Early lessons from DREAMS impact evaluations - Isolde Birdthistle | July 23, 2018 - PEPFAR
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Early lessons from DREAMS
impact evaluations
Isolde Birdthistle | July 23, 2018
On behalf of the BMGF-funded impact evaluation partnership
The BMGF-funded impact evaluation of DREAMS
Part 1. Why, how, where, when will we evaluate?
Part 2. What have we learned so far?
After approx 1 year of DREAMS implementation…
• What is the coverage of DREAMS: who is being reached and
with what services?
• What are some early effects of DREAMS?
2
Part 1. The BMGF funded
impact evaluation
3
Aims of the impact evaluation
As part of its contribution to the DREAMS Partnership, BMGF is supporting
impact evaluation in 4 settings, to generate lessons on:
1. What is the impact of the combined DREAMS package on HIV
infection rates and other key outcomes among AGYW and their male
partners? [1 urban & 1 rural Kenyan setting; 1 rural South African setting]
2. What is the impact of a DREAMS package which also includes an offer of
oral PrEP to the highest risk AGYW? [Zimbabwe]
3. Through what pathways does DREAMS affect the health, education and
social well-being of AGYW? [all settings]
4. What was implemented and how? With what coverage and fidelity? [all]
4
How and where are we evaluating DREAMS?
Through community-wide cohorts {for population-level change} and in-depth cohorts
{individual-level change among AGYW} followed over time before, during and after roll-
out of DREAMS
Building on existing large research platforms…
3 Population-based studies
Gem, Siaya, western Kenya
• The CDC/KEMRI HDSS with HIV, demographic
& behavioural surveillance and nested
DREAMS cohorts of AGYW
[Partners: LSTM & KEMRI]
Nairobi, Kenya
• The Nairobi Urban HDSS with demographic &
behavioural surveillance and nested DREAMS
cohorts, including 10-14 yr olds
[Partner: APHRC]
uMkhanyakude, S Africa
• The HDSS in KZN with HIV, HSV2,
demographic, behavioural and phylogenetic
surveillance and nested DREAMS cohorts
[Partner: AHRI]
1 Key population study
Zimbabwe
• Evaluation of DREAMS+PrEP among most
vulnerable AGYW, using the Sisters programme
as a platform for cohorts of YWSS and HIV
testing in 2 DREAMS & 4 comparison sites
5
[Partners: LSTM & CeSHHAR]
Theory of change to guide impact evaluation
6
Timeline 2016 - 2019
Year Impact evaluation Process
evaluation
2016 Preparation, ethics approvals
Map & analyse historical data for baseline
Ongoing
2017 Round 1: General population & nested AGYW cohorts
Share baseline summaries
[PLOS One eCollection on DREAMS]
2018 Round 2: General population & nested AGYW cohorts
Share interim findings by Q4 2018
• Uptake of DREAMS interventions
• Secondary, HIV-related outcomes and mediators
2019 Round 3: General population & nested AGYW cohorts
Share end-line findings by Q4 2019/Q1 2020
• Secondary outcomes and mediators
• Primary outcome: HIV incidence
7
Part 2. What have we
learned so far?
a) DREAMS reach so far
8
DREAMS’ reach: Sample findings to date (1)
In general populations (with representative samples), by mid-2017…
• There is high awareness and participation in DREAMS, especially among young women,
more so among adolescent girls (10-17y) than young women (18-22y)
• HIV testing services and school-based prevention education are the most accessed
interventions
• Among those invited into DREAMS, good penetration of ‘newer’ interventions, like social
asset building including safe spaces but not yet among a majority of beneficiaries
• Most AGYW invited into DREAMS have accessed multiple services, including “layered”
services (>1 category in the Core Package) in last 12 months
• “Individual”-level interventions are often combined with “contextual” (community- / family
level interventions)
9
DREAMS’ reach: Sample findings to date (2)
• AGYW were more likely to be invited to participate in DREAMS if they were:
• in school, had never had sex, never married (Kenya), were never pregnant/gave birth
• had socio-economic vulnerabilities (‘very poor’ or food insecure [Kenya] or received Govt grant
[SA])
• Very few AGYW accessed all ‘primary interventions’ intended for their age / need
• Among older women, low usage of community- /family-level DREAMS interventions
including parent/caregiver, violence prevention and social norms programs
• Among men, usage of DREAMS services is generally low, apart from HIV testing in
some settings
10DREAMS’ reach: Sample findings to date (3)
In a high-risk key population, of young women who sell sex (YWSS) …
• By mid-2017, there was very low uptake of DREAMS interventions
• Few YWSS were reached by DREAMS, or referred when targets were already full
Examples of supporting data
follow…
11Awareness and uptake of DREAMS (Nairobi 2017)
• In Nairobi, high awareness of DREAMS programme among AGYW
(less so among other groups, esp/ men)
• Half of AGYW invited to participate in DREAMS [N=10,874]
General
General population
AGYW nested cohorts population
males
females
10-14y 15-17y 18-22y 25-49y 15-29y 30-49y
(N=606) (N=547) (N=534) (N=4426) (N=2561) (N=2200)
n % n % n % n % n % n %
Heard of a
programme 482 80% 489 89% 414 78% 2838 64% 1044 41% 727 33%
called DREAMS
Invited to
participate in
290 48% 322 59% 214 40% 420 9% 75 3% 56 3%
any DREAMS
activity
12Awareness and uptake of DREAMS (Nairobi & KZN 2017)
• Awareness of DREAMS is highest among adolescent girls, versus
young women, in both Kenya and South Africa
• Lower awareness & participation in SA relative to Kenya
AGYW nested cohorts
AGYW nested cohorts
uMkhanyakude, South
Nairobi
Africa
10-14y 15-17y 18-22y 13-17y 18-22y
(N=606) (N=547) (N=534) (N=1148) (N=1036)
n % n % n % n % n %
Heard of a
programme 482 80% 489 89% 414 78% 627 55% 324 31%
called DREAMS
Invited to
participate in any 290 48% 322 59% 214 40% 463 40% 176 17%
DREAMS activity
1314
15
16
Uptake of DREAMS services in a key population
• Low among Young Women who Sell Sex in the evaluation cohort in Zimbabwe
2017 (>1yr of implementation)
• Re-prioritisation discussed for Year 3 of DREAMS; 2018 data now under review
17Part 3. What have we
learned so far?
a) DREAMS reach so far
b) Early effects of DREAMS
18Measuring HIV incidence: Direct observation of sero-conversions via
repeat testing in cohorts to be followed through 2019
New
infections
measured
through
2019
1920
Example of a secondary outcome
Young People’s Knowledge of their HIV Status
in 2 informal settlement areas of Nairobi
21Young people’s knowledge of their HIV status
By whether AGYW were beneficiaries of DREAMS in the past year…
• Levels among DREAMS beneficiaries are significantly higher in both age groups
• Larger % difference among the younger AG, 15-17yr-olds
22Young people’s knowledge of their HIV status
In uMkhanyakude…
• Differences by DREAMS are also evident but not as great as Kenya (HIV testing not delivered
as systematically as Nairobi, where enrolment includes an offer of HIV testing?)
• And they are only significant among the younger AG (13-17y), not the older YW (18-22y)
• Levels remain sub-optimal but promising signs that DREAMS can reach adolescent girls 23Young people’s knowledge of their HIV status
Reflections so far
• Knowledge of HIV status is the gateway to HIV prevention and treatment
services, but typically low among young people (big gap to 95:95:95)
• DREAMS is helping to quickly increase young women’s knowledge of their HIV
status:
• especially in Kenya, where DREAMS enrolment was usually accompanied by an HIV
test
• but also in KwaZulu-Natal, SA, where levels were low pre-DREAMS
• in both settings, DREAMS is boosting knowledge of status among adolescent girls
13-17yrs (more so than young women 18+), showing that adolescent girls can be
reached before ANC / pregnancy-related services.
• The DREAMS model can be expanded to reach young males, whose
knowledge of their status remains very low in most settings, over time and
relative to females (see Annex).
24CONCLUSIONS (so far)
• DREAMS has mobilised communities and governments to deliver a complex program
across sectors introducing new services (e.g., social asset building, PrEP) and new ways
of working
• DREAMS offers a model that – with commitment and resources – can be adapted to diverse
contexts, with these lessons so far:
For impact on HIV incidence?
25
It is too soon to say. We will observe sero-conversions through 2019.Related talk at AIDS2018 this week…
HIV incidence trends among the general population in Eastern and Southern
Africa 2000-2014
Emma Slaymaker, London School of Hygiene & Tropical Medicine, United Kingdom
Session: “Forging new pathways towards HIV elimination”
Code: TUAC01
Session Type: Oral Abstract Session Track C – Epidemiology and prevention research
Venue: Elicium 1
Date Time: 14:30 Tuesday 24 July, 14:30 – 16:00
26In memory of our colleague and
co-Investigator Basia Zaba
Thank YouAnnex
28Baseline HIV incidence Trend pre-DREAMS:
Persistently high incidence in
- pre-DREAMS in uMkhanyakude, KZN 10 years prior to DREAMS;
no evidence of rise or
decline. A steady baseline.
Females aged 15-24 years (2006-2015)
Age group Calendar period New HIV Person-years Incidence rate / Rate ratio
infections 100 person-years (95% CI)
15–19 years 2006–2010 254 5395 4.71 (4.10 -5.41 ) 1
2011–2015 197 4330 4.54 (3.89 -5.30 ) 0.97 (0.78 -1.19 )
20–24 years 2006–2010 340 4462 7.62 (6.71 -8.65 ) 1
2011–2015 289 3881 7.45 (6.51 -8.51 ) 0.98 (0.81 -1.18 )
Males aged 20-29 years (2006-2015)
Age group Calendar period New HIV Person-years Incidence rate / Rate ratio
infections 100 person-years (95% CI)
2006–2010 103 3430 2.99 (2.38 -3.77 ) 1
20–24 years
2011–2015 76 2876 2.62 (2.01 -3.42 0.85 (0.59 -1.23 )
2006–2010 59 1299 4.54 (3.32 -6.21 ) 1
25–29 years
2011–2015 66 1592 4.16 (3.12 -5.56 ) 0.92 (0.59 -1.42 )Young people’s knowledge of their HIV status
By age and sex, among random samples of young people in Nairobi 2017…
• Levels among females are quite high (>75%), and increase with age
• Lower levels among male peers, in both 15-19y and 20-22yr groups
30Comparison with uMkhanyakude, KZN, S Africa
By age and sex, among representative samples of young people
• Knowledge of HIV status is much lower overall than seen in Nairobi (reflecting a history of
relatively few HIV prevention programs targeting young people in this area)
• Again, higher levels among females than males (15-19y): 54% v 21%
• Among females, it’s higher (double) among older YW than younger AG 31You can also read
