1. FANRPAN HIV & AIDS Database Lindiwe Majele Sibanda Linds@ecoweb.co.zw Linds@mweb.co.za

2. Background to the 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 impacts of HIV and AIDS. Analysis carried out at country and regional levels. Integrated framework within Epi Info allows for analysis and reporting.

3. Variables tracked Key impact areaHypothesisKey Variables /IndicatorsCountries data situation 1.Primary data 2.Secondary data 3.Data not available Agricultural productivityH/A has led to a decline in agric productivityYield, (area cultivated) Overall output, Agric inputs: type and quantity Number of productive HH members infected Number of HHs affected Education level Demographic variables Type and quality of equipment Gender- of infected/affected Changes in household structure Extension and support services Area cultivated MarketingReduces participation in the marketSales (no. animal, no. bags) Number of strayed animals Price per herd No. of animals sold to butcheries 1, 2 2 1, 2 2, 3 Livestock assetReduces number and quality of livestockSize of herd Price per head Expenditure on inputs Availability of labor 1, 2 2 1, 2

4. Variables tracked (ctd) MobilityIncreases mobility of HH membersTravel expenditure Household size/composition/structure Changing household structure Number of patients at health care centers 1, 2 1 2 EnvironmentalIncreased degradation of environmentAccumulation of disposable litter Number of animals with measles Educational level Gender 12111211 Food ConsumptionDecline in household food consumptionTypes of food consumed Expenditure and income patterns Household income levels Size of household Dietary composition 1111111111 Production AssetsErosion of Household productive asset baseHH resource allocation HH sources of Income HH expenditure patterns 111111 Extension & Support services Erosion of extension and research servicesAbsentism due to illness Farmer: extension ratios Number of deaths in the community Health status of extensionists 33333333 Demographic structureIncreased dependency ratiosNumber of children under 15 years Number of adults above 65 years Sex composition of household members Education levels of household members Employment status 1111111111

5. Example of variables collected: demographics Variable descriptionVariable nameWhether Countries collected data Country NAMIBI A BOTS WANA ZIMBA BWE SWAZI LAND LESOT HO SOUTH AFRICAZAMBIA QUESTIONNAIRE NUMBERQuestionnaireNumberyes Date no yesno yesno District or RegionDistrictyes Age Of Household HeadAgeOfHeadofHHyes WARD/Enumeration area/villageLocalAreanoyes noyes Sex of Household HeadSexofHeadofHHyes Family nameFamilyNameno yes noyesno Position of the respondent in the familyRespondentPositionnoyes noyes Who is/are the head(s) of this family?FamilyHeadyes noyesno How long has the family been in agriculture (Years)?YearsFarmingno yes no Total household sizeTotalHouseholdSizeyes noyes Number of children/Dependents in the HouseholdDependentsyesnoyes Dependancy RatioDependencyyesnoyes

6. LIVESTOCK IS SOLD TO FINANCE MEDICATION OF THE SICKFarmingTimeLostnoyes no yes IT TAKES FARMING TIME AS PEOPLE WILL BE LOOKING AFTER SICK PEOPLE FinancialResources Divertedno yes noyes FARMING FINANCIAL RESOURCES ARE DIVERTED TO MEDICATION for THE SICK FarmingImplements Soldno yesno yesno FARMING IMPLEMENTS ARE SOLD TO FINANCE MEDICAL EXPENSESChoresTimeLostno yesno yesno TIME TO DO HOUSEHOLD CHORES IS SACRIFICED LOOKING AFTER THE SICKSchoolTimeLostno yesno yesno IT TAKES CHILDREN'S TIME TO BE AT SCHOOL LOOKING AFTER THE SICKParentingTimeLostno yesno yesno IT TAKES AWAY PARENTS" TIME TO BE WITH THEIR CHILDREN HouseholdProperty Soldno yes noyes SICKNESS RESULTS IN THE SELLING OF HOUSEHOLD PROPERTYWarno yesno yesno Example of variables collected: impacts