Could widespread use of combination antiretroviral therapy eradicate HIV epidemics?

Current combination antiretroviral therapies (ARV) are widely used to treat HIV. However drug-resistant strains of HIV have quickly evolved, and the level of risky behaviour has increased in certain communities. Hence, currently the overall impact that ARV will have on HIV epidemics remains unclear. We have used a mathematical model to predict whether the current therapies: are reducing the severity of HIV epidemics, and could even lead to eradication of a high-prevalence (30%) epidemic. We quantified the epidemic-level impact of ARV on reducing epidemic severity by deriving the basic reproduction number (R(0)(ARV)). R(0)(ARV) specifies the average number of new infections that one HIV case generates during his lifetime when ARV is available and ARV-resistant strains can evolve and be transmitted; if R(0)(ARV) is less than one epidemic eradication is possible. We estimated for the HIV epidemic in the San Francisco gay community (using uncertainty analysis), the present day value of R(0)(ARV), and the probability of epidemic eradication. We assumed a high usage of ARV and three behavioural assumptions: that risky sex would (1) decrease, (2) remain stable, or (3) increase. Our estimated values of R(0)(ARV) (median and interquartile range [IQR]) were: 0.90 (0.85-0.96) if risky sex decreases, 1.0 (0.94-1.05) if risky sex remains stable, and 1.16 (1.05-1.28) if risky sex increases. R(0)(ARV) decreased as the fraction of cases receiving treatment increased. The probability of epidemic eradication is high (p=0.85) if risky sex decreases, moderate (p=0.5) if levels of risky sex remain stable, and low (p=0.13) if risky sex increases. We conclude that ARV can function as an effective HIV-prevention tool, even with high levels of drug resistance and risky sex. Furthermore, even a high-prevalence HIV epidemic could be eradicated using current ARV.

Problems and solutions for the Stop TB partnership.

Recent international efforts for global control of tuberculosis have resulted in a new movement: the Stop TB partnership. One of the operational goals of this movement is based on WHO-determined targets to detect, by 2005, 70% of new smear-positive cases under DOTS, and to successfully treat 85% of these cases. In a paper in the Bulletin of the World Health Organization, Dye and colleagues present data that show the current case-detection rate to be low (only 27%), and that in many areas treatment-success rates are still below the WHO target level. Dye and colleagues predict, by linear extrapolation of these data, that the WHO target of a 70% case detection rate will be achieved by 2013. Here, we discuss why it is unlikely that the WHO global targets for either case detection or treatment success will be reached by 2013, and we also offer some potential solutions.

Amplification dynamics: predicting the effect of HIV on tuberculosis outbreaks.

HIV affects the pathogenesis and the transmission of Mycobacterium tuberculosis. We used a discrete event simulation model to predict the potential impact of HIV on increasing the probability and the expected severity of tuberculosis outbreaks. Our predictions reveal that an HIV epidemic can significantly increase the frequency and severity of tuberculosis outbreaks, but that this amplification effect of HIV on tuberculosis outbreaks is very sensitive to the tuberculosis treatment rate. At moderate or low treatment rates, even a moderate HIV epidemic can cause the average size of tuberculosis outbreaks to almost double in comparison with the expected outbreak size when HIV is absent. However, we determined that the amplification effect of HIV can be substantially reduced if the treatment rate of tuberculosis is very high. We discuss the significant implications of these results for the global control of tuberculosis. Our results also reveal that occasionally a "normal-virulence" strain of M. tuberculosis can be expected to generate a large outbreak. We discuss the implications of these results in understanding the virulence of M. tuberculosis and in the planned elimination of tuberculosis in the United States.

Predicting the unpredictable: transmission of drug-resistant HIV.

We use a mathematical model to understand (from 1996 to 2001) and to predict (from 2001 to 2005) the evolution of the epidemic of drug-resistant HIV in San Francisco. We predict the evolutionary trajectories for 1,000 different drug-resistant strains with each strain having a different fitness relative to a drug-sensitive strain. We calculate that the current prevalence of resistance is high, and predict it will continue to rise. In contrast, we calculate that transmission of resistance is currently low, and predict it will remain low. We show that the epidemic of resistance is being generated mainly by the conversion of drug-sensitive cases to drug-resistant cases, and not by the transmission of resistant strains. We also show that transmission of resistant strains has not increased the overall number of new HIV infections. Our results indicate that transmission of resistant strains is, and will remain, a relatively minor public health problem.

Live attenuated HIV vaccines: predicting the tradeoff between efficacy and safety.

The utility of live attenuated vaccines for controlling HIV epidemics is being debated. Live attenuated HIV vaccines (LAHVs) could be extremely effective in protecting against infection with wild-type strains, but may not be completely safe as the attenuated strain could cause AIDS in some vaccinated individuals. We present a theoretical framework for evaluating the consequences of the tradeoff between vaccine efficacy (in terms of preventing new infections with wild-type strains) and safety (in terms of vaccine-induced AIDS deaths). We use our framework to predict, for Zimbabwe and Thailand, the epidemiological impact of 1,000 different (specified by efficacy and safety characteristics) LAHVs. We predict that paradoxically: (i) in Zimbabwe (where transmission is high) LAHVs would significantly decrease the AIDS death rate, but (ii) in Thailand (where transmission is low) exactly the same vaccines (in terms of efficacy and safety characteristics) would increase the AIDS death rate. Our results imply that a threshold transmission rate exists that determines whether any given LAHV has a beneficial or a detrimental impact. We also determine the vaccine perversity point, which is defined in terms of the fraction of vaccinated individuals who progress to AIDS as a result of the vaccine strain. Vaccination with any LAHV that causes more than 5% of vaccinated individuals to progress to AIDS in 25 years would, even 50 years later, lead to perversity (i.e., increase the annual AIDS death rate) in Thailand; these same vaccines would lead to decreases in the annual AIDS death rate in Zimbabwe.

Early therapy for latent tuberculosis infection.

The risk of developing active tuberculosis is highest within the first 2 years of infection. Therefore, an intervention that targets persons with recent infection, such as identifying contacts of active cases, could be particularly effective as an epidemic control measure. A mathematical model of a tuberculosis epidemic is formulated and used to evaluate the strategy of targeting therapy to persons with recently acquired latent tuberculosis infection. The model is used to quantify the effectiveness of therapy for early latent tuberculosis infection in reducing the prevalence of active tuberculosis. The model is also used to demonstrate how effective therapy for early latent tuberculosis infection has to be to eliminate tuberculosis, when used in conjunction with therapy for active tuberculosis. Analysis of the model suggests that programs such as contact investigations, which identify and treat persons recently infected with Mycobacterium tuberculosis, may have a substantial effect on controlling tuberculosis epidemics.

Potential impact of tuberculosis vaccines as epidemic control agents.

We use 2 simple mathematical models (one a preexposure vaccine model and the other a postexposure vaccine model) to provide general insight into the effects of vaccination on tuberculosis epidemics. We discuss how these models can be used as health policy tools: to identify which vaccines are "equivalent," to design control strategies, and to predict the epidemiological impact of different vaccination strategies. Our results show that even moderately effective vaccines could have a significant effect on reducing tuberculosis epidemics if they can be coupled with moderate to high treatment rates. We suggest that both preexposure and postexposure tuberculosis vaccines can be used to help eliminate tuberculosis in developing countries. In developed countries, only a preexposure vaccine (used in combination with a high level of treatment) would be necessary to eliminate tuberculosis.

Impact of antivirals and emergence of drug resistance: HSV-2 epidemic control.

Genital herpes, caused by herpes simplex virus type-2 (HSV-2), affects more people world-wide than any other sexually transmitted disease (STD). Antivirals are effective in decreasing the duration of symptoms and in reducing viral shedding; however, currently antiviral usage is extremely low. Increased usage of antivirals would have a beneficial epidemic-level effect (due to the decreased transmission of drug-sensitive strains) as well as potentially a detrimental epidemic-level effect (if drug-resistant strains emerge and are transmitted). Previously, we have developed a mathematical model that we have used to predict (with a degree of uncertainty) the beneficial and the potential detrimental epidemic-level effects of increased antiviral usage. Here, we use our model to make further predictions about the impact of increasing antiviral usage. We calculate the effect, on individual patients, of antiviral usage in terms of: (1) the decrease in the average number of infectious days per year and (2) an individual's lifetime probability of acquiring permanent drug resistance. We also use our model: (1) to determine the probability of eliminating herpes by antivirals and (2) to quantify the effect of increasing antiviral usage on decreasing HSV-2 prevalence. Our results show that theoretically it would be possible to eliminate herpes epidemics by using a drug that does not cure.

A tale of two futures: HIV and antiretroviral therapy in San Francisco.

The effect of antiretroviral therapy (ART) in preventing human immunodeficiency virus (HIV) infections and averting acquired immunodeficiency syndrome (AIDS) deaths in the San Francisco gay community over the next 10 years was predicted. A transmission model was coupled with a statistical approach that enabled inclusion of a high degree of uncertainty in the potential treatment effects of ART (in terms of infectivity and survival), increase in risky behavior, and rate of emergence of drug resistance. Increasing the usage of ART in San Francisco would decrease the AIDS death rate and could substantially reduce the incidence rate.

Quantifying the intrinsic transmission dynamics of tuberculosis.

Previously we have formulated transmission models of untreated tuberculosis epidemics (Blower et al., Nature, Medicine 1 (1995), 815-821); in this paper, we present time-dependent uncertainty and sensitivity analyses in order to quantitatively understand the transmission dynamics of tuberculosis epidemics in the absence of treatment. The time-dependent uncertainty analysis enabled us to evaluate the variability in the epidemiological outcome variables of the model during the progression of a tuberculosis epidemic. Calculated values (from the uncertainty analysis) for the disease incidence, disease prevalence, and mortality rates were approximately consistent with historical data. The time-dependent sensitivity analysis revealed that only a few of the model's input parameters significantly affected the severity of a tuberculosis epidemic; these parameters were the disease reactivation rate, the fraction of infected individuals who develop tuberculosis soon after infection, the number of individuals that an infectious individual infects per year, the disease death rate, and the population recruitment rate. Our analysis demonstrates that it is possible to improve our understanding of the behavior of tuberculosis epidemics by applying time-dependent uncertainty and sensitivity analysis to a transmission model.

Understanding, predicting and controlling the emergence of drug-resistant tuberculosis: a theoretical framework.

The high prevalence of tuberculosis in developing countries and the recent resurgence of tuberculosis in many developed countries suggests that current control strategies are suboptimal. The increase in drug-resistant cases exacerbates the control problems. Currently employed epidemic control strategies are not devised on the basis of a theoretical understanding of the transmission dynamics of Mycobacterium tuberculosis. We describe and discuss a theoretical framework based upon mathematical transmission models that can be used for understanding, predicting, and controlling tuberculosis epidemics. We illustrate how the theoretical framework can be used to predict the temporal dynamics of the emergence of drug resistance, to predict the epidemiological consequences of epidemic control strategies in developing and developed countries, and to design epidemic control strategies.

Predicting and preventing the emergence of antiviral drug resistance in HSV-2.

Genital herpes, caused by herpes simplex virus, is the most prevalent sexually transmitted disease worldwide. In many developing countries genital herpes is untreated, and in the United States only 10% of cases are treated. We present a mathematical model that we use as a health policy tool to predict the levels of antiviral drug resistance that would emerge, if treatment rates were increased, and to identify the key factors in determining the emergence of drug resistance. We use our results to suggest control measures for herpes epidemics that would prevent the emergence of substantial levels of antiviral drug resistance.

Uncertainty and sensitivity analysis of the basic reproductive rate. Tuberculosis as an example.

The basic reproductive rate (R0) is a measure of the severity of an epidemic. On the basis of replicated Latin hypercube sampling, the authors performed an uncertainty and sensitivity analysis of the basic reproductive rate of tuberculosis (TB). The uncertainty analysis allowed for the derivation of a frequency distribution for R0 and the assessment of the relative contribution each of the three components of R0 made when TB epidemics first arose centuries ago. (The three components of R0 are associated with fast, slow, and relapse TB.) R0 estimates indicated the existence of fairly severe epidemics when TB epidemics first arose. The R0 for the susceptible persons who developed TB slowly (R0(slow)) contributed the most to the R0 estimates; however, the relative R0(slow) contribution decreased as the severity of TB epidemics increased. The sensitivity of the magnitude of R0 to the uncertainty in estimating values of each of the input parameters was assessed. These results indicated that five of the nine input parameters, because of their estimation uncertainty, were influential in determining the magnitude of R0. This uncertainty and sensitivity methodology provides results that can aid investigators in understanding the historical epidemiology of TB by quantifying the effect of the transmission processes involved. Additionally, this method can be applied to the R0 of any other infectious disease to estimate the probability of an epidemic outbreak.

Control strategies for tuberculosis epidemics: new models for old problems.

Tuberculosis, although preventable and curable, causes more adult deaths than any other infectious disease. A theoretical framework for designing effective control strategies is developed and used to determine treatment levels for eradication, to assess the effects of noneradicating control, and to examine the global goals of the World Health Organization. The theory is extended to assess how suboptimal control programs contribute to the evolution of drug resistance. A new evaluation criterion is defined and used to suggest how control strategies can be improved. In order to control tuberculosis, treatment failure rates must be lower in developing countries than in developed countries.

Modelling HIV vaccination.

Relatively recently, mathematical models have been applied to issues r elated to HIV vaccination. Significant progress has been made towards understanding how rather ineffective vaccines will perform in trials and in the community, but some areas still need research.

The intrinsic transmission dynamics of tuberculosis epidemics.

In developed countries the major tuberculosis epidemics declined long before the disease became curable in the 1940s. We present a theoretical framework for assessing the intrinsic transmission dynamics of tuberculosis. We demonstrate that it takes one to several hundred years for a tuberculosis epidemic to rise, fall and reach a stable endemic level. Our results suggest that some of the decline of tuberculosis is simply due to the natural behaviour of an epidemic. Although other factors must also have contributed to the decline, these causal factors were constrained to operate within the slow response time dictated by the intrinsic dynamics.

HIV transmission in sexual networks: an empirical analysis.

Risk behaviour and egocentric sexual network data collected from a large random sample of young gay men in San Francisco were analysed to assess the importance of sexual mixing (i.e. sexual networks) in the acquisition of HIV. These data were collected in 1993, during wave one of a longitudinal cohort study of HIV transmission in gay men; the seroprevalence level in the sample was 18%. We identify recent sexual mixing patterns and we demonstrate that seropositives and seronegatives have very different age-stratified sexual mixing patterns. We show that sexual mixing can explain the current seroprevalence patterns in the young gay community; seroprevalence levels in risk groups reflect the degree of sexual mixing with the older (and more heavily infected) age group. Our results suggest that seropositives became infected with HIV not simply owing to an increased rate of acquisition of sex partners, but also as a result of their sexual mixing pattern. We develop and apply a simple methodology that uses the sexual network data in combination with risk behaviour data to estimate the future number of seroconverters. Our methodology is validated by testing our predictions against the observed seroconversion data collected during wave two of the cohort study in 1994. Our analyses empirically demonstrate (for the first time) the significance of sexual mixing as a risk factor for HIV transmission.

An analysis of the process of human immunodeficiency virus sexual risk behavior change.

Few studies have tried to identify the process of risk behavior change. In this paper, we present a method for the analysis of the process of risk behavior change; the methodology involves using time series data to form transition probability matrices. We apply the method to human immunodeficiency virus (HIV) sexual risk behavioral data from a cohort of gay men in Amsterdam. We determine the process of risk behavior change in this cohort, and we demonstrate that it is not possible to deduce the process simply from an examination of the static pattern. Our results imply that the risk behavior change that is observed in this cohort may be viewed as a homogeneous one-step Markovian process. This process of risk behavior change has implications for the long-term prediction of HIV seroconversion rates and for the design and evaluation of HIV behavioral intervention studies and vaccine trials. Our results also have implications for the interpretation of relapse behavior.

Prophylactic vaccines, risk behavior change, and the probability of eradicating HIV in San Francisco.

Theory is linked with data to assess the probability of eradicating human immunodeficiency virus (HIV) in San Francisco through the use of prophylactic vaccines. The necessary vaccine efficacy levels and population coverage levels for eradication are quantified. The likely impact of risk behavior changes on vaccination campaigns is assessed. The results show it is unlikely that vaccines will be able to eradicate HIV in San Francisco unless they are combined with considerable reductions in risk behaviors. Furthermore, if risk behavior increases as the result of a vaccination campaign, then vaccination could result in a perverse outcome by increasing the severity of the epidemic.