PROJECT ACCEPT PERFORMANCE FEEDBACK
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Transcript of PROJECT ACCEPT PERFORMANCE FEEDBACK
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NIMH Project Accept
(HPTN 043)A CLUSTER-RANDOMIZED TRIAL OF COMMUNITY
MOBILIZATION, MOBILE HIV TESTING, POST-TEST SUPPORT
SERVICES, AND REAL-TIME PERFORMANCE FEEDBACK FOR
HIV PREVENTION IN ENTIRE COMMUNITIES
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10 Years Work
presented in
10 MinutesA CLUSTER-RANDOMIZED TRIAL OF COMMUNITY
MOBILIZATION, MOBILE HIV TESTING, POST-TEST SUPPORT
SERVICES, AND REAL-TIME PERFORMANCE FEEDBACK FOR
HIV PREVENTION IN ENTIRE COMMUNITIES
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The AIDS Free Generation
Depends on You
(Mike Cohen)A CLUSTER-RANDOMIZED TRIAL OF COMMUNITY
MOBILIZATION, MOBILE HIV TESTING, POST-TEST SUPPORT
SERVICES, AND REAL-TIME PERFORMANCE FEEDBACK FOR
HIV PREVENTION IN ENTIRE COMMUNITIES
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HIV PREVENTION NEEDS TO
Encourage
widespreadHIV testing
Behavioralrisk reduction
Mobilize
Communities
Accessstrategies
and devices
Behavioralrisk reduction
Access careand treatment
HIV Uninfected HIV Infected
Providesupport
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NIMH PROJECT ACCEPT (HPTN 043) STUDY SITES
Vulindlela, South Africa
Chiang Mai, Thailand
Kisarawe, Tanzania
Soweto, South Africa
Mutoko, Zimbabwe
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Communities were randomized to 2 approaches
Mobilization, Testing, Support, and
Access to Services
Community-based VCT(CBVCT N = 24 communities)
1. Community preparation,outreach, mobilization
2. Mobile VCT
3. Post-test support services
a. Stigma-reduction skills training
b. Coping effectiveness training
c. Ongoing counseling
4. Ongoing data feedback and field
adjustments
Standard VCT(SVCT N = 24 communities)
1. Clinic-based VCT2. Standard VCT services
normally provided in that
community
Van Rooyen et al, AIDS and
Behavior, 2012
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The joint efforts that make Project AFIKI
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THE COMPLETE INTERVENTION PACKAGE
FOR COMMUNITY BASED VCT (CBVCT)
Community
Mobilization
Mobile VCTbrought to
where peopleare
TestingSupportServices
TSS club guests receive
stigma and HIV/AIDS
info: Mobilized for testing
Participants receive risk
reduction information andmobilize partners for testing
Community
members mobilized:Social networks,
door-to-door, mob
talks, community
events
Social networks are
identified and secured forinformation sessions
Update from community
members around
caravan
Participants tested, move on to
TSS for support and referrals
DATA
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Study Design: Timeline
Pilot studies in
Zimbabwe and Thailand
Community
Selection,Recruitment,
Funding
Baseline
Survey
2001 20042003 2005 2006 2007 20082002 2009 2010 2011
INTERVENTION
CommunityRandom-
izationPost-
Intervention
Assessment
Qualitative Cohort
Probability sample of 18-32 year olds Survey only
Total N =48 communities24 intervention / 24 control
Assessment of a random sample of18-32 year olds in each intervention andcontrol community
Behavioral survey Biologic assays to estimate HIV incidence
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The goal was to affect the entire community and not
just a study cohort
Anyone in the community could participate in any of
the community events including mobile testing
Outcomes were evaluated at the end of the
intervention among a probability sample of 54,326
community residents 18 to 32 years of age (89%
response rate)
Incident infections were estimated using a multi-assay
algorithm (MAA) developed by the HPTN Core Lab at
Hopkins and the Core Statistical Unit at SCHARP and
Charles University (Prague)
Primary outcome = HIV incidence,
evaluated at the community level
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ALL OF THIS RESULTED IN:
86,720 HIV tests
50,000 individuals
when repeat tests are excluded
69,987
in CBVCT
communities
7,636
in SVCT
communities
140,755 post-test support visits
Sweat et al, Lancet ID, 2011
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There has been gender equity in uptake for CBVCT
47.8 45.9
59.8
50.2 47.1
52.2 54.1
40.2
49.8 52.9
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Thailand Zimbabwe Tanzania Soweto Vulindlela
Percent
Male Female
Lancet Infectious Diseases, 2011
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We Have Reached a Relatively Young Group of Clients
36
28
30
28
21
05
10
15
20
25
30
35
40
Thailand Zimbabwe Tanzania Soweto Vulindlela
Me
dianAge(Years)
Project Sites
Lancet Infectious Diseases, 2011
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Proportion of the Population
Using Mobile VCT
Country CBVCT
SVCT Ratio
South Africa--Soweto 17% 1% 14.8
South Africa--Vulindlela 20% 1% 16.8
Zimbabwe 25% 8% 3.07
Tanzania 21% 7% 2.93
Thailand 35% 1% 35.0
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Testing Uptake: 12 Months
Effecta
95% CI p-value
All sites 1.06 1.03 1.09 0.0001
Thailand 1.09 1.02 1.16Zimbabwe 1.07 1.00 1.13
Tanzania 1.05 1.01 1.09
Vulindlela 1.07 0.97 1.18
Soweto 1.01 0.88 1.15
SVCT-B SVCT-P CBVCT-B CBVCT-P Ratio P-Value
Overall 16% 26% 14% 32% 1.25 0.0003
Thailand 17% 15% 17% 24% 1.56
Zimbabwe 7% 26% 3% 32% 1.20
Tanzania 15% 32% 16% 37% 1.13
Vulindlela 20% 35% 19% 40% 1.14
Soweto 33% 37% 31% 41% 1.10
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The interventionincreased HIV testing by
45% among men and
15% among women
Improvements in testing
rates were highest among
men and young people
Many women had been
tested in antenatal clinics
but the increase was still
significant
Increased
testingespecially
among men
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Testing Uptake Men: 12 Months
Effecta
95% CI p-value
All sites 1.06 1.03 1.09 0.0001
Thailand 1.09 1.02 1.16Zimbabwe 1.07 1.00 1.13
Tanzania 1.05 1.01 1.09
Vulindlela 1.07 0.97 1.18
Soweto 1.01 0.88 1.15
SVCT-B SVCT-P CBVCT-B CBVCT-P Ratio P-Value
Overall 8% 16% 9% 24% 1.45
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Testing Uptake Women: 12 Months
Effecta
95% CI p-value
All sites 1.06 1.03 1.09 0.0001
Thailand 1.09 1.02
1.16Zimbabwe 1.07 1.00 1.13
Tanzania 1.05 1.01 1.09
Vulindlela 1.07 0.97 1.18
Soweto 1.01 0.88 1.15
SVCT-B SVCT-P CBVCT-B CBVCT-P Ratio P-Value
Overall 22% 34% 19% 39% 1.15 0.01
Thailand 21% 20% 21% 28% 1.56
Zimbabwe 10% 37% 4% 36% 1.20
Tanzania 23% 44% 26% 45% 1.03
Vulindlela 28% 46% 25% 47% 1.03
Soweto 45% 46% 45% 54% 1.17
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Prevalence and Estimated IncidenceCountry Prevalence
Incidence Population Size
South Africa--Soweto 14.1 1.2152,000
(8 communities)
South Africa--Vulindlela 30.8 3.967,200
(8 communities)
Zimbabwe 12.9 0.993,300
(8 communities)
Tanzania 5.9 0.854,900
(10 communities)
Thailand 1.0
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Incidence Differences:
Intervention vs. Control CommunitiesSubgroup
(N of Incident Infections)Effect
a95% CI p-value
All participants 49 (464) 0.86 0.73 1.02 0.0822
Women (316)
Men (148)
0.88
0.81
0.73 1.06
0.57 1.15
0.1691
0.1934
Age 18-24 years (271)
Age 25-32 years (193)
0.98
0.75
0.80 1.22
0.54 1.04
0.8554
0.0777
Women, age 18-24 years (201)Women, age 25-32 years (115)
1.000.70
0.78 1.280.54 0.90
0.98330.0085
Men, age 18-24 years (69)
Men, age 25-32 years (79)
0.95
0.78
0.64 1.40
0.41 1.47
0.6934
0.3914
a
Relative risk of infection (CBVCT vs. SVCT); weighted incidence ratio
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The intervention producedan almost 4-fold increase
in the detection of
previously undiagnosed
HIV cases
This was true at all of the
3 sites where differential
utilization could be
assessed
Increased
HIV CaseFinding
Sweat et al, Lancet ID, 2011
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Number of sexual partnersreported by HIV-infected
individuals lower by 8% 95% CI:1% - 15%, p = 0.03
Number of sexual partners
among HIV-positive men
lower by 18% (95% CI = 5% to 28%,p = .009).
Reductions
in SexualRisk
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Multiple sexual partnerslower by 30% 95% CI: 0.54 0.92, p = 0.01
Multiple sexual partnersamong HIV-infected men
lower by 29% 95% CI: 0.57to 0.89, p = .0006
Reductions
in SexualRisk
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No increase observed innegative effects of the
intervention in
communities
No increasein violence towards women
as a result of learning
their HIV status
TheIntervention
was Safe
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HIV PREVENTION NEEDS TO
EncouragewidespreadHIV testing
Behavioralrisk reduction
Mobilize
Communities
Accessstrategies
and devices
Behavioralrisk reduction
Access careand treatment
HIV Uninfected HIV Infected
Provide
support
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NIMH Project Accept (HPTN 043)demonstrated that it is possible to:
Produce modest reductions in
HIV incidence
This suggests that the additionof other components referraland maintenance in care, earlytreatment, male circumcision,pre-exposure prophylaxis might be successful in achievinggreater reductions in HIV
incidence in entire communities.
Implications
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Principal Investigators
Soweto, South Africa: Thomas Coates / Glenda Gray
Tanzania: Michael Sweat / Jessie Mbwambo
Thailand: David Celentano / Suwat Chariyalertsak
Vulindlela, South Africa: Thomas Coates / Linda Richter /
Heidi van Rooyen
Zimbabwe: Steve Morin / Alfred Chingono
NIMH Cooperative Agreement Project Officer: Chris Gordon
Core Lab: Susan Eshleman/Estelle Piwowar-Manning
Statistical Core: Michal Kulich, Deborah Donnell
Collaborators:
NIMH Project Accept (HPTN 043)
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ACKNOWLEDGEMENTS
Sponsored by NIMH under the following Cooperative Agreements: U01MH066687 (Johns Hopkins University: David Celentano, PI)
U01MH066688 (Medical University of South Carolina: Michael Sweat, PI)
U01MH066701 (University of California, Los Angeles: Thomas J. Coates, PI)
U01MH066702 (University of California, San Francisco: Stephen F. Morin, PI)
Also Sponsored by the Division of AIDS at NIAID and the Office of AIDS Research ofthe NIH, as HPTN Protocol 043:
U01AI068613/UM1AI068613 (HPTN Network Laboratory: Susan Eshleman, PI)
U01AI068617/UM1AI068617 (SCHARP: Deborah Donnell, PI)
U01AI068619/UM1AI068619 (HIV Prevention Trials Network: Sten Vermund, PI)
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We thank the communities that partnered with us in conducting
this research, and all study participants for their contributions.
We also thank study staff and volunteers at all participating
institutions for their work and dedication.
Acknowledgements