A public health model for the molecular surveillance of HIV transmission in San Diego, California

Predictors of HIV Molecular Cluster Membership and Implications for Partner Services

Public health surveillance data used in HIV molecular cluster analyses lack contextual information that is available from partner services (PS) data. Integrating these data sources in retrospective analyses can enrich understanding of the risk profile of people in clusters. In this study, HIV molecular clusters were identified and matched to information on partners and other information gleaned at the time of diagnosis, including coinfection with syphilis. We aimed to produce a more complete understanding of molecular cluster membership in Houston, Texas, a city ranking ninth nationally in rate of new HIV diagnoses that may benefit from retrospective matched analyses between molecular and PS data to inform future intervention. Data from PS were matched to molecular HIV records of people newly diagnosed from 2012 to 2018. By conducting analyses in HIV-TRACE (TRAnsmission Cluster Engine) using viral genetic sequences, molecular clusters were detected. Multivariable logistic regression models were used to estimate the association between molecular cluster membership and completion of a PS interview, number of named partners, and syphilis coinfection. Using data from 4,035 people who had a viral genetic sequence and matched PS records, molecular cluster membership was not significantly associated with completion of a PS interview. Among those with sequences who completed a PS interview (n = 3,869), 45.3% (n = 1,753) clustered. Molecular cluster membership was significantly associated with naming 1 or 3+ partners compared with not naming any partners [adjusted odds ratio, aOR: 1.27 (95% confidence interval, CI: 1.08-1.50), p = .003 and aOR: 1.38 (95% CI: 1.06-1.81), p = .02]. Alone, coinfection with syphilis was not significantly associated with molecular cluster membership. Syphilis coinfection was associated with molecular cluster membership when coupled with incarceration [aOR: 1.91 (95% CI: 1.08-3.38), p = .03], a risk for treatment interruption. Enhanced intervention among those with similar profiles, such as people coinfected with other risks, may be warranted.

An Automated Bioinformatics Pipeline Informing Near-Real-Time Public Health Responses to New HIV Diagnoses in a Statewide HIV Epidemic

Molecular HIV cluster data can guide public health responses towards ending the HIV epidemic. Currently, real-time data integration, analysis, and interpretation are challenging, leading to a delayed public health response. We present a comprehensive methodology for addressing these challenges through data integration, analysis, and reporting. We integrated heterogeneous data sources across systems and developed an open-source, automatic bioinformatics pipeline that provides molecular HIV cluster data to inform public health responses to new statewide HIV-1 diagnoses, overcoming data management, computational, and analytical challenges. We demonstrate implementation of this pipeline in a statewide HIV epidemic and use it to compare the impact of specific phylogenetic and distance-only methods and datasets on molecular HIV cluster analyses. The pipeline was applied to 18 monthly datasets generated between January 2020 and June 2022 in Rhode Island, USA, that provide statewide molecular HIV data to support routine public health case management by a multi-disciplinary team. The resulting cluster analyses and near-real-time reporting guided public health actions in 37 phylogenetically clustered cases out of 57 new HIV-1 diagnoses. Of the 37, only 21 (57%) clustered by distance-only methods. Through a unique academic-public health partnership, an automated open-source pipeline was developed and applied to prospective, routine analysis of statewide molecular HIV data in near-real-time. This collaboration informed public health actions to optimize disruption of HIV transmission.

Quantifying and Predicting Ongoing Human Immunodeficiency Virus Type 1 Transmission Dynamics in Switzerland Using a Distance-Based Clustering Approach

BACKGROUND

Despite effective prevention approaches, ongoing human immunodeficiency virus 1 (HIV-1) transmission remains a public health concern indicating a need for identifying its drivers.

METHODS

We combined a network-based clustering method using evolutionary distances between viral sequences with statistical learning approaches to investigate the dynamics of HIV transmission in the Swiss HIV Cohort Study and to predict the drivers of ongoing transmission.

RESULTS

We found that only a minority of clusters and patients acquired links to new infections between 2007 and 2020. While the growth of clusters and the probability of individual patients acquiring new links in the transmission network was associated with epidemiological, behavioral, and virological predictors, the strength of these associations decreased substantially when adjusting for network characteristics. Thus, these network characteristics can capture major heterogeneities beyond classical epidemiological parameters. When modeling the probability of a newly diagnosed patient being linked with future infections, we found that the best predictive performance (median area under the curve receiver operating characteristic AUCROC = 0.77) was achieved by models including characteristics of the network as predictors and that models excluding them performed substantially worse (median AUCROC = 0.54).

CONCLUSIONS

These results highlight the utility of molecular epidemiology-based network approaches for analyzing and predicting ongoing HIV transmission dynamics. This approach may serve for real-time prospective assessment of HIV transmission.

Molecular epidemiology of HIV-1 among adult female sex workers at the Guatemala-Mexico border

ABSTRACTSex workers have been demonstrated to have increased vulnerabilities to HIV and a high population prevalence of the disease. Despite their increased risk, sex workers have been underrepresented in molecular epidemiology studies assessing HIV in Mesoamerica. This study aims to describe the sociodemographic characteristics and phylogenetic profile of HIV-1 within a cohort of HIV-positive female sex workers (FSW) situated at the Guatemala-Mexico border. HIV viral sequences were collected from a cohort of FSW ≥18 years of age from San Marcos, Guatemala (n = 6) and compared to viral sequences collected as part of the Mesoamerican Drug Resistance Monitoring Programme to assess HIV viral diversity in Mexico and Guatemala (n = 3956). All of the FSW sampled were determined to have genetically unrelated HIV infections, suggesting multiple introductions of the virus and/or the potential existence of populations not captured by current surveillance efforts. Many reported numerous vulnerabilities that may have heightened their risk of acquiring and transmitting HIV through sex work activities. Our phylogenetic analysis indicated that national surveillance programmes may not fully capture the viral diversity among FSW and their clients within this region. Additional research is needed to fully capture HIV diversity and transmission in Mesoamerica, especially in the Guatemala-Mexico border region.

HIV Response Interventions that Integrate HIV Molecular Cluster and Social Network Analysis: A Systematic Review

Due to improved efficiency and reduced cost of viral sequencing, molecular cluster analysis can be feasibly utilized alongside existing human immunodeficiency virus (HIV) prevention strategies. The goal of this paper is to elucidate how HIV molecular cluster and social network analyses are being integrated to implement HIV response interventions. We searched PubMed, Scopus, PsycINFO, and Cochrane Library databases for studies incorporating both HIV molecular cluster and social network data. We identified 32 articles that combined analyses of HIV molecular sequences and social or sexual networks. All studies were descriptive. Six studies described network interventions informed by molecular and social data but did not fully evaluate their efficacy. There is no current standard for incorporating molecular and social network analyses to inform interventions or data demonstrating its utility. More research must be conducted to delineate benefits and best practices for leveraging molecular data for network-based interventions.

Multiple CRF01_AE/CRF07_BC Recombinants Enhanced the HIV-1 Epidemic Complexity Among MSM in Shenyang City, Northeast China

The transmission of Unique Recombinant Forms (URFs) has complicated the molecular epidemic of HIV-1. This increasing genetic diversity has implications for prevention surveillance, diagnosis, and vaccine design. In this study, we characterized the HIV-1 URFs from 135 newly diagnosed HIV-1 infected cases between 2016 and 2020 in Shenyang, northeast China and analyzed the evolutionary relationship of them by phylogenetic and recombination approaches. Among 135 URFs, we found that the CRF01_AE/CRF07_BC recombinants were the most common (81.5%, 110/135), followed by CRF01_AE/B (11.9%, 16/135), B/C (3.7%, 5/135), and others (3.0%, 4/135). 94.8% (128/135) of patients infected by URFs were through homosexual contact. Among 110 URFs_0107, 60 (54.5%) formed 11 subclusters (branch support value = 1) and shared the consistent recombination structure, respectively. Four subclusters have caused small-scale spread among different high-risk populations. Although the recombination structures of URFs_0107 are various, the hotspots of recombinants gathered between position 2,508 and 2,627 (relative to the HXB2 position). Moreover, the CRF07_BC and CRF01AE fragments of URFs_0107 were mainly derived from the MSM population. In brief, our results reveal the complex recombinant modes and the high transmission risk of URFs_0107, which calls for more attention on the new URFs_0107 monitoring and strict control in the areas led by homosexual transmission route.

Phylogenetic prioritization of HIV-1 transmission clusters with viral lineage-level diversification rates

Background and objectives

Public health officials faced with a large number of transmission clusters require a rapid, scalable and unbiased way to prioritize distribution of limited resources to maximize benefits. We hypothesize that transmission cluster prioritization based on phylogenetically derived lineage-level diversification rates will perform as well as or better than commonly used growth-based prioritization measures, without need for historical data or subjective interpretation.

Methodology

9822 HIV pol sequences collected during routine drug resistance genotyping were used alongside simulated sequence data to infer sets of phylogenetic transmission clusters via patristic distance threshold. Prioritized clusters inferred from empirical data were compared to those prioritized by the current public health protocols. Prioritization of simulated clusters was evaluated based on correlation of a given prioritization measure with future cluster growth, as well as the number of direct downstream transmissions from cluster members.

Results

Empirical data suggest diversification rate-based measures perform comparably to growth-based measures in recreating public heath prioritization choices. However, unbiased simulated data reveals phylogenetic diversification rate-based measures perform better in predicting future cluster growth relative to growth-based measures, particularly long-term growth. Diversification rate-based measures also display advantages over growth-based measures in highlighting groups with greater future transmission events compared to random groups of the same size. Furthermore, diversification rate measures were notably more robust to effects of decreased sampling proportion.

Conclusions and implications

Our findings indicate diversification rate-based measures frequently outperform growth-based measures in predicting future cluster growth and offer several additional advantages beneficial to optimizing the public health prioritization process.

Integrated molecular and affiliation network analysis: Core-periphery social clustering is associated with HIV transmission patterns

This study investigates the two-mode core-periphery structures of venue affiliation networks of younger Black men who have sex with men (YBMSM). We examined the association between these structures and HIV phylogenetic clusters, defined as members who share highly similar HIV strains that are regarded as a proxy for sexual affiliation networks. Using data from 114 YBMSM who are living with HIV in two large U.S. cities, we found that HIV phylogenetic clustering patterns were associated with social clustering patterns whose members share affiliation with core venues that overlap with those of YBMSM. Distinct HIV transmission patterns were found in each city, a finding that can help to inform tailored venue-based and network intervention strategies.

Characteristics and growth of the genetic HIV transmission network of Mexico City during 2020

INTRODUCTION

Molecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention.

METHODS

All new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV-TRACE tool: Seguro HIV-TRACE. Socio-demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions.

RESULTS

A total of 3168 HIV sequences from unique individuals were included. One thousand and one-hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p<0.001; >34 vs. <24 years), being a man who has sex with men (MSM) (aOR: 2.47, p = 0.004; MSM vs. cisgender women), having higher viral load (aOR: 1.28, p<0.001) and higher CD4+ T cell count (aOR: 1.80, p<0.001; ≥500 vs. <200 cells/mm3 ) remained associated with higher odds of clustering. Compared to MSM, cisgender women and heterosexual men had significantly lower education (none or any elementary: 59.1% and 54.2% vs. 16.6%, p<0.001) and socio-economic status (low income: 36.4% and 29.0% vs. 18.6%, p = 0.03) than MSM. We identified 10 (2.6%) clusters with constant growth, for prioritized intervention, that included intersecting sexual risk groups, highly connected nodes and bridge nodes between possible sub-clusters with high growth potential.

CONCLUSIONS

HIV transmission in Mexico City is strongly driven by young MSM with higher education level and recent infection. Nevertheless, leveraging network inference, we identified actively growing clusters that could be prioritized for focused intervention with demographic and risk characteristics that do not necessarily reflect the ones observed in the overall clustering population. Further studies evaluating different models to predict growing clusters are warranted. Focused interventions will have to consider structural and risk disparities between the MSM and the heterosexual populations.

Interdisciplinary HIV Sentinel Case Review: Identifying Practices to Prevent Outbreaks in Philadelphia

INTRODUCTION

The Ending the HIV Epidemic in the U.S. initiative considers cluster and outbreak response essential. This article describes the design, implementation, and early findings of a Philadelphia-based project to systematically assess sentinel cases among priority populations for improving public health infrastructure and preventing future outbreaks.

METHODS

Sentinel HIV cases (i.e., early-stage or acute infection or molecular cluster cases) were identified among priority populations (Black and Hispanic/Latino men who have sex with men, youth aged 18-24 years, and transgender people who have sex with men). Chart abstraction and structured interview data were reviewed to determine themes and service gaps and to identify, prioritize, and implement recommendations. Interdisciplinary review teams included individuals with lived experience, frontline staff, and local agency leadership.

RESULTS

Data were collected during July 2019-December 2020 and analyzed for 53 of 126 sentinel cases of HIV diagnosed since July 1, 2018. The majority were men who have sex with men (79.3%), those aged 18-24 years (67.9%), and non-Hispanic Black (67.9%). More than half received sexually transmitted infection and HIV testing ≤3 years preceding HIV diagnosis (56.6% and 54.7%, respectively), had a healthcare visit within 12 months before diagnosis (64.2%), and had no evidence of pre-exposure prophylaxis awareness (58.5%). Project recommendations effectuated actions to improve pre-exposure prophylaxis provision, integrate sexually transmitted infection and HIV testing, and educate primary care providers.

CONCLUSIONS

HIV sentinel case review is a model for health departments to rapidly respond to recent transmission, identify missed HIV prevention opportunities, strengthen community partnerships, and implement programmatic and policy changes. Such efforts may prevent outbreaks and inform longer-term strategies.

Sorting by Race/Ethnicity Across HIV Genetic Transmission Networks in Three Major Metropolitan Areas in the United States

An important component underlying the disparity in HIV risk between race/ethnic groups is the preferential transmission between individuals in the same group. We sought to quantify transmission between different race/ethnicity groups and measure racial assortativity in HIV transmission networks in major metropolitan areas in the United States. We reconstructed HIV molecular transmission networks from viral sequences collected as part of HIV surveillance in New York City, Los Angeles County, and Cook County, Illinois. We calculated assortativity (the tendency for individuals to link to others with similar characteristics) across the network for three candidate characteristics: transmission risk, age at diagnosis, and race/ethnicity. We then compared assortativity between race/ethnicity groups. Finally, for each race/ethnicity pair, we performed network permutations to test whether the number of links observed differed from that expected if individuals were sorting at random. Transmission networks in all three jurisdictions were more assortative by race/ethnicity than by transmission risk or age at diagnosis. Despite the different race/ethnicity proportions in each metropolitan area and lower proportions of clustering among African Americans than other race/ethnicities, African Americans were the group most likely to have transmission partners of the same race/ethnicity. This high level of assortativity should be considered in the design of HIV intervention and prevention strategies.

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.

Molecular surveillance of HIV-1 newly diagnosed infections in Shenzhen, China from 2011 to 2018

OBJECTIVES

Shenzhen is suffering severe HIV epidemic. No systematic surveillance on high risk populations, HIV genetic diversity, transmitted drug resistance (TDR) and molecular transmission clusters (MTCs) have been reported yet. In this study, we described them based on newly diagnosed HIV positive cases from 2011 to 2018 in Shenzhen city, China.

METHODS

Plasma samples of newly reported HIV positive cases in Shenzhen, China were collected from 2011 to 2018. The HIV pol gene was amplified and sequenced for subtyping, genetic characterization, TDR and phylogenetic analysis. Demographic and risk characteristics associated with transmitted drug resistance-associated mutations (TDRAMs) and MTCs were explored by using logistic regression analyses.

RESULTS

10,378 HIV pol sequences were successfully obtained from newly diagnosed patients with available background information. The most prevalent HIV-1 subtype was CRF07_BC (40.92%). CRF07_BC, CRF55_01B and URFs increased across years. Total TDR was 6.02% during 2011 to 2018. CRF01_AE, CRF08_BC, CRF55_01B and subtype B were more likely to be associated with TDRAMs than CRF07_BC. 4460 (42.98%) patients were infected with strains included in MTCs. Patients younger than 30 and over 50 years were more likely to cluster.

CONCLUSIONS

The prevalence of HIV-1 drug resistance and molecular transmission clusters in Shenzhen should raise a high alert. Interventions targeting on patients with strains locating in MTCs should be considered to improve prevention effect in Shenzhen.

HIV Care Prioritization Using Phylogenetic Branch Length

BACKGROUND

The structure of the HIV transmission networks can be dictated by just a few individuals. Public health intervention, such as ensuring people living with HIV adhere to antiretroviral therapy and remain virally suppressed, can help control the spread of the virus. However, such intervention requires using limited public health resource allocations. Determining which individuals are most at risk of transmitting HIV could allow public health officials to focus their limited resources on these individuals.

SETTING

Molecular epidemiology can help prioritize people living with HIV by patterns of transmission inferred from their sampled viral sequences. Such prioritization has been previously suggested and performed by monitoring cluster growth. In this article, we introduce Prioritization using AnCesTral edge lengths (ProACT), a phylogenetic approach for prioritizing individuals living with HIV.

METHODS

ProACT starts from a phylogeny inferred from sequence data and orders individuals according to their terminal branch length, breaking ties using ancestral branch lengths. We evaluated ProACT on a real data set of 926 HIV-1 subtype B pol data obtained in San Diego between 2005 and 2014 and a simulation data set modeling the same epidemic. Prioritization methods are compared by their ability to predict individuals who transmit most after the prioritization.

RESULTS

Across all simulation conditions and most real data sampling conditions, ProACT outperformed monitoring cluster growth for multiple metrics of prioritization efficacy.

CONCLUSION

The simple strategy used by ProACT improves the effectiveness of prioritization compared with state-of-the-art methods that rely on monitoring the growth of transmission clusters defined based on genetic distance.

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.

Advances in research of HIV transmission networks

Transmission network analysis is a crucial evaluation tool aiming to explore the characteristics of the human immunodeficiency virus epidemic, develop evidence-based prevention strategies, and contribute to various areas of human immunodeficiency virus/acquired immunodeficiency syndrome prevention and control. Over recent decades, transmission networks have made tremendous strides in terms of modes, methods, applications, and various other aspects. Transmission network methods, including social, sexual, and molecular transmission networks, have played a pivotal role. Each transmission network research method has its advantages, as well as its limitations. In this study, we established a systematic review of these aforementioned transmission networks with respect to their definitions, applications, limitations, recent progress, and synthetic applications.

The Relationship Between the Human Immunodeficiency Virus-1 Transmission Network and the HIV Care Continuum in Los Angeles County

BACKGROUND

Public health action combating human immunodeficiency virus (HIV) includes facilitating navigation through the HIV continuum of care: timely diagnosis followed by linkage to care and initiation of antiretroviral therapy to suppress viral replication. Molecular epidemiology can identify rapidly growing HIV genetic transmission clusters. How progression through the care continuum relates to transmission clusters has not been previously characterized.

METHODS

We performed a retrospective study on HIV surveillance data from 5226 adult cases in Los Angeles County diagnosed from 2010 through 2014. Genetic transmission clusters were constructed using HIV-TRACE. Cox proportional hazard models were used to estimate the impact of transmission cluster growth on the time intervals between care continuum events. Gamma frailty models incorporated the effect of heterogeneity associated with genetic transmission clusters.

RESULTS

In contrast to our expectations, there were no differences in time to the care continuum events among individuals in clusters with different growth dynamics. However, upon achieving viral suppression, individuals in high growth clusters were slower to experience viral rebound (hazard ratio 0.83, P = .011) compared with individuals in low growth clusters. Heterogeneity associated with cluster membership in the timing to each event in the care continuum was highly significant (P < .001), with and without adjustment for transmission risk and demographics.

CONCLUSIONS

Individuals within the same transmission cluster have more similar trajectories through the HIV care continuum than those across transmission clusters. These findings suggest molecular epidemiology can assist public health officials in identifying clusters of individuals who may benefit from assistance in navigating the HIV care continuum.

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.

Bayesian reconstruction of transmission trees from genetic sequences and uncertain infection times

Genetic sequence data of pathogens are increasingly used to investigate transmission dynamics in both endemic diseases and disease outbreaks. Such research can aid in the development of appropriate interventions and in the design of studies to evaluate them. Several computational methods have been proposed to infer transmission chains from sequence data; however, existing methods do not generally reliably reconstruct transmission trees because genetic sequence data or inferred phylogenetic trees from such data contain insufficient information for accurate estimation of transmission chains. Here, we show by simulation studies that incorporating infection times, even when they are uncertain, can greatly improve the accuracy of reconstruction of transmission trees. To achieve this improvement, we propose a Bayesian inference methods using Markov chain Monte Carlo that directly draws samples from the space of transmission trees under the assumption of complete sampling of the outbreak. The likelihood of each transmission tree is computed by a phylogenetic model by treating its internal nodes as transmission events. By a simulation study, we demonstrate that accuracy of the reconstructed transmission trees depends mainly on the amount of information available on times of infection; we show superiority of the proposed method to two alternative approaches when infection times are known up to specified degrees of certainty. In addition, we illustrate the use of a multiple imputation framework to study features of epidemic dynamics, such as the relationship between characteristics of nodes and average number of outbound edges or inbound edges, signifying possible transmission events from and to nodes. We apply the proposed method to a transmission cluster in San Diego and to a dataset from the 2014 Sierra Leone Ebola virus outbreak and investigate the impact of biological, behavioral, and demographic factors.

HIV-1 transmitted drug resistance surveillance: shifting trends in study design and prevalence estimates

INTRODUCTION

HIV-1 transmitted drug resistance (TDR) prevalence increased during the initial years of the antiretroviral therapy (ART) global scale-up. Few studies have examined recent trends in TDR prevalence using published genetic sequences and described the characteristics of ART-naïve persons from whom these published sequences have been obtained.

METHODS

We identified 125 studies published between 2014 and 2019 for which HIV-1 reverse transcriptase (RT) with or without protease from ≥50 ART-naïve adult persons were submitted to the GenBank sequence database. The population characteristics and TDR prevalence were compared to those in 122 studies published in the preceding five years between 2009 and 2013. TDR prevalence was analysed using median study-level and person-level data.

RESULTS AND DISCUSSION

The 2009 to 2013 and 2014 to 2019 studies reported sequence data from 32,866 and 41,724 ART-naïve persons respectively. Studies from the low- and middle-income country (LMIC) regions in sub-Saharan Africa, South/Southeast Asia and Latin America/Caribbean accounted for approximately two-thirds of the studies during each period. Between the two periods, the proportion of studies from sub-Saharan Africa and from South/Southeast Asia countries other than China decreased from 43% to 32% and the proportion of studies performed at sentinel sites for recent HIV-1 infection decreased from 33% to 22%. Between 2014 and 2019, median study-level TDR prevalence was 4.1% in South/Southeast Asia, 6.0% in sub-Saharan Africa, 9.1% in Latin America/Caribbean, 8.5% in Europe and 14.2% in North America. In the person-level analysis, there was an increase in overall, NNRTI and two-class NRTI/NNRTI resistance in sub-Saharan Africa; an increase in NNRTI resistance in Latin America/Caribbean, and an increase in overall, NNRTI and PI resistance in North America.

CONCLUSIONS

Overall, NNRTI and dual NRTI/NNRTI-associated TDR prevalence was significantly higher in sub-Saharan Africa studies published between 2014 and 2019 compared with those published between 2009 and 2013. The decreasing proportion of studies from the hardest hit LMIC regions and the shift away from sentinel sites for recent infection suggests that global TDR surveillance efforts and publication of findings require renewed emphasis.

Recent HIV Infection among men who have sex with men and transgender women in Tijuana

OBJECTIVE To characterize recent HIV infections among newly diagnosed men who have sex with men and transgender women in Tijuana. METHODS Limiting Antigen (LAg)-Avidity testing was performed to detect recent HIV infection within a cohort of newly-diagnosed men who have sex with men and transgender women in Tijuana. Logistic regression was used to determine characteristics associated with recent infection. A partial transmission network was inferred using HIV-1 pol sequences. Tamura-Nei 93 genetic distances were measured between all pairs of sequences, and the network was constructed by inferring putative transmission links (genetic distances ≤ 1.5%). We assessed whether recent infection was associated with clustering within the inferred network. RESULTS Recent infection was detected in 11% (22/194) of newly-diagnosed participants. Out of the participants with sequence data, 60% (9/15) with recent infection clustered compared with 31% (43/139) with chronic infection. Two recent infections belonged to the same cluster. In adjusted analyses, recent infection was associated with years of residence in Tijuana (OR = 1.5; 95%CI 1.01-1.09), cocaine use (past month) (OR = 8.50; 95%CI 1.99-28.17), and ever experiencing sexual abuse (OR = 2.85; 95%CI 1.03-7.85). DISCUSSION A total of 11% of men newly diagnosed with HIV who have sex with men and transgender women in Tijuana were recently infected. The general lack of clustering between participants with recent infection suggests continued onward HIV transmission rather than an outbreak within a particular cluster.

Incident infection in high-priority HIV molecular transmission clusters in the United States

OBJECTIVE

To identify correlates of incident HIV infection in rapidly growing HIV molecular clusters.

DESIGN

Phylogenetic analysis of HIV public health surveillance data.

METHODS

High-priority HIV genetic transmission clusters with evidence of rapid growth in 2012 (i.e. clusters with a pairwise genetic distance ≤0.005 substitutions/site and at least three cases diagnosed in 2012) were identified using HIV-TRACE. Then, we investigated cluster growth, defined as HIV cases diagnosed in the following 5 years that were genetically linked to these clusters. For clusters that grew during the follow-up period, Bayesian molecular clock phylogenetic inference was performed to identify clusters with evidence of incident HIV infection (as opposed to diagnosis of previously infected cases) during this follow-up period.

RESULTS

Of the 116 rapidly growing clusters identified, 73 (63%) had phylogenetic evidence for an incident HIV case during the 5-year follow-up period. Correlates of an incident HIV case arising in clusters included a greater number of diagnosed but virally unsuppressed cases in 2012, a greater number of inferred undiagnosed cases in the cluster in 2012, and a younger time of most recent common ancestor for the cluster.

CONCLUSION

These findings suggest that incident infections in rapidly growing clusters originate equally from diagnosed but unsuppressed cases and undiagnosed infections. These results highlight the importance of promoting retention in care and viral suppression as well as partner notification and other case-finding activities when investigating and intervening on high-priority molecular transmission clusters.

HIV-1 Drug Resistance in ART-Naïve Individuals in Myanmar

Background

Estimating the prevalence and characterizing the transmission of HIV-1 drug resistance in treatment-naïve individuals are very important in the prevention and control of HIV/AIDS. As one of the areas most affected by HIV/AIDS, few data are currently available for HIV-1 drug resistance in antiretroviral therapy (ART)-naïve individuals in Myanmar, which borders Yunnan, China.

Methods

HIV-1 pol sequences from ART-naïve HIV-1-infected individuals during 2008 and 2014 in Myanmar were retrieved from our previous studies. HIV-1 transmitted drug resistance (TDR) and susceptibility to antiretroviral drugs were predicted using the Stanford HIVdb program. HIV-1 transmission cluster (TC) was determined by Cluster Picker.

Results

A total of 169 partial pol sequences from ART-naïve HIV-1 positive Burmese were analyzed. The prevalence of TDR was 20.1%. CRF01_AE and BC recombinants appeared to have a higher prevalence of TDR than other subtypes. The V179D/T was found to be very common in the China–Myanmar border region and was involved in half of the transmission clusters formed by HIV-1 drug-resistance strains in this region. Comparison showed that drug-resistance mutation profile in Myanmar was very similar to that in Dehong prefecture of Yunnan. By further phylogenetic analysis with all available sequences from the China–Myanmar border region, four HIV-1 drug-resistance-related TCs were identified. Three of them were formed by Burmese long-distance truck drivers and the Burmese staying in Yunnan, and another was formed by Burmese injection drug users staying in Myanmar and Yunnan. These results suggest a potential transmission link of HIV-1 drug resistance between Myanmar and Yunnan.

Conclusion

Given the high prevalence of TDR in Myanmar, and the potential risk of cross-border transmission of HIV-1 drug-resistant strains between Myanmar and Yunnan, China, ongoing monitoring of HIV-1 drug resistance in ART-naïve individuals will provide a guideline for clinical antiretroviral treatment and benefit the prevention and control of HIV/AIDS in this border region.

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.

Genetic characterization of HIV-1 epidemic in Anhui Province, China

Background

Anhui Province in China is facing a severe HIV epidemic with an increasing number of newly diagnosed cases.

Methods

In this study, HIV genetic characteristics in the province were investigated. Newly reported HIV-positive individuals from 15 districts of Anhui Province were enrolled and interviewed. Total viral RNA was extracted from plasma isolated from blood samples. We amplified and sequenced an HIV pol fragment of the 1062 bp. The sequences were used for determination of HIV subtypes and the presence of drug resistance mutations. Transmission networks were constructed to explore possible relationships. And all of assembled partial pol genes were submitted to the Stanford HIV Drug Resistance Database website to find the transmitted drug resistance.

Results

Partial pol gene sequences were obtained from 486 cases. The results showed that MSM was the most dominant transmission route (253, 52.06%), followed by heterosexual transmission (210, 43.21%) and blood-borne transmission (1, 0.21%). Many subtypes were identified, including CRF01_AE (226, 46.50%), CRF07_BC (151, 31.07%), subtype B (28, 5.76%), CRF08_BC (20, 4.12%), CRF55_01B (15, 3.09%), CRF68_01B (7, 1.44%), CRF67_01B (3, 0.62%), CRF57_BC (2, 0.41%), CRF59_01B (2, 0.41%), CRF79_0107 (2, 0.41%), subtype C (2, 0.41%), CRF64_BC (1, 0.21%), and circulating recombinant forms (URFs) (27, 5.55%). Four transmission subnetworks containing high transmission risk individuals (with degree ≥4) were identified based on CRF01_AE and CRF07_BC sequences, including two CRF01_AE transmission subnetworks constituted by elderly people with average ages of 67.9 and 61.5 years. Infection occurred most likely through heterosexual transmission, while the other two CRF07_BC transmission subnetworks consist mainly of MSMs with average ages of 31.73 and 34.15. The level of HIV-transmitted drug resistance is 3.09%.

Conclusions

The simultaneous spread of multiple HIV subtypes in Anhui province underscores that close surveillance of the local HIV epidemic is necessary. Furthermore, the elderly people were frequently involved, arguing for behaviour intervention in this specific population besides the MSM risk group.

Characterization of Molecular Cluster Detection and Evaluation of Cluster Investigation Criteria Using Machine Learning Methods and Statewide Surveillance Data in Washington State

Molecular cluster detection can be used to interrupt HIV transmission but is dependent on identifying clusters where transmission is likely. We characterized molecular cluster detection in Washington State, evaluated the current cluster investigation criteria, and developed a criterion using machine learning. The population living with HIV (PLWH) in Washington State, those with an analyzable genotype sequences, and those in clusters were described across demographic characteristics from 2015 to2018. The relationship between 3- and 12-month cluster growth and demographic, clinical, and temporal predictors were described, and a random forest model was fit using data from 2016 to 2017. The ability of this model to identify clusters with future transmission was compared to Centers for Disease Control and Prevention (CDC) and the Washington state criteria in 2018. The population with a genotype was similar to all PLWH, but people in a cluster were disproportionately white, male, and men who have sex with men. The clusters selected for investigation by the random forest model grew on average 2.3 cases (95% CI 1.1–1.4) in 3 months, which was not significantly larger than the CDC criteria (2.0 cases, 95% CI 0.5–3.4). Disparities in the cases analyzed suggest that molecular cluster detection may not benefit all populations. Jurisdictions should use auxiliary data sources for prediction or continue using established investigation criteria.

Using Social Networks to Understand and Overcome Implementation Barriers in the Global HIV Response

BACKGROUND

Despite the development of several efficacious HIV prevention and treatment methods in the past 2 decades, HIV continues to spread globally. Uptake of interventions is nonrandomly distributed across populations. Such inequality is socially patterned and reinforced by homophily arising from both social selection (becoming friends with similar people) and influence (becoming similar to friends).

METHODS

We conducted a narrative review to describe how social network analysis methods-including egocentric, sociocentric, and respondent-driven sampling designs-provide tools to measure key populations, to understand how epidemics spread, and to evaluate intervention take-up.

RESULTS

Social network analysis-informed designs can improve intervention effectiveness by reaching otherwise inaccessible populations. They can also improve intervention efficiency by maximizing spillovers, through social ties, to at-risk but susceptible individuals. Social network analysis-informed designs thus have the potential to be both more effective and less unequal in their effects, compared with social network analysis-naïve approaches. Although social network analysis-informed designs are often resource-intensive, we believe they provide unique insights that can help reach those most in need of HIV prevention and treatment interventions.

CONCLUSION

Increased collection of social network data during both research and implementation work would provide important information to improve the roll-out of existing studies in the present and to inform the design of more data-efficient, social network analysis-informed interventions in the future. Doing so will improve the reach of interventions, especially to key populations, and to maximize intervention impact once delivered.

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.

Identifying Clusters of Recent and Rapid HIV Transmission Through Analysis of Molecular Surveillance Data

BACKGROUND

Detecting recent and rapid spread of HIV can help prioritize prevention and early treatment for those at highest risk of transmission. HIV genetic sequence data can identify transmission clusters, but previous approaches have not distinguished clusters of recent, rapid transmission. We assessed an analytic approach to identify such clusters in the United States.

METHODS

We analyzed 156,553 partial HIV-1 polymerase sequences reported to the National HIV Surveillance System and inferred transmission clusters using 2 genetic distance thresholds (0.5% and 1.5%) and 2 periods for diagnoses (all years and 2013-2015, ie, recent diagnoses). For rapidly growing clusters (with ≥5 diagnoses during 2015), molecular clock phylogenetic analysis estimated the time to most recent common ancestor for all divergence events within the cluster. Cluster transmission rates were estimated using these phylogenies.

RESULTS

A distance threshold of 1.5% identified 103 rapidly growing clusters using all diagnoses and 73 using recent diagnoses; at 0.5%, 15 clusters were identified using all diagnoses and 13 using recent diagnoses. Molecular clock analysis estimated that the 13 clusters identified at 0.5% using recent diagnoses had been diversifying for a median of 4.7 years, compared with 6.5-13.2 years using other approaches. The 13 clusters at 0.5% had a transmission rate of 33/100 person-years, compared with previous national estimates of 4/100 person-years.

CONCLUSIONS

Our approach identified clusters with transmission rates 8 times those of previous national estimates. This method can identify groups involved in rapid transmission and help programs effectively direct and prioritize limited public health resources.

Low prevalence of transmitted HIV-1 drug resistance detected by a dried blood spot (DBS)-based next-generation sequencing (NGS) method in newly diagnosed individuals in Cameroon in the years 2015-16

Objectives

To determine the most recent prevalence, transmission patterns and risk factors of transmitted drug-resistance mutations (TDRMs) in Cameroon, we initiated a multicentre study monitoring HIV-1 drug resistance in newly HIV-1-diagnosed individuals using a novel next-generation sequencing (NGS) assay applicable to fingerprick dried blood spot (DBS) samples.

Methods

Fingerprick DBS samples and questionnaires were collected from 360 newly HIV-1-diagnosed individuals in four hospitals in urban areas in Cameroon in the years 2015-16. We developed an HIV-1 protease and reverse transcriptase drug resistance genotyping assay applicable to DBS samples and HIV-1 genomes of groups M, N and O. The WHO 2009 list of mutations for surveillance of transmitted drug-resistant HIV strains was used to analyse TDRMs.

Results

Applying our 'DBS-NGS-genotypic resistance test', baseline HIV-1 drug resistance data were successfully obtained from 82.8% (298/360) of newly diagnosed individuals. At nucleotide frequencies >15%, TDRMs to NRTIs were observed in 3.0% (9/298), to NNRTIs in 4.0% (12/298) and to PIs in 1.3% (3/240). The NNRTI mutation K103N was most commonly detected (2.7%). Expanding the analysis to low-abundance TDRMs, i.e. 3%-15%, 12 additional individuals (4.0%) harbouring TDRMs were identified. Having unprotected sex with a known HIV-1-positive person was significantly associated with the transmission of DRMs (adjusted OR 9.6; 95% CI 1.79-51.3).

Conclusions

The prevalence of transmitted HIV-1 drug resistance is currently low in the study sites in Cameroon. Evidence of some risky sexual behaviours depicts a public health problem with possible implications for the prevention of new HIV-1 infections.

Recent and Rapid Transmission of HIV Among People Who Inject Drugs in Scotland Revealed Through Phylogenetic Analysis

Background

Harm reduction has dramatically reduced HIV incidence among people who inject drugs (PWID). In Glasgow, Scotland, <10 infections/year have been diagnosed among PWID since the mid-1990s. However, in 2015 a sharp rise in diagnoses was noted among PWID; many were subtype C with 2 identical drug-resistant mutations and some displayed low avidity, suggesting the infections were linked and recent.

Methods

We collected Scottish pol sequences and identified closely related sequences from public databases. Genetic linkage was ascertained among 228 Scottish, 1820 UK, and 524 global sequences. The outbreak cluster was extracted to estimate epidemic parameters.

Results

All 104 outbreak sequences originated from Scotland and contained E138A and V179E. Mean genetic distance was <1% and mean time between transmissions was 6.7 months. The average number of onward transmissions consistently exceeded 1, indicating that spread was ongoing.

Conclusions

In contrast to other recent HIV outbreaks among PWID, harm reduction services were not clearly reduced in Scotland. Nonetheless, the high proportion of individuals with a history of homelessness (45%) suggests that services were inadequate for those in precarious living situations. The high prevalence of hepatitis C (>90%) is indicative of sharing of injecting equipment. Monitoring the epidemic phylogenetically in real time may accelerate public health action.

Two-year cross-sectional studies reveal that single, young MSMs in Shenzhen, China are at high risk for HIV infection

BACKGROUND

Shenzhen City is a rapidly growing area with a large number of floating populations, thus making it difficult to control HIV. Serial cross-sectional studies are helpful for the prediction of epidemiological tendency. In this study, two parallel cross-sectional studies were compared to explore changes in HIV epidemiology in Shenzhen, China.

METHODS

Two hundred and fifty newly reported HIV-positive cases were randomly selected in Shenzhen City in 2013 and 2015. Socio-demographical information was collected with informed consent. Full-length gag and partial pol genes were amplified using nested RT-PCR followed by sequencing and phylogenetic analysis. The genotypes of anti-HIV drug resistance were also analyzed. The characteristics of the HIV epidemics of 2013 and 2015 were compared to identify patterns.

RESULTS

The proportion of single, young MSMs dramatically increased in 2015 compared to 2013. Many subtypes, including CRF07_BC (36.4%), CRF01_AE (34.1%), CRF55_01B (10.2%), B (6.4%), CRF08_BC (3.4%), CRF59_01B (0.9%), C (0.7%), D (0.2%), CRF68_01B (0.2%), CRF67_01B (0.2%), and unique recombinant forms (URFs, 7.3%), were identified. Close phylogenetic relationships between strains prevalent in Shenzhen and other areas of China was observed. No epidemic cluster confined to single, young MSMs was identified. 0.4 and 2.8% of the strains contained transmitted drug-resistant mutations in 2013 and 2015, respectively.

CONCLUSION

Although the interval period is short, changes in HIV epidemiology in Shenzhen City are distinct. Frequent surveillance of HIV epidemics in Shenzhen City is thus necessary. Single, young MSMs have become a high-risk population for HIV infection and should be considered as focus population for HIV prevention and behavior intervention in Shenzhen City.

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.

Solid Organ Transplantation in HIV-Infected Recipients: History, Progress, and Frontiers

PURPOSE OF REVIEW

End-stage organ disease prevalence is increasing among HIV-infected (HIV+) individuals. Trial and registry data confirm that solid organ transplantation (SOT) is efficacious in this population. Optimizing access to transplant and decreasing complications represent active frontiers.

RECENT FINDINGS

HIV+ recipients historically experienced 2-4-fold higher rejection. Integrase strand transferase inhibitors (INSTIs) minimize drug interactions and may reduce rejection along with lymphodepleting induction immunosuppression. Hepatitis C virus (HCV) coinfection has been associated with inferior outcomes, yet direct-acting antivirals (DAAs) may mitigate this. Experience in South Africa and the US HIV Organ Policy Equity (HOPE) Act support HIV+ donor to HIV+ recipient (HIV D+/R+) transplantation. SOT is the optimal treatment for end-stage organ disease in HIV+ individuals. Recent advances include use of INSTIs and DAAs in transplant recipients; however, strategies to improve access to transplant are needed. HIV D+/R+ transplantation is under investigation and may improve access and provide insights for HIV cure and pathogenesis research.

Ethical issues in HIV phylogenetics and molecular epidemiology

PURPOSE OF REVIEW

HIV phylogenetic and molecular epidemiology analyses are increasingly being performed with a goal of improving HIV prevention efforts. However, ethical, legal and social issues are associated with these analyses, and should be considered when performed.

RECENT FINDINGS

Several working groups have recently outlined the major issues surrounding the use of molecular epidemiology for HIV prevention. First, the benefits of HIV molecular epidemiology remain unclear, and further work is needed to quantitatively demonstrate the benefits that can be expected. Second, privacy loss is an important risk, with implications of disclosure varying by the regional legal and social climate. Inferential privacy risks will increase with technological improvements in sequencing and analysis. Third, data sharing, which enhances the utility of the data, may also increase the risk of inferential privacy loss. Mitigation strategies are available to address each of these issues.

SUMMARY

HIV molecular epidemiology for research and public health pose significant ethical issues that continue to evolve with improving technology, increased sampling and a changing legal and social climate. Guidance surrounding these issues needs to be developed for researchers and public health officials in an iterative and region specific manner that accounts for the potential benefits and risks of this technology.

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.

HIV transmission networks among transgender women in Los Angeles County, CA, USA: a phylogenetic analysis of surveillance data

BACKGROUND

Transgender women are among the groups at highest risk for HIV infection, with a prevalence of 27·7% in the USA; and despite this known high risk, undiagnosed infection is common in this population. We set out to identify transgender women and their partners in a molecular transmission network to prioritise public health activities.

METHODS

Since 2006, HIV protease and reverse transcriptase gene (pol) sequences from drug resistance testing have been reported to the Los Angeles County Department of Public Health and linked to demographic data, gender, and HIV transmission risk factor data for each case in the enhanced HIV/AIDS Reporting System. We reconstructed a molecular transmission network by use of HIV-TRAnsmission Cluster Engine (with a pairwise genetic distance threshold of 0·015 substitutions per site) from the earliest pol sequences from 22 398 unique individuals, including 412 (2%) self-identified transgender women. We examined the possible predictors of clustering with multivariate logistic regression. We characterised the genetically linked partners of transgender women and calculated assortativity (the tendency for people to link to other people with the same attributes) for each transmission risk group.

FINDINGS

8133 (36·3%) of 22 398 individuals clustered in the network across 1722 molecular transmission clusters. Transgender women who indicated a sexual risk factor clustered at the highest frequency in the network, with 147 (43%) of 345 being linked to at least one other person (adjusted odds ratio [aOR] 2·0, p=0·0002). Transgender women were assortative in the network (assortativity 0·06, p<0·001), indicating that they tended to link to other transgender women. Transgender women were more likely than expected to link to other transgender women (OR 4·65, p<0·001) and cisgender men who did not identify as men who have sex with men (MSM; OR 1·53, p<0·001). Transgender women were less likely than expected to link to MSM (OR 0·75, p<0·001), despite the high prevalence of HIV among MSM. Transgender women were distributed across 126 clusters, and cisgender individuals linked to one transgender woman were 9·2 times more likely to link to a second transgender woman than other individuals in the surveillance database. Reconstruction of the transmission network is limited by sample availability, but sequences were available for more than 40% of diagnoses.

INTERPRETATION

Clustering of transgender women and the observed tendency for linkage with cisgender men who did not identify as MSM, shows the potential to use molecular epidemiology both to identify clusters that are likely to include undiagnosed transgender women with HIV and to improve the targeting of public health prevention and treatment services to transgender women.

FUNDING

California HIV and AIDS Research Program and National Institutes of Health-National Institute of Allergy and Infectious Diseases.

Social Networks of Substance-Using Populations: Key Issues and Promising New Approaches for HIV

PURPOSE OF REVIEW

This paper presents recent literature on substance using networks and HIV, highlighting renewed and emerging themes in the field. The goal is to draw attention to research that holds considerable promise for advancing our understanding of the role of networks in shaping behaviors, while also providing critical information for the development of interventions, programs, and policies to reduce HIV and other drug-related harms.

RECENT FINDINGS

Recent research advances our understanding of networks and HIV, including among understudied populations, and provides new insight into how risk environments shape the networks and health of substance-using populations. In particular, the integration of network approaches with molecular epidemiology, research on space and place, and intervention methods provides exciting new avenues of investigation. Continued advances in network research are critical to supporting the health and rights of substance-using populations and ensuring the development of high-impact HIV programs and policies.

Completeness of HIV nucleotide sequence ascertainment and its potential impact on understanding HIV transmission - Maryland, 2011-2013

HIV nucleotide sequences generated through routine drug resistance testing (DRT) and reported to Maryland's Molecular HIV Surveillance system are most effective for elucidating transmission patterns and identifying outbreaks if DRT is ordered promptly and sequences are reported completely. Among reported cases of HIV infection newly diagnosed during 2011-2013 in Maryland residents aged ≥13 years, we assessed sequence ascertainment completeness. To better understand which populations were most likely to have a sequence, we examined associations between sequence ascertainment and clinical and demographic characteristics. During 2011-2013, 4423 new HIV infection diagnoses were reported; sequences were ascertained for 1282 (29.0%). Among 3267 cases with complete data, odds for having a sequence ascertained were highest for cases in persons living inside Maryland's Central Region with initial CD4 counts ≤500 cells/mm³ (adjusted odds ratio [aOR] 2.4, 95% confidence interval [CI] 1.9-3.1). Sequence ascertainment did not vary significantly by patient age, sex, race/ethnicity or HIV transmission category. Educational interventions, policy changes and improved processes to increase timely DRT and subsequent sequence reporting with a focus on testing at entry to care, particularly for those with higher CD4 counts and those living outside the Central Region, might improve ascertainment completeness.

Growth of HIV-1 Molecular Transmission Clusters in New York City

Background

HIV-1 genetic sequences can be used to infer viral transmission history and dynamics. Throughout the United States, HIV-1 sequences from drug resistance testing are reported to local public health departments.

Methods

We investigated whether inferred HIV transmission network dynamics can identify individuals and clusters of individuals most likely to give rise to future HIV cases in a surveillance setting. We used HIV-TRACE, a genetic distance-based clustering tool, to infer molecular transmission clusters from HIV-1 pro/RT sequences from 65736 people in the New York City surveillance registry. Logistic and LASSO regression analyses were used to identify correlates of clustering and cluster growth, respectively. We performed retrospective transmission network analyses to evaluate individual- and cluster-level prioritization schemes for identifying parts of the network most likely to give rise to new cases in the subsequent year.

Results

Individual-level prioritization schemes predicted network growth better than random targeting. Across the 3600 inferred molecular transmission clusters, previous growth dynamics were superior predictors of future transmission cluster growth compared to individual-level prediction schemes. Cluster-level prioritization schemes considering previous cluster growth relative to cluster size further improved network growth predictions.

Conclusions

Prevention efforts based on HIV molecular epidemiology may improve public health outcomes in a US surveillance setting.

Sexual, Social, and Genetic Network Overlap: A Socio-Molecular Approach Toward Public Health Intervention of HIV

OBJECTIVES

To determine how network-level factors influence individual risk of HIV acquisition, which is key in preventing disease transmission.

METHODS

We recruited a cohort of young Black men who have sex with men (n = 618) in Chicago, Illinois, from 2013 to 2016. We identified potential molecular ties via pairwise genetic distance analysis of HIV pol sequences with links inferred between individuals whose sequences were 1.5% or less genetically distant. We defined clusters as 1 or more connections to another individual. We conducted entity resolution between confidant, sexual, referral, and Facebook network data between network types.

RESULTS

Of 266 (43.0%) participants identified as HIV-positive, we obtained 86 (32.3%) genetic sequences. Of these, 35 (40.7%) were linked to 1 or more other sequence; however, none of these were identified in first-, second-, or third-degree confidant and sexual networks. Minimal overlap existed between genetic and Facebook ties.

CONCLUSIONS

These results suggest that HIV transmissions may have occurred before elicitation of network data; future studies should expand the data collection timeframe to more accurately determine risk networks. Virtual network data, such as Facebook, may be particularly useful in developing one's risk environment.

Network Viral Load: A Critical Metric for HIV Elimination

BACKGROUND

Associations have been observed between an aggregate viral load measure, the community viral load, and new HIV diagnoses. The community viral load aggregates viral loads within chosen geographic areas, restricting inferences about HIV acquisition risk to these areas. We develop a more precise metric, the network viral load (NVL), to measure the composite viral load within a risk network of a HIV-negative individual.

METHODS

We examined the relationship between NVL and HIV infection among young men who have sex with men in Chicago, United States. Networks were generated using respondent-driven sampling. NVL was defined as the prevalence of viremic individuals in one's risk network, characterized as those with a viral load ≥20 k copies per milliliter. Permutation tests were conducted to account for dependency.

RESULTS

After controlling for total connections, age, substance use during sex, syphilis diagnosis (previous 12 months), and frequency of condomless anal sex (previous 6 months), we found a positive association between NVL and HIV infection. Compared with a network with all HIV-seronegative members, the odds of HIV infection with an NVL of <10% viremia were 1.85 (95% confidence interval: 1.18 to 2.92) times higher and those with an NVL of ≥10% viremia were 2.73 (95% confidence interval: 1.54 to 4.85) times higher.

CONCLUSIONS

We found a positive association between NVL and HIV seroprevalence. Although limited in its ability to infer causality, NVL could have substantial public health implications for persons most at risk for HIV infection, given that this novel metric avoids overreliance on individual level behavior or broad community indices.

Short Communication: Phylogenetic Evidence of HIV-1 Transmission Between Adult and Adolescent Men Who Have Sex with Men

HIV-1 incidence among youth, especially men who have sex with men (MSM), is increasing in the United States. We aimed to better understand the patterns of adolescent HIV-1 acquisition, to help guide future prevention interventions. We conducted a study combining epidemiologic and HIV-1 pol sequence data from a retrospective cohort of HIV-infected adults and adolescents in Seattle, WA between 2000 and 2013. Adolescents were defined as 13-24 years of age at the time of first HIV-1 care. Maximum-likelihood phylogenetic trees were reconstructed to identify putative viral transmission clusters of two or more individuals, followed by multivariable regression tests of associations between clustering and demographic and clinical parameters. The dataset included 3,102 sequences from 1,953 individuals; 72 putative transmission clusters were identified, representing 168 individuals (8.6%). MSM and MSM/intravenous drug use (IDU) were positively associated with clustering, with aOR 3.18 (95% CI: 1.34-7.55) and 2.59 (95% CI: 1.04-6.49), respectively. African American race was negatively associated with clustering (aOR 0.54 95% CI: 0.32-0.91). Twenty-five clusters contained one adolescent and five clusters contained two adolescents. Other individuals who clustered with adolescents were predominantly male (95%), white (85%), and either MSM (66%) or MSM/IDU (16%), with a greater mean age (34 years vs. 22 years; p < .01). In this Seattle cohort, HIV-1 transmission linkages were identified between white male adolescents and older MSM adults. Interventions aimed at age-discrepant pairs may reduce HIV-1 infections in adolescent males.

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional dataset (n = 1,022) containing 91 epidemiologically linked heterosexual couples. We calculated the optimal genetic distance threshold to separate linked versus unlinked NGS datasets using a receiver operating curve analysis. We evaluated the number, size, and composition of clusters detected by Cluster Picker and HIV-TRACE at six genetic distance thresholds (1%-5.3%) on all three datasets. We further tested the effect of using all NGS, versus only a single variant for each patient/time point, for datasets (1) and (2). The optimal gp41 genetic distance threshold to distinguish linked and unlinked couples and individuals was 5.3% and 4%, respectively. HIV-TRACE tended to detect larger and fewer clusters, whereas Cluster Picker detected more clusters containing only two sequences. For NGS datasets (1) and (2), HIV-TRACE and Cluster Picker detected all linked pairs at 3% and 4% genetic distances, respectively. However, at 5.3% genetic distance, 20% of couples in dataset (3) did not cluster using either program, and for >1/3 of couples cluster assignment were discordant. We suggest caution in choosing thresholds for clustering analyses in a generalized epidemic.

Expanding HIV-1 subtype B transmission networks among men who have sex with men in Poland

INTRODUCTION

Reconstruction of HIV transmission links allows to trace the spread and dynamics of infection and guide epidemiological interventions. The aim of this study was to characterize transmission networks among subtype B infected patients from Poland.

MATERIAL AND METHODS

Maximum likelihood phylogenenetic trees were inferred from 966 HIV-1 subtype B protease/reverse transcriptase sequences from patients followed up in nine Polish HIV centers. Monophyletic clusters were identified using 3% within-cluster distance and 0.9 bootstrap values. Interregional links for the clusters were investigated and time from infection to onward transmission estimated using Bayesian dated MCMC phylogeny.

RESULTS

Three hundred twenty one (33.2%) sequences formed 109 clusters, including ten clusters of ≥5 sequences (n = 81, 8.4%). Transmission networks were more common among MSM (234 sequences, 68.6%) compared to other infection routes (injection drug use: 28 (8.2%) and heterosexual transmissions: 59 (17.3%) cases, respectively [OR:3.5 (95%CI:2.6-4.6),p<0.001]. Frequency of clustering increased from 26.92% in 2009 to 50.6% in 2014 [OR:1.18 (95%CI:1.06-1.31),p = 0.0026; slope +2.8%/year] with median time to onward transmission within clusters of 1.38 (IQR:0.59-2.52) years. In multivariate models clustering was associated with both MSM transmission route [OR:2.24 (95%CI:1.38-3.65),p<0.001] and asymptomatic stage of HIV infection [OR:1.93 (95%CI:1.4-2.64),p<0.0001]. Additionally, interregional networks were linked to MSM transmissions [OR:4.7 (95%CI:2.55-8.96),p<0.001].

CONCLUSIONS

Reconstruction of the HIV-1 subtype B transmission patterns reveals increasing degree of clustering and existence of interregional networks among Polish MSM. Dated phylogeny confirms the association between onward transmission and recent infections. High transmission dynamics among Polish MSM emphasizes the necessity for active testing and early treatment in this group.

Spatiotemporal dynamics of HIV-1 transmission in France (1999-2014) and impact of targeted prevention strategies

Background

Characterizing HIV-1 transmission networks can be important in understanding the evolutionary patterns and geospatial spread of the epidemic. We reconstructed the broad molecular epidemiology of HIV from individuals with primary HIV-1 infection (PHI) enrolled in France in the ANRS PRIMO C06 cohort over 15 years.

Results

Sociodemographic, geographic, clinical, biological and pol sequence data from 1356 patients were collected between 1999 and 2014. Network analysis was performed to infer genetic relationships, i.e. clusters of transmission, between HIV-1 sequences. Bayesian coalescent-based methods were used to examine the temporal and spatial dynamics of identified clusters from different regions in France. We also evaluated the use of network information to target prevention efforts. Participants were mostly Caucasian (85.9%) and men (86.7%) who reported sex with men (MSM, 71.4%). Overall, 387 individuals (28.5%) were involved in clusters: 156 patients (11.5%) in 78 dyads and 231 participants (17%) in 42 larger clusters (median size: 4, range 3–41). Compared to individuals with single PHI (n = 969), those in clusters were more frequently men (95.9 vs 83%, p < 0.01), MSM (85.8 vs 65.6%, p < 0.01) and infected with CRF02_AG (20.4 vs 13.4%, p < 0.01). Reconstruction of viral migrations across time suggests that Paris area was the major hub of dissemination of both subtype B and CRF02_AG epidemics. By targeting clustering individuals belonging to the identified active transmission network before 2010, 60 of the 143 onward transmissions could have been prevented.

Conclusion

These analyses support the hypothesis of a recent and rapid rise of CRF02_AG within the French HIV-1 epidemic among MSM. Combined with a short turnaround time for sample processing, targeting prevention efforts based on phylogenetic monitoring may be an efficient way to deliver prevention interventions but would require near real time targeted interventions on the identified index cases and their partners.

Electronic supplementary material

The online version of this article (doi:10.1186/s12977-017-0339-4) contains supplementary material, which is available to authorized users.

Partner services in adults with acute and early HIV infection

BACKGROUND

To examine the yield of HIV partner services provided to persons newly diagnosed with acute and early HIV infection (AEH) in San Diego, United States.

DESIGN

Observational cohort study.

METHODS

The study investigated the yield (i.e. number of new HIV and AEH diagnoses, genetically linked partnerships and high-risk uninfected partners) of partner services (confidential contact tracing) for individuals with AEH enrolled in the San Diego Primary Infection Resource Consortium 1996-2014.

RESULTS

A total of 107 of 574 persons with AEH (19%; i.e. index cases) provided sufficient information to recruit 119 sex partners. Fifty-seven percent of the 119 recruited partners were HIV infected, and 33% of the 119 were newly HIV diagnosed. Among those newly HIV diagnosed, 36% were diagnosed during AEH. There were no significant demographic or behavioral risk differences between HIV-infected and HIV-uninfected recruited partners. Genetic sequences were available for both index cases and partners in 62 partnerships, of which 61% were genetically linked. Partnerships in which both index case and partner enrolled within 30 days were more likely to yield a new HIV diagnosis (P = 0.01) and to be genetically linked (P < 0.01).

CONCLUSION

Partner services for persons with AEH within 30 days of diagnosis represents an effective tool to find HIV-unaware persons, including those with AEH who are at greatest risk of HIV transmission.

Social and Genetic Networks of HIV-1 Transmission in New York City

Background

Sexually transmitted infections spread across contact networks. Partner elicitation and notification are commonly used public health tools to identify, notify, and offer testing to persons linked in these contact networks. For HIV-1, a rapidly evolving pathogen with low per-contact transmission rates, viral genetic sequences are an additional source of data that can be used to infer or refine transmission networks.

Methods and Findings

The New York City Department of Health and Mental Hygiene interviews individuals newly diagnosed with HIV and elicits names of sexual and injection drug using partners. By law, the Department of Health also receives HIV sequences when these individuals enter healthcare and their physicians order resistance testing. Our study used both HIV sequence and partner naming data from 1342 HIV-infected persons in New York City between 2006 and 2012 to infer and compare sexual/drug-use named partner and genetic transmission networks. Using these networks, we determined a range of genetic distance thresholds suitable for identifying potential transmission partners. In 48% of cases, named partners were infected with genetically closely related viruses, compatible with but not necessarily representing or implying, direct transmission. Partner pairs linked through the genetic similarity of their HIV sequences were also linked by naming in 53% of cases. Persons who reported high-risk heterosexual contact were more likely to name at least one partner with a genetically similar virus than those reporting their risk as injection drug use or men who have sex with men.

Conclusions

We analyzed an unprecedentedly large and detailed partner tracing and HIV sequence dataset and determined an empirically justified range of genetic distance thresholds for identifying potential transmission partners. We conclude that genetic linkage provides more reliable evidence for identifying potential transmission partners than partner naming, highlighting the importance and complementarity of both epidemiological and molecular genetic surveillance for characterizing regional HIV-1 epidemics.

Understanding the path over which viruses such as HIV have been transmitted may be crucial for directing public health resources and guiding policy decisions. Contact tracing of named sexual and injection drug-use partners of people recently diagnosed with HIV is an indispensible tool for reconstructing this transmission network. Viral genetic sequence data—routinely collected by public health agencies—can also be used to infer the dynamics of HIV transmission. We analyzed partner naming and viral genetic sequence data in 1342 people living with HIV in New York City reported to the New York City Department of Health and Mental Hygiene between 2006 and 2012. Genetically linked partners were more likely to be named partners than named partners were to be genetically linked. This finding indicates that genetic sequence data are better than partner naming data for reconstructing this viral transmission network. Importantly, the success rate in naming a genetically linked partner varied by transmission risk category (e.g., men who have sex with men, heterosexuals, and injection drug users). This study validates the use viral genetic sequences in reconstructing these viral transmission networks in a public health surveillance setting.