Implementation Science in Kenya……..cira.yale.edu/sites/default/files/Implementation...

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Implementation Science in Kenya…….. and opportunities for Partnerships Dr Peter Cherutich, PhD Director, Division of Strategic Health Information &Research, Ministry of Health, Kenya Centre for Interdisciplinary Research on AIDS, Yale University, April 24, 2017

Transcript of Implementation Science in Kenya……..cira.yale.edu/sites/default/files/Implementation...

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Implementation Science in Kenya……..

and opportunities for Partnerships

Dr Peter Cherutich, PhDDirector, Division of Strategic Health Information &Research,

Ministry of Health, Kenya

Centre for Interdisciplinary Research on AIDS, Yale University, April 24, 2017

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Research Interests

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• Aim 1: Evaluate seek test treat retain – ‘Testing & Linkage to Care for IDUs’ (TLC-IDU Kenya) – using a stepped wedge cluster-randomized design.

• Aim 2 : Conduct mathematical modeling to estimate community viral load in IDU injecting and sexual networks, and to assess potential population-level impact of the TLC-IDU

• Aim 3 : Assess the incremental cost-effectiveness ratio of the TLC-IDU model, using a national payer perspective.

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Other Selected Research Interests

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Policy Initiatives

• Scale up of HIV testing through various approaches– Introduction of HIV self-testing into national guidelines

• Catalyzed the discussions on Pre-exposure prophylaxis for HIV prevention– Now leading the research and impact evaluation thematic

group• Large scale implementation of male circumcision• Re-engineer HIV prevention in Kenya

– Prevention revolution• Now leading discussions on unique personal

identifiers as part of health informatics

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Where are we now?

Kenya’s HIV epidemicAdults aged 15 to 49 prevalence rate

5.9% [4.9% - 7.0%]

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Geographical Heterogeneity

Sources: UNAIDS 2015 estimates; Kenya Ministry of Health.

10/47 counties > 60% of prevalent HIV

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HIV Care Cascade-the trouble with first 90

Maman D, Zeh C, Mukui I, Kirubi B, Masson S, Opolo V, Szumilin E, Riche B,Etard JF. Cascade of HIV care and population viral suppression in a high-burdenregion of Kenya. AIDS. 2015 Jul 31;29(12):1557-65

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Stable HIV Incidence after a rapid decline

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Dissecting the Know-Do Gap

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Case Study on Male Circumcision

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Doyle SM, Kahn JG, Hosang N, Carroll PR. The impact of male circumcision on HIV transmission. J Urol. 2010 Jan;183(1):21-6

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Sgaier SK et al. Achieving the HIV prevention impact of voluntary medical male circumcision: lessons and challenges for managing programs. PLoS Med. 2014 May 6;11(5)

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Sgaier SK et al. Achieving the HIV prevention impact of voluntary medical male circumcision: lessons and challenges for managing programs. PLoS Med. 2014 May 6;11(5)

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Results

Dickson KE et al.Voluntary medical male circumcision: a framework analysis of policy and program implementation in eastern and southern Africa. PLoS Med. 2011 Nov;8(11):e1001133

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Kenya(Nyanza)

0

3.36

Namibia

0.060.020.06

Rwanda

0.06

Botswana

0.07

Lesotho

0.11

Tanzania

0.20

Mozam.

0.22

Malawi

0.24

3

0.34

Zambia

0.34

Zimbabwe

0.57

Uganda

1.08

2

1

4

SwazilandSouth Africa

Note: Assumes each country achieves 80% MC prevalence target by 2015. Kenya infections averted only applies to Nyanza province. MC targets have been revised for select countries since original WHO goals were set, changing total MC target to ~22 M.Source: Njeuhmeli et.al., Voluntary Medical Male Circumcision: Modeling the Impact and Cost of Expanding Male Circumcision for HIV Prevention in Eastern and Southern Africa, PLoS Medicine, Nov. 2011

HIV Infections Averted by 2025 if 80% coverage in 5 years

Five countries, ~80% potential

global impact of MC

Total InfectionsAverted

Infe

ctio

ns a

verte

d (m

illion

s)

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Galbraith JS et al.Status of voluntary medical male circumcision in Kenya: findings from 2 nationally representative surveys in Kenya, 2007 and 2012. J Acquir Immune Defic Syndr. 2014 May 1;66 Suppl 1:S37-45.

16.1% to 46.7% within target ethnic group

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Early on: Communicating about partial protection

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General SRH session

Mobile clinic set up

Individual MC counseling / VCTGroup MC education

• Partnering with health facilities

• Using nurses to perform surgery

• Mass Campaigns

Surgery ongoing

Different service delivery channels

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Mass Campaigns-2010/2011

• 36,077 MCs (120% achievement)• 28,445 (79%) in 7 of the 11 target districts:

– Average10 (8-12) MCs/team/day– 56% tested for HIV during RRI – Men ≥15 year – 55%– Seven day follow up - 23%– Overall AE - 1.9% (1.83%= mod, 0.05% =severe)

• For 6,595 returning for F/up: 8.4% AEs (8.2% mod, 0.2% severe)– Deferred or opted out - 694 (256 and 438 respectively)

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Num

ber

of M

Cs

requ

ired

(‘000

s)Geospatial Focus

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Surgical Efficiency

• Models for Optimizing Volume and Efficiency (MOVE)– use of task-shifting, – task-sharing, – pre-bundled kits with

disposable supplies, – rotation among surgical

beds, electrocautery, – and forceps-guided

surgical method

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Bollinger L et al. Cost drivers for voluntary medical male circumcision using primary source data from sub-Saharan Africa. PLoS One. 2014 May 6;9(5)

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Provider Experience and Quality

Herman-Roloff A, Bailey RC, Agot K. Factors associated with the safety of voluntary medical male circumcision in Nyanza province, Kenya. Bull World Health Organ. 2012 Oct 1;90(10):773-81

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Key Lessons Learnt• Deep commitment for impact-driven approach to

scale up– Significant population coverage– High intensity-3-5 years

• Social change necessary for uptake– Community ownership– Meaningful engagement with political, cultural and social

leaders• Government leadership, coordination and strong

partnerships– Technical and programmatic support from government– Passionate researchers, NGO’s– Timely funding-PEPFAR, Bill & Melinda Gates Foundation

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Case Study on HIV Prevention Revolution

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All Regions, all Epidemics are not born equal

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Need to do more and do it better!

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Estimated Health Production Functions (HPFs) for each county in Kenya.

a b

The HPF defines the expansion pathway for services that maximizes the health generated (articulated as ‘InfectionsAverted’) for input cost. (a) HPFS for each county are plotted. Across counties, the shape and scale of the HPFs varysubstantially due to difference in underlying epidemiological and demographic conditions. (b) The plot shows therelative priority of each form of intervention in each county (vertical scale) for each county (horizontal scale). Bluecolour indicates that the strategy comes early in the optimal expansion pathway for that county; red colour indicatesthat the strategy is introduced only at the end of the optimal expansion pathway. There is broad consistency in theexpansion pathways across the counties although there are key different in the relative priority of more expensiveinterventions for lower risk groups. (Key: M-Men, W-Women, SW-Sex Workers; BC- Behaviour Change, ART- EarlyART (>350 cells per microlitre), MC – Male Circumcision and Pr –PrEP)

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Optimizing allocations funds between counties for maximum prevention impact.

Budget = X

In each panel, a comparison is made of the configuration of intervention across the country, either when ignoring data on epidemicheterogeneities (upper part) or when using that data (lower part). Each box indicates whether that the intervention (vertical axis) inthat county (horizontal axis) is used: green for not used and yellow for used. Without using the data on epidemic heterogeneities,interventions are deployed uniformally across counties, whereas when using that information, intervention effort is redirected to otherinterventions in particular counties.

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ftDraKenya HIV PreventionRevolution Road Map

Countdown to 2030

MINSTRY OF HEALTH

Kenya National AIDS & STI Control Programme (NASCOP)& National AIDS Control Council (NACC)

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Ambitious Goals!

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Proposed Strategic Shifts

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Novel Surveillance Systems• Focused investments in surveys, survey cycles, and

institutional capacity– AIDS Indicator Surveys that define areas of high and low

prevalence• Powered to give incidence estimates through incidence assays• Viral load on all positives and known positives not retested

– Oversampling in the tails – high prevalence areas and some very low prevalence areas

• Significant investments in technology– Geographic information systems

• Embedded in health information systems• Need for viral load monitoring as an outcome of both

treatment and prevention• Case based surveillance

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Incidence based clustering of regions

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A new Research Agenda!

• Access policies• Safeguarding IP• Manufacturing

plans

• Country own and led R&D

• Long-term commitment of partners and governments

• Capacity building for local scientist

• Unified advocacy, policy and stakeholder engagement

• in synch with epidemic realities and right-based

• Coordinated and synergetic R&D agenda

• Participatory agenda setting

• Unified R&D hub for information and knowledge management Prioritise R&D

for New and cost effective

Prevention Tools

Develop timely policy and guidelines

Expedite Demonstration and Delivery of

newly found efficacious

interventions

Increase national funding for R&D and set

national R&D priorities

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Parting Shot !

Sgaier SK et al. Achieving the HIV prevention impact of voluntary medical male circumcision: lessons and challenges for managing programs. PLoS Med. 2014 May 6;11(5)

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Opportunities for collaboration

• Enhance the existing research partnership between Kenyan institutions and Yale University– Universities-Increase emphasis on non-communicable

diseases, neglected tropical diseases and health informatics– Maximize opportunities for closing the 90:90:90 gap for HIV– Expand CIRA’s network to Kenya– Joint grant applications– Enhance research infrastructure

• Explore newer possibilities– MoH- Structured Implementation Science mentorship– Universities-Capacity building on Implementation Science,

Big data analytics, artificial intelligence, precision medicine

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• Kenya– HIV Prevention Revolution– Study Staff

• University of Washington– Judy Wasserheit– Kenny Sherr– Carey Farquhar

• Yale University– Dini Harsono– Elizabeth Cappello– John Lizcano– Ann Kurth

Acknowledgements