HIV competition dynamics over sexual networks: first comer advantage conserves founder effects

How to report and make sense of a new HIV-1 circulating recombinant form?

Co-circulation of multiple HIV-1 subtypes in the same high-risk groups leads to the on-going generation of various inter-subtype recombinants, including unique (URFs) and circulating (CRFs) recombinant forms, which brings a new challenge for the prevention and eradication of HIV/AIDS. Identification and prompt reporting of new CRFs will provide not only new insights into the understanding of genetic diversity and evolution of HIV-1, but also an early warning of potential prevalence of these variants. Currently, 140 HIV-1 CRFs have been described; however, their prevalence and clinical importance are less concerned. Apart from the mosaic genomic maps, less other valuable information, including the clinical and demographic data, genomic sequence characteristics, origin and evolutionary dynamics, as well as representative genomic fragments for determining the variants, are available for most of these CRFs. Accompanied with the growing increase of HIV-1 full-length genomic sequences, more and more CRFs will be identified in the near future due to the high recombination potential of HIV-1. Here, we discuss the prevalence and clinical importance of various HIV-1 CRFs and propose how to report and make sense of a new HIV-1 CRF.

Reconstructing the phylodynamic history and geographic spread of the CRF01_AE-predominant HIV-1 epidemic in the Philippines from PR/RT sequences sampled from 2008 to 2018

The Philippines has had a rapidly growing human immunodeficiency virus (HIV) epidemic with a shift in the prevalent subtype from B to CRF01_AE. However, the phylodynamic history of CRF01_AE in the Philippines has yet to be reconstructed. We conducted a descriptive retrospective study reconstructing the history of HIV-1 CRF01_AE transmissions in the Philippines through molecular epidemiology. Partial polymerase sequences (n = 1144) collected between 2008 and 2018 from three island groups were collated from the Research Institute for Tropical Medicine drug resistance genotyping database. Estimation of the time to the most recent common ancestor (tMRCA), effective reproductive number (Re), effective viral population size (Ne), relative migration rates, and geographic spread of CRF01_AE was performed with BEAST. Re and Ne were compared between CRF01_AE and B. Most CRF01_AE sequences formed a single clade with a tMRCA of June 1996 [95 per cent highest posterior density (HPD): December 1991, October 1999]. An increasing CRF01_AE Ne was observed from the tMRCA to 2013. The CRF01_AE Re reached peaks of 2.46 [95 per cent HPD: 1.76, 3.27] in 2007 and 2.52 [95 per cent HPD: 1.83, 3.34] in 2015. A decrease of CRF01_AE Re occurred in the intervening years of 2007 to 2011, reaching as low as 1.43 [95 per cent HPD: 1.06, 1.90] in 2011, followed by a rebound. The CRF01_AE epidemic most likely started in Luzon and then spread to the other island groups of the country. Both CRF01_AE and Subtype B exhibited similar patterns of Re fluctuation over time. These results characterize the subtype-specific phylodynamic history of the largest CRF01_AE cluster in the Philippines, which contextualizes and may inform past, present, and future public health measures toward controlling the HIV epidemic in the Philippines.

A Tale of Three Recent Pandemics: Influenza, HIV and SARS-CoV-2

Emerging infectious diseases are one of the main threats to public health, with the potential to cause a pandemic when the infectious agent manages to spread globally. The first major pandemic to appear in the 20th century was the influenza pandemic of 1918, caused by the influenza A H1N1 strain that is characterized by a high fatality rate. Another major pandemic was caused by the human immunodeficiency virus (HIV), that started early in the 20th century and remained undetected until 1981. The ongoing HIV pandemic demonstrated a high mortality and morbidity rate, with discrepant impacts in different regions around the globe. The most recent major pandemic event, is the ongoing pandemic of COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused over 5.7 million deaths since its emergence, 2 years ago. The aim of this work is to highlight the main determinants of the emergence, epidemic response and available countermeasures of these three pandemics, as we argue that such knowledge is paramount to prepare for the next pandemic. We analyse these pandemics’ historical and epidemiological contexts and the determinants of their emergence. Furthermore, we compare pharmaceutical and non-pharmaceutical interventions that have been used to slow down these three pandemics and zoom in on the technological advances that were made in the progress. Finally, we discuss the evolution of epidemiological modelling, that has become an essential tool to support public health policy making and discuss it in the context of these three pandemics. While these pandemics are caused by distinct viruses, that ignited in different time periods and in different regions of the globe, our work shows that many of the determinants of their emergence and countermeasures used to halt transmission were common. Therefore, it is important to further improve and optimize such approaches and adapt it to future threatening emerging infectious diseases.

Toward a Theory of the Underpinnings and Vulnerabilities of Structural Racism: Looking Upstream from Disease Inequities among People Who Use Drugs

Structural racism is increasingly recognized as a key driver of health inequities and other adverse outcomes. This paper focuses on structural racism as an "upstream" institutionalized process, how it creates health inequities and how structural racism persists in spite of generations of efforts to end it. So far, "downstream" efforts to reduce these health inequities have had little success in eliminating them. Here, we attempt to increase public health awareness of structural racism and its institutionalization and sociopolitical supports so that research and action can address them. This paper presents both a theoretic and an analytic approach to how structural racism contributes to disproportionate rates of HIV/AIDS and related diseases among oppressed populations. We first discuss differences in disease and health outcomes among people who use drugs (PWUD) and other groups at risk for HIV from different racial and ethnic populations. The paper then briefly analyzes the history of racism; how racial oppression, class, gender and other intersectional divisions interact to create health inequities; and how structural racism is institutionalized in ways that contribute to disease disparities among people who use drugs and other people. It examines the processes, institutions and other structures that reinforce structural racism, and how these, combined with processes that normalize racism, serve as barriers to efforts to counter and dismantle the structural racism that Black, indigenous and Latinx people have confronted for centuries. Finally, we discuss the implications of this analysis for public health research and action to undo racism and to enhance the health of populations who have suffered lifetimes of racial/ethnic oppression, with a focus on HIV/AIDS outcomes.

Modeling the Spread of Epidemics Based on Cellular Automata

Mathematical modeling is a powerful tool to study the process of the spread of infectious diseases. Among various mathematical methods for describing the spread of infectious diseases, the cellular automaton makes it possible to explicitly simulate both the spatial and temporal evolution of epidemics with intuitive local rules. In this paper, a model is proposed and realized on a cellular automata platform, which is applied to simulate the spread of coronavirus disease 2019 (COVID-19) for different administrative districts. A simplified social community is considered with varying parameters, e.g., sex ratio, age structure, population movement, incubation and treatment period, immunity, etc. COVID-19 confirmation data from New York City and Iowa are adopted for model validation purpose. It can be observed that the disease exhibits different spread patterns in different cities, which could be well accommodated by this model. Then, scenarios under different control strategies in the next 100 days in Iowa are simulated, which could provide a valuable reference for decision makers in identifying the critical factors for future infection control in Iowa.

Increasing prevalence and local transmission of non-B HIV-1 subtypes in the French Antilles and French Guiana between 1995 and 2018

The Caribbean and South American French Overseas Territories (CSAFOT) are the regions most heavily affected by the Human Immunodeficiency Virus type 1 (HIV-1) epidemic in France. Although dominated by HIV-1 subtype B, the detection of non-B subtypes and the great proportion of HIV-positive persons born abroad demonstrated the potential for local spread of non-B subtype strains in CSAFOT. To reconstruct the epidemiologic dynamics of major non-B subtype clusters spreading in CSAFOT, we conducted phylogenetic and evolutionary analyses of 2,523 HIV-1 pol sequences collected from patients living in Martinique, Guadeloupe, and French Guiana from 1995 to 2018. A large variety of HIV-1 non-B subtype strains (eight subtypes, twelve CRFs, and multiple URFs) have been introduced in CSAFOT and their prevalence significantly increases over time in Martinique and Guadeloupe. We identified twelve major transmission networks of non-B subtypes (CRF02_AG and subtypes A3, C, D, and F1) that probably arose in Guadeloupe, Martinique, French Guiana, and mainland France between the late 1970s and the middle 2000s. Phylogeographic analyses support frequent non-B subtype viral transmissions within CSAFOT as well as transatlantic transmission between CSAFOT and mainland France. Domestic transmission networks of non-B subtype variants in CSAFOT comprise both men having sex with men and heterosexual individuals from different age groups. Different HIV-1 non-B subtype variants were sequentially introduced in CSAFOT between the late 1970s and the middle 2000s and are currently spreading through domestic, regional, and/or transatlantic networks of individuals from different age and risk groups.

Variation in HIV-1 Nef function within and among viral subtypes reveals genetically separable antagonism of SERINC3 and SERINC5

HIV Nef counteracts cellular host restriction factors SERINC3 and SERINC5, but our understanding of how naturally occurring global Nef sequence diversity impacts these activities is limited. Here, we quantify SERINC3 and SERINC5 internalization function for 339 Nef clones, representing the major pandemic HIV-1 group M subtypes A, B, C and D. We describe distinct subtype-associated hierarchies for Nef-mediated internalization of SERINC5, for which subtype B clones display the highest activities on average, and of SERINC3, for which subtype B clones display the lowest activities on average. We further identify Nef polymorphisms that modulate its ability to counteract SERINC proteins, including substitutions in the N-terminal domain that selectively impair SERINC3 internalization. Our findings demonstrate that the SERINC antagonism activities of HIV Nef differ markedly among major viral subtypes and between individual isolates within a subtype, suggesting that variation in these functions may contribute to global differences in viral pathogenesis.

The Changing Epidemiological Profile of HIV-1 Subtype B Epidemic in Ukraine

While HIV-1 subtype B has caused a large epidemic in the Western world, its transmission in Ukraine remains poorly understood. We assessed the genetic diversity of HIV-1 subtype B viruses circulating in Ukraine, characterized the transmission group structure, and estimated key evolutionary and epidemiological parameters. We analyzed 120 HIV-1 subtype B pol sequences (including 46 newly generated) sampled from patients residing in 11 regions of Ukraine between 2002 and 2017. Phylogenies were estimated using maximum likelihood and Bayesian phylogenetic methods. A Bayesian molecular clock coalescent analysis was used to estimate effective population size dynamics and date the most recent common ancestors of identified clades. A phylodynamic birth-death model was used to estimate the effective reproductive number (R_e) of these clades. We identified two phylogenetically distinct predominantly Ukrainian (≥75%) clades of HIV-1 subtype B. We found no significant transmission group structure for either clade, suggesting frequent mixing among transmission groups. The estimated dates of origin of both subtype B clades were around early 1970s, similar to the introduction of HIV-1 subtype A into Ukraine. R_e was estimated to be 1.42 [95% highest posterior density (HPD) 1.26-1.56] for Clade 1 and 1.69 (95% HPD 1.49-1.84) for Clade 2. Evidently, the subtype B epidemic in the country is no longer concentrated in specific geographical regions or transmission groups. The study results highlight the necessity for strengthening preventive and monitoring efforts to reduce the further spread of HIV-1 subtype B.

Variable Effect of HIV Superinfection on Clinical Status: Insights From Mathematical Modeling

HIV superinfection (infection of an HIV positive individual with another strain of the virus) has been shown to result in a deterioration of clinical status in multiple case studies. However, superinfection with no (or positive) clinical outcome might easily go unnoticed, and the typical effect of superinfection is unknown. We analyzed mathematical models of HIV dynamics to assess the effect of superinfection under various assumptions. We extended the basic model of virus dynamics to explore systematically a set of model variants incorporating various details of HIV infection (homeostatic target cell dynamics, bystander killing, interference competition between viral clones, multiple target cell types, virus-induced activation of target cells). In each model, we identified the conditions for superinfection, and investigated whether and how successful invasion by a second viral strain affects the level of uninfected target cells. In the basic model, and in some of its extensions, the criteria for invasion necessarily entail a decrease in the equilibrium abundance of uninfected target cells. However, we identified three novel scenarios where superinfection can substantially increase the uninfected cell count: (i) if the rate of new infections saturates at high infectious titers (due to interference competition or cell-autonomous innate immunity); or when the invading strain is more efficient at infecting activated target cells, but less efficient at (ii) activating quiescent cells or (iii) inducing bystander killing of these cells. In addition, multiple target cell types also allow for modest increases in the total target cell count. We thus conclude that the effect of HIV superinfection on clinical status might be variable, complicated by factors that are independent of the invasion fitness of the second viral strain.

The epidemic emergence of HIV: what novel enabling factors were involved?

Humans acquired retroviruses from simians, mainly through bushmeat handling. All epidemically successful HIV groups started to spread in early 20th century, contrasting with the antiquity of T-cell lymphotropic viruses, implying that novel enabling factors were involved in HIV emergence. Here we review the Parenteral Serial Transmission and the Enhanced Heterosexual Transmission hypotheses for the adaptation and early spread of HIV. Epidemic start roughly coincides in time with peak genital ulcer disease in cities, suggesting a major role for sexual transmission. Only ill-adapted and rare HIV groups emerged after approximately 1950, when injections and transfusions attained their maximal levels, suggesting that if parenteral serial transmission was necessary for HIV adaptation, it had to be complemented by sexual transmission for HIV to reach epidemic potential.

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Phylodynamics on local sexual contact networks

Phylodynamic models are widely used in infectious disease epidemiology to infer the dynamics and structure of pathogen populations. However, these models generally assume that individual hosts contact one another at random, ignoring the fact that many pathogens spread through highly structured contact networks. We present a new framework for phylodynamics on local contact networks based on pairwise epidemiological models that track the status of pairs of nodes in the network rather than just individuals. Shifting our focus from individuals to pairs leads naturally to coalescent models that describe how lineages move through networks and the rate at which lineages coalesce. These pairwise coalescent models not only consider how network structure directly shapes pathogen phylogenies, but also how the relationship between phylogenies and contact networks changes depending on epidemic dynamics and the fraction of infected hosts sampled. By considering pathogen phylogenies in a probabilistic framework, these coalescent models can also be used to estimate the statistical properties of contact networks directly from phylogenies using likelihood-based inference. We use this framework to explore how much information phylogenies retain about the underlying structure of contact networks and to infer the structure of a sexual contact network underlying a large HIV-1 sub-epidemic in Switzerland.

Phylodynamic models relate the branching pattern of a pathogen’s phylogenetic tree to the tree-like growth of an epidemic as it spreads through a host population. Such models are increasingly used to learn about the epidemiology of different pathogens. We extend current models to consider the structure of host contact networks—the web of physical interactions through which pathogens spread. By considering how local interactions among hosts shape the phylogeny of a pathogen, our models offer a “pathogen’s eye view” of these networks. Our models also provide a statistical framework that can be used to infer network structure directly from phylogenies, which we use to estimate the properties of a sexual contact network in Switzerland from a HIV phylogeny.