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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

ARV-Based Prevention:Perspective from Epidemiology & Modelling

Tim Hallett

Imperial College London

slide2

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?

slide3

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
slide4

“Test and Treat” intervention making different assumptions about population risk behaviours.

Some models assume this....

... But others assume this.

Dodd et al., AIDS 2010

slide5

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

slide6

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

slide7

Drop-out rate: 1% per year

Drop-out rate: 7.5% per year

Eaton et al., Forthcoming

slide8

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

slide9

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

slide10

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.

slide11

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.

slide12

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?
slide13

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