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Estimating HIV
Prevalence from the
Swaziland HIV Incidence
Measurement Survey
Rejoice Nkambule, Henry Ginindza, George Bicego,
Deborah Donnell, Jessica Justman, Jason Reed, Ingrid Peterson
and the SHIMS team
Abstract # 142
March 8, 2012
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The Kingdom of Swaziland
*calculated from DHS 2006
Small country in southern Africa
Population: 1.2 million
Demographic Health Survey 2006:
Overall HIV prevalence 31% among
men and women (ages 18-49)*
Highest national HIV prevalence in
the world
Adapted from WorldVision
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Male Circumcision as Part of Swaziland’s
Scale-Up of Combination Prevention Strategy
National combination prevention program:
HIV testing and counseling
PMTCT
Social behavior change communication
ART expansion
Voluntary medical male circumcision
2010: Soka Uncobe (“Conquer through Circumcision”),
the national campaign to scale-up male circumcision
from 8% to 80% of adult men in one year
What will be the reduction in HIV incidence in
Swaziland?
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Primary Objective :
To estimate HIV incidence rates in a household-based,
nationally representative sample of men and women, before
and after accelerated scale-up of HIV prevention programs .
Current Analysis
To estimate HIV prevalence rate in a household-based,
nationally representative sample of men and women.
Swaziland HIV Incidence
Measurement Survey (SHIMS)
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SHIMS Methods
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Select 575 of 2054 Enumeration Areas (EAs)
Randomly select 26 households from each EA
Invite all adults aged 18-49 in households to participate in cross-sectional survey
Invite HIV-uninfected adults to join incidence cohort
SHIMS: Two-stage Cluster
Sampling Design
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Resides or has slept the
night before in selected
household
Age 18-49 years
Able to provide consent
SHIMS Survey: Inclusion Criteria
SHIMS Study team visiting a selected household
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Interviewer-administered questionnaire
HIV counseling and testing 4th generation Determine®
HIV 1/2 Antigen/Antibody Combo
If HIV-positive, refer to care services
If HIV-negative, refer to prevention services
SHIMS Study Procedures
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SHIMS sample weighted to achieve
population representativeness
Weights adjust for sample selection and
differences in non-response
Weighting Methods
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Results
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Total
Selected households 14,950
Participating households 12,597 (84%)
Men Women Total
Eligible household members 10,886 13,414 24,300
No contact made 2445
(22%)
1353
(10%)
3798
(16%)
Refused participation 1362
(13%)
1084
(8%)
2446
(10%)
Participating household
members
7,079
(65%)
10,977
(82%)
18,056
(74%)
SHIMS Survey Participation
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Men Women Total
Age
18-24 37% 35% 36%
25-34 36% 33% 34%
35-49 27% 32% 30%
Education
None 6% 7% 7%
Primary 27% 29% 28%
Secondary 49% 50% 50%
Higher 17% 14% 15%
Married or living with a
partner 36% 51% 44%
Circumcised (self-reported) 15% - -
Swaziland Demographics
(Ages 18-49)
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HIV Prevalence In Swaziland:
HIV+ Test in SHIMS (n= 18,056)
23%
38%
31%
Men Women Total
Perc
ent
HIV
Sero
positiv
e
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2011 HIV PREVALENCE IN SWAZILAND
SHIMS SURVEY (AGES 18-49)
Men: Prevalence by Age Women: Prevalence by Age
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2011 HIV PREVALENCE IN SWAZILAND
SHIMS SURVEY (AGES 18-49)
Men: Prevalence by Age Women: Prevalence by Age
48% in men
aged 35-39
54% in
women aged
30-34
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2006 DHS AND 2011 SHIMS
HIV PREVALENCE IN SWAZILAND (AGES 18-49)
Men: Prevalence by Age Women: Prevalence by Age
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48%
32%
52%
68%
Among HIV-Seropositives:
Knowledge of HIV Status
Unaware Aware
Men Men Women Women
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Self-Reported ART Use
among HIV-Seropositives
*No CD4 data collected therefore results
do not indicate proportion eligible for ART
58%
47% 50%
33% 34% 34%
Men Men Women Women Total Total
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National HIV prevalence remains high at 31%
Overall HIV prevalence stable since 2006
Shift in age-pattern of prevalence points towards
“survival effect” related to ART use at older ages
reduced rate of new infections at younger ages
Half of all HIV+ men are not aware of their status
Evidence for public programs to target HTC for men
Half of individuals aware of their HIV infection are
on ART, irrespective of CD4
Analysis of HIV incidence estimate in progress
Conclusions
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Protocol Team
*Rej oice
Nka m bule
*George Bicego
Naomi Bock
Muhle Dlamini
Deborah Donnel l
Dennis
El lenberge r
Tedd El lerbrock
Wafaa El -Sadr
Jonathan Gr und
*Jess ica Justm a n
Amy Medley
Jan Moore
Emmanuel
Njeuhmel i
*Ja son Reed
Nelis iwe
S ikhosana
ICAP at
Columbia
University
E l izabeth
Barone
Montina Befus
Mar y Diehl
Mark Fussel l
Al l ison
Goldberg
Lesl ie Hor n
Jacquel ine
Maxwell
Joan
Monser rate
Neena Phi l ip
Peter Twyman
Leah Westra
Al l ison Zerbe
It Takes A Village:
Nat’l Ref Laboratory
Hosea Sukati
Sindi Dlamini
All Laboratory Scientists
CDC Atlanta
Anindya De
Joy Chang
Josh DeVos
Yen Duong
Dennis Ellenberger
Al Garcia
Carole Moore
John Nkengasong
Michele Owen
Bharat Parekh
Hetal Patel
Connie Sexton
Barbara Suligoi
Chunfu Yang
CDC Swaziland
Peter Ehrenkranz
Ahmed Liban
Khosi Makhanya
SCHARP
Claire Chapdu
Lynda Emel
Iraj Mohebalian
Lei Wang
Epicentre/Maromi
Health Research
Cherie Cawood
Mark Colvin
David Khanyile
Nomsa Nzama
Phindile Radebe
All Regional Managers
All field teams
ICAP in Swaziland
Alfred Adams
Kerry Bruce
Gcinekile Dlamini
Ndumisi Dlamini
Sindisiwe Dlamini
Henry Ginindza
Sibuse Ginindza
Alison Koler
Yvonne Mavengere
Khudzie Mlambo
Phakamile
Ndlangamandla
Ingrid Peterson
Nicola Pierce
Bhangazi Zwane
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Local And International
Partnership
Kingdom of Swaziland & CSO