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