CROI 2018 Abstract eBook

Abstract eBook

Poster Abstracts

Poster Abstracts

1155 ASSESSING THE UTILITY OF THE TIPPING POINT RATIO FOR MONITORING ART PROGRAM SUCCESS Simon de Montigny 1 , Marie-Claude Boily 2 , Benoît R. Mâsse 1 , Kate M. Mitchell 2 , Dobromir Dimitrov 3 1 Université de Montréal, Montreal, QC, Canada, 2 Imperial College London, London, UK, 3 Fred Hutchinson Cancer Research Center, Seattle, WA, USA Background: The tipping point ratio (i.e. theoretical TPR), defined as the yearly ratio of new HIV infections to the net increase in HIV+ individuals on antiretroviral therapy (ART), has been used to compare ART scale-up efforts across countries and measure their progress toward HIV elimination. However, in the literature, estimates of TPR are often based on a definition, using new ART initiations as the denominator (i.e. practical TPR), which is easier to estimate. We analyze the utility of TPR, theoretical and practical, to evaluate the progress of ART rollout using different definitions under various epidemic conditions. Methods: We developed a compartmental model of HIV transmission and ART rollout in South Africa, calibrated to 2012 epidemic data and reflecting expansion to universal treatment in 2017. We used Monte Carlo filtering to select 1000 simulations which represented uncertainty in base-case epidemic conditions. We simulated scenarios in which the theoretical TPR is targeting a fixed value between 0.6 and 1.8 over 2020-2024 using compensation for losses of individuals on ART over time (due to deaths and interrupted ART) and different ART access strategies by stage of HIV progression (late or early ART initiation). We compared the reduction in HIV incidence relative to the base-case epidemic in 2024 as function of the practical or theoretical TPR (averaged over 2020-2024) and ART coverage in 2024. Results: Results show that the same HIV incidence reduction (35%) can be achieved with a wide range of TPR (theoretical TPRs 0.68-1.58; practical TPRs 0.42-0.72). Practical TPR which counts ART compensation as new initiations yields lower incidence reduction for the same value as theoretical TPR, e.g. TPR = 0.8 has 19-30% incidence reduction under practical definition and 29-54% under theoretical definition (Fig A). Simulated ART coverage achieved in 2024 (Fig B) is a better predictor of HIV incidence reduction (with Pearson’s r = 0.85) than theoretical TPR (Pearson’s r = -0.79). The difference between early and late ART initiation is small due to ART compensation. Conclusion: Our analysis suggests some confusion when TPR is used in the literature. The practical TPR likely overestimates the progress of ART programs and often produces TPR values below 1. Although a more reasonable indicator, the theoretical TPR is technically more difficult to estimate and should be supplemented with ART coverage data to judge the progress of ART programs.

1156 PREDICTING THE PROBABILITY AND TREATMENT COSTS OF ELIMINATING HIV IN BOTSWANA Katie Sharp , Sally Blower University of California Los Angeles, Los Angeles, CA, USA Background: Botswana has one of the most severe HIV epidemics worldwide, where ~24% of adults are infected with HIV. In 2002, Botswana was the first African country to roll out anti-retroviral treatment. Dolutegravir was introduced into first-line regimens in 2016 and all individuals became treatment eligible, regardless of CD4 cell count. We use modeling to reconstruct the epidemiological impact of treatment from 2002 to 2016. We then predict whether treatment, coupled with preventative interventions, will enable Botswana to reach the WHO elimination threshold of 1 new HIV infection per 1,000 individuals/year, and both UNAIDS’s treatment targets, by 2030. We also estimate cumulative drug costs. Methods: We use a transmission model, calibrated and parameterized with data from Botswana. We model both first and second-line therapies; including acquired and transmitted drug resistance. We conduct an uncertainty analysis and a multivariate sensitivity analysis based on response hypersurface modeling. We investigate the effect of treatment rates, viral suppression rates (VSR) (reflecting both efficacy and adherence), and the effectiveness (reflecting both efficacy and coverage) of interventions. Results: We find the WHO elimination threshold will only be reached by 2030 if very stringent conditions are met: the effectiveness of interventions is > 55%, and the VSR for first-line regimens is > 95%. UNAIDS 90-90-90 goals will be reached if the VSR for second-line regimens is > 95%. The number of individuals needing treatment will increase steeply to ~2021, then stabilize and remain approximately constant to 2030. However, the proportion needing first-line regimens will decrease, and the proportion needing second-line regimens will increase; by 2030, ~25% of patients may need second-line regimens. Total cumulative drug costs for second-line regimens will be determined by the VSR to first-line regimens. If this is extremely high (95%), cumulative costs for second-line drugs will be ~70 million; if the VSR is only moderate (70%), costs will be approximately double. Conclusion: Botswana will only be able to eliminate HIV by 2030 if adherence to first-line regimens is extremely high, and extremely effective interventions are also implemented. A high level of adherence is the key determinant in

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