Early HIV RNA decay during raltegravir-containing regimens exhibits two distinct subphases (1a and 1b)

A simple model for viral decay dynamics and the distribution of infected cell life spans in SHIV-infected infant rhesus macaques

The dynamics of HIV viral load following the initiation of antiretroviral therapy is not well-described by simple, single-phase exponential decay. Several mathematical models have been proposed to describe its more complex behavior, the most popular of which is two-phase exponential decay. The underlying assumption in two-phase exponential decay is that there are two classes of infected cells with different lifespans. However, with the exception of CD4+ T cells, there is not a consensus on all of the cell types that can become productively infected, and the fit of the two-phase exponential decay to observed data from SHIV.C.CH505 infected infant rhesus macaques was relatively poor. Therefore, we propose a new model for viral decay, inspired by the Gompertz model where the decay rate itself is a dynamic variable. We modify the Gompertz model to include a linear term that modulates the decay rate. We show that this simple model performs as well as the two-phase exponential decay model on HIV and SIV data sets, and outperforms it for the infant rhesus macaque SHIV.C.CH505 infection data set. We also show that by using a stochastic differential equation formulation, the modified Gompertz model can be interpreted as being driven by a population of infected cells with a continuous distribution of cell lifespans, and estimate this distribution for the SHIV.C.CH505-infected infant rhesus macaques. Thus, we find that the dynamics of viral decay in this model of infant HIV infection and treatment may be explained by a distribution of cell lifespans, rather than two distinct cell types.

Complex decay dynamics of HIV virions, intact and defective proviruses, and 2LTR circles following initiation of antiretroviral therapy

In persons living with HIV-1 (PLWH) who start antiretroviral therapy (ART), plasma virus decays in a biphasic fashion to below the detection limit. The first phase reflects the short half-life (<1 d) of cells that produce most of the plasma virus. The second phase represents the slower turnover (t1/2 = 14 d) of another infected cell population, whose identity is unclear. Using the intact proviral DNA assay (IPDA) to distinguish intact and defective proviruses, we analyzed viral decay in 17 PLWH initiating ART. Circulating CD4+ T cells with intact proviruses include few of the rapidly decaying first-phase cells. Instead, this population initially decays more slowly (t1/2 = 12.9 d) in a process that largely represents death or exit from the circulation rather than transition to latency. This more protracted decay potentially allows for immune selection. After ∼3 mo, the decay slope changes, and CD4+ T cells with intact proviruses decay with a half-life of 19 mo, which is still shorter than that of the latently infected cells that persist on long-term ART. Two-long-terminal repeat (2LTR) circles decay with fast and slow phases paralleling intact proviruses, a finding that precludes their use as a simple marker of ongoing viral replication. Proviruses with defects at the 5' or 3' end of the genome show equivalent monophasic decay at rates that vary among individuals. Understanding these complex early decay processes is important for correct use of reservoir assays and may provide insights into properties of surviving cells that can constitute the stable latent reservoir.

Why the HIV Reservoir Never Runs Dry: Clonal Expansion and the Characteristics of HIV-Infected Cells Challenge Strategies to Cure and Control HIV Infection

Antiretroviral therapy (ART) effectively reduces cycles of viral replication but does not target proviral populations in cells that persist for prolonged periods and that can undergo clonal expansion. Consequently, chronic human immunodeficiency virus (HIV) infection is sustained during ART by a reservoir of long-lived latently infected cells and their progeny. This proviral landscape undergoes change over time on ART. One of the forces driving change in the landscape is the clonal expansion of infected CD4 T cells, which presents a key obstacle to HIV eradication. Potential mechanisms of clonal expansion include general immune activation, antigenic stimulation, homeostatic proliferation, and provirus-driven clonal expansion, each of which likely contributes in varying, and largely unmeasured, amounts to maintaining the reservoir. The role of clinical events, such as infections or neoplasms, in driving these mechanisms remains uncertain, but characterizing these forces may shed light on approaches to effectively eradicate HIV. A limited number of individuals have been cured of HIV infection in the setting of bone marrow transplant; information from these and other studies may identify the means to eradicate or control the virus without ART. In this review, we describe the mechanisms of HIV-1 persistence and clonal expansion, along with the attempts to modify these factors as part of reservoir reduction and cure strategies.

Modeling HIV-1 Within-Host Dynamics After Passive Infusion of the Broadly Neutralizing Antibody VRC01

VRC01 is a broadly neutralizing antibody that targets the CD4 binding site of HIV-1 gp120. Passive administration of VRC01 in humans has assessed the safety and the effect on plasma viremia of this monoclonal antibody (mAb) in a phase 1 clinical trial. After VRC01 infusion, the plasma viral load in most of the participants was reduced but had particular dynamics not observed during antiretroviral therapy. In this paper, we introduce different mathematical models to explain the observed dynamics and fit them to the plasma viral load data. Based on the fitting results we argue that a model containing reversible Ab binding to virions and clearance of virus-VRC01 complexes by a two-step process that includes (1) saturable capture followed by (2) internalization/degradation by phagocytes, best explains the data. This model predicts that VRC01 may enhance the clearance of Ab-virus complexes, explaining the initial viral decay observed immediately after antibody infusion in some participants. Because Ab-virus complexes are assumed to be unable to infect cells, i.e., contain neutralized virus, the model predicts a longer-term viral decay consistent with that observed in the VRC01 treated participants. By assuming a homogeneous viral population sensitive to VRC01, the model provides good fits to all of the participant data. However, the fits are improved by assuming that there were two populations of virus, one more susceptible to antibody-mediated neutralization than the other.

Next-Generation Sequencing in a Direct Model of HIV Infection Reveals Important Parallels to and Differences from In Vivo Reservoir Dynamics

Next-generation sequencing (NGS) represents a powerful tool to unravel the genetic make-up of the HIV reservoir, but limited data exist on its use in vitro Moreover, most NGS studies do not separate integrated from unintegrated DNA, even though selection pressures on these two forms should be distinct. We reasoned we could use NGS to compare the infection of resting and activated CD4 T cells in vitro to address how the metabolic state affects reservoir formation and dynamics. To address these questions, we obtained HIV sequences 2, 4, and 8 days after NL4-3 infection of metabolically activated and quiescent CD4 T cells (cultured with 2 ng/ml interleukin-7). We compared the composition of integrated and total HIV DNA by isolating integrated HIV DNA using pulsed-field electrophoresis before performing sequencing. After a single-round infection, the majority of integrated HIV DNA was intact in both resting and activated T cells. The decay of integrated intact proviruses was rapid and similar in both quiescent and activated T cells. Defective forms accumulated relative to intact ones analogously to what is observed in vivo Massively deleted viral sequences formed more frequently in resting cells, likely due to lower deoxynucleoside triphosphate (dNTP) levels and the presence of multiple restriction factors. To our surprise, the majority of these deleted sequences did not integrate into the human genome. The use of NGS to study reservoir dynamics in vitro provides a model that recapitulates important aspects of reservoir dynamics. Moreover, separating integrated from unintegrated HIV DNA is important in some clinical settings to properly study selection pressures.IMPORTANCE The major implication of our work is that the decay of intact proviruses in vitro is extremely rapid, perhaps as a result of enhanced expression. Gaining a better understanding of why intact proviruses decay faster in vitro might help the field identify strategies to purge the reservoir in vivo When used wisely, in vitro models are a powerful tool to study the selective pressures shaping the viral landscape. Our finding that massively deleted sequences rarely succeed in integrating has several ramifications. It demonstrates that the total HIV DNA can differ substantially in character from the integrated HIV DNA under certain circumstances. The presence of unintegrated HIV DNA has the potential to obscure selection pressures and confound the interpretation of clinical studies, especially in the case of trials involving treatment interruptions.

Uncovering critical properties of the human respiratory syncytial virus by combining in vitro assays and in silico analyses

Many aspects of the respiratory syncytial virus (RSV) are still poorly understood. Yet these knowledge gaps have had and could continue to have adverse, unintended consequences for the efficacy and safety of antivirals and vaccines developed against RSV. Mathematical modelling was used to test and evaluate hypotheses about the rate of loss of RSV infectivity and the mechanisms and kinetics of RSV infection spread in SIAT cells in vitro. While the rate of loss of RSV integrity, as measured via qRT-PCR, is well-described by an exponential decay, the latter mechanism failed to describe the rate at which RSV A Long loses infectivity over time in vitro based on the data presented herein. This is unusual given that other viruses (HIV, HCV, influenza) have been shown to lose their infectivity exponentially in vitro, and indeed an exponential rate of loss of infectivity is always assumed in mathematical modelling and experimental analyses. The infectivity profile of RSV in HEp-2 and SIAT cells remained consistent over the course of an RSV infection, over time and a large range of infectivity. However, SIAT cells were found to be ∼ 100× less sensitive to RSV infection than HEp-2 cells. In particular, we found that RSV spreads inefficiently in SIAT cells, in a manner we show is consistent with the establishment of infection resistance in uninfected cells. SIAT cells are a good in vitro model in which to study RSV in vivo dissemination, yielding similar infection timescales. However, the higher sensitivity of HEp-2 cells to RSV together with its RSV infectivity profile being similar to that of SIAT cells, makes HEp-2 cells more suitable for quantifying RSV infectivity over the course of in vitro RSV infections in SIAT cells. Our findings highlight the importance and urgency of resolving the mechanisms at play in the dissemination of RSV infections in vitro, and the processes by which this infectivity is lost.

The dynamics of simian immunodeficiency virus after depletion of CD8+ cells

Human immunodeficiency virus infection is still one of the most important causes of morbidity and mortality in the world, with a disproportionate human and economic burden especially in poorer countries. Despite many years of intense research, an aspect that still is not well understood is what (immune) mechanisms control the viral load during the prolonged asymptomatic stage of infection. Because CD8+ T cells have been implicated in this control by multiple lines of evidence, there has been a focus on understanding the potential mechanisms of action of this immune effector population. One type of experiment used to this end has been depleting these cells with monoclonal antibodies in the simian immunodeficiency virus-macaque model and then studying the effect of that depletion on the viral dynamics. Here we review what these experiments have told us. We emphasize modeling studies to interpret the changes in viral load observed in these experiments, including discussion of alternative models, assumptions and interpretations, as well as potential future experiments.

Insight into treatment of HIV infection from viral dynamics models

The odds of living a long and healthy life with HIV infection have dramatically improved with the advent of combination antiretroviral therapy. Along with the early development and clinical trials of these drugs, and new field of research emerged called viral dynamics, which uses mathematical models to interpret and predict the time-course of viral levels during infection and how they are altered by treatment. In this review, we summarize the contributions that virus dynamics models have made to understanding the pathophysiology of infection and to designing effective therapies. This includes studies of the multiphasic decay of viral load when antiretroviral therapy is given, the evolution of drug resistance, the long-term persistence latently infected cells, and the rebound of viremia when drugs are stopped. We additionally discuss new work applying viral dynamics models to new classes of investigational treatment for HIV, including latency-reversing agents and immunotherapy.

Mathematical Analysis of Viral Replication Dynamics and Antiviral Treatment Strategies: From Basic Models to Age-Based Multi-Scale Modeling

Viral infectious diseases are a global health concern, as is evident by recent outbreaks of the middle east respiratory syndrome, Ebola virus disease, and re-emerging zika, dengue, and chikungunya fevers. Viral epidemics are a socio-economic burden that causes short- and long-term costs for disease diagnosis and treatment as well as a loss in productivity by absenteeism. These outbreaks and their socio-economic costs underline the necessity for a precise analysis of virus-host interactions, which would help to understand disease mechanisms and to develop therapeutic interventions. The combination of quantitative measurements and dynamic mathematical modeling has increased our understanding of the within-host infection dynamics and has led to important insights into viral pathogenesis, transmission, and disease progression. Furthermore, virus-host models helped to identify drug targets, to predict the treatment duration to achieve cure, and to reduce treatment costs. In this article, we review important achievements made by mathematical modeling of viral kinetics on the extracellular, intracellular, and multi-scale level for Human Immunodeficiency Virus, Hepatitis C Virus, Influenza A Virus, Ebola Virus, Dengue Virus, and Zika Virus. Herein, we focus on basic mathematical models on the population scale (so-called target cell-limited models), detailed models regarding the most important steps in the viral life cycle, and the combination of both. For this purpose, we review how mathematical modeling of viral dynamics helped to understand the virus-host interactions and disease progression or clearance. Additionally, we review different types and effects of therapeutic strategies and how mathematical modeling has been used to predict new treatment regimens.

Dynamics of Simian Immunodeficiency Virus Two-Long-Terminal-Repeat Circles in the Presence and Absence of CD8+ Cells

CD8⁺ cells play a key role in human immunodeficiency virus (HIV)/simian immunodeficiency virus (SIV) infection, but their specific mechanism(s) of action in controlling the virus is unclear. Two-long-terminal-repeat (2-LTR) circles are extrachromosomal products generated upon failed integration of HIV/SIV. To understand the specific effects of CD8⁺ cells on infected cells, we analyzed the dynamics of 2-LTR circles in SIVmac251-infected rhesus macaques (RMs) treated with an integrase inhibitor (INT). Twenty RMs underwent CD8⁺ cell depletion and received raltegravir (RAL) monotherapy or a combination of both. Blood, lymph nodes (LNs), and gut biopsy specimens were routinely sampled. Plasma viral loads (pVLs) and 2-LTR circles from peripheral blood mononuclear cells (PBMCs) and LN lymphocytes were measured with quantitative reverse transcription-PCR (qRT-PCR). In the CD8 depletion group, an ∼1-log increase in pVLs and a slow increase in PBMC 2-LTRs occurred following depletion. In the INT group, a strong decline in pVLs upon treatment initiation and no change in 2-LTR levels were observed. In the INT and CD8⁺ cell depletion group, an increase in pVLs following CD8 depletion similar to that in the CD8 depletion group was observed, with a modest decline following INT initiation, and 2-LTR circles significantly increased in PBMCs and LNs. Analyzing the 2-LTR data across all treatment groups with a mathematical model indicates that the data best support an effect of CD8⁺ cells in killing cells prior to viral integration. Sensitivity analyses of these results confirm that effect but also allow for additional effects, which the data do not discriminate well. Overall, we show that INT does not significantly increase the levels of 2-LTR circles. However, CD8⁺ cell depletion increases the 2-LTR levels, which are enhanced in the presence of an INT.IMPORTANCE CD8⁺ T cells play an essential role in controlling HIV and SIV infection, but the specific mechanisms involved remain poorly understood. Due to failed viral infection, HIV and SIV can form 2-LTR extrachromosomal circles that can be quantified. We present novel data on the dynamics of these 2-LTR forms in a SIV-infected macaque model under three different treatment conditions: depletion of CD8⁺ cells, administration of the integrase inhibitor in a monotherapy, which favors the formation of 2-LTR circles, and a combination of the two treatments. We used a new mathematical model to help interpret the data, and the results suggest that CD8⁺ cells exert a killing effect on infected cells prior to virus integration. These results provide new insights into the mechanisms of action of CD8⁺ cells in SIV infection. Confirmation of our results would be an important step in understanding immune control of HIV.

Measuring integrated HIV DNA ex vivo and in vitro provides insights about how reservoirs are formed and maintained

The identification of the most appropriate marker to measure reservoir size has been a great challenge for the HIV field. Quantitative viral outgrowth assay (QVOA), the reference standard to quantify the amount of replication-competent virus, has several limitations, as it is laborious, expensive, and unable to robustly reactivate every single integrated provirus. PCR-based assays have been developed as an easier, cheaper and less error-prone alternative to QVOA, but also have limitations. Historically, measuring integrated HIV DNA has provided insights about how reservoirs are formed and maintained. In the 1990s, measuring integrated HIV DNA was instrumental in understanding that a subset of resting CD4 T cells containing integrated HIV DNA were the major source of replication-competent virus. Follow-up studies have further characterized the phenotype of these cells containing integrated HIV DNA, as well as shown the correlation between the integration levels and clinical parameters, such as duration of infection, CD4 count and viral load. Integrated HIV DNA correlates with total HIV measures and with QVOA. The integration assay has several limitations. First, it largely overestimates the reservoir size, as both defective and replication-competent proviruses are detected. Since defective proviruses are the majority in patients on ART, it follows that the number of proviruses capable of reactivating and releasing new virions is significantly smaller than the number of integrated proviruses. Second, in patients on ART clonal expansion could theoretically lead to the preferential amplification of proviruses close to an Alu sequence though longitudinal studies have not captured this effect. Proviral sequencing combined with integration measures is probably the best estimate of reservoir size, but it is expensive, time-consuming and requires considerable bioinformatics expertise. All these reasons limit its use on a large scale. Herein, we review the utility of measuring HIV integration and suggest combining it with sequencing and total HIV measurements can provide insights that underlie reservoir maintenance.

Treatment with integrase inhibitor suggests a new interpretation of HIV RNA decay curves that reveals a subset of cells with slow integration

The kinetics of HIV-1 decay under treatment depends on the class of antiretrovirals used. Mathematical models are useful to interpret the different profiles, providing quantitative information about the kinetics of virus replication and the cell populations contributing to viral decay. We modeled proviral integration in short- and long-lived infected cells to compare viral kinetics under treatment with and without the integrase inhibitor raltegravir (RAL). We fitted the model to data obtained from participants treated with RAL-containing regimes or with a four-drug regimen of protease and reverse transcriptase inhibitors. Our model explains the existence and quantifies the three phases of HIV-1 RNA decay in RAL-based regimens vs. the two phases observed in therapies without RAL. Our findings indicate that HIV-1 infection is mostly sustained by short-lived infected cells with fast integration and a short viral production period, and by long-lived infected cells with slow integration but an equally short viral production period. We propose that these cells represent activated and resting infected CD4+ T-cells, respectively, and estimate that infection of resting cells represent ~4% of productive reverse transcription events in chronic infection. RAL reveals the kinetics of proviral integration, showing that in short-lived cells the pre-integration population has a half-life of ~7 hours, whereas in long-lived cells this half-life is ~6 weeks. We also show that the efficacy of RAL can be estimated by the difference in viral load at the start of the second phase in protocols with and without RAL. Overall, we provide a mechanistic model of viral infection that parsimoniously explains the kinetics of viral load decline under multiple classes of antiretrovirals.

Duration of SHIV production by infected cells is not exponentially distributed: Implications for estimates of infection parameters and antiviral efficacy

The duration of the eclipse phase, from cell infection to the production and release of the first virion progeny, immediately followed by the virus-production phase, from the first to the last virion progeny, are important steps in a viral infection, by setting the pace of infection progression and modulating the response to antiviral therapy. Using a mathematical model (MM) and data for the infection of HSC-F cells with SHIV in vitro, we reconfirm our earlier finding that the eclipse phase duration follows a fat-tailed distribution, lasting 19 h (18–20 h). Most importantly, for the first time, we show that the virus-producing phase duration, which lasts 11 h (9.8–12 h), follows a normal-like distribution, and not an exponential distribution as is typically assumed. We explore the significance of this finding and its impact on analysis of plasma viral load decays in HIV patients under antiviral therapy. We find that incorrect assumptions about the eclipse and virus-producing phase distributions can lead to an overestimation of antiviral efficacy. Additionally, our predictions for the rate of plasma HIV decay under integrase inhibitor therapy offer an opportunity to confirm whether HIV production duration in vivo also follows a normal distribution, as demonstrated here for SHIV infections in vitro.

HIV viral kinetics and T cell dynamics in antiretroviral naïve persons starting an integrase strand transfer inhibitor and protease inhibitor regimen

BACKGROUND

Nucleos(t)ide reverse transcriptase inhibitor (NRTI)-sparing regimens may potentially minimize antiretroviral (ART) toxicities, but demonstrate mixed efficacy and toxicity results. The impact of an integrase strand transfer inhibitor (INSTI) and protease inhibitor (PI) regimen on HIV viral dynamics and T cell kinetics remains underdescribed.

OBJECTIVE

To compare the effect of raltegravir + ritonavir boosted lopinavir (RAL + LPV/r) to efavirenz/tenofovir disoproxil fumarate/emtricitabine (EFV/TDF/FTC) on HIV kinetics and T cell dynamics.

METHODS

Fifty participants naïve to ART underwent HIV viral kinetic sampling evaluated using biexponential mixed effects modeling. A subset of 28 subjects (with complete viral suppression) underwent flow cytometry and evaluation of soluble markers of inflammation at weeks 0, 4, and 48 of ART.

RESULTS

RAL + LPV/r compared to EFV/TDF/FTC resulted in a prolonged first phase viral decay rate (18 vs. 13 days p < 0.01). From weeks 0 to 4, RAL + LPV/r was associated with a trend toward greater decreases in activated CD4⁺ T cells (-3.81 vs. -1.18 p = 0.09) and less decreases in activated effector memory CD4⁺ T cells (-0.63 vs. -2.69 p-0.07). These trends did not persist to week 48. No differences were noted at any time point for soluble markers of immune activation.

CONCLUSIONS

The prolonged first phase viral decay observed with RAL + LPV/r in persons starting ART did not result in differences in viral suppression at week 48. We also observed trends in declines in certain cellular markers of immune activation but it remains unclear if this could translate to long-term immunologic benefits in persons on an INSTI + PI.

Influence of raltegravir intensification on viral load and 2-LTR dynamics in HIV patients on suppressive antiretroviral therapy

Antiretroviral therapy can suppress HIV-1 plasma viral load to below the detection limit but cannot eradicate the virus. Whether residual ongoing viral replication persists during suppressive therapy remains unclear. A few clinical studies showed that treatment intensification with an additional drug led to a lower viral load or an increase in 2-LTR (long terminal repeat), a marker for ongoing viral replication. However, some other studies found no change in the viral load and 2-LTR. In this paper, we developed multi-stage models to evaluate the influence of treatment intensification with the integrase inhibitor raltegravir on viral load and 2-LTR dynamics in HIV patients under suppressive therapy. We analyzed one model and obtained the local and global stability of the steady states. The model and its variation predict that raltegravir intensification induces a very minor decrease in the viral load and a minor increase in 2-LTR. We also compared modeling prediction with the 2-LTR data in a raltegravir intensification study. To achieve the 2-LTR increase observed in some patients, the level of viral replication needs to be substantially high, which is inconsistent with the sustained viral suppression in patients during treatment intensification. These modeling results, together with the theoretical estimate of the upper bound of the 2-LTR increase, suggest that treatment intensification with raltegravir has a minor effect on the plasma viremia and 2-LTR in patients under suppressive therapy. Other treatment strategies have to be developed for the cure or functional control of the infection.

Dynamics of an HIV Model with Multiple Infection Stages and Treatment with Different Drug Classes

Highly active antiretroviral therapy can effectively control HIV replication in infected individuals. Some clinical and modeling studies suggested that viral decay dynamics may depend on the inhibited stages of the viral replication cycle. In this paper, we develop a general mathematical model incorporating multiple infection stages and various drug classes that can interfere with specific stages of the viral life cycle. We derive the basic reproductive number and obtain the global stability results of steady states. Using several simple cases of the general model, we study the effect of various drug classes on the dynamics of HIV decay. When drugs are assumed to be 100% effective, drugs acting later in the viral life cycle lead to a faster or more rapid decay in viremia. This is consistent with some patient and experimental data, and also agrees with previous modeling results. When drugs are not 100% effective, the viral decay dynamics are more complicated. Without a second population of long-lived infected cells, the viral load decline can have two phases if drugs act at an intermediate stage of the viral replication cycle. The slopes of viral load decline depend on the drug effectiveness, the death rate of infected cells at different stages, and the transition rate of infected cells from one to the next stage. With a second population of long-lived infected cells, the viral load decline can have three distinct phases, consistent with the observation in patients receiving antiretroviral therapy containing the integrase inhibitor raltegravir. We also fit modeling prediction to patient data under efavirenz (a nonnucleoside reverse-transcriptase inhibitor) and raltegravir treatment. The first-phase viral load decline under raltegravir therapy is longer than that under efavirenz, resulting in a lower viral load at initiation of the second-phase decline in patients taking raltegravir. This explains why patients taking a raltegravir-based therapy were faster to achieve viral suppression than those taking an efavirenz-based therapy. Taken together, this work provides a quantitative and systematic comparison of the effect of different drug classes on HIV decay dynamics and can explain the viral load decline in HIV patients treated with raltegravir-containing regimens.

Residual Viremia in Treated HIV+ Individuals

Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. However, some residual virus remains, below the level of detection, in HIV-infected patients on ART. The source of this viremia is an area of debate: does it derive primarily from activation of infected cells in the latent reservoir, or from ongoing viral replication? Observations seem to be contradictory: there is evidence of short term evolution, implying that there must be ongoing viral replication, and viral strains should thus evolve. However, phylogenetic analyses, and rare emergent drug resistance, suggest no long-term viral evolution, implying that virus derived from activated latent cells must dominate. We use simple deterministic and stochastic models to gain insight into residual viremia dynamics in HIV-infected patients. Our modeling relies on two underlying assumptions for patients on suppressive ART: that latent cell activation drives viral dynamics and that the reproductive ratio of treated infection is less than 1. Nonetheless, the contribution of viral replication to residual viremia in patients on ART may be non-negligible. However, even if the portion of viremia attributable to viral replication is significant, our model predicts (1) that latent reservoir re-seeding remains negligible, and (2) some short-term viral evolution is permitted, but long-term evolution can still be limited: stochastic analysis of our model shows that de novo emergence of drug resistance is rare. Thus, our simple models reconcile the seemingly contradictory observations on residual viremia and, with relatively few parameters, recapitulates HIV viral dynamics observed in patients on suppressive therapy.

In HIV⁺ individuals, antiretroviral therapy (ART) effectively controls HIV viral loads to below levels detectable by routine tests. However, more sensitive tests can detect some residual viremia. The source of this virus is a matter of debate: does it derive from ongoing viral replication, or from viral production following activation of latently infected cells? Experimental observations support both sides of the argument: in patients on therapy, HIV shows no long-term evolution, and emergence of drug-resistant mutants is rare, implying no ongoing viral replication, but there remains short-term evolution, implying the opposite. To reconcile these observations, we propose a mathematical model of latently and productively infected cells and virus. Using our models we predict that, in patients on suppressive ART, the contribution of viral replication to residual virus, while small, yields short term-evolution. But even if the contribution is large, for example if adherence to therapy is poor, long-term evolution can still be limited, and de novo emergence of drug resistance is rare. Thus, our simple models reconcile the seemingly contradictory observations on residual viremia.