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

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Presentation on theme: "ARV-Based Prevention: Perspective from Epidemiology & Modelling Tim Hallett Imperial College London."— Presentation transcript:

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 Programme Uptake Clinical Care Effectiveness and feasibility studies Biology

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 Power et al. The Lancet, 2011 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?

6 Eaton et al., Forthcoming 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. Probability of reducing HIV incidence by >60%:

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

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

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

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

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

12 PrEP (65% efficacy) to 60% of 15- 24 year old men and women. + CIRCUMCISION….?

13 Baseline HIV prevalence & mapping HBTC-Plus Implemented The Challenge of Measurement HIV incidence measurement Behaviour change Expedited referral for treatment Circumcision +Treatment at all CD4 Alsallaq et al., Forthcoming

14 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?

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


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