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. 2010 Mar 13;24(5):729-35.
doi: 10.1097/QAD.0b013e32833433fe.

Examining the promise of HIV elimination by 'test and treat' in hyperendemic settings

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Examining the promise of HIV elimination by 'test and treat' in hyperendemic settings

Peter J Dodd et al. AIDS. .

Abstract

Background: It has been suggested that a new strategy for HIV prevention, 'Universal Test and Treat', whereby everyone is tested for HIV once a year and treated immediately with antiretroviral therapy (ART) if they are infected, could 'eliminate' the epidemic and reduce ART costs in the long term.

Methods: We investigated the impact of test-and-treat interventions under a variety of assumptions about the epidemic using a deterministic mathematical model.

Results: Our model shows that such an intervention can substantially reduce HIV transmission, but that impact depends crucially on the epidemiological context; in some situations, less aggressive interventions achieve the same results, whereas in others, the proposed intervention reduces HIV by much less. It follows that testing every year and treating immediately is not necessarily the most cost-efficient strategy. We also show that a test-and-treat intervention that does not reach full implementation or coverage could, perversely, increase long-term ART costs.

Conclusion: Interventions that prevent new infections through ART scale-up may hold substantial promise. However, as plans move forward, careful consideration should be given to the nature of the epidemic and the potential for perverse outcomes.

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Figures

Figure 1
Figure 1. The impact of Test and Treat interventions depends on epidemiological context
Panels show impact of ART on incidence (percentage reduction) as contour-lines, with respect to coverage of the intervention (vertical axis), the mean years after infection that treatment is begun (horizontal axis), and the corresponding mean CD4 count at initiation (horizontal axis) and required interval between tests (horizontal axis). Panels show three types of epidemiological context: (a) Scenario A - Even risk distribution; (b) Scenario B - Heterogeneous risk distribution with random mixing; (c) Scenario C - Heterogeneous risk distribution with assortative mixing.
Figure 2
Figure 2. Test and Treat impact and costs
(a) Reduction in incidence (%) versus mean interval between HIV tests (years). (b) Person-years on ART required at equilibrium (as fraction of population) versus mean interval between HIV tests (years). (c) Number of tests per year at equilibrium (assuming population of 5 million adults) versus mean interval between HIV tests (years). Parameters values are for ‘Scenario B’ (described in the text). Note that treatment-years person-years is approximately equal to T/N, T is the number people on treatment that year, in a population of size N.
Figure 3
Figure 3. Test and Treat cost-efficiency
Cost-efficiency of the intervention (reduction in incidence divided by ART and HIV testing costs) of test and treat interventions reaching 30, 50 or 80% of the population, in epidemiological context Scenario A (panel a) and Scenario C (panel b). Dashed vertical lines indicate optimal strategy for each level of coverage.

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