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The population impact of ART scale-up on the risk of new HIV infection in rural KwaZulu-Natal, South Africa Frank Tanser Presentation at IAS, Kuala Lampur 02 July 2013. Outline. Background ART coverage and risk of HIV acquisition Population viral load . Global ART scale-up.

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slide1

The population impact of ART scale-up on the risk of new HIV infection in rural KwaZulu-Natal, South AfricaFrank TanserPresentation at IAS, Kuala Lampur02 July 2013

outline
Outline
  • Background
  • ART coverage and risk of HIV acquisition
  • Population viral load
global art scale up
Global ART scale-up

South Africa has the worldwide largest absolute number of patients on ART,

>1.6 million by some estimates

UNAIDS Report on the Global AIDS Epidemic 2012; WHO Universal Access Report 2013; Aaron Motsoaledi 2012

slide4

Study setting

  • Adult HIV prevalence 24%
  • High levels of unemployment and poverty
  • Zulu-speaking population
  • Former homeland under apartheid
slide5

The Africa Centre

Africa Centre for Health and Population Studies

slide6

Adult life expectancy over time

13,060 deaths among 101,286

individuals aged 15 years and older, contributing

a total of 651,350 person-years of follow-up time

Bor, Herbst, Newell, and BärnighausenScience 2013

hiv incidence by age and sex 2004 2010
HIV incidence by age and sex 2004-2010

Females

Males

Tanser, Bärnighausen, Newell CROI 2011

spatial clustering of new hiv infections
Spatial clustering of new HIV infections

Tanser et al CROI. Boston, MA; 2011.

outline1
Outline
  • Background
  • ART coverage and risk of HIV acquisition
  • Population viral load
population based hiv surveillance
Population-based HIV surveillance
  • Since 2003: Population-based HIV surveillance
    • Longitudinal, dynamic cohort
    • Entire adult population living in a contiguous geographical area of 438 km2 under surveillance
    • Annual rounds
    • 75% of those observed to be HIV-uninfected subsequently retest
    • All individuals geo-located

Tanser, Hosegood, Bärnighausen et al. International Journal of Epidemiology 2007

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ART coverage of all HIV-infected individuals 2004-2011

Tanser, Bärnighausen, Grapsa, Zaidi& Newell Science 2013

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Population impact of ART coverage on risk of HIV acquisition (2004-2012)

Survival analysis

> 17,000 HIV-negative individuals followed-up for HIV acquisition over 60,558 person-years

1,573 HIV sero-conversions

Time- (and space-) varying demographic, sexual behavior, economic and geographic controls, including HIV prevalence

p=0.171

P<0.0001

p<0.0001

P<0.0001

Adjusted for age, sex, community-level HIV prevalence, urban vs. rural locale, marital status, >1 partner in last 12 months, and household wealth index

slide13

Population impact of condom use on risk of HIV acquisition (2005-2011)

Adjusted for age, sex, community-level HIV prevalence, urban vs. rural locale, marital status, >1 partner in last 12 months, and household wealth index

Tanser et al, Science, 2013

conclusion
Conclusion
  • We find continued reductions in risk of acquiring HIV infection with increasing ART coverage in this typical rural sub-Saharan African setting
  • However, there is evidence of a “reduction saturation” effect (at coverage of >40%) under treatment guidelines of <350 CD4+ cells/µl
outline2
Outline
  • Background
  • ART coverage and risk of HIV acquisition
  • Population viral load
population community viral load
Population/Community viral load
  • Proposed as:
    • an aggregate measure of the potential for ongoing HIV transmission within a community
    • as a surveillance measure for monitoring uptake and effectiveness of antiretroviral therapy.
slide17

Figure 1

CVC as a measure for assessment of HIV treatment as prevention

Miller, Powers, Smith et al Lancet Infectious Diseases 2013

cvc as a measure for assessment of hiv treatment as prevention
CVC as a measure for assessment of HIV treatment as prevention

“ The issue of selection bias [in community viral load] could be addressed with a population-based survey in a clearly defined target population of all people in a community, including those with and without known HIV infection”

Miller, Powers, Smith et al Lancet Infectious Diseases 2013

objectives
Objectives
  • Asses whether viral loads in this population are randomly distributed in space or whether high or low viral loads tend to cluster in certain areas
  • Assess the degree to which different population viral load summary measures highlight known areas of high incidence
  • (Establish the degree to which different population viral load summary measures predict future risk of new HIV infection in uninfected individuals)
methods
Methods
  • All 2,456 individuals testing positive in the population-based HIV testing conducted in 2011
  • Total number DBS specimens tested was 2,420 (36 specimens excluded due to being insufficient for testing).
  • Of these, 30% (726) were below the detectable limit of 1550 copies/ml(Viljoen et al, JAIDS 2010)
viral load distribution
Viral load distribution

Median viral load = 6428 copies per ml

adjusted hiv acquisition hazard by p revalence category
Adjusted HIV acquisition hazard by prevalence category

Adjusted for age, sex, community-level HIV prevalence, urban vs. rural locale, marital status, >1 partner in last 12 months, and household wealth index

conclusion1
Conclusion
  • To measure transmission potential of a community, any viral load summary index must take into account the size of the uninfected population
  • Population prevalence of detectable virus (PPDV) successfully identified known areas of continued high HIV incidence
  • We propose the PPDV as a simple community-level index of transmission potential
acknowledgements
Acknowledgements
  • The members of the community in Hlabisa sub-district who gave their time to this research
  • Staff of the Africa Centre for Health and Population Studies and the Hlabisa HIV Care and Treatment Programme
  • Colleagues at Africa Centre (Marie-Louise Newell, Till Bärnighausen, Tulio de Oliveira,KobusHerbst, Colin Newell, Jacob Bor, JafferZaidi and many more)
  • Funding
    • Wellcome Trust (Africa Centre for Health and Population Studies)
    • National Institutes of Health grants R01 HD058482-01 and 1R01MH083539-01
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