1. What do models estimate to be the impacts on HIV incidence of various percentages of people with HIV on ART ? National AIDS Trust Treatment as Prevention Seminar 25 th November 2010 Southwark Cathedral, London

2. Death rate ~ 5.2 per 1000 person years If early ART reduces risk by 50% => risk reduction 2.6 / 1000 person years 1 death averted per 385 person years of ART - Will initiation of ART in people with CD4 count > 350 / 500 be funded ? - Assessment of cost-effectiveness requires a model that takes account of reductions in incidence Policy of initiation of treatment at CD4 counts > 350 may require cost justification Study group on Death Rates at High CD4 count in ART naïve people. Lancet 2010

3. Montaner et al, Lancet 2010 Association between number on HAART and new HIV diagnoses

4. Association between mean “community” viral load and new HIV infections Das et al, PLOS One 2010

5. ~ 90% of gay men have been tested for HIV High rates of HIV testing but rising incidence in gay men in Australia Wand et al, 2010, Prestage et al, 2008

6. Granich et al, Lancet 2008 1980 2000 2020 2040

7. Models of the impact of ART on transmission ART can function as an effective prevention tool, even with high levels of drug resistance and risky sex Velasco-Hernandez JX, Gershengorn HB, Blower SM. Lancet Inf Dis 2002 The use of treatment as prevention has the potential to reduce HIV epidemics only if consistent condom use is maintained. Wilson et al, Lancet 2008 ART is predicted to have individual and public health benefits...but the benefit can be lost by residual infectivity or …… sexual disinhibition... Abbas UL, Anderson RM, Mellors JW. JAIDS 2006 ART cannot be seen as a direct transmission prevention measure, regardless of the degree of coverage Baggaley RF, Garnett GP, Ferguson NM. PLoS Med 2006 Expansion of HAART (amongst those with CD4 < 200 / < 350) led to substantial reductions in the growth of the HIV epidemic and related costs Lima et al JID 2008

8. Predicted effects on HIV incidence depend on assumptions on: - Testing coverage and frequency - Effect on individual health of early ART - Feasibility of identifying people in primary infection - Durability of adherence / viral load suppression on ART - Development and transmission of drug resistant virus - Change in unprotected sex due to HIV diagnosis - Change in unprotected sex due to viral suppression - Extent of reduction in infectivity with ART

9. Fixed variables Variables updated at infectionover time Years from infection 0 0.25 0.5 0.75 1.00 1.25 Calendar date Age at infection Gender Primary resistance Calendar date Age Viral load CD4 count Risk of AIDS / death Use of specific ARVs Resistance mutations HIV synthesis model Creates a ‘dataset’ of the course of infection and therapy for individual simulated patients.

10. HIV progression in absence of ART PCP prophylaxis Gender Age Viral load CD4 count AIDS Death from HIV Death from other cause Phillips et al, HIV Medicine 2007; Lancet 2008 Assumed 1.5- fold increased

11. Effect of ART CD4 count Phillips et al, HIV Medicine 2007, Lancet 2008 Death from HIV* Acquisition of new resistance mutations Time on current regimen Viral load CD4 counts AIDS* *influenced by age and PCP prophylaxis also Current adherence # Active drugs in regimen Switch to next line of ART Failure of current line of ART

12. Effect of stopping ART CD4 count Phillips et al, HIV Medicine 2007, Lancet 2008 Death From HIV* Viral load CD4 counts AIDS* Probability of resuming ART Time off ART Loss from majority virus of acquired resistance mutations *influenced by age and PCP prophylaxis also Other processes include: - Loss to follow-up - Substitution of drugs due to toxicity

13. Fit to observed data Phillips et al, HIV Medicine 2007 ObservedModelled Natural history AIDS by 10 years46%48% Median CD4 count at diagnosis of AIDS~ 40 35 % dead by 1 year from initial AIDS40%45% Effect of ART Virologic failure by 7 years 27%29% >1 resistance mutation by 7 yrs 19%25% Rate of viral rebound in those with < 50 cps/mL3-6% per yr6% per yr >1 resistance mutation to 3 classes by 6 yrs 4% 6% Mean CD4 count increase at 3 years273 270

14. Additional variables updated over time Years from 1985 1985 1985.25 1985.5 1985.75 1986.00 1986.25 e.g. Calendar date Infection with HIV Sexual risk behaviour: - Long term partnership status - Number of new partners HIV transmission synthesis model: Heterosexual epidemic in southern Africa Creates a ‘dataset’ of the lifetime experiences of ~50,000 people in a population, aged over 15.

15. Number of new partners Gender Risk of HIV infection in uninfected subject Probability of HIV infection Long term partner HIV+ Number of new partners who are HIV+ Number of new partnerships formed by HIV+ people Current viral load of infected partner Subject Concurrent HIV+ population Incidence and prevalence of HIV in people with long term partnerships Long term partnership status Age Risk of infection also depends on current STI

16. Comments - In southern African heterosexual epidemic setting: Assuming that unprotected sex with long term partners will reduce upon HIV diagnosis, a policy of frequent testing is likely to be beneficial for incidence, regardless of whether ART initiation threshold is CD4 200, CD4 350 or higher. - Plans to adapt this model for MSM in UK

17. Conclusion Models so far have demonstrated that intensive HIV testing with early ART initiation can, in principle, lead to substantial reductions in incidence if certain conditions hold. Models required now are ones that will give as realistic and detailed assessment as possible of the predicted impact of frequent testing and early ART on HIV incidence, and thus enable estimation of cost-effectiveness of the approach.

18. Acknowledgements Valentina Cambiano Geoff Garnett Deenan Pillay Marco Vitoria Diane Bennett Deenan Pillay Jens Lundgren Current funding from National Institute for Health Research Programme Grant