Collecting data from the field: nationwide surveys
WFP/VAM for the CEDAT
‘Data from Conflict-Affected Regions: Filling in the Blanks’ workshop
Brussels 9th June 2011
VAM data collection • Countrywide: CFSVA• Context/area-specific: EFSA• On-going: FSMS, Market monitoring• Defined collaboration: JAM (with UNHCR) and CFSAM
(with FAO)• Reports: Global Update, Market Monitor
• Information on food security at household level from– Secondary data analysis – Key Informants, community & focus groups– Household questionnaires– Individuals within household
Why information is collected
• To answer ‘who, where, when and why households are food insecure'.
• Focus on household food security
• Based on conceptual framework
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Food and nutrition security conceptual framework
Food Food Utilization Utilization
Food Availability (Production,
Imports,Market,
Functioning)
Access to Basic Services and Infrastructure
Political, Economical, Institutional,
Security, Social, Cultural,
Gender Environment
Agro-ecological Conditions
LivelihoodLivelihoodStrategies Strategies
LivelihoodLivelihoodOutcomesOutcomes
Livelihood Livelihood Assets Assets
Underlying Causes
Immediate Causes
Natural Physical Human
Financial Social Capital
Health Status / Disease
Individual Food Intake
Nutrition StatusMortality
Household Food Access
HH Food Production, Gifts, Exchange, Cash Earnings, Loans, Savings, Transfers
Health and Hygiene
ConditionsCare Practices
Basic Causes
What information is collected?
• Non-specific to conflicts • For conflict – focus on
– displacement, including current living conditions, – shocks/coping – changes in food security as a result of the conflict – compare with
baseline.
hh composition & displacement
housing, water & energy
agriculture & livestock
income & assets expenditure & debts livelihoods
food sources & consumption
shocks & coping health & nutrition
Data collection at household level in conflict situation
External Constraints
• Insufficient baseline/secondary information
• Population estimates, migrating
• Sampling – purposive vs representative
• Ensuring all population groups represented
• Access – security
• Administrative boundaries
Data collection at household level in conflict situation
Internal Constraints• Availability of teams also affected by crisis – especially
females• Time limited, logistics not prepared for changes related
to security• Understanding conflict-related issues – expertise is in
food security
Kyrgyzstan 2010: HQ support• Sampling – purposive – based on discussion with KIs• National company to: (i) translate the questionnaires, (ii) identify &
train enumerators & supervisors, (iii) collect, enter and clean the data, (iv) produce output tables.
• Data were collected on the displacement status, demographics, current accommodation & extent of damage of house, livelihoods (income sources, food sources, main expenditures), ownership of assets, food consumption patterns, coping strategies, assistance received, and priorities.
• WFP provided a Plan of Analysis & conducted final data interpretation & analysis.
• Comparisons made between current & pre-crisis situation to estimate the impact of the crisis on livelihoods.
• Comparisons made between households according to their displacement &hosting status, and degree of food insecurity.
ResultsLinking food security and conflict:
Full loss of house is a clear criterion associated with food insecurity.
• Results not statistically representative of whole of crisis-affected areas.
• Combination of household and Key Informant information, direct observations from WFP staff involved in the field work, consistency of results, give confidence that the findings provide a solid representation of the situation of IDPs, host families and residents on the ground.
DRC 2005: Independent mission• Main constraint was determining sample size
– limited number of days to collect information – number of villages selected could not be respected because of logistic/transport or
security problems – in many villages, the entire population had only just recently returned after months of
taking refuge in distant forests. – reduced representativity & thus quality of analysis.
• No reference/baseline data was available to determine prevalence of acute
malnutrition and thus an appropriate sample size – selected 1000 children 40/20 hh/village – based on number children 6-59 months/hh.
• Data collection tools included a village questionnaire, a hh questionnaire, a mother and child questionnaire. A triangulation matrix was developed to consolidate qualitative information. Profile of interviewers was researchers or analysts.
• Prevailing conditions made data collection very difficult – impact on representativity, reliability of qualitative information, comparability of results.
DRC: Findings
• Reduced agricultural production - getting to their fields is a dangerous and often life-threatening
• Constant theft of goods left families with very few resources in terms of productive assets, food stocks, etc.
• Significant increase in the price of food commodities (76%) has forced affected livelihood groups to adopt erosive strategies
• Agriculture, livestock herding and fishing are perilous investments for households. Petty trade is a growing livelihood strategy, but it too has major disadvantages in terms of security.
Despite not being representative, the results described the reality of the current situation in the study areas.
The high level of food insecurity is transitory, and directly related to violence.
Afghanistan 2001: In-country team
• Strategy = Be prepared– Developed understanding of terrain prior to
conflict. – Mapped out access routes and potential
areas of displacement.– Building scenarios and preparing
interventions – eg stock-piling food.
Iraq 2008: Government & WFP
• 25,000 households, 115 districts, 166 teams – Teams comprised members from each
governorate as well as supervisors from stats office and research institute.
• WFP supported training, questionnaire design, methodology, data entry, analysis and report writing.
Libya 2011: HQ and regional bureau
No immediate access, limited secondary data
• Background information collected from web resources.
• Actual situation collected from WFP staff & contacts in Libya.
• Partnerships with NGOs present for market data.• Food security cluster launched for information
sharing.
Solutions to constraints• Collaboration with government (research
institute, stats office)
• Training government staff
• National staff, local government staff
• Good pre-crisis data collection
• Good SDA
• Preparedness – predicting what might happen & getting ready for it
• Transport – helicopter