The impact of clinical, demographic and risk factors on rates of HIV transmission: a population-based phylogenetic analysis in British Columbia, Canada

Improvement in the 95-95-95 Targets Is Accompanied by a Reduction in Both the Human Immunodeficiency Virus Transmission Rate and Incidence in China

BACKGROUND

In 2016, China has implemented the World Health Organization's "treat all" policy. We aimed to assess the impact of significant improvements in the 95-95-95 targets on population-level human immunodeficiency virus (HIV) transmission dynamics and incidence.

METHODS

We focused on 3 steps of the HIV care continuum: diagnosed, on antiretroviral therapy, and achieving viral suppression. The molecular transmission clusters were inferred using HIV-TRACE. New HIV infections were estimated using the incidence method in the European Centre for Disease Prevention and Control HIV Modelling Tool.

RESULTS

Between 2004 and 2023, the national HIV epidemiology database recorded 2.99 billion person-times of HIV tests and identified 1 976 878 new diagnoses. We noted a roughly "inverted-V" curve in the clustering frequency, with the peak recorded in 2014 (67.1% [95% confidence interval, 63.7%-70.5%]), concurrent with a significant improvement in the 95-95-95 targets from 10-13-<71 in 2005 to 84-93-97 in 2022. Furthermore, we observed a parabolic curve for a new infection with the vertex occurring in 2010.

CONCLUSIONS

In general, it was suggested that the improvements in the 95-95-95 targets were accompanied by a reduction in both the population-level HIV transmission rate and incidence. Thus, China should allocate more effort to the first "95" target to achieve a balanced 95-95-95 target.

Prioritization of ethical concerns regarding HIV molecular epidemiology by public health practitioners and researchers

BACKGROUND

HIV molecular epidemiology (HIV ME) can support the early detection of emerging clusters of new HIV infections by combining HIV sequence data routinely obtained during the clinical treatment of people living with HIV with behavioral, geographic, and sociodemographic information. While information about emerging clusters promises to facilitate HIV prevention and treatment efforts, the use of this data also raises several ethical concerns. We sought to assess how those working on the frontlines of HIV ME, specifically public health practitioners (PHPs) and researchers, prioritized these issues.

METHODS

Ethical issues were identified through literature review, qualitative in-depth interviews, and stakeholder engagement. PHPs and researchers using HIV ME prioritized the issues using best-worst scaling (BWS). A balanced incomplete block design was used to generate 11 choice tasks each consisting of a sub-set of 5 ethical concerns. In each task, respondents were asked to assess the most and least concerning issue. Data were analyzed using conditional logit, with a Swait-Louviere test of poolability. Latent class analysis was then used to explore preference heterogeneity.

RESULTS

In total, 57 respondents completed the BWS experiment May-June 2023 with the Swait-Louviere test indicating that researchers and PHPs could be pooled (p = 0.512). Latent class analysis identified two classes, those highlighting "Harms" (n = 29) (prioritizing concerns about potential risk of legal prosecution, individual harm, and group stigma) and those highlighting "Utility" (n = 28) (prioritizing concerns about limited evidence, resource allocation, non-disclosure of data use for HIV ME, and the potential to infer the directionality of HIV transmission). There were no differences in the characteristics of members across classes.

CONCLUSIONS

The ethical issues of HIV ME vary in importance among stakeholders, reflecting different perspectives on the potential impact and usefulness of the data. Knowing these differences exist can directly inform the focus of future deliberations about the policies and practices of HIV ME in the United States.

Origin and evolution of subtype B variants in the former Soviet Union countries

Contrary to the global trend, between 2010 and 2020, an increase of 43% new HIV infections was recorded in Eastern Europe and Central Asia. Analyses of phylogenetic relationship, and routes and modes of transmission of the HIV-1 subtype B across the former Soviet Union (FSU) region are currently lacking. The objective of this analysis was to investigate the origin and transmission routes of HIV subtype B in FSU countries. We performed phylogenetic and phylodynamic analyses using 21,007 publicly available subtype B sequences from Europe and Asia, including thirteen FSU countries. Our study suggests that B_FSU strain evolved more recently in FSU countries (Russia, Kyrgyzstan, Uzbekistan, Tajikistan, Belarus, Ukraine, Lithuania, Latvia, Georgia, Armenia, Azerbaijan) compared to the Western B variant in Western Europe (Austria, Belgium, Germany, Luxembourg, Netherlands, Switzerland). The primary high-risk group responsible for the transmission of subtype B was found to be MSM/homosexual. Intermixing of phylogenetic clusters among high-risk groups and bridging with the general population indicated that the HIV epidemic is no longer confined to distinct key populations - emphasizing an urgent need to improve the HIV harm-reduction efforts among high risk as well as general populations.

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.

Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities

The rapid implementation of molecular HIV surveillance (MHS) has resulted in significant challenges for local health departments to develop real-time cluster detection and response (CDR) interventions for priority populations impacted by HIV. This study is among the first to explore professionals' strategies to implement MHS and develop CDR interventions in real-world public health settings. Methods: Semi-structured qualitative interviews were completed by 21 public health stakeholders in the United States' southern and midwestern regions throughout 2020-2022 to identify themes related to the implementation and development of MHS and CDR. Results for the thematic analysis revealed (1) strengths and limitations in utilizing HIV surveillance data for real-time CDR; (2) limitations of MHS data due to medical provider and staff concerns related to CDR; (3) divergent perspectives on the effectiveness of partner services; (4) optimism, but reluctance about the social network strategy; and (5) enhanced partnerships with community stakeholders to address MHS-related concerns. Conclusions: Enhancing MHS and CDR efforts requires a centralized system for staff to access public health data from multiple databases to develop CDR interventions; designating staff dedicated to CDR interventions; and establishing equitable meaningful partnerships with local community stakeholders to address MHS concerns and develop culturally informed CDR interventions.

Community Insights in Phylogenetic HIV Research: The CIPHR Project Protocol

Inferring HIV transmission networks from HIV sequences is gaining popularity in the field of HIV molecular epidemiology. However, HIV sequences are often analyzed at distance from those affected by HIV epidemics, namely without the involvement of communities most affected by HIV. These remote analyses often mean that knowledge is generated in absence of lived experiences and socio-economic realities that could inform the ethical application of network-derived information in 'real world' programmes. Procedures to engage communities are noticeably absent from the HIV molecular epidemiology literature. Here we present our team's protocol for engaging community activists living in Nairobi, Kenya in a knowledge exchange process - The CIPHR Project (Community Insights in Phylogenetic HIV Research). Drawing upon a community-based participatory approach, our team will (1) explore the possibilities and limitations of HIV molecular epidemiology for key population programmes, (2) pilot a community-based HIV molecular study, and (3) co-develop policy guidelines on conducting ethically safe HIV molecular epidemiology. Critical dialogue with activist communities will offer insight into the potential uses and abuses of using such information to sharpen HIV prevention programmes. The outcome of this process holds importance to the development of policy frameworks that will guide the next generation of the global response.

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.

Insights into HIV-1 Transmission Dynamics Using Routinely Collected Data in the Mid-Atlantic United States

Background: Molecular epidemiological approaches provide opportunities to characterize HIV transmission dynamics. We analyzed HIV sequences and virus load (VL) results obtained during routine clinical care, and individual’s zip-code location to determine utility of this approach. Methods: HIV-1 pol sequences aligned using ClustalW were subtyped using REGA. A maximum likelihood (ML) tree was generated using IQTree. Transmission clusters with ≤3% genetic distance (GD) and ≥90% bootstrap support were identified using ClusterPicker. We conducted Bayesian analysis using BEAST to confirm transmission clusters. The proportion of nucleotides with ambiguity ≤0.5% was considered indicative of early infection. Descriptive statistics were applied to characterize clusters and group comparisons were performed using chi-square or t-test. Results: Among 2775 adults with data from 2014−2015, 2589 (93%) had subtype B HIV-1, mean age was 44 years (SD 12.7), 66.4% were male, and 25% had nucleotide ambiguity ≤0.5. There were 456 individuals in 193 clusters: 149 dyads, 32 triads, and 12 groups with ≥ four individuals per cluster. More commonly in clusters were males than females, 349 (76.5%) vs. 107 (23.5%), p < 0.0001; younger individuals, 35.3 years (SD 12.1) vs. 44.7 (SD 12.3), p < 0.0001; and those with early HIV-1 infection by nucleotide ambiguity, 202/456 (44.3%) vs. 442/2133 (20.7%), p < 0.0001. Members of 43/193 (22.3%) of clusters included individuals in different jurisdictions. Clusters ≥ four individuals were similarly found using BEAST. HIV-1 viral load (VL) ≥3.0 log10 c/mL was most common among individuals in clusters ≥ four, 18/21, (85.7%) compared to 137/208 (65.8%) in clusters sized 2−3, and 927/1169 (79.3%) who were not in a cluster (p < 0.0001). Discussion: HIV sequence data obtained for HIV clinical management provide insights into regional transmission dynamics. Our findings demonstrate the additional utility of HIV-1 VL data in combination with phylogenetic inferences as an enhanced contact tracing tool to direct HIV treatment and prevention services. Trans-jurisdictional approaches are needed to optimize efforts to end the HIV epidemic.

Characterization of HIV-1 Transmission Clusters Inferred from the Brazilian Nationwide Genotyping Service Database

The study of HIV-1 transmission networks inferred from viral genetic data can be used to clarify important factors about the dynamics of HIV-1 transmission, such as network growth rate and demographic composition. In Brazil, HIV transmission has been stable since the early 2000s and the study of transmission clusters can provide valuable data to understand the drivers of virus spread. In this work, we analyzed a nation-wide database of approximately 53,000 HIV-1 nucleotide pol sequences sampled from genotyped patients from 2008-2017. Phylogenetic trees were reconstructed for the HIV-1 subtypes B, C and F1 in Brazil and transmission clusters were inferred by applying genetic distances thresholds of 1.5%, 3.0% and 4.5%, as well as high (>0.9) cluster statistical support. An odds ratio test revealed that young men (15-24 years) and individuals with more years of education presented higher odds to cluster. The assortativity coefficient revealed that individuals with similar demographic features tended to cluster together, with emphasis on features, such as place of residence and age. We also observed that assortativity weakens as the genetic distance threshold increases. Our results indicate that the phylogenetic clusters identified here are likely representative of the contact networks that shape HIV transmission, and this is a valuable tool even in sites with low sampling density, such as Brazil.

Optimized phylogenetic clustering of HIV-1 sequence data for public health applications

Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14, 221 sequences) from four sites in USA (Tennessee, Washington), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.

Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012-2016

We aimed to elucidate the characteristics of HIV molecular epidemiology and identify transmission hubs in eastern China using genetic transmission network and lineage analyses. HIV-TRACE was used to infer putative relationships. Across the range of epidemiologically-plausible genetic distance (GD) thresholds (0.1-2.0%), a sensitivity analysis was performed to determine the optimal threshold, generating the maximum number of transmission clusters and providing reliable resolution without merging different small clusters into a single large cluster. Characteristics of genetically linked individuals were analyzed using logistic regression. Assortativity (shared characteristics) analysis was performed to infer shared attributes between putative partners. 1,993 persons living with HIV-1 were enrolled. The determined GD thresholds within subtypes CRF07_BC, CRF01_AE, and B were 0.5%, 1.2%, and 1.7%, respectively, and 826 of 1,993 (41.4%) sequences were linked with at least one other sequence, forming 188 transmission clusters of 2-80 sequences. Clustering rates for the main subtypes CRF01_AE, CRF07_BC, and B were 50.9% (523/1027), 34.2% (256/749), and 32.1% (25/78), respectively. Median cluster sizes of these subtypes were 2 (2-52, n = 523), 2 (2-80, n = 256), and 3 (2-6, n = 25), respectively. Subtypes in individuals diagnosed and residing in Hangzhou city (OR = 1.423, 95% CI: 1.168-1.734) and men who have sex with men (MSM) were more likely to cluster. Assortativity analysis revealed individuals were more likely to be genetically linked to individuals from the same age group (AIage = 0.090, P<0.001) and the same area of residency in Zhejiang (AIcity = 0.078, P<0.001). Additionally, students living with HIV were more likely to be linked with students than show a random distribution (AI student = 0.740, P<0.01). These results highlight the importance of Hangzhou City in the regional epidemic and show that MSM comprise the population rapidly transmitting HIV in Zhejiang Province. We also provide a molecular epidemiology framework for improving our understanding of HIV transmission dynamics in eastern China.

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.

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.

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.

Concordance of HIV transmission risk factors elucidated using viral diversification rate and phylogenetic clustering

BACKGROUND AND OBJECTIVES

Although HIV sequence clustering is routinely used to identify subpopulations experiencing elevated transmission, it over-simplifies transmission dynamics and is sensitive to methodology. Complementarily, viral diversification rates can be used to approximate historical transmission rates. Here, we investigated the concordance and sensitivity of HIV transmission risk factors identified by phylogenetic clustering, viral diversification rate, changes in viral diversification rate and a combined approach.

METHODOLOGY

Viral sequences from 9848 people living with HIV in British Columbia, Canada, sampled between 1996 and February 2019, were used to infer phylogenetic trees, from which clusters were identified and viral diversification rates of each tip were calculated. Factors associated with heightened transmission risk were compared across models of cluster membership, viral diversification rate, changes in diversification rate, and viral diversification rate among clusters.

RESULTS

Viruses within larger clusters had higher diversification rates and lower changes in diversification rate than those within smaller clusters; however, rates within individual clusters, independent of size, varied widely. Risk factors for both cluster membership and elevated viral diversification rate included being male, young, a resident of health authority E, previous injection drug use, previous hepatitis C virus infection or a high recent viral load. In a sensitivity analysis, models based on cluster membership had wider confidence intervals and lower concordance of significant effects than viral diversification rate for lower sampling rates.

CONCLUSIONS AND IMPLICATIONS

Viral diversification rate complements phylogenetic clustering, offering a means of evaluating transmission dynamics to guide provision of treatment and prevention services.

LAY SUMMARY

Understanding HIV transmission dynamics within clusters can help prioritize public health resource allocation. We compared socio-demographic and clinical risk factors associated with phylogenetic cluster membership and viral diversification rate, a historical branching rate, in order to assess their relative concordance and sampling sensitivity.

Integrating Phylogenetic Biomarker Data and Qualitative Approaches: An example of HIV Transmission Clusters as a Sampling Frame for Semistructured Interviews and Implications for the COVID-19 Era

Mixed methods studies of human disease that combine surveillance, biomarker, and qualitative data can help elucidate what drives epidemiological trends. Viral genetic data are rarely coupled with other types of data due to legal and ethical concerns about patient privacy. We developed a novel approach to integrate phylogenetic and qualitative methods in order to better target HIV prevention efforts. The overall aim of our mixed methods study was to characterize HIV transmission clusters. We combined surveillance data with HIV genomic data to identify cases whose viruses share enough similarities to suggest a recent common source of infection or participation in linked transmission chains. Cases were recruited through a multi-phase process to obtain consent for recruitment to semi-structured interviews. Through linkage of viral genetic sequences with epidemiological data, we identified individuals in large transmission clusters, which then served as a sampling frame for the interviews. In this article, we describe the multi-phase process and the limitations and challenges encountered. Our approach contributes to the mixed methods research field by demonstrating that phylogenetic analysis and surveillance data can be harnessed to generate a sampling frame for subsequent qualitative data collection, using an explanatory sequential design. The process we developed also respected protections of patient confidentiality. The novel method we devised may offer an opportunity to implement a sampling frame that allows for the recruitment and interview of individuals in high-transmission clusters to better understand what contributes to spread of other infectious diseases, including COVID-19.

Combining traditional and molecular epidemiology methods to quantify local HIV transmission among foreign-born residents

OBJECTIVES

We evaluated the ability for molecular epidemiology to augment traditional HIV surveillance beyond the detection of clusters for outbreak investigation. To do this, we address a question of interest to Public Health - Seattle and King County: what proportion of HIV diagnoses among people born outside of the United States are acquired locally?

DESIGN

King County residents diagnosed with HIV, 2010-2018.

METHODS

We linked HIV-1 pol gene sequences to demographic information obtained from the National HIV Surveillance System, Public Health - Seattle and King County case investigation and partner services interviews. We determined the likely location of HIV acquisition based on HIV testing, travel histories and cluster-based molecular analyses.

RESULTS

Among 2409 people diagnosed with HIV, 798 (33%) were born outside of the United States. We inferred the location of acquisition for 77% of people born outside of the United States: 26% likely acquired HIV locally in King County (of whom 69% were MSM, 16% heterosexual), and 51% likely acquired HIV outside of King County (primarily outside of the United States). Of this 77% of people for whom we inferred the location of HIV acquisition, 45% were determined using traditional epidemiology methods and an additional 32% were inferred using molecular epidemiology methods.

CONCLUSION

We found that the National HIV Surveillance System misclassified the majority of HIV-infected foreign-born residents as 'new' local infections, and that these cases contribute to an overestimate of local incidence. Our findings highlight how molecular epidemiology can augment traditional HIV surveillance activities and provide useful information to local health jurisdictions beyond molecular cluster detection.

HIV transmission network analysis allows identifying unreported risk factors in HIV-positive blood donors in France

OBJECTIVES

As sex between men is a major route of human immunodeficiency virus (HIV) infection in most western countries, restrictive deferral rules for blood donation have largely been implemented regarding men having sex with men (MSM). Here, we sought here to assign unreported HIV risk factors in blood donors (BDs) and reevaluated the MSM-associated fraction of HIV transfusion residual risk (%RR_MSM ).

METHODS

We applied a genetic distance-based approach to infer an HIV transmission network for 384 HIV sequences from French BDs and 1337 HIV sequences from individuals with known risk factors (ANRS PRIMO primary HIV infection cohort). We validated the possibility of assigning a risk factor according to clustering using assortative mixing. Finally, we recalculated the %RR_MSM .

RESULTS

A total of 81 of 284 (28.5%) male and 5 of 100 (5%) female BDs belonged to a cluster; 72 (88.9%) of the 81 male BDs belonged to MSM clusters. After cluster correction, 8 of 67 (11.9%), 4 of 21 (19.0%), and 19 of 88 (21.6%) HIV-positive (HIV+) male BDs with heterosexual, other, or unknown risk factors could be reclassified as MSM, accounting for 10.9% of the total HIV+ male BDs. Overall, 139 of 284 HIV+ male donors (48.9%) could be considered MSM between 2000 and 2016 in France. Between 2005 and 2016, the %RR_MSM increase varied from 0 to 19%, without differing significantly from the %RR_MSM before reclassification.

CONCLUSION

Network inference can be used to complement declaration data on risk factors for HIV infection in BDs. This approach, complementary to behavioral studies, is a valuable tool to evaluate the effect of changes in deferral criteria on BD compliance.

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.

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.

Empirical comparison of analytical approaches for identifying molecular HIV-1 clusters

Public health interventions guided by clustering of HIV-1 molecular sequences may be impacted by choices of analytical approaches. We identified commonly-used clustering analytical approaches, applied them to 1886 HIV-1 Rhode Island sequences from 2004-2018, and compared concordance in identifying molecular HIV-1 clusters within and between approaches. We used strict (topological support ≥ 0.95; distance 0.015 substitutions/site) and relaxed (topological support 0.80-0.95; distance 0.030-0.045 substitutions/site) thresholds to reflect different epidemiological scenarios. We found that clustering differed by method and threshold and depended more on distance than topological support thresholds. Clustering concordance analyses demonstrated some differences across analytical approaches, with RAxML having the highest (91%) mean summary percent concordance when strict thresholds were applied, and three (RAxML-, FastTree regular bootstrap- and IQ-Tree regular bootstrap-based) analytical approaches having the highest (86%) mean summary percent concordance when relaxed thresholds were applied. We conclude that different analytical approaches can yield diverse HIV-1 clustering outcomes and may need to be differentially used in diverse public health scenarios. Recognizing the variability and limitations of commonly-used methods in cluster identification is important for guiding clustering-triggered interventions to disrupt new transmissions and end the HIV epidemic.

Inferring transmission heterogeneity using virus genealogies: Estimation and targeted prevention

Spread of HIV typically involves uneven transmission patterns where some individuals spread to a large number of individuals while others to only a few or none. Such transmission heterogeneity can impact how fast and how much an epidemic spreads. Further, more efficient interventions may be achieved by taking such transmission heterogeneity into account. To address these issues, we developed two phylogenetic methods based on virus sequence data: 1) to generally detect if significant transmission heterogeneity is present, and 2) to pinpoint where in a phylogeny high-level spread is occurring. We derive inference procedures to estimate model parameters, including the amount of transmission heterogeneity, in a sampled epidemic. We show that it is possible to detect transmission heterogeneity under a wide range of simulated situations, including incomplete sampling, varying levels of heterogeneity, and including within-host genetic diversity. When evaluating real HIV-1 data from different epidemic scenarios, we found a lower level of transmission heterogeneity in slowly spreading situations and a higher level of heterogeneity in data that included a rapid outbreak, while R0 and Sackin's index (overall tree shape statistic) were similar in the two scenarios, suggesting that our new method is able to detect transmission heterogeneity in real data. We then show by simulations that targeted prevention, where we pinpoint high-level spread using a coalescence measurement, is efficient when sequence data are collected in an ongoing surveillance system. Such phylogeny-guided prevention is efficient under both single-step contact tracing as well as iterative contact tracing as compared to random intervention.

Phylogenetic clustering networks among heterosexual migrants with new HIV diagnoses post-migration in Australia

Background

It is estimated that approximately half of new HIV diagnoses among heterosexual migrants in Victoria, Australia, were acquired post-migration. We investigated the characteristics of phylogenetic clusters in notified cases of HIV among heterosexual migrants.

Methods

Partial HIV pol sequences obtained from routine clinical genotype tests were linked to Victorian HIV notifications with the following exposures listed on the notification form: heterosexual sexual contact, injecting drug use, bisexual sexual contact, male-to male sexual contact or heterosexual sexual contact in combination with injecting drug use, unknown exposure. Those with heterosexual sexual contact as the only exposure were the focus of this study, with the other exposures included to better understand transmission networks. Additional reference sequences were extracted from the Los Alamos database. Maximum likelihood methods were used to infer the phylogeny and the robustness of the resulting tree was assessed using bootstrap analysis. Phylogenetic clusters were defined on the basis of bootstrap and genetic distance.

Results

HIV pol sequences were available for 332 of 445 HIV notifications attributed to only heterosexual sexual contact in Victoria from 2005–2014. Forty-three phylogenetic clusters containing at least one heterosexual migrant were detected, 30 (70%) of which were pairs. The characteristics of these phylogenetic clusters varied considerably by cluster size. Pairs were more likely to be composed of people living with HIV from a single country of birth (p = 0.032). Larger clusters (n≥3) were more likely to contain people born in Australian/New Zealand (p = 0.002), migrants from more than one country of birth (p = 0.013) and viral subtype-B, the most common subtype in Australia (p = 0.006). Pairs were significantly more likely to contain females (p = 0.037) and less likely to include HIV diagnoses with male-to-male sexual contact reported as a possible exposure (p<0.001) compared to larger clusters (n≥3).

Conclusion

Migrants appear to be at elevated risk of HIV acquisition, in part due to intimate relationships between migrants from the same country of origin, and in part due to risks associated with the broader Australian HIV epidemic. However, there was no evidence of large transmission clusters driven by heterosexual transmission between migrants. A multipronged approach to prevention of HIV among migrants is warranted.

HIV-1 phylodynamic analysis among people who inject drugs in Pakistan correlates with trends in illicit opioid trade

Pakistan is considered by the World Health Organization to currently have a "concentrated" HIV-1 epidemic due to a rapid rise in infections among people who inject drugs (PWID). Prevalence among the country's nearly 105,000 PWID is estimated to be 37.8% but has been shown to be higher in several large urban centers. A lack of public health resources, the common use of professional injectors and unsafe injection practices are believed to have fueled the outbreak. Here we evaluate the molecular characteristics of HIV-1 sequences (n = 290) from PWID in several Pakistani cities to examine transmission dynamics and the association between rates of HIV-1 transmission with regards to regional trends in opioid trafficking. Tip-to-tip (patristic) distance based phylogenetic cluster inferences and BEAST2 Bayesian phylodynamic analyses of time-stamped data were performed on HIV-1 pol sequences generated from dried blood spots collected from 1,453 PWID as part of a cross-sectional survey conducted in Pakistan during 2014/2015. Overall, subtype A1 strains were dominant (75.2%) followed by CRF02_AG (14.1%), recombinants/unassigned (7.2%), CRF35_AD (2.1%), G (1.0%) and C (0.3%). Nearly three quarters of the PWID HIV-1 sequences belonged to one of five distinct phylogenetic clusters. Just below half (44.4%) of individuals in the largest cluster (n = 118) did seek help injecting from professional injectors which was previously identified as a strong correlate of HIV-1 infection. Spikes in estimated HIV-1 effective population sizes coincided with increases in opium poppy cultivation in Afghanistan, Pakistan's western neighbor. Structured coalescent analysis was undertaken in order to investigate the spatial relationship of HIV-1 transmission among the various cities under study. In general terms, our analysis placed the city of Larkana at the center of the PWID HIV-1 epidemic in Pakistan which is consistent with previous epidemiological data.

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.

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.

Quality Control of Next-Generation Sequencing-Based HIV-1 Drug Resistance Data in Clinical Laboratory Information Systems Framework

Next-generation sequencing (NGS) in HIV drug resistance (HIVDR) testing has the potential to improve both clinical and public health settings, however it challenges the normal operations of quality management systems to be more flexible due to its complexity, massive data generation, and rapidly evolving protocols. While guidelines for quality management in NGS data have previously been outlined, little guidance has been implemented for NGS-based HIVDR testing. This document summarizes quality control procedures for NGS-based HIVDR testing laboratories using a laboratory information systems (LIS) framework. Here, we focus in particular on the quality control measures applied on the final sequencing product aligned with the recommendations from the World Health Organization HIV Drug Resistance Laboratory Network.

Evaluation of A Phylogenetic Pipeline to Examine Transmission Networks in A Canadian HIV Cohort

Keywords: HIV; Canada; molecular phylogenetics; viral evolution; person-to-person transmission inference; transmission network; summary statistics.

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.

Natural selection favoring more transmissible HIV detected in United States molecular transmission network

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.

Detection of HIV transmission hotspots in British Columbia, Canada: A novel framework for the prioritization and allocation of treatment and prevention resources

Background

Identifying populations at high risk of HIV transmission is critical for prioritizing treatment and prevention resources and achieving the UNAIDS 90-90-90 Targets.

Methods

HIV transmission rates can be estimated from phylogenetic trees as viral lineage-level diversification rates. To identify HIV-1 transmission foci in British Columbia, Canada, we inferred diversification rates from phylogenetic trees of 36 271 HIV-1 sequences from 9630 anonymized individuals. Diversification rates were combined with sociodemographic and clinical data, then aggregated by patients’ area of residence to predict the distribution of new HIV cases between 2008 and 2018. The predictive power of the model was compared with a phylogenetically uninformed model.

Findings

Aggregated diversification rate measures were predictive of new HIV cases in the subsequent year after adjusting for prevalent and incident cases in the previous year. For every one-unit increase in the mean of the top five diversification rates, the number of new HIV cases increased by on average 1·38-fold (95% CI, 1·28–1·49). In a blind prediction of 2018 cases, diversification rate improved the model's specificity by 12%, accuracy by 9%, top 20 agreement by 100%, and correlation of predicted and observed values by 162% relative to a model that incorporated epidemiological data alone.

Interpretation

By predicting the distribution of future HIV cases, a combined phylogenetic and epidemiological approach identifies hotspots where public health resources are needed most.

Funding

Canadian Institutes of Health Research, University of British Columbia, Public Health Agency of Canada, Genome Canada, Genome BC, Michael Smith Foundation for Health Research, and BC Centre for Excellence in HIV/AIDS.

HIV-1 subtype diversity, drug resistance, and genetic transmission networks in men who have sex with men with virologic failure in antiretroviral therapy in Sichuan, China, 2011 to 2017

This study sought to examine the human immunodeficiency virus type 1 (HIV-1) genetic diversity on drug resistance among men who have sex with men (MSM) with virologic failure in antiretroviral therapy (ART), and investigate linking-associated factors for genetic transmission networks.Seven hundred and thirty-four HIV-positive MSM with virologic failure in ART were recruited into our study from 2011 to 2017. HIV-1 pol gene sequences were used for phylogenetic and genotypic drug resistance analyses. The drug resistance mutations were determined using the Stanford University HIV Drug Resistance Database. The genetic transmission networks were analyzed for CRF01_AE and CRF07_BC sequences by the genetic distance-based method.Of 734 subjects, 372 (50.68%) showed drug resistance, in which CRF01_AE and CRF07_BC were the predominating subtypes. Drug resistance more frequently occurred in non-nucleoside reverse transcriptase inhibitors (NNRTIs) treatment (48.64%), and followed by nucleoside reverse transcriptase inhibitors (NRTIs) (36.51%) and PIs (4.03%). The most common drug resistance-associated mutations in protease inhibitors (PIs), NRTIs and NNRTIs were K20I/R, M184V/I and K103N/KN, respectively. For 283CRF01_AE sequences, 64 (22.61%) fell into clusters at a genetic distance of 0.011, resulting in 17 clusters ranging in size from 2 to 16 individuals. For 230 CRF07_BC sequences, 66 (28.69%) were connected to at least one other sequence with 0.005 genetic distances, resulting in 8 clusters ranging in size from 2 to 52 individuals. Individuals who showed drug resistance to ART were less likely to fall into clusters than those who did not. The genetic linkage was robust by the exclusion of sites associated with drug resistance.CRF01_AE and CRF07_BC were the main strains among MSM with virologic failure in ART, and the drug resistance more frequently occurred in NNRTIs, followed by NRTIs and PIs. Genetic transmission networks revealed a complexity of transmission pattern, suggesting early-diagnosis and in-time intervention among MSM.

Transmission Dynamics of HIV Subtype A in Tel Aviv, Israel: Implications for HIV Spread and Eradication

OBJECTIVE

Subtype-A HIV was introduced into Israel in the mid-1990s, predominantly by immigrants from the former Soviet Union (FSU) infected via intravenous drug use (IVDU). HIV subsequently spread beyond the FSU-IVDU community. In 2012, a mini-HIV outbreak, associated with injection of amphetamine cathinone derivatives, started in Tel Aviv, prompting public health response. To assess current trends and the impact of the outbreak and control measures, we conducted a phyloepidemiologic analysis.

METHOD

Demographic and clinical records and HIV sequences were compiled from 312 subtype-A HIV-infected individuals attending the Tel-Aviv Sourasky Medical Center between 2005-2016, where >40% of all subtype-A HIV-infected individuals in Israel are undergoing care. Molecular evolutionary genetics analysis (MEGA) and ayesian evolutionary analysis sampling trees (BEAST) programs were implemented in a phylogenetic analysis of pol sequences. Reconstructed phylogenies were assessed in the context of demographic information and drug-resistance profiles. Clusters were identified as sequence populations with posterior probability ≥0.95 of having a recent common ancestor.

RESULTS

After 2010, the subtype-A epidemic acquired substantial phylogenetic structure, having been unrecognized in studies covering the earlier period. Nearly 50% of all sequences were present in 11 distinct clusters consisting of 4-43 individuals. Cluster composition reflected transmission across ethnic groups, with men who have sex with men (MSM) playing an increasing role. The cathinone-associated cluster was larger than previously documented, containing variants that continued to spread within and beyond the IVDU community.

CONCLUSIONS

Phyloepidemiologic analysis revealed diverse clusters of HIV infection with MSM having a central role in transmission across ethic groups. A mini outbreak was reduced by public health measures, but molecular evidence of ongoing transmission suggests additional measures are necessary.

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.

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-1 molecular transmission clusters in nine European countries and Canada: association with demographic and clinical factors

BACKGROUND

Knowledge of HIV-1 molecular transmission clusters (MTCs) is important, especially in large-scale datasets, for designing prevention programmes and public health intervention strategies. We used a large-scale HIV-1 sequence dataset from nine European HIV cohorts and one Canadian, to identify MTCs and investigate factors associated with the probability of belonging to MTCs.

METHODS

To identify MTCs, we applied maximum likelihood inferences on partial pol sequences from 8955 HIV-positive individuals linked to demographic and clinical data. MTCs were defined using two different criteria: clusters with bootstrap support >75% (phylogenetic confidence criterion) and clusters consisting of sequences from a specific region at a proportion of >75% (geographic criterion) compared to the total number of sequences within the network. Multivariable logistic regression analysis was used to assess factors associated with MTC clustering.

RESULTS

Although 3700 (41%) sequences belonged to MTCs, proportions differed substantially by country and subtype, ranging from 7% among UK subtype C sequences to 63% among German subtype B sequences. The probability of belonging to an MTC was independently less likely for women than men (OR = 0.66; P < 0.001), older individuals (OR = 0.79 per 10-year increase in age; P < 0.001) and people of non-white ethnicity (OR = 0.44; P < 0.001 and OR = 0.70; P = 0.002 for black and 'other' versus white, respectively). It was also more likely among men who have sex with men (MSM) than other risk groups (OR = 0.62; P < 0.001 and OR = 0.69; P = 0.002 for people who inject drugs, and sex between men and women, respectively), subtype B (ORs 0.36-0.70 for A, C, CRF01 and CRF02 versus B; all P < 0.05), having a well-estimated date of seroconversion (OR = 1.44; P < 0.001), a later calendar year of sampling (ORs 2.01-2.61 for all post-2002 periods versus pre-2002; all P < 0.01), and being naïve to antiretroviral therapy at sampling (OR = 1.19; P = 0.010).

CONCLUSIONS

A high proportion (>40%) of individuals belonged to MTCs. Notably, the HIV epidemic dispersal appears to be driven by subtype B viruses spread within MSM networks. Expansion of regional epidemics seems mainly associated with recent MTCs, rather than the growth of older, established ones. This information is important for designing prevention and public health intervention strategies.

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.

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.

Extensive host immune adaptation in a concentrated North American HIV epidemic

Supplemental Digital Content is available in the text

Objective:

HIV incidence in the Canadian province of Saskatchewan, where Indigenous persons make up 80% of those infected, are among the highest on the continent. Reports of accelerated HIV progression, associated with carriage of certain human leukocyte antigen (HLA) alleles (including the typically protective HLA-B∗51) have also emerged from the region. Given that acquisition of HIV preadapted to host HLA negatively impacts clinical outcome, we hypothesized that HIV-host adaptation may be elevated in Saskatchewan.

Design:

Comparative analysis of population-level HIV sequence datasets from Saskatchewan and elsewhere in Canada/USA.

Methods:

We analyzed 1144 HIV subtype B Pol sequences collected in Saskatchewan between 2000 and 2016, comprising ∼65% of cumulative provincial HIV cases, for the presence of 70 HLA-associated Pol mutations. Sequences from British Columbia (N = 6525) and elsewhere in Canada/USA (N = 6517) were used for comparison. HIV adaptation levels to 34 HLA alleles were also computed. Putative HIV transmission clusters were identified, and the prevalence of HLA-associated adaptations within and outside these clusters was investigated.

Results:

Analyses confirmed significantly elevated and temporally increasing levels of HIV adaptation to commonly expressed HLA alleles, in particular B∗51. Notably, HLA-adapted HIV strains were significantly enriched among phylogenetic clusters in Saskatchewan.

Conclusion:

Extensive circulating HIV adaptation to HLA in Saskatchewan provides a plausible explanation for accelerated progression, while enrichment of adapted variants in phylogenetic clusters suggests they are being widely transmitted. Results highlight the utility of Pol sequences, routinely collected for drug resistance monitoring, for surveillance of HIV-host adaptation, and underscore the urgent need to expand HIV prevention and treatment programmes in Saskatchewan.

Molecular Analysis of Human Immunodeficiency Virus Type 1 (HIV-1)-Infected Individuals in a Network-Based Intervention (Transmission Reduction Intervention Project): Phylogenetics Identify HIV-1-Infected Individuals With Social Links

Background

The Transmission Reduction Intervention Project (TRIP) is a network-based intervention that aims at decreasing human immunodeficiency virus type 1 (HIV-1) spread. We herein explore associations between transmission links as estimated by phylogenetic analyses, and social network-based ties among persons who inject drugs (PWID) recruited in TRIP.

Methods

Phylogenetic trees were inferred from HIV-1 sequences of TRIP participants. Highly supported phylogenetic clusters (transmission clusters) were those fulfilling 3 different phylogenetic confidence criteria. Social network-based ties (injecting or sexual partners, same venue engagement) were determined based on personal interviews, recruitment links, and field observation.

Results

TRIP recruited 356 individuals (90.2% PWID) including HIV-negative controls; recently HIV-infected seeds; long-term HIV-infected seeds; and their social network members. Of the 150 HIV-infected participants, 118 (78.7%) were phylogenetically analyzed. Phylogenetic analyses suggested the existence of 13 transmission clusters with 32 sequences. Seven of these clusters included 14 individuals (14/32 [43.8%]) who also had social ties with at least 1 member of their cluster. This proportion was significantly higher than what was expected by chance.

Conclusions

Molecular methods can identify HIV-infected people socially linked with another person in about half of the phylogenetic clusters. This could help public health efforts to locate individuals in networks with high transmission rates.

HIV-1 infection among crack cocaine users in a region far from the epicenter of the HIV epidemic in Brazil: Prevalence and molecular characteristics

Brazil has the largest cocaine market in South America, and crack cocaine use is closely associated with HIV-1 infection. This study investigated the prevalence, risk factors, and HIV-1 subtypes, including recombinant forms and mutations associated with drug resistance, among crack cocaine users in Central-West Brazil. We recruited 600 crack cocaine users admitted to a referral hospital in Goiânia for psychiatric disorders. The participants were interviewed; blood samples were collected for anti-HIV-1/2 serological screening. HIV-1 pol gene sequences (entire protease [PR] and partial reverse transcriptase [RT]) were obtained from plasma RNA. HIV-1 subtypes, recombinant viruses, transmitted drug resistance (TDR), and secondary drug resistance mutations were investigated. The median participant age was 30 years (range, 18-68 years); most were male, single, unemployed, and of mixed races. Among them, 2.8% (17/600) were HIV-1 positive: 2.2% of men (11/507) and 6.5% of women (6/93). The main predictors of HIV-1 seropositivity were a sexual partner with HIV infection, irregular condom use, and previous homelessness. HIV-1 pol sequences (12/17) indicated the predominance of subtype B (n = 7), followed by recombinant forms FPR/BRT (n = 1) and BPR/FRT (n = 2) and subtypes F1 (n = 1) and C (n = 1). TDR prevalence was 58.3% (7/12). Isolates from two participants showed mutations associated with resistance to nucleoside reverse transcriptase inhibitors (NRTI) only (M41L, T125C, T125F, M184V), while an isolate from one patient who had received antiretroviral therapy (ART) since 2008 had a mutation associated with resistance to non-NRTI (G190S). Five isolates had secondary mutations to protease inhibitors (K20M, L10V, L33I, A71T, A71V). In conclusion, the findings of HIV-1 circulation, TDR to NRTI, and secondary mutations to protease inhibitors in ART-naïve crack cocaine users support the importance of monitoring this population in regions far from the epicenter of the HIV epidemic.

Quantifying the fitness cost of HIV-1 drug resistance mutations through phylodynamics

Drug resistant HIV is a major threat to the long-term efficacy of antiretroviral treatment. Around 10% of ART-naïve patients in Europe are infected with drug-resistant HIV type 1. Hence it is important to understand the dynamics of transmitted drug resistance evolution. Thanks to routinely performed drug resistance tests, HIV sequence data is increasingly available and can be used to reconstruct the phylogenetic relationship among viral lineages. In this study we employ a phylodynamic approach to quantify the fitness costs of major resistance mutations in the Swiss HIV cohort. The viral phylogeny reflects the transmission tree, which we model using stochastic birth–death-sampling processes with two types: hosts infected by a sensitive or resistant strain. This allows quantification of fitness cost as the ratio between transmission rates of hosts infected by drug resistant strains and transmission rates of hosts infected by drug sensitive strains. The resistance mutations 41L, 67N, 70R, 184V, 210W, 215D, 215S and 219Q (nRTI-related) and 103N, 108I, 138A, 181C, 190A (NNRTI-related) in the reverse trancriptase and the 90M mutation in the protease gene are included in this study. Among the considered resistance mutations, only the 90M mutation in the protease gene was found to have significantly higher fitness than the drug sensitive strains. The following mutations associated with resistance to reverse transcriptase inhibitors were found to be less fit than the sensitive strains: 67N, 70R, 184V, 219Q. The highest posterior density intervals of the transmission ratios for the remaining resistance mutations included in this study all included 1, suggesting that these mutations do not have a significant effect on viral transmissibility within the Swiss HIV cohort. These patterns are consistent with alternative measures of the fitness cost of resistance mutations. Overall, we have developed and validated a novel phylodynamic approach to estimate the transmission fitness cost of drug resistance mutations.

The introduction of antiretroviral therapy (ART) has decreased mortality and morbidity rates among HIV-infected people, and improved their quality of life. In fact, the WHO states that antiretroviral therapy programmes averted an estimated 7.8 million deaths worldwide between 2000 and 2014. However, the antiretroviral regimen prescribed to a patient may be unable to control HIV infection. Factors that can contribute to treatment failure include drug resistance, drug toxicity, or poor treatment adherence. In this study we aim to understand the dynamics of transmitted drug resistance by analysing the viral sequence data that was collected for resistance testing. We present a novel approach to quantify how drug resistance impacts virus lineage transmissibility, how fast resistance mutations evolve in sensitive strains and how fast they revert back to the sensitive type. We apply our approach to the Swiss HIV cohort study, and obtain patterns of viral transmission fitness that are consistent with alternative, harder to obtain measures of fitness.

Detailed Transmission Network Analysis of a Large Opiate-Driven Outbreak of HIV Infection in the United States

In January 2015, an outbreak of undiagnosed human immunodeficiency virus (HIV) infections among persons who inject drugs (PWID) was recognized in rural Indiana. By September 2016, 205 persons in this community of approximately 4400 had received a diagnosis of HIV infection. We report results of new approaches to analyzing epidemiologic and laboratory data to understand transmission during this outbreak. HIV genetic distances were calculated using the polymerase region. Networks were generated using data about reported high-risk contacts, viral genetic similarity, and their most parsimonious combinations. Sample collection dates and recency assay results were used to infer dates of infection. Epidemiologic and laboratory data each generated large and dense networks. Integration of these data revealed subgroups with epidemiologic and genetic commonalities, one of which appeared to contain the earliest infections. Predicted infection dates suggest that transmission began in 2011, underwent explosive growth in mid-2014, and slowed after the declaration of a public health emergency. Results from this phylodynamic analysis suggest that the majority of infections had likely already occurred when the investigation began and that early transmission may have been associated with sexual activity and injection drug use. Early and sustained efforts are needed to detect infections and prevent or interrupt rapid transmission within networks of uninfected PWID.