FANRPAN HIV & AIDS
Policy Studies
Lindiwe Majele Sibanda
linds@ecoweb.co.zw
linds@mweb.co.za
FANRPAN Mission
• To coordinate, influence and
facilitate policy research, analysis and
dialogue at the national, regional and
global levels in order to develop the
food, agriculture and natural resources
sector.
• The Mission is achieved through
research, networking, capacity
building and information 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 socioeconomic development
Project
implemented as
planned with
maximum
stakeholder
cooperation
HIV & AIDS built
into the regional
and country
development
policies and
strategies
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 Productivity
Hypothesis: 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 Asset
Hypothesis: 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. Mobility
Hypothesis: Increase mobility of HH
members.
Travel expenditure; Household size /
composition / structure; Changing HH
structure; Number of patients at health
care centres.
4. Environmental
Hypothesis: Increased degradation of
environment.
Accumulation of disposable litter;
Number of animals with measles;
Educational level; Gender.
5. Food Consumption
Hypothesis: 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 Assets
Hypothesis: Erosion of household
productive asset base.
Household resource allocation;
Household sources of income;
Household expenditure patterns.
7. Extension and Support Services
Hypothesis: 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 Structure
Hypothesis: 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
Country
Country
QUESTIONNAIRE NUMBER
Questionnaire
Number
Date
Date
District or Region
Whether Countries collected data
NAMIB
BOTS
ZIMB
SWAZI
LESOT
S.AFRICA
ZAMBIA
yes
yes
yes
yes
yes
yes
yes
no
no
yes
no
no
yes
no
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
Example of variables collected:
impacts
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
FinancialResources
Diverted
no
no
yes
yes
no
yes
yes
FARMING FINANCIAL RESOURCES
ARE DIVERTED TO MEDICATION for
THE SICK
FarmingImplements
Sold
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
HouseholdProperty
Sold
no
no
yes
yes
no
yes
yes
SICKNESS RESULTS IN THE SELLING
OF HOUSEHOLD PROPERTY
War
no
no
yes
no
no
yes
no
Achievements to Date
Policy
Brief
Policy
brief
with
Recomm
.
Draft
X
10 Sept.
X
Draft
X
10 Sept.
X
X
Draft
X
10 Sept.
X
X
X
Draft
X
10 Sept.
X
X
X
X
Draft
X
10 Sept.
X
X
X
X
X
Draft
X
10 Sept.
Zimbabwe
X
X
X
X
X
Draft
X
10 Sept.
REGIONAL
LEVEL
X
X
X 10/03
X 10/04
X 05/05
X 10/05
Lit.
Review
&Method.
Field
Data
Collection
Data
Analysis
Electronic
Database
Trang/
Dissem
W/shops
Country
Moongraph
Botswana
X
X
X
X
X
Namibia
X
X
X
X
Lesotho
X
X
X
Swaziland
X
X
South Africa
X
Zambia
Newsletter
Magazine
Journal
Articles
Regional
Book
NATIONAL
LEVEL
X
Draft
4 Oct.
Final
15 Dec.
Emerging results
1. 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 Research
In 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