Data from Conflict-affected Regions: Filling in the Blanks Mohamed Ali WHO Regional office, Cairo.
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Transcript of Data from Conflict-affected Regions: Filling in the Blanks Mohamed Ali WHO Regional office, Cairo.
![Page 1: Data from Conflict-affected Regions: Filling in the Blanks Mohamed Ali WHO Regional office, Cairo.](https://reader036.fdocuments.in/reader036/viewer/2022083009/5697bfe21a28abf838cb475b/html5/thumbnails/1.jpg)
Data from Conflict-affected Regions: Filling in the Blanks
Mohamed Ali
WHO Regional office, Cairo
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Collecting data from the field: Nation-wide surveys
Coverage, size, questionnaires or different respondents
Complex design and the cost
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Surveys always needed
• Survey vs. routine data• Imposing a survey on the national authority• Bilateral agreement or international
organizations (country initiative)
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Challenges at different stages
• Design• Implementation • Analysis and dissemination
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Design stage:
• Stakeholders/funders influence– Agreeing with the stakeholders and the funding agencies
what to include is not always easy, in emergency situation it is even worse, sometime the questionnaire end up with irrelevant question or key questions were dropped
– Implementers role
• Definition of outcome and set of questions used (child mortality): – real vs. synthetic cohorts and direct or indirect
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• Some tools are not yet fully developed or field tested tested
• Most CSO/MoH do not have enough trained interviewers and recruitment of short term inexperienced field staff increases the cost, attrition problem and impact the data quality
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Implementation:
• Security and safety of the field staff (government employee use of GPS)
• Access to household is not always granted • Coverage and Response rates • Matching the interviewer and respondents
gender and ethnic background • Categorical vs. continuous measure (present or
absence of disease vs anthropometric)
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• Recall period• Invasive procedures (blood sample or measuring
hip or waist)• Personal and sensitive questions (income and
sexual behaviour to single un married women)• Exaggeration and concealing (mortality,
behaviour, chronic illness)• Supervision and data quality checks in the field
are lacking
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Data analysis and reporting
• How do you handle missing and incomplete data, what adjustment and imputation methods to be used.
• Reporting crude or adjusted estimates • Politically charged results usually generate
rumours and counter rumours, how do you handle such a situation?
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Last but not least
Did we build local capacity after all???