K. Jean, P. Lissouba, D. Taljaard, R. Rain-Taljaard, B. Singh, J. Bouscaillou, G. Peytavin, R. Sitta, S.G. Mahiane, D. Lewis, A. Puren, B. Auvert

Inserm CESP U1018, Villejuif, FranceUniversité Versailles Saint-Quentin-en-Yvelines, Versailles, FranceCHAPS, Johannesburg, South AfricaNational Institute for Communicable Diseases, Johannesburg, South Africa

HIV incidence among women is associated with their partners' circumcision status in the township

of Orange Farm, South Africa (ANRS-12126)

Melbourne – July, 25th 2014

Introduction- The effect of VMMC roll-out on HIV among women

Background – The effect of VMMC on HIV among men• 3 RCTs documenting a protective effect of VMMC among men• Recommended by WHO-UNAIDS since 2007• Effect of roll-out demonstrated among men

(Auvert et al, Plos Med 2013)

An effect on HIV among women?• No direct effect observed in epidemiological studies

(Weiss et al, Lancet ID 2009)

• An indirect effect through reduced exposure?• Predicted by modelling studies

(Williams et al, Plos Med 2006; Njeuhmeli et al, Plos Med 2011)

VMMC: Voluntary Male Medical Circumcision RCT: Randomized Controlled Trial

2

• To assess the association between their partner’s circumcision status and HIV incidence among women in Orange Farm (South Africa)

Objective

Context - The ANRS « Bophelo Pele » project • Orange Farm: Township of ~110,000 adults

• Since 2007: roll-out of free VMMC

VMMC: Voluntary Male Medical Circumcision

3

ORANGE FARM

Context (2) - The ANRS « Bophelo Pele » project

Auvert et al, Plos Med 2013

• MC prevalence increased from 11% in 2007 to 53% in 2011

4

Context (3) - The ANRS « Bophelo Pele » project • HIV prevalence reduced by ~50% among circumcised men

Auvert et al, Plos Med 2013

5

Data collected among women: 3 independant surveys (2007-2010-2012)

• Questionnaire: age, ethnic group, religion, occupation, age at first sexual intercourse, alcohol consumption, education, ever having been married, number of lifetime partners, consistent condom use

• Blood sample: HIV

Methods (1) – Surveys6

Pooled sample• N= 4538 women (15-49 y) having ever had sexual intercourse

Methods (2):Modelling HIV incidence from observed age-specific prevalence

• A classical mathematical deterministic compartmental modeling approach (Gregson et al, AIDS 1996; Williams et al, Stat Med 2001)

• Finding the age-incidence function that best fits the observed age-prevalence curve

• Use of propensity score weigthing to account for other covariates:

survey, age, ethnic group, religion, occupation, age at first sexual intercourse, alcohol consumption, education, ever having been married, number of lifetime partners, consistent condom use

3 steps in the modelling process

1. Assuming a parametric age-incidence function

2. Calculating age-specific prevalence from parametric incidence

3. Fitting the predicted age-specific prevalence to the observed age-specific prevalence

→ Estimating the incidence parameters→ Estimating incidence rate

→ Computing 95% confidence interval (Bootstrap)

7

N= 4538 women (15-49 y) having ever had sexual intercourse

n=1363 (30.0%) women having had only circumcised partners (HHOCP)

HIV prevalence rate : 22.4% [20.2% - 24.6%]

n=3175 (70.0%) other women

HIV prevalence rate : 36.6% [35.0% - 38.3%]

0

10

20

30

40

50

60

15–19 20–24 25–29 30–34 35–39 40–49

Age group (years)

HIV

pre

vale

nce

(%)

All partners circumcised

Other

Polynomial (Other)

Polynomial (All partnerscircumcised)

aPRR: adjusted Prevalence Rate Ratio (computed with Poisson regression)

aPRR: 0.85 [0.76-0.95]Reduction: 15% 2[5%-24%]

8Results (1) – HIV prevalence among women

Results (2) – Fitting age-specific HIV prevalence9

0

0.2

0.4

15 20 25 30 35 40 45

Age (years)

HIV

pre

vale

nce

rate

0

0.2

0.4

15 20 25 30 35 40 45

Age (years)

HIV

pre

vale

nce

rate

Women HHOCP: n=1363

Other women: n=3175

HHOCP: Having Had Only Circumcised Partners

Results (3) – Estimating HIV incidence10

0

0.2

0.4

15 20 25 30 35 40 45

Age (years)

HIV

pre

vale

nce

rate

0

0.2

0.4

15 20 25 30 35 40 45

Age (years)

HIV

pre

vale

nce

rate

Women HHOCP: n=1363

Other women: n=3175

HHOCP: Having Had Only Circumcised Partners

0

0.02

0.04

0.06

14 19 24 29 34 39 44 49

Age (years)

HIV

inci

denc

e ra

te (/

y)

Normal line: Women HHOCPBold line: Other women

(95% bootstrapped confidence intervals)

Results (4) – Effect on HIV incidence11

0

0.2

0.4

15 20 25 30 35 40 45

Age (years)

HIV

pre

vale

nce

rate

0

0.2

0.4

15 20 25 30 35 40 45

Age (years)

HIV

pre

vale

nce

rate

Women HHOCP: n=1363

Other women: n=3175

HHOCP: Having Had Only Circumcised Partners

0

0.02

0.04

0.06

14 19 24 29 34 39 44 49

Age (years)

HIV

inci

denc

e ra

te (/

y)

Normal line: Women HHOCPBold line: Other women

(95% bootstrapped confidence intervals)

Incidence rates among 15-49 y• Women HHOCP: 0.032 [0.027-0.037] /py• Other Women: 0.039 [0.036-0.042] /py

Þ Incidence Rate Ratio: 0.83 [0.69-0.99]

Þ Reduction: 16.9% [1.1%-31.0%]

Among 15-29 yÞ Reduction: 20.3% [5.8%-33.8%]

Discussion12

Main finding• Reduced HIV incidence among women having only circumcised

partners

Interpretation• Lower exposure due to a lower level of HIV among circumcised

men

Limitations• Direct or indirect effect?• HIV incidence modelled, not measured

Overview of results on VMMC roll-out obtained in Orange Farm (2007-2014)

Among men• VMMC uptake can be rapid and large• VMMC is not statistically associated with condom use• Circumcised men have a lower risk of prevalent HIV infection• Circumcised men have a lower risk of incident HIV infection (BED assay)

Among women• Most women are in favor of VMMC• Most women prefer circumcised men• Partner’s circumcision status is not statistically associated with condom use• Women having only circumcised partners have a lower risk of lower risk of

prevalent HIV infection• Women having only circumcised partners have a lower risk of incident HIV

infection (modelled)

VMMC: Voluntary Male Medical Circumcision

Auvert et al, Plos Med 2013

Auvert et al, CROI 2014; AIDS 2014

13

Aknowledgments

We thank all participants who took part in this study and the whole community of Orange Farm

Portia Ntshangase Josephine Otchere-DarkoDino RechThabile SekhukhuneDaniel Shabangu Gaph Sipho PhatediYvon de la SoudièreBrian Williams

Muhammad BarmaniaScott BillyAlexandre BlakeMale Alina Chakela Ewalde CutlerSasha FradeAgenda GumboMohamed Haffejee

Fikile KateBongiwe Klaas Paul LoubetVenessa MasekoAudrey MkhwanaziBantu Mupompa Cynthia NhlapoGrace Nomsa Nhlapho