corroborated the modeled UNAIDS incidence and prevalence estimates.

Conclusion

The rapid decline in the HIV epidemic took place a decade before introducing antiretroviral therapy in Ethiopia and coincided with early behavioral, preventive, and awareness interventions implemented in the country. Our findings highlight the importance of behavioral interventions and antiretroviral therapy scale-up to halt and maintain HIV transmissions at low levels (Re &lt; 1). The phylodynamic analyses provide epidemiological insights not directly available using standard surveillance and may inform the adjustment of public health strategies in HIV prevention in Ethiopia.

Using molecular transmission networks to understand the epidemic characteristics of HIV-1 CRF08_BC across China

HIV-1 CRF08_BC has become a major epidemic in heterosexuals and intravenous drug users (IDUs) in southern China. In order to evaluate the trends of its epidemic and facilitate targeted HIV prevention, we constructed the genetic transmission networks based on its pol sequences, derived from the National HIV Molecular Epidemiology Survey. Through retrospective network analysis, to study the epidemiological and demographic correlations with the transmission network. Of the 1,829 study subjects, 639 (34.9%) were clustered in 151 transmission networks. Factors associated with increased clustering include IDUs, heterosexual men, young adults and people with lower education (P < 0.05 for all). The IDUs, MSM, young adult and person with low education had more potential transmission links as well (P < 0.05 for all). The most crossover links were found between heterosexual women and IDUs, with 30.9% heterosexual women linked to IDUs. The crossover links heterosexual women were mainly those with middle age and single (P < 0.001). This study indicated that the HIV-1 CRF08_BC epidemic was still on going in China with more than one third of the infected people clustered in the transmission networks. Meanwhile, the study could help identify the active CRF08_BC spreader in the local community and greatly facilitate précising AIDS prevention with targeted intervention.

Using molecular transmission networks to understand the epidemic characteristics of HIV-1 CRF08_BC across China

HIV-1 CRF08_BC has become a major epidemic in heterosexuals and intravenous drug users (IDUs) in southern China. In order to evaluate the trends of its epidemic and facilitate targeted HIV prevention, we constructed the genetic transmission networks based on its pol sequences, derived from the National HIV Molecular Epidemiology Survey. Through retrospective network analysis, to study the epidemiological and demographic correlations with the transmission network. Of the 1,829 study subjects, 639 (34.9%) were clustered in 151 transmission networks. Factors associated with increased clustering include IDUs, heterosexual men, young adults and people with lower education (P < 0.05 for all). The IDUs, MSM, young adult and person with low education had more potential transmission links as well (P < 0.05 for all). The most crossover links were found between heterosexual women and IDUs, with 30.9% heterosexual women linked to IDUs. The crossover links heterosexual women were mainly those with middle age and single (P < 0.001). This study indicated that the HIV-1 CRF08_BC epidemic was still on going in China with more than one third of the infected people clustered in the transmission networks. Meanwhile, the study could help identify the active CRF08_BC spreader in the local community and greatly facilitate précising AIDS prevention with targeted intervention.

Prevalence and Molecular Epidemiology of Transmitted Drug Resistance and Genetic Transmission Networks Among Newly Diagnosed People Living With HIV/AIDS in a Minority Area, China

Introduction: Transmitted drug resistance (TDR) can compromise antiretroviral therapy (ART) efficacy. We aimed to understand the molecular epidemiology of TDR and its genetic transmission networks among newly diagnosed people living with HIV/AIDS (PLWH).

Methods: A total of 1,318 newly diagnosed PLWH, identified in all population-based HIV screening in an HIV-affected county of a minority area of China (i.e., Butuo county), were enrolled between January 1, 2018, and November 31, 2018. HIV-1 pol gene sequences were used for phylogenetic and genotypic drug resistance analyses. The genetic transmission networks were identified.

Results: The prevalence of TDR among newly diagnosed PLWH was 8.12% (107/1,318). Patients in the stage of AIDS (adjusted odds ratio, OR: 2.32) and who had a history of sharing a needle ≥5 times (adjusted OR: 3.89) were more likely to have an increased risk of TDR. The prevalence of TDR for non-nucleoside reverse transcriptase inhibitors (NNRTIs) is higher than that of other inhibitors, with a relatively high prevalence of three mutations [V179D/E/DE (4.93%), K103N/KN (3.11%), and E138A/G (1.52%)]. A total of 577 (43.78%) pol sequences were involved in the genetic transmission network, with 171 clusters ranging in size from 2 to 91 pol sequences; 37.38% (40/107) of individuals carrying TDR were involved in the network, and individuals with the same TDR-associated mutations were usually cross-linked.

Conclusions: Our data suggest a relatively high level of TDR and many transmission clusters among the newly diagnosed PLWH. Targeted intervention, early identification, and monitoring of resistance are warranted to reduce the TDR and prevent HIV-1 transmission in areas with a high rate of HIV-1.

Characterization of HIV Risk Behaviors and Clusters Using HIV-Transmission Cluster Engine Among a Cohort of Persons Living with HIV in Washington, DC

Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3-12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5-12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2-19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.

Perceptions of social norms played an important role in the occurrence of casual sex among Yi minority residents in China: a population-based study

BACKGROUND

Liangshan is one of the areas severely affected by both HIV and poverty in China. We investigated associations between perceptions of social norms related to casual sex and the occurrence of casual sex in lifetime among Yi minority people. Participants were Yi minority people aged 15-49 years old living in Liangshan. Of the participants, 11.8% were confirmed to be HIV-positive. About half of the participants (46.6%) had engaged in casual sex in their lifetime. All six perceptions of social norms were significantly associated with the presence of casual sex in lifetime. They were acceptable of belife: (1) casual sex in general (OR: 15.03), (2) not to use condom during casual sex (OR: 1.58), (3) a Yi woman to have more than one sex partner(OR: 4.54), (4) a Yi man to have more than one sex partner(OR: 4.51), (5) premarital sex with casual sex partner (OR: 4.29), and (6) extra-marital sex with casual sex partner (OR: 3.23). Casual sex may play an important role in facilitating HIV transmission among Yi minority people. Future interventions should consider making use of the Yi clan system to change perceptions of social norms related to casual sex.

Using longitudinal genetic-network study to understand HIV treatment-as-prevention

OBJECTIVE

The WHO has recommended that antiretroviral therapy be provided to all HIV patients to reduce future HIV transmission rates. However, few studies have examined this public health strategy at the population level in a real-world setting.

METHODS

In this longitudinal genetic-network study in Guangxi, China, the baseline and follow-up data were collected from HIV patients in 2014 and newly diagnosed HIV patients from 2015 to 2018, respectively. The prevention efficacy was used to estimate the effect of treatment-as-prevention in reducing HIV secondary transmission.

RESULTS

Among 804 newly diagnosed HIV patients during 2015-2018, 399 (49.6%) of them genetically linked to HIV patients at baseline during 2014-2017. The overall proportion of genetic linkage between newly diagnosed HIV patients during 2015-2018 with untreated and treated HIV patients at baseline during 2014-2017 was 6.2 and 2.9%, respectively. The prevention efficacy in HIV transmission for treated HIV patients was 53.6% [95% confidence interval (95% CI): 42.1-65.1]. Subgroup analyses indicated an 80.3% (95% CI: 74.8-85.8) reduction in HIV transmission among HIV patients who were treated for 4 years or more and had viral loads less than 50 copies/ml. There was no significant reduction in HIV transmission among treated HIV patients who dropped out or who had missing viral load measures.

CONCLUSION

Our study results support the feasibility of treating all HIV patients for future reductions in HIV transmission at the population level in real-world settings. Comprehensive intervention prevention programmes are urgently needed.

Priority Intervention Targets Identified Using an In-Depth Sampling HIV Molecular Network in a Non-Subtype B Epidemics Area

Molecular network analysis based on the genetic similarity of HIV-1 is increasingly used to guide targeted interventions. Nevertheless, there is a lack of experience regarding molecular network inferences and targeted interventions in combination with epidemiological information in areas with diverse epidemic strains of HIV-1.We collected 2,173 pol sequences covering 84% of the total newly diagnosed HIV-1 infections in Shenyang city, Northeast China, between 2016 and 2018. Molecular networks were constructed using the optimized genetic distance threshold for main subtypes obtained using sensitivity analysis of plausible threshold ranges. The transmission rates (TR) of each large cluster were assessed using Bayesian analyses. Molecular clusters with the characteristics of ≥5 newly diagnosed cases in 2018, high TR, injection drug users (IDUs), and transmitted drug resistance (TDR) were defined as priority clusters. Several HIV-1 subtypes were identified, with a predominance of CRF01_AE (71.0%, 1,542/2,173), followed by CRF07_BC (18.1%, 393/2,173), subtype B (4.5%, 97/2,173), other subtypes (2.6%, 56/2,173), and unique recombinant forms (3.9%, 85/2,173). The overall optimal genetic distance thresholds for CRF01_AE and CRF07_BC were both 0.007 subs/site. For subtype B, it was 0.013 subs/site. 861 (42.4%) sequences of the top three subtypes formed 239 clusters (size: 2-77 sequences), including eight large clusters (size ≥10 sequences). All the eight large clusters had higher TR (median TR = 52.4/100 person-years) than that of the general HIV infections in Shenyang (10.9/100 person-years). A total of ten clusters including 231 individuals were determined as priority clusters for targeted intervention, including eight large clusters (five clusters with≥5 newly diagnosed cases in 2018, one cluster with IDUs, and two clusters with TDR (K103N, Q58E/V179D), one cluster with≥5 newly diagnosed cases in 2018, and one IDUs cluster. In conclusion, a comprehensive analysis combining in-depth sampling HIV-1 molecular networks construction using subtype-specific optimal genetic distance thresholds, and baseline epidemiological information can help to identify the targets of priority intervention in an area epidemic for non-subtype B.

Methodological synthesis of Bayesian phylodynamics, HIV-TRACE, and GEE: HIV-1 transmission epidemiology in a racially/ethnically diverse Southern U.S. context

This study introduces an innovative methodological approach to identify potential drivers of structuring HIV-1 transmission clustering patterns between different subpopulations in the culturally and racially/ethnically diverse context of Houston, TX, the largest city in the Southern United States. Using 6332 HIV-1 pol sequences from persons newly diagnosed with HIV during the period 2010–2018, we reconstructed HIV-1 transmission clusters, using the HIV-TRAnsmission Cluster Engine (HIV-TRACE); inferred demographic and risk parameters on HIV-1 transmission dynamics by jointly estimating viral transmission rates across racial/ethnic, age, and transmission risk groups; and modeled the degree of network connectivity by using generalized estimating equations (GEE). Our results indicate that Hispanics/Latinos are most vulnerable to the structure of transmission clusters and serve as a bridge population, acting as recipients of transmissions from Whites (3.0 state changes/year) and from Blacks (2.6 state changes/year) as well as sources of transmissions to Whites (1.8 state changes/year) and to Blacks (1.2 state changes/year). There were high rates of transmission and high network connectivity between younger and older Hispanics/Latinos as well as between younger and older Blacks. Prevention and intervention efforts are needed for transmission clusters that involve younger racial/ethnic minorities, in particular Hispanic/Latino youth, to reduce onward transmission of HIV in Houston.

Molecular Transmission Dynamics of Primary HIV Infections in Lazio Region, Years 2013-2020

Molecular investigation of primary HIV infections (PHI) is crucial to describe current dynamics of HIV transmission. Aim of the study was to investigate HIV transmission clusters (TC) in PHI referred during the years 2013–2020 to the National Institute for Infectious Diseases in Rome (INMI), that is the Lazio regional AIDS reference centre, and factors possibly associated with inclusion in TC. These were identified by phylogenetic analysis, based on population sequencing of pol; a more in depth analysis was performed on TC of B subtype, using ultra-deep sequencing (UDS) of env. Of 270 patients diagnosed with PHI during the study period, 229 were enrolled (median follow-up 168 (IQR 96–232) weeks). Median age: 39 (IQR 32–48) years; 94.8% males, 86.5% Italians, 83.4% MSM, 56.8% carrying HIV-1 subtype B. Of them, 92.6% started early treatment within a median of 4 (IQR 2–7) days after diagnosis; median time to sustained suppression was 20 (IQR 8–32) weeks. Twenty TC (median size 3, range 2–9 individuals), including 68 patients, were identified. A diagnosis prior to 2015 was the unique factor associated with inclusion in a TC. Added value of UDS was the identification of shared quasispecies components in transmission pairs within TC.

Human Immunodeficiency Virus Type 1 Phylodynamics to Detect and Characterize Active Transmission Clusters in North Carolina

BACKGROUND

Human immunodeficiency virus type 1 (HIV-1) phylodynamics can be used to monitor epidemic trends and help target prevention through identification and characterization of transmission clusters.

METHODS

We analyzed HIV-1 pol sequences sampled in North Carolina from 1997 to 2014. Putative clusters were identified using maximum-likelihood trees and dated using Bayesian Markov Chain Monte Carlo inference. Active clusters were defined as clusters including internal nodes from 2009 to 2014. Effective reproductive numbers (Re) were estimated using birth-death models for large clusters that expanded ≥2-fold from 2009 to 2014.

RESULTS

Of 14 921 persons, 7508 (50%) sequences were identified in 2264 clusters. Only 288 (13%) clusters were active from 2009 to 2014; 37 were large (10-36 members). Compared to smaller clusters, large clusters were increasingly populated by men and younger persons; however, nearly 60% included ≥1 women. Clusters with ≥3 members demonstrated assortative mixing by sex, age, and sample region. Of 15 large clusters with ≥2-fold expansion, nearly all had Re approximately 1 by 2014.

CONCLUSIONS

Phylodynamics revealed transmission cluster expansion in this densely sampled region and allowed estimates of Re to monitor active clusters, showing the propensity for steady, onward propagation. Associations with clustering and cluster characteristics vary by cluster size. Harnessing sequence-derived epidemiologic parameters within routine surveillance could allow refined monitoring of local subepidemics.

Molecular epidemiology in the HIV and SARS-CoV-2 pandemics

PURPOSE OF REVIEW

The aim of this review was to compare and contrast the application of molecular epidemiology approaches for the improved management and understanding of the HIV versus SARS-CoV-2 epidemics.

RECENT FINDINGS

Molecular biology approaches, including PCR and whole genome sequencing (WGS), have become powerful tools for epidemiological investigation. PCR approaches form the basis for many high-sensitivity diagnostic tests and can supplement traditional contact tracing and surveillance strategies to define risk networks and transmission patterns. WGS approaches can further define the causative agents of disease, trace the origins of the pathogen, and clarify routes of transmission. When coupled with clinical datasets, such as electronic medical record data, these approaches can investigate co-correlates of disease and pathogenesis. In the ongoing HIV epidemic, these approaches have been effectively deployed to identify treatment gaps, transmission clusters and risk factors, though significant barriers to rapid or real-time implementation remain critical to overcome. Likewise, these approaches have been successful in addressing some questions of SARS-CoV-2 transmission and pathogenesis, but the nature and rapid spread of the virus have posed additional challenges.

SUMMARY

Overall, molecular epidemiology approaches offer unique advantages and challenges that complement traditional epidemiological tools for the improved understanding and management of epidemics.

Persistence of HIV transmission clusters among people who inject drugs

OBJECTIVE

We investigated the duration of HIV transmission clusters.

DESIGN

Fifty-four individuals newly infected at enrollment in the ALIVE cohort were included, all of whom had sequences at an intake visit (T1) and from a second (T2) and/or a third (T3) follow-up visit, median 2.9 and 5.4 years later, respectively.

METHODS

Sequences were generated using the 454 DNA sequencing platform for portions of HIV pol and env (HXB2 positions 2717-3230; 7941-8264). Genetic distances were calculated using tn93 and sequences were clustered over a range of thresholds (1--5%) using HIV-TRACE. Analyses were performed separately for individuals with pol sequences for T1 + T2 (n = 40, 'Set 1') and T1 + T3 (n = 25; 'Set 2'), and env sequences for T1 + T2 (n = 47, 'Set 1'), and T1 + T3 (n = 30; 'Set 2').

RESULTS

For pol, with one exception, a single cluster contained more than 75% of samples at all thresholds, and cluster composition was at least 90% concordant between time points/thresholds. For env, two major clusters (A and B) were observed at T1 and T2/T3, although cluster composition concordance between time points/thresholds was low (<60%) at lower thresholds for both sets 1 and 2. In addition, several individuals were included in clusters at T2/T3, although not at T1.

CONCLUSION

Caution should be used in applying a single threshold in population studies where seroconversion dates are unknown. However, the retention of some clusters even after 5 + years is evidence for the robustness of the clustering approach in general.

Dynamics of HIV-1 Molecular Networks Reveal Effective Control of Large Transmission Clusters in an Area Affected by an Epidemic of Multiple HIV Subtypes

This study reconstructed molecular networks of human immunodeficiency virus (HIV) transmission history in an area affected by an epidemic of multiple HIV-1 subtypes and assessed the efficacy of strengthened early antiretroviral therapy (ART) and regular interventions in preventing HIV spread. We collected demographic and clinical data of 2221 treatment-naïve HIV-1–infected patients in a long-term cohort in Shenyang, Northeast China, between 2008 and 2016. HIV pol gene sequencing was performed and molecular networks of CRF01_AE, CRF07_BC, and subtype B were inferred using HIV-TRACE with separate optimized genetic distance threshold. We identified 168 clusters containing ≥ 2 cases among CRF01_AE-, CRF07_BC-, and subtype B-infected cases, including 13 large clusters (≥ 10 cases). Individuals in large clusters were characterized by younger age, homosexual behavior, more recent infection, higher CD4 counts, and delayed/no ART (P < 0.001). The dynamics of large clusters were estimated by proportional detection rate (PDR), cluster growth predictor, and effective reproductive number (R_e). Most large clusters showed decreased or stable during the study period, indicating that expansion was slowing. The proportion of newly diagnosed cases in large clusters declined from 30 to 8% between 2008 and 2016, coinciding with an increase in early ART within 6 months after diagnosis from 24 to 79%, supporting the effectiveness of strengthened early ART and continuous regular interventions. In conclusion, molecular network analyses can thus be useful for evaluating the efficacy of interventions in epidemics with a complex HIV profile.

Differing impacts of global and regional responses on SARS-CoV-2 transmission cluster dynamics

Although the global response to COVID-19 has not been entirely unified, the opportunity arises to assess the impact of regional public health interventions and to classify strategies according to their outcome. Analysis of genetic sequence data gathered over the course of the pandemic allows us to link the dynamics associated with networks of connected individuals with specific interventions. In this study, clusters of transmission were inferred from a phylogenetic tree representing the relationships of patient sequences sampled from December 30, 2019 to April 17, 2020. Metadata comprising sampling time and location were used to define the global behavior of transmission over this earlier sampling period, but also the involvement of individual regions in transmission cluster dynamics. Results demonstrate a positive impact of international travel restrictions and nationwide lockdowns on global cluster dynamics. However, residual, localized clusters displayed a wide range of estimated initial secondary infection rates, for which uniform public health interventions are unlikely to have sustainable effects. Our findings highlight the presence of so-called "super-spreaders", with the propensity to infect a larger-than-average number of people, in countries, such as the USA, for which additional mitigation efforts targeting events surrounding this type of spread are urgently needed to curb further dissemination of SARS-CoV-2.

A Nationwide Study about the Dispersal Patterns of the Predominant HIV-1 Subtypes A1 and B in Greece: Inference of the Molecular Transmission Clusters

Our aim was to investigate the dispersal patterns and parameters associated with local molecular transmission clusters (MTCs) of subtypes A1 and B in Greece (predominant HIV-1 subtypes). The analysis focused on 1751 (28.4%) and 2575 (41.8%) sequences of subtype A1 and B, respectively. Identification of MTCs was based on phylogenetic analysis. The analyses identified 38 MTCs including 2-1518 subtype A1 sequences and 168 MTCs in the range of 2-218 subtype B sequences. The proportion of sequences within MTCs was 93.8% (1642/1751) and 77.0% (1982/2575) for subtype A1 and B, respectively. Transmissions within MTCs for subtype A1 were associated with risk group (Men having Sex with Men vs. heterosexuals, OR = 5.34, p < 0.001) and Greek origin (Greek vs. non-Greek origin, OR = 6.05, p < 0.001) and for subtype B, they were associated with Greek origin (Greek vs. non-Greek origin, OR = 1.57, p = 0.019), younger age (OR = 0.96, p < 0.001), and more recent sampling (time period: 2011-2015 vs. 1999-2005, OR = 3.83, p < 0.001). Our findings about the patterns of across and within country dispersal as well as the parameters associated with transmission within MTCs provide a framework for the application of the study of molecular clusters for HIV prevention.

Evaluation of HIV Transmission Clusters among Natives and Foreigners Living in Italy

We aimed at evaluating the characteristics of HIV-1 molecular transmission clusters (MTCs) among natives and migrants living in Italy, diagnosed between 1998 and 2018. Phylogenetic analyses were performed on HIV-1 polymerase (pol) sequences to characterise subtypes and identify MTCs, divided into small (SMTCs, 2–3 sequences), medium (MMTCs, 4–9 sequences) and large (LMTCs, ≥10 sequences). Among 3499 drug-naïve individuals enrolled in the Italian Cohort Naive Antiretroviral (ICONA) cohort (2804 natives; 695 migrants), 726 (20.8%; 644 natives, 82 migrants) were involved in 228 MTCs (6 LMTCs, 36 MMTCs, 186 SMTCs). Migrants contributed 14.4% to SMTCs, 7.6% to MMTCs and 7.1% to LMTCs, respectively. HIV-1 non-B subtypes were found in 51 MTCs; noteworthy was that non-B infections involved in MTCs were more commonly found in natives (n = 47) than in migrants (n = 4). Factors such as Italian origin, being men who have sex with men (MSM), younger age, more recent diagnosis and a higher CD4 count were significantly associated with MTCs. Our findings show that HIV-1 clustering transmission among newly diagnosed individuals living in Italy is prevalently driven by natives, mainly MSM, with a more recent diagnosis and frequently infected with HIV-1 non-B subtypes. These results can contribute to monitoring of the HIV epidemic and guiding the public health response to prevent new HIV infections.

Migration interacts with the local transmission of HIV in developed trade areas: A molecular transmission network analysis in China

The HIV-1 epidemic is a remarkable public health concern in China, especially in developed trade areas. We aimed to investigate the interaction of migration with the local transmission network in a typical trade area, Yiwu City, the world's largest commodity distribution center. Based on 390 pol sequences from 413 participants diagnosed between 2014 and 2016, putative transmission clusters and the underlying demographic and behavioral characteristics were analyzed. Recent infection status was determined by HIV-1 limiting antigen avidity enzyme immunoassay to identify active clusters. Multiple subtypes were identified, with a predominance of CRF01_AE (47.4%) and CRF07_BC (40.8%), followed by 9 other subtypes and 8 URFs. Multivariable analyses revealed that individuals in clusters were more likely to be local residents, infected through heterosexual behaviors, and infected with CRF01_AE (P < .05). Of men who have sex with men (MSM), 81% were linked to other MSM, and only 3% were linked to heterosexual women. Of heterosexual women, 67% were linked to heterosexual men, and 11% to MSM. Yiwu residents were more likely to link to locals than that of migrants (43% vs 20%, P < .001). By contrast, local MSM and migrant MSM all had high percentages of linkage to migrant MSM (57% vs 69%, P = .069). Our findings reveal that migration promotes the dissemination and dynamic change of HIV, which are interwoven between locals and migrants. The results highlight the far-reaching influence of migrant MSM on the local HIV transmission network.

Molecular network-based intervention brings us closer to ending the HIV pandemic

Precise identification of HIV transmission among populations is a key step in public health responses. However, the HIV transmission network is usually difficult to determine. HIV molecular networks can be determined by phylogenetic approach, genetic distance-based approach, and a combination of both approaches. These approaches are increasingly used to identify transmission networks among populations, reconstruct the history of HIV spread, monitor the dynamics of HIV transmission, guide targeted intervention on key subpopulations, and assess the effects of interventions. Simulation and retrospective studies have demonstrated that these molecular network-based interventions are more cost-effective than random or traditional interventions. However, we still need to address several challenges to improve the practice of molecular network-guided targeting interventions to finally end the HIV epidemic. The data remain limited or difficult to obtain, and more automatic real-time tools are required. In addition, molecular and social networks must be combined, and technical parameters and ethnic issues warrant further studies.

Phylogenetic and Demographic Characterization of Directed HIV-1 Transmission Using Deep Sequences from High-Risk and General Population Cohorts/Groups in Uganda

Across sub-Saharan Africa, key populations with elevated HIV-1 incidence and/or prevalence have been identified, but their contribution to disease spread remains unclear. We performed viral deep-sequence phylogenetic analyses to quantify transmission dynamics between the general population (GP), fisherfolk communities (FF), and women at high risk of infection and their clients (WHR) in central and southwestern Uganda. Between August 2014 and August 2017, 6185 HIV-1 positive individuals were enrolled in 3 GP and 10 FF communities, 3 WHR enrollment sites. A total of 2531 antiretroviral therapy (ART) naïve participants with plasma viral load >1000 copies/mL were deep-sequenced. One hundred and twenty-three transmission networks were reconstructed, including 105 phylogenetically highly supported source–recipient pairs. Only one pair involved a WHR and male participant, suggesting that improved population sampling is needed to assess empirically the role of WHR to the transmission dynamics. More transmissions were observed from the GP communities to FF communities than vice versa, with an estimated flow ratio of 1.56 (95% CrI 0.68–3.72), indicating that fishing communities on Lake Victoria are not a net source of transmission flow to neighboring communities further inland. Men contributed disproportionally to HIV-1 transmission flow regardless of age, suggesting that prevention efforts need to better aid men to engage with and stay in care.

Characterisation of HIV-1 Molecular Epidemiology in Nigeria: Origin, Diversity, Demography and Geographic Spread

Nigeria has the highest number of AIDS-related deaths in the world. In this study, we characterised the HIV-1 molecular epidemiology by analysing 1442 HIV-1 pol sequences collected 1999-2014 from four geopolitical zones in Nigeria using state-of-the-art maximum-likelihood and Bayesian phylogenetic analyses. The main circulating forms were the circulating recombinant form (CRF) 02_AG (44% of the analysed sequences), CRF43_02G (16%), and subtype G (8%). Twenty-three percent of the sequences represented unique recombinant forms (URFs), whereof 37 (11%) could be grouped into seven potentially novel CRFs. Bayesian phylodynamic analysis suggested that five major Nigerian HIV-1 sub-epidemics were introduced in the 1960s and 1970s, close to the Nigerian Civil War. The analysis also indicated that the number of effective infections decreased in Nigeria after the introduction of free antiretroviral treatment in 2006. Finally, Bayesian phylogeographic analysis suggested gravity-like dynamics in which virus lineages first emerge and expand within large urban centers such as Abuja and Lagos, before migrating towards smaller rural areas. This study provides novel insight into the Nigerian HIV-1 epidemic and may have implications for future HIV-1 prevention strategies in Nigeria and other severely affected countries.

Phylogenetic Clustering by Linear Integer Programming (PhyCLIP)

Subspecies nomenclature systems of pathogens are increasingly based on sequence data. The use of phylogenetics to identify and differentiate between clusters of genetically similar pathogens is particularly prevalent in virology from the nomenclature of human papillomaviruses to highly pathogenic avian influenza (HPAI) H5Nx viruses. These nomenclature systems rely on absolute genetic distance thresholds to define the maximum genetic divergence tolerated between viruses designated as closely related. However, the phylogenetic clustering methods used in these nomenclature systems are limited by the arbitrariness of setting intra and intercluster diversity thresholds. The lack of a consensus ground truth to define well-delineated, meaningful phylogenetic subpopulations amplifies the difficulties in identifying an informative distance threshold. Consequently, phylogenetic clustering often becomes an exploratory, ad hoc exercise. Phylogenetic Clustering by Linear Integer Programming (PhyCLIP) was developed to provide a statistically principled phylogenetic clustering framework that negates the need for an arbitrarily defined distance threshold. Using the pairwise patristic distance distributions of an input phylogeny, PhyCLIP parameterizes the intra and intercluster divergence limits as statistical bounds in an integer linear programming model which is subsequently optimized to cluster as many sequences as possible. When applied to the hemagglutinin phylogeny of HPAI H5Nx viruses, PhyCLIP was not only able to recapitulate the current WHO/OIE/FAO H5 nomenclature system but also further delineated informative higher resolution clusters that capture geographically distinct subpopulations of viruses. PhyCLIP is pathogen-agnostic and can be generalized to a wide variety of research questions concerning the identification of biologically informative clusters in pathogen phylogenies. PhyCLIP is freely available at http://github.com/alvinxhan/PhyCLIP, last accessed March 15, 2019.

Public health in genetic spaces: a statistical framework to optimize cluster-based outbreak detection

Genetic clustering is a popular method for characterizing variation in transmission rates for rapidly evolving viruses, and could potentially be used to detect outbreaks in 'near real time'. However, the statistical properties of clustering are poorly understood in this context, and there are no objective guidelines for setting clustering criteria. Here, we develop a new statistical framework to optimize a genetic clustering method based on the ability to forecast new cases. We analysed the pairwise Tamura-Nei (TN93) genetic distances for anonymized HIV-1 subtype B pol sequences from Seattle (n = 1,653) and Middle Tennessee, USA (n = 2,779), and northern Alberta, Canada (n = 809). Under varying TN93 thresholds, we fit two models to the distributions of new cases relative to clusters of known cases: 1, a null model that assumes cluster growth is strictly proportional to cluster size, i.e. no variation in transmission rates among individuals; and 2, a weighted model that incorporates individual-level covariates, such as recency of diagnosis. The optimal threshold maximizes the difference in information loss between models, where covariates are used most effectively. Optimal TN93 thresholds varied substantially between data sets, e.g. 0.0104 in Alberta and 0.016 in Seattle and Tennessee, such that the optimum for one population would potentially misdirect prevention efforts in another. For a given population, the range of thresholds where the weighted model conferred greater predictive accuracy tended to be narrow (±0.005 units), and the optimal threshold tended to be stable over time. Our framework also indicated that variation in the recency of HIV diagnosis among clusters was significantly more predictive of new cases than sample collection dates (ΔAIC > 50). These results suggest that one cannot rely on historical precedence or convention to configure genetic clustering methods for public health applications, especially when translating methods between settings of low-level and generalized epidemics. Our framework not only enables investigators to calibrate a clustering method to a specific public health setting, but also provides a variable selection procedure to evaluate different predictive models of cluster growth.

Inferring putative transmission clusters with Phydelity

Current phylogenetic clustering approaches for identifying pathogen transmission clusters are limited by their dependency on arbitrarily defined genetic distance thresholds for within-cluster divergence. Incomplete knowledge of a pathogen’s underlying dynamics often reduces the choice of distance threshold to an exploratory, ad hoc exercise that is difficult to standardise across studies. Phydelity is a new tool for the identification of transmission clusters in pathogen phylogenies. It identifies groups of sequences that are more closely related than the ensemble distribution of the phylogeny under a statistically principled and phylogeny-informed framework, without the introduction of arbitrary distance thresholds. Relative to other distance threshold- and model-based methods, Phydelity outputs clusters with higher purity and lower probability of misclassification in simulated phylogenies. Applying Phydelity to empirical datasets of hepatitis B and C virus infections showed that Phydelity identified clusters with better correspondence to individuals that are more likely to be linked by transmission events relative to other widely used non-parametric phylogenetic clustering methods without the need for parameter calibration. Phydelity is generalisable to any pathogen and can be used to identify putative direct transmission events. Phydelity is freely available at https://github.com/alvinxhan/Phydelity.

Leveraging Phylogenetics to Understand HIV Transmission and Partner Notification Networks

BACKGROUND

Partner notification is an important component of public health test and treat interventions. To enhance this essential function, we assessed the potential for molecular methods to supplement routine partner notification and corroborate HIV networks.

METHODS

All persons diagnosed with HIV infection in Wake County, NC, during 2012-2013 and their disclosed sexual partners were included in a sexual network. A data set containing HIV-1 pol sequences collected in NC during 1997-2014 from 15,246 persons was matched to HIV-positive persons in the network and used to identify putative transmission clusters. Both networks were compared.

RESULTS

The partner notification network comprised 280 index cases and 383 sexual partners and high-risk social contacts (n = 131 HIV-positive). Of the 411 HIV-positive persons in the partner notification network, 181 (44%) did not match to a HIV sequence, 61 (15%) had sequences but were not identified in a transmission cluster, and 169 (41%) were identified in a transmission cluster. More than half (59%) of transmission clusters bridged sexual network partnerships that were not recognized in the partner notification; most of these clusters were dominated by men who have sex with men.

CONCLUSIONS

Partner notification and HIV sequence analysis provide complementary representations of the existent partnerships underlying the HIV transmission network. The partner notification network components were bridged by transmission clusters, particularly among components dominated by men who have sex with men. Supplementing the partner notification network with phylogenetic data highlighted avenues for intervention.

A Short-Term Assessment of Nascent HIV-1 Transmission Clusters Among Newly Diagnosed Individuals Using Envelope Sequence-Based Phylogenetic Analyses

The identification of transmission clusters (TCs) of HIV-1 using phylogenetic analyses can provide insights into viral transmission network and help improve prevention strategies. We compared the use of partial HIV-1 envelope fragment of 1,070 bp with its loop 3 (108 bp) to determine its utility in inferring HIV-1 transmission clustering. Serum samples of recently (n = 106) and chronically (n = 156) HIV-1-infected patients with status confirmed were sequenced. HIV-1 envelope nucleotide-based phylogenetic analyses were used to infer HIV-1 TCs. Those were constructed using ClusterPickerGUI_1.2.3 considering a pairwise genetic distance of ≤10% threshold. Logistic regression analyses were used to examine the relationship between the demographic factors that were likely associated with HIV-1 clustering. Ninety-eight distinct consensus envelope sequences were subjected to phylogenetic analyses. Using a partial envelope fragment sequence, 42 sequences were grouped into 15 distinct small TCs while the V3 loop reproduces 10 clusters. The agreement between the partial envelope and the V3 loop fragments was significantly moderate with a Cohen's kappa (κ) coefficient of 0.59, p < .00001. The mean age (<38.8 years) and HIV-1 B subtype are two factors identified that were significantly associated with HIV-1 transmission clustering in the cohort, odds ratio (OR) = 0.25, 95% confidence interval (CI, 0.04-0.66), p = .002 and OR: 0.17, 95% CI (0.10-0.61), p = .011, respectively. The present study confirms that a partial fragment of the HIV-1 envelope sequence is a better predictor of transmission clustering. However, the loop 3 segment may be useful in screening purposes and may be more amenable to integration in surveillance programs.

TreeCluster: Clustering biological sequences using phylogenetic trees

Clustering homologous sequences based on their similarity is a problem that appears in many bioinformatics applications. The fact that sequences cluster is ultimately the result of their phylogenetic relationships. Despite this observation and the natural ways in which a tree can define clusters, most applications of sequence clustering do not use a phylogenetic tree and instead operate on pairwise sequence distances. Due to advances in large-scale phylogenetic inference, we argue that tree-based clustering is under-utilized. We define a family of optimization problems that, given an arbitrary tree, return the minimum number of clusters such that all clusters adhere to constraints on their heterogeneity. We study three specific constraints, limiting (1) the diameter of each cluster, (2) the sum of its branch lengths, or (3) chains of pairwise distances. These three problems can be solved in time that increases linearly with the size of the tree, and for two of the three criteria, the algorithms have been known in the theoretical computer scientist literature. We implement these algorithms in a tool called TreeCluster, which we test on three applications: OTU clustering for microbiome data, HIV transmission clustering, and divide-and-conquer multiple sequence alignment. We show that, by using tree-based distances, TreeCluster generates more internally consistent clusters than alternatives and improves the effectiveness of downstream applications. TreeCluster is available at https://github.com/niemasd/TreeCluster.

Enhanced use of phylogenetic data to inform public health approaches to HIV among men who have sex with men

The multidimensional nature and continued evolution of HIV epidemics among men who have sex with men (MSM) requires innovative intervention approaches. Strategies are needed that recognise the individual, social and structural factors driving HIV transmission; that can pinpoint networks with heightened transmission risk; and that can help target intervention in real time. HIV phylogenetics is a rapidly evolving field with strong promise for informing innovative responses to the HIV epidemic among MSM. Currently, HIV phylogenetic insights are providing new understandings of characteristics of HIV epidemics involving MSM, social networks influencing transmission, characteristics of HIV transmission clusters involving MSM, targets for antiretroviral and other prevention strategies and dynamics of emergent epidemics. Maximising the potential of HIV phylogenetics for HIV responses among MSM will require attention to key methodological challenges and ethical considerations, as well as resolving key implementation and scientific questions. Enhanced and integrated use of HIV surveillance, sociobehavioural and phylogenetic data resources are becoming increasingly critical for informing public health approaches to HIV among MSM.

A Phylogenetic Analysis of Human Immunodeficiency Virus Type 1 Sequences in Kiev: Findings Among Key Populations

Background

The human immunodeficiency virus (HIV) epidemic in Ukraine has been driven by a rapid rise among people who inject drugs, but recent studies have shown an increase through sexual transmission.

Methods

Protease and reverse transcriptase sequences from 876 new HIV diagnoses (April 2013-March 2015) in Kiev were linked to demographic data. We constructed phylogenetic trees for 794 subtype A1 and 64 subtype B sequences and identified factors associated with transmission clustering. Clusters were defined as ≥2 sequences, ≥80% local branch support, and maximum genetic distance of all sequence pairs in the cluster ≤2.5%. Recent infection was determined through the limiting antigen avidity enzyme immunoassay. Sequences were analyzed for transmitted drug resistance mutations.

Results

Thirty percent of subtype A1 and 66% of subtype B sequences clustered. Large clusters (maximum 11 sequences) contained mixed risk groups. In univariate analysis, clustering was significantly associated with subtype B compared to A1 (odds ratio [OR], 4.38 [95% confidence interval {CI}, 2.56-7.50]); risk group (OR, 5.65 [95% CI, 3.27-9.75]) for men who have sex with men compared to heterosexual males; recent, compared to long-standing, infection (OR, 2.72 [95% CI, 1.64-4.52]); reported sex work contact (OR, 1.93 [95% CI, 1.07-3.47]); and younger age groups compared with age ≥36 years (OR, 1.83 [95% CI, 1.10-3.05] for age ≤25 years). Females were associated with lower odds of clustering than heterosexual males (OR, 0.49 [95% CI, .31-.77]). In multivariate analysis, risk group, subtype, and age group were independently associated with clustering (P < .001, P = .007, and P = .033, respectively). Eighteen sequences (2.1%) indicated evidence of transmitted drug resistance.

Conclusions

Our findings suggest high levels of transmission and bridging between risk groups.

HIV-TRACE (TRAnsmission Cluster Engine): a Tool for Large Scale Molecular Epidemiology of HIV-1 and Other Rapidly Evolving Pathogens

In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoe-leather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, that is, on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from www.github.com/veg/hivtrace, along with the accompanying result visualization module from www.github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens.

Injection of cocaine is associated with a recent HIV outbreak in people who inject drugs in Luxembourg

BACKGROUND

An outbreak of HIV infections among people who inject drugs (PWID) started in 2014 in Luxembourg.

OBJECTIVES

We conducted phylogenetic and epidemiological analyses among the PWID infected with HIV in Luxembourg or attending the supervised drug consumption facility (SDCF) to understand the main causes of the outbreak.

METHODS

Between January 2013 and December 2017, analysis of medical files were performed from all PWID infected with HIV at the National Service of Infectious Diseases (NSID) providing clinical care nationwide. PWID were interviewed at NSID and SDCF using a standardized questionnaire focused on drug consumption and risk behaviours. The national drug monitoring system RELIS was consulted to determine the frequency of cocaine/heroin use. Transmission clusters were analysed by phylogenetic analyses using approximate maximum-likelihood. Univariate and multivariate logistic regression analyses were performed on epidemiological data collected at NSID and SDCF to determine risk factors associated with cocaine use.

RESULTS

From January 2013 to December 2017, 68 new diagnosis of HIV infection reported injecting drug use as the main risk of transmission at NSID. The proportion of female cases enrolled between 2013-2017 was higher than the proportion among cases enrolled prior to 2013. (33% vs 21%, p < 0.05). Fifty six viral sequences were obtained from the 68 PWID newly diagnosed for HIV. Two main transmission clusters were revealed: one HIV-1 subtype B cluster and one CRF14_BG cluster including 37 and 9 patients diagnosed since 2013, respectively. Interviews from 32/68 (47%) newly diagnosed PWID revealed that 12/32 (37.5%) were homeless and 27/32 (84.4%) injected cocaine. Increased cocaine injection was indeed reported by the RELIS participants from 53 to 63% in drug users with services contacts between 2012 and 2015, and from 5 to 22% in SDCF users between 2012 and 2016. Compared with PWID who injected only heroin (n = 63), PWID injecting cocaine and heroin (n = 107) were younger (mean of 38 vs 44 years, p≤0.001), reported more frequent piercing (≤0.001), shared and injected drugs more often (p≤0.01), and were more frequently HIV positive (p<0.05) at SDCF using univariate logistic regression analysis. Finally, in the multivariate analysis, use of heroin and cocaine was independently associated with younger age, piercing, sharing of drugs, and regular consumption (p<0.05).

CONCLUSIONS

Injecting cocaine is a new trend of drug use in Luxembourg associated with HIV infection in this recent outbreak among PWID.

Characterisation of HIV-1 molecular transmission clusters among newly diagnosed individuals infected with non-B subtypes in Italy

OBJECTIVE

We evaluated the characteristics of HIV-1 molecular transmission clusters (MTCs) in 1890 newly diagnosed individuals infected with non-B subtypes between 2005 and 2017 in Italy.

METHODS

Phylogenetic analyses were performed on pol sequences to characterise subtypes/circulating recombinant forms and identify MTCs. MTCs were divided into small (SMTCs, 2-3 sequences), medium (MMTCs, 4-9 sequences) and large (LMTCs, ≥10 sequences). Factors associated with MTCs were evaluated using logistic regression analysis.

RESULTS

145 MTCs were identified and involved 666 individuals (35.2%); 319 of them (16.9%) were included in 13 LMTCs, 111 (5.9%) in 20 MMTCs and 236 (12.5%) in 112 SMTCs. Compared with individuals out of MTCs, individuals involved in MTCs were prevalently Italian (72.7% vs 30.9%, p<0.001), male (82.9% vs 62.3%, p<0.001) and men who have sex with men (MSM) (43.5% vs 14.5%, p<0.001). Individuals in MTCs were also younger (median (IQR) years: 41 (35-49) vs 43 (36-51), p<0.001) and had higher CD4 cell count in comparison with individuals out of MTCs (median (IQR): 10⁹/L: 0.4 (0.265-0.587) vs 0.246 (0.082-0.417), p<0.001). The viral load remained stable between the two groups (median (IQR) log₁₀ copies/mL: 4.8 (4.2-5.5) vs 5.0 (4.3-5.5), p=0.87). Logistic regression confirmed that certain factors such as being MSM, of Italian origin, younger age and higher CD4 cell count were significantly associated with MTCs.

CONCLUSIONS

Our findings show that HIV-1 newly diagnosed individuals infected with non-B subtypes are involved in several MTCs in Italy. These MTCs include mainly Italians and MSM and highlight the complex phenomenon characterising the HIV-1 spread. This is important especially in view of monitoring the HIV epidemic and guiding the public health response.

Comparative analysis of HIV sequences in real time for public health

PURPOSE OF REVIEW

The purpose of this study is to summarize recent advances in public health applications of comparative methods for HIV-1 sequence analysis in real time, including genetic clustering methods.

RECENT FINDINGS

Over the past 2 years, several groups have reported the deployment of established genetic clustering methods to guide public health decisions for HIV prevention in 'near real time'. However, it remains unresolved how well the readouts of comparative methods like clusters translate to events that are actionable for public health. A small number of recent studies have begun to elucidate the linkage between clusters and HIV-1 incidence, whereas others continue to refine and develop new comparative methods for such applications.

SUMMARY

Although the use of established methods to cluster HIV-1 sequence databases has become a widespread activity, there remains a critical gap between clusters and public health value.

Integration of Contact Tracing and Phylogenetics in an Investigation of Acute HIV Infection

BACKGROUND

The integration of traditional contact tracing with HIV sequence analyses offers opportunities to mitigate some of the barriers to effective network construction. We used combined analyses during an outbreak investigation of spatiotemporally clustered acute HIV infections to evaluate if the observed clustering was the product of a single outbreak.

METHODS

We investigated acute and recent HIV index cases reported in North Carolina from 2013 to 2014 and their reported contacts. Contact tracing networks were constructed with surveillance data and compared with phylogenetic transmission clusters involving an index case using available HIV-1 pol sequences including 1672 references. Clusters were defined as clades of 2 or more sequences with a less than 1.5% genetic distance and a bootstrap of at least 98% on maximum-likelihood phylogenies.

RESULTS

In total, 68 index cases and 210 contacts (71 HIV infected) were reported. The contact tracing network involved 58 components with low overall density (1.2% statewide); 33% of first-degree contacts could not be located. Among 38 (56%) of 68 index cases and 34 (48%) of 71 contacts with sequences, 13 phylogenetic clusters were identified (size 2-4 members). Four clusters connected network components that were not linked in contact tracing. The largest component (n = 28 cases) included 2 distinct phylogenetic clusters and spanned 2 regions.

CONCLUSIONS

We identified the concurrent expansion of multiple small transmission clusters rather than a single outbreak in a largely disconnected contact tracing network. Integration of phylogenetic analyses provided timely information on transmission networks during the investigation. Our findings highlight the potential of combined methods to better identify high-risk networks for intervention.

HIV-1 subtype diversity, transmission networks and transmitted drug resistance amongst acute and early infected MSM populations from Coastal Kenya

Background

HIV-1 molecular epidemiology amongst men who have sex with men (MSM) in sub-Saharan Africa remains not well characterized. We aimed to determine HIV-1 subtype distribution, transmission clusters and transmitted drug resistance (TDR) in acute and early infected MSM from Coastal Kenya.

Methods

Analysis of HIV-1 partial pol sequences from MSM recruited 2005–2017 and sampled within six months of the estimated date of infection. Volunteers were classified as men who have sex with men exclusively (MSME) or with both men and women (MSMW). HIV-1 subtype and transmission clusters were determined by maximum-likelihood phylogenetics. TDR mutations were determined using the Stanford HIV drug resistance database.

Results

Of the 97 volunteers, majority (69%) were MSMW; 74%, 16%, 9% and 1% had HIV-1 subtypes A1, D, C or G, respectively. Overall, 65% formed transmission clusters, with substantial mixing between MSME and MSMW. Majority of volunteer sequences were either not linked to any reference sequence (56%) or clustered exclusively with sequences of Kenyan origin (19%). Eight (8% [95% CI: 4–16]) had at least one TDR mutation against nucleoside (n = 2 [2%]) and/or non-nucleoside (n = 7 [7%]) reverse transcriptase inhibitors. The most prevalent TDR mutation was K103N (n = 5), with sequences forming transmission clusters of two and three taxa each. There were no significant differences in HIV-1 subtype distribution and TDR between MSME and MSMW.

Conclusions

This HIV-1 MSM epidemic was predominantly sub-subtype A1, of Kenyan origin, with many transmission clusters and having intermediate level of TDR. Targeted HIV-1 prevention, early identification and care interventions are warranted to break the transmission cycle amongst MSM from Coastal Kenya.

Maintenance and reappearance of extremely divergent intra-host HIV-1 variants

Understanding genetic variation in human immunodeficiency virus (HIV) is clinically and immunologically important for patient treatment and vaccine development. We investigated the longitudinal intra-host genetic variation of HIV in over 3,000 individuals in the US National HIV Surveillance System with at least four reported HIV-1 polymerase (pol) sequences. In this population, we identified 149 putative instances of superinfection (i.e. an individual sequentially infected with genetically divergent, polyphyletic viruses). Unexpectedly, we discovered a group of 240 individuals with consecutively sampled viral strains that were >0.015 substitutions/site divergent, despite remaining monophyletic in the phylogeny. Viruses in some of these individuals had a maximum genetic divergence approaching that found between two random, unrelated HIV-1 subtype-B pol sequences within the US population. Individuals with these highly divergent viruses tended to be diagnosed nearly a decade earlier in the epidemic than people with superinfection or virus with less intra-host genetic variation, and they had distinct transmission risk factor profiles. To better understand this genetic variation in cases with extremely divergent, monophyletic viruses, we performed molecular clock phylogenetic analysis. Our findings suggest that, like Hepatitis C virus, extremely divergent HIV lineages can be maintained within an individual and reemerge over a period of years.

Transmission dynamics among participants initiating antiretroviral therapy upon diagnosis of early acute HIV-1 infection in Thailand

OBJECTIVE

To assess transmission characteristics in a predominantly MSM cohort initiating antiretroviral therapy (ART) immediately following diagnosis of acute HIV-1infection (AHI).

METHODS

A longitudinal study (2009-2017) was performed in participants with AHI (n = 439) attending a single clinic in Bangkok. Plasma samples obtained prior to ART were used to obtain HIV-1 pol sequences and combined with clinical and epidemiologic data to assess transmission dynamics (cluster formation and size) using phylogenetic analysis. Clusters were estimated using maximum likelihood, genetic distance of 1.5% and visual inspection. The potential transmitter(s) in a cluster was determined using time to viral suppression and interview data.

RESULTS

The cohort was predominantly MSM (93%) and infected with HIV-1 CRF01_AE (87%). Medians (ranges) for age and viral load prior to ART were 26 (18-70) years and 5.9 (2.5-8.2) log10 HIV-1 RNA copies/ml. Median time from history of HIV-1 exposure to diagnosis was 19 (3-61) days. Viral suppression was observed in 388 of 412 (94%) participants at a median time of 12 weeks following ART. Twenty-six clusters with median cluster size of 2 (2-5) representing 62 of 439 (14%) participants were observed. Younger age was associated with cluster formation: median 28 versus 30 years for unique infections (P = 0.01). A potential transmitter was identified in 11 of 26 (42%) clusters.

CONCLUSION

Despite high rates of viral suppression following diagnosis and treatment of AHI within a cohort of young Thai MSM, HIV-1 transmission continued, reflecting the need to expand awareness and treatment access to the entire MSM population.

HIV-genetic diversity and drug resistance transmission clusters in Gondar, Northern Ethiopia, 2003-2013

BACKGROUND

The HIV-1 epidemic in Ethiopia has been shown to be dominated by two phylogenetically distinct subtype C clades, the Ethiopian (C'-ET) and East African (C-EA) clades, however, little is known about the temporal dynamics of the HIV epidemic with respect to subtypes and distinct clades. Moreover, there is only limited information concerning transmission of HIV-1 drug resistance (TDR) in the country.

METHODS

A cross-sectional survey was conducted among young antiretroviral therapy (ART)-naïve individuals recently diagnosed with HIV infection, in Gondar, Ethiopia, 2011-2013 using the WHO recommended threshold survey. A total of 84 study participants with a median age of 22 years were enrolled. HIV-1 genotyping was performed and investigated for drug resistance in 67 individuals. Phylogenetic analyses were performed on all available HIV sequences obtained from Gondar (n = 301) which were used to define subtype C clades, temporal trends and local transmission clusters. Dating of transmission clusters was performed using BEAST.

RESULT

Four of 67 individuals (6.0%) carried a HIV drug resistance mutation strain, all associated with non-nucleoside reverse transcriptase inhibitors (NNRTI). Strains of the C-EA clade were most prevalent as we found no evidence of temporal changes during this time period. However, strains of the C-SA clade, prevalent in Southern Africa, have been introduced in Ethiopia, and became more abundant during the study period. The oldest Gondar transmission clusters dated back to 1980 (C-EA), 1983 (C-SA) and 1990 (C'-ET) indicating the presence of strains of different subtype C clades at about the same time point in Gondar. Moreover, some of the larger clusters dated back to the 1980s but transmissions within clusters have been ongoing up till end of the study period. Besides being associated with more sequences and larger clusters, the C-EA clade sequences were also associated with clustering of HIVDR sequences. One cluster was associated with the G190A mutation and showed onward transmissions at high rate.

CONCLUSION

TDR was detected in 6.0% of the sequenced samples and confirmed pervious reports that the two subtype C clades, C-EA and C'-ET, are common in Ethiopia. Moreover, the findings indicated an increased diversity in the epidemic as well as differences in transmission clusters sizes of the different clades and association with resistance mutations. These findings provide epidemiological insights not directly available using standard surveillance and may inform the adjustment of public health strategies in HIV prevention in Ethiopia.

Prevalence of Transmitted HIV drug resistance in antiretroviral treatment naïve newly diagnosed individuals in China

To investigate the prevalence and temporal trend of transmitted drug resistance (TDR), a nationwide cross-sectional survey was conducted among 5627 ART naïve newly diagnosed HIV-infected individuals in 2015 in China. Totally 4704 partial pol sequences were obtained. Among them, the most common HIV-1 circulating recombinant form (CRF) or subtype was CRF01_AE (39.0%), followed by CRF07_BC (35.6%), CRF08_BC (8.9%), and subtype B (5.5%). TDR mutations were found in 3.6% of the cases, with 1.1% harboring TDR to protease inhibitors (PIs), 1.3% having TDR to nucleoside reverse transcriptase inhibitors (NRTIs), and 1.6% to non-nucleoside reverse transcriptase inhibitors (NNRTIs). No significant difference was found in the prevalence of TDR, as compared with the results of another nationwide survey performed among ART naïve HIV-infected people in between 2004 and 2005, except in the 16-25 year-old group. In addition, four drug-resistant transmission clusters were identified in phylogenetic trees, accounting for 6.2% (9/145) of the individuals with TDR. Although the rate of TDR remained relatively low in the past 10 years in China, surveillance is still needed to monitor the trend of TDR and to optimize the first-line regimens.