Episodic sexual transmission of HIV revealed by molecular phylodynamics

Molecular epidemiology of SARS-CoV-2 genome sentinel surveillance in commercial COVID-19 testing sites targeting asymptomatic individuals during Japan's seventh epidemic wave

Eight peaks of coronavirus disease 2019 (COVID-19) outbreak occurred in Japan, each associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern. The National Epidemiological Surveillance of Infectious Diseases (NESID) analyzed viral genome sequences from symptomatic patients and submitted the results to GISAID. Meanwhile, commercial testing services occasionally sequence samples from asymptomatic individuals. We compared a total of 1248 SARS-CoV-2 full-genome sequences obtained from the SB Coronavirus Inspection Center Corp. (SBCVIC) during Japan's seventh wave, which was dominated by Omicron variants, with 1764 sequences obtained in Japan from GISAID during the same period using chronological phylogenies and molecular transmission networks. The number of SBCVIC sequences was consistent with the number of cases reported by NESID. The SBCVIC detected a shift in the PANGO lineage from BA.2 to BA.5 earlier than that of GISAID. BA.2 lineages from the SBCVIC were distributed at different locations in the transmission network dominated by GISAID entries, whereas BA.5 lineages from SBCVIC and GISAID often formed distinct subclusters. Test-based sentinel surveillance of asymptomatic individuals may be a more manageable approach compared to notifiable disease surveillance; however, it may not necessarily capture all infection populations throughout Japan.

Identification of a circulating long non-coding RNA signature panel in plasma as a novel biomarker for the detection of acute/early-stage HIV-1 infection

BACKGROUND

Individuals with acute / early HIV-1 infection are often unaware that they are infected with HIV-1 and may be involved in high-risk behavior leading to transmission of HIV-1. Identifying individuals with acute / early HIV-1 infection is critical to prevent further HIV-1 transmission, as diagnosis can lead to several effective HIV-1 prevention strategies. Identification of disease-stage specific non-viral host biomarkers would be useful as surrogate markers to accurately identify new HIV-1 infections. The goal of this study was to identify a panel of host derived plasma long non-coding RNAs (lncRNAs) that could serve as prognostic and predictive biomarkers to detect early/acute HIV-1 infection.

METHODS

A total of 84 lncRNAs were analyzed in sixteen plasma samples from HIV-1 infected individuals and four healthy controls using the lncRNA PCR-array. Twenty-one lncRNAs were selected and validated in 80 plasma samples from HIV-1 infected individuals [HIV-1 infected patients in the eclipse stage (n = 20), acute stage (n = 20), post-seroconversion p31 negative stage (n = 20), and post-seroconversion p31 positive stage (n = 20) of infection] and 20 healthy controls. The validation study results were used to develop a plasma lncRNA panel that was evaluated in the panel test phase to detect early/acute HIV-1 infection in 52 independent samples.

RESULTS

We identified a lncRNA panel (Pmodel-I) containing eight lncRNAs (DISC2, H19, IPW, KRASP1, NEAT1, PRINS, WT1-AS and ZFAS1) that could distinguish HIV-1 infection from healthy controls with high AUC 0·990 (95% CI 0.972-1.000), sensitivity (98.75%), and specificity (95%). We also found that Pmodel-II and Pmodel-III demonstrates 100% sensitivity and specificity (AUC 1·00; 95%CI:1·00-1·00) and could distinguish eclipse stage and acute stage of HIV-1 infection from healthy controls respectively. Antiretroviral treatment (ART) cumulatively restored the levels of lncRNAs to healthy controls levels.

CONCLUSION

lncRNA expression changes significantly in response to HIV-1 infection. Our findings also highlight the potential of using circulating lncRNAs to detect both the eclipse and acute stages of HIV-1 infection, which may help to shorten the window period and facilitate early detection and treatment initiation. Initiating ART treatment at this stage would significantly reduce HIV-1 transmission. The differentially expressed lncRNAs identified in this study could serve as potential prognostic and diagnostic biomarkers of HIV-1 infection, as well as new therapeutic targets.

Dynamics and features of transmission clusters of HIV-1 subtypes in the state of São Paulo, Brazil

Background

Molecular epidemiology techniques allow us to track the HIV-1 transmission dynamics. Herein, we combined genetic, clinical and epidemiological data collected during routine clinical treatment to evaluate the dynamics and characteristics of transmission clusters of the most prevalent HIV-1 subtypes in the state of São Paulo, Brazil.

Methods

This was a cross-sectional study conducted with 2,518 persons living with HIV (PLWH) from 53 cities in São Paulo state between Jan 2004 to Feb 2015. The phylogenetic tree of protease/reverse transcriptase (PR/RT) regions was reconstructed by PhyML and ClusterPicker used to infer the transmission clusters based on Shimodaira-Hasegawa (SH) greater than 90% (phylogenetic support) and genetic distance less than 6%.

Results

Of a total of 2,518 sequences, 2,260 were pure subtypes at the PR/RT region, being B (88%), F1 (8.1%), and C (4%). About 21.2% were naïve with a transmitted drug resistance (TDR) rate of 11.8%. A total of 414 (18.3%) of the sequences clustered. These clusters were less evident in subtype B (17.7%) and F1 (15.1%) than in subtype C (40.2%). Clustered sequences were from PLWH at least 5 years younger than non-clustered among subtypes B (p < 0.001) and C (p = 0.037). Men who have sex with men (MSM) predominated the cluster in subtype B (51%), C (85.7%), and F1 (63.6%; p < 0.05). The TDR rate in clustered patients was 15.4, 13.6, and 3.1% for subtypes B, F1, and C, respectively. Most of the infections in subtypes B (80%), C (64%), and F1 (59%) occurred within the state of São Paulo. The metropolitan area of São Paulo presented a high level of endogenous clustering for subtypes B and C. The São Paulo city had 46% endogenous clusters of subtype C.

Conclusion

Our findings showed that MSM, antiretroviral therapy in Treatment-Naive (ART-naïve) patients, and HIV1-C, played an important role in the HIV epidemic in the São Paulo state. Further studies in transmission clusters are needed to guide the prevention intervention.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Increasing intra- and inter-subtype HIV diversity despite declining HIV incidence in Uganda

HIV incidence has been declining in Africa with scale-up of HIV interventions. However, there is limited data on HIV evolutionary trends in African populations with waning epidemics. We evaluated changes in HIV viral diversity and genetic divergence in southern Uganda over a twenty-five-year period spanning the introduction and scale-up of HIV prevention and treatment programs using HIV sequence and survey data from the Rakai Community Cohort Study, an open longitudinal population-based HIV surveillance cohort. Gag (p24) and env (gp41) HIV data were generated from persons living with HIV (PLHIV) in 31 inland semi-urban trading and agrarian communities (1994 to 2018) and four hyperendemic Lake Victoria fishing communities (2011 to 2018) under continuous surveillance. HIV subtype was assigned using the Recombination Identification Program with phylogenetic confirmation. Inter-subtype diversity was estimated using the Shannon diversity index and intra-subtype diversity with the nucleotide diversity and pairwise TN93 genetic distance. Genetic divergence was measured using root-to-tip distance and pairwise TN93 genetic distance analyses. Evolutionary dynamics were assessed among demographic and behavioral sub-groups, including by migration status. 9,931 HIV sequences were available from 4,999 PLHIV, including 3,060 and 1,939 persons residing in inland and fishing communities, respectively. In inland communities, subtype A1 viruses proportionately increased from 14.3% in 1995 to 25.9% in 2017 (p<0.001), while those of subtype D declined from 73.2% in 1995 to 28.2% in 2017 (p<0.001). The proportion of viruses classified as recombinants significantly increased by more than four-fold. Inter-subtype HIV diversity has generally increased. While p24 intra-subtype genetic diversity and divergence leveled off after 2014, diversity and divergence of gp41 increased through 2017. Inter- and intra-subtype viral diversity increased across all population sub-groups, including among individuals with no recent migration history or extra-community sexual partners. This study provides insights into population-level HIV evolutionary dynamics in declining African HIV epidemics following the scale-up of HIV prevention and treatment programs. Continued molecular surveillance may provide a better understanding of the dynamics driving population HIV evolution and yield important insights for epidemic control and vaccine development.

Molecular epidemiology to aid virtual elimination of HIV transmission in Australia

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

Temporal Pattern of the Emergence of a Mutant Virus Escaping Cross-Immunity and Stochastic Extinction Within a Host

A high mutation rate of the RNA virus results in the emergence of novel mutants that may escape the immunity activated by the original (wild-type) strain. However, many of them go extinct because of the stochasticity due to the small initial number of infected cells. In a previous paper, we studied the probability of escaping stochastic extinction when the novel mutant has a faster rate of infection and when it is resistant to a drug that suppresses the wild-type virus. In this study, we examine the effect of escaping the immune reaction of the host. Based on a continuous-time branching process with time-dependent rates, we conclude the chance for a mutant strain to be established [Formula: see text] decreases with time [Formula: see text] since the wild-type infection when the mutant is produced. The number of novel mutants that can escape extinction risk has a peak soon after the wild-type infection. The number of novel escape mutations produced per patient in the early phase of host infection is small both for very strong and very weak immune responses, and it attains its maximum value when immune activity is of an intermediate strength.

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

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

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

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

The potential of genomics for infectious disease forecasting

Genomic technologies have led to tremendous gains in understanding how pathogens function, evolve and interact. Pathogen diversity is now measurable at high precision and resolution, in part because over the past decade, sequencing technologies have increased in speed and capacity, at decreased cost. Alongside this, the use of models that can forecast emergence and size of infectious disease outbreaks has risen, highlighted by the coronavirus disease 2019 pandemic but also due to modelling advances that allow for rapid estimates in emerging outbreaks to inform monitoring, coordination and resource deployment. However, genomics studies have remained largely retrospective. While they contain high-resolution views of pathogen diversification and evolution in the context of selection, they are often not aligned with designing interventions. This is a missed opportunity because pathogen diversification is at the core of the most pressing infectious public health challenges, and interventions need to take the mechanisms of virulence and understanding of pathogen diversification into account. In this Perspective, we assess these converging fields, discuss current challenges facing both surveillance specialists and modellers who want to harness genomic data, and propose next steps for integrating longitudinally sampled genomic data with statistical learning and interpretable modelling to make reliable predictions into the future.

Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana

Background

HIV-1 is endemic in Botswana. The country’s primary challenge is identifying people living with HIV who are unaware of their status. We evaluated factors associated with undiagnosed HIV infection using HIV-1 phylogenetic, behavioural, and demographic data.

Methods

As part of the Botswana Combination Prevention Project, 20% of households in 30 villages were tested for HIV and followed from 2013 to 2018. A total of 12,610 participants were enrolled, 3596 tested HIV-positive at enrolment, and 147 participants acquired HIV during the trial. Extensive socio-demographic and behavioural data were collected from participants and next-generation sequences were generated for HIV-positive cases. We compared three groups of participants: (1) those previously known to be HIV-positive at enrolment (n = 2995); (2) those newly diagnosed at enrolment (n = 601) and (3) those who tested HIV-negative at enrolment but tested HIV-positive during follow-up (n = 147). We searched for differences in demographic and behavioural factors between known and newly diagnosed group using logistic regression. We also compared the topology of each group in HIV-1 phylogenies and used a genetic diversity-based algorithm to classify infections as recent (< 1 year) or chronic (≥ 1 year).

Results

Being male (aOR = 2.23) and younger than 35 years old (aOR = 8.08) was associated with undiagnosed HIV infection (p < 0.001), as was inconsistent condom use (aOR = 1.76). Women were more likely to have undiagnosed infections if they were married, educated, and tested frequently. For men, being divorced increased their risk. The genetic diversity-based algorithm classified most incident infections as recent (75.0%), but almost none of known infections (2.0%). The estimated proportion of recent infections among new diagnoses was 37.0% (p < 0.001).

Conclusion

Our results indicate that those with undiagnosed infections are likely to be young men and women who do not use condoms consistently. Among women, several factors were predictive: being married, educated, and testing frequently increased risk. Men at risk were more difficult to delineate. A sizeable proportion of undiagnosed infections were recent based on a genetic diversity-based classifier. In the era of “test and treat all”, pre-exposure prophylaxis may be prioritized towards individuals who self-identify or who can be identified using these predictors in order to halt onward transmission in time.

Trace the History of HIV and Predict Its Future through Genetic Sequences

Traditional methods of quantifying epidemic spread are based on surveillance data. The most widely used surveillance data are normally incidence data from case reports and hospital records, which are normally susceptible to human error, and sometimes, they even can be seriously error-prone and incomplete when collected during a destructive epidemic. In this manuscript, we introduce a new method to study the spread of infectious disease. We gave an example of how to use this method to predict the virus spreading using the HIV gene sequences data of China. First, we applied Bayesian inference to gene sequences of two main subtypes of the HIV virus to infer the effective reproduction number (GRe(t)) to trace the history of HIV transmission. Second, a dynamic model was established to forecast the spread of HIV medication resistance in the future and also obtain its effective reproduction number (MRe(t)). Through fitting the two effective reproduction numbers obtained from the two separate ways above, some crucial parameters for the dynamic model were obtained. Simply raising the treatment rate has no impact on lowering the infection rate, according to the dynamics model research, but would instead increase the rate of medication resistance. The negative relationship between the prevalence of HIV and the survivorship of infected individuals following treatment may be to blame for this. Reducing the MSM population’s number of sexual partners is a more efficient strategy to reduce transmission per the sensitivity analysis.

Similar But Different: Integrated Phylogenetic Analysis of Austrian and Swiss HIV-1 Sequences Reveal Differences in Transmission Patterns of the Local HIV-1 Epidemics

OBJECTIVES

Phylogenetic analyses of 2 or more countries allow to detect differences in transmission dynamics of local HIV-1 epidemics beyond differences in demographic characteristics.

METHODS

A maximum-likelihood phylogenetic tree was built using pol -sequences of the Swiss HIV Cohort Study (SHCS) and the Austrian HIV Cohort Study (AHIVCOS), with international background sequences. Three types of phylogenetic cherries (clusters of size 2) were analyzed further: (1) domestic cherries; (2) international cherries; and (3) SHCS/AHIVCOS-cherries. Transmission group and ethnicities observed within the cherries were compared with the respective distribution expected from a random distribution of patients on the phylogeny.

RESULTS

The demographic characteristics of the AHIVCOS (included patients: 3'141) and the SHCS (included patients: 12'902) are very similar. In the AHIVCOS, 36.5% of the patients were in domestic cherries, 8.3% in international cherries, and 7.0% in SHCS/AHIVCOS cherries. Similarly, in the SHCS, 43.0% of the patients were in domestic cherries, 8.2% in international cherries, and 1.7% in SHCS/AHIVCOS cherries. Although international cherries in the SHCS were dominated by heterosexuals with men who have sex with men being underrepresented, the opposite was the case for the AHIVCOS. In both cohorts, cherries with one patient belonging to the transmission group intravenous drug user and the other one non-intravenous drug user were underrepresented.

CONCLUSIONS

In both cohorts, international HIV transmission plays a major role in the local epidemics, mostly driven by men who have sex with men in the AHIVOS, and by heterosexuals in the SHCS, highlighting the importance of international collaborations to understand global HIV transmission links on the way to eliminate HIV.

An Approach to Quantifying the Interaction between Behavioral and Transmission Clusters

We hypothesize that patterns of sexual behavior play a role in the conformation of transmission networks, i.e., the way you behave might influence whom you have sex with. If that was the case, behavioral grouping might in turn correlate with, and potentially predict transmission networking, e.g., proximity in a viral phylogeny. We rigorously present an intuitive approach to address this hypothesis by quantifying mapped interactions between groups defined by similarities in sexual behavior along a virus phylogeny while discussing power and sample size considerations. Data from the Swiss HIV Cohort Study on condom use and hepatitis C virus (HCV) sequences served as proof-of-concept. In this case, a strict inclusion criteria contrasting with low HCV prevalence hindered our possibilities to identify significant relationships. This manuscript serves as guide for studies aimed at characterizing interactions between behavioral patterns and transmission networks. Large transmission networks such as those of HIV or COVID-19 are prime candidates for applying this methodological approach.

MicroRNA let-7 and viral infections: focus on mechanisms of action

MicroRNAs (miRNAs) are fundamental post-transcriptional modulators of several critical cellular processes, a number of which are involved in host defense mechanisms. In particular, miRNA let-7 functions as an essential regulator of the function and differentiation of both innate and adaptive immune cells. Let-7 is involved in several human diseases, including cancer and viral infections. Several viral infections have found ways to dysregulate the expression of miRNAs. Extracellular vesicles (EV) are membrane-bound lipid structures released from many types of human cells that can transport proteins, lipids, mRNAs, and miRNAs, including let-7. After their release, EVs are taken up by the recipient cells and their contents released into the cytoplasm. Let-7-loaded EVs have been suggested to affect cellular pathways and biological targets in the recipient cells, and can modulate viral replication, the host antiviral response, and the action of cancer-related viruses. In the present review, we summarize the available knowledge concerning the expression of let-7 family members, functions, target genes, and mechanistic involvement in viral pathogenesis and host defense. This may provide insight into the development of new therapeutic strategies to manage viral infections.

Dating the Origin and Estimating the Transmission Rates of the Major HIV-1 Clusters in Greece: Evidence about the Earliest Subtype A1 Epidemic in Europe

Our aim was to estimate the date of the origin and the transmission rates of the major local clusters of subtypes A1 and B in Greece. Phylodynamic analyses were conducted in 14 subtype A1 and 31 subtype B clusters. The earliest dates of origin for subtypes A1 and B were in 1982.6 and in 1985.5, respectively. The transmission rate for the subtype A1 clusters ranged between 7.54 and 39.61 infections/100 person years (IQR: 9.39, 15.88), and for subtype B clusters between 4.42 and 36.44 infections/100 person years (IQR: 7.38, 15.04). Statistical analysis revealed that the average difference in the transmission rate between the PWID and the MSM clusters was 6.73 (95% CI: 0.86 to 12.60; p = 0.026). Our study provides evidence that the date of introduction of subtype A1 in Greece was the earliest in Europe. Transmission rates were significantly higher for PWID than MSM clusters due to the conditions that gave rise to an extensive PWID HIV-1 outbreak ten years ago in Athens, Greece. Transmission rate can be considered as a valuable measure for public health since it provides a proxy of the rate of epidemic growth within a cluster and, therefore, it can be useful for targeted HIV prevention programs.

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

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

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

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

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

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

Drug resistance mutations in HIV: new bioinformatics approaches and challenges

Drug resistance mutations appear in HIV under treatment pressure. Resistant variants can be transmitted to treatment-naive individuals, which can lead to rapid virological failure and can limit treatment options. Consequently, quantifying the prevalence, emergence and transmission of drug resistance is critical to effectively treating patients and to shape health policies. We review recent bioinformatics developments and in particular describe: (1) the machine learning approaches intended to predict and explain the level of resistance of HIV variants from their sequence data; (2) the phylogenetic methods used to survey the emergence and dynamics of resistant HIV transmission clusters; (3) the impact of deep sequencing in studying within-host and between-host genetic diversity of HIV variants, notably regarding minority resistant variants.

Scale-Free Spanning Trees and Their Application in Genomic Epidemiology

We study the algorithmic problem of finding the most “scale-free-like” spanning tree of a connected graph. This problem is motivated by the fundamental problem of genomic epidemiology: given viral genomes sampled from infected individuals, reconstruct the transmission network (“who infected whom”). We use two possible objective functions for this problem and introduce the corresponding algorithmic problems termedm-SF (-scale free) ands-SF Spanning Tree problems. We prove that those problems are APX- and NP-hard, respectively, even in the classes of cubic and bipartite graphs. We propose two integer linear programming (ILP) formulations for thes-SF Spanning Tree problem, and experimentally assess its performance using simulated and experimental data. In particular, we demonstrate that the ILP-based approach allows for accurate reconstruction of transmission histories of several hepatitis C outbreaks.

Accounting for the Biological Complexity of Pathogenic Fungi in Phylogenetic Dating

In the study of pathogen evolution, temporal dating of phylogenies provides information on when species and lineages may have diverged in the past. When combined with spatial and epidemiological data in phylodynamic models, these dated phylogenies can also help infer where and when outbreaks occurred, how pathogens may have spread to new geographic locations and/or niches, and how virulence or drug resistance has developed over time. Although widely applied to viruses and, increasingly, to bacterial pathogen outbreaks, phylogenetic dating is yet to be widely used in the study of pathogenic fungi. Fungi are complex organisms with several biological processes that could present issues with appropriate inference of phylogenies, clock rates, and divergence times, including high levels of recombination and slower mutation rates although with potentially high levels of mutation rate variation. Here, we discuss some of the key methodological challenges in accurate phylogeny reconstruction for fungi in the context of the temporal analyses conducted to date and make recommendations for future dating studies to aid development of a best practices roadmap in light of the increasing threat of fungal outbreaks and antifungal drug resistance worldwide.

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.

Using phylogenetic surveillance and epidemiological data to understand the HIV-1 transmission dynamics in French Guiana

OBJECTIVE

The aim of this study was to understand the transmission dynamics of the HIV-1 subtype B epidemic in French Guiana and the factors that shaped the expansion of major phylogenetic transmission clusters.

DESIGN

HIV-1 subtype B pol sequences with associated epidemiological data obtained from 703 treatment-naive patients living in French Guiana between 2006 and 2012, which correspond to 91% of all HIV cases diagnosed in that period, were employed in this study.

METHODS

Maximum likelihood and Bayesian methods were used to construct phylogenetic trees, identify transmission clusters and estimate intervals between successive infections. Statistical analysis was performed to evaluate epidemiological characteristics associated with cluster membership.

RESULTS

HIV-1 subtype B pol sequences from French Guiana were distributed in 10 large/medium transmission clades (LMTC, n > 10, 55%), 19 small transmission clades (STC, n = 3-8, 10%), 36 dyads (10%) or were nonclustered (25%). The rate of clustering did not differ by sex or clinical stage, but sex workers, crack-cocaine users, young individuals (15-20 years) and nationals or migrants from neighbouring South American countries were more likely to cluster within LMTC than individuals from other groups. We estimated that 53-63% of immigrants were infected after the arrival in French Guiana and that 50% of HIV transmissions within LMTC occurred during the first 2 years after infection.

CONCLUSION

These findings reinforce the notion that high-risk sexual behaviours among young individuals and migrants (postmigration) combined with late HIV diagnosis are key drivers of onward dissemination of major HIV transmission clusters in French Guiana.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Nation-Wide Viral Sequence Analysis of HIV-1 Subtype B Epidemic in 2003–2012 Revealed a Contribution of Men Who Have Sex With Men to the Transmission Cluster Formation and Growth in Japan

Background: To better understand the epidemiology of human immunodeficiency virus type 1 (HIV-1) subtype B transmission in Japan, phylodynamic analysis of viral pol sequences was conducted on individuals newly diagnosed as HIV-1 seropositive.

Methodology: A total of 5,018 patients newly diagnosed with HIV-1 infection and registered in the Japanese Drug Resistance HIV Surveillance Network from 2003 to 2012 were enrolled in the analysis. Using the protease-reverse transcriptase nucleotide sequences, their subtypes were determined, and phylogenetic relationships among subtype B sequences were inferred using three different methods: distance-matrix, maximum likelihood, and Bayesian Markov chain Monte Carlo. Domestically spread transmission clusters (dTCs) were identified based on the following criteria: >95% in interior branch test, >95% in Bayesian posterior probability and <10% in depth-first searches for sub-tree partitions. The association between dTC affiliation and individuals' demographics was analyzed using univariate and multivariate analyses.

Results: Among the cases enrolled in the analysis, 4,398 (87.6%) were classified as subtype B. Many of them were Japanese men who had sex with men (MSM), and 3,708 (84.3%) belonged to any of 312 dTCs. Among these dTCs, 243 (77.9%) were small clusters with <10 individuals, and the largest cluster consisted of 256 individuals. Most dTCs had median time of the most recent common ancestor between 1995 and 2005, suggesting that subtype B infection was spread among MSMs in the second half of the 1990s. Interestingly, many dTCs occurred within geographical regions. Comparing with singleton cases, TCs included more MSM, young person, and individuals with high CD4+ T-cell count at the first consultation. Furthermore, dTC size was significantly correlated with gender, age, transmission risks, recent diagnosis and relative population size of the region mainly distributed.

Conclusions: Our study clarified that major key population of HIV-1 subtype B epidemic in Japan is local MSM groups. The study suggests that HIV-1 subtype B spread via episodic introductions into the local MSM groups, some of the viruses spread to multiple regions. Many cases in dTC were diagnosed during the early phase of infection, suggesting their awareness to HIV risks.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

High Prevalence of HIV-1 Drug Resistance and Dynamics of Transmission Among High-Risk Populations in Port-au-Prince, Haiti

BACKGROUND

In low HIV prevalence settings, understanding the transmission dynamics and the impact of drug resistance is critical to curb down the epidemic. This study aims to explore the prevalence and dynamics of transmission of HIV drug-resistance mutations (DRMs) among key populations in Haiti.

SETTINGS

Eligible participants (naive, treated) were selected from 7 key population friendly health care centers in Port-au-Prince, Haiti, from September 2018 to July 2019.

METHODS

A total of 119 HIV-1 pol sequences were analyzed from men having sex with men (MSM), female sex workers (FSWs), and their sexual partners. Screening for HIV DRMs was performed using the Stanford University Drug Resistance Database. Phylogenetic and network analyses using HIV-TRACE software were performed to infer putative relationships and shared DRMs.

RESULTS

Of the 119 participants, 62.2% were men (74/119), and 75.7% of them (56/74) reported MSM as a main risk factor. The overall DRM prevalence was 58.8% (70/119). A DRM was observed in 37.5% of MSM (21/56), 82.2% of FSWs (37/45), and 66.7% (12/18) among FSWs' clients. In a multivariate model, age and FSWs were significant predictors for DRMs (P = 0.001). Transmission network analysis found 24 of the 119 (20.2%) genetically linked individuals forming 8 clusters. Clustering participants were mostly MSM (15/24; 62.5%). Five clusters (62.5%) had shared DRMs, and K103N and M184V were the main shared mutations.

CONCLUSIONS

High prevalence of HIV DRMs was observed among MSM, FSWs, and their clients in Port-au-Prince, Haiti. Network analysis revealed frequent DRM transmission among genetically linked individuals, highlighting the need for appropriate interventions to limit HIV transmission in these high-risk populations.

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.

Characteristics of HIV-1 molecular transmission networks and drug resistance among men who have sex with men in Tianjin, China (2014-2018)

Background

In Tianjin, China, there is a relatively high prevalence of HIV in men who have sex with men (MSM). The number of HIV cases in Tianjin is also increasing. We investigated the HIV molecular transmission network, genetic tropisms, and drug resistance mutations in Tianjin.

Methods

Blood samples were collected from 510 newly diagnosed antiretroviral therapy (ART)-naïve HIV-1-infected subjects among MSM in Tianjin. Partial pol and env genes were sequenced and used for phylogenetic, genetic tropism, and genotypic drug resistance analyses. Molecular clusters were identified with 1.5% genetic distance and 90% bootstrap support.

Results

Among the 436 HIV-1 pol sequences obtained from the study participants, various genotypes were identified, including CRF01_AE (56.9%), CRF07_BC (27.8%), B (7.3%), CRF55_01B (4.1%), unique recombinant forms (URFs) (3.7%), and CRF59_01B (0.2%). A higher prevalence of X4 viruses was observed in individuals infected with CRF55_01B (56.3%) and CRF01_AE (46.2%) than with other subtypes. Of all 110 sequences in the 36 clusters, 62 (56.4%) were observed in 23 CRF01_AE clusters and 18 (16.4%) in four CRF07_BC clusters. Eight sequences clustered with at least one other shared the same drug resistance mutation (DRM). In different cluster sizes, the distributions of individuals by age, presence of sexually transmitted disease, and presence of DRMs, were significantly different.

Conclusion

We revealed the characteristics of HIV molecular transmission, tropism, and DRMs of ART-naïve HIV-infected individuals among the MSM population in Tianjin. Identifying infected persons at risk of transmission is necessary for proposing counseling and treating these patients to reduce the risk of HIV transmission.

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

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

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

OBJECTIVE

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

DESIGN

Phylogenetic analysis of HIV public health surveillance data.

METHODS

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

RESULTS

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

CONCLUSION

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

Earlier treatment initiation is associated with a decreased number of HIV-1 subtype A1 transmissions in Greece

OBJECTIVES

Subtypes A1 and B are the most prevalent HIV-1 clades in Greece. Subtype A1 epidemic is highly monophyletic and corresponds to transmissions that occurred locally. Our aim in this molecular epidemiology analysis was to investigate the role of early treatment in preventing new HIV-1 transmissions.

METHODS

Our analysis focused on 791 subtype A1 sequences from treatment-naïve individuals in Greece. Estimation of infection dates was performed by molecular clock calculations using Bayesian methods. We estimated the time interval between (1) the infection and sampling dates (linkage to care window), (2) the sampling dates and antiretroviral therapy (ART) initiation (treatment window), and (3) the infection dates and ART initiation (transmissibility window) for the study population. We also inferred the putative source of HIV infections between individuals of different groups divided according to the length of treatment, linkage to care or transmissibility window.

RESULTS

A significant decline was detected for the treatment window during 2014-2015 versus the 2 previous years (p=0.0273), while the linkage to care interval remained unchanged during the study period. Inference of the putative source of HIV infections suggested that individuals with a recent diagnosis or narrow transmissibility window (time period between HIV infection and ART initiation) were not sources of HIV infections to other groups. Contrarily, a significant number of HIV infections originated from individuals with longer transmissibility window interval.

CONCLUSIONS

Our findings showed that the treatment window is decreasing over time, presumably due to the updated treatment guidelines. Our study also demonstrates that people treated earlier after infection do not transmit at high rates, thus documenting the benefits of early ART initiation in preventing ongoing HIV-1 transmission.

A Mathematical Framework for Predicting Lifestyles of Viral Pathogens

Despite being similar in structure, functioning, and size, viral pathogens enjoy very different, usually well-defined ways of life. They occupy their hosts for a few days (influenza), for a few weeks (measles), or even lifelong (HCV), which manifests in acute or chronic infections. The various transmission routes (airborne, via direct physical contact, etc.), degrees of infectiousness (referring to the viral load required for transmission), antigenic variation/immune escape and virulence define further aspects of pathogenic lifestyles. To survive, pathogens must infect new hosts; the success determines their fitness. Infection happens with a certain likelihood during contact of hosts, where contact can also be mediated by vectors. Besides structural aspects of the host-contact network, three parameters appear to be key: the contact rate and the infectiousness during contact, which encode the mode of transmission, and third the immunity of susceptible hosts. On these grounds, what can be said about the reproductive success of viral pathogens? This is the biological question addressed in this paper. The answer extends earlier results of the author and makes explicit connection to another basic work on the evolution of pathogens. A mathematical framework is presented that models intra- and inter-host dynamics in a minimalistic but unified fashion covering a broad spectrum of viral pathogens, including those that cause flu-like infections, childhood diseases, and sexually transmitted infections. These pathogens turn out as local maxima of numerically simulated fitness landscapes. The models involve differential and integral equations, agent-based simulation, networks, and probability.

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.

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

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

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

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

Source identification of HIV-1 transmission in three lawsuits Using Ultra-Deep pyrosequencing and phylogenetic analysis

BACKGROUND/PURPOSE

Intentional transmission of HIV-1 is a crime. Identifying the source of transmission between HIV-1 infected cases using phylogenetic analysis has limitations, including delayed examinations after the initiation of infection and ambiguity of phyletic relationships. This study was the first to introduce phylogenetic tree Results as forensic evidence in a trial in Taiwan.

METHODS

Three lawsuit cases from different district courts in Taiwan were chosen for this study. We identified the source of transmission between individuals in each lawsuit based on the maximum likelihood and Bayesian phylogenetic tree analyses using the HIV-1 sequences from molecular cloning and ultra-deep pyrosequencing (UDPS). Two gene regions of the HIV genome, env and gag, were involved.

RESULTS

The results of phylogenetic analysis using sequences from molecular cloning were clear and evidential enough in lawsuits 1 and 3. Due to the delayed sampling time, the result of sequences from molecular cloning in lawsuit 2 was ambiguous. Combined with the analyzed result of sequences from UDPS and epidemiological information, the source of transmission in lawsuit 2 was further identified.

CONCLUSION

Hence phylogenetic analyses cannot exclude the possibility of unsampled intermediaries, the data interpretation should be more careful and conservative, and it should not be considered as the only evidence for the source identification in a trial without epidemiological or serological information. The evaluation of the introduced UDPS method in the identification of transmission source has shown that the validity and evidential effects were still limited and need further optimization.

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

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

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

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

SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces

SimpactCyan is an open-source simulator for individual-based models in HIV epidemiology. Its core algorithm is written in C++ for computational efficiency, while the R and Python interfaces aim to make the tool accessible to the fast-growing community of R and Python users. Transmission, treatment and prevention of HIV infections in dynamic sexual networks are simulated by discrete events. A generic “intervention” event allows model parameters to be changed over time, and can be used to model medical and behavioural HIV prevention programmes. First, we describe a more efficient variant of the modified Next Reaction Method that drives our continuous-time simulator. Next, we outline key built-in features and assumptions of individual-based models formulated in SimpactCyan, and provide code snippets for how to formulate, execute and analyse models in SimpactCyan through its R and Python interfaces. Lastly, we give two examples of applications in HIV epidemiology: the first demonstrates how the software can be used to estimate the impact of progressive changes to the eligibility criteria for HIV treatment on HIV incidence. The second example illustrates the use of SimpactCyan as a data-generating tool for assessing the performance of a phylodynamic inference framework.

Analysis of HIV-1 diversity, primary drug resistance and transmission networks in Croatia

Molecular epidemiology of HIV-1 infection in treatment-naive HIV-1 infected persons from Croatia was investigated. We included 403 persons, representing 92.4% of all HIV-positive individuals entering clinical care in Croatia in 2014–2017. Overall prevalence of transmitted drug resistance (TDR) was estimated at 16.4%. Resistance to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside RTI (NNRTIs) and protease inhibitors (PIs) was found in 11.4%, 6.7% and 2.5% of persons, respectively. Triple-class resistance was determined in 2.2% of individuals. In addition, a single case (1.0%) of resistance to integrase strand-transfer inhibitors (InSTIs) was found. Deep sequencing was performed on 48 randomly selected samples and detected additional TDR mutations in 6 cases. Phylogenetic inference showed that 347/403 sequences (86.1%) were part of transmission clusters and identified forward transmission of resistance in Croatia, even that of triple-class resistance. The largest TDR cluster of 53 persons with T215S was estimated to originate in the year 1992. Our data show a continuing need for pre-treatment HIV resistance testing in Croatia. Even though a low prevalence of resistance to InSTI was observed, surveillance of TDR to InSTI should be continued.

Effectiveness of Transmitted Drug Resistance Testing Before Initiation of Antiretroviral Therapy in HIV-Positive Individuals

BACKGROUND

For people living with HIV, major guidelines in high-income countries recommend testing for transmitted drug resistance (TDR) to guide the choice of first-line antiretroviral therapy (ART). However, individuals who fail a first-line regimen can now be switched to one of several effective regimens. Therefore, the virological and clinical benefit of TDR testing needs to be evaluated.

METHODS

We included individuals from the HIV-CAUSAL Collaboration who enrolled <6 months of HIV diagnosis between 2006 and 2015, were ART-naive, and had measured CD4 count and HIV-RNA. Follow-up started at the date when all inclusion criteria were first met (baseline). We compared 2 strategies: (1) TDR testing within 3 months of baseline versus (2) no TDR testing. We used inverse probability weighting to estimate the 5-year proportion and hazard ratios (HRs) of virological suppression (confirmed HIV-RNA <50 copies/mL), and of AIDS or death under both strategies.

RESULTS

Of 25,672 eligible individuals (82% males, 52% diagnosed in 2010 or later), 17,189 (67%) were tested for TDR within 3 months of baseline. Of these, 6% had intermediate- or high-level TDR to any antiretroviral drug. The estimated 5-year proportion virologically suppressed was 77% under TDR testing and 74% under no TDR testing; HR 1.06 (95% confidence interval: 1.03 to 1.19). The estimated 5-year risk of AIDS or death was 6% under both strategies; HR 1.03 (95% confidence interval: 0.95 to 1.12).

CONCLUSIONS

TDR prevalence was low. Although TDR testing improved virological response, we found no evidence that it reduced the incidence of AIDS or death in first 5 years after diagnosis.

Leveraging Phylogenetics to Understand HIV Transmission and Partner Notification Networks

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Phylogenetic Methods Inconsistently Predict the Direction of HIV Transmission Among Heterosexual Pairs in the HPTN 052 Cohort

BACKGROUND

We evaluated use of phylogenetic methods to predict the direction of human immunodeficiency virus (HIV) transmission.

METHODS

For 33 pairs of HIV-infected patients (hereafter, "index patients") and their partners who acquired genetically linked HIV infection during the study, samples were collected from partners and index patients close to the time when the partner seroconverted (hereafter, "SC samples"); for 31 pairs, samples collected from the index patient at an earlier time point (hereafter, "early index samples") were also available. Phylogenies were inferred using env next-generation sequences (1 tree per pair/subtype). The direction of transmission (DoT) predicted from each tree was classified as correct or incorrect on the basis of which sequences (those from the index patient or the partner) were closest to the root. DoT was also assessed using maximum parsimony to infer ancestral node states for 100 bootstrap trees.

RESULTS

DoT was predicted correctly for both single-pair and subtype-specific trees in 22 pairs (67%) by using SC samples and in 23 pairs (74%) by using early index samples. DoT was predicted incorrectly for 4 pairs (15%) by using SC or early index samples. In the bootstrap analysis, DoT was predicted correctly for 18 pairs (55%) by using SC samples and for 24 pairs (73%) by using early index samples. DoT was predicted incorrectly for 7 pairs (21%) by using SC samples and for 4 pairs (13%) by using early index samples.

CONCLUSIONS

Phylogenetic methods based solely on the tree topology of HIV env sequences, particularly without consideration of phylogenetic uncertainty, may be insufficient for determining DoT.

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

Background

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

Methods

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

Results

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

Conclusions

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

The phylogenetic approach for viral infectious disease evolution and epidemiology: An updating review

In the last decade, the phylogenetic approach is recurrent in molecular evolutionary analysis. On 12 May, 2019, about 2 296 213 papers are found, but typing "phylogeny" or "epidemiology AND phylogeny" only 199 804 and 20 133 are retrieved, respectively. Molecular epidemiology in infectious diseases is widely used to define the source of infection as so as the ancestral relationships of individuals sampled from a population. Coalescent theory and phylogeographic analysis have had scientific application in several, recent pandemic events, and nosocomial outbreaks. Hepatitis viruses and immunodeficiency virus (human immunodeficiency virus) have been largely studied. Phylogenetic analysis has been recently applied on Polyomaviruses so as in the more recent outbreaks due to different arboviruses type as Zika and chikungunya viruses discovering the source of infection and the geographic spread. Data on sequences isolated by the microorganism are essential to apply the phylogenetic tools and research in the field of infectious disease phylodinamics is growing up. There is the need to apply molecular phylogenetic and evolutionary methods in areas out of infectious diseases, as translational genomics and personalized medicine. Lastly, the application of these tools in vaccine strategy so as in antibiotic and antiviral researchers are encouraged.