Apparent declining efficacy in randomized trials: examples of the Thai RV144 HIV vaccine and South African CAPRISA 004 microbicide trials

Prevention efficacy of the broadly neutralizing antibody VRC01 depends on HIV-1 envelope sequence features

In the Antibody Mediated Prevention (AMP) trials (HVTN 704/HPTN 085 and HVTN 703/HPTN 081), prevention efficacy (PE) of the monoclonal broadly neutralizing antibody (bnAb) VRC01 (vs. placebo) against HIV-1 acquisition diagnosis varied according to the HIV-1 Envelope (Env) neutralization sensitivity to VRC01, as measured by 80% inhibitory concentration (IC80). Here, we performed a genotypic sieve analysis, a complementary approach to gaining insight into correlates of protection that assesses how PE varies with HIV-1 sequence features. We analyzed HIV-1 Env amino acid (AA) sequences from the earliest available HIV-1 RNA-positive plasma samples from AMP participants diagnosed with HIV-1 and identified Env sequence features that associated with PE. The strongest Env AA sequence correlate in both trials was VRC01 epitope distance that quantifies the divergence of the VRC01 epitope in an acquired HIV-1 isolate from the VRC01 epitope of reference HIV-1 strains that were most sensitive to VRC01-mediated neutralization. In HVTN 704/HPTN 085, the Env sequence-based predicted probability that VRC01 IC80 against the acquired isolate exceeded 1 µg/mL also significantly associated with PE. In HVTN 703/HPTN 081, a physicochemical-weighted Hamming distance across 50 VRC01 binding-associated Env AA positions of the acquired isolate from the most VRC01-sensitive HIV-1 strain significantly associated with PE. These results suggest that incorporating mutation scoring by BLOSUM62 and weighting by the strength of interactions at AA positions in the epitope:VRC01 interface can optimize performance of an Env sequence-based biomarker of VRC01 prevention efficacy. Future work could determine whether these results extend to other bnAbs and bnAb combinations.

Competing Heterogeneities in Vaccine Effectiveness Estimation

Understanding the waning of vaccine-induced protection is important for both immunology and public health. Population heterogeneities in underlying (pre-vaccination) susceptibility and vaccine response can cause measured vaccine effectiveness (mVE) to change over time, even in the absence of pathogen evolution and any actual waning of immune responses. We use multi-scale agent-based models parameterized using epidemiological and immunological data, to investigate the effect of these heterogeneities on mVE as measured by the hazard ratio. Based on our previous work, we consider the waning of antibodies according to a power law and link it to protection in two ways: (1) motivated by correlates of risk data and (2) using a within-host model of stochastic viral extinction. The effect of the heterogeneities is given by concise and understandable formulas, one of which is essentially a generalization of Fisher's fundamental theorem of natural selection to include higher derivatives. Heterogeneity in underlying susceptibility accelerates apparent waning, whereas heterogeneity in vaccine response slows down apparent waning. Our models suggest that heterogeneity in underlying susceptibility is likely to dominate. However, heterogeneity in vaccine response offsets <10% to >100% (median of 29%) of this effect in our simulations. Our study suggests heterogeneity is more likely to 'bias' mVE downwards towards the faster waning of immunity but a subtle bias in the opposite direction is also plausible.

Competing Heterogeneities in Vaccine Effectiveness Estimation

Understanding waning of vaccine-induced protection is important for both immunology and public health. Population heterogeneities in underlying (pre-vaccination) susceptibility and vaccine response can cause measured vaccine effectiveness (mVE) to change over time even in the absence of pathogen evolution and any actual waning of immune responses. We use a multi-scale agent-based models parameterized using epidemiological and immunological data, to investigate the effect of these heterogeneities on mVE as measured by the hazard ratio. Based on our previous work, we consider waning of antibodies according to a power law and link it to protection in two ways: 1) motivated by correlates of risk data and 2) using a within-host model of stochastic viral extinction. The effect of the heterogeneities is given by concise and understandable formulas, one of which is essentially a generalization of Fisher's fundamental theorem of natural selection to include higher derivatives. Heterogeneity in underlying susceptibility accelerates apparent waning, whereas heterogeneity in vaccine response slows down apparent waning. Our models suggest that heterogeneity in underlying susceptibility is likely to dominate. However, heterogeneity in vaccine response offsets <10% to >100% (median of 29%) of this effect in our simulations. Our methodology and results may be helpful in understanding competing heterogeneities and waning of immunity and vaccine-induced protection. Our study suggests heterogeneity is more likely to 'bias' mVE downwards towards faster waning of immunity but a subtle bias in the opposite direction is also plausible.

Estimating Waning of Vaccine Effectiveness: A Simulation Study

BACKGROUND

Developing accurate and reliable methods to estimate vaccine protection is a key goal in immunology and public health. While several statistical methods have been proposed, their potential inaccuracy in capturing fast intraseasonal waning of vaccine-induced protection needs to be rigorously investigated.

METHODS

To compare statistical methods for estimating vaccine effectiveness (VE), we generated simulated data using a multiscale, agent-based model of an epidemic with an acute viral infection and differing extents of VE waning. We apply a previously proposed framework for VE measures based on the observational data richness to assess changes of vaccine-induced protection over time.

RESULTS

While VE measures based on hard-to-collect information (eg, the exact timing of exposures) were accurate, usually VE studies rely on time-to-infection data and the Cox proportional hazards model. We found that its extension using scaled Schoenfeld residuals, previously proposed for capturing VE waning, was unreliable in capturing both the degree of waning and its functional form and identified the mathematical factors contributing to this unreliability. We showed that partitioning time and including a time-vaccine interaction term in the Cox model significantly improved estimation of VE waning, even in the case of dramatic, rapid waning. We also proposed how to optimize the partitioning scheme.

CONCLUSIONS

While appropriate for rejecting the null hypothesis of no waning, scaled Schoenfeld residuals are unreliable for estimating the degree of waning. We propose a Cox-model-based method with a time-vaccine interaction term and further optimization of partitioning time. These findings may guide future analysis of VE waning data.

Interpreting vaccine efficacy trial results for infection and transmission

Randomized controlled trials (RCTs) have shown high efficacy of multiple vaccines against SARS-CoV-2 disease (COVID-19), and recent studies have shown the vaccines are also effective against infection. Evidence for the effect of each of these vaccines on ability to transmit the virus is also beginning to emerge. We describe an approach to estimate these vaccines' effects on viral positivity, a prevalence measure which under the reasonable assumption that vaccinated individuals who become infected are no more infectious than unvaccinated individuals forms a lower bound on efficacy against transmission. Specifically, we recommend separate analysis of positive tests triggered by symptoms (usually the primary RCT outcome) and cross-sectional prevalence of positive tests obtained regardless of symptoms. The odds ratio of carriage for vaccine vs. placebo provides an unbiased estimate of vaccine effectiveness against viral positivity, under certain assumptions, and we show through simulations that likely departures from these assumptions will only modestly bias this estimate. Applying this approach to published data from the RCT of the Moderna vaccine, we estimate that one dose of vaccine reduces the potential for transmission by at least 61%, possibly considerably more. We describe how these approaches can be translated into observational studies of vaccine effectiveness.

Joint modeling of time-varying HIV exposure and infection for estimation of per-act efficacy in HIV prevention trials

Objectives

Using the MTN-020/ASPIRE HIV prevention trial as a motivating example, our objective is to construct a joint model for the HIV exposure process through vaginal intercourse and the time to HIV infection in a population of sexually active women. By modeling participants' HIV infection in terms of exposures, rather than time exposed, our aim is to obtain a valid estimate of the per-act efficacy of a preventive intervention.

Methods

Within the context of HIV prevention trials, in which the frequency of sex acts is self-reported periodically by the participants, we model the exposure process of the trial participants with a non-homogeneous Poisson process. This approach allows for variability in the rate of sexual contacts between participants as well as variability in the rate of sexual contacts over time. The time to HIV infection for each participant is modeled as the time to the exposure that results in HIV infection, based on the modeled sexual contact rate. We propose an empirical Bayes approach for estimation.

Results

We report the results of a simulation study where we evaluate the performance of our proposed approachandcompareittothetraditionalapproachofestimatingtheoverallreductioninHIVincidenceusing a Proportional Hazards Cox model. The proposed approach is also illustrated with data from the MTN-020/ASPIRE trial.

Conclusions

The proposed joint modeling, along with the proposed empirical Bayes estimation approach, can provide valid estimation of the per-exposure efficacy of a preventive intervention.

Interpreting vaccine efficacy trial results for infection and transmission

Randomized controlled trials (RCTs) have shown high efficacy of multiple vaccines against SARS-CoV-2 disease (COVID-19), and recent studies have shown the vaccines are also effective against infection. Evidence for the effect of each of these vaccines on ability to transmit the virus is also beginning to emerge. We describe an approach to estimate these vaccines' effects on viral positivity, a prevalence measure which under the reasonable assumption that vaccinated individuals who become infected are no more infectious than unvaccinated individuals forms a lower bound on efficacy against transmission. Specifically, we recommend separate analysis of positive tests triggered by symptoms (usually the primary outcome) and cross-sectional prevalence of positive tests obtained regardless of symptoms. The odds ratio of carriage for vaccine vs. placebo provides an unbiased estimate of vaccine effectiveness against viral positivity, under certain assumptions, and we show through simulations that likely departures from these assumptions will only modestly bias this estimate. Applying this approach to published data from the RCT of the Moderna vaccine, we estimate that one dose of vaccine reduces the potential for transmission by at least 61%, possibly considerably more. We describe how these approaches can be translated into observational studies of vaccine effectiveness.

Depletion-of-susceptibles Bias in Analyses of Intra-season Waning of Influenza Vaccine Effectiveness

Bias arises in studies of waning vaccine effectiveness when higher-risk individuals are depleted from the at-risk population at different rates between study groups. We examined how this bias arises and how to avoid it. A reanalysis of data from California confirmed a finding of intra-season waning of influenza vaccine effectiveness.

Depletion-of-susceptibles bias in influenza vaccine waning studies: how to ensure robust results

Vaccine effectiveness studies are subject to biases due to depletion-of-persons at risk of infection, or at especially high risk of infection, at different rates from different groups (depletion-of-susceptibles bias), a problem that can also lead to biased estimates of waning effectiveness, including spurious inference of waning when none exists. An alternative study design to identify waning is to study only vaccinated persons, and compare for each day the incidence in persons with earlier or later dates of vaccination to assess waning in vaccine protection as a function of vaccination time (namely whether earlier vaccination would result in lower subsequent protection compared to later vaccination). Prior studies suggested under what conditions this alternative would yield correct estimates of waning. Here we define the depletion-of-susceptibles process formally and show mathematically that for influenza vaccine waning studies, a randomised trial or corresponding observational study that compares incidence at a specific calendar time among individuals vaccinated at different times before the influenza season begins will not be vulnerable to depletion-of-susceptibles bias in its inference of waning as a function of vaccination time under the null hypothesis that none exists, and will - if waning does actually occur - underestimate the extent of waning. Such a design is thus robust in the sense that a finding of waning in that inference framework reflects actual waning of vaccine-induced immunity. We recommend such a design for future studies of waning, whether observational or randomised.

Competing biomedical HIV prevention strategies: potential cost-effectiveness of HIV vaccines and PrEP in Seattle, WA

INTRODUCTION

Promising HIV vaccine candidates are steadily progressing through the clinical trial pipeline. Once available, HIV vaccines will be an important complement but also potential competitor to other biomedical prevention tools such as pre-exposure prophylaxis (PrEP). Accordingly, the value of HIV vaccines and the policies for rollout may depend on that interplay and tradeoffs with utilization of existing products. In this economic modelling analysis, we estimate the cost-effectiveness of HIV vaccines considering their potential interaction with PrEP and condom use.

METHODS

We developed a dynamic model of HIV transmission among the men who have sex with men population (MSM), aged 15-64 years, in Seattle, WA offered PrEP and HIV vaccine over a time horizon of 2025-2045. A healthcare sector perspective with annual discount rate of 3% for costs (2017 USD) and quality-adjusted life years (QALYs) was used. The primary economic endpoint is the incremental cost-effectiveness ratio (ICER) when compared to no HIV vaccine availability.

RESULTS

HIV vaccines improved population health and increased healthcare costs. Vaccination campaigns achieving 90% coverage of high-risk men and 60% coverage of other men within five years of introduction are projected to avoid 40% of new HIV infections between 2025 and 2045. This increased total healthcare costs by $30 million, with some PrEP costs shifted to HIV vaccine spending. HIV vaccines are estimated to have an ICER of $42,473/QALY, considered cost-effective using a threshold of $150,000/QALY. Results were most sensitive to HIV vaccine efficacy and future changes in the cost of PrEP drugs. Sensitivity analysis found ranges of 30-70% HIV vaccine efficacy remained cost-effective. Results were also sensitive to reductions in condom use among PrEP and vaccine users.

CONCLUSIONS

Access to an HIV vaccine is desirable as it could increase the overall effectiveness of combination HIV prevention efforts and improve population health. Planning for the rollout and scale-up of HIV vaccines should carefully consider the design of policies that guide interactions between vaccine and PrEP utilization and potential competition.

Measurement of Vaccine Direct Effects Under the Test-Negative Design

Test-negative designs are commonplace in assessments of influenza vaccination effectiveness, estimating this value from the exposure odds ratio of vaccination among individuals treated for acute respiratory illness who test positive for influenza virus infection. This approach is widely believed to recover the vaccine direct effect by correcting for differential health-care-seeking behavior among vaccinated and unvaccinated persons. However, the relationship of the measured odds ratio to true vaccine effectiveness is poorly understood. We derived the odds ratio under circumstances of real-world test-negative studies. The odds ratio recovers the vaccine direct effect when 2 conditions are met: 1) Individuals' vaccination decisions are uncorrelated with exposure or susceptibility to the test-positive or test-negative conditions, and 2) vaccination confers "all-or-nothing" protection (whereby certain individuals have no protection while others are perfectly protected). Biased effect-size estimates arise if either condition is unmet. Such bias might suggest misleading associations of vaccine effectiveness with time since vaccination or the force of infection of influenza. The test-negative design could also fail to correct for differential health-care-seeking behavior among vaccinated and unvaccinated persons without stringent criteria for enrollment and testing. Our findings demonstrate a need to reassess how data from test-negative studies can inform policy decisions.

Effectiveness of influenza vaccination on influenza-associated hospitalisations over time among children in Hong Kong: a test-negative case-control study

BACKGROUND

The protection conferred by influenza vaccination is generally thought to last less than a year, necessitating annual revaccination. However, the speed with which influenza vaccine effectiveness might decline during a year is unknown, which is of particular importance for locations with year-round influenza activity. We aimed to assess how influenza vaccine effectiveness changes by time intervals between vaccination and admission to hospital, taking advantage of almost year-round circulation of influenza in Hong Kong.

METHODS

In this test-negative case-control study, we analysed vaccine effectiveness in children (aged 6 months to 17 years) who were admitted to hospital in Hong Kong over 5 consecutive years (2012-17). We included those who were admitted to general wards in four public hospitals in Hong Kong with a fever (≥38°C) and any respiratory symptom, such as runny nose, cough, or sore throat. We used direct immunofluorescence assay and reverse transcription PCR to detect influenza virus infection, and recorded children's influenza immunisation history. We compared characteristics of positive cases and negative controls and examined how vaccine effectiveness changed by time between vaccination and admission to hospital with regression analyses.

FINDINGS

Between Sept 1, 2012, and Aug 31, 2017, we enrolled 15 695 children hospitalised for respiratory infections, including 2500 (15·9%) who tested positive for influenza A or B and 13 195 (84·1%) who tested negative. 159 (6·4%) influenza-positive cases and 1445 (11·0%) influenza-negative cases had been vaccinated. Most vaccinations were done by December of each influenza vaccination season. Influenza-related admissions to hospital occurred year-round, with peaks in January through March in most years and a large summer peak in 2016; pooled vaccine effectiveness for children of all ages was 79% (95% CI 42-92) for September to December, 67% (57-74) for January to April, and 43% (25-57) for May to August. Vaccine effectiveness against influenza A or B was estimated as 79% (95% CI 64-88) within 0·5-2 months of vaccination, 60% (46-71) within >2-4 months, 57% (39-70) within >4-6 months, and 45% (22-61) within >6-9 months. In separate analyses by type and subtype, we estimated that vaccine effectiveness declined by 2-5 percentage points per month.

INTERPRETATION

Influenza vaccine effectiveness decreased during the 9 months after vaccination in children in Hong Kong. Our findings confirm the importance of annual vaccination in children. Influenza vaccines that provide broader and longer-lasting protection are needed to provide year-round protection in regions with irregular influenza seasonality or lengthy periods of influenza activity.

FUNDING

Health and Medical Research Fund, Hong Kong and the Research Grants Council, Hong Kong.

Immune History and Influenza Vaccine Effectiveness

The imperfect effectiveness of seasonal influenza vaccines is often blamed on antigenic mismatch, but even when the match appears good, effectiveness can be surprisingly low. Seasonal influenza vaccines also stand out for their variable effectiveness by age group from year to year and by recent vaccination status. These patterns suggest a role for immune history in influenza vaccine effectiveness, but inference is complicated by uncertainty about the contributions of bias to the estimates themselves. In this review, we describe unexpected patterns in the effectiveness of seasonal influenza vaccination and explain how these patterns might arise as consequences of study design, the dynamics of immune memory, or both. Resolving this uncertainty could lead to improvements in vaccination strategy, including the use of universal vaccines in experienced populations, and the evaluation of vaccine efficacy against influenza and other antigenically variable pathogens.

Temporally Varying Relative Risks for Infectious Diseases: Implications for Infectious Disease Control

Risks for disease in some population groups relative to others (relative risks) are usually considered to be consistent over time, although they are often modified by other, nontemporal factors. For infectious diseases, in which overall incidence often varies substantially over time, the patterns of temporal changes in relative risks can inform our understanding of basic epidemiologic questions. For example, recent studies suggest that temporal changes in relative risks of infection over the course of an epidemic cycle can both be used to identify population groups that drive infectious disease outbreaks, and help elucidate differences in the effect of vaccination against infection (that is relevant to transmission control) compared with its effect against disease episodes (that reflects individual protection). Patterns of change in the age groups affected over the course of seasonal outbreaks can provide clues to the types of pathogens that could be responsible for diseases for which an infectious cause is suspected. Changing apparent efficacy of vaccines during trials may provide clues to the vaccine's mode of action and/or indicate risk heterogeneity in the trial population. Declining importance of unusual behavioral risk factors may be a signal of increased local transmission of an infection. We review these developments and the related public health implications.

Observational studies and the difficult quest for causality: lessons from vaccine effectiveness and impact studies

Although randomized placebo-controlled trials (RCT) are critical to establish efficacy of vaccines at the time of licensure, important remaining questions about vaccine effectiveness (VE)-used here to include individual-level measures and population-wide impact of vaccine programmes-can only be answered once the vaccine is in use, from observational studies. However, such studies are inherently at risk for bias. Using a causal framework and illustrating with examples, we review newer approaches to detecting and avoiding confounding and selection bias in three major classes of observational study design: cohort, case-control and ecological studies. Studies of influenza VE, especially in seniors, are an excellent demonstration of the challenges of detecting and reducing such bias, and so we use influenza VE as a running example. We take a fresh look at the time-trend studies often dismissed as 'ecological'. Such designs are the only observational study design that can measure the overall effect of a vaccination programme [indirect (herd) as well as direct effects], and are in fact already an important part of the evidence base for several vaccines currently in use. Despite the great strides towards more robust observational study designs, challenges lie ahead for evaluating best practices for achieving robust unbiased results from observational studies. This is critical for evaluation of national and global vaccine programme effectiveness.

Prolonging herd immunity to cholera via vaccination: Accounting for human mobility and waning vaccine effects

BACKGROUND

Oral cholera vaccination is an approach to preventing outbreaks in at-risk settings and controlling cholera in endemic settings. However, vaccine-derived herd immunity may be short-lived due to interactions between human mobility and imperfect or waning vaccine efficacy. As the supply and utilization of oral cholera vaccines grows, critical questions related to herd immunity are emerging, including: who should be targeted; when should revaccination be performed; and why have cholera outbreaks occurred in recently vaccinated populations?

METHODS AND FINDINGS

We use mathematical models to simulate routine and mass oral cholera vaccination in populations with varying degrees of migration, transmission intensity, and vaccine coverage. We show that migration and waning vaccine efficacy strongly influence the duration of herd immunity while birth and death rates have relatively minimal impacts. As compared to either periodic mass vaccination or routine vaccination alone, a community could be protected longer by a blended "Mass and Maintain" strategy. We show that vaccination may be best targeted at populations with intermediate degrees of mobility as compared to communities with very high or very low population turnover. Using a case study of an internally displaced person camp in South Sudan which underwent high-coverage mass vaccination in 2014 and 2015, we show that waning vaccine direct effects and high population turnover rendered the camp over 80% susceptible at the time of the cholera outbreak beginning in October 2016.

CONCLUSIONS

Oral cholera vaccines can be powerful tools for quickly protecting a population for a period of time that depends critically on vaccine coverage, vaccine efficacy over time, and the rate of population turnover through human mobility. Due to waning herd immunity, epidemics in vaccinated communities are possible but become less likely through complementary interventions or data-driven revaccination strategies.

Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model

Inconsistent results in recent HIV prevention trials of pre-exposure prophylactic interventions may be due to heterogeneity in risk among study participants. Intervention effectiveness is most commonly estimated with the Cox model, which compares event times between populations. When heterogeneity is present, this population-level measure underestimates intervention effectiveness for individuals who are at risk. We propose a likelihood-based Bayesian hierarchical model that estimates the individual-level effectiveness of candidate interventions by accounting for heterogeneity in risk with a compound Poisson-distributed frailty term. This model reflects the mechanisms of HIV risk and allows that some participants are not exposed to HIV and, therefore, have no risk of seroconversion during the study. We assess model performance via simulation and apply the model to data from an HIV prevention trial. Copyright © 2016 John Wiley & Sons, Ltd.

Measuring the potential role of frailty in apparent declining efficacy of HIV interventions

Objective:In recent HIV intervention trials, intervention efficacies appear to decline over time. Researchers have attributed this to “waning,” or a loss of intervention efficacy. Another possible reason is heterogeneity in infection risk or “frailty.” We propose an approach to assessing the impact of frailty and waning on measures of intervention efficacy and statistical power in randomized-controlled trials.

Methods:Using multiplicative risk reduction, we developed a mathematical formulation for computing disease incidence and the incidence rate ratio (IRR) as a function of frailty and waning. We designed study scenarios, which held study-related factors constant, varied waning and frailty parameters and measured the change in disease incidence, IRR, and statistical power.

Results:We found that frailty alone can impact disease incidence over time. However, frailty has minimal impact on the IRR. The factor that has the greatest influence on the IRR is intervention efficacy and the degree to which it is projected to wane. We also found that even moderate waning can cause an unacceptable decrease in statistical power while the impact of frailty on statistical power is minimal.

Discussion:We conclude that frailty has minimal impact on trial results relative to intervention efficacy. Study resources would, therefore, be better spent on efforts to keep the intervention efficacy constant throughout the trial (e.g., enhancing the vaccine schedule or promoting treatment adherence).

Estimating the per-exposure effect of infectious disease interventions

The average effect of an infectious disease intervention (eg, a vaccine) varies across populations with different degrees of exposure to the pathogen. As a result, many investigators favor a per-exposure effect measure that is considered independent of the population level of exposure and that can be used in simulations to estimate the total disease burden averted by an intervention across different populations. However, while per-exposure effects are frequently estimated, the quantity of interest is often poorly defined, and assumptions in its calculation are typically left implicit. In this article, we build upon work by Halloran and Struchiner (Epidemiology. 1995;6:142-151) to develop a formal definition of the per-exposure effect and discuss conditions necessary for its unbiased estimation. With greater care paid to the parameterization of transmission models, their results can be better understood and can thereby be of greater value to decision-makers.

Estimating the effectiveness in HIV prevention trials by incorporating the exposure process: application to HPTN 035 data

Estimating the effectiveness of a new intervention is usually the primary objective for HIV prevention trials. The Cox proportional hazard model is mainly used to estimate effectiveness by assuming that participants share the same risk under the covariates and the risk is always non-zero. In fact, the risk is only non-zero when an exposure event occurs, and participants can have a varying risk to transmit due to varying patterns of exposure events. Therefore, we propose a novel estimate of effectiveness adjusted for the heterogeneity in the magnitude of exposure among the study population, using a latent Poisson process model for the exposure path of each participant. Moreover, our model considers the scenario in which a proportion of participants never experience an exposure event and adopts a zero-inflated distribution for the rate of the exposure process. We employ a Bayesian estimation approach to estimate the exposure-adjusted effectiveness eliciting the priors from the historical information. Simulation studies are carried out to validate the approach and explore the properties of the estimates. An application example is presented from an HIV prevention trial.

HIV epidemic in Asia: optimizing and expanding vaccine development

The recent evidence in Thailand for protection from acquisition of HIV through vaccination in a mostly heterosexual population has generated considerable hope. Building upon these results and the analysis of the correlates of risk remains among the highest priorities. Improved vaccine concepts including heterologous prime-boost regimens, improved proteins with potent adjuvants and new vectors expressing mosaic antigens may soon enter clinical development to assess vaccine efficacy in men who have sex with men. Identifying heterosexual populations with sufficient HIV incidence for the conduct of efficacy trials represents perhaps the main challenge in Asia. Fostering translational research efforts in Asian countries may benefit from the development of master strategic plans and program management processes.

Good CoP, bad CoP? Interrogating the immune responses to primate lentiviral vaccines

Correlates of protection (CoPs) against infection by primate lentiviruses remain undefined. Modest protection against HIV-1 was observed in one human vaccine trial, whereas previous trials and vaccine-challenge experiments in non-human primates have yielded inconsistent but intriguing results. Although high levels of neutralizing antibodies are known to protect macaques from mucosal and intravenous viral challenges, antibody or other adaptive immune responses associated with protection might also be mere markers of innate immunity or susceptibility. Specific strategies for augmenting the design of both human trials and animal experiments could help to identify mechanistic correlates of protection and clarify the influences of confounding factors. Robust protection may, however, require the combined actions of immune responses and other host factors, thereby limiting what inferences can be drawn from statistical associations. Here, we discuss how to analyze immune protection against primate lentiviruses, and how host factors could influence both the elicitation and effectiveness of vaccine-induced responses.