How various design decisions on matching individuals in relationships affect the outcomes of microsimulations of sexually transmitted infection epidemics.

Microsimulations are increasingly used to estimate the prevalence of sexually transmitted infections (STIs). These models consist of agents which represent a sexually active population. Matching agents into sexual relationships is computationally intensive and presents modellers with difficult design decisions: how to select which partnerships between agents break up, which agents enter a partnership market, and how to pair agents in the partnership market. The aim of this study was to analyse the effect of these design decisions on STI prevalence. We compared two strategies for selecting which agents enter a daily partnership market and which agent partnerships break up: random selection in which agents are treated homogenously versus selection based on data from a large German longitudinal data set that accounts for sex, sexual orientation and age heterogeneity. We also coupled each of these strategies with one of several recently described algorithms for pairing agents and compared their speed and outcomes. Additional design choices were also considered, such as the number of agents used in the model, increasing the heterogeneity of agents' sexual behaviour, and the proportion of relationships which are casual sex encounters. Approaches which account for agent heterogeneity estimated lower prevalence than less sophisticated approaches which treat agents homogeneously. Also, in simulations with non-random pairing of agents, as the risk of infection increased, incidence declined as the number of agents increased. Our algorithms facilitate the execution of thousands of simulations with large numbers of agents quickly. Fast pair-matching algorithms provide a practical way for microsimulation modellers to account for varying sexual behaviour within the population they are studying. For STIs with high infection rates modellers may need to experiment with different population sizes.

Modelling the human immunodeficiency virus (HIV) epidemic: A review of the substance and role of models in South Africa.

We review key mathematical models of the South African human immunodeficiency virus (HIV) epidemic from the early 1990s onwards. In our descriptions, we sometimes differentiate between the concepts of a model world and its mathematical or computational implementation. The model world is the conceptual realm in which we explicitly declare the rules - usually some simplification of 'real world' processes as we understand them. Computing details of informative scenarios in these model worlds is a task requiring specialist knowledge, but all other aspects of the modelling process, from describing the model world to identifying the scenarios and interpreting model outputs, should be understandable to anyone with an interest in the epidemic.

The role of activists in access to HIV and tuberculosis treatment and prevention.

PURPOSE OF REVIEW: We describe the role of activism in improving access to quality HIV treatment. RECENT FINDINGS: In many countries, AIDS activists have campaigned for improved access to HIV treatment and prevention interventions. Studying medicine, epidemiology and law, and developing expertise in these fields, has been crucial to the success of these campaigns. Also important has been the building of alliances by activists with clinicians, nurses, scientists, and public health policy experts, persuading them of the importance of these campaigns. This article describes examples of campaigns in several middle and low-income countries, showing how activists, by becoming familiar with HIV science, have helped make antiretrovirals available to millions of people across the world. HIV activists have also been drawn into, and driven, broader struggles for health social justice, such as campaigns for new tuberculosis and hepatitis C. SUMMARY: Scientists and activists need to continue to work together to improve access to treatment. But to be effective, a critical mass of activists must develop expertise in HIV science and the law.

A Comparison of Two Mathematical Modeling Frameworks for Evaluating Sexually Transmitted Infection Epidemiology.

BACKGROUND: Different models of sexually transmitted infections (STIs) can yield substantially different conclusions about STI epidemiology, and it is important to understand how and why models differ. Frequency-dependent models make the simplifying assumption that STI incidence is proportional to STI prevalence in the population, whereas network models calculate STI incidence more realistically by classifying individuals according to their partners' STI status. METHODS: We assessed a deterministic frequency-dependent model approximation to a microsimulation network model of STIs in South Africa. Sexual behavior and demographic parameters were identical in the 2 models. Six STIs were simulated using each model: HIV, herpes, syphilis, gonorrhea, chlamydia, and trichomoniasis. RESULTS: For all 6 STIs, the frequency-dependent model estimated a higher STI prevalence than the network model, with the difference between the 2 models being relatively large for the curable STIs. When the 2 models were fitted to the same STI prevalence data, the best-fitting parameters differed substantially between models, with the frequency-dependent model suggesting more immunity and lower transmission probabilities. The fitted frequency-dependent model estimated that the effects of a hypothetical elimination of concurrent partnerships and a reduction in commercial sex were both smaller than estimated by the fitted network model, whereas the latter model estimated a smaller impact of a reduction in unprotected sex in spousal relationships. CONCLUSIONS: The frequency-dependent assumption is problematic when modeling short-term STIs. Frequency-dependent models tend to underestimate the importance of high-risk groups in sustaining STI epidemics, while overestimating the importance of long-term partnerships and low-risk groups.

Anything to Stay Alive: The Challenges of a Campaign for an Experimental Drug.

Drug-resistant tuberculosis (TB) has a high mortality rate. Most medicines used to treat it are poorly tested and have terrible side effects. Activists have campaigned for patients with drug-resistant TB to have access to experimental drugs, particularly one called bedaquiline, before these have been approved by regulatory authorities such as the Food and Drug Administration (FDA) in the United States (US) and the Medicines Control Council (MCC) in South Africa. Some activists have also campaigned for bedaquiline to be approved by regulatory authorities before testing of the drug is completed. These campaigns raise ethical concerns about whether patients should be offered experimental, unapproved, medicines for the treatment of life-threatening illnesses, and if authorities should approve drugs for life-threatening illnesses when vital questions about safety and efficacy remain outstanding.

Community views: balancing the public health benefits of earlier antiretroviral treatment with the implications for individual patients - perspectives from the community.

PURPOSE OF REVIEW: When should people with HIV start treatment? This question is widely debated. The recent momentum to initiate treatment at a CD4 cell count above 350 cells/mm3 is driven by the potential population benefits of antiretroviral treatment reducing infectiousness together with operational concerns. These are important. However, we focus on the clinical benefits and risks for the person taking treatment, and how this may vary depending on the background health setting. RECENT FINDINGS: We refer to the recent guideline changes and the limited evidence on which they are based. Many studies that have informed guideline changes reference plausible benefits, but have limited follow-up and are not designed to assess the potential risks. We note historical examples to show that expert opinion in the absence of data warrants caution. SUMMARY: Results from well powered studies designed to look at the question of when to start treatment are essential for quantifying the benefits and risks of earlier treatment. Meanwhile, the decision of when to start must be taken by the HIV-positive person in consultation with their health worker based on accurate information. That choice will vary depending on a person's individual health, their reason to want to treat and the resources of the health-care facility.

The impact of reduced drug prices on the cost-effectiveness of HAART in South Africa.

South Africa has started 'rolling out' highly active anti-retroviral therapy (HAART) through the public health sector, but implementation has been slow. Studies have shown that in Africa AIDS prevention may be more cost-effective than providing HAART; such published results provide some support for the South African government's apparent reluctance to implement a large-scale rapid HAART roll-out. However, previous studies have not linked treatment and prevention plans, and do not, for the most part, consider the potential savings to the public health sector (e.g., fewer hospital admissions) that may arise from the introduction of HAART. The South African costing exercise summarised here avoids both these limitations. It provides an update of earlier work and takes into account the recent decline in antiretroviral drug prices. It shows that once HIV-related hospital costs are included in the calculation, the cost per HIV infection averted is lower in a treatment-plus-prevention intervention scenario than it is in a prevention-only scenario. This suggests that it is economically advantageous to fund a large-scale comprehensive intervention plan and that the constraints for doing so are political. Once human-rights considerations are included, the case for providing HAART is even more compelling.