Nested model reveals potential amplification of an HIV epidemic due to drug resistance

The effect of bottleneck size on evolution in nested Darwinian populations

Previous work has shown how a minimal ecological structure consisting of patchily distributed resources and recurrent dispersal between patches can scaffold Darwinian properties onto collections of cells. When the timescale of dispersal is long compared with the time to consume resources, patch fitness increases but comes at a cost to cell growth rates. This creates conditions that initiate evolutionary transitions in individuality. A key feature of the scaffold is a bottleneck created during dispersal, causing patches to be founded by single cells. The bottleneck decreases competition within patches and, hence, creates a strong hereditary link at the level of patches. Here, we construct a fully stochastic model to investigate the effect of bottleneck size on the evolutionary dynamics of both cells and collectives. We show that larger bottlenecks simply slow the dynamics, but, at some point, which depends on the parameters of the within-patch model, the direction of evolution towards the equilibrium reverses. Introduction of random fluctuations in bottleneck sizes with some positive probability of smaller sizes counteracts this, even when the probability of smaller bottlenecks is minimal.

Transmitted HIV-1 is more virulent in heterosexual individuals than men-who-have-sex-with-men

Transmission bottlenecks introduce selection pressures on HIV-1 that vary with the mode of transmission. Recent studies on small cohorts have suggested that stronger selection pressures lead to fitter transmitted/founder (T/F) strains. Manifestations of this selection bias at the population level have remained elusive. Here, we analysed early CD4 cell count measurements reported from ∼340,000 infected heterosexual individuals (HET) and men-who-have-sex-with-men (MSM), across geographies, ethnicities and calendar years. The reduction in CD4 counts early in infection is reflective of the virulence of T/F strains. MSM and HET use predominant modes of transmission, namely, anal and penile-vaginal, with among the largest differences in the selection pressures at transmission across modes. Further, in most geographies, the groups show little inter-mixing, allowing for the differential selection bias to be sustained and amplified. We found that the early reduction in CD4 counts was consistently greater in HET than MSM (P<0.05). To account for inherent variations in baseline CD4 counts, we constructed a metric to quantify the extent of progression to AIDS as the ratio of the reduction in measured CD4 counts from baseline and the reduction associated with AIDS. We found that this progression corresponding to the early CD4 measurements was ∼68% for MSM and ∼87% for HET on average (P<10⁻⁴; Cohen’s d, d_s = 0.36), reflecting the more severe disease caused by T/F strains in HET than MSM at the population level. Interestingly, the set-point viral load was not different between the groups (d_s<0.12), suggesting that MSM were more tolerant and not more resistant to their T/F strains than HET. This difference remained when we controlled for confounding factors using multivariable regression. We concluded that the different selection pressures at transmission have resulted in more virulent T/F strains in HET than MSM. These findings have implications for our understanding of HIV-1 pathogenesis, evolution, and epidemiology.

HIV-1 encounters a key bottleneck at the time of its transmission from one individual to another. This transmission bottleneck can differ between modes of transmission. The stronger this bottleneck is, the more fit the virus has to be to be successfully transmitted. Accordingly, the transmitted/founder (T/F) strains of HIV-1 may have different fitness in risk groups that use different modes of transmission. While studies on small cohorts do support this notion, observations of the manifestations of this differential selection bias at the population level have been lacking. Here, we examined reported early CD4 count measurements from ∼340,000 HET and MSM, across geographies, ethnicities, and calendar years. Early CD4 counts are a measure of the severity of the infection due to T/F strains. HET and MSM transmit predominantly via penile-vaginal and anal modes, respectively, and do not inter-mix significantly. Remarkably, we found that HET consistently had lower early CD4 counts than MSM. This difference could not be attributed to potential confounding factors, such as set-point viral load. The difference thus provided evidence that T/F strains had evolved to be more virulent in HET than MSM at the population level. Intervention strategies may benefit from accounting for this difference between risk groups.

A Network Immuno-Epidemiological HIV Model

In this paper we formulate a multi-scale nested immuno-epidemiological model of HIV on complex networks. The system is described by ordinary differential equations coupled with a partial differential equation. First, we prove the existence and uniqueness of the immunological model and then establish the well-posedness of the multi-scale model. We derive an explicit expression of the basic reproduction number [Formula: see text] of the immuno-epidemiological model. The system has a disease-free equilibrium and an endemic equilibrium. The disease-free equilibrium is globally stable when [Formula: see text] and unstable when [Formula: see text]. Numerical simulations suggest that [Formula: see text] increases as the number of nodes in the network increases. Further, we find that for a scale-free network the number of infected individuals at equilibrium is a hump-like function of the within-host reproduction number; however, the dependence becomes monotone if the network has predominantly low connectivity nodes or high connectivity nodes.

Linked within-host and between-host models and data for infectious diseases: a systematic review

The observed dynamics of infectious diseases are driven by processes across multiple scales. Here we focus on two: within-host, that is, how an infection progresses inside a single individual (for instance viral and immune dynamics), and between-host, that is, how the infection is transmitted between multiple individuals of a host population. The dynamics of each of these may be influenced by the other, particularly across evolutionary time. Thus understanding each of these scales, and the links between them, is necessary for a holistic understanding of the spread of infectious diseases. One approach to combining these scales is through mathematical modeling. We conducted a systematic review of the published literature on multi-scale mathematical models of disease transmission (as defined by combining within-host and between-host scales) to determine the extent to which mathematical models are being used to understand across-scale transmission, and the extent to which these models are being confronted with data. Following the PRISMA guidelines for systematic reviews, we identified 24 of 197 qualifying papers across 30 years that include both linked models at the within and between host scales and that used data to parameterize/calibrate models. We find that the approach that incorporates both modeling with data is under-utilized, if increasing. This highlights the need for better communication and collaboration between modelers and empiricists to build well-calibrated models that both improve understanding and may be used for prediction.

Conflict and accord of optimal treatment strategies for HIV infection within and between hosts

Most of previous studies investigated the optimal control of HIV infection at either within-host or between-host level. However, the optimal treatment strategy for the individual may not be optimal for the population and vice versa. To determine when the two-level optimal controls are in accord or conflict, we develop a multi-scale model using various functions that link the viral load within host and the transmission rate between hosts, calibrated by cohort data. We obtain the within-host optimal treatment scheme that minimizes the viral load and maximizes the count of healthy cells at the individual level, and the coupled optimal scheme that minimizes the basic reproduction number at the population level. Mathematical analysis shows that whether the two-level optimal controls coincide depends on the sign of the product of their switching functions. Numerical results suggest that they are in accord for a high maximal drug efficacy but may conflict for a low drug efficacy. Using the multi-scale model, we also identify a threshold of the treatment effectiveness that determines how early treatment initiation can affect the disease dynamics among population. These results may help develop a synergistic treatment protocol beneficial to both HIV-infected individuals and the whole population.

Evolution of HIV-1 within untreated individuals and at the population scale in Uganda

HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important.

Multi-scale immunoepidemiological modeling of within-host and between-host HIV dynamics: systematic review of mathematical models

OBJECTIVE

The objective of this study is to conduct a systematic review of multi-scale HIV immunoepidemiological models to improve our understanding of the synergistic impact between the HIV viral-immune dynamics at the individual level and HIV transmission dynamics at the population level.

BACKGROUND

While within-host and between-host models of HIV dynamics have been well studied at a single scale, connecting the immunological and epidemiological scales through multi-scale models is an emerging method to infer the synergistic dynamics of HIV at the individual and population levels.

METHODS

We reviewed nine articles using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework that focused on the synergistic dynamics of HIV immunoepidemiological models at the individual and population levels.

RESULTS

HIV immunoepidemiological models simulate viral immune dynamics at the within-host scale and the epidemiological transmission dynamics at the between-host scale. They account for longitudinal changes in the immune viral dynamics of HIV+ individuals, and their corresponding impact on the transmission dynamics in the population. They are useful to analyze the dynamics of HIV super-infection, co-infection, drug resistance, evolution, and treatment in HIV+ individuals, and their impact on the epidemic pathways in the population. We illustrate the coupling mechanisms of the within-host and between-host scales, their mathematical implementation, and the clinical and public health problems that are appropriate for analysis using HIV immunoepidemiological models.

CONCLUSION

HIV immunoepidemiological models connect the within-host immune dynamics at the individual level and the epidemiological transmission dynamics at the population level. While multi-scale models add complexity over a single-scale model, they account for the time varying immune viral response of HIV+ individuals, and the corresponding impact on the time-varying risk of transmission of HIV+ individuals to other susceptibles in the population.

Short Communication: High Viral Load and Multidrug Resistance Due to Late Switch to Second-Line Regimens Could Be a Major Obstacle to Reach the 90-90-90 UNAIDS Objectives in Sub-Saharan Africa

In the context of lifelong antiretroviral treatment (ART) as early as possible and to end the HIV/AIDS epidemic as a public health treat by 2030, it is important to evaluate the potential risk of transmission of HIV-1 drug resistance (HIVDR) in resource-limited countries (RLCs). Since HIV transmission is driven by HIV-1 RNA viral load (VL), we studied the association between plasma VL and HIVDR profiles in 451 adults failing first-line ART from the 2LADY-ANRS12169/EDCTP trial in Burkina Faso, Cameroon, and Senegal. Median duration on first-line ART was 49 months (IQR: 33-69) and 91% patients were asymptomatic. Genotypic drug resistance testing was successful for 446 patients and 98.7% of them were resistant to at least one of the first-line drugs; 40.6% and 55.8% were resistant to two or three drugs of their ongoing first-line ART, respectively. The median VL was higher in patients with HIVDR to all ongoing first-line drugs than in those still susceptible to at least one drug; 4.7 log₁₀ copies/ml (IQR: 4.3-5.2) versus 4.2 log₁₀ copies/ml (IQR: 3.7-4.7), respectively (p < .001). The proportion of patients with HIVDR to all ongoing first-line drugs was highest (77.9% [95/122]) in patients with VL >5.0 log₁₀ copies/ml. High rates of cross-resistance to other nucleoside reverse-transcriptase inhibitors were observed and were also highest in patients with high VL. Without improvement of patient monitoring to avoid late switch to second-line regimens, a potential new epidemic caused by HIVDR strains could emerge in sub-Saharan Africa and compromise all efforts to reach 90-90-90 UNAIDS objective by 2020.

Crossing the scale from within-host infection dynamics to between-host transmission fitness: a discussion of current assumptions and knowledge

The progression of an infection within a host determines the ability of a pathogen to transmit to new hosts and to maintain itself in the population. While the general connection between the infection dynamics within a host and the population-level transmission dynamics of pathogens is widely acknowledged, a comprehensive and quantitative understanding that would allow full integration of the two scales is still lacking. Here, we provide a brief discussion of both models and data that have attempted to provide quantitative mappings from within-host infection dynamics to transmission fitness. We present a conceptual framework and provide examples of studies that have taken first steps towards development of a quantitative framework that scales from within-host infections to population-level fitness of different pathogens. We hope to illustrate some general themes, summarize some of the recent advances and-maybe most importantly-discuss gaps in our ability to bridge these scales, and to stimulate future research on this important topic.

Increased Prevalence of Controlled Viremia and Decreased Rates of HIV Drug Resistance Among HIV-Positive People Who Use Illicit Drugs During a Community-wide Treatment-as-Prevention Initiative

BACKGROUND

Although treatment-as prevention (TasP) is a new cornerstone of global human immunodeficiency virus (HIV)-AIDS strategies, its effect among HIV-positive people who use illicit drugs (PWUD) has yet to be evaluated. We sought to describe longitudinal trends in exposure to antiretroviral therapy (ART), plasma HIV-1 RNA viral load (VL) and HIV drug resistance during a community-wide TasP intervention.

METHODS

We used data from the AIDS Care Cohort to Evaluate Exposure to Survival Services study, a prospective cohort of HIV-positive PWUD linked to HIV clinical monitoring records. We estimated longitudinal changes in the proportion of individuals with VL <50 copies/mL and rates of HIV drug resistance using generalized estimating equations (GEE) and extended Cox models.

RESULTS

Between 1 January 2006 and 30 June 2014, 819 individuals were recruited and contributed 1 or more VL observation. During that time, the proportion of individuals with nondetectable VL increased from 28% to 63% (P < .001). In a multivariable GEE model, later year of observation was independently and positively associated with greater likelihood of nondetectable VL (adjusted odds ratio = 1.20 per year; P < .001). Although the proportion of individuals on ART increased, the incidence of HIV drug resistance declined (adjusted hazard ratio = 0.78 per year; P = .011).

CONCLUSIONS

We observed significant improvements in several measures of exposure to ART and virologic status, including declines in HIV drug resistance, in this large long-running community-recruited cohort of HIV-seropositive illicit drug users during a community-wide ART expansion intervention. Our findings support continued efforts to scale up ART coverage among HIV-positive PWUD.

Exposure to MIV-150 from a high-dose intravaginal ring results in limited emergence of drug resistance mutations in SHIV-RT infected rhesus macaques

When microbicides used for HIV prevention contain antiretroviral drugs, there is concern for the potential emergence of drug-resistant HIV following use in infected individuals who are either unaware of their HIV infection status or who are aware but still choose to use the microbicide. Resistant virus could ultimately impact their responsiveness to treatment and/or result in subsequent transmission of drug-resistant virus. We tested whether drug resistance mutations (DRMs) would emerge in macaques infected with simian immunodeficiency virus expressing HIV reverse transcriptase (SHIV-RT) after sustained exposure to the potent non-nucleoside reverse transcriptase inhibitor (NNRTI) MIV-150 delivered via an intravaginal ring (IVR). We first treated 4 SHIV-RT-infected animals with daily intramuscular injections of MIV-150 over two 21 day (d) intervals separated by a 7 d drug hiatus. In all 4 animals, NNRTI DRMs (single and combinations) were detected within 14 d and expanded in proportion and diversity with time. Knowing that we could detect in vivo emergence of NNRTI DRMs in response to MIV-150, we then tested whether a high-dose MIV-150 IVR (loaded with >10 times the amount being used in a combination microbicide IVR in development) would select for resistance in 6 infected animals, modeling use of this prevention method by an HIV-infected woman. We previously demonstrated that this MIV-150 IVR provides significant protection against vaginal SHIV-RT challenge. Wearing the MIV-150 IVR for 56 d led to only 2 single DRMs in 2 of 6 animals (430 RT sequences analyzed total, 0.46%) from plasma and lymph nodes despite MIV-150 persisting in the plasma, vaginal fluids, and genital tissues. Only wild type virus sequences were detected in the genital tissues. These findings indicate a low probability for the emergence of DRMs after topical MIV-150 exposure and support the advancement of MIV-150-containing microbicides.

Is HIV short-sighted? Insights from a multistrain nested model

An important component of pathogen evolution at the population level is evolution within hosts. Unless evolution within hosts is very slow compared to the duration of infection, the composition of pathogen genotypes within a host is likely to change during the course of an infection, thus altering the composition of genotypes available for transmission as infection progresses. We develop a nested modeling approach that allows us to follow the evolution of pathogens at the epidemiological level by explicitly considering within-host evolutionary dynamics of multiple competing strains and the timing of transmission. We use the framework to investigate the impact of short-sighted within-host evolution on the evolution of virulence of human immunodeficiency virus (HIV), and find that the topology of the within-host adaptive landscape determines how virulence evolves at the epidemiological level. If viral reproduction rates increase significantly during the course of infection, the viral population will evolve a high level of virulence even though this will reduce the transmission potential of the virus. However, if reproduction rates increase more modestly, as data suggest, our model predicts that HIV virulence will be only marginally higher than the level that maximizes the transmission potential of the virus.