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.

Data from Conflict-affected Regions: Filling in the Blanks

Mohamed Ali

WHO Regional office, Cairo

Collecting data from the field: Nation-wide surveys

Coverage, size, questionnaires or different respondents

Complex design and the cost

Surveys always needed

• Survey vs. routine data• Imposing a survey on the national authority• Bilateral agreement or international

organizations (country initiative)

Challenges at different stages

• Design• Implementation • Analysis and dissemination

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

• 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

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)

• 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

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?

Last but not least

Did we build local capacity after all???