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ARV-Based Prevention: Perspective from Epidemiology & Modelling

ARV-Based Prevention: Perspective from Epidemiology & Modelling. Tim Hallett Imperial College London. 96% reduction in transmission in couples may not translate into a 96% reduction in population level HIV incidence. Can we talk about “elimination”. Is this above or below R0=1?.

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ARV-Based Prevention: Perspective from Epidemiology & Modelling

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  1. ARV-Based Prevention:Perspective from Epidemiology & Modelling Tim Hallett Imperial College London

  2. 96% reduction in transmission in couples may not translate into a 96% reduction in population level HIV incidence. Can we talk about “elimination”. Is this above or below R0=1?

  3. How many infections are generated by a newly-infected person before they could be initiated on ART? Network Clinical Care Programme Uptake Biology • Effectiveness and feasibility studies

  4. “Test and Treat” intervention making different assumptions about population risk behaviours. Some models assume this.... ... But others assume this. Dodd et al., AIDS 2010

  5. Powers et al. estimate large contribution of early HIV infection…… And that infections are generated so rapidly after infection that, elimination not possible with treatment to chronic infection only. • Questions: • Influence assumptions about sexual risk behaviours? • Influence of assumed high and variable infectiousness during early HIV infection? Power et al. The Lancet, 2011

  6. Probability of reducing HIV incidence by >60%: • To get a 60% reduction in incidence: • 90% are treated, irrespective of CD4 cell count. • Sufficient frequency of testing such that 60% within 1 years of infection. • 1% of patient drop out • 87% viral suppression within 6 months of initiation. Eaton et al., Forthcoming

  7. Drop-out rate: 1% per year Drop-out rate: 7.5% per year Eaton et al., Forthcoming

  8. What else? Combination Treatment and PrEP. 80% Coverage ART (CD4<200) No PrEP 80% Coverage ART (half at CD4<350) PrEP to 40% Young People 80% Coverage ART (all at CD4<350) PrEP to 80% of Young People 80% Coverage ART (Any CD4) PrEP to 80% of Population Cremin et al., Forthcoming

  9. 80% Coverage ART (CD4<200) 80% Coverage ART (Any CD4) 80% Coverage ART (half at CD4<350) 80% Coverage ART (all at CD4<350) No PrEP No PrEP No PrEP No PrEP 80% Coverage ART (all at CD4<350) 80% Coverage ART (half at CD4<350) 80% Coverage ART (CD4<200) 80% Coverage ART (Any CD4) PrEP to 40% Young People PrEP to 40% Young People PrEP to 40% Young People PrEP to 40% Young People 80% Coverage ART (all at CD4<350) 80% Coverage ART (Any CD4) 80% Coverage ART (half at CD4<350) 80% Coverage ART (CD4<200) PrEP to 80% Young People PrEP to 80% Young People PrEP to 80% Young People PrEP to 80% Young People 80% Coverage ART (Any CD4) 80% Coverage ART (CD4<200) 80% Coverage ART (all at CD4<350) 80% Coverage ART (half at CD4<350) PrEP to 80% of Population PrEP to 80% of Population PrEP to 80% of Population PrEP to 80% of Population Cremin et al., Forthcoming

  10. KZN, South Africa Early ART + PrEP to any age Early ART + PrEP to young people Early ART ART < 350 + PrEP to 80% young people ART <350 ART <200 ART only ART + PrEP to young people ART + PrEP to any age.

  11. KZN, South Africa Early ART ART <350 + PrEP to young people ART <350 ART <200 ART only ART + PrEP to young people ART + PrEP to any age.

  12. The potential questions about the impact of treatment on prevention are MANY. • Impact will depend on myriad factors, so it will be have to be an INTERDISCIPLINARY research effort. • New data will keep on moving us from “What If..?” speculation to a “What now?” precise set of questions. • Not a silver bullet, so what are the smart COMBINATIONS?

  13. Thanks to... Imperial College London Geoff Garnett, Simon Gregson IdeCremin, AnnickBourquez, Gabriela Gomez, Jeff Eaton, Pete Dodd, John Williams, Christophe Fraser UNAID & WHO Bernhard Schwartlander Peter Ghys Kevin O’Reilly University of Washington Connie Celum, RamziAlsallaq, Jared Baeten, Jim Hughes, Weill-Cornell Laith Abu-Raddad HiamChemaitelly LSHTM Peter Piot Georgetown Mark Dybul Funded by: The Wellcome Trust, Bill & Melinda Gates Foundation, NIH

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