Limitations to contact tracing and phylogenetic analysis in establishing HIV type 1 transmission networks in Cuba

Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV-1 evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5-50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling and that adding biomarkers improves reconstructions of real HIV-1 transmission histories. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies.

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

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

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.

High-throughput sequencing (HTS) for the analysis of viral populations

The development of High-Throughput Sequencing (HTS) technologies is having a major impact on the genomic analysis of viral populations. Current HTS platforms can capture nucleic acid variation across millions of genes for both selected amplicons and full viral genomes. HTS has already facilitated the discovery of new viruses, hinted new taxonomic classifications and provided a deeper and broader understanding of their diversity, population and genetic structure. Hence, HTS has already replaced standard Sanger sequencing in basic and applied research fields, but the next step is its implementation as a routine technology for the analysis of viruses in clinical settings. The most likely application of this implementation will be the analysis of viral genomics, because the huge population sizes, high mutation rates and very fast replacement of viral populations have demonstrated the limited information obtained with Sanger technology. In this review, we describe new technologies and provide guidelines for the high-throughput sequencing and genetic and evolutionary analyses of viral populations and metaviromes, including software applications. With the development of new HTS technologies, new and refurbished molecular and bioinformatic tools are also constantly being developed to process and integrate HTS data. These allow assembling viral genomes and inferring viral population diversity and dynamics. Finally, we also present several applications of these approaches to the analysis of viral clinical samples including transmission clusters and outbreak characterization.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Tracking virus outbreaks in the twenty-first century

Emerging viruses have the potential to impose substantial mortality, morbidity and economic burdens on human populations. Tracking the spread of infectious diseases to assist in their control has traditionally relied on the analysis of case data gathered as the outbreak proceeds. Here, we describe how many of the key questions in infectious disease epidemiology, from the initial detection and characterization of outbreak viruses, to transmission chain tracking and outbreak mapping, can now be much more accurately addressed using recent advances in virus sequencing and phylogenetics. We highlight the utility of this approach with the hypothetical outbreak of an unknown pathogen, ‘Disease X’, suggested by the World Health Organization to be a potential cause of a future major epidemic. We also outline the requirements and challenges, including the need for flexible platforms that generate sequence data in real-time, and for these data to be shared as widely and openly as possible.

This Review Article describes how recent advances in viral genome sequencing and phylogenetics have enabled key issues associated with outbreak epidemiology to be more accurately addressed, and highlights the requirements and challenges for generating, sharing and using such data when tackling a viral outbreak.

Molecular epidemiology of a primarily MSM acute HIV-1 cohort in Bangkok, Thailand and connections within networks of transmission in Asia

INTRODUCTION

Thailand plays a substantial role in global HIV-1 transmission of CRF01_AE. Worldwide, men who have sex with men (MSM) are at elevated risk for HIV-1 infection. Hence, understanding HIV-1 diversity in a primarily Thai MSM cohort with acute infection, and its connections to the broader HIV-1 transmission network in Asia is crucial for research and development of HIV-1 vaccines, treatment and cure.

METHODS

Subtypes and diversity of infecting viruses from individuals sampled from 2009 to 2015 within the RV254/SEARCH 010 cohort were assessed by multiregion hybridization assay (MHAbce), multiregion subtype-specific PCR assay (MSSPbce) and full-length single-genome sequencing (SGS). Phylogenetic analysis was performed by maximum likelihood. Pairwise genetic distances of envelope gp160 sequences obtained from the cohort and from Asia (Los Alamos National Laboratory HIV Database) were calculated to identify potential transmission networks.

RESULTS

MHAbce/MSSPbce results identified 81.6% CRF01_AE infecting strains in RV254. CRF01_AE/B recombinants and subtype B were found at 7.3% and 2.8% respectively. Western subtype B strains outnumbered Thai B' strains. Phylogenetic analysis revealed one C, one CRF01_AE/CRF02_AG recombinant and one CRF01_AE/B/C recombinant. Asian network analysis identified one hundred and twenty-three clusters, including five clusters of RV254 participants. None of the RV254 sequences clustered with non-RV254 sequences. The largest international cluster involved 15 CRF01_AE strains from China and Vietnam. The remaining clusters were mostly intracountry connections, of which 31.7% included Thai nodes and 43.1% included Chinese nodes.

CONCLUSION

While the majority of strains in Thailand are CRF01_AE and subtype B, emergence of unique recombinant forms (URFs) are found in a moderate fraction of new HIV-1 infections. Approaches to vaccine design and immunotherapeutics will need to monitor and consider the expanding proportion of recombinants and the increasing genetic diversity in the region. Identified HIV-1 transmission networks indicate ongoing spread of HIV-1 among MSM. As HIV-1 epidemics continue to expand in other Asian countries, transmission network analyses can inform strategies for prevention, intervention, treatment and cure.

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

Background

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

Methods and Findings

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

Conclusions

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

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

Genotypic Resistance Tests Sequences Reveal the Role of Marginalized Populations in HIV-1 Transmission in Switzerland

Targeting hard-to-reach/marginalized populations is essential for preventing HIV-transmission. A unique opportunity to identify such populations in Switzerland is provided by a database of all genotypic-resistance-tests from Switzerland, including both sequences from the Swiss HIV Cohort Study (SHCS) and non-cohort sequences. A phylogenetic tree was built using 11,127 SHCS and 2,875 Swiss non-SHCS sequences. Demographics were imputed for non-SHCS patients using a phylogenetic proximity approach. Factors associated with non-cohort outbreaks were determined using logistic regression. Non-B subtype (univariable odds-ratio (OR): 1.9; 95% confidence interval (CI): 1.8–2.1), female gender (OR: 1.6; 95% CI: 1.4–1.7), black ethnicity (OR: 1.9; 95% CI: 1.7–2.1) and heterosexual transmission group (OR:1.8; 95% CI: 1.6–2.0), were all associated with underrepresentation in the SHCS. We found 344 purely non-SHCS transmission clusters, however, these outbreaks were small (median 2, maximum 7 patients) with a strong overlap with the SHCS’. 65% of non-SHCS sequences were part of clusters composed of >= 50% SHCS sequences. Our data suggests that marginalized-populations are underrepresented in the SHCS. However, the limited size of outbreaks among non-SHCS patients in-care implies that no major HIV outbreak in Switzerland was missed by the SHCS surveillance. This study demonstrates the potential of sequence data to assess and extend the scope of infectious-disease surveillance.

Deep sequencing increases hepatitis C virus phylogenetic cluster detection compared to Sanger sequencing

Effective surveillance and treatment strategies are required to control the hepatitis C virus (HCV) epidemic. Phylogenetic analyses are powerful tools for reconstructing the evolutionary history of viral outbreaks and identifying transmission clusters. These studies often rely on Sanger sequencing which typically generates a single consensus sequence for each infected individual. For rapidly mutating viruses such as HCV, consensus sequencing underestimates the complexity of the viral quasispecies population and could therefore generate different phylogenetic tree topologies. Although deep sequencing provides a more detailed quasispecies characterization, in-depth phylogenetic analyses are challenging due to dataset complexity and computational limitations. Here, we apply deep sequencing to a characterized population to assess its ability to identify phylogenetic clusters compared with consensus Sanger sequencing. For deep sequencing, a sample specific threshold determined by the 50th percentile of the patristic distance distribution for all variants within each individual was used to identify clusters. Among seven patristic distance thresholds tested for the Sanger sequence phylogeny ranging from 0.005-0.06, a threshold of 0.03 was found to provide the maximum balance between positive agreement (samples in a cluster) and negative agreement (samples not in a cluster) relative to the deep sequencing dataset. From 77 HCV seroconverters, 10 individuals were identified in phylogenetic clusters using both methods. Deep sequencing analysis identified an additional 4 individuals and excluded 8 other individuals relative to Sanger sequencing. The application of this deep sequencing approach could be a more effective tool to understand onward HCV transmission dynamics compared with Sanger sequencing, since the incorporation of minority sequence variants improves the discrimination of phylogenetically linked clusters.

Modelling the effects of mass drug administration on the molecular epidemiology of schistosomes

As national governments scale up mass drug administration (MDA) programs aimed to combat neglected tropical diseases (NTDs), novel selection pressures on these parasites increase. To understand how parasite populations are affected by MDA and how to maximize the success of control programmes, it is imperative for epidemiological, molecular and mathematical modelling approaches to be combined. Modelling of parasite population genetic and genomic structure, particularly of the NTDs, has been limited through the availability of only a few molecular markers to date. The landscape of infectious disease research is being dramatically reshaped by next-generation sequencing technologies and our understanding of how repeated selective pressures are shaping parasite populations is radically altering. Genomics can provide high-resolution data on parasite population structure, and identify how loci may contribute to key phenotypes such as virulence and/or drug resistance. We discuss the incorporation of genetic and genomic data, focussing on the recently sequenced Schistosoma spp., into novel mathematical transmission models to inform our understanding of the impact of MDA and other control methods. We summarize what is known to date, the models that exist and how population genetics has given us an understanding of the effects of MDA on the parasites. We consider how genetic and genomic data have the potential to shape future research, highlighting key areas where data are lacking, and how future molecular epidemiology knowledge can aid understanding of transmission dynamics and the effects of MDA, ultimately informing public health policy makers of the best interventions for NTDs.

Transmission clustering among newly diagnosed HIV patients in Chicago, 2008 to 2011: using phylogenetics to expand knowledge of regional HIV transmission patterns

INTRODUCTION

HIV transmission cluster analyses can inform HIV prevention efforts. We describe the first such assessment for transmission clustering among HIV patients in Chicago.

METHODS

We performed transmission cluster analyses using HIV pol sequences from newly diagnosed patients presenting to Chicago's largest HIV clinic between 2008 and 2011. We compared sequences through progressive pairwise alignment, using neighbor joining to construct an unrooted phylogenetic tree. We defined clusters as >2 sequences among which each sequence had at least 1 partner within a genetic distance of ≤1.5%. We used multivariable regression to examine factors associated with clustering and used geospatial analysis to assess geographic proximity of phylogenetically clustered patients.

RESULTS

We compared sequences from 920 patients, median age of 35 years, 75% male, 67% black, 23% Hispanic, and 8% had a rapid plasma reagin titer ≥1:16 concurrent with their HIV diagnosis. We had HIV transmission risk data for 54%; 43% identified as men who have sex with men (MSM). Phylogenetic analysis demonstrated 123 patients (13%) grouped into 26 clusters, the largest having 20 members. In multivariable regression, age <25, black race, MSM status, male gender, higher HIV viral load, and rapid plasma reagin ≥1:16 associated with clustering. We did not observe geographic grouping of genetically clustered patients.

DISCUSSION

Our results demonstrate high rates of HIV transmission clustering, without local geographic foci, among young black MSM in Chicago. Applied prospectively, phylogenetic analyses could guide prevention efforts and help break the cycle of transmission.

Bridging epidemiology with population genetics in a low incidence MSM-driven HIV-1 subtype B epidemic in Central Europe

Background

The HIV-1 epidemic in Slovenia, a small Central European country, has some characteristics that make it an ideal model to study HIV-1 transmission. The epidemic is predominantly affecting men who have sex with men infected with subtype B (89% of all patients), has a low prevalence (less than 1/1000) and is growing slowly. The aim of the present study was to analyze in detail the evolutionary history and the determinants of transmission.

Methods

A total of 223 partial pol gene sequences from therapy naïve individuals were included, representing 52% of all patients newly diagnosed in 13 years (2000–2012) and analyzed together with genetically similar worldwide sequences, selected in a BLAST search.

Results

Combined analysis (maximum likelihood and Bayesian) of HIV-1 transmission chains revealed 8 major clusters (n ≥ 10 patients), 1 group of 4 patients, 2 trios and 12 transmission pairs, thus leaving only 43 (19.3%) Slovenian patients infected with subtype B without a local epidemiological link, indicating a predominance of local transmission of HIV-1 infection. Bayesian analysis performed on a full set of sequences estimated several introductions of HIV-1 into Slovenia, with the most recent common ancestor (tMRCA) of the earliest Slovenian cluster dated to the late 1980s, although tMRCAs obtained from separate independent analysis of each cluster showed considerably more recent estimates. These findings indicate inconsistencies in molecular clock estimation, which we further explored.

We hypothesize that these inconsistent dating estimates across the tree could be caused by an evolutionary rate acceleration of HIV-1 after entering the Slovenia epidemic that is not taken into account by the molecular clock model. It could be caused by a lower transmission rate in this setting, as demonstrated by the low epidemic growth rate estimated by Bayesian skyline plot analysis.

Conclusions

HIV-1 subtype B was introduced into Slovenia at several time points from the late 80s onward. The majority of patients had a local transmission link, indicating a closed HIV community. The observed slower epidemic rate suggests that individuals with a long-lasting infection are the driving force of the epidemic in this region.

Molecular tools for studying HIV transmission in sexual networks

PURPOSE OF REVIEW

Phylogenetics is frequently used for studies of population-based HIV transmission. The purpose of this review is to highlight the current utilities and limitations of phylogenetics in HIV epidemiological research from sample collection through to data analysis.

RECENT FINDINGS

Studies of HIV phylogenies can provide critical information about HIV epidemics that are otherwise difficult to obtain through traditional study design such as transmission of drug-resistant virus, mixing between demographic groups, and rapidity of viral spread within populations. However, recent results from empirical and theoretical studies of HIV phylogenies challenge some of the key assumptions and interpretations from phylogenetic studies. Recent findings include lack of transmission bottlenecks in MSM and injection drug use epidemics, evidence for preferential transmission of HIV virus in heterosexual epidemics, and limited evidence that tree topologies correlate directly with underlying network structures. Other challenges include a lack of a standardized definition for a phylogenetic transmission cluster and biased or sparse sampling of HIV transmission networks.

SUMMARY

Phylogenetics is an important tool for HIV research, and offers opportunities to understand critical aspects of the HIV epidemic. Like all epidemiological research, the methods used and interpretation of results from phylogenetic studies should be made cautiously with careful consideration.

Six challenges in measuring contact networks for use in modelling

Contact networks are playing an increasingly important role in epidemiology. A contact network represents individuals in a host population as nodes and the interactions among them that may lead to the transmission of infection as edges. New avenues for data collection in recent years have afforded us the opportunity to collect individual- and population-scale information to empirically describe the patterns of contact within host populations. Here, we present some of the current challenges in measuring empirical contact networks. We address fundamental questions such as defining contact; measurement of non-trivial contact properties; practical issues of bounding measurement of contact networks in space, time and scope; exploiting proxy information about contacts; dealing with missing data. Finally, we consider the privacy and ethical issues surrounding the collection of contact network data.

HIV Type 1 transmission networks among men having sex with men and heterosexuals in Kenya

We performed a molecular phylogenetic study on HIV-1 polymerase sequences of men who have sex with men (MSM) and heterosexual patient samples in Kenya to characterize any observed HIV-1 transmission networks. HIV-1 polymerase sequences were obtained from samples in Nairobi and coastal Kenya from 84 MSM, 226 other men, and 364 women from 2005 to 2010. Using Bayesian phylogenetics, we tested whether sequences clustered by sexual orientation and geographic location. In addition, we used trait diffusion analyses to identify significant epidemiological links and to quantify the number of transmissions between risk groups. Finally, we compared 84 MSM sequences with all HIV-1 sequences available online at GenBank. Significant clustering of sequences from MSM at both coastal Kenya and Nairobi was found, with evidence of HIV-1 transmission between both locations. Although a transmission pair between a coastal MSM and woman was confirmed, no significant HIV-1 transmission was evident between MSM and the comparison population for the predominant subtype A (60%). However, a weak but significant link was evident when studying all subtypes together. GenBank comparison did not reveal other important transmission links. Our data suggest infrequent intermingling of MSM and heterosexual HIV-1 epidemics in Kenya.

Characterizing HIV transmission networks across the United States

BACKGROUND

Clinically, human immunodeficiency virus type 1 (HIV-1) pol sequences are used to evaluate for drug resistance. These data can also be used to evaluate transmission networks and help describe factors associated with transmission risk.

METHODS

HIV-1 pol sequences from participants at 5 sites in the CFAR Network of Integrated Clinical Systems (CNICS) cohort from 2000-2009 were analyzed for genetic relatedness. Only the first available sequence per participant was included. Inferred transmission networks ("clusters") were defined as ≥2 sequences with ≤1.5% genetic distance. Clusters including ≥3 patients ("networks") were evaluated for clinical and demographic associations.

RESULTS

Of 3697 sequences, 24% fell into inferred clusters: 155 clusters of 2 individuals ("dyads"), 54 clusters that included 3-14 individuals ("networks"), and 1 large cluster that included 336 individuals across all study sites. In multivariable analyses, factors associated with being in a cluster included not using antiretroviral (ARV) drugs at time of sampling (P < .001), sequence collected after 2004 (P < .001), CD4 cell count >350 cells/mL (P < .01), and viral load 10,000-100,000 copies/mL (P < .001) or >100,000 copies/mL (P < .001). In networks, women were more likely to cluster with other women (P < .001), and African Americans with other African Americans (P < .001).

CONCLUSIONS

Molecular epidemiology can be applied to study HIV transmission networks in geographically and demographically diverse cohorts. Clustering was associated with lack of ARV use and higher viral load, implying transmission may be interrupted by earlier diagnosis and treatment. Observed female and African American networks reinforce the importance of diagnosis and prevention efforts targeted by sex and race.

Molecular epidemiology of HIV-1 transmission in a cohort of HIV-1 concordant heterosexual couples from Dakar, Senegal

Background

A large number of HIV-1 infections in Africa occur in married couples. The predominant direction of intracouple transmission and the principal external origins of infection remain important issues of debate.

Methods

We investigated HIV-1 transmission in 46 HIV-1 concordant positive couples from Dakar, Senegal. Intracouple transmission was confirmed by maximum-likelihood phylogenetic analysis and pairwise distance comparisons of HIV-1 env gp41 sequences from both partners. Standardized interview data were used to deduce the direction as well as the external sources of the intracouple transmissions.

Results

Conservative molecular analyses showed linked viruses in 34 (74%) couples, unlinked viruses in 6 (13%) couples, and indeterminate results for 6 (13%) couples. The interview data corresponded completely with the molecular analyses: all linked couples reported internal transmission and all unlinked couples reported external sources of infection. The majority of linked couples (93%) reported the husband as internal source of infection. These husbands most frequently (82%) reported an occasional sexual relationship as external source of infection. Pairwise comparisons of the CD4 count, antiretroviral therapy status, and the proportion of gp41 ambiguous base pairs within transmission pairs correlated with the reported order of infection events.

Conclusions

In this suburban Senegalese population, a majority of HIV-1 concordant couples showed linked HIV-1 transmission with the husband as likely index partner. Our data emphasize the risk of married women for acquiring HIV-1 as a result of the occasional sexual relationships of their husbands.

The HIV Epidemic: High-Income Countries

The HIV epidemic in higher-income nations is driven by receptive anal intercourse, injection drug use through needle/syringe sharing, and, less efficiently, vaginal intercourse. Alcohol and noninjecting drug use increase sexual HIV vulnerability. Appropriate diagnostic screening has nearly eliminated blood/blood product-related transmissions and, with antiretroviral therapy, has reduced mother-to-child transmission radically. Affected subgroups have changed over time (e.g., increasing numbers of Black and minority ethnic men who have sex with men). Molecular phylogenetic approaches have established historical links between HIV strains from central Africa to those in the United States and thence to Europe. However, Europe did not just receive virus from the United States, as it was also imported from Africa directly. Initial introductions led to epidemics in different risk groups in Western Europe distinguished by viral clades/sequences, and likewise, more recent explosive epidemics linked to injection drug use in Eastern Europe are associated with specific strains. Recent developments in phylodynamic approaches have made it possible to obtain estimates of sequence evolution rates and network parameters for epidemics.

Transmission network parameters estimated from HIV sequences for a nationwide epidemic

BACKGROUND

Many studies of sexual behavior have shown that individuals vary greatly in their number of sexual partners over time, but it has proved difficult to obtain parameter estimates relating to the dynamics of human immunodeficiency virus (HIV) transmission except in small-scale contact tracing studies. Recent developments in molecular phylodynamics have provided new routes to obtain these parameter estimates, and current clinical practice provides suitable data for entire infected populations.

METHODS

A phylodynamic analysis was performed on partial pol gene sequences obtained for routine clinical care from 14,560 individuals, representing approximately 60% of the HIV-positive men who have sex with men (MSM) under care in the United Kingdom.

RESULTS

Among individuals linked to others in the data set, 29% are linked to only 1 individual, 41% are linked to 2-10 individuals, and 29% are linked to ≥10 individuals. The right-skewed degree distribution can be approximated by a power law, but the data are best fitted by a Waring distribution for all time depths. For time depths of 5-7 years, the distribution parameter ρ lies within the range that indicates infinite variance.

CONCLUSIONS

The transmission network among UK MSM is characterized by preferential association such that a randomly distributed intervention would not be expected to stop the epidemic.

A novel methodology for large-scale phylogeny partition

Understanding the determinants of virus transmission is a fundamental step for effective design of screening and intervention strategies to control viral epidemics. Phylogenetic analysis can be a valid approach for the identification of transmission chains, and very-large data sets can be analysed through parallel computation. Here we propose and validate a new methodology for the partition of large-scale phylogenies and the inference of transmission clusters. This approach, on the basis of a depth-first search algorithm, conjugates the evaluation of node reliability, tree topology and patristic distance analysis. The method has been applied to identify transmission clusters of a phylogeny of 11,541 human immunodeficiency virus-1 subtype B pol gene sequences from a large Italian cohort. Molecular transmission chains were characterized by means of different clinical/demographic factors, such as the interaction between male homosexuals and male heterosexuals. Our method takes an advantage of a flexible notion of transmission cluster and can become a general framework to analyse other epidemics.

Transmission of new CRF07_BC strains with 7 amino acid deletion in Gag p6

A 7 amino acid deletion in Gag p6 (P6delta7) emerged in Chinese prevalent HIV-1 strain CRF07_BC from different epidemic regions. It is important to determine whether this mutation could be transmitted and spread. In this study, HIV-1 Gag sequences from 5 different epidemic regions in China were collected to trace the transmission linkage and to analyze genetic evolution of P6delta7 strains. The sequence analysis demonstrated that P6delta7 is a CRF07_BC specific deletion, different P6delta7 strains could be originated from different parental CRF07_BC recombinants in different epidemic regions, and the transmission of P6delta7 strain has occurred in IDU populations. This is for the first time to identify the transmission linkage for P6delta7 strains and serves as a wake-up call for further monitoring in the future; In addition, P6delta7 deletion may represent an evolutionary feature which might exert influence on the fitness of CRF07_BC strain.

The threshold bootstrap clustering: a new approach to find families or transmission clusters within molecular quasispecies

Background

Phylogenetic methods produce hierarchies of molecular species, inferring knowledge about taxonomy and evolution. However, there is not yet a consensus methodology that provides a crisp partition of taxa, desirable when considering the problem of intra/inter-patient quasispecies classification or infection transmission event identification. We introduce the threshold bootstrap clustering (TBC), a new methodology for partitioning molecular sequences, that does not require a phylogenetic tree estimation.

Methodology/Principal Findings

The TBC is an incremental partition algorithm, inspired by the stochastic Chinese restaurant process, and takes advantage of resampling techniques and models of sequence evolution. TBC uses as input a multiple alignment of molecular sequences and its output is a crisp partition of the taxa into an automatically determined number of clusters. By varying initial conditions, the algorithm can produce different partitions. We describe a procedure that selects a prime partition among a set of candidate ones and calculates a measure of cluster reliability. TBC was successfully tested for the identification of type-1 human immunodeficiency and hepatitis C virus subtypes, and compared with previously established methodologies. It was also evaluated in the problem of HIV-1 intra-patient quasispecies clustering, and for transmission cluster identification, using a set of sequences from patients with known transmission event histories.

Conclusion

TBC has been shown to be effective for the subtyping of HIV and HCV, and for identifying intra-patient quasispecies. To some extent, the algorithm was able also to infer clusters corresponding to events of infection transmission. The computational complexity of TBC is quadratic in the number of taxa, lower than other established methods; in addition, TBC has been enhanced with a measure of cluster reliability. The TBC can be useful to characterise molecular quasipecies in a broad context.

Epidemiological study of phylogenetic transmission clusters in a local HIV-1 epidemic reveals distinct differences between subtype B and non-B infections

Background

The number of HIV-1 infected individuals in the Western world continues to rise. More in-depth understanding of regional HIV-1 epidemics is necessary for the optimal design and adequate use of future prevention strategies. The use of a combination of phylogenetic analysis of HIV sequences, with data on patients' demographics, infection route, clinical information and laboratory results, will allow a better characterization of individuals responsible for local transmission.

Methods

Baseline HIV-1 pol sequences, obtained through routine drug-resistance testing, from 506 patients, newly diagnosed between 2001 and 2009, were used to construct phylogenetic trees and identify transmission-clusters. Patients' demographics, laboratory and clinical data, were retrieved anonymously. Statistical analysis was performed to identify subtype-specific and transmission-cluster-specific characteristics.

Results

Multivariate analysis showed significant differences between the 59.7% of individuals with subtype B infection and the 40.3% non-B infected individuals, with regard to route of transmission, origin, infection with Chlamydia (p = 0.01) and infection with Hepatitis C virus (p = 0.017). More and larger transmission-clusters were identified among the subtype B infections (p < 0.001). Overall, in multivariate analysis, clustering was significantly associated with Caucasian origin, infection through homosexual contact and younger age (all p < 0.001). Bivariate analysis additionally showed a correlation between clustering and syphilis (p < 0.001), higher CD4 counts (p = 0.002), Chlamydia infection (p = 0.013) and primary HIV (p = 0.017).

Conclusions

Combination of phylogenetics with demographic information, laboratory and clinical data, revealed that HIV-1 subtype B infected Caucasian men-who-have-sex-with-men with high prevalence of sexually transmitted diseases, account for the majority of local HIV-transmissions. This finding elucidates observed epidemiological trends through molecular analysis, and justifies sustained focus in prevention on this high risk group.

Unlocking pathogen genotyping information for public health by mathematical modeling

Molecular typing and mathematical modeling have gone through rapid development in the past decade. Both offer new insights into the epidemiology of infectious diseases, thereby contributing to a better understanding of transmission dynamics. Infectious disease surveillance and control benefit from the optimum use of these techniques. In this paper, we review recent developments and propose methods to integrate pathogen ecology and molecular evolution based on their common dependence on the underlying host contact patterns.

Transmission networks of HIV-1 among men having sex with men in the Netherlands

OBJECTIVE

To obtain insight in the HIV-1 transmission networks among men having sex with men (MSM) in the Netherlands.

DESIGN

A phylogenetic tree was constructed from polymerase sequences isolated from 2877 HIV-1 subtype B-infected patients monitored as part of the AIDS Therapy Evaluation in the Netherlands (ATHENA) nationwide observational cohort.

METHODS

For MSM with a known date of infection, the most similar sequences were selected as potential transmission pairs when they clustered with bootstrap value of at least 99%. Time from infection to onward transmission was estimated as the median time between dates of infection for each transmission pair. The source of infections with a resistant strain was traced using the entire phylogenetic tree.

RESULTS

Of sequences from 403 MSM with a known date of infection between 1987 and 2007, 175 (43%) formed 63 clusters. Median time to onward transmission was 1.4 years (interquartile range 0.6-2.7). Twenty-four (6%) MSM carried a virus with resistance-related mutations, 13 of these were in eight clusters together with sequences from 28 other patients in the entire phylogenetic tree. Six clusters contained sequences obtained from 29 men all presenting the same resistance-related mutations.

CONCLUSION

From our selection of likely transmission pairs, we conclude that onward transmission of HIV-1 from infected MSM in the Netherlands happens both during and after primary infection. Transmission of resistant strains from the antiretroviral therapy-treated population is limited, but strains with resistance-related mutations have formed subepidemics.

Molecular tracing of sexual HIV Type 1 transmission in the southwest border of China

Since the first outbreak of HIV-1 was reported in heroin users in China in 1989, HIV-1 has spread steadily among injection drug users, leading to an exponential growth of nationwide outbreaks from 1998 to 2004. However, the impact of sexual transmission on outbreaks of HIV in China's general population is still unclear. Through a governmental HIV/AIDS surveillance program, an HIV serological study was conducted in volunteers between 1996 and 2005 in Xishuangbanna Dai Autonomous Prefecture of Yunnan province. We performed the transmission reconstruction by molecular epidemiological tracing in a subset of the HIV-1-seropositive individuals diagnosed during this survey. Neighbor joining and maximum likelihood trees based on the HIV-1 pol and env genes were implemented to provide information on putative epidemiological links, which were then confirmed by contact tracing. Of 25,390 volunteers, 501 (2%) accumulated cases of HIV-1 infection (21.1% in needle-sharing drug users, 77.3% in heterosexual adults, 0.4% in homosexual adults, and 1.2% in children born from infected mothers) were diagnosed. Among 44 heterosexually infected and antiretroviral-naive local-traceable individuals (27 infected with HIV-1 subtype CRF01_AE, 15 with CRF08_BC, 1 with G, and 1 with a new B/C recombinant), 18 (40.9%) were coclustered into 8 transmission chains with an average size of 2.25 infections per chain. Phylogenetic and epidemiological linkages confirmed eight heterosexual transmission events. This is the first report providing molecular epidemiological evidence of heterosexual transmission of HIV-1 in China's general population. The reconstruction of transmission of current HIV-1 outbreaks by molecular epidemiological tracing is instrumental in identifying sources of the epidemic and in defining prevention strategies.

Episodic sexual transmission of HIV revealed by molecular phylodynamics

BACKGROUND

The structure of sexual contact networks plays a key role in the epidemiology of sexually transmitted infections, and their reconstruction from interview data has provided valuable insights into the spread of infection. For HIV, the long period of infectivity has made the interpretation of contact networks more difficult, and major discrepancies have been observed between the contact network and the transmission network revealed by viral phylogenetics. The high rate of HIV evolution in principle allows for detailed reconstruction of links between virus from different individuals, but often sampling has been too sparse to describe the structure of the transmission network. The aim of this study was to analyze a high-density sample of an HIV-infected population using recently developed techniques in phylogenetics to infer the short-term dynamics of the epidemic among men who have sex with men (MSM).

METHODS AND FINDINGS

Sequences of the protease and reverse transcriptase coding regions from 2,126 patients, predominantly MSM, from London were compared: 402 of these showed a close match to at least one other subtype B sequence. Nine large clusters were identified on the basis of genetic distance; all were confirmed by Bayesian Monte Carlo Markov chain (MCMC) phylogenetic analysis. Overall, 25% of individuals with a close match with one sequence are linked to 10 or more others. Dated phylogenies of the clusters using a relaxed clock indicated that 65% of the transmissions within clusters took place between 1995 and 2000, and 25% occurred within 6 mo after infection. The likelihood that not all members of the clusters have been identified renders the latter observation conservative.

CONCLUSIONS

Reconstruction of the HIV transmission network using a dated phylogeny approach has revealed the HIV epidemic among MSM in London to have been episodic, with evidence of multiple clusters of transmissions dating to the late 1990s, a period when HIV prevalence is known to have doubled in this population. The quantitative description of the transmission dynamics among MSM will be important for parameterization of epidemiological models and in designing intervention strategies.

Identifying HIV-1 dual infections

Transmission of human immunodeficiency virus (HIV) is no exception to the phenomenon that a second, productive infection with another strain of the same virus is feasible. Experiments with RNA viruses have suggested that both coinfections (simultaneous infection with two strains of a virus) and superinfections (second infection after a specific immune response to the first infecting strain has developed) can result in increased fitness of the viral population. Concerns about dual infections with HIV are increasing. First, the frequent detection of superinfections seems to indicate that it will be difficult to develop a prophylactic vaccine. Second, HIV-1 superinfections have been associated with accelerated disease progression, although this is not true for all persons. In fact, superinfections have even been detected in persons controlling their HIV infections without antiretroviral therapy. Third, dual infections can give rise to recombinant viruses, which are increasingly found in the HIV-1 epidemic. Recombinants could have increased fitness over the parental strains, as in vitro models suggest, and could exhibit increased pathogenicity. Multiple drug resistant (MDR) strains could recombine to produce a pan-resistant, transmittable virus.

We will describe in this review what is presently known about super- and re-infection among ambient viral infections, as well as the first cases of HIV-1 superinfection, including HIV-1 triple infections. The clinical implications, the impact of the immune system, and the effect of anti-retroviral therapy will be covered, as will as the timing of HIV superinfection. The methods used to detect HIV-1 dual infections will be discussed in detail. To increase the likelihood of detecting a dual HIV-1 infection, pre-selection of patients can be done by serotyping, heteroduplex mobility assays (HMA), counting the degenerate base codes in the HIV-1 genotyping sequence, or surveying unexpected increases in the viral load during follow-up. The actual demonstration of dual infections involves a great deal of additional research to completely characterize the patient's viral quasispecies. The identification of a source partner would of course confirm the authenticity of the second infection.