Potential Impact of Antiretroviral Therapy on HIV-1 Transmission and AIDS Mortality in Resource-Limited Settings

Evaluating the impact of antiretroviral therapy on HIV transmission

As global efforts proceed to scale up the delivery of antiretroviral therapy (ART) to HIV-infected persons in most urgent need, it is essential to understand the potential impact of treatment expansion on the transmission of new HIV infections. In this study, we use a series of simple mathematical models to explore the direction and magnitude of treatment effects on the sexual transmission of HIV. By defining the circumstances under which ART can reduce the number of new infections transmitted by treated patients, we provide critical benchmarks to aid in prioritizing efforts to maximize the population health impact of treatment and in evaluating the performance of different treatment programmes. We find that, based on the best currently available evidence of possible treatment effects on patient infectiousness, survival and behavior, the potential remains for either positive or negative changes in overall transmission. In relation to the total number of expected secondary infections caused by each infected person, however, these net treatment effects are relatively modest, particularly if treatment is initiated at advanced stages of the disease. This finding implies that treatment alone should not be expected to alter the population-level incidence of new infections dramatically, in the absence of changes in other factors including possible behavioral responses among uninfected persons and among infected persons who are not yet treatment candidates.

Outcomes from monitoring of patients on antiretroviral therapy in resource-limited settings with viral load, CD4 cell count, or clinical observation alone: a computer simulation model

BACKGROUND

In lower-income countries, WHO recommends a population-based approach to antiretroviral treatment with standardised regimens and clinical decision making based on clinical status and, where available CD4 cell count, rather than viral load. Our aim was to study the potential consequences of such monitoring strategies, especially in terms of survival and resistance development.

METHODS

A validated computer simulation model of HIV infection and the effect of antiretroviral therapy was used to compare survival, use of second-line regimens, and development of resistance that result from different strategies-based on viral load, CD4 cell count, or clinical observation alone-for determining when to switch people starting antiretroviral treatment with the WHO-recommended first-line regimen of stavudine, lamivudine, and nevirapine to second-line antiretroviral treatment.

FINDINGS

Over 5 years, the predicted proportion of potential life-years survived was 83% with viral load monitoring (switch when viral load >500 copies per mL), 82% with CD4 cell count monitoring (switch at 50% drop from peak), and 82% with clinical monitoring (switch when two new WHO stage 3 events or a WHO stage 4 event occur). Corresponding values over 20 years were 67%, 64%, and 64%. Findings were robust to variations in model specification in extensive univariable and multivariable sensitivity analyses. Although survival was slightly longer with viral load monitoring, this strategy was not the most cost effective.

INTERPRETATION

For patients on the first-line regimen of stavudine, lamivudine, and nevirapine the benefits of viral load or CD4 cell count monitoring over clinical monitoring alone are modest. Development of cheap and robust versions of these assays is important, but widening access to antiretrovirals-with or without laboratory monitoring-is currently the highest priority.

Potential impact of antiretroviral chemoprophylaxis on HIV-1 transmission in resource-limited settings

Background

The potential impact of pre-exposure chemoprophylaxis (PrEP) on heterosexual transmission of HIV-1 infection in resource-limited settings is uncertain.

Methodology/Principle Findings

A deterministic mathematical model was used to simulate the effects of antiretroviral PrEP on an HIV-1 epidemic in sub-Saharan Africa under different scenarios (optimistic, neutral and pessimistic) both with and without sexual disinhibition. Sensitivity analyses were used to evaluate the effect of uncertainty in input parameters on model output and included calculation of partial rank correlations and standardized rank regressions. In the scenario without sexual disinhibition after PrEP initiation, key parameters influencing infections prevented were effectiveness of PrEP (partial rank correlation coefficient (PRCC) = 0.94), PrEP discontinuation rate (PRCC = −0.94), level of coverage (PRCC = 0.92), and time to achieve target coverage (PRCC = −0.82). In the scenario with sexual disinhibition, PrEP effectiveness and the extent of sexual disinhibition had the greatest impact on prevention. An optimistic scenario of PrEP with 90% effectiveness and 75% coverage of the general population predicted a 74% decline in cumulative HIV-1 infections after 10 years, and a 28.8% decline with PrEP targeted to the highest risk groups (16% of the population). Even with a 100% increase in at-risk behavior from sexual disinhibition, a beneficial effect (23.4%–62.7% decrease in infections) was seen with 90% effective PrEP across a broad range of coverage (25%–75%). Similar disinhibition led to a rise in infections with lower effectiveness of PrEP (≤50%).

Conclusions/Significance

Mathematical modeling supports the potential public health benefit of PrEP. Approximately 2.7 to 3.2 million new HIV-1 infections could be averted in southern sub-Saharan Africa over 10 years by targeting PrEP (having 90% effectiveness) to those at highest behavioral risk and by preventing sexual disinhibition. This benefit could be lost, however, by sexual disinhibition and by high PrEP discontinuation, especially with lower PrEP effectiveness (≤50%).

The requirement for surveillance of HIV drug resistance within antiretroviral rollout in the developing world

PURPOSE OF REVIEW

To describe surveillance measures to inform HIV drug-resistance prevention, as part of the public health approach to antiretroviral therapy in developing countries.

RECENT FINDINGS

Neither HIV drug-resistance transmission nor its emergence in treatment is routinely assessed in the developing world, but routine methods should be part of antiretroviral therapy scale-up. Mathematical modelling and experience in resource-rich countries suggest HIV drug-resistance transmission will increase as antiretroviral therapy coverage increases, but its rise will be limited initially. Transmission surveys should begin in geographic areas in each country where antiretroviral therapy coverage is widespread. Reports from resource-limited countries suggest that antiretroviral therapy programs are as effective as in resource-rich countries, which should limit HIV drug resistance if effectiveness is maintained with antiretroviral therapy expansion. Surveillance of HIV drug resistance emerging in treatment and other factors will support implementation of prevention measures on a population level.

SUMMARY

Standardized surveillance of transmitted and treatment-associated HIV drug resistance is critical to the success of antiretroviral therapy expansion in developing countries. Routine assessment of prescribing practices, availability of and access to appropriate regimens for adults and children, antiretroviral drug supply continuity, and measures to prevent HIV transmission will supply critical information for HIV drug-resistance prevention.

Impact of HIV-1 pol diversity on drug resistance and its clinical implications

PURPOSE OF REVIEW

HIV knowledge is based on subtype B, common in resource-rich settings, whereas globally non-B subtypes predominate. Inter-subtype pol diversity encompasses multiple genotypic differences among HIV variants, the consequence of which is unknown. This review summarizes publications from the past year relevant to the impact of HIV diversity on drug resistance evolution and its potential clinical implications.

RECENT FINDINGS

The benefit of antiretroviral therapy in non-B infected patients is ongoing, though subtype heterogeneity in rates of disease progression is observed. Pol inter-subtype diversity is high, and known subtype B drug resistance mutations occur in non-B subtypes. New mutations and subtype-specific mutation rates are identified, however, unexplained drug susceptibilities are seen, and additional insight is offered on structural pathogenic mechanisms of resistance in non-B subtypes. These differences may affect genotypic interpretation and our ability to apply drug resistance to patient care.

SUMMARY

Current evidence suggests good treatment response and comparable drug resistance evolution in HIV-1 B and non-B infected patients, with increasingly emerging differences. Impact of inter-subtype diversity on drug susceptibility and on evolution of drug resistance should continue to be a major research focus to increase our understanding and ability to improve global patient care.