Could disease-modifying HIV vaccines cause population-level perversity?

Evolution of HIV virulence in response to disease-modifying vaccines: A modeling study

Pathogens face a tradeoff with respect to virulence; while more virulent strains often have higher per-contact transmission rates, they are also more likely to kill their hosts earlier. Because virulence is a heritable trait, there is concern that a disease-modifying vaccine, which reduces the disease severity of an infected vaccinee without changing the underlying pathogen genotype, may result in the evolution of higher pathogen virulence. We explored the potential for such virulence evolution with a disease-modifying HIV-1 vaccine in an agent-based stochastic epidemic model of HIV in United States men who have sex with men (MSM). In the model, vaccinated agents received no protection against infection, but experienced lower viral loads and slower disease progression. We compared the genotypic set point viral load (SPVL), a measure of HIV virulence, in populations given vaccines that varied in the degree of SPVL reduction they induce. Sensitivity analyses were conducted under varying vaccine coverage scenarios. With continual vaccination rollout under ideal circumstances of 90 % coverage over thirty years, the genotypic SPVL of vaccinated individuals evolved to become greater than the genotypic SPVL of unvaccinated individuals. This virulence evolution in turn diminished the public health benefit of the vaccine, and in some scenarios resulted in an accelerated epidemic. These findings demonstrate the complexity of viral evolution and have important implications for the design and development of HIV vaccines.

Evaluating strategies for spatial allocation of vaccines based on risk and centrality

When vaccinating a large population in response to an invading pathogen, it is often necessary to prioritize some individuals to be vaccinated first. One way to do this is to choose individuals to vaccinate based on their location. Methods for this prioritization include strategies that target those regions most at risk of importing the pathogen, and strategies that target regions with high centrality on the travel network. We use a simple infectious disease epidemic model to compare a risk-targeting strategy to two different centrality-targeting strategies based on betweenness centrality and random walk percolation centrality, respectively. We find that the relative effectiveness of these strategies in reducing the total number of infections varies with the basic reproduction number of the pathogen, travel rates, structure of the travel network and vaccine availability. We conclude that when a pathogen has high spreading capacity, or when vaccine availability is limited, centrality-targeting strategies should be considered as an alternative to the more commonly used risk-targeting strategies.

Is a COVID-19 Vaccine Likely to Make Things Worse?

In order to limit the disease burden and economic costs associated with the COVID-19 pandemic, it is important to understand how effective and widely distributed a vaccine must be in order to have a beneficial impact on public health. To evaluate the potential effect of a vaccine, we developed risk equations for the daily risk of COVID-19 infection both currently and after a vaccine becomes available. Our risk equations account for the basic transmission probability of COVID-19 (β) and the lowered risk due to various protection options: physical distancing; face coverings such as masks, goggles, face shields or other medical equipment; handwashing; and vaccination. We found that the outcome depends significantly on the degree of vaccine uptake: if uptake is higher than 80%, then the daily risk can be cut by 50% or more. However, if less than 40% of people get vaccinated and other protection options are abandoned-as may well happen in the wake of a COVID-19 vaccine-then introducing even an excellent vaccine will produce a worse outcome than our current situation. It is thus critical that effective education strategies are employed in tandem with vaccine rollout.

The Impact of Pre-exposure Prophylaxis for Human Immunodeficiency Virus on Gonorrhea Prevalence

Pre-exposure prophylaxis (PrEP) has been shown to be highly effective in reducing the risk of HIV infection in gay and bisexual men who have sex with men (GbMSM). However, PrEP does not protect against other sexually transmitted infections (STIs). In some populations, PrEP has also led to riskier behavior such as reduced condom usage, with the result that the prevalence of bacterial STIs like gonorrhea has increased. Here, we develop a compartmental model of the transmission of HIV and gonorrhea and the impacts of PrEP, condom usage, STI testing frequency and potential changes in sexual risk behavior stemming from the introduction of PrEP in a population of GbMSM. We find that introducing PrEP causes an increase in gonorrhea prevalence for a wide range of parameter values, including at the currently recommended frequency of STI testing once every three months for individuals on PrEP. Moreover, the model predicts that a higher STI testing frequency alone is not enough to prevent a rise in gonorrhea prevalence, unless the testing frequency is increased to impractical levels. However, testing every 2 months in combination with a 10-25 % reduction in risky behavior by individuals on PrEP would maintain gonorrhea prevalence at pre-PrEP levels. The results emphasize that programs making PrEP more available should be accompanied by efforts to support condom usage and frequent STI testing, in order to avoid an increase in the prevalence of gonorrhea and other bacterial STIs.

ART in HIV-Positive Persons With Low Pretreatment Viremia: Results From the START Trial

BACKGROUND

The benefit of immediate antiretroviral therapy (ART) at CD4 >500 cells/μL was established in the Strategic Timing of Antiretroviral Treatment (START) study. The benefits and risks of immediate ART in participants with low pretreatment viremia, including virologic suppressors, were further assessed.

SETTING

Randomized prospective international study.

METHODS

START participants with enrollment viremia <3000 c/mL were included. We compared clinical outcomes (grade 4 adverse events, hospitalizations, or death), plasma viremia, CD4 counts, and changes in biomarkers in immediate versus deferred ART groups.

RESULTS

Participants (N = 1134 including 93 with viremia ≤50 c/mL) had a median age of 37 years, 40% were women, and median CD4 was 713 cells/µL. Ninety-seven percent in the immediate and 29% in the deferred arm initiated ART at a median of 6 and 699 days, respectively. Clinical outcomes were experienced in 64 versus 61 patients in immediate and deferred arms (hazard ratio 1.10, 95% confidence interval: 0.77 to 1.56). The CD4 count difference was 125 cells/µL at 12 and 235 cells/µL at 36 months higher in the immediate versus deferred groups. D-dimer and VCAM levels decreased, and C-reactive protein increased, in the immediate arm at month 8. No significant changes in CD4 counts or biomarkers were observed in persons who maintained spontaneous virologic suppression.

CONCLUSIONS

START participants with low enrollment viremia experienced higher CD4 counts, greater proportion with suppressed viremia, and decreases in D-dimer levels on immediate ART despite the lack of difference in serious clinical outcomes. These data support immediate ART in people with low viremia, although equipoise remains for suppressors.

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

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

An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2

When mathematical models of infectious diseases are used to inform health policy, an important first step is often to calibrate a model to disease surveillance data for a specific setting (or multiple settings). It is increasingly common to also perform sensitivity analyses to demonstrate the robustness, or lack thereof, of the modeling results. Doing so requires the modeler to find multiple parameter sets for which the model produces behavior that is consistent with the surveillance data. While frequently overlooked, the calibration process is nontrivial at best and can be inefficient, poorly communicated and a major hurdle to the overall reproducibility of modeling results. In this work, we describe a general approach to calibrating infectious disease models to surveillance data. The technique is able to match surveillance data to high accuracy in a very efficient manner as it is based on the Newton-Raphson method for solving nonlinear systems. To demonstrate its robustness, we use the calibration technique on multiple models for the interacting dynamics of HIV and HSV-2.

HIV population-level adaptation can rapidly diminish the impact of a partially effective vaccine

BACKGROUND

Development of an HIV vaccine might be essential to ending the HIV/AIDS pandemic. However, vaccines can result in the emergence and spread of vaccine-resistant strains. Indeed, analyses of breakthrough infections in the HIV phase 3 vaccine trial RV144 identified HIV genotypes with differential rates of transmission in vaccine and placebo recipients. We hypothesized that, for HIV vaccination programs based on partially effective vaccines similar to RV144, HIV adaptation will rapidly diminish the expected vaccine impact.

METHODS AND FINDINGS

Using two HIV epidemic models, we simulated large-scale vaccination programs and, critically, included HIV strain diversity with respect to the vaccine response. We show here that rapid population-level viral adaptation can lead to decreased overall vaccine efficacy and substantially fewer infections averted by vaccination, when comparing scenarios with and without viral evolution (with outcomes depending on vaccination coverage, vaccine efficacy against the sensitive allele, and the initial resistant allele frequency). Translating this to the epidemic in South Africa, a scenario with 70% vaccination coverage may result in 250,000 infections (non-averted by vaccination) within 10 years of vaccine rollout that are due solely to HIV adaptation, all else being equal.

CONCLUSIONS

These findings suggest that approaches to HIV vaccine development, program implementation, and epidemic modeling may require attention to viral adaptation in response to vaccination.

Multiplayer games and HIV transmission via casual encounters

Population transmission models have been helpful in studying the spread of HIV. They assess changes made at the population level for different intervention strategies. To further understand how individual changes affect the population as a whole, game-theoretical models are used to quantify the decision-making process. Investigating multiplayer nonlinear games that model HIV transmission represents a unique approach in epidemiological research. We present here 2-player and multiplayer noncooperative games where players are defined by HIV status and age and may engage in casual (sexual) encounters. The games are modelled as generalized Nash games with shared constraints, which is completely novel in the context of our applied problem. Each player's HIV status is known to potential partners, and players have personal preferences ranked via utility values of unprotected and protected sex outcomes. We model a player's strategy as their probability of being engaged in a casual unprotected sex encounter (USE), which may lead to HIV transmission; however, we do not incorporate a transmission model here. We study the sensitivity of Nash strategies with respect to varying preference rankings, and the impact of a prophylactic vaccine introduced in players of youngest age groups. We also study the effect of these changes on the overall increase in infection level, as well as the effects that a potential prophylactic treatment may have on age-stratified groups of players. We conclude that the biggest impacts on increasing the infection levels in the overall population are given by the variation in the utilities assigned to individuals for unprotected sex with others of opposite HIV status, while the introduction of a prophylactic vaccine in youngest age group (15-20 yr olds) slows down the increase in HIV infection.

A Multi-Host Agent-Based Model for a Zoonotic, Vector-Borne Disease. A Case Study on Trypanosomiasis in Eastern Province, Zambia

BACKGROUND

This paper presents a new agent-based model (ABM) for investigating T. b. rhodesiense human African trypanosomiasis (rHAT) disease dynamics, produced to aid a greater understanding of disease transmission, and essential for development of appropriate mitigation strategies.

METHODS

The ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The method offers a complementary approach to traditional compartmentalised modelling techniques, permitting incorporation of fine scale demographic data such as ethnicity, age and gender into the simulation.

RESULTS

Through identification of possible spatial, demographic and behavioural characteristics which may have differing implications for rHAT risk in the region, the ABM produced output that could not be readily generated by other techniques. On average there were 1.99 (S.E. 0.245) human infections and 1.83 (S.E. 0.183) cattle infections per 6 month period. The model output identified that the approximate incidence rate (per 1000 person-years) was lower amongst cattle owning households (0.079, S.E. 0.017), than those without cattle (0.134, S.E. 0.017). Immigrant tribes (e.g. Bemba I.R. = 0.353, S.E.0.155) and school-age children (e.g. 5-10 year old I.R. = 0.239, S.E. 0.041) were the most at-risk for acquiring infection. These findings have the potential to aid the targeting of future mitigation strategies.

CONCLUSION

ABMs provide an alternative way of thinking about HAT and NTDs more generally, offering a solution to the investigation of local-scale questions, and which generate results that can be easily disseminated to those affected. The ABM can be used as a tool for scenario testing at an appropriate spatial scale to allow the design of logistically feasible mitigation strategies suggested by model output. This is of particular importance where resources are limited and management strategies are often pushed to the local scale.

Sexual behavior, risk perception, and HIV transmission can respond to HIV antiviral drugs and vaccines through multiple pathways

There has been growing use of highly active antiretroviral treatment (HAART) for HIV and significant progress in developing prophylactic HIV vaccines. The simplest theories of counterproductive behavioral responses to such interventions tend to focus on single feedback mechanisms: for instance, HAART optimism makes infection less scary and thus promotes risky sexual behavior. Here, we develop an agent based, age-structured model of HIV transmission, risk perception, and partner selection in a core group to explore behavioral responses to interventions. We find that interventions can activate not one, but several feedback mechanisms that could potentially influence decision-making and HIV prevalence. In the model, HAART increases the attractiveness of unprotected sex, but it also increases perceived risk of infection and, on longer timescales, causes demographic impacts that partially counteract HAART optimism. Both HAART and vaccination usually lead to lower rates of unprotected sex on the whole, but intervention effectiveness depends strongly on whether individuals over- or under-estimate intervention coverage. Age-specific effects cause sexual behavior and HIV prevalence to change in opposite ways in old and young age groups. For complex infections like HIV-where interventions influence transmission, demography, sexual behavior and risk perception-we conclude that evaluations of behavioral responses should consider multiple feedback mechanisms.

Disease Interventions Can Interfere with One Another through Disease-Behaviour Interactions

Theoretical models of disease dynamics on networks can aid our understanding of how infectious diseases spread through a population. Models that incorporate decision-making mechanisms can furthermore capture how behaviour-driven aspects of transmission such as vaccination choices and the use of non-pharmaceutical interventions (NPIs) interact with disease dynamics. However, these two interventions are usually modelled separately. Here, we construct a simulation model of influenza transmission through a contact network, where individuals can choose whether to become vaccinated and/or practice NPIs. These decisions are based on previous experience with the disease, the current state of infection amongst one's contacts, and the personal and social impacts of the choices they make. We find that the interventions interfere with one another: because of negative feedback between intervention uptake and infection prevalence, it is difficult to simultaneously increase uptake of all interventions by changing utilities or perceived risks. However, on account of vaccine efficacy being higher than NPI efficacy, measures to expand NPI practice have only a small net impact on influenza incidence due to strongly mitigating feedback from vaccinating behaviour, whereas expanding vaccine uptake causes a significant net reduction in influenza incidence, despite the reduction of NPI practice in response. As a result, measures that support expansion of only vaccination (such as reducing vaccine cost), or measures that simultaneously support vaccination and NPIs (such as emphasizing harms of influenza infection, or satisfaction from preventing infection in others through both interventions) can significantly reduce influenza incidence, whereas measures that only support expansion of NPI practice (such as making hand sanitizers more available) have little net impact on influenza incidence. (However, measures that improve NPI efficacy may fare better.) We conclude that the impact of interference on programs relying on multiple interventions should be more carefully studied, for both influenza and other infectious diseases.

Modelling the HIV epidemic among MSM in the United Kingdom: quantifying the contributions to HIV transmission to better inform prevention initiatives

OBJECTIVES

HIV is a major public health problem among MSM in the United Kingdom with around 2400 new infections annually. We quantified the contribution of biological and behavioural factors.

DESIGN

Modelling study.

METHODS

A partnership-based model of HIV transmission among UK MSM aged 15-64 years was developed and calibrated to time series HIV prevalence. The calibration was validated using multiple surveillance datasets. Population-attributable fractions were used to estimate the contribution of behavioural and biological factors to HIV transmission over the period 2001-2002, 2014-2015, and 2019-2020.

RESULTS

The contribution of most biological and behavioural factors was relatively constant over time, with the key group sustaining HIV transmission being higher-sexual activity MSM aged below 35 years living with undiagnosed HIV. The effect of primary HIV infection was relatively small with 2014-2015 population-attributable fraction of 10% (3-28%) in comparison with other subsequent asymptomatic stages. Diagnosed men who were not on antiretroviral therapy (ART) currently contributed 26% (14-39%) of net infections, whereas ART-treated MSM accounted for 17% (10-24%). A considerable number of new infections are also likely to occur within long-term relationships.

CONCLUSION

The majority of the new HIV infections among MSM in the United Kingdom during 2001-2020 is expected to be accounted for by a small group of younger and highly sexually active individuals, living with undiagnosed HIV in the asymptomatic stage. Bringing this group into HIV/AIDS care by improving testing uptake is a vital step for preventing onward transmission and will determine the success of using ART as prevention.

Potential future impact of a partially effective HIV vaccine in a southern African setting

Background

It is important for public health and within the HIV vaccine development field to understand the potential population level impact of an HIV vaccine of partial efficacy—both in preventing infection and in reducing viral load in vaccinated individuals who become infected—in the context of a realistic future implementation scenario in resource limited settings.

Methods

An individual level model of HIV transmission, progression and the effect of antiretroviral therapy was used to predict the outcome to 2060 of introduction in 2025 of a partially effective vaccine with various combinations of efficacy characteristics, in the context of continued ART roll-out in southern Africa.

Results

In the context of our base case epidemic (in 2015 HIV prevalence 28% and incidence 1.7 per 100 person years), a vaccine with only 30% preventative efficacy could make a substantial difference in the rate with which HIV incidence declines; the impact on incidence in relative terms is projected to increase over time, with a projected 67% lower HIV incidence in 2060 compared with no vaccine introduction. The projected mean decline in the general adult population death rate 2040–2060 is 11%. A vaccine with no prevention efficacy but which reduces viral load by 1 log is predicted to result in a modest (14%) reduction in HIV incidence and an 8% reduction in death rate in the general adult population (mean 2040–2060). These effects were broadly similar in multivariable uncertainty analysis.

Interpretation

Introduction of a partially effective preventive HIV vaccine would make a substantial long-term impact on HIV epidemics in southern Africa, in addition to the effects of ART. Development of an HIV vaccine, even of relatively low apparent efficacy at the individual level, remains a critical global public health goal.

Coevolution of risk perception, sexual behaviour, and HIV transmission in an agent-based model

Risk perception shapes individual behaviour, and is in turn shaped by the consequences of that behaviour. Here we explore this dynamics in the context of human immunodeficiency virus (HIV) spread. We construct a simplified agent-based model based on a partner selection game, where individuals are paired with others in the population, and through a decision tree, agree on unprotected sex, protected sex, or no sex. An individual's choice is conditioned on their HIV status, their perceived population-level HIV prevalence, and the preferences expressed by the individual with whom they are paired. HIV is transmitted during unprotected sex with a certain probability. As expected, in model simulations, the perceived population-level HIV prevalence climbs along with actual HIV prevalence. During this time, HIV- individuals increasingly switch from unprotected sex to protected sex, HIV+ individuals continue practicing unprotected sex whenever possible, and unprotected sex between HIV+ and HIV- individuals eventually becomes rare. We also find that the perceived population-level HIV prevalence diverges according to HIV status: HIV- individuals develop a higher perceived HIV prevalence than HIV+ individuals, although this result is sensitive to how much information is derived from global versus local sources. This research illustrates a potential mechanism by which distinct groups, as defined by their sexual behaviour, HIV status, and risk perceptions, can emerge through coevolution of HIV transmission and risk perception dynamics.

Network effects of risk behavior change following prophylactic interventions

We formulated a network-based model to understand how risk behavior change in conjunction with failure of prophylactic interventions can lead to unintended outcomes where "less (intervention) is more (effective)." Our model captures the distinction between one- and two-sided risk behavior change. In one-sided situations (e.g. influenza/H1N1) it is sufficient for either individual in an interaction to exhibit risk behavior change whereas in two-sided situations (e.g. AIDS/HIV) it is necessary for both individuals in the interaction to exhibit risk behavior change, for a potential transmission of the disease. A central discovery is that this phenomenon occurs at differing levels of intervention coverage depending upon the "sidedness" of the interaction. We find that for one-sided interactions, sufficiently high vaccination coverage is necessary for mitigating the effects of risk behavior; for two-sided interactions, it is essential to combine prophylactic treatments with programs aimed at reducing risky behavior. Furthermore, again dependent on the "sidedness," targeting highly connected nodes can be strictly worse than uniformly random interventions at the same level of coverage.

Modelling the epidemiological impact of scaling up HIV testing and antiretroviral treatment in China

BACKGROUND

The HIV epidemic in China has been increasing. In response, a 5-year action plan in China has prioritised the scale-up of HIV testing and treatment.

METHODS

We use a mathematical model to reproduce HIV epidemic trends in China and to forecast epidemic trends according to current conditions or increases in the rate of HIV testing or roll-out of antiretroviral therapy.

RESULTS

We show that the epidemic in China could be expected to experience a 2.5-fold expansion over the next 5 years such that ~1.8 million people will be infected with HIV in China by 2015. However, increasing testing and treatment rates can have substantial epidemiological benefits. For example, a four-fold increase in testing rates may avert more than 42000 HIV infections and 11000 deaths over the next 5 years. A 10-fold increase in the treatment rate could decrease the number of HIV-related deaths by 58% and the number of new infections by one-quarter by 2015.

CONCLUSIONS

Increasing HIV testing and treatment are important public health strategies for prevention.

Modeling dynamic interactions between pre-exposure prophylaxis interventions & treatment programs: predicting HIV transmission & resistance

Clinical trials have recently demonstrated the effectiveness of Pre-Exposure Prophylaxis (PrEP) in preventing HIV infection. Consequently, PrEP may soon be used for epidemic control. We model the dynamic interactions that will occur between treatment programs and potential PrEP interventions in resource-constrained countries. We determine the consequences for HIV transmission and drug resistance. We use response hypersurface modeling to predict the effect of PrEP on decreasing transmission as a function of effectiveness, adherence and coverage. We predict PrEP will increase need for second-line therapies (SLT) for treatment-naïve individuals, but could significantly decrease need for SLT for treatment-experienced individuals. If the rollout of PrEP is carefully planned it could increase the sustainability of treatment programs. If not, need for SLT could increase and the sustainability of treatment programs could be compromised. Our results show the optimal strategy for rolling out PrEP in resource-constrained countries is to begin around the "worst" treatment programs.

Modelling the spread of HIV immune escape mutants in a vaccinated population

Because cytotoxic T-lymphocytes (CTLs) have been shown to play a role in controlling human immunodeficiency virus (HIV) infection and because CTL-based simian immunodeficiency virus (SIV) vaccines have proved effective in non-human primates, one goal of HIV vaccine design is to elicit effective CTL responses in humans. Such a vaccine could improve viral control in patients who later become infected, thereby reducing onwards transmission and enhancing life expectancy in the absence of treatment. The ability of HIV to evolve mutations that evade CTLs and the ability of these ‘escape mutants’ to spread amongst the population poses a challenge to the development of an effective and robust vaccine. We present a mathematical model of within-host evolution and between-host transmission of CTL escape mutants amongst a population receiving a vaccine that elicits CTL responses to multiple epitopes. Within-host evolution at each epitope is represented by the outgrowth of escape mutants in hosts who restrict the epitope and their reversion in hosts who do not restrict the epitope. We use this model to investigate how the evolution and spread of escape mutants could affect the impact of a vaccine. We show that in the absence of escape, such a vaccine could markedly reduce the prevalence of both infection and disease in the population. However the impact of such a vaccine could be significantly abated by CTL escape mutants, especially if their selection in hosts who restrict the epitope is rapid and their reversion in hosts who do not restrict the epitope is slow. We also use the model to address whether a vaccine should span a broad or narrow range of CTL epitopes and target epitopes restricted by rare or common HLA types. We discuss the implications and limitations of our findings.

The evolution and spread of HIV strains that evade the immune response poses a major challenge to the development of an effective and robust HIV vaccine. We present a new mathematical tool that we use to dissect the drivers of the spread of these ‘immune escape mutants’ in a vaccinated population. Our study focuses on a vaccine that can reduce infectiousness and enhance longevity but does not provide sterilizing immunity. We show that in the absence of escape such a vaccine could reduce the prevalence of both infection and disease in the population. However, vaccine impact could be significantly abated by immune escape mutants, especially if they emerge rapidly and revert very slowly after transmission to hosts in whom the original selection pressure is absent. We also discuss the effect that vaccine breadth and the frequency with which different epitopes are targeted have upon vaccine impact.

Modeling HIV vaccines in Brazil: assessing the impact of a future HIV vaccine on reducing new infections, mortality and number of people receiving ARV

Background

The AIDS epidemic in Brazil remains concentrated in populations with high vulnerability to HIV infection, and the development of an HIV vaccine could make an important contribution to prevention. This study modeled the HIV epidemic and estimated the potential impact of an HIV vaccine on the number of new infections, deaths due to AIDS and the number of people receiving ARV treatment, under various scenarios.

Methods and Findings

The historical HIV prevalence was modeled using Spectrum and projections were made from 2010 to 2050 to study the impact of an HIV vaccine with 40% to 70% efficacy, and 80% coverage of adult population, specific groups such as MSM, IDU, commercial sex workers and their partners, and 15 year olds. The possibility of disinhibition after vaccination, neglecting medium- and high-risk groups, and a disease-modifying vaccine were also considered. The number of new infections and deaths were reduced by 73% and 30%, respectively, by 2050, when 80% of adult population aged 15–49 was vaccinated with a 40% efficacy vaccine. Vaccinating medium- and high-risk groups reduced new infections by 52% and deaths by 21%. A vaccine with 70% efficacy produced a great decline in new infections and deaths. Neglecting medium- and high-risk population groups as well as disinhibition of vaccinated population reduced the impact or even increased the number of new infections. Disease-modifying vaccine also contributed to reducing AIDS deaths, the need for ART and new HIV infections.

Conclusions

Even in a country with a concentrated epidemic and high levels of ARV coverage, such as Brazil, moderate efficacy vaccines as part of a comprehensive package of treatment and prevention could have a major impact on preventing new HIV infections and AIDS deaths, as well as reducing the number of people on ARV. Targeted vaccination strategies may be highly effective and cost-beneficial.

HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis

The administration of antiretrovirals before HIV exposure to prevent infection (i.e., preexposure prophylaxis; PrEP) is under evaluation in clinical trials. Because PrEP is based on antiretrovirals, there is considerable concern that it could substantially increase transmitted resistance, particularly in resource-rich countries. Here we use a mathematical model to predict the effect of PrEP interventions on the HIV epidemic in the men-who-have-sex-with-men community in San Francisco. The model is calibrated using Monte Carlo filtering and analyzed by constructing nonlinear response hypersurfaces. We predict PrEP interventions could substantially reduce transmission but significantly increase the proportion of new infections caused by resistant strains. Two mechanisms can cause this increase. If risk compensation occurs, the proportion increases due to increasing transmission of resistant strains and decreasing transmission of wild-type strains. If risk behavior remains stable, the increase occurs because of reduced transmission of resistant strains coupled with an even greater reduction in transmission of wild-type strains. We define this as the paradox of PrEP (i.e., resistance appears to be increasing, but is actually decreasing). We determine this paradox is likely to occur if the efficacy of PrEP regimens against wild-type strains is greater than 30% and the relative efficacy against resistant strains is greater than 0.2 but less than the efficacy against wild-type. Our modeling shows, if risk behavior increases, that it is a valid concern that PrEP could significantly increase transmitted resistance. However, if risk behavior remains stable, we find the concern is unfounded and PrEP interventions are likely to decrease transmitted resistance.

Potential population health outcomes and expenditures of HIV vaccination strategies in the United States

Estimating the potential health benefits and expenditures of a partially effective HIV vaccine is an important consideration in the debate about whether HIV vaccine research should continue. We developed an epidemic model to estimate HIV prevalence, new infections, and the cost-effectiveness of vaccination strategies in the U.S. Vaccines with modest efficacy could prevent 300,000-700,000 HIV infections and save $30 billion in healthcare expenditures over 20 years. Targeted vaccination of high-risk individuals is economically efficient, but difficulty in reaching these groups may mitigate these benefits. Universal vaccination is cost-effective for vaccines with 50% efficacy and price similar to other infectious disease vaccines.

Importance of promoting HIV testing for preventing secondary transmissions: modelling the Australian HIV epidemic among men who have sex with men

BACKGROUND

We address the research questions: (i) what proportion of new HIV infections is transmitted from people who are (a) undiagnosed, (b) in primary HIV infection (PHI), (c) on antiretroviral therapy?; and (ii) what is the expected epidemiological impact of (a) increasing the proportion of newly acquired HIV infections receiving early treatment, and (b) increasing HIV testing rates?

METHODS

We used a mathematical model to simulate HIV transmission in the population of men who have sex with men (MSM) in Australia. We calibrated the model using established biological and clinical data and a wide range of Australian MSM epidemiological and behavioural data sources.

RESULTS

We estimate that ~19% of all new HIV infections are transmitted from the ~3% of Australian HIV-infected MSM who are in PHI; ~31% of new HIV infections are estimated to be transmitted from the ~9% of MSM with undiagnosed HIV. We estimate that the average number of infections caused per HIV-infected MSM through the duration of PHI is ~0.14-0.28.

CONCLUSIONS

The epidemiological impact of increasing treatment in PHI would be modest due to insufficient detection of newly-infected individuals. In contrast, increases in HIV testing rates could have substantial epidemiological consequences. The benefit of testing will also increase over time. Promoting increases in the coverage and frequency of testing for HIV could be a highly-effective public health intervention, but the population-level impact of interventions based on promoting early treatment of patients diagnosed in PHI is likely to be small. Treating PHI requires further evaluation of its long-term effects on HIV-infected individuals.

Modeling the population level effects of an HIV-1 vaccine in an era of highly active antiretroviral therapy

First generation HIV vaccines may have limited ability to prevent infection. Instead, they may delay the onset of AIDS or reduce the infectiousness of vaccinated individuals who become infected. To assess the population level effects of such a vaccine, we formulate a deterministic model for the spread of HIV in a homosexual population in which the use of highly active antiretroviral therapy (HAART) to treat HIV infection is incorporated. The basic reproduction number R(0) is obtained under this model. We then expand the model to include the potential effects of a prophylactic HIV vaccine. The reproduction number R(f) is derived for a population in which a fraction f of susceptible individuals is vaccinated and continues to benefit from vaccination. We define f(*) as the minimum vaccination fraction for which R(f )< or =1 and describe situations in which it equals the critical vaccination fraction necessary to eliminate disease. When R(0) is large or an HIV vaccine is only partially effective, the critical vaccination fraction may exceed one. HIV vaccination, however, may still reduce the prevalence of disease if the reduction in infectiousness is at least as great as the reduction in the rate of disease progression. In particular, a vaccine that reduces infectiousness during acute infection may have an important public health impact especially if coupled with counseling to reduce risky behavior.

Considerations regarding efficacy endpoints in HIV vaccine trials: executive summary and recommendations of an expert consultation jointly organized by WHO, UNAIDS and ANRS in support of the Global HIV Vaccine Enterprise

HIV vaccines of the first generation are, in contrast to most currently licensed vaccines, unlikely to provide sterilizing immunity against infection with HIV. However, they are expected to exert a beneficial effect on the maintenance of CD4 T-cell counts by reducing viral load. There is a recognized need for clarifying the path to licensure of such novel vaccines and defining the clinical trial endpoints. This was the focus of discussions of a 2-day workshop organized by the WHO, UNAIDS and the ANRS, in support of the Global HIV Vaccine Enterprise, which took place in Paris, France (5-6 September 2007). This expert consultation, the proceedings of which are presented here, was intended to review the fundamental principles and approaches to validate surrogate markers in clinical research, as well as the significance of viral load for the individual course of disease and for secondary transmission. Recommendations were also made for additional research to inform decision-making regarding potential licensure and delivery of vaccines which do not prevent HIV acquisition but do reduce viral load.

Relation between HIV viral load and infectiousness: a model-based analysis

BACKGROUND

A consensus statement released on behalf of the Swiss Federal Commission for HIV/AIDS suggests that people receiving effective antiretroviral therapy-ie, those with undetectable plasma HIV RNA (<40 copies per mL)-are sexually non-infectious. We analysed the implications of this statement at a population level.

METHODS

We used a simple mathematical model to estimate the cumulative risk of HIV transmission from effectively treated HIV-infected patients (HIV RNA <10 copies per mL) over a prolonged period. We investigated the risk of unprotected sexual transmission per act and cumulatively over many exposures, within couples initially discordant for HIV status.

FINDINGS

Assuming that each couple had 100 sexual encounters per year, the cumulative probability of transmission to the serodiscordant partner each year is 0.0022 (uncertainty bounds 0.0008-0.0058) for female-to-male transmission, 0.0043 (0.0016-0.0115) for male-to-female transmission, and 0.043 (0.0159-0.1097) for male-to-male transmission. In a population of 10 000 serodiscordant partnerships, over 10 years the expected number of seroconversions would be 215 (80-564) for female-to-male transmission, 425 (159-1096) for male-to-female transmission, and 3524 (1477-6871) for male-to-male transmission, corresponding to an increase in incidence of four times compared with incidence under current rates of condom use.

INTERPRETATION

Our analyses suggest that the risk of HIV transmission in heterosexual partnerships in the presence of effective treatment is low but non-zero and that the transmission risk in male homosexual partnerships is high over repeated exposures. If the claim of non-infectiousness in effectively treated patients was widely accepted, and condom use subsequently declined, then there is the potential for substantial increases in HIV incidence.

FUNDING

Australian Research Council.

Dynamical analysis of a multi-strain model of HIV in the presence of anti-retroviral drugs

One major drawback associated with the use of anti-retroviral drugs in curtailing HIV spread in a population is the emergence and transmission of HIV strains that are resistant to these drugs. This paper presents a deterministic HIV treatment model, which incorporates a wild (drug sensitive) and a drug-resistant strain, for gaining insights into the dynamical features of the two strains, and determining effective ways to control HIV spread under this situation. Rigorous qualitative analysis of the model reveals that it has a globally asymptotically stable disease-free equilibrium whenever a certain epidemiological threshold (R t 0) is less than unity and that the disease will persist in the population when this threshold exceeds unity. Further, for the case where R t 0 > 1, it is shown that the model can have two co-existing endemic equilibria, and competitive exclusion phenomenon occurs whenever the associated reproduction number of the resistant strain (R t r) is greater than that of the wild strain (R t w). Unlike in the treatment model, it is shown that the model without treatment can have a family of infinitely many endemic equilibria when its associated epidemiological threshold (R(0)) exceeds unity. For the case when [Formula in text], it is shown that the widespread use of treatment against the wild strain can lead to its elimination from the community if the associated reduction in infectiousness of infected individuals (treated for the wild strain) does not exceed a certain threshold value (in this case, the use of treatment is expected to make R t w < R t r.

Measuring the public-health impact of candidate HIV vaccines as part of the licensing process

The full impact of vaccines against infectious diseases is manifest at both the individual and the community levels. We argue that evaluating the community-level impact of HIV vaccine candidates should be an integral part of the licensing process. We describe a framework for the public-health evaluation of an HIV vaccine, which is based on the interactive use of mathematical models and community randomised clinical trials (C-RCTs) following completion of individual-based clinical trials (I-RCTs). Mathematical models of HIV vaccine can be used to take public-health considerations into account during the licensing process and can also help to select promising vaccine candidates for testing in C-RCTs. We also describe community and individual-based measures useful for defining public-health criteria necessary to guide the licensing process. To move forward, it is crucial to reach a consensus on what should constitute adequate public-health criteria. At the very least, a suitable vaccine would provide some individual benefit to vaccinees and not be detrimental to the population at large. In future I-RCTs and C-RCTs, quantifying each protective vaccine characteristic (eg, reductions in susceptibility or viral load) is important if regulators are to evaluate adequately the potential community-level impact of the vaccine across different settings, populations, and conditions of use.

Mathematical models for HIV transmission dynamics: tools for social and behavioral science research

HIV researchers have long appreciated the need to understand the social and behavioral determinants of HIV-related risk behavior, but the cumulative impact of individual behaviors on population-level HIV outcomes can be subtle and counterintuitive, and the methods for studying this are rarely part of a traditional social science or epidemiology training program. Mathematical models provide a way to examine the potential effects of the proximate biologic and behavioral determinants of HIV transmission dynamics, alone and in combination. The purpose of this article is to show how mathematical modeling studies have contributed to our understanding of the dynamics and disparities in the global spread of HIV. Our aims are to demonstrate the value that these analytic tools have for social and behavioral sciences in HIV prevention research, to identify gaps in the current literature, and to suggest directions for future research.

Predicting the impact of a partially effective HIV vaccine and subsequent risk behavior change on the heterosexual HIV epidemic in low- and middle-income countries: A South African example

We developed a mathematical model to simulate the impact of various partially effective preventive HIV vaccination scenarios in a population at high risk for heterosexually transmitted HIV. We considered an adult population defined by gender (male/female), disease stage (HIV-negative, HIV-positive, AIDS, and death), and vaccination status (unvaccinated/vaccinated) in Soweto, South Africa. Input data included initial HIV prevalence of 20% (women) and 12% (men), vaccination coverage of 75%, and exclusive male negotiation of condom use. We explored how changes in vaccine efficacy and postvaccination condom use would affect HIV prevalence and total HIV infections prevented over a 10-year period. In the base-case scenario, a 40% effective HIV vaccine would avert 61,000 infections and reduce future HIV prevalence from 20% to 13%. A 25% increase (or decrease) in condom use among vaccinated individuals would instead avert 75,000 (or only 46,000) infections and reduce the HIV prevalence to 12% (or only 15%). Furthermore, certain combinations of increased risk behavior and vaccines with <43% efficacy could worsen the epidemic. Even modestly effective HIV vaccines can confer enormous benefits in terms of HIV infections averted and decreased HIV prevalence. However, programs to reduce risk behavior may be important components of successful vaccination campaigns.

Effects of public health educational campaigns and the role of sex workers on the spread of HIV/AIDS among heterosexuals

This paper presents a sex-structured model for heterosexual transmission of HIV/AIDS in which the population is divided into three subgroups: susceptibles, infectives and AIDS cases. The subgroups are further divided into two classes, consisting of individuals involved in high-risk sexual activities and individuals involved in low-risk sexual activities. The model considers the movement of individuals from high to low sexual activity groups as a result of public health educational campaigns. Thus, in this case public health educational campaigns are resulting in the split of the population into risk groups. The equilibrium and epidemic threshold, which is known as the basic reproductive number (R0), are obtained, and stability (local and global) of the disease-free equilibrium is investigated. The model is extended to incorporate sex workers, and their role in the spread of HIV/AIDS in settings with heterosexual transmission is explored. Comprehensive analytic and numerical techniques are employed in assessing the possible community benefits of public health educational campaigns in controlling HIV/AIDS. From the study, we conclude that the presence of sex workers enlarges the epidemic threshold R0, thus fuels the epidemic among the heterosexuals, and that public health educational campaigns among the high-risk heterosexual population reduces R0, thus can help slow or eradicate the epidemic.

Analytic insights into the population level impact of imperfect prophylactic HIV vaccines

The population level implications of imperfect HIV vaccines were studied using a mathematical model. A criterion for determining the utility of a vaccine at the population level is introduced, and 2 useful summary measures, namely, vaccine utility (phi) and vaccine infection fitness (psi), are derived and shown to characterize the population-level utility once vaccine efficacies are determined. The utility of the vaccine alone does not guarantee a substantial impact, however, because the effectiveness of partially effective vaccines also depends on the prevailing level of HIV infectious spread. Therefore, a second criterion is introduced through a third summary measure, the hazard index (xi), to describe the effectiveness of a vaccine in substantially reducing HIV incidence. The qualitative features of the impact are delineated by studying 4 distinct scenarios of HIV vaccination. Accordingly, our work delineates the link between vaccine efficacies and the impact of vaccination at the population level and provides the tools for vaccine developers to assess the utility and effectiveness of a given imperfect vaccine straightforwardly and rapidly.

Understanding the mechanisms and limitations of immune control of HIV

A large number of experimental studies have been performed over the past decade in an attempt to develop a vaccine for human immunodeficiency virus (HIV). These studies have used a variety of approaches aimed at stimulating both antibody-mediated and cell-mediated immunity. Many of these experiments have been performed in macaque models of HIV. Analysis and modeling of the results of these studies provide the opportunity to investigate the mechanisms and limitations of viral control by humoral and cell-mediated immunity. These studies suggest that CD8(+) T cells do 'too little too late' to prevent the establishment of viral infection and latency. By contrast, passively administered antibody acts extremely early to reduce the initial inoculum and slow viral growth. In both cases, reduction in peak viral load appears crucial to the maintenance of CD4(+) T cells in acute infection and for effective long-term viral control. The insights gained from studies of simian human immunodeficiency virus infection have important implications for HIV vaccination. However, important questions remain as to whether differences in pathogenesis in HIV will lead to different 'rules of engagement' for immune control of virus.

A susceptible-infected epidemic model with voluntary vaccinations

An susceptible-infected epidemic model with endogenous behavioral changes is presented to analyze the impact of a prophylactic vaccine on disease prevalence. It is shown that, with voluntary vaccination, whether an endemic equilibrium exists or not does not depend on vaccine efficacy or the distribution of agent-types. Although an endemic equilibrium is unique in the absence of a vaccine, the availability of a vaccine can lead to multiple endemic equilibria that differ in disease prevalence and vaccine coverage. Depending on the distribution of agent-types, the introduction of a vaccine or, if one is available, a subsidy for vaccination can increase disease prevalence by inducing more risky behavior.

Unusually High Frequency MHC Class I Alleles in Mauritian Origin Cynomolgus Macaques

Acute shortages of Indian origin Rhesus macaques significantly hinder HIV/AIDS research. Cellular immune responses are particularly difficult to study because only a subset of animals possess MHC class I (MHC I) alleles with defined peptide-binding specificities. To expand the pool of nonhuman primates suitable for studies of cellular immunity, we defined 66 MHC I alleles in Cynomolgus macaques (Macaca fascicularis) of Chinese, Vietnamese, and Mauritian origin. Most MHC I alleles were found only in animals from a single geographic origin, suggesting that Cynomolgus macaques from different origins are not interchangeable in studies of cellular immunity. Animals from Mauritius may be particularly valuable because >50% of these Cynomolgus macaques share the MHC class I allele combination Mafa-B*430101, Mafa-B*440101, and Mafa-B*460101. The increased MHC I allele sharing of Mauritian origin Cynomolgus macaques may dramatically reduce the overall number of animals needed to study cellular immune responses in nonhuman primates while simultaneously reducing the confounding effects of genetic heterogeneity in HIV/AIDS research.

High-potency human immunodeficiency virus vaccination leads to delayed and reduced CD8+ T-cell expansion but improved virus control

CD8(+) T lymphocytes are thought to play an important role in the control of acute and chronic human immunodeficiency virus infections. However, there is a significant delay between infection and the first observed increase in virus-specific CD8(+) T-cell numbers. Prior to this time, viral kinetics are not significantly different between controls and vaccinees. Surprisingly, higher initial virus-specific CD8(+) T-cell numbers lead to a longer delay prior to initial CD8(+) T-cell expansion, and slower CD8(+) T-cell increases. Nevertheless, higher initial CD8(+) T-cell numbers were associated with reduced peak and chronic viral loads and reduced CD4(+) T-cell depletion.

The antiretroviral rollout and drug-resistant HIV in Africa: insights from empirical data and theoretical models

The U.S. Government has pledged to spend $15 billion in Africa and the Caribbean on AIDS. A central focus of this plan is to provide antiretroviral treatment (ART) to millions. Here, we evaluate whether the plan to rollout ART in Africa is likely to generate an epidemic of drug-resistant strains of HIV. We review what has occurred as a result of high usage of ART in developed countries in terms of changes in risky behavior, and the emergence and transmission of drug-resistant HIV. We also review how mathematical models have been used to predict the evolution of drug-resistant HIV epidemics. We then show how models can be used to predict the likely impact of the ART rollout on the evolution of drug-resistant HIV in Africa. At currently planned levels of treatment coverage, we predict that (over the next decade) in Africa: (i) the impact of ART on reducing HIV transmission (and prevalence) is likely to be undetectable (unless accompanied by substantial changes in behavior), (ii) the transmission rate of drug-resistant HIV will be below the WHO surveillance threshold of 5%, and (ii) the majority of cases of drug-resistant HIV that will occur will be due to acquired (and not transmitted) resistance. For the next decade, large-scale surveillance for detecting transmitted resistance in Africa is unnecessary. Instead, we recommend that patients should be closely monitored for acquired resistance, and sentinel surveillance (in a few urban centers) should be used to monitor transmitted resistance.