• Like
Dr M Bhattacharya
Upcoming SlideShare
Loading in...5
×
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
489
On Slideshare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
7
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Data Triangulation in HIV
    Prof Madhulekha Bhattacharya
    HOD ,Deptt of Community Health Administration
    National Institute of Health & Family Welfare
    Munirka,New Delhi--67
  • 2. Data Triangulation
    Is an analytical approach that integrates multiple data sources to improve understanding of a public health problem and to guide programmatic decision-making to address these problems
    Involves the synthesis and integration of data from multiple sources through collection, examination, comparison and interpretation
    By collecting and comparing multiple data sets with each other, triangulation helps to overcome biases inherent in each data source
    bhattacrya-NIHFW
  • 3. Gather data from multiple sources
    Refine hypothesis (corroborate, refute or modify)
    Examine data
    Planning Triangulation
    Conducting Triangulation
    Communicating Results (for Action)
    A visual representation of the triangulation process
  • 4. Difference from ---
    Meta Analysis
    Data triangulation
    Meta analysis combines rigourous scientific data of similar quality and design to conduct statistical analysis
    Uses data from diverse sources
    Lists judgements and limitations of each
    To be used by programme managers policy makers , and also researchers
    bhattacrya-NIHFW
  • 5. Steps in Data Triangulation
    Specify the question
    Identify data sources, organize the data and identify data gaps
    Conduct data quality and validation checks
    Decide on data outlier and/or missing data
    Refine/revisit the questions chosen for data triangulation
    Analyze data from different sources for each question
    Data triangulation
    Summarize findings and draw conclusions
    Outline next steps based on findings
    bhattacrya-NIHFW
  • 6. Questions
    What are the levels, differentials and trends in HIV/STI in general population, high-risk groups, and the bridge population?
    What are the drivers of the epidemic?
    What are the gaps in HIV/AIDS response at district level?
    What are the data gaps?
    bhattacrya-NIHFW
  • 7. Identifying and refining key questions
    Brainstorming questions
    Refining brainstormed questions
    Key question(s)
    • Data available
    • 8. Important, answerable
    • 9. Actionable, appropriate
    • 10. Method appropriate
    • 11. Feasible
    bhattacrya-NIHFW
  • 12. Data sources
    1. Data from HIV Sentinel Surveillance for different population groups
    2. ICTC/PPTCT data on HIV prevalence
    3. Mapping of HRGs - urban (under TI program) & rural (under Link Worker Program)
    4. ART registration data
    5. Behavioural Sentinel Survey (BSS)
    6. Integrated Biological & Behavioural Assessment (IBBA)
    7. Blood Bank data, STD Clinic data
    8. Census of India, NFHS-3, DLHS-3
    9.Any special studies
    bhattacrya-NIHFW
    NATIONAL INSTITUTE OF HEALTH & FAMILY WELFARE MUNIRKA, NEW DELHI – 110067.
  • 13. Inputs to Evidence-Based Planning
    Overall burden of HIV
    Sub-population distribution of HIV
    Basic HIV transmission dynamics
    Assessing gaps in responses to HIV situation
    bhattacrya-NIHFW
    • Evidence required at the lowest levels of planning such as Districts and Sub-districts
    • 14. Integration and triangulation using data from different sources
    • 15. To Use valid and standardized methods to ensure that evidence derived is credible and comparable across states and districts
  • Levels, Differentials and Trends
    What is the current level of HIV and other specific STIs in the general population, among FSWs, MSM-T, IDUs, and clients of FSWs in the district?
    Does HIV/STI prevalence differ across different sub-groups? Does HIV/STI prevalence vary by:
    Rural and urban areas, Taluka/Block/Mandal, Age, Literacy and education, Occupation
    Duration in sex work, Sex work typology, Client volume,
    Self identity, Volume of anal sex partners
    Frequency of needle sharing
    bhattacrya-NIHFW
  • 16. SURAT
    PHC – 75, CHC – 17
    ICTC – 50, DIC – 3
    Blood Bank – 8
    STD Clinics – 31
    ART Centre – 2
    CCC - 2
  • 17.
    • No of PLHIV- 22083
    • 18. On ART – 2603
    • 19. MSM/1000 Adult Population -1.21
    • 20. FSW/1000 Adult Population - 1.35
  • HIV Positivity – Talukawise from PPTCT sites (2008-09) Gujarat
  • 21. HIV Positivity Talukawise – for General Clients (ICTC) (2008-09) Gujarat
    HIV Positivity at ICTC – General (2008-09) Gujarat – 5.5 (14645/267840)
    Mehsana – 11.9 (435/3656)
    Rapar – 21.8 (12/55)
    Vadodara -
    10.8 (864/7992)
    Bhachau – 11.7 (40/343)
    Rajkot – 17.6 (1278/7261)
    Rajula – 13.3
    (8/60)
    Keshod – 10.1 (57/567)
    To 5
    Amreli –11.6 (113/972)
    Surat City – 12.4 (2814/22609)
  • 22. HIV prevalence amongst General Clients from ICTC by various characteristics in Gujarat, 2008
  • 23. Differentials of HIV Tested & %Positivity in ICTC Attendees(CMIS), Jamnagar
  • 24. Trends
    What has been the trend in HIV/STI prevalence in the general population, among FSWs, MSM-T, IDUs, and clients of FSWs in the district?
    bhattacrya-NIHFW
  • 25. Comparative trend of HIV Infection among pregnant women from different sources in Gandhinagar
  • 26. Prevalence of HIV in Low Risk Group, SURAT (SAPCU)
  • 27. Prevalence of HIV among High Risk Group, SURAT(SAPCU)
  • 28. Trends among High Risk Group, SURAT(SAPCU)
  • 29. Drivers of the Epidemic
    Size estimation
    Size and distribution of HRGs and bridge population
    Underlying vulnerabilities
    Migration
    Risk behaviours
    Risk profile of HRGs and bridge population including condom use behaviour
    Profile of PLHIV
    Characteristics and geographic distribution
    bhattacrya-NIHFW
  • 30. Map of HIV prevalence district wise of PPTCT and number of High Risk Groups at Gujarat.
  • 31. Dual Drivers of STD Epidemics: Populations and Pathogens
    bhattacrya-NIHFW
    Pathogen
    Population
    Demography
    Sexual Structure
    Infectiousness
    Virulence
    Duration
    ß, efficiency of transmission
    c, contact rate between infected and susceptible
    D, duration of infectiousness
  • 32. HIV Positivity Talukawise – for General Clients (ICTC) (2008-09) Gujarat
    HIV Positivity at ICTC – General (2008-09) Gujarat – 5.5 (14645/267840)
    Mehsana – 11.9 (435/3656)
    Rapar – 21.8 (12/55)
    Vadodara -
    10.8 (864/7992)
    Bhachau – 11.7 (40/343)
    Rajkot – 17.6 (1278/7261)
    Rajula – 13.3
    (8/60)
    Keshod – 10.1 (57/567)
    To 5
    Amreli –11.6 (113/972)
    Surat City – 12.4 (2814/22609)
  • 33. HIV prevalence amongst General Clients from ICTC by various characteristics in Gujarat, 2008
  • 34. Drivers of the Epidemic
    Size estimation
    Size and distribution of HRGs and bridge population
    Underlying vulnerabilities
    Migration
    Risk behaviours
    Risk profile of HRGs and bridge population including condom use behaviour
    Profile of PLHIV
    Characteristics and geographic distribution
  • 35. HIV Prevalence amongst MSM in consistent sites of Gujarat, 2005-2007
  • 36. Occupation of MSM
  • 37. HIV Prevalence amongst FSW in consistent sites of Gujarat, 2005-2007
  • 38. Risk Profile Of High Risk Group(MSM),Surat-SAPCU
  • 39. Response Gaps
    What are the gaps in HIV prevention programs
    HRGs yet to be covered in each taluka of the district
    HRGs currently being contacted on a regular basis
    Condom supply against requirement among HRGs
    HRG’s access to services
    What are the gaps in HIV/AIDS care, support and treatment programs?
    Size estimation of PLHA in the district
    Detection of HIV against the estimate
    ART registration against the diagnosed
    Started on ART against the registered
    Currently on ART against those ever started
    Differences in the profile of the registered, currently on ART and those who have dropped out of ART
    bhattacrya-NIHFW
  • 40. Question /Response Gaps
    What are the gaps in HIV prevention programs
    HRGs yet to be covered in each taluka of the district
    HRGs currently being contacted on a regular basis
    Condom supply against requirement among HRGs
    HRG’s access to services
    What are the gaps in HIV/AIDS care, support and treatment programs?
    Size estimation of PLHA in the district
    Detection of HIV against the estimate
    ART registration against the diagnosed
    Started on ART against the registered
    Currently on ART against those ever started
    Differences in the profile of the registered, currently on ART and those who have dropped out of ART
  • 41. Route of Transmission of HIV positive cases in VCTC (Direct walk-in) Gujarat, 2007
  • 42. PPTCT coverage in Gujarat
  • 43. Yearly Performance Trend for NVP Coverage of MBP (ICTC- PPTCT)
  • 44. Yearly Performance HIV-TB (2006-2010)
  • 45. Status of ART/Link ART & CCC Centre in Gujarat 2008
  • 46. District & Residence Wise Patients on ART per 1 Lac Population
  • 47. District wise PLHIV by sex in Gujarat, 2008
  • 48. IEC Programs Implemented (GUJARAT)
    IEC Programs Implemented (GUJARAT)
    I
    J
    R
    C
    D
    D
    C
    J
    I
    R
    C
    J
    D
    C
    J
    C
    J
    Category of District
    J
    I
    I
    R
    C
    C
    D
    J
    J
    C
    J
    J
    C
    C
    D
    J
    C
    D
    R
    C
    D
    C
    R
    J
    I
    C
    D
    U
    U
    D
    R
    C
    R
    J
    C
    D
    16 DIC -12
    J
    C
    C
    J
    U
    J
    20 JEEVAN DEEP - 20
    I
    R
    C
    J
    C
    D
    D
    J
    5 UJAAS - 5
    U
    U
    J
    U
    I
    IRHAP/LINK WORKER - 8
    I
    D
    J
    C
    I
    R
    8 RED RIBBON CLUB - 8
    IDC CAMPAIGN - 22
    J
    C
    C
  • 49. SURAT
  • 50. Outline for presenting the triangulation process and findings…2
    4. Discuss data interpretation findings (secondary findings).
    i. Summarize other secondary results identified through the triangulation analysis.
    5. Note limitations (be honest).
    6. Summarize findings.
    7. Translate findings into:
    i. need for additional data;
    ii. programmatic recommendations;
    iii. policy recommendations.
    bhattacrya-NIHFW
  • 51. Information flow in the monitoring and evaluation system within the context of strategic information: an overview
    Health information systems HMIS,
    vital statistics
    Programme monitoring
    Programme evaluation
    Qualitative studies
    Behavioural surveys
    DLHS 1,2,3
    Operations
    research
    HIV surveillance;
    Pop based eg NFHS
    Data management
    Data analysis and synthesis
    Use of data for action
    Communication
    to the media
    Advocacy material
    Estimates
    (e.g. HIV, ART)
    Resource allocation
    Programme planning
    Reports
    Policy
    Formulation
    bhattacrya-NIHFW
  • 52. 4545
    THANKS