Genetic Cluster Analysis for HIV Prevention

Determinants of HIV-1 transmission clusters and transmitted drug resistance in men who have sex with men: A multicenter study in Portugal (2014-2019)

INTRODUCTION

In the EU/EEA, men who have sex with men (MSM) is a priority group for the prevention and control of HIV-1 infection. In Portugal, the 2023 HIV incidence rate was 8.2 per 100,000 inhabitants, with 876 new infections, 41.7% in MSM. We aim to characterize HIV-1 transmission clusters (TC) and transmitted drug resistance (TDR) and its sociodemographic, behavioral, clinical, and viral genomic determinants in MSM newly diagnosed in Portugal between 2014 and 2019.

METHODS

A total of 340 MSM newly diagnosed with HIV-1 infection at 17 hospitals in Portugal were included. TC was identified with branch support ≥90% and 1.5% genetic distance. Logistic regression models were used to examine factors associated with TC and TDR.

RESULTS

We identified 38 TC with 104 MSM, which includes 81 (26.6%) of the 305 MSM from our sample included in cluster analysis. The overall prevalence of TDR was 8.2%. Only HIV-1 subtype C was significantly associated with TDR. Overall, 10.5% of the clusters had at least 1 surveillance drug resistance mutation. There was no significant difference in the prevalence of TDR or the proportion of Portuguese and migrant MSM inside and outside clusters. Age at diagnosis, district of residence, unprotected sex with a woman, HIV testing, presenter status, and HIV-1 subtype were significantly associated with TC.

CONCLUSION

Specific subgroups of MSM are contributing to HIV-1 clustered transmission in Portugal. However, no association was found between TDR and sociodemographic or behavioral factors. Directed prevention measures should focus on those subgroups.

Analysis of HIV transmission characteristics and intervention effects in Guangxi based on molecular networks

OBJECTIVE

This study evaluates changes in HIV transmission and the effectiveness of interventions after two rounds of the Guangxi AIDS Conquering Project (GACP) in Guangxi, China.

METHODS

Samples and epidemiological data from newly diagnosed people with HIV (PWH) between 2014 and 2020 were analyzed. Molecular networks were constructed using nested PCR amplification and sequencing of the pol region, and multivariable logistic regression identified factors associated with clustering and high-degree nodes.

RESULTS

A total of 4227 valid sequences (73.12% inclusion rate) were analyzed. Demographic changes included an increasing proportion of individuals aged at least 50 years (49.66%), with lower education (50.51%), peasants (76.82%), and heterosexual transmission (90.29%). The overall clustering rate was 86.89%, with higher clustering among individuals aged at least 50 years (92.57%), those with primary school or below (89.09%), peasants (88.11%), and CRF08_BC infections (91.48%). Annual declines in cluster growth rate and clustering rates were observed, particularly among individuals aged less than 30 years, college graduates, MSM, and people who inject drugs (PWID). Key transmission hotspots were identified in Lingshan, particularly among older, less-educated individuals, and peasants. Factors associated with clustering included being male (aOR: 1.27), aged at least 50 years (aOR: 3.84), and infected with CRF08_BC (aOR: 2.12). From 2017 to 2020, the risk of clustering and high-degree nodes was lower compared to 2014-2016, suggesting the effectiveness of interventions.

CONCLUSION

Interventions in Guangxi effectively reduced HIV transmission among younger, high-degree populations. However, older, less-educated individuals remain at high risk, necessitating targeted strategies to address their specific needs and achieve better HIV control.

Bayesian mixture models for phylogenetic source attribution from consensus sequences and time since infection estimates

In stopping the spread of infectious diseases, pathogen genomic data can be used to reconstruct transmission events and characterize population-level sources of infection. Most approaches for identifying transmission pairs do not account for the time passing since the divergence of pathogen variants in individuals, which is problematic in viruses with high within-host evolutionary rates. This prompted us to consider possible transmission pairs in terms of phylogenetic data and additional estimates of time since infection derived from clinical biomarkers. We develop Bayesian mixture models with an evolutionary clock as a signal component and additional mixed effects or covariate random functions describing the mixing weights to classify potential pairs into likely and unlikely transmission pairs. We demonstrate that although sources cannot be identified at the individual level with certainty, even with the additional data on time elapsed, inferences into the population-level sources of transmission are possible, and more accurate than using only phylogenetic data without time since infection estimates. We apply the proposed approach to estimate age-specific sources of HIV infection in Amsterdam tranamission networks among men who have sex with men between 2010 and 2021. This study demonstrates that infection time estimates provide informative data to characterize transmission sources, and shows how phylogenetic source attribution can then be done with multi-dimensional mixture models.

Challenges in Elucidating HIV-1 Genetic Diversity in the Middle East and North Africa: A Review Based on a Systematic Search

The extensive genetic diversity of HIV-1 represents a major challenge to public health interventions, treatment, and successful vaccine design. This challenge is particularly pronounced in the Middle East and North Africa (MENA) region, where limited data among other barriers preclude the accurate characterization of HIV-1 genetic diversity. The objective of this review was to analyze studies conducted in the MENA region to delineate possible barriers that would hinder the accurate depiction of HIV-1 genetic diversity in this region. A systematic search of PubMed/MEDLINE and Google Scholar was conducted for published records on HIV-1 genetic diversity in the English language up until 1 October 2024 across 18 MENA countries. The pre-defined themes of challenges/barriers included limited sampling, data gaps, resource and infrastructure constraints, HIV-1-specific factors, and socio-cultural barriers. A total of 38 records were included in the final review, comprising original articles (55.3%), reviews (21.1%), and sequence notes (10.5%). Libya (15.8%), Morocco (13.2%), Saudi Arabia, and MENA as a whole (10.5% for each) were the primary sources of the included records. Of the 23 records with original MENA HIV-1 sequences, the median number of sequences was 46 (range: 6-193). The identified barriers included the following: (1) low sampling density; (2) limited clinical data (21.7% with no data, 60.9% partial data, and 17.4% with full data); (3) reliance solely on population sequencing and insufficient use of advanced sequencing technologies; (4) lack of comprehensive recombination analysis; and (5) socio-cultural barriers, including stigma with subsequent under-reporting among at-risk groups. The barriers identified in this review can hinder the ability to map the genetic diversity of HIV-1 in the MENA. Poor characterization of HIV-1's genetic diversity in the MENA would hinder efforts to optimize prevention strategies, monitor drug resistance, and develop MENA-specific treatment protocols. To overcome these challenges, investment in public health/research infrastructure, policy reforms to reduce stigma, and strengthened regional collaboration are recommended.

Assessment of genetic structure and trait associations of Watkins wheat landraces under Egyptian field conditions

Background

Wheat landraces represent a reservoir of genetic diversity that can support wheat improvement through breeding. A core panel of 300 Watkins wheat landraces, as well as 16 non-Watkins landraces and elite wheat cultivars, was grown during the 2020-2021 and 2021-2022 seasons at four Agricultural Research Stations in Egypt, Gemmiza, Nubaria, Sakha, and Sids, to evaluate the core panel for agromorphological and yield-related traits. The genetic population structure within these genotypes were assessed using 35,143 single nucleotide polymorphisms (SNPs).

Results

Cluster analyses using Discriminant Analysis of Principal Components (DAPC) and k-means revealed three clusters with moderate genetic differentiation and population structure, possibly due to wheat breeding systems and geographical isolation. The best ancestry was k = 4, but k = 2 and k = 3 were also significant. A genome-wide association study (GWAS) identified clustered marker trait associations (MTAs) linked to thousand kernel weight on chromosome 5A, plant height on chromosomes 3B and 1D, days to heading on chromosomes 2A, 4B, 5B and 1D, and plant maturity on chromosomes 3A, 2B, and 6B. In the future, these MTAs can be used to accelerate the incorporation of beneficial alleles into locally adapted germplasm through marker-assisted selection. Gene enrichment analysis identified key genes within these loci, including Reduced height-1 (Rht-A1) and stress-related genes.

Conclusion

These findings underscore significant genetic connections and the involvement of crucial biological pathways.

AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained heterosexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

The Role of Late Presenters in HIV-1 Transmission Clusters in Europe

BACKGROUND

Investigating the role of late presenters (LPs) in HIV-1 transmission is important, as they can contribute to the onward spread of HIV-1 virus before diagnosis, when they are not aware of their HIV status.

OBJECTIVE

To characterize individuals living with HIV-1 followed up in Europe infected with subtypes A, B, and G and to compare transmission clusters (TC) in LP vs. non-late presenter (NLP) populations.

METHODS

Information from a convenience sample of 2679 individuals living with HIV-1 was collected from the EuResist Integrated Database between 2008 and 2019. Maximum likelihood (ML) phylogenies were constructed using FastTree. Transmission clusters were identified using Cluster Picker. Statistical analyses were performed using R.

RESULTS

2437 (91.0%) sequences were from subtype B, 168 (6.3%) from subtype A, and 74 (2.8%) from subtype G. The median age was 39 y/o (IQR: 31.0-47.0) and 85.2% of individuals were males. The main transmission route was via homosexual (MSM) contact (60.1%) and 85.0% originated from Western Europe. In total, 54.7% of individuals were classified as LPs and 41.7% of individuals were inside TCs. In subtype A, individuals in TCs were more frequently males and natives with a recent infection. For subtype B, individuals in TCs were more frequently individuals with MSM transmission route and with a recent infection. For subtype G, individuals in TCs were those with a recent infection. When analyzing cluster size, we found that LPs more frequently belonged to small clusters (<8 individuals), particularly dual clusters (2 individuals).

CONCLUSION

LP individuals are more present either outside or in small clusters, indicating a limited role of late presentation to HIV-1 transmission.

The utility of SARS-CoV-2 genomic data for informative clustering under different epidemiological scenarios and sampling

OBJECTIVES

Clustering pathogen sequence data is a common practice in epidemiology to gain insights into the genetic diversity and evolutionary relationships among pathogens. We can find groups of cases with a shared transmission history and common origin, as well as identifying transmission hotspots. Motivated by the experience of clustering SARS-CoV-2 cases using whole genome sequence data during the COVID-19 pandemic to aid with public health investigation, we investigated how differences in epidemiology and sampling can influence the composition of clusters that are identified.

METHODS

We performed genomic clustering on simulated SARS-CoV-2 outbreaks produced with different transmission rates and levels of genomic diversity, along with varying the proportion of cases sampled.

RESULTS

In single outbreaks with a low transmission rate, decreasing the sampling fraction resulted in multiple, separate clusters being identified where intermediate cases in transmission chains are missed. Outbreaks simulated with a high transmission rate were more robust to changes in the sampling fraction and largely resulted in a single cluster that included all sampled outbreak cases. When considering multiple outbreaks in a sampled jurisdiction seeded by different introductions, low genomic diversity between introduced cases caused outbreaks to be merged into large clusters. If the transmission and sampling fraction, and diversity between introductions was low, a combination of the spurious break-up of outbreaks and the linking of closely related cases in different outbreaks resulted in clusters that may appear informative, but these did not reflect the true underlying population structure. Conversely, genomic clusters matched the true population structure when there was relatively high diversity between introductions and a high transmission rate.

CONCLUSION

Differences in epidemiology and sampling can impact our ability to identify genomic clusters that describe the underlying population structure. These findings can help to guide recommendations for the use of pathogen clustering in public health investigations.

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 Prisoners in Central Brazil and Evidence of Transmission Clusters

Higher rates of human immunodeficiency virus (HIV) infection have been detected in prisoners when compared with the general population, but research into HIV molecular epidemiology and its transmission network has been lacking among them. Thus, this study aimed to verify potential HIV molecular transmission networks among prisoners. In addition, we aimed to describe the mutations related to antiretroviral resistance in these isolates. Thus, we conducted a cross-sectional survey from 2013 to 2018 in prisons in Central-Western Brazil, and the final sampling composed of 84 prisoners. Proviral DNA was extracted from each whole blood sample followed by amplification of the partial polymerase gene and sequencing. Forty-nine sequences (58.3%) were classified as subtype B, followed by C (14.3%), D, and F1 (2.4% each). A complex and dynamic HIV-1 epidemic is observed in the prisons, as 25% of the sequences were recombinant forms. We detected 15 HIV transmission clusters composed of at least two sequences, that included not only prisoners but also individuals from the general population from the same State with a variety of risk behaviors. Thirty-two percent (32.0%) of treatment-experienced prisoners had at least one drug resistance mutation (DRM), while transmitted DRMs were found in 5.9% of the prisoners. We highlight the urgent need for routine surveillance of HIV-1 infection including resistance genotypic tests considering the high disease burden, risky behaviors inside prisons, and the dynamic relationship of prisoners with the outside community.

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

INTRODUCTION

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

METHODS AND ANALYSIS

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

ETHICS AND DISSEMINATION

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

Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial - BCPP/ Ya Tsie trial

Background: Mathematical models predict that community-wide access to HIV testing-and-treatment can rapidly and substantially reduce new HIV infections. Yet several large universal test-and-treat HIV prevention trials in high-prevalence epidemics demonstrated variable reduction in population-level incidence.

Methods: To elucidate patterns of HIV spread in universal test-and-treat trials we quantified the contribution of geographic-location, gender, age and randomized-HIV-intervention to HIV transmissions in the 30-community Ya Tsie trial in Botswana. We sequenced HIV viral whole genomes from 5,114 trial participants among the 30 trial communities.

Results: Deep-sequence phylogenetic analysis revealed that most inferred HIV transmissions within the trial occurred within the same or between neighboring communities, and between similarly-aged partners. Transmissions into intervention communities from control communities were more common than the reverse post-baseline (30% [12.2 - 56.7] versus 3% [0.1 - 27.3]) than at baseline (7% [1.5 - 25.3] versus 5% [0.9 - 22.9]) compatible with a benefit from treatment-as-prevention.

Conclusion: Our findings suggest that population mobility patterns are fundamental to HIV transmission dynamics and to the impact of HIV control strategies.

Funding: This study was supported by the National Institute of General Medical Sciences (U54GM088558); the Fogarty International Center (FIC) of the U.S. National Institutes of Health (D43 TW009610); and the President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention (CDC) (Cooperative agreements U01 GH000447 and U2G GH001911).

HIV transmission patterns among transgender women, their cisgender male partners, and cisgender MSM in Lima, Peru: A molecular epidemiologic and phylodynamic analysis

BACKGROUND

Transgender women (TW) in Peru are disproportionately affected by HIV. The role that cisgender men who have sex with TW (MSTW) and their sexual networks play in TW's risk of acquiring HIV is not well understood. We used HIV sequences from TW, MSTW, and cisgender men who have sex with men (MSM) to examine transmission dynamics between these groups.

METHODS

We used HIV-1 pol sequences and epidemiologic data collected through three Lima-based studies from 2013 to 2018 (n = 139 TW, n = 25 MSTW, n = 303 MSM). We identified molecular clusters based on pairwise genetic distance and used structured coalescent phylodynamic modeling to estimate transmission patterns between groups.

FINDINGS

Among 200 participants (43%) found in 62 clusters, the probability of clustering did not differ by group. Both MSM and TW were more likely to cluster with members of their own group than would be expected based on random mixing. Phylodynamic modeling estimated that there was frequent transmission from MSTW to TW (67·9% of transmission from MSTW; 95%CI = 52·8-83·2%) and from TW to MSTW (76·5% of transmissions from TW; 95%CI = 65·5-90·3%). HIV transmission between MSM and TW was estimated to comprise a small proportion of overall transmissions (4·9% of transmissions from MSM, and 11·8% of transmissions from TW), as were transmissions between MSM and MSTW (7·2% of transmissions from MSM, and 32·0% of transmissions from MSTW).

INTERPRETATION

These results provide quantitative evidence that MSTW play an important role in TW's HIV vulnerability and that MSTW have an HIV transmission network that is largely distinct from MSM.

Characterization of HIV-1 Epidemic in Kyrgyzstan

Kyrgyzstan has one of the highest rates of HIV-1 spread in Central Asia. In this study, we used molecular–epidemiological approaches to examine the HIV-1 epidemic in Kyrgyzstan. Samples were obtained from HIV-positive individuals who visited HIV/AIDS clinics. Partial pol gene sequences were used to identify HIV-1 subtypes and drug resistance mutations (DRMs) and to perform phylogenetic analysis. Genetic diversity and history reconstruction of the major HIV-1 subtypes were explored using BEAST. This study includes an analysis of 555 HIV-positive individuals. The study population was equally represented by men and women aged 1–72 years. Heterosexual transmission was the most frequent, followed by nosocomial infection. Men were more likely to acquire HIV-1 during injection drug use and while getting clinical services, while women were more likely to be infected through sexual contacts (p < 0.01). Heterosexual transmission was the more prevalent among individuals 25–49 years old; individuals over 49 years old were more likely to be persons who inject drugs (PWID). The major HIV-1 variants were CRF02_AG, CRF63_02A, and sub-subtype A6. Major DRMs were detected in 26.9% of the study individuals; 62.2% of those had DRMs to at least two antiretroviral (ARV) drug classes. Phylogenetic analysis revealed a well-defined structure of CRF02_AG, indicating locally evolving sub-epidemics. The lack of well-defined phylogenetic structure was observed for sub-subtype A6. The estimated origin date of CRF02_AG was January 1997; CRF63_02A, April 2004; and A6, June 1995. A rapid evolutionary dynamic of CRF02_AG and A6 among Kyrgyz population since the mid-1990s was observed. We observed the high levels of HIV-1 genetic diversity and drug resistance in the study population. Complex patterns of HIV-1 phylogenetics in Kyrgyzstan were found. This study highlights the importance of molecular–epidemiological analysis for HIV-1 surveillance and treatment implementation to reduce new HIV-1 infections.

Longitudinal typing of molecular HIV clusters in a statewide epidemic

BACKGROUND

HIV molecular epidemiology is increasingly integrated into public health prevention. We conducted cluster typing to enhance characterization of a densely sampled statewide epidemic towards informing public health.

METHODS

We identified HIV clusters, categorized them into types, and evaluated their dynamics between 2004 and 2019 in Rhode Island. We grouped sequences by diagnosis year, assessed cluster changes between paired phylogenies, t0 and t1, representing adjacent years and categorized clusters as stable (cluster in t0 phylogeny = cluster in t1 phylogeny) or unstable (cluster in t0 ≠ cluster in t1). Unstable clusters were further categorized as emerging (t1 phylogeny only) or growing (larger in t1 phylogeny). We determined proportions of each cluster type, of individuals in each cluster type, and of newly diagnosed individuals in each cluster type, and assessed trends over time.

RESULTS

A total of 1727 individuals with available HIV-1 subtype B pol sequences were diagnosed in Rhode Island by 2019. Over time, stable clusters and individuals in them dominated the epidemic, increasing over time, with reciprocally decreasing unstable clusters and individuals in them. Conversely, proportions of newly diagnosed individuals in unstable clusters significantly increased. Within unstable clusters, proportions of emerging clusters and of individuals in them declined; whereas proportions of newly diagnosed individuals in growing clusters significantly increased over time.

CONCLUSION

Distinct molecular cluster types were identified in the Rhode Island epidemic. Cluster dynamics demonstrated increasing stable and decreasing unstable clusters driven by growing, rather than emerging clusters, suggesting consistent in-state transmission networks. Cluster typing could inform public health beyond conventional approaches and direct interventions.

Role of geospatial mapping in the planning of HIV programs: A case study from Southern India

ABSTRACT

Geographic information systems (GIS) tools can be used to understand the spatial distribution of local HIV epidemics but are often underutilized, especially in low-middle income countries. We present characteristics of an HIV epidemic within Hyderabad, a large city in southern India, as a case study to highlight the utility of such data in program planning.Cross-sectional sample recruited using respondent-driven sampling in a cluster-randomized trial.We analyzed data from 2 cross-sectional respondent-driven sampling surveys of MSM in Hyderabad, which were conducted as part of a cluster-randomized trial. All participants were tested for HIV and those positive underwent viral load quantification. ArcGIS was used to create heat maps of MSM distribution using self-reported postal code of residence and combined into larger zones containing at least 200 MSM.Postal code data was available for 661 MSM (66.2%) in the baseline and 978 MSM (97.8%) in the follow-up survey. The proportion of HIV-positive MSM (12.7-15.7%) and prevalence of virally suppressed persons (2.6-8.2%) increased between the 2 surveys. The distribution of all MSM, HIV-positive MSM, and HIV-viremic MSM differed significantly by geographic zone with several zones having higher numbers of HIV-positive and viremic individuals than would be expected based on the distribution of all MSM.The prevalence of HIV and HIV viremia among MSM differed by geographic zones within a city and evolved over time. Such data could be critical to improving program implementation efficiency by accurately targeting resources to population characteristics.

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.

Phylogenetic Cluster Analysis Identifies Virological and Behavioral Drivers of Human Immunodeficiency Virus Transmission in Men Who Have Sex With Men

BACKGROUND

Identifying local outbreaks and their drivers is a key step toward curbing human immunodeficiency virus (HIV) transmission and potentially achieving HIV elimination. Such outbreaks can be identified as transmission clusters extracted from phylogenetic trees constructed of densely sampled viral sequences. In this study, we combined phylogenetic transmission clusters with extensive data on virological suppression and behavioral risk of cluster members to quantify the drivers of ongoing transmission over 10 years.

METHODS

Using the comprehensive Swiss HIV Cohort Study and its drug-resistance database, we reconstructed phylogenetic trees for each year between 2007 and 2017. We identified HIV transmission clusters dominated by men who have sex with men (MSM) and determined their annual growth. We used Poisson regression to assess if cluster growth was associated with a per-cluster infectivity and behavioral risk score.

RESULTS

Both infectivity and behavioral risk scores were significantly higher in growing MSM transmission clusters compared to nongrowing clusters (P ≤ .01). The fraction of transmission clusters without infectious members acquiring new infections increased significantly over the study period. The infectivity score was significantly associated with per-capita incidence of MSM transmission clusters in 8 years, while the behavioral risk score was significantly associated with per-capita incidence of MSM transmission clusters in 3 years.

CONCLUSIONS

We present a phylogenetic method to identify hotspots of ongoing transmission among MSM. Our results demonstrate the effectiveness of treatment as prevention at the population level. However, the significantly increasing number of new infections among transmission clusters without infectious members highlights a relative shift from diagnosed to undiagnosed individuals as drivers of HIV transmission in Swiss MSM.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Phylogenetic Analysis of Human Immunodeficiency Virus from People Who Inject Drugs in Indonesia, Ukraine, and Vietnam: HPTN 074

BACKGROUND

HIV Prevention Trials Network (HPTN) 074 evaluated human immunodeficiency virus (HIV) prevention interventions for people who inject drugs (PWID) in Indonesia, Ukraine, and Vietnam. Study interventions included support for HIV infection and substance use treatment. The study enrolled index participants living with HIV and injection partners who were not living with HIV. Seven partners acquired HIV infection during the study (seroconverters). We analyzed the phylogenetic relatedness between HIV strains in the cohort and the multiplicity of infection in seroconverters.

METHODS

Pol region consensus sequences were used for phylogenetic analysis. Data from next-generation sequencing (NGS, env region) were used to evaluate genetic linkage of HIV from the 7 seroconverters and the corresponding index participants (index-partner pairs), to analyze HIV from index participants in pol sequence clusters, and to analyze multiplicity of HIV infection.

RESULTS

Phylogenetic analysis of pol sequences from 445 index participants and 7 seroconverters identified 18 sequence clusters (2 index-partner pairs, 1 partner-partner pair, and 15 index-only groups with 2-7 indexes/cluster). Analysis of NGS data confirmed linkage for the 2 index-partner pairs, the partner-partner pair, and 11 of the 15 index-index clusters. The remaining 5 seroconverters had infections that were not linked to the corresponding enrolled index participant. Three (42.9%) of the 7 seroconverters were infected with more than 1 HIV strain (3-8 strains per person).

CONCLUSIONS

We identified complex patterns of HIV clustering and linkage among PWID in 3 communities. This should be considered when designing strategies for HIV prevention for PWID.

CLINICAL TRIALS REGISTRATION

NCT02935296.

Social Network Interventions for HIV Transmission Elimination

Purpose of Review

Network interventions for HIV prevention represent a potential area for growth in a globalizing world, where persons are more easily connected to one another through social media and networking applications. The basic tenets of network interventions such as (1) selection of a change agent, (2) segmentation, (3) induction, and (4) alteration represent myriad ways to structure network interventions for HIV prevention with the potential for large public health impact.

Recent Findings

Recent studies have employed the use of social networking websites such as Facebook to identify key persons to recruit others and disseminate information aimed at decreasing HIV transmission and improving safe sex practices among groups who are more vulnerable to HIV acquisition. Many of these interventions have successfully decreased HIV risk behaviors as well as decreased the spread of HIV among intervention cohorts.

Summary

Network interventions for HIV prevention provide more opportunities to reach populations who have not been reached through typical efforts employed in clinical and public health settings, though they are not currently widely employed by the public health community and other stakeholders.

Human T-cell lymphotropic virus type 1 transmission dynamics in rural villages in the Democratic Republic of the Congo with high nonhuman primate exposure

The Democratic Republic of the Congo (DRC) has a history of nonhuman primate (NHP) consumption and exposure to simian retroviruses yet little is known about the extent of zoonotic simian retroviral infections in DRC. We examined the prevalence of human T-lymphotropic viruses (HTLV), a retrovirus group of simian origin, in a large population of persons with frequent NHP exposures and a history of simian foamy virus infection. We screened plasma from 3,051 persons living in rural villages in central DRC using HTLV EIA and western blot (WB). PCR amplification of HTLV tax and LTR sequences from buffy coat DNA was used to confirm infection and to measure proviral loads (pVLs). We used phylogenetic analyses of LTR sequences to infer evolutionary histories and potential transmission clusters. Questionnaire data was analyzed in conjunction with serological and molecular data. A relatively high proportion of the study population (5.4%, n = 165) were WB seropositive: 128 HTLV-1-like, 3 HTLV-2-like, and 34 HTLV-positive but untypeable profiles. 85 persons had HTLV indeterminate WB profiles. HTLV seroreactivity was higher in females, wives, heads of households, and increased with age. HTLV-1 LTR sequences from 109 persons clustered strongly with HTLV-1 and STLV-1 subtype B from humans and simians from DRC, with most sequences more closely related to STLV-1 from Allenopithecus nigroviridis (Allen's swamp monkey). While 18 potential transmission clusters were identified, most were in different households, villages, and health zones. Three HTLV-1-infected persons were co-infected with simian foamy virus. The mean and median percentage of HTLV-1 pVLs were 5.72% and 1.53%, respectively, but were not associated with age, NHP exposure, village, or gender. We document high HTLV prevalence in DRC likely originating from STLV-1. We demonstrate regional spread of HTLV-1 in DRC with pVLs reported to be associated with HTLV disease, supporting local and national public health measures to prevent spread and morbidity.

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.

Mapping of HIV-1C Transmission Networks Reveals Extensive Spread of Viral Lineages Across Villages in Botswana Treatment-as-Prevention Trial

BACKGROUND

Phylogenetic mapping of HIV-1 lineages circulating across defined geographical locations is promising for better understanding HIV transmission networks to design optimal prevention interventions.

METHODS

We obtained near full-length HIV-1 genome sequences from people living with HIV (PLWH), including participants on antiretroviral treatment in the Botswana Combination Prevention Project, conducted in 30 Botswana communities in 2013-2018. Phylogenetic relationships among viral sequences were estimated by maximum likelihood.

RESULTS

We obtained 6078 near full-length HIV-1C genome sequences from 6075 PLWH. We identified 984 phylogenetically distinct HIV-1 lineages (molecular HIV clusters) circulating in Botswana by mid-2018, with 2-27 members per cluster. Of these, dyads accounted for 62%, approximately 32% (n = 316) were found in single communities, and 68% (n = 668) were spread across multiple communities. Men in clusters were approximately 3 years older than women (median age 42 years, vs 39 years; P < .0001). In 65% of clusters, men were older than women, while in 35% of clusters women were older than men. The majority of identified viral lineages were spread across multiple communities.

CONCLUSIONS

A large number of circulating phylogenetically distinct HIV-1C lineages (molecular HIV clusters) suggests highly diversified HIV transmission networks across Botswana communities by 2018.

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.

Information technology in emergency management of COVID-19 outbreak

Emergency management of the emerging infectious disease outbreak is critical for public health threats. Currently, control of the COVID-19 outbreak is an international concern and has become a crucial challenge in many countries. This article reviews significant information technologyIT) applications in emergency management of COVID-19 by considering the prevention/mitigation, preparedness, response, and recovery phases of the crisis. This review was conducted using MEDLINE PubMed), Embase, IEEE, and Google Scholar. Expert opinions were collected to show existence gaps, useful technologies for each phase of emergency management, and future direction. Results indicated that various IT-based systems such as surveillance systems, artificial intelligence, computational methods, Internet of things, remote sensing sensor, online service, and GIS geographic information system) could have different outbreak management applications, especially in response phases. Information technology was applied in several aspects, such as increasing the accuracy of diagnosis, early detection, ensuring healthcare providers' safety, decreasing workload, saving time and cost, and drug discovery. We categorized these applications into four core topics, including diagnosis and prediction, treatment, protection, and management goals, which were confirmed by five experts. Without applying IT, the control and management of the crisis could be difficult on a large scale. For reducing and improving the hazard effect of disaster situations, the role of IT is inevitable. In addition to the response phase, communities should be considered to use IT capabilities in prevention, preparedness, and recovery phases. It is expected that IT will have an influential role in the recovery phase of COVID-19. Providing IT infrastructure and financial support by the governments should be more considered in facilitating IT capabilities.

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.

Reassessing the Ethics of Molecular HIV Surveillance in the Era of Cluster Detection and Response: Toward HIV Data Justice

In the United States, clinical HIV data reported to surveillance systems operated by jurisdictional departments of public health are re-used for epidemiology and prevention. In 2018, all jurisdictions began using HIV genetic sequence data from clinical drug resistance tests to identify people living with HIV in "clusters" of others with genetically similar strains. This is called "molecular HIV surveillance" (MHS). In 2019, "cluster detection and response" (CDR) programs that re-use MHS data became the "fourth pillar" of the national HIV strategy. Public health re-uses of HIV data are done without consent and are a source of concern among stakeholders. This article presents three cases that illuminate bioethical challenges associated with re-uses of clinical HIV data for public health. We focus on evidence-base, risk-benefit ratio, determining directionality of HIV transmission, consent, and ethical re-use. The conclusion offers strategies for "HIV data justice." The essay contributes to a "bioethics of the oppressed."

Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention

Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013-2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic's effective reproductive number (Re) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated Re were similar in Odessa and Kyiv before the initiation of TRIP; Re started to decline in 2013 and is now below Re = 1 in Odessa (Re = 0.4, 95%HPD 0.06-0.75), but not in Kyiv (Re = 2.3, 95%HPD 0.2-5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013-2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool.

Understanding disclosed and cryptic HIV transmission risk via genetic analysis: what are we missing and when does it matter?

PURPOSE OF REVIEW

To discuss the recent HIV phylogenetic analyses examining HIV transmission patterns among and within risk groups.

RECENT FINDINGS

Phylodynamic analysis has recently been applied to multiple HIV outbreaks among people who inject drugs to determine whether HIV transmission is ongoing. Large-scale analyses of datasets of HIV sequences collected for drug-resistance testing provide population-level insights into transmission patterns. One focus across world regions has been to investigate whether age-disparity is a driver of HIV transmission. In sub-Saharan Africa, researchers have examined transmission between heterosexuals and MSM and between high prevalence fishing communities and inland communities. In the US and the UK, cryptic risk groups such as nondisclosed MSM and the partners of transgender women are increasingly being uncovered based on their position in densely sampled molecular transmission networks.

SUMMARY

Analysis of HIV genetic sequence can resolve viral transmission patterns between risk groups at unprecedented scales and levels of detail. Future research should focus on understanding the effect of missing data on inferences and the biases of different methods. Uncovering groups and patterns obscured from traditional epidemiolocal analyses is exciting but should not compromise the privacy of the groups in question.

Spatial distribution and characteristics of HIV clusters in Ethiopia

OBJECTIVES

Ethiopia's HIV prevalence has decreased by 75% in the past 20 years with the implementation of antiretroviral therapy, but HIV transmission continues in high-risk clusters. Identifying the spatial and temporal trends, and epidemiologic correlates, of these clusters can lead to targeted interventions.

METHODS

We used biomarker and survey data from the 2005, 2011 and 2016 Ethiopia Demographic and Health Surveys (DHS). The spatial-temporal distribution of HIV was estimated using the Kulldorff spatial scan statistic, a likelihood-based method for determining clustering. Significant clusters (P < 0.05) were identified and compared based on HIV risk factors to non-cluster areas.

RESULTS

In 2005, 2011 and 2016, respectively, 219, 568 and 408 individuals tested positive for HIV. Four HIV clusters were identified, representing 17% of the total population and 43% of all HIV cases. The clusters were centred around Addis Ababa (1), Afar (2), Dire Dawa (3) and Gambella (4). Cluster 1 had higher rates of unsafe injections (4.9% vs. 2.2%, P < 0.001) and transactional sex (6.0% vs. 1.6%, P < 0.001) than non-cluster regions, but more male circumcision (98.5% vs. 91.3%, P < 0.001). Cluster 2 had higher levels of transactional sex (4.9% vs. 1.6%, P < 0.01), but lower levels of unsafe injections (0.8% vs. 2.2%, P < 0.01). Cluster 3 had fewer individuals with> 1 sexual partner (0% vs. 1.7%, P < 0.001) and more male circumcision (100% vs. 91.3%, P < 0.001). Cluster 4 had less male circumcision (59.1% vs. 91.3%, P < 0.01).

CONCLUSIONS

In Ethiopia, geographic HIV clusters are driven by different risk factors. Decreasing the HIV burden requires targeted interventions.

Genetic clustering analysis for HIV infection among MSM in Nigeria: implications for intervention

BACKGROUND

The HIV epidemic continues to grow among MSM in countries across sub-Saharan Africa including Nigeria. To inform prevention efforts, we used a phylogenetic cluster method to characterize HIV genetic clusters and factors associated with cluster formation among MSM living with HIV in Nigeria.

METHODS

We analyzed HIV-1 pol sequences from 417 MSM living with HIV enrolled in the TRUST/RV368 cohort between 2013 and 2017 in Abuja and Lagos, Nigeria. A genetically linked cluster was defined among participants whose sequences had pairwise genetic distance of 1.5% or less. Binary and multinomial logistic regressions were used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with HIV genetic cluster membership and size.

RESULTS

Among 417 MSM living with HIV, 153 (36.7%) were genetically linked. Participants with higher viral load (AOR = 1.72 95% CI: 1.04-2.86), no female partners (AOR = 3.66; 95% CI: 1.97-6.08), and self-identified as male sex (compared with self-identified as bigender) (AOR = 3.42; 95% CI: 1.08-10.78) had higher odds of being in a genetic cluster. Compared with unlinked participants, MSM who had high school education (AOR = 23.84; 95% CI: 2.66-213.49), were employed (AOR = 3.41; 95% CI: 1.89-10.70), had bacterial sexually transmitted infections (AOR = 3.98; 95% CI: 0.89-17.22) and were not taking antiretroviral therapy (AOR = 6.61; 95% CI: 2.25-19.37) had higher odds of being in a large cluster (size > 4).

CONCLUSION

Comprehensive HIV prevention packages should include behavioral and biological components, including early diagnosis and treatment of both HIV and bacterial sexually transmitted infections to optimally reduce the risk of HIV transmission and acquisition.

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.

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.

PANGEA-HIV 2: Phylogenetics And Networks for Generalised Epidemics in Africa

PURPOSE OF REVIEW

The HIV epidemic in sub-Saharan Africa is far from being under control and the ambitious UNAIDS targets are unlikely to be met by 2020 as declines in per-capita incidence being largely offset by demographic trends. There is an increasing number of proven and specific HIV prevention tools, but little consensus on how best to deploy them.

RECENT FINDINGS

Traditionally, phylogenetics has been used in HIV research to reconstruct the history of the epidemic and date zoonotic infections, whereas more recent publications focus on HIV diversity and drug resistance. However, it is also the most powerful method of source attribution available for the study of HIV transmission. The PANGEA (Phylogenetics And Networks for Generalized Epidemics in Africa) consortium has generated over 18 000 NGS HIV sequences from five countries in sub-Saharan Africa. Using phylogenetic methods, we will identify characteristics of individuals or groups, which are most likely to be at risk of infection or at risk of infecting others.

SUMMARY

Combining phylogenetics, phylodynamics and epidemiology will allow PANGEA to highlight where prevention efforts should be focussed to reduce the HIV epidemic most effectively. To maximise the public health benefit of the data, PANGEA offers accreditation to external researchers, allowing them to access the data and join the consortium. We also welcome submissions of other HIV sequences from sub-Saharan Africa to the database.

Transmission patterns of HIV-1 non-R5 strains in Poland

HIV-1 env sequencing enables predictions of viral coreceptor tropism and phylogenetic investigations of transmission events. The aim of the study was to estimate the contribution of non-R5 strains to the viral spread in Poland. Partial proviral env sequences were retrieved from baseline blood samples of patients with newly diagnosed HIV-1 infection between 2008-2014, including 46 patients with recent HIV-1 infection (RHI), and 246 individuals with long-term infection (LTHI). These sequences were subjected to the genotypic coreceptor tropism predictions and phylogenetic analyses to identify transmission clusters. Overall, 27 clusters with 57 sequences (19.5%) were detected, including 15 sequences (26.3%) from patients with RHI. The proportion of non-R5 strains among all study participants was 23.3% (68/292), and was comparable between patients with RHI and LTHI (11/46, 23.9% vs 57/246, 23.2%; p = 1.000). All 11 patients with non-R5 strains and RHI were men having sex with men (MSM). Among these patients, 4 had viral sequences grouped within phylogenetic cluster with another sequence of non-R5 strain obtained from patient with LTHI, indicating potential acquisition of non-R5 HIV-1 for at least 4/46 (8.7%) patients with RHI. We were unable to confirm the contribution of patients with RHI to the forward transmission of non-R5 strains, but a relatively high proportion of non-R5 strains among them deserves attention due to the limited susceptibility to CCR5 antagonists.