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Exploring the potential impact of ART in reducing HIV transmission.

Exploring the potential impact of ART in reducing HIV transmission. Geoff Garnett, Jeff Eaton, Tim Hallett & Ide Cremin Imperial College London. Contents. Potential impact of increased treatment at CD4 < 200 and < 350 on spread of infection.

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Exploring the potential impact of ART in reducing HIV transmission.

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  1. Exploring the potential impact of ART in reducing HIV transmission. Geoff Garnett, Jeff Eaton, Tim Hallett & IdeCremin Imperial College London

  2. Contents • Potential impact of increased treatment at CD4 < 200 and < 350 on spread of infection. • Potential impact of pre-exposure prophylaxis (PrEP). • When treatment and when PrEP?

  3. Factors decreasing the role of later stages of HIV infection and the potential of treatment to reduce transmission • Rapid spread and saturation of HIV in the at risk population (i.e. little ongoing spread of infection). • Decreasing number of contacts as a function of time since infection - 1) concurrency leads to more potential contacts early infection; 2) people reducing numbers of partners over time; 3) Saturation in age cohorts • Poor adherence; poor suppression of viral load; treatment failure and resistance. • Slower progression to low CD4 counts. • Increased risk behaviour of those on treatment. • Increased risk behaviour amongst those not on treatment – including susceptibles.

  4. Model - Eaton et al AIDS & Behaviour (In Press): • Transmission model (Stochastic individual based) representing generalised heterosexual epidemic – including: • concurrency in sexual partnerships; • Heterogeneity in propensity to acquire new partnerships; • Transmission risk within partnerships as a function of time since infection. • Movement from high activity to moderate activity and moderate activity to low activity over time. Population size 50,000; seed 1% prevalence; results average of 100 runs.

  5. Transmission risk by stage of HIV infection

  6. Proportion of infections generated as a function of time since infection.

  7. Proportion of transmission by stage of infection as epidemic progresses.

  8. Population size 50,000; seed 1% prevalence; results average of 100 runs.

  9. Generalised epidemic – concurrency driving epidemic CD4< 350 after mean 4.5 years

  10. Slower progression to CD4 <350 More infections in earlier stages. Mean duration to <350 7 years.

  11. Epidemic drive by small (2%) high risk group (prevalence 1.5%) More sensitive to movement from high to low risk.

  12. The first model of PrEP for West Africa • Detailed Representation of PrEP • Detailed patterns of adherence • Targeting • Duration on PrEP • PrEP in Combination Prevention • Treatment for clinical need • Increases in condom use & reductions in numbers of partners • ‘Early’ treatment initiation • PrEP model developed by Tim Hallett and IdeCremin

  13. PrEP for prevention – preliminary results The Mathematical Model • The model captures many important features of HIV transmission in Cotonou: Regular clients Sex workers Men Women

  14. PrEP for prevention – preliminary results • Coverage, Adherence & Duration

  15. “Optimistic”

  16. “Realistic”

  17. For the same number of people staring PrEP, effective targeting to those at most risk can substantially amplify impact. • Effective Targeting Good Targeting Some Targeting No Targeting 10% of population start PrEP

  18. PrEP in Combination Prevention Status quo Intervention to scale (incr. condom use and prompt treatment initiation) + Targeted effective PreP + The missing piece? Numbers based on extrapolation to Urban Benin; *PreP intervention is to 60% of sex workers & clients; 70% efficacy and 80% adherence, for 10 years. ** The missing piece required to reduce incidence by 90% in 2031 and eventually stop the epidemic is a 60% efficacy vaccine delivered to half the population.

  19. 91%* 52%* 13%**

  20. PrEP and ART initiation at CD4<200 ART initiation at CD4<350 Domain where PrEP averts more infections that treatment in couples. Need PreP effectiveness>60%

  21. PrEP and ART initiation at CD4<350 ART initiation immediately Domain where PrEP averts more infections that treatment in couples. Need PreP effectiveness>85%

  22. Conclusions • Good coverage of those with CD4 < 200 could avert around 25% of new infections and with CD4 < 350 a further 15% could be averted. • Reductions in risk behaviour associated with treatment could improve this; increases in risk behaviour could undermine it. • PrEP can reduce incidence but needs high efficacy, coverage and adherence - and needs appropriate targeting to be efficient. • Earlier treatment reduces role of PrEP; its effectiveness per partnership relative to treatment of the infected partner determines how useful it would be in discordant couples.

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