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

Assessing transmission attribution risk from simulated sequencing data in HIV molecular epidemiology

BACKGROUND

HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data.

METHODS

We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population sampling depths. To identify the source of transmissions, we calculated infector probability and used phyloscanner software for the analysis of consensus and NGS data, respectively.

RESULTS

Consensus sequence analyses showed that the risk of correctly inferring the source (direct transmission) within identified transmission pairs was very small and independent of sampling depth. Alternatively, NGS analyses showed that identification of the source of a transmission was very accurate, but only for 6.5% of inferred pairs. False positive transmissions were also observed, where one or more unobserved intermediaries were present when compared to the true network.

CONCLUSION

Source attribution using consensus sequences rarely infers direct transmission pairs with high confidence but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying direct transmission pairs, but for only a small percentage of transmission pairs analyzed.

The first-to-test bias: Impact of testing order on assigning responsibility for contagion

When a contagious disease spreads, people wonder about who to blame for transmission. Herein, we document a novel bias, the "First-To-Test" bias, that emerges when individuals assign responsibility for contagion within a dyad. People tend to believe that the member of the dyad who tested positive first is more likely to have given the disease to the other member, even when all other relevant factors are held constant. That is, while using testing order as a basis for assigning responsibility for a dyad's contraction of a contagious disease may be rational in cases where all other relevant factors are not held constant, we show that individuals are more likely to allocate responsibility to whoever tested positive first even when these relevant factors are held constant. This overgeneralization bias emerges regardless of whether the evaluator is an outside observer or the member of the dyad who tested positive first. While we explore this bias with COVID-19 and strep throat, it has implications for other contagious diseases such as sexually transmitted infections (STIs) and illnesses often spread among school children (e.g., influenza, whooping cough). We conclude by discussing its implications for patients and organizations.

Longitudinal population-level HIV epidemiologic and genomic surveillance highlights growing gender disparity of HIV transmission in Uganda

HIV incidence in eastern and southern Africa has historically been concentrated among girls and women aged 15-24 years. As new cases decline with HIV interventions, population-level infection dynamics may shift by age and gender. Here, we integrated population-based surveillance of 38,749 participants in the Rakai Community Cohort Study and longitudinal deep sequence viral phylogenetics to assess how HIV incidence and population groups driving transmission have changed from 2003 to 2018 in Uganda. We observed 1,117 individuals in the incidence cohort and 1,978 individuals in the transmission cohort. HIV viral suppression increased more rapidly in women than men, however incidence declined more slowly in women than men. We found that age-specific transmission flows shifted, while HIV transmission to girls and women (aged 15-24 years) from older men declined by about one third, transmission to women (aged 25-34 years) from men that were 0-6 years older increased by half in 2003 to 2018. Based on changes in transmission flows, we estimated that closing the gender gap in viral suppression could have reduced HIV incidence in women by half in 2018. This study suggests that HIV programs to increase HIV suppression in men are critical to reduce incidence in women, close gender gaps in infection burden and improve men's health in Africa.

Using phylogenetics to infer HIV-1 transmission direction between known transmission pairs

Identifying the transmission direction between individuals provides unparalleled power to understand infectious disease epidemiology. With epidemiological and clinical information typically unavailable to infer transmission direction, phylogenetic analysis of pathogen sequence data offers an alternative approach. While the success of this phylogenetic analysis varies, the reasons remain unknown. We analyze sequence data from over 100 transmission pairs for which both the transmission direction of HIV is known and detailed additional information is available. We find that easily quantifiable phylogenetic and sampling characteristics discriminate whether a phylogenetically inferred transmission direction is correct. Our analysis highlights that while phylogenetic approaches to infer transmission direction are unsuitable for individual-level analysis, such as forensic investigations, confidence in source attribution can be incorporated in population-level analyses.

Inferring the transmission direction between linked individuals living with HIV provides unparalleled power to understand the epidemiology that determines transmission. Phylogenetic ancestral-state reconstruction approaches infer the transmission direction by identifying the individual in whom the most recent common ancestor of the virus populations originated. While these methods vary in accuracy, it is unclear why. To evaluate the performance of phylogenetic ancestral-state reconstruction to determine the transmission direction of HIV-1 infection, we inferred the transmission direction for 112 transmission pairs where transmission direction and detailed additional information were available. We then fit a statistical model to evaluate the extent to which epidemiological, sampling, genetic, and phylogenetic factors influenced the outcome of the inference. Finally, we repeated the analysis under real-life conditions with only routinely available data. We found that whether ancestral-state reconstruction correctly infers the transmission direction depends principally on the phylogeny's topology. For example, under real-life conditions, the probability of identifying the correct transmission direction increases from 32%—when a monophyletic–monophyletic or paraphyletic–polyphyletic tree topology is observed and when the tip closest to the root does not agree with the state at the root—to 93% when a paraphyletic–monophyletic topology is observed and when the tip closest to the root agrees with the root state. Our results suggest that documenting larger differences in relative intrahost diversity increases our confidence in the transmission direction inference of linked pairs for population-level studies of HIV. These findings provide a practical starting point to determine our confidence in transmission direction inference from ancestral-state reconstruction.

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

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

Use of next generation sequencing technologies for the diagnosis and epidemiology of infectious diseases

For the first time, next generation sequencing technologies provide access to genomic information at a price and scale that allow their implementation in routine clinical practice and epidemiology. While there are still many obstacles to their implementation, there are also multiple examples of their major advantages compared with previous methods. Their main advantage is that a single determination allows epidemiological information on the causative microorganism to be obtained simultaneously, as well as its resistance profile, although these advantages vary according to the pathogen under study. This review discusses several examples of the clinical and epidemiological use of next generation sequencing applied to complete genomes and microbiomes and reflects on its future in clinical practice.

Methodological synthesis of Bayesian phylodynamics, HIV-TRACE, and GEE: HIV-1 transmission epidemiology in a racially/ethnically diverse Southern U.S. context

This study introduces an innovative methodological approach to identify potential drivers of structuring HIV-1 transmission clustering patterns between different subpopulations in the culturally and racially/ethnically diverse context of Houston, TX, the largest city in the Southern United States. Using 6332 HIV-1 pol sequences from persons newly diagnosed with HIV during the period 2010–2018, we reconstructed HIV-1 transmission clusters, using the HIV-TRAnsmission Cluster Engine (HIV-TRACE); inferred demographic and risk parameters on HIV-1 transmission dynamics by jointly estimating viral transmission rates across racial/ethnic, age, and transmission risk groups; and modeled the degree of network connectivity by using generalized estimating equations (GEE). Our results indicate that Hispanics/Latinos are most vulnerable to the structure of transmission clusters and serve as a bridge population, acting as recipients of transmissions from Whites (3.0 state changes/year) and from Blacks (2.6 state changes/year) as well as sources of transmissions to Whites (1.8 state changes/year) and to Blacks (1.2 state changes/year). There were high rates of transmission and high network connectivity between younger and older Hispanics/Latinos as well as between younger and older Blacks. Prevention and intervention efforts are needed for transmission clusters that involve younger racial/ethnic minorities, in particular Hispanic/Latino youth, to reduce onward transmission of HIV in Houston.

Evaluation of Phylogenetic Methods for Inferring the Direction of Human Immunodeficiency Virus (HIV) Transmission: HIV Prevention Trials Network (HPTN) 052

BACKGROUND

Phylogenetic analysis can be used to assess human immunodeficiency virus (HIV) transmission in populations. We inferred the direction of HIV transmission using whole-genome HIV sequences from couples with known linked infection and known transmission direction.

METHODS

Complete next-generation sequencing (NGS) data were obtained for 105 unique index-partner sample pairs from 32 couples enrolled in the HIV Prevention Trials Network (HPTN) 052 study (up to 2 samples/person). Index samples were obtained up to 5.5 years before partner infection; partner samples were obtained near the time of seroconversion. The bioinformatics method, phyloscanner, was used to infer transmission direction. Analyses were performed using samples from individual sample pairs, samples from all couples (1 sample/person; group analysis), and all available samples (multisample group analysis). Analysis was also performed using NGS data from defined regions of the HIV genome (gag, pol, env).

RESULTS

Using whole-genome NGS data, transmission direction was inferred correctly (index to partner) for 98 of 105 (93.3%) of the individual sample pairs, 99 of 105 (94.3%) sample pairs using group analysis, and 31 of the 32 couples (96.9%) using multisample group analysis. There were no cases where the incorrect transmission direction (partner to index) was inferred. The accuracy of the method was higher with greater time between index and partner sample collection. Pol region sequences performed better than env or gag sequences for inferring transmission direction.

CONCLUSIONS

We demonstrate the potential of a phylogenetic method to infer the direction of HIV transmission between 2 individuals using whole-genome and pol NGS data.

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

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

Number of HIV-1 founder variants is determined by the recency of the source partner infection

During sexual transmission, the high genetic diversity of HIV-1 within an individual is frequently reduced to one founder variant that initiates infection. Understanding the drivers of this bottleneck is crucial to developing effective infection control strategies. Little is known about the importance of the source partner during this bottleneck. To test the hypothesis that the source partner affects the number of HIV founder variants, we developed a phylodynamic model calibrated using genetic and epidemiological data on all existing transmission pairs for whom the direction of transmission and the infection stage of the source partner are known. Our results suggest that acquiring infection from someone in the acute (early) stage of infection increases the risk of multiple-founder variant transmission compared with acquiring infection from someone in the chronic (later) stage of infection. This study provides the first direct test of source partner characteristics to explain the low frequency of multiple-founder strain infections.

Phylogenetics in HIV transmission: taking within-host diversity into account

PURPOSE OF REVIEW

Within-host diversity complicates transmission models because it recognizes that between-host virus phylogenies are not identical to the transmission history among the infected hosts. This review presents the biological and theoretical foundations for recent development in this field, and shows that modern phylodynamic methods are capable of inferring realistic transmission histories from HIV sequence data.

RECENT FINDINGS

Transmission of single or multiple genetic variants from a donor's HIV population results in donor-recipient phylogenies with combinations of monophyletic, paraphyletic, and polyphyletic patterns. Large-scale simulations and analyses of many real HIV datasets have established that transmission direction, directness, or common source often can be inferred based on HIV sequence data. Phylodynamic reconstruction of HIV transmissions that include within-host HIV diversity have recently been established and made available in several software packages.

SUMMARY

Phylodynamic methods that include realistic features of HIV genetic diversification have come of age, significantly improving inference of key epidemiological parameters. This opens the door to more accurate surveillance and better-informed prevention campaigns.

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.

Prevention of HIV Transmission and the HPTN 052 Study

The HIV Prevention Trials Network 052 study (HPTN 052) was a clinical trial designed to determine whether early treatment for HIV infection prevented transmission of the virus in couples where one partner was infected with HIV and the other was not, referred to as HIV serodiscordant or serodifferent couples. The study enrolled 1,763 couples at 13 sites in 9 countries in Asia, Africa, and the Americas. HPTN 052 demonstrated a minimum of 96% reduction of HIV in heterosexual couples ascribed to antiretroviral treatment; early treatment of HIV significantly reduced other infections in the HIV-infected subjects. This study, in conjunction with similar research, led to significant changes in international HIV treatment guidelines and the concept of treatment as prevention (TasP). This article provides the scientific background and history of how HPTN 052 came into being, the challenges it faced, and the ultimate impact it had on the fields of HIV treatment and prevention.

Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis

To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these 'source' populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8-28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.