Back to basics in HIV prevention: focus on exposure.
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Biomedical subjects
Publications and source records attributed to Geoff P Garnett.
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A mathematical model is developed to characterize the distribution of cell turnover rates within a population of T lymphocytes. Previous models of T-cell dynamics have assumed a constant uniform turnover rate; here we consider turnover in a cell pool subject to clonal proliferation in response to diverse and repeated antigenic stimulation. A basic framework is defined for T-cell proliferation in response to antigen, which explicitly describes the cell cycle during antigenic stimulation and subsequent cell division. The distribution of T-cell turnover rates is then calculated based on the history of random exposures to antigens. This distribution is found to be bimodal, with peaks in cell frequencies in the slow turnover (quiescent) and rapid turnover (activated) states. This distribution can be used to calculate the overall turnover for the cell pool, as well as individual contributions to turnover from quiescent and activated cells. The impact of heterogeneous turnover on the dynamics of CD4(+) T-cell infection by HIV is explored. We show that our model can resolve the paradox of high levels of viral replication occurring while only a small fraction of cells are infected.
HIV/AIDS has reached pandemic proportions, and is one of the leading causes of death worldwide. In 2001, the Declaration of Commitment on HIV/AIDS set out several aims with respect to reducing the effect and spread of HIV/AIDS, and an expanded response in low-income and middle-income countries was initiated. Here we examine the potential effect of the expanded global response based on analyses of epidemiological data, of mathematical models of HIV-1 transmission, and a review of the impact of prevention interventions on risk behaviours. Analyses suggest that if the successes achieved in some countries in prevention of transmission can be expanded to a global scale by 2005, about 29 million new infections could be prevented by 2010.
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BACKGROUND: The ongoing development of a vaccine against human papillomavirus (HPV) raises important questions about the impact of various vaccination strategies. METHODS: Two mathematical models are developed to explore the population-level impact of an HPV vaccine. The first model focuses on the infection process and the second on the disease process (specifically, cervical carcinoma and cancer). RESULTS: Both population characteristics (, sexual mixing and rates of sex partner change) and vaccine characteristics affect the steady state prevalence of HPV that would be expected if a vaccine program is implemented. Under a particular set of assumptions, we find that vaccinating both men and women against a specific HPV type would result in a 44% decrease in prevalence of that type whereas vaccinating only women would result in a 30% reduction. We also find that if a vaccine gives protection against some, but not all, high risk types of HPV, the reduction in disease may be less than the reduction in HPV because the remaining high risk HPV types may replace the disease caused by the eliminated types. CONCLUSIONS: A multivalent vaccine containing the majority of disease-causing HPV types would greatly reduce the need for colposcopy, biopsy and treatment. However, it is unlikely that Pap-screening programs would become redundant unless the vaccine is highly effective and coverage is widespread. In contrast to less common infections that are primarily restricted to core groups, targeting the vaccine towards the most sexually active individuals is less effective for a common sexually transmitted infection such as HPV.