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Dr M Bhattacharya

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  • 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
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. Differencefrom ---
Meta Analysis
Data triangulation
Meta analysis combines rigourous scientificdata of similar quality and design toconduct statistical analysis
Uses data from diverse sources
Lists judgements and limitations of each
To be used by programme managers policy makers , and also researchers
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
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?
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. Feasiblebhattacrya-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
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

  • 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

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