Post on 10-Feb-2016
description
FANRPAN HIV & AIDS Policy Studies
Lindiwe Majele Sibandalinds@ecoweb.co.zw
linds@mweb.co.za
FANRPAN Mission
• To coordinatecoordinate, influenceinfluence and facilitatefacilitate policy research, analysis and dialogue at the nationalnational, regionalregional and globalglobal levels in order to develop the food, agriculture and natural resources sector.
• The Mission is achieved through research, networkingnetworking, capacity buildingcapacity building and informationinformation generation generation for the benefit of the SADC region.
Impact of HIV & AIDS on Agriculture & Food Security in the SADC region: A Policy Development Framework
• This is part of a five-year EU funded project
• 2 year study • Aim: To determine the impact of HIV & AIDS on
food security and recommend mitigation and coping strategies for adoption by SADC Ministries of Agriculture
Implementing Countries
• 7 Study Countries:
– Botswana, Lesotho,– Namibia, South Africa, – Swaziland, Zambia & Zimbabwe
Expected Impact
• Capacity building in the SADC Secretariat and FANR sector for the management and control of HIV & AIDS
• Development of programmes and strategies to reduce vulnerability of people in the FANR sector to HIV & AIDS and increased support to people that are living with HIV & AIDS
Overall Objective
Project Purpose
Intervention Logic Indicators Important Assumptions
To contribute to the SADC overarching goal of decreasing the incidence of HIV & AIDS particularly in the FANR sector to promote socio-economic development
HIV & AIDS built into the regional and country development policies and strategies
Project implemented as planned with maximum stakeholder cooperation
Planned Results
Impact Variables Database
• Developed using Epi Info 2000, using Microsoft Access Database
• Developed from national level SPSS databases
• Has 167 variables and 1930 records from 7 countries.
• Variables have household data on demographics, health, income, expenditure and impact of HIV and AIDS.
• Analysis carried out at country and regional levels.
• Integrated framework within Epi Info allows for analysis and reporting.
Variables Tracked
Key Impact Area Key Variables / Indicators
1. Agricultural ProductivityHypothesis: H/A has led to decline in agricultural productivity.
Yield (area cultivated); Overall output; Agricultural input (type and quantity); No. of productive HH members infected/ affected; Education level; Demographic variables; Type and quantity of equipment; Gender of infected/affected; Changes in HH structure; Extension and support services; Area cultivated.
2. Marketing / Livestock AssetHypothesis: Reduces participation in the market.
Sales (no. animal, no. bags); Number of strayed animals; Price per herd; Number of strayed animals; Price per head; Number of animals sold to butcheries; Size of herd; Expenditure on inputs; Availability of labour.
Variables Tracked
Key Impact Area Key Variables / Indicators
3. MobilityHypothesis: Increase mobility of HH members.
Travel expenditure; Household size / composition / structure; Changing HH structure; Number of patients at health care centres.
4. EnvironmentalHypothesis: Increased degradation of environment.
Accumulation of disposable litter; Number of animals with measles; Educational level; Gender.
5. Food ConsumptionHypothesis: Decline in household food consumption.
Types of food consumed; Expenditure and income patterns; Household income levels; Size of household; Dietary composition.
Variables Tracked
Key Impact Area Key Variables / Indicators
6. Production AssetsHypothesis: Erosion of household productive asset base.
Household resource allocation; Household sources of income;Household expenditure patterns.
7. Extension and Support ServicesHypothesis: Erosion of extension and research services.
Absenteeism due to illness; Farmer extension ratios;Number of deaths in the community;Health status of extensionists.
8. Demographic StructureHypothesis: Increased dependency ratios.
Number of children under 15 years; Number of adults above 65 years;Sex composition of HH members;Education levels of HH members;Employment status.
Example of variables collected: demographics
Variable description Variable name Whether Countries collected data
Country Country NAMIB BOTS ZIMB SWAZI LESOT S.AFRICA ZAMBIA
QUESTIONNAIRE NUMBERQuestionnaire Number yes yes yes yes yes yes yes
Date Date no no yes no no yes no
District or Region District yes yes yes yes yes yes yes
Age Of Household Head Age Of Head of HH yes yes yes yes yes yes yes
WARD/Enumeration area/village Local Area no yes yes yes no yes yes
Sex of Household Head Sex of Head of HH yes yes yes yes yes yes yes
Family name Family Name no no yes yes no yes no
Position of the respondent in the family Respondent Position no yes yes no yes yes yes
Who is/are the head(s) of this family? Family Head yes yes yes yes no yes no
How long has the family been in agriculture (Years)? Years Farming no no no yes yes yes no
Total household size TotalHouseholdSize yes yes yes yes yes no yes
Number of children/Dependents in the Household Dependents yes no yes yes yes yes yes
Dependency Ratio Dependency yes no yes yes yes yes yes
LIVESTOCK IS SOLD TO FINANCE MEDICATION OF THE SICK FarmingTimeLost no yes yes no no yes yes
IT TAKES FARMING TIME AS PEOPLE WILL BE LOOKING AFTER SICK PEOPLE
FinancialResourcesDiverted no no yes yes no yes yes
FARMING FINANCIAL RESOURCES ARE DIVERTED TO MEDICATION for THE SICK
FarmingImplementsSold no no yes no no yes no
FARMING IMPLEMENTS ARE SOLD TO FINANCE MEDICAL EXPENSES ChoresTimeLost no no yes no no yes no
TIME TO DO HOUSEHOLD CHORES IS SACRIFICED LOOKING AFTER THE SICK SchoolTimeLost no no yes no no yes no
IT TAKES CHILDREN'S TIME TO BE AT SCHOOL LOOKING AFTER THE SICK ParentingTimeLost no no yes no no yes no
IT TAKES AWAY PARENTS" TIME TO BE WITH THEIR CHILDREN
HouseholdPropertySold no no yes yes no yes yes
SICKNESS RESULTS IN THE SELLING OF HOUSEHOLD PROPERTY War no no yes no no yes no
Example of variables collected: impacts
Achievements to Date
Lit. Review&Method.
Field Data
CollectionData
AnalysisElectronic Database
Trang/ Dissem
W/shopsCountry
MoongraphPolicy
Brief
Policy brief with
Recomm.
NewsletterMagazine
Journal Articles
RegionalBook
NATIONAL LEVEL
Botswana X X X X X Draft X 10 Sept.
Namibia X X X X X Draft X 10 Sept.
Lesotho X X X X X Draft X 10 Sept.
Swaziland X X X X X Draft X 10 Sept.
South Africa X X X X X Draft X 10 Sept.
Zambia X X X X X Draft X 10 Sept.
Zimbabwe X X X X X Draft X 10 Sept.
REGIONAL LEVEL
X X X 10/03X 10/04X 05/05 X 10/05
XDraft 4 Oct.
Final15 Dec.
Emerging results1. HIV and AIDS has led to a decline in agricultural
productivity:• Mean household size was 6.1• About 5% of all households where headed by children under 18years (The
figures were 6.4% for Botswana, 3.9% for Lesotho, 1% for Namibia, 1% for South Africa, 2.5% for Swaziland, 6% for Zambia and 3.8% for Zimbabwe)
• 30 % of households had 3 or more dependents. Of these, Zambian, South African and Namibian households had the largest numbers.
• 65% of Households reported field sizes of under 2 ha. There was no correlation between field size and amount of fertilizer used.
• 18.2 % of Households reported that HIV and AIDS illnesses and funerals deprived them of farming time.
• 75% of households have a dependency ratio greater than 1. ie have more dependents than economically active members.
Contributions to Policy Development
Immediate• Enhanced Policy Dialogue national and regional
• Study identified key variables in agriculture and food security.– Production and Marketing– Availability and Access
• Study quantified impact based on field survey and secondary data.
• Information database for 7 countries.
• Regional Database with baseline information on impact
Contributions to Policy Development
Medium to Long term• Develop & harmonize policies for FANR sector: (baseline)-Impact-policy development-submit for
adoption-monitor implementation
• Develop HIV & AIDS vulnerability index for the FANR sector. This will quantify coping, acute and emergency levels at household and national levels.
• Help SADC develop social protection policies e.g. agricultural inputs pack, basic needs basket.
Challenges / Lessons Learnt
1. Agricultural chain is broad– Production– Processing– Marketing
2. Food Security is multi-variant– Availability– Accessibility– Utililisation
Challenges / Lessons Learnt
3. HIV & AIDS / Issue of Time Series– Sensitivity of subject
4. Data Collection– No documented records– Household mobility– Time series
5. Coordination of Multi-Country ResearchIn country -communication/networking
Exit Intentions
• FANRPAN nodes need to be capacitated so they continue to collect and analyse data for longitudinal surveys
Policy development takes time• Develop & harmonize policies for FANR sector: (baseline)-Impact-policy development-submit for
adoption-monitor implementation
• Formal channel for sharing information at national and regional level created/strengthened
CONCLUSIONS
• Study has demonstrated need for evidence based policy development
• Database is only as good as:– Quality of the data stored– Rigour of the analysis– Utilisation of information
THERE IS NEED TO UPDATE AND SHARE INFORMATION REGULARLY
THANK YOU• EU for financing the study• SADC for supporting and
coordination study implementation