HIV treatment as prevention: considerations in the design, conduct, and analysis of cluster randomized controlled trials of combination HIV prevention

Framework for converting mechanistic network models to probabilistic models

There are two prominent paradigms for the modelling of networks: in the first, referred to as the mechanistic approach, one specifies a set of domain-specific mechanistic rules that are used to grow or evolve the network over time; in the second, referred to as the probabilistic approach, one describes a model that specifies the likelihood of observing a given network. Mechanistic models (models developed based on the mechanistic approach) are appealing because they capture scientific processes that are believed to be responsible for network generation; however, they do not easily lend themselves to the use of inferential techniques when compared with probabilistic models. We introduce a general framework for converting a mechanistic network model (MNM) to a probabilistic network model (PNM). The proposed framework makes it possible to identify the essential network properties and their joint probability distribution for some MNMs; doing so makes it possible to address questions such as whether two different mechanistic models generate networks with identical distributions of properties, or whether a network property, such as clustering, is over- or under-represented in the networks generated by the model of interest compared with a reference model. The proposed framework is intended to bridge some of the gap that currently exists between the formulation and representation of mechanistic and PNMs. We also highlight limitations of PNMs that need to be addressed in order to close this gap.

A Game Theoretic Analysis of Competition Between Vaccine and Drug Companies during Disease Contraction and Recovery

Background

Infectious diseases such as COVID-19 and HIV/AIDS are behaviorally challenging for persons, vaccine and drug companies, and donors.

Methods

In 3 linked games in which a disease may or may not be contracted, N persons choose risky or safe behavior (game 1). Two vaccine companies (game 2) and 2 drug companies (game 3) choose whether to develop vaccines and drugs. Each person chooses whether to buy 1 vaccine (if no disease contraction) or 1 drug (if disease contraction). A donor subsidizes vaccine and drug developments and purchases. Nature probabilistically chooses disease contraction, recovery versus death with and without each drug, and whether vaccines and drugs are developed successfully. COVID-19 data are used for parameter estimation.

Results

Each person chooses risky behavior if its utility outweighs safe behavior, accounting for nature’s probability of disease contraction which depends on how many are vaccinated. Each person buys a vaccine or drug if the companies produce them and if their utilities (accounting for side effects and virus mutation) outweigh the costs, which may be subsidized by a sponsor.

Discussion

Drug purchases depend on nature’s recovery probability exceeding the probability in the absence of a drug. Each company develops and produces a vaccine or drug if nature’s probability of successful development is high, if sufficiently many persons buy the vaccine or drug at a sales price that sufficiently exceeds the production price, and if the donor sponsors.

Conclusion

Accounting for all players’ interlinked decisions allowing 14 outcomes, which is challenging without a game theoretic analysis, the donor maximizes all persons’ expected utilities at the societal level to adjust how persons’ purchases and the companies’ development and production are subsidized.

Highlights

Evaluating the Prevention Benefit of HCV Treatment: Modeling the SToP-C Treatment as Prevention Study in Prisons

BACKGROUND AND AIMS

Between 2014 and 2019, the SToP-C trial observed a halving in HCV incidence in four Australian prisons following scale-up of direct-acting antiviral (DAA) therapy. However, the contribution of HCV treatment to this decline is unclear because the study did not have a control group. We used modeling to consider this question.

APPROACH AND RESULTS

We parameterized and calibrated a dynamic model of HCV transmission in prisons to data from each SToP-C prison on incarceration dynamics, injecting drug use, HCV prevalence trends among prison entrants, baseline HCV incidence before treatment scale-up, and subsequent HCV treatment scale-up. The model projected the decrease in HCV incidence resulting from increases in HCV treatment and other effects. We assessed whether the model agreed better with observed reductions in HCV incidence overall and by prison if we included HCV treatment scale-up, and its prevention benefits, or did not. The model estimated how much of the observed decrease in HCV incidence was attributable to HCV treatment in prison. The model projected a decrease in HCV incidence of 48.5% (95% uncertainty interval [UI], 41.9-54.1) following treatment scale-up across the four prisons, agreeing with the observed HCV incidence decrease (47.6%; 95% CI, 23.4-64.2) from the SToP-C trial. Without any in-prison HCV treatment, the model indicated that incidence would have decreased by 7.2% (95% UI, -0.3 to 13.6). This suggests that 85.1% (95% UI, 72.6-100.6) of the observed halving in incidence was from HCV treatment scale-up, with the remainder from observed decreases in HCV prevalence among prison entrants (14.9%; 95% UI, -0.6 to 27.4).

CONCLUSIONS

Our results demonstrate the prevention benefits of scaling up HCV treatment in prison settings. Prison-based DAA scale-up should be an important component of HCV elimination strategies.

Bayesian validation framework for dynamic epidemic models

Complex models of infectious diseases are used to understand the transmission dynamics of the disease, project the course of an epidemic, predict the effect of interventions and/or provide information for power calculations of community level intervention studies. However, there have been relatively few opportunities to rigorously evaluate the predictions of such models till now. Indeed, while there is a large literature on calibration (fitting model parameters) and validation (comparing model outputs to data) of complex models based on empirical data, the lack of uniformity in accepted criteria for such procedures for models of infectious diseases has led to simple procedures being prevalent for such steps. However, recently, several community level randomized trials of combination HIV intervention have been planned and/or initiated, and in each case, significant epidemic modeling efforts were conducted during trial planning which were integral to the design of these trials. The existence of these models and the (anticipated) availability of results from the related trials, provide a unique opportunity to evaluate the models and their usefulness in trial design. In this project, we outline a framework for evaluating the predictions of complex epidemiological models and describe experiments that can be used to test their predictions.

PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial

Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially those related to the sexual network within which HIV transmission occurs. An individual-based model, which explicitly models sexual partnerships, is thus often the most natural type of model to choose. In this paper we present PopART-IBM, a computationally efficient individual-based model capable of simulating 50 years of an HIV epidemic in a large, high-prevalence community in under a minute. We show how the model calibrates within a Bayesian inference framework to detailed age- and sex-stratified data from multiple sources on HIV prevalence, awareness of HIV status, ART status, and viral suppression for an HPTN 071 (PopART) study community in Zambia, and present future projections of HIV prevalence and incidence for this community in the absence of trial intervention.

In this paper we present PopART-IBM, an individual-based model used to simulate HIV transmission in communities in high prevalence settings. We show that PopART-IBM can simulate transmission over a span of decades in a large community in less than a minute. This computational efficiency allows us to calibrate the model within an inference framework, and we show an illustrative example of calibration using an adaptive population Monte Carlo Approximate Bayesian Computation algorithm for a community in Zambia that was part of the HPTN-071 (PopART) trial. We compare the detailed model output to real-world data collected during the trial from this community. Finally, we project how the HIV epidemic would have changed over time in this community if no intervention from the trial had occurred.

Decisions of persons, the pharmaceutical industry, and donors in disease contraction and recovery assuming virus mutation

BACKGROUND

The article develops an eight-period game between N persons and a pharmaceutical company. The choices of a donor and Nature are parametric.

METHODS

Persons choose between safe and risky behavior, and whether or not to buy drugs. The pharmaceutical company chooses whether or not to develop drugs. The donor chooses parametrically whether to subsidize drug purchases and drug developments. Nature chooses disease contraction, recovery, death, and virus mutation. The game is solved with backward induction.

RESULTS

The conditions are specified for each of seven outcomes ranging from safe behavior to risky behavior and buying no or one or both drugs. The seven outcomes distribute themselves across three outcomes for the pharmaceutical company, which are to develop no drugs, develop one drug, and develop two drugs if the virus mutates. For these three outcomes the donor's expected utility is specified.

CONCLUSION

HIV/AIDS data is used to present a procedure for parameter estimation. The players' strategic choices are exemplified. The article shows how strategic interaction between persons and a pharmaceutical company, with parametric choices of a donor and Nature, impact whether persons choose risky or safe behavior, whether a pharmaceutical company develops no drugs or one drug, or two drugs if a virus mutates, and the impact of subsidies by a donor.

How 'place' matters for addressing the HIV epidemic: evidence from the HPTN 071 (PopART) cluster-randomised controlled trial in Zambia and South Africa

Background

In a cluster-randomised trial (CRT) of combination HIV prevention (HPTN 071 (PopART)) in 12 Zambian communities and nine South African communities, carried out from 2012 to 2018, the intervention arm A that offered HIV treatment irrespective of CD4 count did not have a significant impact on population level HIV incidence. Intervention arm B, where HIV incidence was reduced by 30%, followed national guidelines that mid trial (2016) changed from starting HIV treatment according to a CD4 threshold of 500 to universal treatment. Using social science data on the 21 communities, we consider how place (community context) might have influenced the primary outcome result.

Methods

A social science component documented longitudinally the context of trial communities. Data were collected through rapid qualitative assessment, interviews, group discussions and observations. There were a total of 1547 participants and 1127 observations. Using these data, literature and a series of qualitative analysis steps, we identified key community characteristics of relevance to HIV and triangulated these with HIV community level incidence.

Results

Two interdependent social factors were relevant to communities’ capability to manage HIV: stability/instability and responsiveness/resistance. Key components of stability were social cohesion; limited social change; a vibrant local economy; better health, education and recreational services; strong institutional presence; established middle-class residents; predictable mobility; and less poverty and crime. Key components of responsiveness were community leadership being open to change, stronger history of HIV initiatives, willingness to take up HIV services, less HIV-related stigma and a supported and enterprising youth population. There was a clear pattern of social factors across arms. Intervention arm A communities were notably more resistant and unstable. Intervention arm B communities were overall more responsive and stable.

Conclusions

In the specific case of the dissonant primary outcome results from the HPTN 071 (PopART) trial, the chance allocation of less stable, less responsive communities to arm A compared to arm B may explain some of the apparently smaller impact of the intervention in arm A. Stability and responsiveness appear to be two key social factors that may be relevant to secular trends in HIV incidence. We advocate for a systematic approach, using these factors as a framework, to community context in CRTs and monitoring HIV prevention efforts.

Trial registration

ClinicalTrials.gov NCT01900977. Registered on July 17, 2013.   

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05198-5.

Assessing the use of surveillance data to estimate the impact of prevention interventions on HIV incidence in cluster-randomized controlled trials

BACKGROUND

In cluster-randomized controlled trials (C-RCTs) of HIV prevention strategies, HIV incidence is expensive to measure directly. Surveillance data on HIV diagnoses or viral suppression could provide cheaper incidence estimates. We used mathematical modelling to evaluate whether these measures can replace HIV incidence measurement in C-RCTs.

METHODS

We used a US HIV transmission model to simulate C-RCTs of expanded antiretroviral therapy(ART), pre-exposure prophylaxis(PrEP) and HIV testing, together or alone. We tested whether modelled reductions in total new HIV diagnoses, diagnoses with acute infection, diagnoses with early infection(CD4 > 500 cells/μl), diagnoses adjusted for testing volume, or the proportion virally non-suppressed, reflected HIV incidence reductions.

RESULTS

Over a two-year trial expanding PrEP alone, modelled reductions in total diagnoses underestimated incidence reductions by a median six percentage points(pp), with acceptable variability(95 % credible interval -14,-2pp). For trials expanding HIV testing alone or alongside ART + PrEP, greater, highly variable bias was seen[-20pp(-128,-1) and -30pp(-134,-16), respectively]. Acceptable levels of bias were only seen over longer trial durations when levels of awareness of HIV-positive status were already high. Expanding ART alone, only acute and early diagnoses reductions reflected incidence reduction well, with some bias[-3pp(-6,-1) and -8pp(-16,-3), respectively]. Early and adjusted diagnoses also reliably reflected incidence when scaling up PrEP alone[bias -5pp(-11,1) and 10pp(3,18), respectively]. For trials expanding testing (alone or with ART + PrEP), bias for all measures explored was too variable for them to replace direct incidence measures, unless using diagnoses when HIV status awareness was already high.

CONCLUSIONS

Surveillance measures based on HIV diagnoses may sometimes be adequate surrogates for HIV incidence reduction in C-RCTs expanding ART or PrEP only, if adjusted for bias. However, all surveillance measures explored failed to approximate HIV incidence reductions for C-RCTs expanding HIV testing, unless levels of awareness of HIV-positive status were already high.

Comparative assessment of five trials of universal HIV testing and treatment in sub-Saharan Africa

Design

Universal voluntary HIV counselling and testing followed by prompt initiation of antiretroviral therapy (ART) for all those diagnosed HIV‐infected (universal test and treat, UTT) is now a global health standard. However, its population‐level impact, feasibility and cost remain unknown. Five community‐based trials have been implemented in sub‐Saharan Africa to measure the effects of various UTT strategies at population level: BCPP/YaTsie in Botswana, MaxART in Swaziland, HPTN 071 (PopART) in South Africa and Zambia, SEARCH in Uganda and Kenya and ANRS 12249 TasP in South Africa. This report describes and contrasts the contexts, research methodologies, intervention packages, themes explored, evolution of study designs and interventions related to each of these five UTT trials.

Methods

We conducted a comparative assessment of the five trials using data extracted from study protocols and collected during baseline studies, with additional input from study investigators. We organized differences and commonalities across the trials in five categories: trial contexts, research designs, intervention packages, trial themes and adaptations.

Results

All performed in the context of generalized HIV epidemics, the trials highly differ in their social, demographic, economic, political and health systems settings. They share the common aim of assessing the impact of UTT on the HIV epidemic but differ in methodological aspects such as study design and eligibility criteria for trial populations. In addition to universal ART initiation, the trials deliver a wide range of biomedical, behavioural and structural interventions as part of their UTT strategies. The five studies explore common issues, including the uptake rates of the trial services and individual health outcomes. All trials have adapted since their initiation to the evolving political, economic and public health contexts, including adopting the successive national recommendations for ART initiation.

Conclusions

We found substantial commonalities but also differences between the five UTT trials in their design, conduct and multidisciplinary outputs. As empirical literature on how UTT may improve efficiency and quality of HIV care at population level is still scarce, this article provides a foundation for more collaborative research on UTT and supports evidence‐based decision making for HIV care in country and internationally.

FROM INDIVIDUAL HEALTH TO COMMUNITY HEALTH: TOWARDS MULTISCALE MODELING OF DIRECTLY TRANSMITTED INFECTIOUS DISEASE SYSTEMS

In this paper, we present a new method for developing a class of nested multiscale models for directly transmitted infectious disease systems that integrates within-host scale and between-host scale using community pathogen load (CPL) as a new public health measure of a community’s level of infectiousness and as an indicator of the effectiveness of health interventions. The approach develops a multiscale modeling science base for directly transmitted infectious disease systems (where the inside-host environment’s biological entities such as cells, tissues, organs, body fluids, whole body are the reservoir of infective pathogen in the community) that is comparable to an existing multiscale modeling science base for environmentally transmitted infectious diseases (where the outside-host geographical environment’s physical entities such as soil, air, formites/contact surfaces, food and water are the reservoir of infective pathogen in the community) where pathogen load in the environment is explicitly incorporated into the model. This is achieved by assuming that infected hosts in the community are homogeneous and unevenly distributed microbial habitats. We illustrate the utility of this multiscale modeling methodology by evaluating the comparative effectiveness of HIV/AIDS preventive and treatment interventions as a case study.

Virological Non-suppression and Its Correlates Among Adolescents and Young People Living with HIV in Southern Malawi

We examined virological non-suppression (VLN) among youth ages 13-24 years receiving HIV treatment in public health facilities in six southern Malawi districts. We also tested three ART adherence measures to determine how well each identified VLN: pill counts, a Likert scale item, and a visual analogue scale. VLN was defined as HIV RNA > 1000 copies/ml. Of the 209 youth, 81 (39%) were virally non-suppressed. Male gender and stigma were independently associated with VLN; social support and self-efficacy were independently protective. Pill count had the highest positive predictive value (66.3%). Using a pill count cut-off of < 80% nonadherence, 36 (17%) of the youth were non-adherent. Of the adherent, 120 (69%) were viral suppressed. Results indicate the need to address HIV-related stigma and to bolster social support and selfefficacy in order to enhance viral suppression. In the absence of viral load testing, pill count appears the most accurate means to assess VLN.

An Innovative Study Design to Assess the Community Effect of Interventions to Mitigate HIV Epidemics Using Transmission-Chain Phylodynamics

Given globalization and other social phenomena, controlling the spread of infectious diseases has become an imperative public health priority. A plethora of interventions that in theory can mitigate the spread of pathogens have been proposed and applied. Evaluating the effectiveness of such interventions is costly and in many circumstances unrealistic. Most important, the community effect (i.e., the ability of the intervention to minimize the spread of the pathogen from people who received the intervention to other community members) can rarely be evaluated. Here we propose a study design that can build and evaluate evidence in support of the community effect of an intervention. The approach exploits molecular evolutionary dynamics of pathogens in order to track new infections as having arisen from either a control or an intervention group. It enables us to evaluate whether an intervention reduces the number and length of new transmission chains in comparison with a control condition, and thus lets us estimate the relative decrease in new infections in the community due to the intervention. We provide as an example one working scenario of a way the approach can be applied with a simulation study and associated power calculations.

Modelling the impact of a national scale-up of interventions on hepatitis C virus transmission among people who inject drugs in Scotland

BACKGROUND AND AIMS

To reduce hepatitis C virus (HCV) transmission among people who inject drugs (PWID), Scottish Government-funded national strategies, launched in 2008, promoted scaling-up opioid substitution therapy (OST) and needle and syringe provision (NSP), with some increases in HCV treatment. We test whether observed decreases in HCV incidence post-2008 can be attributed to this intervention scale-up.

DESIGN

A dynamic HCV transmission model among PWID incorporating intervention scale-up and observed decreases in behavioural risk, calibrated to Scottish HCV prevalence and incidence data for 2008/09.

SETTING

Scotland, UK.

PARTICIPANTS

PWID.

MEASUREMENTS

Model projections from 2008 to 2015 were compared with data to test whether they were consistent with observed decreases in HCV incidence among PWID while incorporating the observed intervention scale-up, and to determine the impact of scaling-up interventions on incidence.

FINDINGS

Without fitting to epidemiological data post-2008/09, the model incorporating observed intervention scale-up agreed with observed decreases in HCV incidence among PWID between 2008 and 2015, suggesting that HCV incidence decreased by 61.3% [95% credibility interval (CrI) = 45.1-75.3%] from 14.2/100 person-years (py) (9.0-20.7) to 5.5/100 py (2.9-9.2). On average, each model fit lay within 84% (10.1/12) of the confidence bounds for the 12 incidence data points against which the model was compared. We estimate that scale-up of interventions (OST + NSP + HCV treatment) and decreases in high-risk behaviour from 2008 to 2015 resulted in a 33.9% (23.8-44.6%) decrease in incidence, with the remainder [27.4% (17.6-37.0%)] explained by historical changes in OST + NSP coverage and risk pre-2008. Projections suggest that scaling-up of all interventions post-2008 averted 1492 (657-2646) infections over 7 years, with 1016 (308-1996), 404 (150-836) and 72 (27-137) due to scale-up of OST + NSP, decreases in high-risk behaviour and HCV treatment, respectively.

CONCLUSIONS

Most of the decline in hepatitis C virus (HCV) incidence in Scotland between 2008 and 2015 appears to be attributable to intervention scale-up (opioid substitution therapy and needle and syringe provision) due to government strategies on HCV and drugs.

Incidence rate estimation, periodic testing and the limitations of the mid-point imputation approach

Background

It is common to use the mid-point between the latest-negative and earliest-positive test dates as the date of the infection event. However, the accuracy of the mid-point method has yet to be systematically quantified for incidence studies once participants start to miss their scheduled test dates.

Methods

We used a simulation-based approach to generate an infectious disease epidemic for an incidence cohort with a high (80-100%), moderate (60-79.9%), low (40-59.9%) and poor (30-39.9%) testing rate. Next, we imputed a mid-point and random-point value between the participant's latest-negative and earliest-positive test dates. We then compared the incidence rate derived from these imputed values with the true incidence rate generated from the simulation model.

Results

The mid-point incidence rate estimates erroneously declined towards the end of the observation period once the testing rate dropped below 80%. This decline was in error of approximately 9%, 27% and 41% for a moderate, low and poor testing rate, respectively. The random-point method did not introduce any systematic bias in the incidence rate estimate, even for testing rates as low as 30%.

Conclusions

The mid-point assumption of the infection date is unjustified and should not be used to calculate the incidence rate once participants start to miss the scheduled test dates. Under these conditions, we show an artefactual decline in the incidence rate towards the end of the observation period. Alternatively, the single random-point method is straightforward to implement and produces estimates very close to the true incidence rate.

Mathematical models used to inform study design or surveillance systems in infectious diseases: a systematic review

BACKGROUND

Mathematical models offer the possibility to investigate the infectious disease dynamics over time and may help in informing design of studies. A systematic review was performed in order to determine to what extent mathematical models have been incorporated into the process of planning studies and hence inform study design for infectious diseases transmitted between humans and/or animals.

METHODS

We searched Ovid Medline and two trial registry platforms (Cochrane, WHO) using search terms related to infection, mathematical model, and study design from the earliest dates to October 2016. Eligible publications and registered trials included mathematical models (compartmental, individual-based, or Markov) which were described and used to inform the design of infectious disease studies. We extracted information about the investigated infection, population, model characteristics, and study design.

RESULTS

We identified 28 unique publications but no registered trials. Focusing on compartmental and individual-based models we found 12 observational/surveillance studies and 11 clinical trials. Infections studied were equally animal and human infectious diseases for the observational/surveillance studies, while all but one between humans for clinical trials. The mathematical models were used to inform, amongst other things, the required sample size (n = 16), the statistical power (n = 9), the frequency at which samples should be taken (n = 6), and from whom (n = 6).

CONCLUSIONS

Despite the fact that mathematical models have been advocated to be used at the planning stage of studies or surveillance systems, they are used scarcely. With only one exception, the publications described theoretical studies, hence, not being utilised in real studies.

Policy makers, the international community and the population in the prevention and treatment of diseases: case study on HIV/AIDS

A four-period game is developed between a policy maker, the international community, and the population. This research supplements, through implementing strategic interaction, earlier research analyzing "one player at a time". The first two players distribute funds between preventing and treating diseases. The population reacts by degree of risky behavior which may cause no disease, disease contraction, recovery, sickness/death. More funds to prevention implies less disease contraction but higher death rate given disease contraction. The cost effectiveness of treatment relative to prevention, country specific conditions, and how the international community converts funds compared with the policy maker in a country, are illustrated. We determine which factors impact funding, e.g. large probabilities of disease contraction, and death given contraction, and if the recovery utility and utility of remaining sick or dying are far below the no disease utility. We also delineate how the policy maker and international community may free ride on each other's contributions. The model is tested against empirical data for 43 African countries. The results show consistency between the theoretical model and empirical estimates. The paper argues for the need to create commitment mechanisms to ensure that free riding by both countries and the international community is avoided.

Inference on network statistics by restricting to the network space: applications to sexual history data

Analysis of sexual history data intended to describe sexual networks presents many challenges arising from the fact that most surveys collect information on only a very small fraction of the population of interest. In addition, partners are rarely identified and responses are subject to reporting biases. Typically, each network statistic of interest, such as mean number of sexual partners for men or women, is estimated independently of other network statistics. There is, however, a complex relationship among networks statistics; and knowledge of these relationships can aid in addressing concerns mentioned earlier. We develop a novel method that constrains a posterior predictive distribution of a collection of network statistics in order to leverage the relationships among network statistics in making inference about network properties of interest. The method ensures that inference on network properties is compatible with an actual network. Through extensive simulation studies, we also demonstrate that use of this method can improve estimates in settings where there is uncertainty that arises both from sampling and from systematic reporting bias compared with currently available approaches to estimation. To illustrate the method, we apply it to estimate network statistics using data from the Chicago Health and Social Life Survey. Copyright © 2017 John Wiley & Sons, Ltd.

Displacement of sexual partnerships in trials of sexual behavior interventions: A model-based assessment of consequences

We investigated the impact of the displacement of sexual activity from adherent recipients of an intervention to others within or outside a trial population on the results from hypothetical trials of different sexual behavior interventions. A short-term model of HIV-prevention interventions that lead to female rejection of male partnership requests showed the impact of displacement expected at the start of a trial. An agent-based model, with sexual mixing and other South African specific demographics, evaluated consequences of displacement for sexual behavior interventions targeting young females in South Africa. This model measured the cumulative incidence among adherent, non-adherent, control and non-enrolled females in a hypothetical trial of HIV prevention. When males made more than one attempt to seek a partnership, interventions reduced short-term HIV infection risk among adherent females, but increased it among non-adherent females as well as controls, non-enrolled (females eligible for the trial but not chosen to participate) and ineligible females (females that did not qualify for the trial due to age). The impact of displacement depends on the intervention and the adherence. In both models, the risk to individuals who are not members of the adherent intervention group will increase with displacement leading to a biased calculation for the effect estimates for the trial. Likewise, intent-to-treat effect estimates become nonlinear functions of the proportion adherent.

Intra-Cluster Correlation Estimates for HIV-related Outcomes from Care and Treatment Clinics in Dar es Salaam, Tanzania

Introduction

Researchers planning cluster-randomized controlled trials (cRCTs) require estimates of the intra-cluster correlation coefficient (ICC) from previous studies for sample size calculations. This paper fills a persistent gap in the literature by providing estimates of ICCs for many key HIV-related clinical outcomes.

Methods

Data from HIV-positive patients from 47 HIV care and treatment clinics in Dar es Salaam, Tanzania were used to calculate ICCs by site of enrollment or site of ART initiation for various clinical outcomes using cross-sectional and longitudinal data. ICCs were estimated using linear mixed models where either clinic of enrollment or clinic of ART initiation served as the random effect.

Results

ICCs ranged from 0 to 0.0706 (95% CI: 0.0447, 0.1098). For most outcomes, the ICCs were large enough to meaningfully affect sample size calculations. For binary outcomes, the ICCs for event prevalence at baseline tended to be larger than the ICCs for later cumulative incidences. For continuous outcomes, the ICCs for baseline values tended to be larger than the ICCs for the change in values from baseline.

Conclusion

The ICCs for HIV-related outcomes cannot be ignored when calculating sample sizes for future cluster-randomized trials. The differences between ICCs calculated from baseline data alone and ICCs calculated using longitudinal data demonstrate the importance of selecting an ICC that reflects a study's intended design and duration for sample size calculations. While not generalizable to all contexts, these estimates provide guidance for future researchers seeking to design adequately powered cRCTs in Sub-Saharan African HIV treatment and care clinics.

Antiretroviral Therapy for the Prevention of HIV-1 Transmission

BACKGROUND

An interim analysis of data from the HIV Prevention Trials Network (HPTN) 052 trial showed that antiretroviral therapy (ART) prevented more than 96% of genetically linked infections caused by human immunodeficiency virus type 1 (HIV-1) in serodiscordant couples. ART was then offered to all patients with HIV-1 infection (index participants). The study included more than 5 years of follow-up to assess the durability of such therapy for the prevention of HIV-1 transmission.

METHODS

We randomly assigned 1763 index participants to receive either early or delayed ART. In the early-ART group, 886 participants started therapy at enrollment (CD4+ count, 350 to 550 cells per cubic millimeter). In the delayed-ART group, 877 participants started therapy after two consecutive CD4+ counts fell below 250 cells per cubic millimeter or if an illness indicative of the acquired immunodeficiency syndrome (i.e., an AIDS-defining illness) developed. The primary study end point was the diagnosis of genetically linked HIV-1 infection in the previously HIV-1-negative partner in an intention-to-treat analysis.

RESULTS

Index participants were followed for 10,031 person-years; partners were followed for 8509 person-years. Among partners, 78 HIV-1 infections were observed during the trial (annual incidence, 0.9%; 95% confidence interval [CI], 0.7 to 1.1). Viral-linkage status was determined for 72 (92%) of the partner infections. Of these infections, 46 were linked (3 in the early-ART group and 43 in the delayed-ART group; incidence, 0.5%; 95% CI, 0.4 to 0.7) and 26 were unlinked (14 in the early-ART group and 12 in the delayed-ART group; incidence, 0.3%; 95% CI, 0.2 to 0.4). Early ART was associated with a 93% lower risk of linked partner infection than was delayed ART (hazard ratio, 0.07; 95% CI, 0.02 to 0.22). No linked infections were observed when HIV-1 infection was stably suppressed by ART in the index participant.

CONCLUSIONS

The early initiation of ART led to a sustained decrease in genetically linked HIV-1 infections in sexual partners. (Funded by the National Institute of Allergy and Infectious Diseases; HPTN 052 ClinicalTrials.gov number, NCT00074581 .).

Can the Heterosexual HIV Epidemic be Eliminated in South Africa Using Combination Prevention? A Modeling Analysis

Little is known about how combining efficacious interventions for human immunodeficiency virus (HIV) prevention could lead to HIV elimination. We used an agent-based simulation model, the HIV calibrated dynamic model, to assess the potential for HIV elimination in South Africa. We examined several scenarios (from continuation of the current status quo to perfect achievement of targets) with differing combinations of male condom use, adult male circumcision, HIV testing, and early antiretroviral therapy (ART). We varied numerous parameters, including the proportion of adult males circumcised, the frequency of condom use during sex acts, acceptance of HIV testing, linkage to health care, criteria for ART initiation, ART viral suppression rates, and loss to follow-up. Maintaining current levels of combination prevention would lead to increasing HIV incidence and prevalence in South Africa, while the perfect combination scenario was projected to eliminate HIV on a 50-year time scale from 2013 to 2063. Perfecting testing and treatment, without changing condom use or circumcision rates, resulted in an 89% reduction in HIV incidence but not elimination. Universal adult male circumcision alone resulted in a 21% incidence reduction within 20 years. Substantial decreases in HIV incidence are possible from sufficient uptake of both primary prevention and ART, but with continuation of the status quo, HIV elimination in South Africa is unlikely within a 50-year time scale.

Effectiveness of combination packages for HIV-1 prevention in sub-Saharan Africa depends on partnership network structure: a mathematical modelling study

OBJECTIVES

Combination packages for HIV prevention can leverage the effectiveness of biomedical and behavioural elements to lower disease incidence with realistic targets for individual and population risk reduction. We investigated how sexual network structures can maximise the effectiveness of a package targeting sexually active adults in sub-Saharan Africa (SSA) with intervention components for medical male circumcision (MMC) and sexual partnership concurrency (having >1 ongoing partner).

METHODS

Network-based mathematical models of HIV type 1 (HIV-1) transmission dynamics among heterosexual couples were used to explore how changes to MMC alone and in combination with changes to concurrency impacted endemic HIV-1 prevalence and incidence. Starting from a base model parameterised from empirical data from West Africa, we simulated the prevalence of circumcision from 10% to 90% and concurrency was modelled at four discrete levels corresponding to values observed across SSA.

RESULTS

MMC and concurrency could contribute to the empirical variation in HIV-1 disease prevalence across SSA. Small reductions in concurrency resulted in large declines in HIV-1 prevalence. Scaling up circumcision in low-concurrency settings yields a greater relative benefit, but the absolute number of infections averted depends on both the circumcision coverage and baseline incidence. Epidemic extinction with this package will require substantial scale-up of MMC in low-concurrency settings.

CONCLUSIONS

Dynamic sexual network structure should be considered in the design and targeting of MMC within combination HIV-1 prevention packages. Realistic levels of coverage for these packages within southern Africa could lead to a reduction of incidence to the low levels observed in western Africa, and possibly, epidemic extinction.

CD4+ cell dynamics in untreated HIV-1 infection: overall rates, and effects of age, viral load, sex and calendar time

Background:

CD4⁺ cell count is a key measure of HIV disease progression, and the basis of successive international guidelines for treatment initiation. CD4⁺ cell dynamics are used in mathematical and econometric models for evaluating public health need and interventions. Here, we estimate rates of CD4⁺ decline, stratified by relevant covariates, in a form that is clinically transparent and can be directly used in such models.

Methods:

We analyse the AIDS Therapy Evaluation in the Netherlands cohort, including individuals with date of seroconversion estimated to be within 1 year and with intensive clinical follow-up prior to treatment initiation. Owing to the fact that CD4⁺ cell counts are intrinsically noisy, we separate the analysis into long-term trends of smoothed CD4⁺ cell counts and an observation model relating actual CD4⁺ measurements to the underlying smoothed counts. We use a monotonic spline smoothing model to describe the decline of smoothed CD4⁺ cell counts through categories CD4⁺ above 500, 350–500, 200–350 and 200 cells/μl or less. We estimate the proportion of individuals starting in each category after seroconversion and the average time spent in each category. We examine individual-level cofactors which influence these parameters.

Results:

Among untreated individuals, the time spent in each compartment was 3.32, 2.70, 5.50 and 5.06 years. Only 76% started in the CD4⁺ cell count above 500 cells/μl compartment after seroconversion. Set-point viral load (SPVL) was an important factor: individuals with at least 5 log₁₀ copies/ml took 5.37 years to reach CD4⁺ cell count less than 200 cells/μl compared with 15.76 years for SPVL less than 4 log₁₀ copies/ml.

Conclusion:

Many individuals already have CD4⁺ cell count below 500 cells/μl after seroconversion. SPVL strongly influences the rate of CD4⁺ decline. Treatment guidelines should consider measuring SPVL, whereas mathematical models should incorporate SPVL stratification.

Advances in HIV prevention for serodiscordant couples

Serodiscordant couples play an important role in maintaining the global HIV epidemic. This review summarizes biobehavioral and biomedical HIV prevention options for serodiscordant couples focusing on advances in 2013 and 2014, including World Health Organization guidelines and best evidence for couples counseling, couple-based interventions, and the use of antiviral agents for prevention. In the past few years, marked advances have been made in HIV prevention for serodiscordant couples and numerous ongoing studies are continuously expanding HIV prevention tools, especially in the area of pre-exposure prophylaxis. Uptake and adherence to antiviral therapy remains a key challenge. Additional research is needed to develop evidence-based interventions for couples, and especially for male-male couples. Randomized trials have demonstrated the prevention benefits of antiretroviral-based approaches among serodiscordant couples; however, residual transmission observed in recognized serodiscordant couples represents an important and resolvable challenge in HIV prevention.

Role of oral pre-exposure prophylaxis (PrEP) in current and future HIV prevention strategies

Treatment as prevention is expected to have a major role in reducing HIV incidence, but other prevention interventions will also be required to bring the epidemic under control, particularly among key populations. One or more forms of pre-exposure prophylaxis (PrEP) will likely play a critical role. Oral PrEP with emtricitabine-tenofovir (Truvada®) is currently available in the US and some other countries, but uptake has been slow. We review the concerns that have contributed to this slow uptake and discuss current and future research in this critical area of HIV prevention research.

Sample size considerations using mathematical models: an example with Chlamydia trachomatis infection and its sequelae pelvic inflammatory disease

Background

The success of an intervention to prevent the complications of an infection is influenced by the natural history of the infection. Assumptions about the temporal relationship between infection and the development of sequelae can affect the predicted effect size of an intervention and the sample size calculation. This study investigates how a mathematical model can be used to inform sample size calculations for a randomised controlled trial (RCT) using the example of Chlamydia trachomatis infection and pelvic inflammatory disease (PID).

Methods

We used a compartmental model to imitate the structure of a published RCT. We considered three different processes for the timing of PID development, in relation to the initial C. trachomatis infection: immediate, constant throughout, or at the end of the infectious period. For each process we assumed that, of all women infected, the same fraction would develop PID in the absence of an intervention. We examined two sets of assumptions used to calculate the sample size in a published RCT that investigated the effect of chlamydia screening on PID incidence. We also investigated the influence of the natural history parameters of chlamydia on the required sample size.

Results

The assumed event rates and effect sizes used for the sample size calculation implicitly determined the temporal relationship between chlamydia infection and PID in the model. Even small changes in the assumed PID incidence and relative risk (RR) led to considerable differences in the hypothesised mechanism of PID development. The RR and the sample size needed per group also depend on the natural history parameters of chlamydia.

Conclusions

Mathematical modelling helps to understand the temporal relationship between an infection and its sequelae and can show how uncertainties about natural history parameters affect sample size calculations when planning a RCT.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-015-0953-5) contains supplementary material, which is available to authorized users.

Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence

Antiretroviral therapy (ART) reduces the infectiousness of HIV-infected persons, but only after testing, linkage to care, and successful viral suppression. Thus, a large proportion of HIV transmission during a period of high infectiousness in the first few months after infection ("early transmission") is perceived as a threat to the impact of HIV "treatment-as-prevention" strategies. We created a mathematical model of a heterosexual HIV epidemic to investigate how the proportion of early transmission affects the impact of ART on reducing HIV incidence. The model includes stages of HIV infection, flexible sexual mixing, and changes in risk behavior over the epidemic. The model was calibrated to HIV prevalence data from South Africa using a Bayesian framework. Immediately after ART was introduced, more early transmission was associated with a smaller reduction in HIV incidence rate--consistent with the concern that a large amount of early transmission reduces the impact of treatment on incidence. However, the proportion of early transmission was not strongly related to the long-term reduction in incidence. This was because more early transmission resulted in a shorter generation time, in which case lower values for the basic reproductive number (R0) are consistent with observed epidemic growth, and R0 was negatively correlated with long-term intervention impact. The fraction of early transmission depends on biological factors, behavioral patterns, and epidemic stage and alone does not predict long-term intervention impacts. However, early transmission may be an important determinant in the outcome of short-term trials and evaluation of programs.

Phylogenetic studies of transmission dynamics in generalized HIV epidemics: an essential tool where the burden is greatest?

Efficient and effective HIV prevention measures for generalized epidemics in sub-Saharan Africa have not yet been validated at the population level. Design and impact evaluation of such measures requires fine-scale understanding of local HIV transmission dynamics. The novel tools of HIV phylogenetics and molecular epidemiology may elucidate these transmission dynamics. Such methods have been incorporated into studies of concentrated HIV epidemics to identify proximate and determinant traits associated with ongoing transmission. However, applying similar phylogenetic analyses to generalized epidemics, including the design and evaluation of prevention trials, presents additional challenges. Here we review the scope of these methods and present examples of their use in concentrated epidemics in the context of prevention. Next, we describe the current uses for phylogenetics in generalized epidemics and discuss their promise for elucidating transmission patterns and informing prevention trials. Finally, we review logistic and technical challenges inherent to large-scale molecular epidemiological studies of generalized epidemics and suggest potential solutions.

Modelling in concentrated epidemics: informing epidemic trajectories and assessing prevention approaches

PURPOSE OF THE REVIEW

This review summarizes recent mathematical modelling studies conducted among key populations including MSM, people who inject drugs (PWID), and female sex workers (FSWs) in low prevalence settings used as a marker of concentrated epidemics.

RECENT FINDINGS

Most recent studies focused on MSM, Asian settings or high-income countries, studied the transmission dynamics or modelled pre-exposure prophylaxis, treatment as prevention or behavioural interventions specific to each key population (e.g., needle exchange programme or use of low-dead space syringes for PWID). Biological interventions were deemed effective and cost-effective, though still expensive, and often deemed unlikely to result in HIV elimination if used alone. Targeting high-risk individuals even within key populations improved efficiency. Some studies made innovative use of models to formally evaluate HIV prevention programmes, to interpret genetic or co-infection data, and to address methodological questions and validate epidemiological tools.

CONCLUSION

More work is needed to optimize combination prevention focusing on key populations in different settings. The gaps identified include the limited number of studies modelling drug resistance, structural interventions, treatment as prevention among FSWs, and estimating the contribution of key populations to overall transmission in different settings.

A role for health communication in the continuum of HIV care, treatment, and prevention

: Health communication has played a pivotal role in HIV prevention efforts since the beginning of the epidemic. The recent paradigm of combination prevention, which integrates behavioral, biomedical, and structural interventions, offers new opportunities for employing health communication approaches across the entire continuum of care. We describe key areas where health communication can significantly enhance HIV treatment, care, and prevention, presenting evidence from interventions that include health communication components. These interventions rely primarily on interpersonal communication, especially individual and group counseling, both within and beyond clinical settings to enhance the uptake of and continued engagement in care. Many successful interventions mobilize a network of trained community supporters or accompagnateurs, who provide education, counseling, psychosocial support, treatment supervision, and other pragmatic assistance across the care continuum. Community treatment supporters reduce the burden on overworked medical providers, engage a wider segment of the community, and offer a more sustainable model for supporting people living with HIV. Additionally, mobile technologies are increasingly seen as promising avenues for ongoing cost-effective communication throughout the treatment cascade. A broader range of communication approaches, traditionally employed in HIV prevention efforts, that address community and sociopolitical levels through mass media, school- or workplace-based education, and entertainment modalities may be useful to interventions seeking to address the full care continuum. Future interventions would benefit from development of a framework that maps appropriate communication theories and approaches onto each step of the care continuum to evaluate the efficacy of communication components on treatment outcomes.

The impact of the 2013 WHO antiretroviral therapy guidelines on the feasibility of HIV population prevention trials

BACKGROUND

Several cluster-randomized HIV prevention trials aim to demonstrate the population-level preventive impact of antiretroviral therapy (ART). 2013 World Health Organization (WHO) guidelines raising the ART initiation threshold to CD4 <500/µL could attenuate these trials' effect size by increasing ART usage in control clusters.

METHODS

We used a computational model to simulate strategies from a hypothetical cluster-randomized HIV prevention trial. The primary model outcome was the relative reduction in 24-month HIV incidence between control (ART offered with CD4 below threshold) and intervention (ART offered to all) strategies. We assessed this incidence reduction using the revised (CD4 <500/µL) and prior (CD4 <350/µL) control ART initiation thresholds. Additionally, we evaluated changes to trial characteristics that could bolster the incidence reduction.

RESULTS

With a control ART initiation threshold of CD4 <350/µL, 24-month HIV incidence under control and intervention strategies was 2.46/100 person-years (PY) and 1.96/100 PY, a 21% reduction. Raising the threshold to CD4 <500/µL decreased the incidence reduction by more than one-third, to 12%. Using this higher threshold, moving to a 36-month horizon (vs 24-month), yearly control-strategy HIV screening (vs bian-nual), and intervention-strategy screening every 2 months (vs biannual), resulted in a 31% incidence reduction that was similar to effect size projections for ongoing trials. Alternate assumptions regarding cross-cluster contamination had the greatest influence on the incidence reduction.

CONCLUSIONS

Implementing the 2013 WHO HIV treatment threshold could substantially diminish the incidence reduction in HIV population prevention trials. Alternative HIV testing frequencies and trial horizons can bolster this incidence reduction, but they could be logistically and ethically challenging. The feasibility of HIV population prevention trials should be reassessed as the implementation of treatment guidelines evolves.

Biomedical prevention: state of the science

Preexposure prophylaxis (PrEP) and treatment as prevention (TasP) involve the use of antiretroviral (ARV) drugs by human immunodeficiency virus (HIV)-negative and -positive individuals to reduce HIV acquisition and transmission, respectively. Clinical science has delivered a consistently high effect size for TasP and a range from 0%-73% reduction in incidence across placebo-controlled PrEP trials. However, the quality of evidence for PrEP compares favorably with evidence for postexposure prophylaxis (PEP). It is clear from treatment programs and PrEP trials that daily adherence presents challenges to a large proportion of the population. Although there are factors associated with inconsistent use (ie, younger age), they do not assist clinicians at the point of care. There are additional provider concerns about PrEP (covering cost of drug and delivery, undermining condom promotion, and facilitating resistant strains) that have delayed widespread acceptance. These issues need to be addressed in order to realize the full public health potential of antiretrovirals.

Sample size considerations in the design of cluster randomized trials of combination HIV prevention

Background Cluster randomized trials have been utilized to evaluate the effectiveness of HIV prevention strategies on reducing incidence. Design of such studies must take into account possible correlation of outcomes within randomized units. Purpose To discuss power and sample size considerations for cluster randomized trials of combination HIV prevention, using an HIV prevention study in Botswana as an illustration. Methods We introduce a new agent-based model to simulate the community-level impact of a combination prevention strategy and investigate how correlation structure within a community affects the coefficient of variation - an essential parameter in designing a cluster randomized trial. Results We construct collections of sexual networks and then propagate HIV on them to simulate the disease epidemic. Increasing level of sexual mixing between intervention and standard-of-care (SOC) communities reduces the difference in cumulative incidence in the two sets of communities. Fifteen clusters per arm and 500 incidence cohort members per community provide 95% power to detect the projected difference in cumulative HIV incidence between SOC and intervention communities (3.93% and 2.34%) at the end of the third study year, using a coefficient of variation 0.25. Although available formulas for calculating sample size for cluster randomized trials can be derived by assuming an exchangeable correlation structure within clusters, we show that deviations from this assumption do not generally affect the validity of such formulas. Limitations We construct sexual networks based on data from Likoma Island, Malawi, and base disease progression on longitudinal estimates from an incidence cohort in Botswana and in Durban as well as a household survey in Mochudi, Botswana. Network data from Botswana and larger sample sizes to estimate rates of disease progression would be useful in assessing the robustness of our model results. Conclusion Epidemic modeling plays a critical role in planning and evaluating interventions for prevention. Simulation studies allow us to take into consideration available information on sexual network characteristics, such as mixing within and between communities as well as coverage levels for different prevention modalities in the combination prevention package.

Sampling Networks from Their Posterior Predictive Distribution

Recent research indicates that knowledge about social networks can be leveraged to increase efficiency of interventions (Valente, 2012). However, in many settings, there exists considerable uncertainty regarding the structure of the network. This can render the estimation of potential effects of network-based interventions difficult, as providing appropriate guidance to select interventions often requires a representation of the whole network. In order to make use of the network property estimates to simulate the effect of interventions, it may be beneficial to sample networks from an estimated posterior predictive distribution, which can be specified using a wide range of models. Sampling networks from a posterior predictive distribution of network properties ensures that the uncertainty about network property parameters is adequately captured. The tendency for relationships among network properties to exhibit sharp thresholds has important implications for understanding global network topology in the presence of uncertainty; therefore, it is essential to account for uncertainty. We provide detail needed to sample networks for the specific network properties of degree distribution, mixing frequency, and clustering. Our methods to generate networks are demonstrated using simulated data and data from the National Longitudinal Study of Adolescent Health.

Toward an endgame: finding and engaging people unaware of their HIV-1 infection in treatment and prevention

Epidemic modeling suggests that a major scale-up in HIV treatment could have a dramatic impact on HIV incidence. This has led both researchers and policymakers to set a goal of an "AIDS-Free Generation." One of the greatest obstacles to achieving this objective is the number of people with undiagnosed HIV infection. Despite recent innovations, new research strategies are needed to identify, engage, and successfully treat people who are unaware of their infection.

HPTN 071 (PopART): a cluster-randomized trial of the population impact of an HIV combination prevention intervention including universal testing and treatment: mathematical model

Background

The HPTN 052 trial confirmed that antiretroviral therapy (ART) can nearly eliminate HIV transmission from successfully treated HIV-infected individuals within couples. Here, we present the mathematical modeling used to inform the design and monitoring of a new trial aiming to test whether widespread provision of ART is feasible and can substantially reduce population-level HIV incidence.

Methods and Findings

The HPTN 071 (PopART) trial is a three-arm cluster-randomized trial of 21 large population clusters in Zambia and South Africa, starting in 2013. A combination prevention package including home-based voluntary testing and counseling, and ART for HIV positive individuals, will be delivered in arms A and B, with ART offered universally in arm A and according to national guidelines in arm B. Arm C will be the control arm. The primary endpoint is the cumulative three-year HIV incidence.

We developed a mathematical model of heterosexual HIV transmission, informed by recent data on HIV-1 natural history. We focused on realistically modeling the intervention package. Parameters were calibrated to data previously collected in these communities and national surveillance data.

We predict that, if targets are reached, HIV incidence over three years will drop by >60% in arm A and >25% in arm B, relative to arm C. The considerable uncertainty in the predicted reduction in incidence justifies the need for a trial. The main drivers of this uncertainty are possible community-level behavioral changes associated with the intervention, uptake of testing and treatment, as well as ART retention and adherence.

Conclusions

The HPTN 071 (PopART) trial intervention could reduce HIV population-level incidence by >60% over three years. This intervention could serve as a paradigm for national or supra-national implementation. Our analysis highlights the role mathematical modeling can play in trial development and monitoring, and more widely in evaluating the impact of treatment as prevention.

Linkage of viral sequences among HIV-infected village residents in Botswana: estimation of linkage rates in the presence of missing data

Linkage analysis is useful in investigating disease transmission dynamics and the effect of interventions on them, but estimates of probabilities of linkage between infected people from observed data can be biased downward when missingness is informative. We investigate variation in the rates at which subjects' viral genotypes link across groups defined by viral load (low/high) and antiretroviral treatment (ART) status using blood samples from household surveys in the Northeast sector of Mochudi, Botswana. The probability of obtaining a sequence from a sample varies with viral load; samples with low viral load are harder to amplify. Pairwise genetic distances were estimated from aligned nucleotide sequences of HIV-1C env gp120. It is first shown that the probability that randomly selected sequences are linked can be estimated consistently from observed data. This is then used to develop estimates of the probability that a sequence from one group links to at least one sequence from another group under the assumption of independence across pairs. Furthermore, a resampling approach is developed that accounts for the presence of correlation across pairs, with diagnostics for assessing the reliability of the method. Sequences were obtained for 65% of subjects with high viral load (HVL, n = 117), 54% of subjects with low viral load but not on ART (LVL, n = 180), and 45% of subjects on ART (ART, n = 126). The probability of linkage between two individuals is highest if both have HVL, and lowest if one has LVL and the other has LVL or is on ART. Linkage across groups is high for HVL and lower for LVL and ART. Adjustment for missing data increases the group-wise linkage rates by 40–100%, and changes the relative rates between groups. Bias in inferences regarding HIV viral linkage that arise from differential ability to genotype samples can be reduced by appropriate methods for accommodating missing data.

The analysis of viral genomes has great potential for investigating transmission of disease, including the identification of risk factors and transmission clusters, and can thereby aid in targeting interventions. To make use of genetic data in this way, it is necessary to make inferences about population-level patterns of viral linkage. As with any rigorous statistical inference from sampled data to a population, it is important to consider the effect of the sampling strategy and the occurrence of missing data on the final inferences made. In this paper we highlight the effects of missing data on the resulting estimates of population level linkage rates and develop methods for adjusting for the presence of missing data. As an example, we consider comparing the rates of linkage of HIV sequences from subjects with high viral load, low viral load, or on antiretroviral treatment, and show that comparative inferences are compromised when adjustment is not made for missing sequences and bias in inferences can be reduced with proper adjustment.

Challenges and potential barriers to the uptake of antiretroviral-based prevention in Asia and the Pacific region

Evidence has emerged over the past few years on the effectiveness of antiretroviral-based prevention technologies to prevent (i) HIV transmission while decreasing morbidity and mortality in HIV-infected persons, and (ii) HIV acquisition in HIV-uninfected individuals through pre-exposure prophylaxis (PrEP). Only few of the planned studies on treatment as prevention (TasP) are conducted in Asia. TasP might be more feasible and effective in concentrated rather than in generalised epidemics, as resources for HIV testing and antiretroviral treatment could focus on confined and much smaller populations than in the generalised epidemics observed in sub-Saharan Africa. Several countries such as Cambodia, China, Thailand and Vietnam, are now paving the way to success. Similar challenges arise for both TasP and PrEP. However, the operational issues for PrEP are amplified by the need for frequent retesting and ensuring adherence. This paper describes challenges for the implementation of antiretroviral-based prevention and makes the case that TasP and PrEP implementation research in Asia is much needed to provide insights into the feasibility of these interventions in populations where firm evidence of ‘real world’ effectiveness is still lacking.

Dropout and re-enrollment: implications for epidemiological projections of treatment programs

OBJECTIVE

EMOD-HIV v0.8 has been used to estimate the potential impact of expanding treatment guidelines to allow earlier initiation of antiretroviral therapy (ART) in sub-Saharan Africa with current or improved treatment coverage. In generating these results, a model must additionally make assumptions about the rates of dropout and re-initiation into ART programs before and after the program change, about which little is known. The objective of this work is to rigorously analyze modeling assumptions and the sensitivity of model results with respect to relevant mechanisms and parameters.

METHODS

We varied key model assumptions pertaining to ART dropout and re-enrollment to analyze their effect on the cost, impact, and cost-effectiveness of expanding treatment guidelines, and of expanding coverage via improved testing and linkage to care. Additionally, we performed a sensitivity analysis of 17 relevant model parameters.

SETTING

South Africa.

RESULTS

Allowing re-initiation of ART irrespective of prior treatment doubled the cost and impact of expanding treatment guidelines, as compared with a scenario in which re-initiation could only be triggered by a health event (AIDS symptoms, diagnosis of a partner, or an antenatal care visit). Increasing the probability of 'voluntary' re-initiation (not triggered by a health event) was the most cost-effective way to improve the treatment program, especially in the short term because it provided immediate benefits to those who would otherwise have delayed re-initiation until the onset of AIDS symptoms. However, the maximum impact of this change was limited compared with expanding coverage through improvements in testing and linkage to care. Beyond improvements in coverage and re-initiation, further gains could be made by improving retention in care. Only with optimal retention in care was expansion of guidelines cost-saving after 20 years due to reductions in transmission. Re-initiation did not reduce transmission sufficiently to make a guideline change cost-effective due to transmission that occurred while patients were away from care. Sensitivity analysis suggested that enormous health benefits could be attained by improving treatment regimens to have higher efficacy at preventing transmission, increasing the proportion of the population with access to improved healthcare, and reducing 'leaks' in the 'cascade of care.' Increasing the proportion of individuals who receive CD4 cell results was particularly cost-effective at baseline levels of coverage, and increasing retention on ART was particularly cost-effective with expanded coverage.

CONCLUSION

This analysis provides a sense of the magnitude of uncertainty in program cost and impact that policy-makers could anticipate in the face of uncertain future programmatic changes. Our findings suggest that increasing re-initiation is the most cost-effective means of initial program improvement, especially in the short term, but that improvements in retention are necessary in order to reap the full transmission-blocking benefits of a test-and-treat program in the long term.

Health benefits, costs, and cost-effectiveness of earlier eligibility for adult antiretroviral therapy and expanded treatment coverage: a combined analysis of 12 mathematical models

BACKGROUND

New WHO guidelines recommend ART initiation for HIV-positive persons with CD4 cell counts ≤500 cells/µL, a higher threshold than was previously recommended. Country decision makers must consider whether to further expand ART eligibility accordingly.

METHODS

We used multiple independent mathematical models in four settings-South Africa, Zambia, India, and Vietnam-to evaluate the potential health impact, costs, and cost-effectiveness of different adult ART eligibility criteria under scenarios of current and expanded treatment coverage, with results projected over 20 years. Analyses considered extending eligibility to include individuals with CD4 ≤500 cells/µL or all HIV-positive adults, compared to the previous recommendation of initiation with CD4 ≤350 cells/µL. We assessed costs from a health system perspective, and calculated the incremental cost per DALY averted ($/DALY) to compare competing strategies. Strategies were considered 'very cost-effective' if the $/DALY was less than the country's per capita gross domestic product (GDP; South Africa: $8040, Zambia: $1425, India: $1489, Vietnam: $1407) and 'cost-effective' if $/DALY was less than three times per capita GDP.

FINDINGS

In South Africa, the cost per DALY averted of extending ART eligibility to CD4 ≤500 cells/µL ranged from $237 to $1691/DALY compared to 2010 guidelines; in Zambia, expanded eligibility ranged from improving health outcomes while reducing costs (i.e. dominating current guidelines) to $749/DALY. Results were similar in scenarios with substantially expanded treatment access and for expanding eligibility to all HIV-positive adults. Expanding treatment coverage in the general population was therefore found to be cost-effective. In India, eligibility for all HIV-positive persons ranged from $131 to $241/DALY and in Vietnam eligibility for CD4 ≤500 cells/µL cost $290/DALY. In concentrated epidemics, expanded access among key populations was also cost-effective.

INTERPRETATION

Earlier ART eligibility is estimated to be very cost-effective in low- and middle-income settings, although these questions should be revisited as further information becomes available. Scaling-up ART should be considered among other high-priority health interventions competing for health budgets.

FUNDING

The Bill and Melinda Gates Foundation and World Health Organization.

Antiretroviral treatment of HIV-1 prevents transmission of HIV-1: where do we go from here?

Antiretroviral drugs that inhibit viral replication were expected to reduce transmission of HIV by lowering the concentration of HIV in the genital tract. In 11 of 13 observational studies, antiretroviral therapy (ART) provided to an HIV-infected index case led to greatly reduced transmission of HIV to a sexual partner. In the HPTN 052 randomised controlled trial, ART used in combination with condoms and counselling reduced HIV transmission by 96·4%. Evidence is growing that wider, earlier initiation of ART could reduce population-level incidence of HIV. However, the full benefits of this strategy will probably need universal access to very early ART and excellent adherence to treatment. Challenges to this approach are substantial. First, not all HIV-infected individuals can be located, especially people with acute and early infection who are most contagious. Second, the ability of ART to prevent HIV transmission in men who have sex with men (MSM) and people who use intravenous drugs has not been shown. Indeed, the stable or increased incidence of HIV in MSM in some communities where widespread use of ART has been established emphasises the concern that not enough is known about treatment as prevention for this crucial population. Third, although US guidelines call for immediate use of ART, such guidelines have not been embraced worldwide. Some experts do not believe that immediate or early ART is justified by present evidence, or that health-care infrastructure for this approach is sufficient. These concerns are very difficult to resolve. Ongoing community-based prospective trials of early ART are likely to help to establish the population-level benefit of ART, and-if successful-to galvanise treatment as prevention.

Assessment of the population-level effectiveness of the Avahan HIV-prevention programme in South India: a preplanned, causal-pathway-based modelling analysis

BACKGROUND

Avahan, the India AIDS initiative of the Bill & Melinda Gates Foundation, was a large-scale, targeted HIV prevention intervention. We aimed to assess its overall effectiveness by estimating the number and proportion of HIV infections averted across Avahan districts, following the causal pathway of the intervention.

METHODS

We created a mathematical model of HIV transmission in high-risk groups and the general population using data from serial cross-sectional surveys (integrated behavioural and biological assessments, IBBAs) within a Bayesian framework, which we used to reproduce HIV prevalence trends in female sex workers and their clients, men who have sex with men, and the general population in 24 South Indian districts over the first 4 years (2004-07 or 2005-08 dependent on the district) and the full 10 years (2004-13) of the Avahan programme. We tested whether these prevalence trends were more consistent with self-reported increases in consistent condom use after the implementation of Avahan or with a counterfactual (assuming consistent condom use increased at slower, pre-Avahan rates) using a Bayes factor, which gave a measure of the strength of evidence for the effectiveness estimates. Using regression analysis, we extrapolated the prevention effect in the districts covered by IBBAs to all 69 Avahan districts.

FINDINGS

In 13 of 24 IBBA districts, modelling suggested medium to strong evidence for the large self-reported increase in consistent condom use since Avahan implementation. In the remaining 11 IBBA districts, the evidence was weaker, with consistent condom use generally already high before Avahan began. Roughly 32700 HIV infections (95% credibility interval 17900-61600) were averted over the first 4 years of the programme in the IBBA districts with moderate to strong evidence. Addition of the districts with weaker evidence increased this total to 62800 (32000-118000) averted infections, and extrapolation suggested that 202000 (98300-407000) infections were averted across all 69 Avahan districts in South India, increasing to 606000 (290000-1 193000) over 10 years. Over the first 4 years of the programme 42% of HIV infections were averted, and over 10 years 57% were averted.

INTERPRETATION

This is the first assessment of Avahan to account for the causal pathway of the intervention, that of changing risk behaviours in female sex workers and high-risk men who have sex with men to avert HIV infections in these groups and the general population. The findings suggest that substantial preventive effects can be achieved by targeted behavioural HIV prevention initiatives.

FUNDING

Bill & Melinda Gates Foundation.

Combination prevention: new hope for stopping the epidemic

HIV research has identified approaches that can be combined to be more effective in transmission reduction than any 1 modality alone: delayed adolescent sexual debut, mutual monogamy or sexual partner reduction, correct and consistent condom use, pre-exposure prophylaxis with oral antiretroviral drugs or vaginal microbicides, voluntary medical male circumcision, antiretroviral therapy (ART) for prevention (including prevention of mother to child HIV transmission [PMTCT]), treatment of sexually transmitted infections, use of clean needles for all injections, blood screening prior to donation, a future HIV prime/boost vaccine, and the female condom. The extent to which evidence-based modalities can be combined to prevent substantial HIV transmission is largely unknown, but combination approaches that are truly implementable in field conditions are likely to be far more effective than single interventions alone. Analogous to PMTCT, "treatment as prevention" for adult-to-adult transmission reduction includes expanded HIV testing, linkage to care, antiretroviral coverage, retention in care, adherence to therapy, and management of key co-morbidities such as depression and substance use. With successful viral suppression, persons with HIV are far less infectious to others, as we see in the fields of sexually transmitted infection control and mycobacterial disease control (tuberculosis and leprosy). Combination approaches are complex, may involve high program costs, and require substantial global commitments. We present a rationale for such investments and cite an ongoing research agenda that seeks to determine how feasible and cost-effective a combination prevention approach would be in a variety of epidemic contexts, notably that in a sub-Saharan Africa.

Can we stop AIDS with antiretroviral-based treatment as prevention?

Challenges to scaling up treatment as prevention (TasP) of HIV transmission are considerable in the developing-world context and include accessing at-risk populations, human resource shortages, adherence and retention in care, access to newer treatments, measurement of treatment effects, and long-term sustainable funding. Optimism about ending AIDS needs to be tempered by the realities of the logistic challenges of strengthening health systems in countries most affected and by balancing TasP with overall combination prevention approaches.

HIV treatment as prevention: issues in economic evaluation

Meyer-Rath and Over assert in another article in the July 2012 PLoS Medicine Collection, "Investigating the Impact of Treatment on New HIV Infections", that economic evaluations of antiretroviral therapy (ART) in currently existing programs and in HIV treatment as prevention (TasP) programs should use cost functions that capture cost dependence on a number of factors, such as scale and scope of delivery, health states, ART regimens, health workers' experience, patients' time on treatment, and the distribution of delivery across public and private sectors. We argue that for particular evaluation purposes (e.g., to establish the social value of TasP) and from particular perspectives (e.g., national health policy makers) less detailed cost functions may be sufficient. We then extend the discussion of economic evaluation of TasP, describing why ART outcomes and costs assessed in currently existing programs are unlikely to be generalizable to TasP programs for several fundamental reasons. First, to achieve frequent, widespread HIV testing and high uptake of ART immediately following an HIV diagnosis, TasP programs will require components that are not present in current ART programs and whose costs are not included in current estimates. Second, the early initiation of ART under TasP will change not only patients' disease courses and treatment experiences--which can affect behaviors that determine clinical treatment success, such as ART adherence and retention--but also quality of life and economic outcomes for HIV-infected individuals. Third, the preventive effects of TasP are likely to alter the composition of the HIV-infected population over time, changing its biological and behavioral characteristics and leading to different costs and outcomes for ART.

HIV treatment as prevention: optimising the impact of expanded HIV treatment programmes

Until now, decisions about how to allocate ART have largely been based on maximising the therapeutic benefit of ART for patients. Since the results of the HPTN 052 study showed efficacy of antiretroviral therapy (ART) in preventing HIV transmission, there has been increased interest in the benefits of ART not only as treatment, but also in prevention. Resources for expanding ART in the short term may be limited, so the question is how to generate the most prevention benefit from realistic potential increases in the availability of ART. Although not a formal systematic review, here we review different ways in which access to ART could be expanded by prioritising access to particular groups based on clinical or behavioural factors. For each group we consider (i) the clinical and epidemiological benefits, (ii) the potential feasibility, acceptability, and equity, and (iii) the affordability and cost-effectiveness of prioritising ART access for that group. In re-evaluating the allocation of ART in light of the new data about ART preventing transmission, the goal should be to create policies that maximise epidemiological and clinical benefit while still being feasible, affordable, acceptable, and equitable.