Technical Leadership in Monitoring and Evaluation

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Presented by Heidi Reynolds, Leopoldo Villegas and Sharon Weir at the MEASURE Evaluation End-of-Phase-III Event.

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Technical Leadership in Monitoring and Evaluation

  1. 1. Session X: Technical Leadership in Monitoring and Evaluation MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  2. 2. Responsive M&E Systems for Program Success Heidi W. Reynolds, PhD, MPH MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  3. 3. Number Of Malaria Donors In Recipient Country, 2009-11
  4. 4. Number Of HIV Donors In Recipient Country, 2009-11
  5. 5. Develop and refine tools to improve measures
  6. 6. Build Evidence
  7. 7. Support National Systems
  8. 8. Build Capacity
  9. 9. Sharing
  10. 10. M&E Investments Better Data Measure infections and deaths
  11. 11. “ For time and the world do not stand still. Change is the law of life. And those who look only to the past or the present are certain to miss the future.” -John F. Kennedy
  12. 12. Epidemiology Program response Data needs What is Changing?
  13. 13. Looking Forward Monitoring resistance and adherence Understanding structural factors Subnational data to tailor response
  14. 14. Malaria M&E Looking for Impact, Finding a System Dr. Leopoldo Villegas, MD, DTM&H, MSc, DrPH, AdvDPHM MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  15. 15. What is Malaria?
  16. 16. Malaria – The Basics BiomedicalBehavioral Physical environment Political, Legal & Economic Social & Cultural Knowledge Management
  17. 17. Clinical Spectrum
  18. 18. Distribution ≠ Use Interventions
  19. 19. Control Pre- elimination Elimina- tion Prevention of reintroduction Malaria free SPR<5% <1 case/1000 pop at risk 0 locally acquired cases 3 years From Control to Elimination
  20. 20. National: DHS, MICS, MIS, RMIS State: DHS, MICS, MIS, RMIS District: RMIS Facility/Sentinel: RMIS Community/Individual: RMIS No households surveys (2011-2013) At least 1 households surveys (2011-2013) Measuring Malaria Control Pre- elimination Elimina- tion Prevention of reintroduction Malaria free
  21. 21. 3.4 B Population at risk 207.4 M Cases 627 K Deaths Malaria 2012 Artemisinin Resistance 80% Financial
  22. 22. >3.3 M Deaths prevented 50% # children dying Cases Deaths Funding 2000 2012 Impact
  23. 23. Contribution & coordination M&ETools Technical leadership Building capacities Country Support Malaria Portfolio
  24. 24. Global Contribution World Malaria Report (2010, 2011) Global plan for artemisinin resistance containment (GPARC) Reports Presentations Articles Secretarial and technical support to RBM MERG
  25. 25. M&E Tools MIS 2013 Updated MIS toolkit Supported Regional Malaria Framework for South East Asia Finalized Released Household Survey Indicators for malaria control Framework for evaluating the impact of malaria control programs – June 2014 Malaria M&E training curriculum
  26. 26. Technical Leadership Publication in peer-reviewed journals Symposium/presentations at international conferences Multi-Agency Malaria Impact Evaluation PMI 15
  27. 27. Building Capacities Malaria M&E courses 2010-2013 2011-2014 2011 2013 Malaria M&E short course Extensive mentoring/capacity building Curriculum development – M&E cascading training
  28. 28. Country Support
  29. 29. Challenges Implementation & priorities Difficult global consensus Uncoordinated & duplication of efforts Difficulties measuring achievements Global financial gap Increase Artemisinin resistance
  30. 30. Changing Context Intervention Coverage Malaria Burden Focal local transmission From control to elimination Data from lowest ADM level Adaptation
  31. 31. Adaptive Local Systems Understand your system Multisectoral approaches – tailored to local conditions Combination optimal “mix” interventions Knowledge of your malaria epidemiology, actors & roles Common goal > Elimination Monitoring and evaluation knowledge management
  32. 32. Acknowledgements  Countries  National programs  USAID teams  Malaria Stakeholders Thank you! MEASURE Evaluation partners
  33. 33. Session X: Advances in Monitoring and Evaluation of Programs for Key Populations Sharon S. Weir MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  34. 34. THIS IS A TEST
  35. 35. ANSWER SHEET 1 COMMON THEME: _________________________________ 2 CIRCLE ONE ANSWER: 3 CIRCLE ALL THAT APPLY: 4 CIRCLE BEST ANSWER: 5 How many questions did you answer correctly? 0 1 2 3 4 WINNERS GET A PRIZE! Your Name:____________________________________________ 0 1 2 3 4 5 6 7 8 9 A B C D 0 1 2 3
  36. 36. 1. 3 STATEMENTS. WHAT IS THE COMMON THEME? Welcome to Lake Wobegon, where all the women are strong, all the men are good-looking, and all the children are above average. A Garrison Keillor
  37. 37. 1. THEME? For the first time ever, overweight people outnumber average people in America. Doesn't that make overweight the average then? Last month you were fat, now you're average - hey, let's get a pizza! B Jay Leno
  38. 38. 1. THEME? “She said, You’re not Mr. Right, but Mr. O.K. will do….” C Lyrics, Just Say No, Beres Hammond
  39. 39. 1. COMMON THEME? Fill in the blank. A C B
  40. 40. EACH STATEMENT CHALLENGES OUR NOTION OF WHAT IS AVERAGE. ANSWER:
  41. 41. -- AND BY EXTENSION WHAT IS NOT AVERAGE, WHAT LIVES IN THE TAILS. ANSWER:
  42. 42. 2. HOW MANY OF THESE 3 STATEMENTS COMMUNICATE THAT KEY POPULATIONS LIVE IN THE TAILS? 1. Key populations (also referred to as most-at-risk populations) are  people who inject drugs,  gay men and other men who have sex with men,  transgender persons and  sex workers. 2. They are disproportionately infected with HIV compared to the general population. 3. There is no way toward an AIDS-free future without targeting approaches toward these highly marginalized and often hard to reach populations. Source: FROM USAID WEBSITE APRIL 22 http://www.usaid.gov/what-we-do/global-health/hiv- and-aids/technical-areas/key-populations-targeted-approaches
  43. 43. 2. ANSWER: ALL 3 1. Key populations (also referred to as most-at-risk populations) are  people who inject drugs,  gay men and other men who have sex with men (MSM),  transgender persons and  sex workers. 2. They are disproportionately infected with HIV compared to the general population. 3. There is no way toward an AIDS-free future without targeting approaches toward these highly marginalized and often hard to reach populations.
  44. 44. Figure 2 Forest plot showing meta-analysis of risk of HIV infection among female sex workers compared with women aged 15–49 years in low-income and middle-income countries, 2007–11, Stefan Baral , Chris Beyrer , Kathryn Muessig , Tonia Poteat , Andrea L Wirtz , Michele R Decker, Susan G Sherma, The Lancet Infectious Diseases, Volume 12, Issue 7, 2012, 538 - 549 It’s true. Meta-analysis shows HIV infection among Sex Workers is much higher than among women 15-49. But…. IS SOMETHING MISSING?
  45. 45. DIGGING DEEPER 1. Who are key populations? 2. Why are they more likely to be infected? 3. What programmatic response is needed? 4. Where?
  46. 46. TOOLS TO DIG DEEPER
  47. 47. DEFINITIONS MATTER
  48. 48. 3. WHO Are Key Populations Per Global Definitions? KEY POP? A) Alli A 29 year old female who exchanges sex for cash? Yes or No B) Bob A 24 year old man with 5 female partners in the past 4 weeks who pays women for sex? Yes or No C) Chip A 34 year man who has had sex with men? Yes or No D) Daisy A 17 year old female student who has had 4 partners in the past 4 weeks and exchanges sex for cash Yes or No
  49. 49. 3. WHO Are Key Populations? A and C ARE YOU SATISFIED WITH THE DEFINITIONS? KEY POP? Vulnerability STI PLACE A) Alli – A 29 year old female who exchanges sex for cash Yes Jailed HIV Yes B) Bob – A 24 year old man with 5 female partners in the past 4 weeks who pays women for sex No None None Yes C) Chip – A 34 year man who has had sex with men Yes Jailed Gonorrhea, Chlamydia Yes D) Daisy – A 17 year old student who has had 4 partners in the past 4 weeks and exchanges sex for cash No Youth Sex age 13 Chlamydia Yes
  50. 50. Of 678 female workers at a sample of venues where people meet new sexual partners in Liuzhou China, how many are sex workers? 678 •Ever had sex 648 • 50+ 231•Exchanged sex for cash/gifts 148 • 26+  35+ • 148 Exchanged sex for cash past 4 weeks • 50+ Number with a a positive rapid test for syphilis. Illustrates limitation of a narrow sex worker definition. PLACE approach includes all 50 workers at venues who had a positive rapid syphilis test.
  51. 51. WHY? ? ? ? New HIV Infections Extra credit: Fill in the blanks.
  52. 52. CAUSAL MODEL Underlying Proximate Biological New HIV Infections Determinants Transmission  Exposure to HIV  Susceptibility to HIV  Number of partners  Lack of condom use  Anal Sex  Lack of Circumcision
  53. 53. UNDERLYING DETERMINANTS Based on Boerma, Weir JID 2004 and collaboration with JP Figueroa General • Age • Sexual Orientation • Location Vulnerability • Unemployment • Low Education • Stress • Inadequate support • Genetics Adverse Life Events • Rape • Jail • Untreated infections • Homeless • Violence
  54. 54. TAILORED RESPONSE Combination Prevention Programme Package of Individual Level High Quality Health Services Programme Enabler Interventions  SiteOutreach  Improveavailability,acceptability andaccessibilityofservices  Improvedqualityofservices Social Enabler Interventions  Empowermentactivities  Improvelegalandpolicyenvironment  Programstoaddressstigma,violence anddiscrimination EnablingEnvironmentatthe CommunityLevel Biomedical Services  HIVtestingandcounselling  Linkagetocare,viralload reduction  STIscreeningandtreatment  Psychosocialinterventions  Harmreduction includingneedle andsyringeprogramsandopioid substitutiontherapy  HBVImmunization Behaviour Change Services  Condompromotion& distribution  Targetededucation andriskreduction counselling Figure 1 Combination Prevention Programme (modified from Operational Guidelines for Monitoring and Evaluation of HIV Programmes for Sex Workers, Men who Have Sex with Men and Transgender People)
  55. 55. PLACEStudy2012inAngolaIdentifiedVenuesWherePeople MeetNewSexualPartnersButInterventionProgramsare Insufficient Area with clusters of venues but no prevention program. WHERE? Programmatic Mapping To adequately focus effective, locally tailored HIV prevention response where it is most needed.
  56. 56. “Superstar lawyers and math whizzes and software entrepreneurs appear at first blush to lie outside ordinary experience. But they don't. They are products of history and community, of opportunity and legacy. Their success is not exceptional or mysterious. It is grounded in a web of advantages and inheritances, some deserved, some not, some earned, some just plain lucky – but all critical to making them who they are. The outlier, in the end, is not an outlier at all.” Malcolm Gladwell, Outliers: The Story of Success
  57. 57. “Sex workers, and gay men, transgender people, and people who inject drugs appear at first blush to lie outside ordinary experience. But they don't. They are products of history and community, of opportunity and legacy. The higher prevalence of HIV infection they share, their lack of access to services, their vulnerability, is not exceptional or mysterious. It is grounded in a web of disadvantages and disinheritances, prejudices and prison sentences, mostly undeserved, some just plain unlucky – but all critical to making them who they are, how they live, and what they will die from. The outlier, in the end, is not an outlier at all.” ― Sharon Weir, Edited text from Malcolm Gladwell, Outliers: The Story of Success
  58. 58. ACKNOWLEDGEMENTS AND LAST QUESTION  MEASURE PLACE Team o Sarah Hileman, Zahra Reynolds, William Miller, Jess Edwards, Grace Mulholland  Mentors , Colleagues, Supporters o Peter Figueroa, Freddie Ssengooba, Ties Boerma, Keith Sabin, Abu Abdul-Quader, Jamie Blanchard, Jinkou Zhao, Ludo Bok, Jenny Butler, Lovette Byfield, Krista Stewart, Erin Balch, Joseph Mwangi, MEASURE Evaluation team 4) How many Jamaica references (loosely defined) appear in this presentation?
  59. 59. ANSWER: 8 Based on Boerma, Weir JID 2004 and in collaboration with JP Figueroa Malcolm Gladwell, Outliers: 2 Mentors, Colleagues, Supporters Peter Figueroa, Lovette Byfield Jamaica Venue: Alli, Bob, Chip, Daisy
  60. 60. www.measureevaluation.org/eop

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